Substances tested on cellular model
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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He is a member of the editorial boards of several international organizations and journals and has authored/co-authored numerous articles in the areas of decision science and business management.",institutionString:"University of Cassino and Southern Lazio Lazio",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"University of Cassino and Southern Lazio",institutionURL:null,country:{name:"Italy"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"345821",firstName:"Darko",lastName:"Hrvojic",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/345821/images/16410_n.",email:"darko@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"6291",title:"Digital Transformation in Smart Manufacturing",subtitle:null,isOpenForSubmission:!1,hash:"0a889d0839f7d4e2639d44c429a20906",slug:"digital-transformation-in-smart-manufacturing",bookSignature:"Antonella Petrillo, Raffaele Cioffi and Fabio De Felice",coverURL:"https://cdn.intechopen.com/books/images_new/6291.jpg",editedByType:"Edited by",editors:[{id:"181603",title:"Dr.",name:"Antonella",surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8264",title:"New Frontiers on Life Cycle Assessment",subtitle:"Theory and Application",isOpenForSubmission:!1,hash:"59f13958eb30b72de4f8d1bc63f6dd2d",slug:"new-frontiers-on-life-cycle-assessment-theory-and-application",bookSignature:"Antonella Petrillo and Fabio De Felice",coverURL:"https://cdn.intechopen.com/books/images_new/8264.jpg",editedByType:"Edited by",editors:[{id:"181603",title:"Dr.",name:"Antonella",surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10020",title:"Operations Management",subtitle:"Emerging Trend in the Digital Era",isOpenForSubmission:!1,hash:"526f0dbdc7e4d85b82ce8383ab894b4c",slug:"operations-management-emerging-trend-in-the-digital-era",bookSignature:"Antonella Petrillo, Fabio De Felice, Germano Lambert-Torres and Erik Bonaldi",coverURL:"https://cdn.intechopen.com/books/images_new/10020.jpg",editedByType:"Edited by",editors:[{id:"181603",title:"Dr.",name:"Antonella",surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"40756",title:"Use of Natural Products for Direct Anti-Atherosclerotic Therapy",doi:"10.5772/52967",slug:"use-of-natural-products-for-direct-anti-atherosclerotic-therapy",body:'\n\t\tAtherosclerosis and vascular disorders, which result from atherosclerosis, represent one of the major problems in the modern medicine and public health. Atherosclerosis is characterized by structural and functional changes of large arteries. The approaches for the treatment of atherosclerosis require at least the prevention of growth of atherosclerotic lesions and reduction in the lipid core mass, which would followed by plaque stabilization. Taken together, these approaches could theoretically result in the regression of arterial lesions.
\n\t\t\tAtherosclerosis develops in the arterial wall and remains asymptomatic until ischemia of distal organs is evident. Therapy of clinical manifestations of atherosclerosis is largely aimed at reducing symptoms or affecting hemodynamic response and often does not affect the cause or course of disease, namely the atherosclerotic lesion itself. Of course, anti-atherosclerotic effects of statins revealed in many prospective clinical trials may be considered; however, statins have never been recognized as the drugs indicated just for direct treatment or prevention of atherosclerosis. They are used predominately in the course of hypolipidemic therapy, and the effects of treatment are estimated by success in reaching the target level of low density lipoprotein (LDL) cholesterol, but not the regression of atherosclerotic lesion or intima-media thickness. The last should be considered as beneficial effect, which is mainly due to pleiotropic mechanisms of action. Atherosclerosis develops over many years, so anti-atherosclerotic therapy should be a long-term or even lifelong therapy. Tachyphylaxis, long-term toxicity and cost amongst other issues may present problems for the use of conventional medications in a long-term. Drugs based on natural products can be a good alternative.
\n\t\t\tIn epidemiological studies of hypercholesterolemia, a high level of plasma cholesterol and the plasma concentration of LDL are significantly associated with the development of premature atherosclerosis [1]. Cholesterol accumulation in the arterial wall is the main sign of atherosclerosis. It was suggested that LDL is the major source of cholesterol deposited in the vessel wall.
\n\t\t\tAccumulation of cholesterol and other lipids is the most prominent manifestation of atherosclerosis at the arterial cell level. In addition to lipid accumulation, elevated proliferative activity of vascular cells and enhanced synthesis of the extracellular matrix are characteristics of cellular atherogenesis. Collagen and glycoproteins are the main components of the extracellular matrix which forms a fibrous plaque.
\n\t\t\tIntracellular lipid accumulation can be induced by LDL; however native lipoprotein does not increase the cholesterol content of the cell [2]. On the other hand, incubation of cell culture with chemically modified LDLs results in a massive accumulation of cholesterol in the cells [2]. The in vitro studies revealed a great number of atherogenic modifications of LDL, i.e. modifications which lead to cellular lipidosis [2]. This findings suggest that modified, but not native LDLs are the source of lipids accumulated in arterial cells. Arterial intimal cells populating atherosclerotic lesion are overloaded with lipids, their cytoplasm is almost completely filled with lipid inclusions [3]. These cells are referred to as foam cells.
\n\t\tRecent studies of the cellular mechanisms of atherosclerosis carried out on cultured human aortic cells have revealed the outlined below regularities.
\n\t\t\tModified LDL circulates in the bloodstream. We have discovered modified (desialylated) LDL in blood plasma of patients with coronary atherosclerosis [4-7]. This LDL induces accumulation of cholesterol in arterial cells [4-7]. Naturally occurring modified LDL has lesser sialic acid, triglyceride and cholesterol contents, lesser particle size, greater density and negative charge, higher aggregative activity and some other specific features [8]. We have discovered an enzyme, trans-sialydase, responsible for desialylation of LDL particle in blood [9].
\n\t\t\tIn addition to desialylated LDL, more electronegative LDL and small dense LDL were detected in human blood [10,11]. We have performed a comparative study of in vivo modified LDLs. This study showed that more electronegative LDL isolated by ion-exchange chromatography is desialylated LDL [12]. Desialylated LDL isolated from patient blood [4-7] is more electronegative LDL. These facts suggest that both desialylated LDL and electronegative LDL are similar if not identical.
\n\t\t\tWe have found that a particle of desialylated LDL is smaller and denser than that of native LDL, i.e., this LDL is small dense lipoprotein. On the other hand, La Belle and Krauss showed that small dense LDL has a low content of sialic acid, i.e., is desialylated [13]. These findings point out to a similarity between the two types of modified LDL.
\n\t\t\tGlycosylation is another type of in vivo LDL modification. Glycosylated LDL was found in the blood of patients with diabetes mellitus [14]. This LDL is also atherogenic, i.e. induces intracellular lipid accumulation [15]. Oxidation is probably also one type of an atherogenic modification of LDL in vivo. There are indirect evidences of the presence of oxidized LDL in vivo [16].
\n\t\t\tAutoantibodies are produced in response to the appearance of modified LDL (either desialylated, glycosylated or oxidized) in the bloodstream [16-18]. Autoantibodies to desialylated LDL react with both modified and, though with a lesser affinity, native lipoproteins [17,19,20]. The interaction between anti-LDL autoantibodies and the lipoprotein results in the formation of LDL-containing immune complexes [12]. Desialylated LDL which enter the cells as a component of immune complexes possess a higher atherogenic potential compared with free lipoprotein, i.e. induce a more intense cholesterol accumulation in the cell [21,22]. The interaction with anti-LDL converts native non-atherogenic LDL into atherogenic, i.e. enables it to induce intracellular cholesterol accumulation which accompanied by enhanced cell proliferation and the extracellular matrix production [17,20]. We have found circulating immune complexes consisting of LDL and anti-LDL autoantibodies in the blood of most atherosclerotic patients [21,22]. A positive correlation between level of LDL-containing immune complexes and the severity of atherosclerosis has been demonstrated [23-25].
\n\t\t\tWe and others have demonstrated that LDL is able to form complexes with cellular debris, collagen, elastin, and proteoglycans of human aortic intima [26-28]. Addition of these complexes to cultured cells stimulated intracellular accumulation of lipids. Experiments with iodinated LDL showed an increased uptake and decreased intracellular degradation of lipoproteins in complexes.
\n\t\t\tIn 1989 we showed that in vivo and in vitro modified LDLs are spontaneously self-associated under cell culture conditions, while native LDLs do not forms self-associates [29]. A positive correlation between atherogenic activity of modified LDLs and the degree of LDL self-association has been established [30,31]. Lipoprotein associates isolated by gel filtration induced a dramatic increase in the lipid accumulation by cultured human aortic intimal cells. Removal of LDL associates from the incubation medium by filtration through filter with pore diameter 0.1 µm completely prevented intracellular lipid accumulation. Thus, self-association increases atherogenic potential of LDL.
\n\t\t\tThus, we can conclude that formation of large complexes (self-associates, immune complexes, and complexes with connective tissue matrix) by modified LDL leads to intracellular lipid accumulation through enhanced cellular uptake and slow intracellular degradation of lipoprotein particles.
\n\t\tTaken together, our data allow us to identify possible targets for anti-atherosclerotic therapy. The first target is atherogenic modification (desialylation) of LDL particle in blood. Prevention of LDL modification may be an approach to anti-atherosclerosis therapy. The second approach may be selective removal of modified LDLs from blood (target 2). The third one may be based on prevention of modified LDL accumulation in arterial cells (target 3). Also one more approach is removal of excess lipids from foam cells (target 4). Figure 1 schematically represents these four approaches. We have used all of these approaches and now we believe that the most suitable approach is the third one, namely, the prevention of modified LDL accumulation in arterial cells. Bellow we describe the application of this approach for the development of anti-atherosclerotic therapy.
\n\t\t\tAgents capable of preventing atherogenesis are anti-atherogenic drugs, agents promoting the regression of atherosclerotic manifestations are anti-atherosclerotic drugs. Prevention of intracellular lipid accumulation accompanied by the stimulation of arterial cell proliferation and massive extracellular matrix production may be regarded as anti-atherogenic (preventive). In terms of arterial cells, any drug effect which does not prevent directly the conversion of the normal cell into an atherosclerotic one (foam cell) should be regarded as an indirect anti-atherogenic action. Only that drug which exhibits its preventive activity at the arterial level is a direct anti-atherogenic drug. At the arterial cell level, a drug with a direct anti-atherosclerotic action should induce the regression of the major cellular manifestations of atherosclerosis, i.e. reduce the intracellular lipid content, suppress cell proliferation and inhibit the extracellular matrix production.
\n\t\t\tTargets of anti-atherosclerotic and anti-atherogenic drug actions
Solid circles, multiple modified LDL; open circles, native LDL
\n\t\t\t(see explanation in the text).
\n\t\t\tThus, the drugs that affect atherosclerosis can be divided into 3 groups:
\n\t\t\t- anti-atherosclerotic;
- direct anti-atherogenic;
- indirect anti-atherogenic.
The identification of anti-atherosclerotic or/and anti-atherogenic activities of a drug is associated with considerable difficulties. There are no simple and rapid techniques to estimate the anti-atherogenic/anti-atherosclerotic effect of a drug in an animal model or in clinical trials. That is why we employ a culture of human atherosclerotic vascular cells in the screening of potential drugs, investigation of their mechanisms of action and optimization of anti-atherosclerotic drug therapy.
\n\t\t\tWe use human aortic cells to examine the effects of various agents on atherosclerosis-related features of cultured cells. Cells are isolated from the subendothelial part of the human aortic intima, i.e. from the part of aorta which is localized between the endothelial lining and the media [32]. The intima of adult human aorta is a well-defined structure. The thickness of a normal intima varies from 50 to 120 µm [32]. Sometimes a thickened intima is called a diffuse intimal thickening [32]. This term underlines its essential difference from a very thin intima of animal and adolescent aorta. Unaffected intima of adult human aorta contains 10-12 lines of subendothelial cells [32].
\n\t\t\tUsing collagenase and elastase, cells are isolated from the subendothelial layer of the intima of both normal and atherosclerotic parts of the aorta [33-36]. This approach makes it possible to study a direct anti-atherosclerotic and anti-atherogenic action of a drug at the vascular cell level. An important advantage of this technique is that human material is used and thus, the results obtained are relevant to human atherosclerosis.
\n\t\t\tBy the well-established criteria, the cells cultured from the intima can be classified as the cells of smooth muscle origin. These cells are stained with antibodies to smooth muscle myosin [33-35]. For further identification of cultured cells we have used a monoclonal antibody HHF-35 which reacts specifically with muscle α-actin and can reveal smooth muscle cells [37]. According to our calculations, primary culture of subendothelial cells contains about 90% of smooth muscle cells interacting with HHF-35. In addition, cells cultured from subendothelial part of uninvolved (healthy) intima have the ultrastructural features characteristic of smooth muscle cells, namely: the basal membrane and filament bundles with dense bodies [33-36]. The culture on which our experiments are performed is represented by mixed population of typical and modified smooth muscle cells revealed in the human aorta earlier [32].
\n\t\t\tCells of the subendothelial intima isolated from atherosclerotic lesions retain in primary culture all major characteristics of atherosclerotic cells. Cells cultures from fatty streak and fatty infiltration zones have an enhanced proliferative activity [38]. These cells have a higher proliferative activity as compared with the cells cultured from unaffected intima [38,39].
\n\t\t\tMany cells cultured from atherosclerotic lesions are so called foam cell containing numerous inclusions filling the whole of the cytoplasm, these inclusions are lipid droplets [34]. The bulk of excess lipids in foam cells is represented by free cholesterol and cholesteryl esters [34]. It should be noted that the content and composition of lipids in cultured cells within the first 10-12 days in culture remain unchanged and correspond to the respective indices of freshly isolated cells [34-39].
\n\t\t\tCells cultured from the subendothelial intima are capable of synthesizing collagen, proteoglycans and other components of extracellular matrix [40,41].
\n\t\t\tThus, the cells isolated from an atherosclerotic lesion of human aorta retain in culture all the main properties characteristic of atherosclerotic cells. They exhibit an enhanced proliferative activity, contain excess cholesterol in the form of intracellular inclusions and synthesize the extracellular matrix. This allows one to regard a culture of atherosclerotic cells as a convenient model for the investigation of the effects of various agents on atherosclerotic manifestations [21]. Thus, the investigations in the cell culture model are carried out directly on exactly the same cells which require a therapeutic action in vivo.
\n\t\t\tUsing this model, we have examined the effects of different drugs and chemicals. By now many substances have been tested [21]. The effects of several substances are summarized in Table 1. Some of them elicited anti-atherosclerotic effects in culture, some proved to be ineffective in this respect, while others even stimulated the development of atherogenic processes.
\n\t\tThree classes of cardiovascular drugs: calcium antagonists, beta-blockers and nitrates have been tested on our cellular model. These drugs are widely used in clinic for therapy of various disorders resulting from atherosclerosis of different arteries. We attempted to find out how calcium antagonists, beta-blockers and nitrates affect atherosclerotic indices of arterial cells.
\n\t\t\t\n\t\t\tFirst, we examined the effects of calcium antagonists on major atherosclerotic indices. It has been found that calcium antagonist, verapamil, has a positive effect on all atherosclerotic cellular indices. Within 48 hrs, verapamil added to culture reduced total intracellular cholesterol level by 3-fold, sharply decreased the [3H]thymidine incorporation into cellular DNA, i.e. suppressed cell proliferative activity, and inhibited the collagen synthesis by cultured cells [38,39]. Thus, this drug has a direct anti-atherosclerotic effect at the arterial cell level.
\n\t\t\tSeveral calcium antagonists: nifedipine, darodipine, isradipine, nicardipine, nitrendipine, felodipine, tiapamil, gallopamil, diltiazem, papaverin, nicardipine, and others were also tested. Verapamil and nifedipine proved to be the most effective [49,55]. Within 24 hrs of incubation with cultured cells all calcium antagonists substantially inhibited [3H] thymidine incorporation and reduced intracellular cholesterol level [54,55]. Thus, calcium antagonists produce a direct anti-atherosclerotic effect on the vascular cells normalizing the major atherosclerotic cell parameters.
\n\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t|
Cyclic AMP elevators | \n\t\t\t\t\t\t[39,42 - 45] | \n\t\t\t\t\t
Prostacyclin | \n\t\t\t\t\t\t[39,46 - 50] | \n\t\t\t\t\t
Prostaglandin E2\n\t\t\t\t\t\t | \n\t\t\t\t\t\t[39,46, 51] | \n\t\t\t\t\t
Artificial HDL | \n\t\t\t\t\t\t[52] | \n\t\t\t\t\t
Antioxidants | \n\t\t\t\t\t\t[39] | \n\t\t\t\t\t
Calcium antagonists | \n\t\t\t\t\t\t[39,49, 50, 53-56] | \n\t\t\t\t\t
Trapidil and trapidil derivatives | \n\t\t\t\t\t\t[57, 58] | \n\t\t\t\t\t
Lipoxygenase inhibitors | \n\t\t\t\t\t\t[51] | \n\t\t\t\t\t
Lipostabil | \n\t\t\t\t\t\t[39] | \n\t\t\t\t\t
Mushroom extracts | \n\t\t\t\t\t\t[59] | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t|
Beta-blockers | \n\t\t\t\t\t\t[55,60] | \n\t\t\t\t\t
Thromboxane A2\n\t\t\t\t\t\t | \n\t\t\t\t\t\t[49,50] | \n\t\t\t\t\t
Phenothiazines | \n\t\t\t\t\t\t[39] | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t|
Nitrates | \n\t\t\t\t\t\t[55] | \n\t\t\t\t\t
Cholestyramine | \n\t\t\t\t\t\t[39] | \n\t\t\t\t\t
Substances tested on cellular model
In addition to anti-atherosclerotic effects imitating the regression of atherosclerosis, anti-atherogenic effects in culture imitating prevention of atherosclerosis were studied. Table 2 demonstrates the major differences between these two approaches. In the case of anti-atherosclerotic effect the regression of atherosclerosis is imitated, whereas in the case of anti-atherogenic effect, the prevention of atherosclerosis is imitated. In the first case the cells obtained from an atherosclerotic plaque are used, while in the second type of experiments cells derived from unaffected intima are employed. When anti-atherosclerotic effect is examined, cells are cultured in the presence of a standard fetal calf serum, while in the experiments on anti-atherogenic effect - atherogenic serum obtained from coronary heart disease patients is added to culture. This serum induces the accumulation of cholesterol and stimulates other atherogenic manifestations in cultured cells [61-64]. In the case of anti-atherosclerotic effect the efficacy of a drug is judged upon by its ability to decrease an elevated content of cholesterol in cultured atherosclerotic cells but in the case of anti-atherogenic effect, the efficacy of a drug is judged upon by the ability to prevent the deposition of intracellular cholesterol in normal cells.
\n\t\t\tFour-hour preincubation of cultured cells with verapamil led to complete prevention of the serum atherogenic effect [65]. Thus, verapamil possesses not only an atherosclerotic effect in culture causing the regression of atherosclerotic manifestations at the cellular level but also elicits an anti-atherogenic, i.e. preventive effect, eliminating atherogenic potential of the serum.
\n\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t
Regression | \n\t\t\t\t\t\tPrevention | \n\t\t\t\t\t
Atherosclerotic plaque | \n\t\t\t\t\t\tUninvolved intima | \n\t\t\t\t\t
Standard (nonatherogenic) serum | \n\t\t\t\t\t\tAtherogenic patients\' serum | \n\t\t\t\t\t
Cholesterol fall | \n\t\t\t\t\t\tPrevention of cholesterol accumulation | \n\t\t\t\t\t
Anti-atherosclerotic and anti-atherogenic drug effects in culture
The effect of several calcium antagonists on primary cholesterol accumulation in cultured cells induced by the patients\' serum was tested. Verapamil and nifedipine completely inhibited the accumulation of intracellular cholesterol induced by the serum while other calcium antagonists: diltiazem, nicardipine, isradipine, darodipine rather substantially reduced cholesterol accumulation [65]. As it is known, the examined calcium antagonists manifested anti-atherogenic action in vivo inhibiting the development of experimental atherosclerosis in animals [66,67]. Thus, our in vitro data obtained on cellular model correspond to the in vivo observations. One can conclude that calcium antagonists elicit not only anti-atherosclerotic but also anti-atherogenic, i.e. preventive effect at the arterial cell level.
\n\t\t\tNitrates and beta-blockers have been tested to reveal their action on atherosclerotic cellular indices. Nitrates had no effect on proliferative activity of atherosclerotic cells and practically did not affect the cholesterol level [55]. On the other hand, all the examined beta-blockers, propranolol, alprenolol, metoprolol, pindolol, and timolol, more or less increased atherosclerotic manifestations, i.e. all of these drugs exhibited atherogenic activity in culture [55,60]. If beta-blockers manifest a similar action in vivo, one may assume that these drugs are atherogenic and realize the atherogenic action at the arterial cell level. Apparently, nitrates are neutral, indifferent in this respect.
\n\t\t\tThe influence of cardiovascular drugs on atherosclerosis-related effects of each other was studied. The study was focused on metoprolol, nifedipine and nitroglycerin, the drugs widely used in clinic [55]. Metoprolol caused an elevation of intracellular cholesterol, nifedipine reduced the cholesterol level while nitroglycerin was without effect on this index. The use of nifedipine on the background of metoprolol did not modify the anti-atherosclerotic action of the calcium antagonist. In this combination atherogenic action of metoprolol was not revealed. The application of metoprolol in combination with nitroglycerin led to the elimination of an atherogenic effect of the beta-blocker. Nifedipine used together with metoprolol and nitroglycerin was just as effective as in the absence of these drugs. Thus, nifedipine produces its anti-atherosclerotic effects both by itself and in combination with widely used nitrates and beta-blockers. These data suggest one important conclusion. Atherogenic action of beta-blockers can be inhibited if a beta-blocker is used in combination with a calcium antagonist or nitrate. This finding allows to hoping that in the nearest future it will be possible to develop beta-blockers devoid of atherogenic side effects.
\n\t\t\tThus, three classes of cardiovascular drugs reveal different influence on cellular manifestation of atherosclerosis. Calcium antagonists exhibit anti-atherosclerotic action. On the contrary, beta-blockers are atherogenic. Nitrates are neutral, indifferent in this respect. Our data obtained on cellular model were supported by results of clinical study. Loaldi et al. have reported that long-term per oral administration of propranolol aggravates coronary atherosclerosis in patients with angina of effort as compared with the calcium antagonists, nifedipiene, and isorobide dinitrate [68]. Nifedipine produced the best effect on coronary atherosclerosis by suppressing the development of existing and preventing the appearance of new atherosclerotic lesions. Isosorbide dinitrate was less effective in this respect, while with propranolol therapy the situation was the worst. These clinical observations encourage us to develop anti-atherosclerotic therapy using our cell culture model.
\n\t\tAll the above conclusions and hypotheses are based on the data obtained in in vitro experiments. Obviously, the question arises, whether anti-atherosclerotic effects of calcium antagonists and atherogenic effects of beta-blockers can be manifested in vivo and what is the optimal anti-atherosclerotic therapy based on calcium antagonists and other drugs.
\n\t\t\tTo optimize anti-atherosclerotic and anti-atherogenic drug therapy, ex vivo model was developed. In case of ex vivo model not drug but blood serum taken from patients after oral drug administration is added to cultured cells.
\n\t\t\tCalcium antagonists, verapamil and nifedipine, and beta-blockers, propranolol and pindolol, were examined using ex vivo model. Within 2-4 hrs after nifedipine or verapamil administration, the patient\'s serum had anti-atherosclerotic properties, i.e. it was able to cause a fall in the intracellular cholesterol and inhibited atherosclerotic cell proliferation [55,56]. On the contrary, the serum of patients who received propranolol or pindolol was pro-atherogenic. Its pro-atherogenic properties manifested themselves at the arterial cell level in the rise of intracellular cholesterol and stimulation of cell proliferation [55,56]. This finding allows to assuming that not only in vitro, but in vivo as well, calcium antagonists and beta-blockers are anti-atherosclerotic and atherogenic drugs, respectively.
\n\t\t\tThe effect of nifedipine on serum properties during a prolonged course was assessed. A patient was on nifedipine for 7 days. He received 20 mg doses three times a day with an 8-hr interval. Twenty-eight days after regular nifedipine therapy the initial atherogenicity of the patient\'s serum was substantially lower than at the beginning. Directly after a dose of nifedipine the atherogenicity was practically completely eliminated [65]. On the contrary, as a result of a prolonged therapy with a beta-blocker, propranolol, patient\'s serum acquired stable atherogenic properties. At the beginning of the course the serum of this patient was nonatherogenic, however, 28 days of regular propranolol therapy led to the emergence of atherogenicity revealed even before the drug administration [65]. Thus, a single dose of beta-blockers brings about temporary atherogenicity of the serum. Prolonged therapy with beta-blockers leads to the emergence of stable atherogenic properties of patients\' blood serum.
\n\t\tCellular model can be used not only to test drugs but foodstuffs as well. We have investigated an anti-atherosclerotic, i.e. therapeutic, causing regression of atherosclerosis, and anti-atherogenic, i.e. preventive activity of certain mushroom species and sea products.
\n\t\t\tPreviously we have shown that alcohol and water extracts from 20 Korean mushroom species cause anti-atherosclerotic and anti-atherogenic activity in cell culture [59]. Thirteen of the 20 extracts tested were anti-atherosclerotic in culture, i.e. they caused a decrease in the cellular cholesterol and/or inhibited proliferation of atherosclerotic cells. Ten of 20 tested extracts displayed anti-atherogenic activity in addition to anti-atherosclerotic effects. Four mushroom species were chosen for the study of anti-atherosclerotic effects ex vivo. Cultivation of atherosclerotic cells during 24 hrs in the presence of serum from healthy subjects who had had mushroom meals resulted in a 21-30% decrease in the cellular cholesterol level, i.e. caused anti-atherosclerotic effect [59]. The atherogenic serum obtained from atherosclerotic patients after dietary mushroom consumption partly (30-41%) lost its ability to increase the cellular cholesterol content [59]. Thus, tested mushrooms exhibited anti-atherosclerotic and anti-atherogenic effects on ex vivo model.
\n\t\t\tAmong sea products mollusk and krill meat were tested [36]. Specifically, the patients were given canned meat of a mollusk belonging to genus
Patients of another group had an initially atherogenic serum causing more then 2-fold increase in cholesterol content of cells derived from normal intima. These patients received a single dietary load of Antarctic krill meat. Two hours later the atherogenicity of their blood serum decreased and four hours later it was practically absent [36]. Thus, krill meat exhibits a preventive anti-atherogenic action on arterial cells.
\n\t\t\tThe results obtained suggest that the krill meat can be employed in diets aimed at the prevention of atherosclerosis. To develop a dietary therapy based on the krill meat, the effective dose and proper regimen should be established. As the first step to develop a dietary therapy, the below outlined study was undertaken to determine the effective dose.
\n\t\t\tThe patients\' blood sera were analyzed for atherogenicity. Patients whose blood serum had an atherogenic potential were included in the study. The blood was collected from each patient before, 2 and 4 hrs after a dose of krill meat. This protocol was repeated on the next day with another dose of krill meat. Blood serum samples were added to a culture of subendothelial cells isolated from uninvolved human aortic intima, and intracellular cholesterol accumulation was assessed in each case. Anti-atherogenic activity of krill meat was evaluated by the ability to reduce serum atherogenicity which manifested in cholesterol accumulation in cultured cells (Figure 2). The dose-effect dependence was revealed by comparing the efficacy of two doses. The efficacy of each dose was evaluated by the analysis of at least 6 sera obtained from different patients. In can be seen from that the krill meat elicits an anti-atherogenic effect at a dose of 10-20 g, half maximum effect was reached at a dose of 30 g and the maximum effect - at a dose of 50 g.
\n\t\t\tWe believe that this approach will be useful in the development and optimization of anti-atherosclerotic and anti-atherogenic diet therapies.
\n\t\t\tAntiatherogenic effect of krill meat on blood serum of atherosclerotic patients
Blood serum atherogenicity was determined using primary culture of cells derived from uninvolved intima of the human aorta.
\n\t\tAnti-atherogenic effects of dietary products promote the development of anti-atherosclerotic therapy on the basis of natural products. Atherosclerosis develops over many years, so the anti-atherosclerotic therapy should be long-term or even lifelong therapy. For such a long-term therapy conventional medicine might not work. Drugs based on natural products can be a good alternative.
\n\t\t\tWe have tested numerous natural products’ extracts to reveal their effects on blood atherogenicity, i.e., a capacity to prevent intracellular cholesterol accumulation caused by atherogenic blood sera from patients. Table 3 presents effective natural products only. As a fact, among tested agents were revealed not only anti-atherogenic but also pro-atherogenic and neutral. Among antiatherogenic natural products the most effective was garlic.
\n\t\t\t\n\t\t\t\t\t\t | Atherogenicity decrease, % | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t51 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t21 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t31 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t70 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t55 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t11 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t | \n\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t52 | \n\t\t\t\t\t
Anti-atherogenic effects of natural products
We extended investigation of the in vitro effect of garlic extract on lipids of cultured human aortic cells. We have earlier shown that lipid accumulation in human aortic cells is accompanied by stimulation of other cellular manifestation of atherosclerosis, namely: proliferation and extracellular matrix synthesis [41,63]. Thus, investigation of garlic action on cellular lipid parameters is closely related to the study of the mechanism of garlic anti-atherosclerosis effect.
\n\t\t\tA direct influence of garlic on atherosclerosis is discussed [70-73]. The anti-atherosclerotic effect of garlic has been attributed to its hypolipidemic activity. Experimental and clinical data have clearly demonstrated that garlic reduces blood cholesterol and LDL levels [74,75]. The cholesterol lowering effect of garlic results from inhibition of hepatic hydroxymethylglutaryl coenzyme A (HMG-CoA) [76]. In contrast to these studies, we examined not the hyperlipidemic but the direct anti-atherosclerotic-related and anti-atherogenic-related effects of garlic, i.e., the ability of garlic to act directly on atherosclerotic process in the vessel wall. To investigate anti-atherosclerotic-related (therapeutic) effect we used smooth muscle cells cultured from atherosclerotic plaques of human aorta. To study anti-atherogenic-related (preventive) effect we imitated atherogenesis in primary cultures of smooth muscle cells derived from grossly uninvolved human aortic intima by adding atherogenic blood serum of patients with angiographically assessed coronary atherosclerosis. Garlic decreased triglyceride, cholesteryl ester and free cholesterol contents of cells cultured from atherosclerotic plaque and prevented atherogenic serum-induced accumulation of these lipids in cells cultured from grossly normal aorta, i.e., elicited direct anti-atherosclerotic-related (therapeutic) and anti-atherogenic-related (preventive) effects. Garlic inhibits ACAT and stimulates CEH, thus displaying a direct influence on synthesis and degradation of cholesteryl esters in the cell. This finding may explain direct anti-atherosclerotic effects of garlic.
\n\t\t\tFurther investigations of garlic anti-atherosclerotic effects included ex vivo study and animal model study. Both types of studies confirmed the in vitro effects of garlic. Finally, we have developed a drug on the basis of garlic powder and carried out atherosclerosis regression clinical study of this drug.
\n\t\tThe AMAR study (Atherosclerosis Monitoring and Atherogenicity Reduction) was designed to estimate the effect of two-year treatment with time-released garlic-based drug Allicor on the progression of carotid atherosclerosis in asymptomatic men in double-blinded placebo-controlled randomized clinical trial. The primary outcome was the rate of atherosclerosis progression, measured by high-resolution B-mode ultrasonography as the increase in carotid intima-media thickness (IMT) of the far wall of common carotid arteries.
\n\t\t\tAtherosclerosis affects most vascular beads, and noninvasive imaging of superficial arteries by ultrasound has been recognized as a surrogate measure of overall atherosclerotic burden in numerous studies. Extracoronary atherosclerotic lesions can be quickly and safely evaluated in the carotids, femoral arteries, and the abdominal aorta. The grade of atherosclerosis in extracoronary sites correlates with a greater number of standard risk factors and, more importantly, with greater cardiac risk [77]. Of the peripheral arterial surrogates, carotid atherosclerosis has been most closely correlated with coronary artery disease [78-82]. Peripheral arterial ultrasonography is regarded to be a sensitive tool for the detection of early atherosclerosis and may be useful in assessing response to therapy. Thickening of the intima-media of the arterial wall is the earliest detectable anatomic change in the development and progression of atherosclerosis. High-resolution B-mode ultrasonography is widely used for noninvasive quantification of carotid IMT as a measure of subclinical atherosclerosis [83]. Carotid IMT is believed to be a marker of generalized atherosclerosis and is predictive of clinical cardiovascular events [79,81,84-88]. Thus, ultrasound imaging of intima-media thickening in carotid arteries served as a means of monitoring atherosclerosis during Allicor long-term treatment. Indeed, Allicor significantly reduced carotid arterial intima-media thickness compared to baseline and the placebo group. In Allicor recipients, a significant increase in the IMT in one or both carotid arteries was observed in 30 (32.2%) patients, and was significantly reduced in 44 (47.3%) patients. In 8 patients (8.6%) there were no significant IMT changes in either the carotid artery, and in the remaining 11 patients (11.8%) divergent changes were observed, i.e. IMT increased in one carotid artery and decreased in the other. IMT lesion progression was observed in 50 (48.5%) placebo cases, and decreased significantly in one or both arteries in 31 (30.1%) patients. Stable situation was observed in 11 (10.7%), and divergent changes occurred in the remaining 7 (6.8%) patients. The difference in the IMT changes between Allicor and placebo recipients was statistically significant (Pearson’s chi-square 9.788, P=0.020). Thus, while spontaneous atherosclerosis progression prevailed in the placebo group, Allicor beneficially impacted early carotid atherosclerosis - significantly increasing lesion regressions and reducing the net number of progressive lesions (Figure 3). The trend to IMT reduction in Allicor recipients was observed already after first 3 months of the study, and became statistically significant different from the baseline measures as well as from placebo group after the first 12 months of treatment. At the end of the two-year study the difference between placebo and Allicor recipients increased and remained statistically significant. The overall lesion progression was clearly different in the treated and untreated groups. IMT in the common carotid artery rose 0.015±0.008 mm annually and above a mean baseline IMT of 0.931±0.009 mm in the placebo group, and fell in Allicor-treated patients at a rate of -0.022±0.007 mm per year (P=0.002). Though the benefit of Allicor was more pronounced in year 1 (-0.028±0.008 mm) it remained significant and as a statistically identical significant difference in year 2 (-0.016±0.007).
\n\t\t\tThe dynamics of IMT changes
Solid circles, Allicor-treated patients; open circles, placebo patients.
*, significant IMT change as compared to baseline, P<0.05;
#, significant difference from placebo group, P<0.05.
The beneficial effects of Allicor were also revealed in analysis of subgroups of patients who had significant increase or reduction in IMT. IMT progression was almost 2.5 fold higher in the 50 patients in the placebo group with progress (0.070±0.016 mm) than in Allicor-treated patients with atherosclerosis progression (n=30, 0.029±0.011 mm increase, P=0.038). Similarly, spontaneous atherosclerosis regression in placebo recipients (n=31) was half as prominent (-0.041±0.014 mm) than in Allicor-treated patients (n=44, -0.082±0.015 mm, P=0.049).
\n\t\t\tThe results obtained in our study are generally in good coincidence with the data from recent double-blinded placebo-controlled randomized study by Koscielny et al. [89]. It has been demonstrated that 4-year treatment with garlic-based drug Kwai inhibited the increase in the volume of atherosclerotic plaques in carotid and femoral arteries by 5-18%. The age-dependent representation of the plaque volume has shown an increase between 50 and 80 years that was diminished under garlic treatment by 6-13% related to 4 years. So, with garlic application the plaque volume in the whole collective remained practically constant within the age-span of 50-80 years [89].
\n\t\t\tOverall, the regression of subclinical atherosclerosis was much more frequently observed in asymptomatic men who randomly received Allicor than in those who received placebo. A rather high proportion of patients in placebo group who demonstrated spontaneous regression, especially at early stages of atherosclerosis, reflects an interesting but poorly understood aspect of vascular biology that requires further study. The decrease in IMT achieved during the AMAR study is quite comparable with the results of most successful trials with other compounds (Table 4). Although, these studies employed potent lipid-lowering agents either calcium antagonists whose beneficial effects of treatment were attributed to reduction in LDL cholesterol, the major risk factor for atherosclerosis development, or arterial wall stress.
\n\t\t\t\n\t\t\t\t\t | ||||
\n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t |
PLAC II | \n\t\t\t\t\t\tPravastatin | \n\t\t\t\t\t\t0.068 | \n\t\t\t\t\t\t0.059 | \n\t\t\t\t\t\t[91] | \n\t\t\t\t\t
KAPS | \n\t\t\t\t\t\tPravastatin | \n\t\t\t\t\t\t0.029 | \n\t\t\t\t\t\t0.010 | \n\t\t\t\t\t\t[90] | \n\t\t\t\t\t
ASAP | \n\t\t\t\t\t\tSimvastatin | \n\t\t\t\t\t\t- | \n\t\t\t\t\t\t-0.009 | \n\t\t\t\t\t\t[92] | \n\t\t\t\t\t
PREVENT | \n\t\t\t\t\t\tAmlodipine | \n\t\t\t\t\t\t0.011 | \n\t\t\t\t\t\t-0.015 | \n\t\t\t\t\t\t[93] | \n\t\t\t\t\t
ASAP | \n\t\t\t\t\t\tAtorvastatin | \n\t\t\t\t\t\t- | \n\t\t\t\t\t\t-0.020 | \n\t\t\t\t\t\t[92] | \n\t\t\t\t\t
CLAS | \n\t\t\t\t\t\tCholestipol, niacin | \n\t\t\t\t\t\t0.010 | \n\t\t\t\t\t\t-0.020 | \n\t\t\t\t\t\t[94, 95] | \n\t\t\t\t\t
MARS | \n\t\t\t\t\t\tLovastatin | \n\t\t\t\t\t\t0.015 | \n\t\t\t\t\t\t-0.028 | \n\t\t\t\t\t\t[94, 96] | \n\t\t\t\t\t
VHAS | \n\t\t\t\t\t\tVerapamil | \n\t\t\t\t\t\t- | \n\t\t\t\t\t\t-0.028 | \n\t\t\t\t\t\t[97] | \n\t\t\t\t\t
AMAR | \n\t\t\t\t\t\tAllicor | \n\t\t\t\t\t\t0.015 | \n\t\t\t\t\t\t-0.022 | \n\t\t\t\t\t\tThis study | \n\t\t\t\t\t
The comparative data from clinical trials on carotid atherosclerosis regression
The main scientific goal of the given double-blinded, placebo-controlled randomized study was to test the hypothesis that long-term lowering of serum atherogenicity may prevent the initial stage of atherogenesis, namely, the excessive deposition of cholesterol in the cells of the arterial wall, thus inhibiting further formation of atherosclerosis lesion [41,62].
\n\t\t\tAt the baseline, the sera from 17 patients in placebo group (16.5%) did not induce significant cholesterol accumulation in cultured cells, while the sera from other 86 patients were atherogenic, i.e. induced a statistically significant (1.2- to 3.9-fold) increase in intracellular cholesterol content (mean result, 166.3±5.5, % of control value). In Allicor-treated patients, 23 patients (24.7%) had non-atherogenic sera, and in other 70 patients the sera increased intracellular cholesterol by 1.2- to 3.5-fold (mean result, 172.1±5.8, % of control value).
\n\t\t\tAmong patients with non-atherogenic sera at the baseline, in placebo recipients blood serum atherogenicity arrived in 11 cases during the study; in Allicor-treated patients at the end of the study serum atherogenicity was revealed in 9 cases, and in other 14 patients the sera remained non-atherogenic. The difference between Allicor and placebo recipients was statistically significant (Pearson’s chi-square 11.023, P<0.001). Thus, Allicor treatment prevented the upraise of blood serum atherogenicity.
\n\t\t\tAmong patients with initially atherogenic sera, in placebo group blood serum atherogenicity spontaneously decreased in 26 patients, did not change significantly in 28 patients, and in 32 cases there was further increase in blood serum atherogenic potential. On the opposite, in Allicor group serum atherogenicity was decreased in 39 patients by the end of the study, remained unchanged in 18 patients, and further increase in serum ability to induce intracellular cholesterol accumulation was observed only in 13 cases. Again, the difference between Allicor and placebo recipients was statistically significant (Pearson’s chi-square 11.274, P=0.004). Thus, Allicor also induced a fall in blood serum atherogenicity, if it existed at the beginning of treatment.
\n\t\t\tThe dynamics of serum atherogenicity changes
Solid circles, Allicor-treated patients; open circles, placebo patients.
*, significant IMT change as compared to baseline, P<0.05;
#, significant difference from placebo group, P<0.05.
The overall dynamic of changes in serum atherogenicity is presented in Figure 4. At the baseline, serum taken from patients was able to induce 1.56-fold increase in intracellular cholesterol content in cell culture test. In the placebo group, the mean level of serum atherogenic potential did not change significantly during two years of the study. On the opposite, in Allicor-treated patients the mean value for the ability of serum to induce intracellular lipid accumulation was significantly lowered (P=0.016) approximately by 30% of the initial level (95% CI: 16.9, 41.0) already after first 3 months of study, and this effect was maintained during the study. General linear model analysis has demonstrated the statistically significant difference in the dynamic of changes in serum atherogenicity between Allicor-treated and placebo groups (P=0.008).
\n\t\t\tThe presence or absence of serum atherogenicity at the baseline, as well as the extent of serum-induced intracellular cholesterol accumulation at the baseline, did not correlate with the following changes in IMT. However, the statistically significant correlation has been revealed between the changes in blood serum atherogenicity during the study and the changes in intima-media thickness of common carotid arteries (r=0.144, P=0.045 for the total study sample). In patients with initially non-atherogenic sera, the correlation between changes in atherogenicity and IMT was stronger (r=0.342, P=0.031). This correlation is explained mainly by the arrival of serum atherogenicity during follow-up in a subgroup of placebo recipients with initially non-atherogenic sera; in them the correlation between increase of atherogenicity and IMT dynamics was the highest (r=0.517, P=0.034).. In patients with initially atherogenic sera, the correlation between changes in atherogenicity and IMT in total group did not reach statistical significance (r=0.147, P=0.067), but in Allicor-treated patients in most of whom the decrease in serum atherogenicity was observed, the above parameters correlated well (r=0.254, P=0.034).
\n\t\t\tThere is a substantial experimental background to explain the possible mechanisms underlying a direct anti-atherosclerotic action of Allicor. The components of garlic can regulate two main intracellular enzymes responsible for cholesterol intracellular metabolism. Garlic extract stimulates cholesteryl ester hydrolase and inhibits acetyl coenzyme A : cholesterol acyl transferase, thus diminishing intracellular content of cholesteryl esters [98]. Additionally, garlic extract inhibits cellular proliferative activity and the synthesis of connective tissue matrix components [98,99]. Allicor also possesses antioxidant activity and lowers LDL susceptibility to oxidation [99]. Allicor prevents serum-induced cholesterol accumulation in cells cultured in the presence of patient’s serum taken after single dose of Allicor administration; in other words, it reduces serum atherogenic potential [99]. In animal studies, garlic-based preparations inhibit the formation of neointimal thickening in cholesterol-fed rabbits [100]. So, it could be easily proposed that long-term Allicor treatment produced a direct antiatherosclerotic effect due to the prevention of lipid deposition and depletion of cholesterol pool already accumulated in arterial wall.
\n\t\t\tGarlic contains a variety of organosulfur compounds, amino acids, vitamins and minerals [101]. Some of the sulfur-containing compounds such as allicin, ajoene, S-allylcysteine, S-methylcysteine, diallyl disulfide and sulfoxides may be responsible for antiatherosclerotic activity of garlic [98,100]. Many garlic-based products are present on the market now. As compared to other garlic preparations, dehydrated garlic powder is thought to retain the same ingredients as raw garlic, both water-soluble and organic-soluble, although the proportions and amounts of various constituents may differ significantly [102,103]. Allicor contains just garlic powder; on the other hand, it possesses a prolonged mode of action, as its antiatherogenic effect lasts for 12-16 hours after single dose administration [99]. So, Allicor differs greatly from other garlic-based preparations and may have considerable benefits in medicinal use.
\n\t\t\tOn the whole, the results of our study demonstrate that long-term treatment with time-released garlic-based drug Allicor provides a direct anti-atherosclerotic effect on carotid atherosclerosis. Being the remedy of natural origin, Allicor is safe with the respect to adverse effects and allows even perpetual administration, which may be quite necessary for prevention and treatment of subclinical atherosclerosis. These results encouraged clinical trials of two other drugs based on natural products, including: Inflaminat, possessing anti-cytokine activity and the phytoestrogen-rich drug Karinat, designed for postmenopausal women.
\n\t\t\tAtherosclerosis is regarded as a pathological process with elements of local aseptic inflammation, while inflammatory cytokines play a role at every stage of atherosclerosis development [104-107]. In this regard, drugs with systemic anti-inflammatory action may be effective for the prevention of atherosclerosis. In our study, we investigated the atherosclerosis regression effect of natural drug Inflaminat based on calendula, elder and violet. These plants are widely used in herbal medicine as anti-inflammatory agents. In a pilot study of Inflaminat using a protocol similar to the AMAR study Inflaminat demonstrated atherosclerosis regression effects and statistically significant difference from the baseline as well as from placebo group (Table 5). Thus, Inflaminat possesses atherosclerosis regression effect in asymptomatic men.
\n\t\t\t\n\t\t\t\t\t\t | |||
Number of participants \n\t\t\t\t\t\t | \n\t\t\t\t\t\t81 | \n\t\t\t\t\t\t77 | \n\t\t\t\t\t\t- | \n\t\t\t\t\t
IMT, μm \n\t\t\t\t\t\t\t \n\t\t\t\t\t\t | \n\t\t\t\t\t\t-62±48 * (-91; -32) р=0,002 | \n\t\t\t\t\t\t42±75 (-9; 93) р=0,109 | \n\t\t\t\t\t\t0.002 | \n\t\t\t\t\t
Carotid IMT changes in 1-year Inflaminat pilot study
* significant differences, p<0.05, Wilcoxon\'s signed ranked test;
**statistical significance of differences was estimated by Mann-Whitney U-test.
Atherosclerosis prevention in postmenopausal women is a striking problem, since modern medicine does not provide any effective approach. Hormone replacement therapy was rejected as a tool for atherosclerosis prevention in women due to the negative results of recent studies – WHI, PEPI and HERS [108-113]. So, the development of novel approaches is highly demanded. Phytoestrogens are often regarded as a possible alternative to hormone replacement therapy, but practically nothing is known on their effects on atherosclerosis.
\n\t\t\tWe screened many natural phytoestrogen-rich components for their antiatherogenic activity using an ex vivo test system [39,61,114-117]. The most promising of these compounds were: garlic powder, extract of grape seeds, green tea leafs and hop cones - all produced a significant antiatherogenic effect. On the basis of their combination, the novel isoflavonoid-rich dietary supplement Karinat was developed. It produces the most efficient antiatherogenic effect in cell culture models and is characterized by improved phytoestrogen profile, providing additional amounts of biologically active polyphenols including resveratrol, genisteine and daidzeine that are claimed to produce some effects on atherosclerosis development. Karinat also contains additional amounts of β-carotene, α-tocopherol and ascorbic acid to provide the necessary daily intake of antioxidants
\n\t\t\tA randomized double-blinded placebo-controlled pilot clinical study on atherosclerotic effect of Karinat was performed in healthy peri- and postmenopausal women to understand the risks and benefits of phytoestrogen therapy in relation to atherosclerosis progression. The primary endpoint was the annual rate of changes in common carotid artery intima-media thickening, and the secondary endpoint was the dynamics of climacteric syndrome, that is monitored only in perimenopausal women. Table 6 demonstrates the effect of Karinat treatment on the dynamics of carotid atherosclerosis in postmenopausal women. In the placebo group an increase in the average IMT of more than 100 μm per year was observed. Thus, the rate of the natural history of atherosclerosis in postmenopausal women is extremely high: the average increase in IMT is 13% per year, and growth of atherosclerotic plaques of 40% per year.
\n\t\t\t\n\t\t\t\t\t\t | ||||
Number of participants | \n\t\t\t\t\t\t80 | \n\t\t\t\t\t\t- | \n\t\t\t\t\t\t77 | \n\t\t\t\t\t\t- | \n\t\t\t\t\t
IMT, μm | \n\t\t\t\t\t\t+6 (85) | \n\t\t\t\t\t\tp<0.05 | \n\t\t\t\t\t\t+111 (91) | \n\t\t\t\t\t\tp<0.02 | \n\t\t\t\t\t
Plaques, scores | \n\t\t\t\t\t\t+0,21 (0,59) | \n\t\t\t\t\t\t0,009 | \n\t\t\t\t\t\t+0,31 (0,55) | \n\t\t\t\t\t\t<0,001 | \n\t\t\t\t\t
Carotid IMT changes in 1-year Karinat pilot study on postmenopausal women
In the Karinat group a completely different picture was observed. The average IMT of carotid arteries was not changed (statistically insignificant increase of 6 μm per year, i.e. less than 1%). However, the progression of existing plaques by 27% per year was detected.
\n\t\t\tThe results of quantitative measurements of the degree of atherosclerosis in the dynamics have shown that the use of phytoestrogen complex in postmenopausal women almost completely suppresses the formation of new atherosclerotic lesions and 1.5-fold slows the progression of existing lesions.
\n\t\t\tThus, as in the AMAR trial Inflaminat caused regression of carotid atherosclerosis while Karinat prevented its development. It should be noted that the anti-atherosclerotic effects of drugs based on natural products are not inferior to the effects of such drugs as statins and calcium antagonists (Table 4). Thus, natural products can be considered as promising drugs for anti-atherosclerotic therapy.
\n\t\tThis review illustrates the use of cultured human arterial cells for:
\n\t\t\t- mass screening of drugs and chemicals (cyclic AMP elevators, calcium antagonists, prostaglandins, - blockers, antioxidants, etc.);
- investigation of the mechanisms responsible for the atherosclerosis-related effects (calcium antagonists and lovastatin);
- optimization of anti-atherosclerotic and anti-atherogenic drug and dietary therapy (β-blockers, calcium antagonists, mushrooms, krill meat).
Cell cultures enable one to perform investigation on models: - in vitro (mass screening, study of the mechanism of drug action);
\n\t\t\t- ex vivo (study of the mechanism of drug action, optimization of therapy);
- in vivo models (animals with experimental atherosclerosis) allowed us to confirm the results obtained on in vitro and ex vivo models.
The in vitro and ex vivo models can be employed to reveal and investigate of:
\n\t\t\t- direct anti-atherosclerotic activity - regression of atherosclerosis (calcium antagonists, prostaglandins, antioxidants, lipostabil, mushrooms, mollusk meat, etc.);
- direct anti-atherogenic activity - prevention of atherosclerosis (calcium antagonists, mushrooms, krill meat);
- indirect anti-atherogenic activity (lovastatin);
- atherogenic activity (β-blockers, thromboxane, phenothiazines).
Natural products can be considered as promising drugs for anti-atherosclerotic therapy. Two-year treatment with Allicor (garlic powder) has a direct anti-atherosclerotic effect on carotid atherosclerosis in asymptomatic men. Inflaminat (calendula, elder and violet), possessing anti-cytokine activity, caused regression of carotid atherosclerosis as a result of 1-year treatment of asymptomatic men. Phytoestrogen-rich drug Karinat (garlic powder, extract of grape seeds, green tea leafs, hop cones, β-carotene, α-tocopherol and ascorbic acid) prevented development of carotid atherosclerosis in postmenopausal women.
\n\t\t\tOur basic studies have shown that cellular lipidosis is the principal event in genesis of atherosclerotic lesion. Using cellular models and natural products we have developed an approach to prevent lipid accumulation in arterial cells. This led to regression of atherosclerosis and/or prevention of its progression in patients. So, our basic findings were successfully translated into clinical practice. As a result of this translation novel approach to anti-atherosclerotic therapy was developed. On the basis of our knowledge we developed drugs possessing direct anti-atherosclerotic activity. Our clinical trial confirmed the efficacy both novel approach and novel drugs.
\n\t\tThis work was supported by the Russian Ministry of Education and Science.
\n\t\tThe objective of this work is to provide novel methods and techniques for the analysis of forensic multimedia data. These methods and techniques should form a novel toolkit for automatic forensic multimedia data. The data modalities the proposed work is considering are images and videos, text, handwriting, speech and audio signals, social media data, log data, and genetic data. The integration of methods for all these different data modalities in one tool kit should allow the cross-analysis of these data and the detection of events by interlinking between these data. The proposed methods will face on standard forensic tasks, for example, identification of events, persons, or groups and device recognition. Together with the end users and the police forces, new standard tasks will be worked out during the project and will give a new input to the standardization aspect of forensic data analysis.
\nThe proposed novel methods and techniques will consider all aspects of multimedia data analysis such as device identification and trustworthiness of the data, signal enhancement, preprocessing, feature extraction, signal and data analysis, and interpretation.
\nTechniques for detecting artifacts in images and videos are of paramount importance. To trust the information extracted from images and videos, it is necessary to make sure that the image and video have been recorded by a camera, and that no artifact has been added. The detection of artifacts is a key element to use an image or a video in court. Thus, it should be clearly assessed the integrity of images and videos used as a proof of evidence.
\nIn most image applications, the acquired images represent a degraded version of the original scene. Degradation in such images may appear in different forms. These types of degradations must be removed before the images are used for classification or decision making.
\nNovelty detection for the identification of novel situation and tasks will be another task that will be important in forensic applications, where the victims or events are very flexible. It will allow to identify new tasks, and by doing so, it will be an automatic method to improve standardization of the analysis of forensic data.
\nWe will also develop learning methods to include new data into the existing cases and summarization of new and old cases into more general cases applicable to a wider range of tasks for further law purposes. For that, novel case-based reasoning methods will be developed that can keep the cases based on their multimedia features and specific event features in a case base, so that they can be easily retrieved and applied for new situations. The case-based reasoning system will consist of novel probabilistic and similarity-based methods. It will provide a wide range of novel similarity-based reasoning methods for the different feature types for identification and similarity determination. A special taxonomy for similarity determination and measures will be worked out and implemented in the CBR system. It will provide explanation capabilities for similarity and as those it will help a forensic data analyst to identify the right reasoning method for his particular problem. This aspect goes along with the training and education aspect for forensic data analysis. Part of this will be self-contained in the chosen methods and realized by the system.
\nIn Section 2, the background and the motivation of our work will be described. Taking into account the special needs for multimedia forensic analysis, identification, and recognition system, we develop a novel architecture based on case-based reasoning. The data used are described in Section 3. Related work and the progress we want to make with our work are described in Section 4. This work does not only take into account to develop novel methods and techniques for multimedia content processing and reasoning, but we are also taking into account the legal aspect that is going along with processing sensible data. Finally, we given conclusions in Section 5. This chapter is continued in the Chapter Part II of Novel Methods for Forensic Multimedia Data Analysis.
\nThe analysis of multimedia data has to consider different aspects of the modalities of the data. We want to deal with images and videos, text, handwriting, speech and audio signals, social media data, log data, and genetic data. The idea is to come up with an automatic system that should cover all aspects of data analysis for the different modalities from the signal enhancement, preprocessing, feature extraction to the analysis, and interpretation. This includes image enhancement in order to eliminate the degradation in an image that might appear because of a known or an unknown blurring function, which leads to the consideration of deconvolution and blind deconvolution problems or because of very low resolution devices, which lead to the combination of several low resolution images to obtain a high resolution one, the so called, super-resolution problem or to the utilization of highly compressed images, which suffer from compression artifacts.
\nTechniques for detecting artifacts in images and videos will be developed to trust the information extracted from images and videos. They should allow to make sure that the image and video have been recorded by a camera, and that no artifact has been added.
\nFeature extraction will be the selection of a set of sufficiently low- and high-level features in order to complement the existing standards for image, video, and audio data, with the aim at enabling novel and robust classification and recognition methods. They should allow modeling the standard tasks for forensic data analysis known so far but should be flexible enough to cover the needs of newly arising task.
\nTwitter was actively used by rivaling gang members to plan their assaults. Twitter data are hard to analyze because the text fragments are very short, multiple persons can be involved in a conversation about various topics, and the data are rapidly changing. Novel methods are necessary, which can be used to monitor in real-time Twitter and identify potential threats including individuals and communities of users who are planning illegal activities.
\nFurthermore, we plan to build a dynamic model on Twitter text to forecast the upcoming significant events and emotions of the crowd associated with these events. While there can be many events with strong presence in Social Media, some of them would have stronger negative emotions associated with them. These events are candidates that may have criminal nature or significant social consequences.
\nThe huge amount of CCTV systems has increased the importance of video and image evidence in forensic labs. An automatic system should be able to select heads, vehicles, license plates, guns, dresses, and all other objects that can link a person to the event.
\nAn important main focus of police work is the identification of people for which a decision of the public prosecutor’s office or a judge to the observation or an arrest warrant was issued. Within the scope of this arrangement, the use of video supervised places and facilities, or at before not known places, the application of mobile video technology should occur for this purpose. The aim is to develop methods and procedures for an automatic system for identification of one or several target people in mobile video recordings based on passport photos or other available pictures.
\nA significant portion of data collected by Law Enforcement Agencies consists of speech and audio files. They form an important part of legal cases. Speech recognition systems (such as dictation systems) are now available in many languages. However, continuous spontaneous speech recognition is still an unsolved problem. Novel methods for the recognition of continuous spontaneous speech and other audio signals are necessary.
\nWhile the commercially available optical character recognition systems are very successful for printed documents, recognition of words in unconstrained settings or “in the wild” still is an open problem, and recognition of handwritten text continues to be a challenge. We propose to develop novel Handwriting Recognition Methods for unconstrained settings.
\nNovel Case-Based Reasoning (CBR) methods will be developed for the recognition, interpretation, and identification task. Case-based reasoning explicitly uses past cases from the domain expert’s successful or failing experiences. CBR is very useful in applications, where generalized knowledge is lacking. Therefore, case-based reasoning can be seen as a method for problem solving as well as a method to capture new experiences and make them immediately available for problem solving. It can be seen as a learning and knowledge discovery approach since it can capture from new experiences some general knowledge such as case classes, prototypes, and some higher-level concept. All these points make a CBR system very useful for the analyses of forensic data. The method is able to capture new cases and store new and old cases in a summarized way, so that they can be easily retrieved or used for reasoning. The reasoning methods are based on similarity that makes it very useful to detect and identify similar and identical cases without having generalized knowledge. Different similarity measures have to be developed that can deal with the different modalities of data and their case representation. A taxonomy of similarity will be developed that explains the relation, usefulness, and application of the different similarity measures to the data that will help a forensic data analyst to efficiently apply these reasoning methods to his problem.
\nAll the above-mentioned facts result in the overall system architecture given in Figure 1. The architecture consists of the three main processing units: media preprocessing, feature extraction, and decision unit based on case-based reasoning. The input is the different media data. The architecture is open, so that new input media data can be considered when the necessary processing modules are available. The outcome of the preprocessing and the feature extraction unit is a description of the different media data by sufficiently low- and high-level features that will be combined to the case representation. The reasoning will be done by the case-based reasoning unit based on formerly calculated case representation. The reasoning will be the identification and recognition of the objects or scenario’s as well as the detection of novel events. The CBR unit will be criticized based on the result of the action, and the decision of the CBR unit has been proposed. Depending on that outcome, case-based maintenance will be done. New case will be stored in the case base, the similarity measure will be updated or changed, or case generalization will be done.
\nSystem overview.
Besides the development of novel processing and reasoning methods, it is necessary to develop a legal framework regulating the process of gathering, processing, analyzing, and integrating multimedia data.
\nDifferent types of security-related data will be used for the work provided by the end users:
Passive millimeter-wave (PMMW) images and video are used for security screening as many materials, including clothing, are transparent to millimeter-waves. The imagers that use this technology, such as those developed by ALFA [1], are therefore installed at security checkpoints to screen people for hidden weapons (including powders, liquids, and gels) and contraband. They are characterized by a low resolution compared to visible images, due to the wavelength used. ALFA’s current software automatically detects objects within the spatial and thermal resolution of the system and draws a red box around them. Some examples of this image type are given in Figures 2
Anonymous Data from Text will be collected. These data are freely available on the Web. We propose to perform initial experiments on anonymized data to validate the feasibility of our approach. After authorization of the responsible superiors of the cybercrime unit is obtained, we will use the developed system for real-life investigations.
A Telekom company will prepare a speech database obtained under various conditions and under various speech coders and encoders to test the new algorithms.
Video and Image databases with case scenarios will be provided by police forces.
Handwriting documents will be collected through the involvement of graduate and undergraduate students. We also plan to use the following benchmark data set: IAM Database for Off-line Cursive Handwritten Text http://www.iam.unibe.ch/~zimmerma/iamdb/iamdb.html. The database contains the forms of unconstrained western handwritten text. It includes 27,000 isolated words (400 pages).
(a) Left: clothed subject; center: raw millimeter-wave image of subject; right: subject showing hidden suicide bomber belt; (b) left: clothed subject; center: raw millimeter-wave image of subject; right: subject showing hidden gun and knife; (c) left: clothed subject at 10 m; center: millimeter-wave image of subject at 10 m; right: subject showing two hidden bags of powder explosives. Subject with gel pack hidden between the legs and automatic millimeter-wave detection marked + raw millimeter-wave image of subject; right: subject with gel pack hidden under the arm and automatic millimeter-wave detection marked + raw millimeter-wave image of subject.
Automatic object and potential threat detection (ATD) on processed millimeter-wave image on the left and privacy protection output to operator on the right.
Person with hidden object around the hip.
In most image applications, the acquired images represent a degraded version of the original scene. These applications include astronomical imaging [2] (e.g., using ground-based imaging systems or extraterrestrial observations of the earth and the planets), commercial photography [3, 4], surveillance and forensics [5, 6], medical imaging [7] (e.g., X-rays, digital angiograms, autoradiographs, MRI, and SPECT), and security tasks where commercial photography and other image modalities like Synthetic Aperture Radar (SAR) [8] and Passive Millimeter (PMMW) [9] are frequently used.
\nDegradations in such images may appear in different forms. They may be due to a known or an unknown blurring function that leads to the consideration of deconvolution [9, 10, 11, 12, 13] and blind deconvolution [3, 14] problems. They may also be due to the use of very low-resolution devices, which lead to the combination of several low-resolution images to obtain a high-resolution one, the so called, super-resolution problem [15, 16] or to the utilization of highly compressed images, which suffer from compression artifacts [17]. These types of degradations must be removed before the images or video sequences are used for classification or decision making. Interestingly, all the problems described above can be formulated within the Bayesian framework [18, 19, 20]. A fundamental principle of the Bayesian philosophy is to regard all parameters and unobservable variables as unknown stochastic quantities, assigning probability distributions based on subjective beliefs. Thus, the original image(s), the observation noise, and even the function(s) defining the acquisition process are all treated as samples of random fields, with corresponding prior probability density functions that model our knowledge about the imaging process and the nature of images.
\nOnce the problem is modeled, inference is then needed. The recently developed variational Bayesian methods have attracted a lot of interest in Bayesian statistics, machine learning, and related areas [18, 19, 20]. A major disadvantage of traditional methods (such as expectation maximization (EM)) is that they generally require exact knowledge of the posterior distributions of the unknowns, or poor approximations of them are used. Variational Bayesian methods overcome this limitation by approximating the unknown posterior distributions with simpler, analytically tractable distributions, which allow for the computation of the needed expectations and therefore extend the applicability of Bayesian inference to a much wider range of modeling options: more complex priors (which are very much needed in applications involving images) modeling the unknowns can be utilized with ease, resulting in improved estimation accuracy.
\nTechniques for detecting artifacts in images and videos are of paramount importance. In order to trust the information extracted from images and videos, it is necessary to make sure that the image and video have been recorded by a camera, and that no artifact has been added. The detection of artifacts is a key element to use an image or a video in court. Thus, the integrity of images and videos used as a proof of evidence should be clearly assessed. The trustworthiness of images and videos has clearly an essential role in many security areas, including forensic investigation, criminal investigation, surveillance systems, and intelligence services.
\nAs stated by Mahdian and Saic [21], verifying the integrity of digital images and detecting the traces of tampering without using any protecting pre-extracted or pre-embedded information have become an important research field of image processing. We will utilize and develop blind methods for detecting image forgery, that is, methods that use the image function to perform the forgery detection task. These methods are based on the fact that forgeries bring into the image-specific detectable changes (e.g., statistical changes). In high-quality forgeries, these changes cannot be found by visual inspection. Existing methods mostly try to identify various traces of tampering and detect them separately. The final decision about the forgery can be carried out by fusion of results of separate detectors.
\nBlind methods can be classified into several categories. In detection of near-duplicated image regions, a part of the image is copied and pasted into another part of the same image with the intention to hide an object or a region. There are methods capable of detecting near duplicated parts of the image that usually require a human interpretation of the results, see Refs. [21, 22, 23]. A different category includes interpolation and geometric transformation that are typically based on the resampling of a portion of an image onto a new sampling lattice, see, for example, Ref. [24]. In the photomontage detection problem, one of the fundamental tasks is the detection of image splicing, which can sometimes be based on analyzing the lighting conditions. Another category is related to compression method. In order to alter an image, typically the image is loaded to photoediting software, and once the changes are done, the digital image is resaved. Methods capable of finding the image compression history can be helpful in forgery detection. Another important category is the study of the noise characteristics and the chromatic aberrations [25, 26]. In the same line, blur and sharpening can also be analyzed to detect the concealment of traces of tampering. When two or more images are spliced together, it is often difficult to keep the appearance of the image correct perspective. Applying the principles from projective geometry to problems in image forgery detection can be also a proper way to detect traces of tampering. There are also other groups of forensic methods effective in forgery detection, see, for instance, single-view recaptured image detection, aliveness detection for face authentication, and device identification in digital image forensics, Refs. [27, 28, 29, 30].
\nCase-Based Reasoning has been shown a successful problem-solving method in different applications were generalized knowledge is lacking. CBR has been used to interpret images [31, 32], 1-D signals [31, 33, 34], and text cases [35]. It also has been used for meta-learning of the best parameter of image segmentation [36] and classification methods [37], so that the best processing and classification results can be achieved, although domain knowledge is lacking. The success of these systems is because cases can be more easily collected than rules or other domain data and because of the flexibility of the systems based on their learning and maintenance mechanisms that allow incrementally improvement of their system performance during usage of the system.
\nThe necessity to study the taxonomy of similarity measures and a first attempt to construct a taxonomy over similarity measures has been given by Perner [38] and has been further studied by Cunningham [39]. More work is necessary especially when not only one feature type and representation is used in a CBR system, as it is the case for multimedia data. These multimedia cases will be more complex as the cases used in the system described above that only face on one specific data type. To understand the similarity between these multimedia cases will require more complex knowledge of similarity by the police investigator for the different types of multimedia data. To develop novel similarity measures for text, videos, images, and audio and speech signals and to construct a taxonomy that allows understanding the relation between the different similarity measures will be a challenging task. Similarity aggregation of the different types of similarity measures is another challenging topic. Specific knowledge for the different types of data such as text [40, 41], images [42, 43, 44], video [45], 1-D signals, and meta-learning [36] is required in this work. The development of new similarity measures for multimedia data types and new data representations and ontologies will be done. A complex CBR system that can handle so many different data types, similarities, and data sources is a novelty.
\nRetrieval of multimedia data from a case base can be refined by relevance feedback mechanisms [46, 47, 48, 49, 50, 51, 52]. The user is asked to mark retrieved results as being “relevant” or not with respect to his/her interests. Then, feature weights and the similarity measures are suitably adapted to reflect user’s interests. Relevance feedback can be implemented in a number of ways, for example, as the solution of an optimization problem, or as a classification problem. According to the problem at hand, the most suited formulation has to be devised. Thus, the main challenge will be to formulate the relevance feedback problem for forensic applications, so that the search is driven toward the cases more relevant to the case at hand.
\nResearch has been described for learning of feature weights and similarity measures [53, 54, 55]. Case mining from raw data in order to get more generalized cases has been described by Jaenichen and Perner [56]. Learning of generalized cases and the hierarchy over the case base has been presented by the authors of Refs. [45, 57]. These works demonstrate that the system performance can be significantly improved by these functions of a CBR system.
\nNew techniques for learning of feature weights and similarity measures and case generalization for different multimedia types are necessary and will be developed for these tasks.
\nThe question of the Life Cycle of a CBR system goes along with the learning capabilities, case base organization and maintenance mechanism, standardization, and software engineering for which new concepts should be developed. As the result, we should come up with generic components for a CBR system for multimedia data analysis and interpretation that form a set of modules that can be easily integrated and updated into the CBR architecture. The CBR system architecture should easily allow configuring modules for new arising task.
\nThe partner IBAI has a number of national and international patents that protect their work on CBR for images and signals. It is to expect that new methods will be developed that can be protected by patents and can ensure the international competition of European entities on CBR systems.
\nMost of computer vision algorithms rely on the extraction of meaningful features that transform raw data values into a more significant representation, better suited for classification and recognition. Although considered often not a central problem, the quality of feature representation can have critically important implications for the performance of the subsequent recognition methods.
\nFeatures are usually defined and selected according to a problem-oriented strategy, that is, ad hoc in light of the information considered relevant for the task at hand. In forensics, a plethora of features have been defined for the automated solutions to different problems, such as face detection, retrieval and recognition in video and images [58, 59, 60], individual people tracking over video sequences [61, 62], recognition of different biometric parameters (ear, gait, and iris) in images or videos [63, 64], speaker identification in audio signals, suspicious word detection, and handwriting recognition in text document.
\nMain challenges in forensics scenarios regard the unconstrained conditions in which multimedia data are collected. For audio signals, this is usually in the form of channel distortion and/or ambient noise. For videos and images, problems arise from changes in the illumination direction and/or in the pose of the subjects, occlusions, aging, and so on.
\nFor images and videos, according to the problem at hand, the features selected can be based on specific morphologic parameters of individuals, such as face characteristics (e.g., nose width and eye distance) [65], posture and gesture, ear details, and so on or on general appearance features computed with low-level descriptors. These descriptors can be either global or local and can exhibit different degrees of invariance. Global descriptor category includes features based on Principal Component Analysis (PCA) [66] and Linear Discriminant Analysis (LDA) [67]. The local descriptor category is currently spreading and comprises features based on local values of color, intensity, or texture. To this category belong Scale-Invariant Feature Transform (SIFT) [68], Local Binary Pattern (LBP) [69], Histograms of Oriented Gradients (HOG) [70], or Gabor wavelets [71]. LBP is a well-known texture descriptor and a successful local descriptor robust to local illumination variations [72]. LBP descriptors are compact and easy to compare by various histogram metrics. In addition, there are many LBP variants that improve the description performance; among these, the most popular is Multi-Scale LBP (MSLBP) [73]. HOG has been successfully applied to tasks such as human detection [70] and face recognition [74]. Similar to LBP, edge information captured by gradients within blocks is packed into a histogram. Discarding pixel location information by block-based histogram binning, LBP and HOG gain invariance to local changes such as small facial expressions and pose variations in pedestrian images. The Gabor wavelets are also successful descriptors that capture global shape information centered at a pixel [75]. The convolution of multiple Gaussian-like kernels with different scales and orientations captures information insensitive to expression variation and blur at a pixel’s location. Recently, a generalization of the Pairs of Pixels (POP) descriptor, called Centre Symmetric-Pairs of Pixels (CCS-POP), has been presented for face identification [76]. Another line of research currently gaining attention regards the computation of biologically inspired descriptors that result from the attempt to mimic natural visual systems. Several works have shown interesting results in a variety of different face and object recognition contexts [77, 78, 79].
\nThe approach based on local descriptors has recently gained popularity, especially in relation to the spreading of the bag-of-feature representation. Indeed, in this frame, local feature descriptors, which can achieve high robustness with respect to appearance variations, are employed to develop a bag of descriptors that represent image content. All such descriptors are, then, quantized using learned visual words to facilitate the retrieval or classification [80, 81, 82, 83]. The approach seems promising in forensic scenarios to fit the high variation of object appearance across different views since some very informative local features can accommodate to bad localizations or part visibility [62].
\nThe problem of automatically extracting relevant information out of the enormous and steadily growing amount of electronic text data is becoming much more pressing. To overcome this problem, various technologies for information management systems have been explored within the Natural Language Processing (NLP) community. Two promising lines of research are represented by the investigation and development of technologies for (a) ontology learning from document collections and (b) feature extraction from texts.
\nOntology learning is concerned with knowledge acquisition from texts as a basis for the construction of ontologies, that is, an explicit and formal specification of the concepts of a given domain and of the relations holding between them; the learning process is typically carried out by combining NLP technologies with machine learning techniques. Buitelaar [84] organized the knowledge acquisition process into a “layer cake” of increasingly complex subtasks, ranging from terminology extraction and synonym acquisition to the bootstrapping of concepts and of the relations linking them. Term extraction is a prerequisite for all aspects of ontology learning from text: measures for termhood assessment range from raw frequency to Information Retrieval measures such as TF-IDF, up to more sophisticated measures [85, 86, 87, 88]. The dynamic acquisition of synonyms from texts is typically carried out through clustering techniques and lexical association measures [89, 90]. The most challenging research area in this domain is represented by the identification and extraction of relationships between concepts (taxonomical ones but not only); this research area presents strong connections with the extraction of relational information from texts, both relations and events (see below).
\nWith feature extraction, we refer to the task of automatically identifying in texts instances of semantic classes defined in an ontology. This task includes recognition and semantic classification of items representing the domain referential entities (“Named Entity Recognition” or NER), either “named entities” or any kind of word or expression that refers to a domain-specific entity. Recently, extraction of inter-entity relational information is becoming a crucial task: relations to be extracted range from “place_of”, “author_of,” etc. to specific events, where entities take part in with usually predefined roles (“Relation Extraction”). Currently, there exist several feature extraction approaches, addressing different requirements, operating in different domains and on different text types, and extracting different information bits. If we look at the type of the underlying extraction methodology, systems can be classified into the following classes:
rule-based systems, using hand-crafted rules. Rule-based systems are particularly appropriate for dealing with documents showing very regular patterns, such as standard tables of data, Web pages with HTML markup, or highly structured text documents;
systems incorporating supervised machine learning: an alternative to the time-consuming process of hand coding of detailed and specific rules is represented by supervised semantic annotation systems, which learn feature extraction rules from a collection of previously annotated documents; and
systems using unsupervised machine learning: they represent a viable alternative, currently being explored in different systems, to supervised machine learning approaches, as they dispense with the need for training data whose production may be as time consuming as rule hand coding.
Depending on nature and depth of the features to be extracted, different amounts of linguistic knowledge must be resorted to. This means that type and role of the linguistic analysis differ from one system to another. The condition part of feature extraction rules may check the presence of a given lexical item, the syntactic category of words in context, and their syntactic dependencies. Different clues such as typographical features, relative position of words, or even coreference relations can also be exploited. Most feature extraction systems therefore involve linguistic text processing and semantic knowledge: segmentation into words, morphosyntactic tagging, (either shallow or full) syntactic analysis, and sometimes even lexical disambiguation, semantic tagging, or anaphora resolution.
\nText analysis can be carried out either at the preprocessing stage or as part of the feature extraction process. In the former case, the whole text is first analyzed. The analysis is global in the sense that items that are spread all over the document can contribute to build the normalized and enriched representation of the text. Then, the feature extraction process operates on the enriched representation of the text. In the latter case, text analysis is driven by the process of verifying a specific condition. The linguistic analysis is local, focuses on the context of the triggering item associated with a specific feature, and fully depends on the conditions to be checked for that feature.
\nDifferent approaches to feature extraction will be investigated to assess their strength and effectiveness to detect and describe the multimedia data content relevant to forensic activities. Both biometric features and local informative descriptors will be studied and collected to create a range of different opportunities to describe multimedia data content. More precisely, low level, local, invariant descriptors will be explored to assure a good performance of detection algorithms, especially for recognition in the wild, whereas global biometric features and properties will be considered as high-level information that is better understandable by end users.
\nA formal model will be adopted to define the features of different kinds. This will result into an ontological model that will organize different classes of features and foster their sharing and reuse. This will be a very innovative result since the ontology will be general and will approach the domain of multimedia data analysis. It will go further current metadata standards such as MPEG 7 or 21 and will be much more comprehensive and specific than other existing ontologies, which are only partially focused on feature extraction and always aimed at other problems such as multimedia data annotation. Additionally, the ontology will be enriched with algorithms to compute the features included, resulting into a toolbox for feature extraction. This will be another very innovative result.
\nAs far as feature extraction from texts is concerned, the main challenge is represented by the typology of texts to be dealt with, testifying noncanonical language usages.
\nTwitter is a new multimedia communication channel that is rapidly gaining popularity and users, yet police forces do not dispose of adequate methods to analyze the large amounts of textual data that are generated each day. Recently, several retrospective investigations concerning football riots revealed that Twitter was actively used by rivaling gang members to plan their assaults. Twitter data are hard to analyze because the text fragments are very short, multiple persons can be involved in a conversation about various topics, and the data are rapidly changing.
\nTwitter is a recently introduced microblogging and information sharing platform [91] with over 140 million users and 340 million tweets per day. In the past, several studies have been dedicated to analyzing twitter feeds, for example, in the field of opinion mining and sentiment analysis. For example, in Ref. [92], the authors analyzed the text content of daily Twitter feeds by two mood tracking tools: OpinionFinder, which measures positive versus negative mood, and Google-Profile of Mood States (GPOMS), which measures mood in terms of six dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). They cross-validated the resulting mood time series by comparing their ability to detect the public’s response to the presidential election and thanksgiving day in 2008. Ratkiewicz et al. [93] used machine learning for analyzing politically motivated individuals and organizations that use multiple centrally controlled twitter accounts to create the appearance of widespread support for a candidate or opinion and to support the dissemination of political misinformation.
\nWe propose to develop and use an integrated data visualization environment based on formal concept analysis, temporal concept analysis, temporal relational semantic systems, and self-organizing maps to identify suspicious tweets.
\nFormal concept analysis (FCA) is a mathematical technique that was introduced in 1982 by Rudolf Wille [94] and takes its roots in earlier work of Birkhoff [95] and the early work on applying lattice-theoretical ideas in information science, like it was done by Barbut et al. [96]. FCA was used in several security text mining projects. The goal in each of these papers was to make an overload of information available in an intuitive visual format that may speed up and improve decision making by police investigators on where and when to act. In the first case study, with the Amsterdam-Amstelland police (RPAA), which started in 2007, FCA was used to analyze statements made by victims to the police. The concept of domestic violence was iteratively enriched and refined, resulting in an improved definition and highly accurate automated labeling of new incoming cases [97]. Later on, the authors made a shift to the millions of observational and very short police reports from which persons involved in human trafficking and terrorism were extracted. Concept lattices allowed for the detection of several suspects involved in human trafficking or showing radicalizing behavior [98, 99].
\nTemporal concept analysis (TCA) was introduced by Wolff [100] and offers a framework for representing and analyzing data containing a temporal dimension. In previously discussed security applications, suspects were mentioned in multiple reports, and a detailed profile of one suspect (and persons in his social network) depicted as a lattice, with timestamps of the observations as objects and indications as attributes helped to gain an insight into his (their) threat to society [101]. Recently, TCA and its relational counterpart temporal relational semantic systems (TRSS, [100]) were successfully applied to the analysis of chat conversations [102].
\nSelf-organizing maps [103] have been used in many applications, where high-dimensional unsupervised data spaces had to be visualized in a two-dimensional plane to make the data accessible for human experts. For example, Ramadas et al. [104] used self-organizing maps for identifying suspicious network activity. In a previous security case study, a special type named emergent self-organizing maps was used to identify domestic violence in police reports [105, 106]. They were found to be more suitable than multidimensional scaling for text mining. Claster et al. [107] used self-organizing maps to mine over 80 million twitter micro logs in order to explore whether these data can be used to identify sentiment about tourism and Thailand amid the unrest in that country during the early part of 2010 and further whether analysis of tweets can be used to discern the effect of that unrest on Phuket’s tourism environment.
\nNevertheless, there are several differences between analyzing twitter feeds and traditional police reports. Whereas individual tweets may not be so interesting, a lot of information can be distilled from conversations consisting of many tweets that emerged between different users concerning a certain topic. Such feeds do not contain a summary of facts; rather several topics emerge between two or more persons. We should judge the interestingness of the feed from a security enforcement perspective and distinguish between several types of twitter users in a relevant conversation, for example, is this person someone who contributed only marginally or did he or she actually contribute to or promote criminal behavior. Ebner et al. [108] used Formal Concept Analysis (FCA) to categorize twitter users who write tweets about the same topics in the context of a conference event. Cuvelier et al. [109] used FCA as an e-reputation monitoring system in combination with tag clouds. Also, the Natural Language Processing of tweets is nowadays a challenging task since Twitter is characterized by a so-called noncanonical language. It is widely acknowledged that NLP systems have a drop of accuracy when tested against text characterized by this kind of language. This negatively affects different levels of text analysis ranging from the linguistic annotation to the information extraction process. It follows that the analysis of noncanonical languages is one of the main topics of the most recent NLP conferences, for example, the First Workshop on Syntactic Analysis of Noncanonical Language (SANCL-2012) (https://sites.google.com/site/sancl2012/), the workshop series on Scritture brevi (lit.: short writings) organized by the University of Rome Tor Vergata (https://sites.google.com/site/scritturebrevi/atti-dei-workshop), and the First Shared Task on Dependency Parsing of Legal Texts at SPLET-2012 (https://sites.google.com/site/splet2012workshop/shared-task). The main challenges in analyzing noncanonical languages, as tweet language, result from the fact that they have different linguistic characteristics with respect to the data from which the tools are trained, typically newswire texts. Among the others, punctuation and capitalization are often inconsistent; slang, technical jargon is widely exploited; and noncanonical syntactic structures frequently occur [110, 111, 112]. Accordingly, several domain adaptation methods and different strategies of analysis have been investigated to improve the accuracies of the NLP tools, among the most recent ones the self-training method used by Le Roux et al. [113], the active-learning method used by Attardi et al. [114], and the term-extraction method proposed by Bonin et al. [88].
\nEvent detection in Twitter has been recently an area of active research and successfully applied to detecting earthquakes [115] and sport events [116]. For events of interest to legal forces, one can utilize the generic features, such as emerging common terms, location, date, and also potentially the participants of the event. Hence, we extract the date/time information and time-event phrases that are learnt from tweets and set the presence of them as a feature. Participant information is also captured via the presence of the ‘@’ character followed by a username within tweets. Specific to the events of legal interest, one can also utilize the overall sentiment of the tweets as a potential feature. According to a recent research by Leetaru [117] at the University of Illinois at Chicago, strong negative emotions in news can suggest upcoming of a significant event. A sentiment analysis in a long period of news revealed that the textual sentiments before the revolutions in Libya and Egypt have shown significant negative signals. The strength of this negativity is found comparable to the signals in 1991 news, right before the United States entered Kuwait; and also in 2003, when the United States-Iraq was about to start.
\nWhile the current approaches, such as Ref. [117], have been shown to work on static data and static models, more research is needed to enhance these methods for the dynamic case. Also, the news text is highly structured and formal, while Twitter consists of informal short text. Based on our prior work on classifying short tweets [118], and sentiment analysis on large-scale data [119], we will categorize the tweets for event detection and identify tweets with strong sentimentality. Our initial hypothesis is that strong sentiment increases the probability of event being of interest to legal forces. Recently, distributional semantic models (DSMs) have been applied to affective text analysis with good results across languages [120]. In this WP, we will also apply DSMs to sentiment analysis of multilingual tweets. The more interesting problem is the forecasting problem, where the events can be predicted beforehand. This would be of high value for preventive law enforcement. Besides the prediction problem, one can also use this approach to get feedback from the crowd on actions taken by the law officers. Such approaches have already been deployed for finance and marketing applications to understand the mood of financial markets and consumer opinions [92, 121, 122]. Similar concepts can be adapted for forensic applications. In fact, FBI and Pentagon have already started to utilize these methods to predict criminal and terrorist activities and monitor persons and regions of high interest [AP Exclusive].
\nThe innovativeness of tool in this area lays in the fact that the combination of the discussed methods has never been proposed for visualizing and clustering data, nor integrated in a software system. It will be the first integrated human centered data discovery environment that combines both statistical methods from machine learning with order-theoretic methods such as concept lattices. The self-organizing map that can handle high-dimensional data spaces and, as a consequence, is an ideal tool for an initial preprocessing is at the start of the human centered discovery process. FCA can then be used to explore dependencies and information links in a smaller subset. TCA and TRSS are used for in-depth profiling of identified individuals and communities. In particular, we focus on the niche of twitter user and feed mining in the broader text-mining field. State-of-the-art domain adaptation methods will be tested to improve the accuracies of the linguistic annotation tools on Twitter data, and customized term-extraction methods will be devised in order to reliably extract relevant keywords from tweets. Needless to say that the proposed system can be easily expanded to other text mining applications.
\nA web crawler will be designed to collect the feeds from the twitter website. This is a technically challenging yet known task to the scientific community (see e.g., [107]). The data collection can be done by an employee hired by the police who received a type P screening. The type of data is fragments of texts. Concerning languages, we will first focus on Dutch tweets. This may later be extended to Hungarian and Bulgarian since most organized crime in areas such as human trafficking is committed by these nationalities in Amsterdam. Since a tweet consists of among others a user name, his twitter ID and the posted text, as well as potentially ID and name of other users, we will first replace these user-identifiable information items by numeric values using regular expressions. In the second step, we will use available Named Entity Recognition methods for removing person names from the tweets themselves.
\nVideo retrieval has a long history [123, 124, 125]. According to the type of video at hand (e.g., film, news, CCTV recording, etc.), different retrieval tasks can be defined both in terms of the type of query and in terms of the processing techniques that are suited for extracting meaningful concepts. For example, it is easy to see that the making of a film comprises the use of techniques whose goal is to provoke sentiments in the watcher. Thus, in order to retrieve concepts from videos, automatic techniques must take into account not only the characteristic of the scene but also the movements of the camera and video editing techniques. On the other hand, still cameras used for video-surveillance purposes allow for the detection of persons and objects moving within the monitored area, as the characteristic of the scene is well known in advance. On these topics, a vast corpus of research has been carried out in the past years, and a number of automatic analysis techniques are embedded into commercial products [126].
\nOne of the first steps in video analysis is the detection of shots, that is, video sequences that contain a continuous camera action in time and space [127, 128]. In the case of films, broadcasted news, and sport videos, shot detection is performed by looking at well-known separators, such as fading and black frames. Each shot is then characterized by one or more key frames, that is, those frames that can be used to characterize the shot. Shot classification can be performed by extracting suitable features and using machine-learning techniques for concept classification. Features can be either extracted from key frames, as well as by looking at global characteristics of the video sequence. They can represent low-level information of such as color and textures as well as characteristics of the shot such as temporal features.
\nA number of techniques for carrying out these steps have been developed for TV broadcasters, in particular for sport as well as news programs [123, 124]. In these areas, the knowledge of the rules of the game and the rules of video shooting allowed for building a reliable ground truth that allows to make objective comparisons of different algorithms. The classification of video shots can be used for retrieval purposes, as soon as the goal is to retrieve all videos related to a particular class. On the other hand, the use of these techniques for forensic applications still needs more investigation due to the low resolution of the cameras, the variability of the recorded scenes, and the presence of person and objects typically in nonfrontal positions and with many occlusions.
\nToday, it is of particular interest the reidentification of people in videos [129, 130]. This problem can be formulated as follows. In many real scenarios, an area is monitored by a number of cameras. When persons move in the monitored environment, they can be identified by their face only if they appear in the video in some pose. After they have been identified in one of the videos, they can be tracked (i.e., reidentified) according to their global appearance (e.g., their clothes) rather than by their face.
\nSpeech and sound files constitute an important part of the data collected by Law Enforcement Agencies. For the last 35 years, practical speech recognition systems have been based on Hidden Markov Models (HMMs), which model the training data using the Baum-Welch algorithm in a global manner. Markov state probability distributions are also represented using Gaussian Mixture Models (GMMs). HMMs try to represent the time-varying speech and sound files [131, 132]. This approach is successful to some extent in controlled environments and dictation systems in which people clearly speak to the machines [133].
\nHMMs and GMMs use features extracted from temporal speech windows. Current speech and sound feature extraction schemes are based on Fourier analysis [131, 134, 135]. Temporal information is only incorporated to the automatic speech recognition systems by only dividing speech into temporal analysis windows. Unfortunately, this global approach loses keyword or speaker-specific features, which are needed in forensic applications. For example, a person cannot modify his or her own average temporal zero crossing rate, even if he or she tries to change his or her own voice by mumbling, or talking with a mouth full of food or cotton balls, etc. [136]. This kind of temporal and person specific information is not used in today’s systems, which are globally trained using all the available data.
\nGlobal approaches provide good speech and speaker recognition and identification results as long as it is possible to have a good description of the unobserved data. However, continuous spontaneous speech recognition is still an unsolved problem [133, 137]. Unfortunately, most of the speech data in legal cases are spontaneous speech data. In many applications, it is required to retrieve keywords, phrases, names, and speakers from spontaneous speech in real time. Therefore, it is necessary to develop not only new feature extraction and speech and sound representation schemes but also exemplar type case and similarity-based reasoning methods to improve the current speech and sound processing systems.
\nThe analysis of videos for forensic applications can be carried out by relying on some of the above techniques, provided they are tailored to the scenario at hand. It is easy to see that in the case of surveillance videos, we cannot define a shot according to the paradigm used to segment a film or a sport video [126, 138]. Rather, the definition of “shot” can be driven by the event that is looked for in the video. In particular, the video analyst should be able to query the system, so that the video is first segmented according to the particular event, and then, the shots that can contain the event of interest with high probability are further analyzed by more sophisticated technique in order to detect the object of interest [139]. The development of such a system is beyond the current state of the art, and it will be carried out within this project.
\nThe development of reidentification techniques may allow tracking a person in videos collected by multiple cameras at different locations and in different periods. Detecting people can be carried out by face detection. Many of the existing facial recognition systems are sensitive to variations in the enrolment phase [140, 141, 142, 143, 144, 145]. Often these systems have been trained by a huge number of pictures of the same person to estimate reliable values of the parameters for statistical classifiers. The current state of the art does not include a suitable system for the generation of a prototype picture of a person nor a suited prototype-based classifier [146, 147]. Some automatic prototype generation developed in the area of pattern recognition could be used for face recognition [148, 149, 150].
\nPrototype-based system could effectively handle changes in illumination, as they can perform recognition by part resemblance [151, 152]. For the above reasons, most of the facial recognition systems available today assume a standardized enrolment procedure to be performed in a controlled environment (e.g., a cabin), where a number of pictures of the face in a frontal position (2-D) with respect to the camera are taken. In addition, the picture is renewed whenever the recognition accuracy decreases.
\nMany different methods have been used so far for face recognition and cover a wide spectrum of methods in the pattern recognition field: geometrical representation of the face [153], templates [154, 155], hidden Markov models [156], principal component analysis [157], independently component analysis [158], elastic graph matching [159], trace transform [160], and SVM [161]. None of the methods can be seen as the most promising method because the performance depends on the scenario at hand, and the assumption behind the proposed theoretical models might not be met in real scenarios. Thus, new techniques based on the exploitation of different picture representations, such as shape, texture, signs for skin, eyes and spatial, sign-based connections, and the prototype-based system, have to be investigated.
\nCase and similarity-based recognition and sensing methods for speech, sound, and audio recognition using both temporal and frequency domain information will be developed. Development of “query by example,” keyword, and phrase-based retrieval schemes using exemplar-based schemes, which will be capable of part and whole similarity matching, will be a significant contribution to the existing speech recognition systems.
\nCurrent methods for speech and audio analysis emphasize spectral methods. For example, well-known Shazam music recognition method uses only spectral peaks [162]. Commonly used mel-cepstral coefficients, line spectral frequencies, and RASTA features [134, 135] do not have any temporal information, either. We believe that temporal information is not fully utilized in current methods. Temporal information will provide critical information for speaker recognition and keyword spotting applications. We are developing temporal speech representation methods based on delta modulation [163, 164], zero-crossing, and wavelet scattering [165, 166] information will be incorporated into content based audio and sound retrieval and speech and audio recognition applications.
\nAs pointed above, another important avenue, which is not explored by current methods, is compressive recognition, similarity-based reasoning, and case-based reasoning. Current data modeling methods assume a global representation. On the other hand, case and similarity-based reasoning methods will be able to incorporate fine details of the test case and will likely to provide better recognition results, especially in spontaneous speech. Temporal representation methods such as delta modulation and zero-crossing information are ideal for exemplar and similarity-based reasoning approaches. It is also possible to combine the differential representation of temporal data with the spectral data using compressive sensing [167], which extends this differential data processing concept by using random weights adding to zero to linearly combine the data and/or features. In this way, similarity learning, case generalization and case storage, and compressive learning and sensing will allow the handling of very large amount (terabytes) of data. Once the keyword and phrases are detected, analysts can manually process the proposed retrieval results.
\nCut-and-paste locations in speech can be also detected using delta modulation and wavelet scattering, providing a differential representation of speech, sound, and audio data. Fragile watermarking schemes based on wavelet scattering and delta modulation will be developed to prevent tampering. Resulting representation can be easily stored, and it will be ideal for different forensic purposes.
\nForensic investigations on multimedia evidence usually develop along four different steps: analysis, selection, evaluation, and comparison. During the analysis step, technicians typically look at huge amounts of different multimedia data (e.g., hours of video or audio recordings, pages and pages of text, and hundreds and hundreds of pictures) to reconstruct the dynamic of the event and collect any piece of relevant information. This step obviously requires a lot of time, and many factors can make it difficult, among which data heterogeneity, quality, and quantity are the most relevant. Afterward, during the selection step, technicians select and acquire the most meaningful pieces of information from the different multimedia data (e.g., frames from videos, audio fragments, and documents). Then, in the evaluation step, they look for relevant elements in the selected data, which will be further investigated in the comparison step. They can select heads, vehicles, license plates, guns, sentences, sounds, and all other elements that can link a person to the event. The main problems are the low quality of media data due to high compression, adverse environmental conditions (e.g., noise, bad lighting condition), camera/object position, and facial expressions. Finally, during the comparison step, technicians place the extracted elements side by side with a known element of comparison. From the comparison of general and particular characteristics, the operators give a level of similarity. In forensic application, the use of automatic pattern recognition system gives poor performance because of the high variability of data recording. On the other hand, human perception is a great pattern recognition system but is characterized by high subjectivity and unknown reproducibility and performance.
\nIn this chapter, we propose to develop a toolkit of methods and instruments that will be able to support analysts along all these steps, strongly reducing human intervention. First of all, it will include instruments to process different kinds of media data and, possibly, correlate them. This will obviously reduce the time spent to find the correct instruments for processing the medium at hand. Furthermore, it comprises preprocessing tools that alleviate, by filtering and enhancement, the problem of low-data quality. In particular, for image and video data, a great help will come from super-resolution methods that will maximize the information contained in low-resolution images or videos (e.g., foster the process of face reconstruction and recognition from blurred images). This feature will greatly support all the subsequent steps.
\nIn this chapter, we focused on the background and motivation for our work. The overall system architecture is explained. We present the data to be used. After a review of the state of the art of related work of the multimedia data we consider in this work, we describe the method and techniques we are developing that go beyond the state of the art. The work will be continued in the Chapter Part II of Forensic Multimedia Data Analysis.
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\n\nOut of all of the publishing options available to researchers, why choose to contribute your research to an IntechOpen Edited Volume? The reasons are simple. IntechOpen has worked exceptionally hard over the past years to fine tune the Open Access book publishing process and we continue to work hard to deliver the best for all of our contributors. The quality of published content is of utmost importance to us, followed closely by speed, and of course, availability and accessibility. To view current Open Access book projects that are Open for Submissions visit us here.
\n\nQUALITY CONTENT
\n\nOver the years we have learned what is important. What makes a difference to the researchers that work with us, what they value. Something that is very high not only on their lists, but our own, is the quality of the published content.
\n\nOur books contain scientific content written by two Nobel Prize winners, two Breakthrough Prize winners and 73 authors who are in the top 1% Most Cited.
\n\nWith regular submission for coverage in the single most important database, the Book Citation Index in the Web of Science™ Core Collection (BKCI), and no rejected submissions to date, over 43% of all Open Access books indexed in the BKCI are IntechOpen published books.
\n\nIn addition to BKCI, IntechOpen covers a number of important discipline specific databases as well, such as Thomson Reuters’ BIOSIS Previews.
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\n\nThe need for up to date information available at the click of a mouse is one thing that sets IntechOpen apart. By developing our own technologies in order to streamline the publishing process, we are able to minimize the amount of time from initial submission of a manuscript to its final publication date, without compromising the rigor of the editorial and peer review process. This means that the research published stays relevant, and in this fast paced world, this is very important.
\n\nYOUR WORK, YOUR COPYRIGHT
\n\nThe utilization of CC licenses allow researchers to retain copyright to their work. Researchers are free to use, adapt and share all content they publish with us. You will never have to pay permission fees to reuse a part of an experiment that you worked so hard to complete and are free to build upon your own research and the research of others. The Edited Volume helps bring together research from all over the world and compiles that research into one book - accessible for all. The research presented in chapter one can inspire the author of chapter three to take his or her research to the next level. It is about sharing ideas, insights and knowledge.
\n\nCan collaboration be inspired by a publishing format? At IntechOpen, the answer is yes. The way the research is published, the way it is accessed, it’s all part of our mission to help academics make a greater impact by giving readers free access to all published work.
\n\nOur Open Access book collection includes:
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