Natural course of diabetic nephropathy in type 1 diabetes
\r\n\tApplied and basic studies - Field studies and lab assays of fungicides can be discussed. We also look for examples of application methods, which may include timing of application, tools for application, fungicide compatibility, phytotoxicity, etc. Field trials have to have at least two years of data;
\r\n\tAdaptation of Integrated Plant Disease Management - How the IPM practice has been adapted in the field. Application of disease risk models, or use of fungicide application aids, which can be hardware or software. The introduction of a new tool for growers can also be included;
\r\n\tNovel fungicides - In addition to the traditional chemical approach, alternative materials (enzymes, oils, extracts, etc.), biological control agents, or plant defense activators can be discussed;
\r\n\tAdaptation of new technologies - Examples will be the use of unmanned vehicles, sensor technologies, advanced sprayers, or disease forecast systems for precision agriculture;
\r\n\tFungicide resistance - Unfortunately, we cannot ignore the fact that fungicide-resistant strains are widespread. Documentation of fungicide-resistant strains, the introduction of new technologies and methods can be discussed.
Diabetes mellitus (DM) is a group of metabolic diseases characterized with inappropriate hyperglycemia due to either a deficiency of insulin secretion or a combination of insulin resistance and inadequate insulin secretion (Masharani, 2008). Type 1 diabetes is caused by absolute deficiency of insulin secretion. Individuals at risk of developing this type of diabetes are found with serologic evidence of an autoimmune process occurring in the pancreatic islets and by genetic markers. In type 2 diabetes, it is a combination of resistance to insulin action and an inadequate compensatory insulin secretion response (American Diabetes Association, 2008). Diabetic nephropathy, one of the common complications of diabetes, has become the leading cause of end-stage renal failure in many countries (Chen et al., 2005). In general, about 1 out of 3 patients with type 1 or type 2 diabetes proceed to developing significant diabetic nephropathy (Zipp and Schelling, 2003). It is believed that the pathophysiologic mechanisms of renal disorder are similar in both types of diabetes (Kern et al., 1999). The pathogenesis and clinical course of diabetic nephropathy can be monitored by structural and hemodynamic changes. The earliest changes is an increase in glomerular filtration rate (GFR), also call “hyperfiltration” stage, which is followed by detectable glomerular lesions with normal albumin excretion rate. The next change is the development of microalbuminuria. Once microalbuminuria persist, both changes in glomerular structure, such as mesangial expansion and basement membrane thickening, and permeability happened, which is referred as “incipient nephropathy”. Diabetic subjects with persistent microalbuminuria are at increased risk for “overt diabetic nephropathy”. At this stage, prominent proteinuria, hypertension, and renal insufficiency progressed. The pathological findings in this stage are glomerular basement membrane (GBM) thickening, mesangial expansion and resulting in diffuse and/or nodular glomerulosclerosis, afferent and efferent arteriolar hyalinosis, and tubulointerstitial fibrosis (Cooper and Gilbert, 2003). After several years of persistent proteinuria, progression to end-stage renal disease will occur (Caramori and Mauer, 2001). Advanced diabetic glomerulopathy is commonly characterized by diffuse glomerulosclerosis and may sometimes exhibit a distinctive morphological appearance, namely, the nodular form of glomerulosclerosis, as first described by Kimmelstiel and Wilson in 1936 (Kimmelstiel and Wilson, 1936; Kern et al., 1999). The stages of diabetic nephropathy are shown in Table 1 (Vora and Ibrahim, 2003).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
1 | \n\t\t\tRenal hyperfiltration (GFR↑) Renal hypertrophy | \n\t\t
2 | \n\t\t\tSilent stage Renal hyperfiltration (GFR*↑); Normal UAER*, blood pressure Early histologic changes: non-specific increase in basement membrane thickness, increase mesangial matrix | \n\t\t
3 | \n\t\t\tMicroalbuminuria (UAER 30-300mg/24 h) or incipient nephropathy GFR may elevated or reduced into normal range. Histology: mesangial expansion, glomerular basement membrane thickening, arteriolar hyalinosis | \n\t\t
4 | \n\t\t\tEstablished or overt nephropathy (Proteinuria, nephrotic syndrome) GFR decline, Hypertension Histology: mesangial nodules (Kimmelstiel-Wilson lesions), tubulointerstitial fibrosis | \n\t\t
5 | \n\t\t\tESRD*** | \n\t\t
Natural course of diabetic nephropathy in type 1 diabetes
* GFR, glomerular filtration rate
**UAER, urine albumin excretion rate
***ESRD, end stage renal disease
The current strategies to treat diabetic nephropathy include intensive glycemic control, antihypertensive treatment with a particular focus on the interruption of renin-angiotensin-aldosterone system (RAS), restriction of dietary protein, and treatment of hyperlipidemia. There are several new approaches to the treatment of diabetic nephropathy based on an ever-growing mechanistic understanding of the causes of diabetic nephropathy by the specific pathogenic roles. These agents include pharmacologic inhibitors of advanced glycation end products (AGEs) formation, protein kinase C (PKC), oxidative stress, and transforming growth factor β (TGF-β) (Williams and Stanton, 2005).
Type 1 diabetes mellitus is typically an immune mediated destruction of the pancreatic
β cells. Type 2 diabetes mellitus is characterized by insulin resistance and insulin secretion impairment. Animal models have been used extensively in the field of diabetes study. The current available animal models of type 1 and type 2 diabetes are shown in Table 2 (Rees and Alcolado, 2005).
Type 1 | \n\t\t\tBB (Bio breeding) rat Chinese hamster Celebes black ape Keeshond dog LETL (Long Evans Tokushima lean) rat New Zeland white rabbit NOD (non-obese diabetic) mouse Streptozotocin-induced rats | \n\t\t
Type 2 | \n\t\t\tCBA/Ca mouse db/db mouse Diabetic Torri rat GK (GotoKakizaki) rat Israeli sand rat KK mouse New Zeland obese mouse NSY (Nagoya-Shibata-Yasuda) mouse Ob/Ob mouse OLETF (Otsuka Long-Evans Tokushima fatty) rat Zucker rat | \n\t\t
Animal models of type 1 and 2 diabetes mellitus
There are four major biochemical pathways considered to lead to the development of diabetic complications associated with hyperglycemia, (1) the polyol pathway, glucose is converted to sorbitol and then metabolized to fructose. Advanced glycation end products (AGE) and reactive oxygen species (ROS) formation also occurs via this pathway, (2) the hexosamine pathway, fructose-6-phosphate is converted to glucosamine intermediates and the production of ROS is subsequently increased, (3) the protein kinase C (PKC) pathway, glucose is converted to glyceraldehyde-3-phosphate and leads to the formation of diacylglycerol (DAG). The elevation of intracellular DAG levels activate PKC, and then activate NADPH oxidase to induce ROS, (4) the formation of advanced glycation end products (AGEs), interaction of AGEs with the receptors of advanced glycation end-products (RAGE) results in ROS activation (Stirban et al., 2008; Shah et al., 2009; Forbes et al., 2008; Brownlee, 2005; Kanwar et al., 2008; Singh et al., 2011).
Increased oxidative stress has been a widely accepted participant in the development and progression of diabetes and its complications (Maritim et al., 2003). ROS are activated in glomerular mesangial and tubular epithelial cells by high glucose, AGE, and cytokines (Park et al., 1999). Hyperglycemia activates the glycolytic pathway and excess generation of mitochondrial ROS initiates a vicious circle by activating several signaling to increase protein kinase C (PKC), and stimulating NADPH oxidase to induce ROS generation (Johansen et al., 2005). Free radicals has been found to be formed disproportionately increase in diabetic subjects by glucose oxidation, nonenzymaticglycation of proteins, and then oxidative degradation of glycated proteins. Excessively amount of free radicals induce damage to cellular proteins, membrane lipids, nucleic acids, and then cell death (Maritim et al., 2003). Besides, increased ROS can cause vascular endothelium abnormalities, reacting directly with nitric oxide (NO) to produce cytotoxic peroxynitrite and increasing reactivity to vasoconstrictors and modification of extracellular matrix proteins (Schnackenberg, 2002). ROS can also damage endothelial cells indirectly by stimulating expression of various genes involved in inflammatory pathway (Baldwin, 1996). Previous study finds that high glucose induces ROS and then up-regulates TGF-β1 and extracellular matrix (ECM) expression in the glomerular mesangial cell (Lee et al., 2003). There are also evidences that antioxidants can effectively inhibit high glucose induced TGF-β1 and fibronectin up-regulation (Ha et al., 1997). Ha et al. (2002) reported that ROS mediate high glucose-induced activation of NF-κB and NF-κB dependent monocyte chemoattractant protein (MCP)-1 expression. NF-κB, a nuclear transcription factor, can initiate the transcription of genes associated with inflammatory response. It is induced by various cell stress-associated stimuli including growth factors, vasoactive agents, cytokines, and oxidative stress (Kuhad and Chopra, 2009). Advanced glycation end products induced by hyperglycemia stimulate NF-κB activation, which sustains the activation of NF-κB in diabetes (Gao et al., 2006). Increased steady-state mRNA levels of inflammatory genes have been shown to associate with interstitial fibrosis and progressive human diabetic nephropathy (Kuhad and Chopra, 2009).
TGF-β plays an important role in the development of renal hypertrophy and accumulation of extracellular matrix (ECM) components in diabetes mellitus (Wolf and Ziyadeh, 1999). The expression of TGF-β was found increased in diabetic nephropathy of experimental animals and in humans (Park et al., 1997; Yamamoto et al., 1993; Sharma et al., 1997; Shankland et al., 1994). Treatment with anti-TGF-β antibody has been documented that it attenuated the effect of high glucose induced cellular hypertrophy
The relation between oxidative stress and diabetic nephropathy* *PKC, protein kinase C; AGE, advanced glycation end products; ROS, reactive oxygen species; NF-κB, nulcear factor-kappa B; AP-1,activator protein-1; TGF-β, transforming growth factor-beta; MCP-1, monocyte chemotactic protein-1
There are many evidences suggest that ROS play an important role in the pathogenesis of diabetic nephropathy (Rosen et al., 2001). To prevent the development and progression of diabetic nephropathy, it would be effective in combing the strategies to prevent overproduction of ROS and to increase the removal of preformed ROS. (Ha et al., 2008). Some natural products were proved to possess the ability to decelerate diabetic nephropathy via reducing oxidative status. The flower of
On the other hand, some evidences show the exogenous or endogenous antioxidants also can reduce diabetic nephropathy. Oxidative stress via nicotinamide adenine dinucleotide phosphate (NADPH) oxidase and vascular endothelial growth factor (VEGF) pathway are documented to play important roles in the development of diabetic nephropathy. Nam et al. (2009) showed the effects of apocynin, a NADPH oxidase inhibitor, on diabetic nephropathy. They found that apocynincan not significantly decrease serum glucose levels but reduce urinary protein and albumin excretions. It is improved in glomerular and mesangial expansion as the apocynin treatment. Apocynin also decreased glomerular VEGF expression and reduced the concentration of 24 h urinary 8-OHdG and MDA. Additionally, Lee et al. (2005) demonstrated that antioxidant taurine prevented glomerular hypertrophy, mesangial expansion, and proteinuria in diabetic rats. Overexpression of catalytic antioxidants was also shown to protect against diabetic injury in several transgenic animals. Craven et al. (2001) showed that diabetic mice transgenic for Cu/Zn SOD had significantly lower urinary albumin excretion, glomerular hypertrophy, and glomerular expression of TGF-β1 and collagen IV protein compared to non-transgenic mice. Hamada et al. (2007) demonstrated that overexpression a small antioxidant, thioredoxin 1, effectively inhibited 8-OHdG in the kidney, albuminuria, mesangial expansion, and tubular injury in diabetic mice. Du et al. (2003) found that overexpression of MnSOD in bovine aortic endothelial cells prevented high glucose-induced activation of PKC, NK-kB, hexosamine, and advanced glycation end product (AGE) pathways. Brezniceanu et al. (2007) demonstrated that renal catalase overexpression in db/db mice attenuated ROS generation, angiotensinogen, proapoptotic gene expression and apoptosis in the kidneys of diabetic mice
Although strict glycemic control is very important in DM patients, many of the current standard therapeutic approaches may also ameliorate oxidative stress as pleiotropic effects (Singh et al., 2011), such as angiotensin-2 converting enzyme (ACE) inhibitors(Kobayashi et al., 2006), angiotensin-2 receptor blockers (ARB) (Ogawa et al., 2006) and aldosterone blockers (spironolactone) (Takebayashi et al., 2006). They activate eNOS to increase bioavailability of nitric oxide, inhibit synthesis of angiotensin 2 and TGF-β and to decelerate or prevent tubulointerstitial fibrosis in diabetic nephropathy, accompanied with control of systemic and intrarenal blood pressure. Cilostazol is a specific inhibitor of phosphodiesterase 3 (PDE 3). Its major effects are prevention of platelet aggregation and dilation of blood vessels via an increase in tissue cAMP levels (Matsumoto et al., 2005). Cilostazol was shown to inhibit vascular smooth muscle cell proliferation
Inheritance has always played a central part in the quest for elucidating the origin of nature, life and mankind. Beyond the epic mythical assumptions, it also has been obvious for millennia that the evolutionary transfer of information plays a key role during the manipulation of inheritance by mating and breeding. Already in antique times many a "theory" was devoted to the apparent, as well as especially to the obvious fact that nature seemed to be composed of small, similar, and consistent subcomponents—so called atoms. With the description of the tissue of plants (including its substructures of vesicles and bubbles) by Robert Hooke or in the case of the cell nucleus by Anton van Leeuwenhook, in the 17th century new momentum entered the field. Nevertheless, it took until 1830 when Robert Brown defined the cell nucleus as such and until 1939 when Theodor Schwann established the cell as the fundamental unit of all plant and animal tissues while linking to the assumed fundamental design principle of life as well as nature in general. Despite fast growing microscopic resolutions there were huge challenges: not only staining and visualization methods were lacking, but also huge preparatory issues were faced especially concerning the "notorious" hard to stain cell nucleus. With the development of the natural sciences many a discovery was made culminating in the structural description of the DNA double helix [1] and the discovery of the nucleosome [2, 3, 4] at the atomic level, full genome sequences and finally histone modifications defining epigenetic landscapes. It also became obvious that the structure and function of genomes co-evolved as an inseparable system allowing the physical storage, replication, and expression of genetic information [5, 6, 7].
\nHowever, the immense size and structural complexity of genomes spanning many orders of magnitude has always imposed huge experimental challenges. Thus, the higher-order architecture has been and still is widely discussed with many interesting details yet to be described. Already how nucleosomes are spaced, positioned, remodelled, and whether and how nucleosome chains fold into fibres at physiological salt concentrations have been matters of continuing debate: e.g. Finch and Klug [8] proposed a relatively regular solenoid and
The higher-order chromatin architecture has been a matter of even greater debate: Pioneering light microscopy studies by Rabl [28] and Boveri [29] hinted towards a hierarchical self-similar, territorial organization. Electron microscopy suggested a more random interphase organization as in the models of Comings [30, 31] or Vogel and Schroeder [32]. In the radial-loop-scaffold model of Paulson and Laemmli [33] ~60 kbp-sized chromatin loops attached to a nuclear matrix/scaffold explained the condensation degree of metaphase chromosomes. According to Pienta and Coffey [34], these loops persisted in interphase and formed stacked rosettes in metaphase. Micro-irradiation studies by C. Cremer and T. Cremer [35, 36] and fluorescence
To further distinguish between the different architecture proposals, proximity crosslinking techniques (developed and used already in the last century) were further developed into a family of interaction capture techniques such as 3C [56, 57], 3C-qPCR [58], 4C [59], 3C-seq/4C-seq [60], 5C [61], and Hi-C [62]. They once more confirmed the existence of looping and subchromosomal domains, now inconsistenly referred to as topologically associated domains (TAD; [63]) with a somewhat higher localization accuracy when compared to FISH. These approaches also led to a number of - although by the underlying (raw) data basically unsupported - conjectures (Imam et al., in preparation), e.g. the fractal globule model [62], the loop array architecture of mitotic chromosomes [64], and the highly dynamic loop formation based on single-cell experiments [65] or in a genome wide assay [66]. In contrast, with the introduction of targeted chromatin capture
Heuristically, it is very instructive how the central part of the 3D genome architecture and dynamics could now be determined by us in detail, and how out of this process immediately an also evolutionary consistent model (Figure 1) arises in agreement with the entire history and heuristics of the field. This has been achieved by a highly integrated systems approach linking holistically: i) a novel high-quality selective high-throughput high-resolution chromosome interaction capture (T2C) technique [25, 26, 67, 68, 69] (elucidating the structure with unprecedented resolution of some base pairs), ii) a novel
Overview on the size and time scaling of genome organization: The scaling and the levels of organization range over 9, 12, and 14 orders of magnitude! Initially base pairs are formed composing the DNA double helix (image see [
To finally determine and structurally sequence with highest resolution, signal-to-noise ratio, interaction frequency range, and statistical significance the 3D genome architecture we developed targeted chromatin capture (T2C) - a chromatin interaction technique though with far-better quality specifically addressing the needs for genome architectural "sequencing" [25, 2667, 68, 69]. Briefly: i) after chromatin crosslinking, ii) cell permeabilization for intra-nuclear enzymatic DNA restriction, iii) the extracted and largely diluted cross-linked DNA is re-ligated primarily within the crosslinked complexes. After iv) de-crosslinking, purification, and final shortening to <500 bp of the chimeric DNA ligates, v) a purified region-specific DNA interaction fragment library is selected by using DNA capture arrays, before finally vi) high-throughput sequencing, mapping to the reference genome, interaction partner determination and visual/quantitative analysis is conducted (Figure 2). Notably, we use only uniquely mapped sequences without applying any other corrections bearing information loss due to the very nature of T2C. This specific setup is not only far superior due to its improvement of 3 to 4 orders of magnitude compared to other interaction approaches (see Introduction), but also allows nearly unlimited opportunities e.g. such as multiplexing for complex research and diagnostics.
\nSimulated chromosome models [
Most importantly, however, T2C allows reaching fundamental resolution limits where "genomic" statistical mechanics and uncertainty principles apply [26]: With fragment length and thus resolutions of a couple of base pairs, a high interaction frequency range, and high signal-to-noise ratio, not only molecular resolution is reached and thus the fundamental limits of cross-linking techniques, but also the mechanism of observation is now on the same scale as the observables (in analogy to classic and quantum mechanics). Actually due to the stochastics following the bias of the system behaviour, the observables, the observation, and thus the measured values are constrained by what we call “genomic” statistical mechanics with corresponding uncertainty principles. This originates from the individual complexity of each highly resolved interaction with a unique but coupled individual probabilistic fragment setting in each cell at a given time. Hence, the actual conditions and components can be determined only partially with high accuracy while with low accuracy otherwise and are eventually even entirely destroyed by the measurement. Thus, the central limit theorem applies with an overlap of system inherent and real noise stochastics, and hence in the end only probabilistic analyses and statements can be drawn as hitherto is well known from classical mechanics, and more so from quantum (mesoscopic) systems. Consequently, population based or multiple single-cell experiments have to be interpreted and understood in a “genome” statistical mechanics manner with uncertainty principles due to the inseparability of factors/parameters also seen there. Thus, in practical terms, valid results are obtained when the statistical limit is reached, i.e. when scaling up the experiment does not narrow down the distribution any further and does not lead to fundamental (overall) changes anymore in observables. Nevertheless, if the statistical limit is reached and if the quality parameters like resolution, frequency range, and signal-to-noise ratio are sound, conclusions could be drawn as in the many cases of classic mechanics, and more so of quantum (mesoscopic) systems.
\nConsequently, due to this sensitivity of T2C, we [26] were able to determine finally the missing parts of the 3D architecture on scales where a "genomic" statistical mechanics applies with stable reproducibility as one can already see visually in colour coded interaction maps (Figure 2): Not only are rare interactions stably detected within an unprecedented frequency range spanning 5-6 orders of magnitude, but also the maps are reproducibly mostly empty (<10% of possible signals are taken). Both interactions and non-interactions show clearly dedicated interaction patterns on all spatial scales within and between domains, including their re-emergence as attenuated repetition on other scales since obviously genomes are scale-bridging systems [22, 23]—all of which can be immediately identified as structural features - briefly (Figure 2):
On the largest genomic and thus spatial scale, subchromosomal domains are visible as square-like interaction domains (often unfortunately called TADs; [63]) featuring in general a higher average uniform interaction degree compared to interactions between domains, with a sharp drop at the edge of domains, as well as a clear linker region between the domains that connects them. The borders of the domains can be determined down to the single fragment level and thus a very high resolution (see below). The interaction of domains with each other and a closer inspection of the interactions in the vicinity of the linker interacting often more frequently compared to other domain parts are mainly due to the breaking of spatial isotropy.
At intermediate scales within the subchromosomal domains, the interaction pattern shows clearly distinct gaps and a quantifiable grid-like arrangement of interactions, which also continues outside and “crosses” with the linear pattern originating from sequentially subsequent domain(s). These interactions on scales of tens of kilo base pairs are doubt-free originating from stable chromatin loops, forming a stable loop aggregate/rosette like architecture, due to several consecutive loops coinciding.
On the smallest scale, a dense and high interaction frequency pattern is observed in the region from 3 to 10 kbp (i.e. < ~5-15, and ~50 nucleosomes, respectively) along the diagonal. It varies independently of the local fragment size with distinct interactions and non-interacting “gaps”. This suggests, that there are defined stable interactions on the nucleosome scale forming an irregular yet locally defined and compacted structure, i.e. a quasi-fibre with average properties (e.g. an average linear mass density).
A detailed quantification [26, 27] of several regions leads to a quasi-fibre compaction of 5 ± 1 nucleosomes per 11 nm, with an average chromatin quasi-fibre persistence length of ~80 to 120 nm, loops and linkers of ~30 to 100 kbp, forming multi-loop aggregates/rosettes with typically 300 kbp to 1.5 Mbp subchromosomal domain sizes. Different cell types, species, or functional conditions showed only a relatively small variation of this theme [26, 27].
\nAll this is consistent with a variety of previous observations and predictions such as compacted fibre structures described throughout the literature (see e.g. [16, 17]), the internal structure of subchromosomal domains [7, 21, 22, 24, 38, 39, 40, 43, 49, 50] agreeing on all structural levels with the absolute nucleosome concentration distributions [18, 19], the dynamic and functional properties such as the architectural stability and movement of chromosomes [7, 22, 54, 71, 72], chromatin dynamics [73], as well as the diffusion of molecules inside nuclei (e.g. [22, 54, 72]), and recent genome wide
To investigate the 3D genome architecture and dynamics also by an orthogonal genome wide and
To better understand the 3D genome organisation suggested e.g. by the above results, to evaluate hypotheses, and to plan future experiments, we were the first who have - since 1996 - developed polymer models with pre-set conditions for
Determination of the 3D architecture in the IGF/H19 11p 15.5-15.4 region by T2C interaction mapping and computer simulations: Interaction matrices (logarithmic and colour coded scale; left & right) in HB2 and HEK293T TEV cells [
Insight into the spatial and dynamic/diffusional properties and morphology of the 3D organization of entire nuclei: The detailed view from the outside into a simulation for an MLS model with 126 kbp loops and linkers [
Simulations (Figure 2) of the Random-Walk/Giant-Loop model in which large individual loops (0.5–5.0 Mbp) are connected by a linker resembling a flexible backbone, as well as the Multi-Loop Subcompartment (MLS) model with rosette-like aggregates (0.5–2 Mbp) with smaller loops (60–250 kbp) connected by linkers (60–250 kbp), have already predicted that only an MLS model, i.e. a compacted quasi-fibre forming stable loops and stable loop aggregates/rosettes connected by a linker, can properly explain the formation of chromosome arms and territories [22], the spatial distances measured both using fluorescence
With the unprecedented quality of both the interaction mapping by T2C and the FCS dynamic measurements (see above) the introduction of simulation and analytical models complex enough to approximate the 3D genome organization adequately showed even more clearly that only a quasi-fibre, stable loop, stable loop aggregate/rosette-like architecture is compatible with the measurements: In essence the simulations and analytical models describe even the slightest details of the T2C and FCS measurements correctly including many at first sight paradoxical results as e.g. i) that high numbers of especially small loops in a rosette result due the high density in steric exclusion and thus stretched loops eventually even “shielding” inner-rosette parts, ii) that inter-domain interactions are influenced by the connecting linker, loop size and numbers, and how non-equilibrium effects would appear, as well as iii) the isotropy breaking of consecutive subchromosomal domains as seen in the interactions at the border of domains and the domain-domain interactions. On a more general level the simulations support also the large and at first sight remarkable emptiness of interaction matrices and its link to the existence of a dedicated chromatin quasi-fibre. Additionally, the simulations hint to a relatively low crosslink probability, radius, and frequency in experiments comparing the clearly visible fine-structure (such as the (anti-)parallel neighbouring of the chromatin quasi-fibre at loop bases [26]. Also both the simulation and analytical approach describe in detail every aspect of the experimentally found multi-scaling behaviour with a fine-structure not only of the architecture and dynamics, but also of the DNA sequence (see below) to a degree of detail even we are still astonished about. The stability of the architecture with respect to the intrinsic chromatin fibre dynamics can also be illustrated by e.g. the decondensation from a mitotic chromosome into interphase (Movie 1 [26]) or just in a normal interphase state (Movie 2 [26]). This also shows that any 3D architecture would dissolve within seconds if it would not be stabilised. Consequently, both theoretic approaches came with old and new data consistently to the same conclusion whatever orthogonal high-quality method is used and thus are a theoretical framework for the understanding, test, and engineering of genomes.
\nSince what is near in physical space should also be near (i.e. in terms of similarity) in DNA sequence space and this presumably genome-wide [22, 23, 24, 55], and because evolutionary surviving mutations of all sorts will be biased by the genome architecture itself and vice versa, the correlation and thus scaling behaviour of the DNA sequence [22, 23, 24, 26, 55] and its connection to the 3D genome architecture scaling - either from T2C interaction mapping [26] or from simulations [21, 22, 23] - allows for comprehensive investigation of genome organization in a unified scale-bridging manner from a few to the mega base pair level. Using to this end, the perhaps simplest correlation analysis possible (to avoid information loss or biases), we calculated the mean square deviation of the base pair composition (purines/pyrimidines) within windows of different sizes and calculating the function
The above described holistic combination of several new orthogonal approaches [26, 27] including the heuristics of the field leads interestingly undoubtedly to a consistent picture of genome architecture, dynamics, and in general organization, by establishing that nucleosomes compact into a quasi-fibre folded into stable loops, forming stable multi-loop aggregates/rosettes connected by linkers creating chromosome arms and entire chromosomes. Nevertheless, the heuristics of the field immediately questions whether i) we really now have an evolutionary consistent picture of genome organization, ii) whether this is the unavoidable outcome of Darwinian natural selection and Lamarkian self-referenced manipulation (what we introduce here), and iii) finally whether we can understand now genome organization in its systems context within cells, organs, and the entire organism? This in essence already relates back to the fundamental question of how life emerged from the primordial soup [5, 6, 22]; see details in following sections) but in the context discussed here can be addressed by first reflecting on the existing major functions of genomes, thus setting the stage: i) genomes need to stably store genetic information, ii) the information needs to be differentially read out to give rise to and regulate the molecular machinery, and iii) genomes need to replicate and mutate to spread and evolve:
Obviously the by far most important function is to stably store over long periods of time genetic information though with enough flexibility including mutations - or in short: without proper storage neither information retrieval, nor replication, nor evolutionary development exist. This involves obviously being resistant against physical/chemical and/or in- or external mechanical destruction. Whereas, the first act mainly as from the bottom up involving one or a group of chemical bonds in proximity by direct interactions in the molecular soup, the latter depends on the large-scale structure of the basic molecular components and thus acts indirectly top-down on chemical bonds, i.e. that in- or external global stress is transferred and eventually accumulated via the global structure down to molecular levels while leading to mechanical failure. Both this physico-chemical and structural conformation-based destruction paradigms, influence genome architecture on all its levels under evolutionary pressure. They can be formulated such that a) mechanical failure rates are minimized regarding very long time spans, and b) in- or external mechanical failure rates reach an optimum due to the right balance between internal stability increasing with scale (for sensible ranges) and external stress decreasing the stability with increasing scale. From the well known average DNA breaking length of ~300–500 bp after already relatively severe sonication, this translates right away to the nucleosome and chromatin quasi-fibre level assuming that internal nucleosomal attachment increases the stability and elongating it by a factor 146 bp to 200 bp (repeat length), i.e. the average breakage length of an uncompacted chromatin fibre is 44 kbp or in the extreme 100 kbp balancing the quasi-fibre internal stability increase by further compaction counteracted by the bigger mechanical susceptibility due to local compaction clusters. Thus, the found loops size of 30-100 kbp as well as its chromatin quasi-fibre persistence length of 80-120 nm is just what one would theoretically expect as the evolutionary outcome. The same holds for the formation of stable multi-loop aggregates/rosettes where the major player is internal stability, which is a function of quasi-fibre compaction, loops sizes, and loop numbers [51, 52], giving rise to the natural found size distribution between ~0.3-1.5 Mbp [21, 22, 23, 24, 26, 27, 40, 41, 42]. Also on the entire chromosome level again in- and external stability criteria have reached an optimum during evolution concerning the number of subchromosomal domains as well as their total size and number within a genome which again would just fit what one would theoretically expect: subchromosomal domain linkers are in the ballpark of loop sizes, the number of subchromosomal domains is <200-300 which just is the optimum size where mechanical stress does not too much destruct mitotic chromosomes under normal conditions. Consequently, the stability criteria are clearly satisfied while obviously still allowing enough flexibility by variation of this theme within the relatively broad boundary limits and various levels compensating individual stretching of limits (e.g. bigger loops might be stabilised by higher quasi-fibre compaction). Beyond, destruction of a complete structural element (e.g. nucleosome, loop) in relation to the characteristic scale seems never really to exceed 1-5% - an important criterion for overall system resilience.
Access to and obstruction of genetic information, i.e. genetic information retrieval in a regulated fashion is, of course, next to pure storage the major task for a genome, although without a stable information storage retrieval gets arbitrarily complicated whether replication takes place or not. Since the information is readout with similar means as the storage itself, i.e. in a molecular way in contrast e.g. to an optical readout, this relies in principle on two major conditions: a) the physical space for the regulation of the 3D architecture needed that a readout takes place, and b) accessibility/obstruction to the genetic information for the readout-machinery as well as post-processing and transport of the transcribed information. For the first the DNA, nucleosomes, chromatin quasi-fibre, loops and loop aggregates/rosettes, need to have the space to be modified and get rearranged, i.e. that a volume several times bigger than the actual structure exists for ease of change. This involves, naturally a certain compaction, since a homogenous soup would not allow this. Since the regulation and readout is done by molecular mechanisms, it is also obvious that a low spatial occupancy allows moderately obstructed diffusional access of both the regulation and readout machinery only for DNA with a certain compaction degree. For such a scenario the volume occupancy of the architecture in aqueous solution should be well (!) below the limit of ~50% (model depending) as known from percolation studies [74], i.e. in terms of the performance expected for genomes, volume occupancy should be <10% since both the genomic architecture as well as the machinery should be able to access it for regulation by modification as well as readout. For chromatin, experimental values are between 2.5% to ~8% with a homogenous mesh spacing ranging from 115 to 65 nm ([22] and literature cited therein). Together with other factors and molecules in the cell nucleus like proteins and RNA, which all have a similar density, the volume occupancy is still <25%. These percolation assumptions hold, of course, also for the dynamics of the structure itself as pointed out above. At first sight this seems to be a dense system but the architecture is moving constantly by Brownian motion like in a spaghetti soup with additional floating components [18, 19, 20, 22, 27, 53, 54]. For chemical reactions this is well known for diffusion limited aggregation processes [75] as well as for percolating systems [75]. Due to the described consistent multi-layered 3D organizations showing also a multi-scaling of its volume occupancy as well as the space in-between this creates now even more and especially a scale dependent accessibility and obstruction to enhance the theoretic predictions of homogeneous though compacted systems with percolating space. Thus, under such conditions the necessary machinery for transcription as well as transcript transport is based mainly on moderately obstructed diffusion and despite of its high overall concentrations acts as an adequate multi-scale space [22, 53]. Consequently, similar to diffusion limited (catalytic) processes modification of the intrinsic architecture and dynamics of the entire genome organization is used for locally or globally fine-tuning of processes and thus functional regulation. Concerning, the stability of the 3D architecture only a quasi-fibre with stable loop aggregates/rosettes allows in terms of stability and flexibility local containment of large-scale interactions during the initiation of transcription e.g. by enhancer promoter interactions. For knot-free replication of the genome these (spatial) arguments also apply: whereas accessibility allows access of the machinery and space for the duplication, spatial obstruction protects the structural integrity. Interestingly, none of the described alternative architectures and dynamics hypothesis (see Introduction) agree to even a sufficient degree with these fundamental necessities to guaranty genome function.
Replication and extinction of genetic information is the most crucial intervention into genome organization, since in contrast to the readout and regulation of genetic information by transcription, the entire structure and dynamics are affected by copying every single component of the organization. Here, an exact copy within a constrained space not only sequence wise, but also of its 3D architecture and dynamics as well as its disentanglement are the crucial parameters while still allowing structural stability/flexibility and even the access/obstruction of genetic information. From protein folding it is well known, that already during the amino-acid chain synthesis in the ribosome folding takes place, leading to a different 3D folding compared to the relaxation of finished and stretched out amino-acid chains. Obviously, also chromosome replication is such an adiabatic process (also chromosomes never fold from scratch, i.e.
In summary, the above proves even further and especially in a holistic combination with the presented new orthogonal approaches [26, 27] and including the heuristics of the field, that indeed the described 3D genome organization - DNA forming nucleosomes compacted into a quasi-fibre folded into stable loops, forming stable multi-loop aggregates/rosettes connected by linkers creating chromosome arms and entire chromosomes (Figure 1) - presents without doubt a consistent scale bridging systems statistical mechanics genomics fulfilling the functional conditions necessary for storage, transcription, and replication. Additionally, the actual values found for the various parameters involved are just found in those "regions" one would expect as the unavoidable outcome of Darwinian natural selection and Lamarkian self-referenced manipulation (see below).
\nThe heuristics leading to the here described consistent 3D genome organization has also resulted in another fundamental breakthrough besides merely clarifying the missing gap(s): the emergence of a multilistic systems statistical mechanics with uncertainty principles by reaching the fundamental resolution limits (see Section 2.1 above; [26]. Hence, this allows directly not only i) to extend the atomic theory based on ancient Greek philosophy and the notion of Theodor Schwann of cells being the fundamental atomic unit of tissues to the mesoscopic scale of genome architecture/dynamics, but also ii) to analyse and to describe how from the collective behaviour of these elements a holistic meta level, i.e. a phenotype, emerges. Thus, by reaching fundamental resolution limits now the statistical and uncertainty properties of each architectural/dynamic level can be determined both by experimental measurements as well as theoretical descriptions. Hence, from each of these "atomistic" basic units/elements their collective behaviour can be derived by a statistical mechanics on each individual level as wells as a complex interwoven scale-bridging, i.e. a hierarchic back referencing networked systems statistical mechanics - which obviously exists - can now be established in detail. This exceeds and is much more complex than establishing the statistical mechanics at the turn of the 20th century where from the individual components e.g. gas molecules a statistical mechanics established the collective properties of the entire system, e.g. the entire gas, because genome organization is not only a simple dualistic system of e.g. two levels but a complex multilistic network system with back references: In detail this means determining experimentally the behaviour of a genome structural/dynamic level precisely with its entire statistics and then doing the same on the level emerging from the underlying level. In principle this is what we have started already by setting up an experimental and theoretic framework over the past 20 years to elucidate genome organization [7, 18, 19, 20, 21, 22, 23, 24, 26, 27, 49, 50], although only now with the complete description of the general 3D genome architecture/dynamics it is possible to fill the existing lack of knowledge in detail, determine the values for parameters with high precision, and in constant cycles of refinement adjust the description to an ever higher degree of approximation. Thus, the difference to the development of statistical mechanics in classical and later quantum physics at the turn to the 20th century is that in biology many and also much higher levels still are determined by and also act back even on the very first level to a much higher degree. This also immediately unites the at first sight contradicting theoretic descriptions of living systems of Ilia Prigogine [75], stating that living systems are far away from thermodynamic equilibrium, with those proposed by Georgi Gladyshev [76] stating that hierarchic substance stability is locally in thermodynamic equilibrium. Actually, these descriptions are even extended due to the multilistic statistical systems mechanics, i.e. manifold recursive hierarchically back-referencing, which are until now not described but e.g. envisioned in efforts to extend quantum mechanics to higher order complexities [77]. Consequently, a genomic multilistic statistical systems mechanics allows not only to describe and test basic properties of life, but also to answer perhaps the most fundamental questions of life as e.g. whether life time-wise can be extended beyond the currently obvious or thought of limits by manipulated engineering in one of its most central parts - the genome - a quest of epic dimensions appearing already at least between the lines in "What Is Life ?" by Erwin Schrödinger [78].
\nThe most important implication from the findings described above is most likely the multilistic entanglement between genotype and phenotype being the natural outcome of Darwinian natural selection and Lamarkian self-referenced manipulation in a genome ecology framework, which is connected directly to the origin of genomes and life itself: While entropy grows like an inexorable river, local disturbances lead to ever more ordered self-organizing and self-sustaining resistors, more complex structures, and finally life. In the 1970s Manfred Eigen [5, 6] showed how from the primordial soup autocatalytic chemical reaction-networks emerged and how they form ever more complex cooperatively organized networks and systems of so called hypercycles. With environmental separation by the emergence of units as cells and specialization of subunits, then genomes have developed as specialized keepers of the blueprint needed to maintain, regulate, and develop this syntropic machinery. Since genetic information is physically stored in molecular structures with dedicated architecture and dynamics, it is thus also obvious that the material carrier for the storage, usage, and replication of genetic information co-evolved inseparably. Yet another inevitable consequence of our results leading to the consistent statistical systems genome mechanic framework is indeed our proof [26, 27] that architecture, dynamics, and DNA sequence are co-evolutionary unseparably entangled (in a quantum mechanical sense): All architecture/dynamics levels have not only left a footprint on the DNA sequence level but beyond also all levels have left a footprint on all other levels with an astonishing degree of detail (see Section 2.4). Consequently, the co-evolution of all levels has also co-evolved not only to a higher degree than previously thought, but also indeed as an entire system where all levels are (equally ?) determinant (Figure 5).
\nGenome ecology emerging from the system mechanics of genomes in relation to the genotype-phenotype entanglement and its embedding in- and environment: Genomes are interwoven holistic multi-scale hierarchic systems entities in which all organizational levels are also manifest, i.e. fingerprinting, on all other levels. Thus, immediately each level is a phenotype of its underlying genotype immediately conditioning back on it recursively. Thus, both genotype and phenotype are entangled inseparably in a (due to the involvement and entanglement of all levels) multilistic manner. In consequence this not only unites Darwinian and Lamarckian evolutionary paradigms, but also embeds and relates genomes with their in- and environment, and thus giving rise to a general genome ecology.
In evolutionary terminology the genotype (i.e. the double helix) creates a phenotype (the nucleosome) and this phenotype recursively conditions the genotype (i.e. again the double helix). The nucleosome is also a genotype conditioning the quasi-fibre phenotype, recursively conditioning the nucleosome and DNA, etc. Since this is happening with all levels simultaneously this inseparable dualism extends in the present genome organisation to a multilism, shaping evolutionary development in hierarchical terms from bottom to top by Darwinian natural selection as well as from top to bottom by Lamarkian self-referenced manipulation. Thus, our finding that indeed all genome architecture/dynamic levels are tightly entangled with each other also immediately resolves the falsely assumed paradoxes between Darwinian and Lamarckian evolution by uniting them at least on the genome level. This is remarkable not only in historic terms considering the even politically and religiously extremely hot debates/fights about "man evolving from apes" as well as the "intentionally planed long neck of giraffes", but also heuristically, since the in principle relatively simple final completion of the 3D genome architecture/dynamics at the limit of the resolution leads not only to a consistent 3D genome organization and statistical systems genome mechanics, but beyond reveals in one go some and perhaps the most important fundamentals of life (Figure 5).
\nBeyond, this strong entanglement over several orders of magnitude (Figures 1, 2) within the genome, the described genotype-phenotype-entanglement can be driven conceptually even further considering the influence of both the a) hierarchically constituting elements giving rise to the system, i.e. chemical molecular base, atomic, and subatomic units, which will be called here i(!)nvironment, and b) the hierarchical higher levels, i.e. tissues, organs, animal etc., which are the environment. Although this may seem far fetched, but influences from both "directions" are well known (see e.g. Section 3), although due to their complexity this is often hard to track down in a reductionistic manner, thus hence their degree of influence is just emerging. In this respect the found entanglements bridging so many multi-scale levels and orders of magnitude in space and time, are on the one hand already astonishing in terms of the obviously wrong assumption that such influences would die-off very fast, while on the other hand this has general implications for all hierarchic systems showing that complex inter-, cross-, and even multi-cross-level influences are much more frequent and far reaching. Actually, the here shown multilistic genotype-phenotype entanglement shows a highly interwoven, networked, and recursive structure: instead of more or less separate hierarchic layers where only first or at the most secondary neighbour layers are connected, there are also influential connections to more distant layers at least locally if not in every part of the layer space. Thus, the genotype-phenotype entanglement embedded within an i(!)n- and environment actually results in a genome ecology in direct analogy to e.g. human ecology, autopoieses of social systems, or just any kind of systems theoretic entity [77, 78, 79, 80, 81, 82].
\nNature has created ever more complex forms of life by creating structural and dynamical islands of systems with specialized organelles such as genomes being responsible for storage, access, and replication of the information for their persistence and development. Despite the epic quest to determine the details and origin of inheritance, only recently we were finally able to fill the debated gaps of the central part of genome architecture and dynamics - despite the pioneering works of the last 170 years - by establishing that nucleosomes compact into a quasi-fibre which is folded into stable loops, forming stable multi-loop aggregates/rosettes connected by linkers creating chromosome arms and entire chromosomes [26, 27]. Although the heuristics of the field leads already to a sound basis, this could only be achieved - as we summarized here - by a highly integrated systems approach linking holistically i) a by far superior selective chromosome interaction (T2C) technique, ii) a novel
For supporting and influencing this long lasting work of T.A.K thanks go to: M. Wachsmuth, T. Weidemann, K. Fejes-Toth, M. Göker, R. Lohner, M. Stör, E. Spiess, K. Rippe, W. Waldeck, C. Cremer, T. Cremer, K. Erenpreisa, A. Ollins, D. Ollins, K. Sullivan, C. C. Murre, J. Skok, A. M. A. Imam, F. G. Grosveld, K. Egger, O. Zimina, and last but not least L. A. Knoch, as well as the German and International Societies for Human Ecology. T2C was invented by T.A.K. and F. G. Grosveld, with many thanks to M. Lesnussa, N. Kepper, A. Abuseiris, P. Kolovos, Jessica Zuin, R. W. W. Brouwer, H. J. G. van de Werken, W. F. J. van IJken, and Kerstin S. Wendt. This work was also part of the EpiGenSys consortium setup and coordinated by T.A.K., funded by ERASysBio+/FP7 and the national funding organizations (the Dutch Ministry for Science and Education, the Netherlands Science Organization, the UK Biotechnology and Biological Sciences Research Council, and the Bundesministerium für Bildung und Forschung (BMBF)). Further support came from the BMBF under grants # 01 KW 9602/2 (Heidelberg 3D Human Genome Study Group, German Human Genome Project), #01AK803A (German MediGRID), #01IG07015G (Services@MediGRID), as well as the Erasmus Medical Centre and the Hogeschool Rotterdam. The High-Performance Computing Center Stuttgart (HLRS; grant HumNuc), the Supercomputing Center Karlsruhe (SCC; grant ChromDyn), and the Computing Facility of the German Cancer Research Center (DKFZ) are thanked for access to their CRAY T3E and IBM SP2s in the initial part of this work. Thanks also go to all those institutions, universities, and companies providing us computational grid resources: the German D-Grid, the European Grid Initiative EGEE, as well as the Erasmus Computing Grid the Almere Grid, and all the unnamed computing grids there is access through via these. Very special thanks go also to all the world-wide distributed and unnamed donors of desktop computer power of our world-wide Correlizer@home BOINC grid!
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Integrity - We are consistent and dependable, always striving for precision and accuracy in the true spirit of science.
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\n\nIntechOpen is a dynamic, vibrant company, where exceptional people are achieving great things. We offer a creative, dedicated, committed, and passionate environment but never lose sight of the fact that science and discovery is exciting and rewarding. We constantly strive to ensure that members of our community can work, travel, meet world-renowned researchers and grow their own career and develop their own experiences.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. 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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Only bioactive glass possesses osteogenic property that stimulates proliferation and differentiation of osteoprogenitor cells and in some cases influencing the fibroblastic properties. But, this material has also some disadvantages such as short-term and low mechanical strength along with decreased fracture resistance; but, this was further minimised by ion doping that positively enhanced new bone formation. There are many metal ions such as magnesium (Mg), strontium (Sr), manganese (Mn), iron (Fe), zinc (Zn), silver (Ag) and some rare earths that have been doped successfully into bioactive glass to enhance their mechanical and biological properties. In some of the cases, mesoporous bioactive glass materials with or without such doping have also been employed (with homogeneous distribution of pores in the size ranging between 2 and 50 nm). These biomaterials can be served as scaffold for bone regeneration with adequate mechanical properties to restore bone defects and facilitate healing process by regeneration of soft tissues as well. This chapter encompasses the use of bioactive glass in bulk and mesoporous form with doped therapeutic ions, their role in bone tissue regeneration, use as delivery of growth factors as well as coating material for orthopaedic implants.",book:{id:"5164",slug:"advanced-techniques-in-bone-regeneration",title:"Advanced Techniques in Bone Regeneration",fullTitle:"Advanced Techniques in Bone Regeneration"},signatures:"Samit Kumar Nandi, Arnab Mahato, Biswanath Kundu and Prasenjit\nMukherjee",authors:[{id:"60514",title:"Dr.",name:"Samit",middleName:null,surname:"Nandi",slug:"samit-nandi",fullName:"Samit Nandi"}]},{id:"37120",doi:"10.5772/29607",title:"Trigeminocardiac Reflex in Neurosurgery - Current Knowledge and Prospects",slug:"the-trigeminocardiac-reflex-in-neurosurgery-current-knowledge-and-prospects",totalDownloads:3423,totalCrossrefCites:10,totalDimensionsCites:27,abstract:null,book:{id:"749",slug:"explicative-cases-of-controversial-issues-in-neurosurgery",title:"Explicative Cases of Controversial Issues in Neurosurgery",fullTitle:"Explicative Cases of Controversial Issues in Neurosurgery"},signatures:"Amr Abdulazim, Martin N. 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Liposuction is a procedure to improve the body contour and not a surgery to reduce weight, although recently people who have failed in their plans to lose weight look at liposuction as a means to contour their body figure. Tumescent liposuction of large volumes requires a meticulous selection of each patient; their preoperative evaluation and perioperative management are essential to obtain the expected results. The various techniques of general anesthesia are the most recommended and should be monitored in the usual way, as well as monitoring the total doses of infiltrated local anesthetics to avoid systemic toxicity. The management of intravenous fluids is controversial, but the current trend is the restricted use of hydrosaline solutions. The most feared complications are deep vein thrombosis, pulmonary thromboembolism, fat embolism, lung edema, hypothermia, infections and even death. The adherence to the management guidelines and prophylaxis of venous thrombosis/thromboembolism is mandatory.",book:{id:"6221",slug:"anesthesia-topics-for-plastic-and-reconstructive-surgery",title:"Anesthesia Topics for Plastic and Reconstructive Surgery",fullTitle:"Anesthesia Topics for Plastic and Reconstructive Surgery"},signatures:"Sergio Granados-Tinajero, Carlos Buenrostro-Vásquez, Cecilia\nCárdenas-Maytorena and Marcela Contreras-López",authors:[{id:"273532",title:"Dr.",name:"Sergio Octavio",middleName:null,surname:"Granados Tinajero",slug:"sergio-octavio-granados-tinajero",fullName:"Sergio Octavio Granados Tinajero"}]},{id:"42855",title:"Critical Care Issues After Major Hepatic Surgery",slug:"critical-care-issues-after-major-hepatic-surgery",totalDownloads:8909,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"3164",slug:"hepatic-surgery",title:"Hepatic Surgery",fullTitle:"Hepatic Surgery"},signatures:"Ashok Thorat and Wei-Chen Lee",authors:[{id:"52360",title:"Prof.",name:"Wei-Chen",middleName:null,surname:"Lee",slug:"wei-chen-lee",fullName:"Wei-Chen Lee"},{id:"157213",title:"Dr.",name:"Ashok",middleName:null,surname:"Thorat",slug:"ashok-thorat",fullName:"Ashok Thorat"}]},{id:"72175",title:"Fontan Operation: A Comprehensive Review",slug:"fontan-operation-a-comprehensive-review",totalDownloads:1252,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Since the first description of the Fontan operation in the early 1970s, a number of modifications have been introduced and currently staged, total cavopulmonary connection with fenestration has become the most commonly used multistage surgery in diverting the vena caval blood flow into the lungs. The existing ventricle, whether it is left or right, is utilized to supply systemic circuit. During Stage I, palliative surgery is performed, usually at presentation in the neonatal period/early infancy, on the basis of pathophysiology of the cardiac defect. During Stage II, a bidirectional Glenn procedure is undertaken in which the superior vena caval flow is diverted into the lungs at an approximate age of 6 months. During Stage IIIA, the blood flow from the inferior vena cava (IVC) is rerouted into the pulmonary arteries, typically by an extra-cardiac conduit along with a fenestration, generally around 2 years of age. During Stage IIIB, the fenestration is closed by transcatheter methodology 6–12 months after Stage IIIA. The evolution of Fontan concepts, the indications for Fontan surgery, and the results of old and current types of Fontan operation form the focus of this review.",book:{id:"9585",slug:"advances-in-complex-valvular-disease",title:"Advances in Complex Valvular Disease",fullTitle:"Advances in Complex Valvular Disease"},signatures:"P. Syamasundar Rao",authors:[{id:"68531",title:"Dr.",name:"P. Syamasundar",middleName:null,surname:"Rao",slug:"p.-syamasundar-rao",fullName:"P. 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Interventions meant to correct these conditions are commonly based on symmetrical models of appearance and do not take into account asymmetric organ weight distribution, asymmetries of respiratory mechanics, and dominant movement patterns that are reinforced in daily functional activities. A model of innate, human asymmetry derived from the theoretical framework of the Postural Restoration Institute® (PRI) explicitly describes the physiological, biomechanical, and respiratory components of human asymmetry. This model is important because it gives an accurate baseline for understanding predisposing factors for the development of postural disorders, which, without intervention, will likely progress to structural dysfunction. Clinical tests to evaluate tri-planar musculoskeletal relationships and function, developed by PRI, are based on this asymmetric model. These tests are valuable for assessing patient’s status in the context of human asymmetry and in guiding appropriate exercise prescription and progression. Balancing musculoskeletal asymmetry is the aim of PRI treatment. Restoration of relative balance decreases pain, restores improved alignment, and strengthens appropriate muscle function. It can also halt the progression of dysfunction and improve respiration, quality of life, and appearance. PRI’s extensive body of targeted exercise progressions are highly effective due to their basis in the tri-planar asymmetric human model.",book:{id:"5816",slug:"innovations-in-spinal-deformities-and-postural-disorders",title:"Innovations in Spinal Deformities and Postural Disorders",fullTitle:"Innovations in Spinal Deformities and Postural Disorders"},signatures:"Susan Henning, Lisa C. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/166457",hash:"",query:{},params:{id:"166457"},fullPath:"/profiles/166457",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()