Effects of IFC-305 administration in mitochondria in the sequential model of cirrhosis-HCC.
\\n\\n
Dr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\\n\\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\\n\\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\\n\\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\\n\\nThank you all for being part of the journey. 5,000 times thank you!
\\n\\nNow with 5,000 titles available Open Access, which one will you read next?
\\n\\nRead, share and download for free: https://www.intechopen.com/books
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Preparation of Space Experiments edited by international leading expert Dr. Vladimir Pletser, Director of Space Training Operations at Blue Abyss is the 5,000th Open Access book published by IntechOpen and our milestone publication!
\n\n"This book presents some of the current trends in space microgravity research. The eleven chapters introduce various facets of space research in physical sciences, human physiology and technology developed using the microgravity environment not only to improve our fundamental understanding in these domains but also to adapt this new knowledge for application on earth." says the editor. Listen what else Dr. Pletser has to say...
\n\n\n\nDr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\n\nSeeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\n\nOver these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\n\nWe are excited about the present, and we look forward to sharing many more successes in the future.
\n\nThank you all for being part of the journey. 5,000 times thank you!
\n\nNow with 5,000 titles available Open Access, which one will you read next?
\n\nRead, share and download for free: https://www.intechopen.com/books
\n\n\n\n
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"6569",leadTitle:null,fullTitle:"Recent Applications in Data Clustering",title:"Recent Applications in Data Clustering",subtitle:null,reviewType:"peer-reviewed",abstract:"Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. 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Hepatocellular carcinoma (HCC) represents 80% of the primary liver cancer and, in minor proportion, bile duct cancer and angiosarcoma of the blood vessels in the liver, but all of them have a poor prognosis. HCC is a major cause of cancer-related deaths globally. The incidence of HCC is increasing and has been rising in the last few decades [1]. The HCC is a complex pathology associated in 80–90% with chronic liver diseases like cirrhosis of diverse etiologies. Cirrhosis is a chronic degenerative disease of the hepatic parenchyma characterized by an inflammation process that leads to liver fibrogenesis. This process induces the loss of liver architecture and a diminution of functional parenchyma, which over time changes the environment of the cells resulting in chromosomal instability. The cause of cirrhosis transformation into HCC is not well known, but chromosomal instability could be an important factor for HCC generation in cirrhotic patients. The main problem of this pathology is the lack of early detection, recurrence of tumors following resection [2], and there are no effective therapies. To understand this complex pathology, it is convenient to have some knowledge of the structure and functions of the liver. Therapeutic options for HCC are very limited, and the incidence is very similar to the death rate per year. Only in the early stage of the disease, there are some approved therapies such as tumor ablation, surgical resection, and liver transplantation, but in advanced stages, when most patients are diagnosed, these treatments are not recommended. There is an average of 5-year survival below 20% with these therapies [3]. In intermediate and advanced stage-HCC, the approved options are transcatheter arterial chemoembolization (TACE) and the multi-kinase inhibitor, sorafenib. TACE therapy could extend survival to 2 years [3]. Sorafenib extends survival of patients with advanced stage disease for only 3 months, and this medication causes considerable adverse effects and offers no symptom palliation [4]. There are other several clinical trial efforts focused on therapies involving multiple signaling pathways, most commonly related to tyrosine-kinase growth factor receptors, but they have inferior survival benefits and several adverse effects. Immunotherapy has demonstrated some efficacy, but, in general, molecular characterization to find effective treatments of HCC is needed.
The liver is the largest internal and heterogeneous organ in the body constituted by different kinds of cells like hepatocytes, endothelial cells, cells of the bile duct, Kupffer cells, hepatic stellate cells (HSC), oval cells and pit cells [5]. The liver is an organ highly irrigated by the portal venous system and blood is distributed by the hepatic sinusoids and the hepatic artery [6]. About 80% of the liver cells are hepatocytes, and are epithelial cells that form cords with high metabolic activity and contain a complete set of organelles: mitochondria, peroxisomes, lysosomes, Golgi complex and a well-organized cytoskeleton [7]. The space between cords of hepatocytes and the endothelium is called the space of Disse. Endothelial cells constitute the wall of the hepatic sinusoids and are separated from the parenchymal cells by the space of Disse. They possess pores or fenestrae that permit the exchange of fluids [8]. These cells show endocytic activity and secrete several mediators such as interleukin-1 (IL-1), interleukin-6 (IL-6), interferon, and nitric oxide as paracrine modulators. Kupffer cells are the fixed macrophages of the liver that can migrate along sinusoids. Their main function is an immunomodulatory one [9]. Pit cells are intrahepatic leucocytes with natural killer cell activity [10] and exert a cytotoxic activity toward tumor and virus-infected cells [11]. HSC, also known as lipocytes, fat storing cells, perisinusoidal cells, and vitamin A storing cells, are quiescent in normal conditions. When they are activated, they play an essential role in the synthesis and degradation of the extracellular matrix (ECM) proteins and fibrogenic cytokines, like hepatocyte growth factor (HGF), insulin growth factor (IGR), transforming growth factor-β (TGF-β), and, consequently, induce cirrhosis. Biliary epithelial cells participate in the formation of bile; they are transported to the bile ducts or Canals of Hering. These cells have the potential to become oval cells [7]. The cell-free hepatic tissue represents 20% of the liver volume and constitutes the ECM located in the Disse space. The ECM contains structural proteins like collagen of different types, glycoproteins, fibronectin, tenascin, laminin, entactin, and perlecan. Their function is to maintain the hepatic architecture and the organization of the entire organ. Hepatocytes contribute with 80–90% of the synthesis of liver collagen, which is degraded by metalloproteinases (MMPs) [12]. The liver has multiple functions needed for its own metabolism and for other organs; it participates intensely in the intermediary metabolism that occurs mainly in hepatocytes and is connected with the nutrients of the diet, reaching from the portal circulation, that is, in carbohydrates, proteins, and lipid metabolism. The liver also generates purines and pyrimidines for its own use and their distribution to other tissues in the form of adenosine, inosine, and hypoxanthine [13]. It also synthetizes and secretes plasma proteins and participates in the biotransformation of endogenous and exogenous compounds.
Previously, we have demonstrated that adenosine is a metabolic modulator of glucose and lipids in the liver and adipose tissue [14]. This molecule also modulates in vivo the energy charge in the liver [15]. The nucleoside adenosine is a substance with multiphysiological effects in different tissues, the central nervous system, and cardiovascular system; it is responsible for the modulation of the immune response and acts as metabolic regulator. Its action could be autocrine, paracrine, and endocrine; its metabolism is very active with a high turnover and a very short half-live. Adenosine presents circadian variations in the rat, which correlated with energetic homeostasis of the cell, modulation of membrane structure and function, cell proliferation, and genetic expression by regulating physiological methylation [16]. Exogenous adenosine administration to normal rats showed some pharmacological effects, like increased ATP levels simultaneous to a decrease in ADP and AMP, resulting in an increase of the energy charge of the liver [14]. Also, in the liver of fasted rats, adenosine induces an enhancement of glycogen synthesis [16] and an inhibition of fatty acid oxidation by inhibiting the extramitochondrial acyl CoA synthase and decreasing the plasma ketone bodies [17] These findings allowed us to demonstrate in vivo the Atkinson hypothesis of metabolism regulation by energy charge [18].
The redox state of the cell in different compartments, calculated by the NAD+/NADH (NAD+ and NADH nicotinamide adenine dinucleotide, oxidized and reduced) system, has been shown to be a key point in the control of metabolism [19]. Adenosine administration induces mitochondrial oxidation and promotes the oxidized state in the cytosol and mitochondria in the presence of fatty acid oxidation inhibition, which is induced by the nucleoside. It has been reported that adenosine modulates vasodilatation and vasoconstriction in the hepatic vessels controlling blood flow from the hepatic artery [20]. All these results observed in normal animals led us to test the effects of the nucleoside in several models of acute hepatotoxicity: one induced with ethanol [21], the second with cycloheximide, and the third with carbon tetrachloride (CCl4). Although the toxic mechanism of each one is different, they yielded a similar response generating a fatty liver that was prevented by adenosine [21, 22, 23]. In this way, the nucleoside, through different mechanisms, protects the liver against acute toxicity.
Continuous acute hepatotoxicity results in chronic liver injury with subsequent cirrhosis, with accumulation of ECM proteins, mainly collagen type I [24], accompanied by a deficient degradation of deposited collagen [25]. These conditions will induce a change in liver architecture with loss of its function. This is a complex process, for which no effective treatment has been developed yet. To study the effects of adenosine in this process, a model of cirrhosis induced in rats with CCl4 was developed, in which two conditions were tested: prevention during cirrhosis development and reversion once it is already established [26, 27]. The simultaneous administration of adenosine partially blocked the stimulated collagen synthesis induced by the hepatotoxin, maintained high levels of hepatic collagenase activity, resulting in 50% diminution of fibrosis [26]. The effect of the nucleoside was clearly observed also in the reversion model; it was tested in well-established cirrhosis after 10 weeks of CCl4 administration. Five weeks after suspension of the toxin, animals were treated with saline or adenosine, the saline group increased the cirrhotic characteristics but the group of animals treated with the nucleoside revealed blocked fibrogenesis, increased collagen degradation and normalized collagen types ratio, promoted hepatocyte proliferation, accelerated normalization of liver function, and decreased oxidative stress. These results suggest adenosine as a potential therapeutic agent in the treatment of chronic hepatic disease.
The transfer of an interesting research finding to a clinical setting is complicated, but in collaboration with Dr. Francisco Hernández Luis from the National Autonomous University of Mexico’s School of Chemistry, we prepared several adenosine derivatives that were tested in the CCl4 induced cirrhosis. The aspartate of adenosine, named IFC-305, showed interesting results [28]; beneficial effects in structure and functional recovery were obtained with a fourfold lower dose of this adenosine derivative because it has a longer half-life. The hepatoprotective mechanism of IFC-305 on fibrogenesis was investigated by means of DNA microarrays analysis [29], showing that the expression of 413 differential genes deregulated in cirrhosis tended to be normalized by IFC-305 treatment. Fibrogenic genes, such as TGF-β, collagen type I, fibronectin I, increased their expression in cirrhotic groups, and IFC-305 diminished their expression supporting the antifibrogenic action of the compound. These results highly suggest a diminution of chromosomal instability. With the increased understanding in chromatin organization of the eukaryote genome at genetic and epigenetic levels and remembering the previously commented role of adenosine on physiological methylations, a possible epigenetic mechanism of the IFC-305 could participate in the obtained results. Global changes in DNA methylation, 5-hydroxymethylation and histone H4 acetylation were decreased in cirrhosis and after the IFC-305 treatment the normal values were recuperated. In contrast, the promoter of Col1a1 gene is hypomethylated in cirrhosis but gains DNA methylation upon treatment with IFC-305, correlating with a decrease of Col1a1 transcript and protein level, showing that the treatment restores globally and specifically epigenetic modifications [30]. The microarray analysis also showed modification of immunity genes which where explored in the CCl4 model; it was found that the IFC-305 compound reduced inflammatory cytokines and increased the anti-inflammatory ones like IL-10, supporting the modulation of the macrophage phenotypes M1 and M2 [31].
The liver is an organ with regenerative capacity. Partial hepatectomy or diverse stimuli promote proliferation of parenchymal and non-parenchymal cells in order to recover the liver mass and architecture. This process is regulated by cell cycle proteins, cytokines, growth factors, and matrix remodeling [32].
In acute liver injury, there is a classic wound healing process in which inflammation triggers scar formation that is subsequently resolved to enable regeneration of the damaged hepatic parenchyma. However, when there is a chronic liver injury, the normal regenerative process is impaired, and instead a net deposition of fibrillar collagen is predominant [33].
Cirrhosis is characterized by a decrease in hepatocyte proliferation, in part, because liver cells have a limited regenerative capacity restricted by telomere length. After several rounds of replication, telomeres reach a critically short length that induces cell cycle arrest, senescence, and apoptosis of hepatocytes. Telomere shortening also activates DNA repair pathways leading to chromosomal fusions and instability [34]. During cirrhosis-activated HSC, inflammatory cells secrete proliferative and angiogenic cytokines that contribute to a proliferative condition milieu, including: HGF, vascular endothelial growth factor (VEGF), and IL-6 [33]. This proliferative milieu could stimulate the proliferation of altered hepatocytes carrying mutations of cell cycle checkpoint genes or could select genetically altered clones, promoting HCC [34].
Among the principal cell cycle checkpoints that are generally altered in HCC are the tumor suppressor p53 and Rb proteins. p53 is implicated in cell cycle control, DNA repair, apoptosis, and regulates different metabolic pathways [35, 36]. p53 is frequently mutated in HCC (28–50%) and core proteins from hepatitis B and C viruses can repress p53 activity [36]. The pRB protein is implicated in the progression from G1 into S phase. The Rb pathway is disrupted in more than 80% of human HCC [34]. Gankyrin binds Mdm2 promoting proteasomal degradation of p53 and pRb. Both gankyrin and Mdm2 proteins are frequently overexpressed in human HCC [34, 35]. p53 is also implicated in the stimulation of ATP production by oxidative phosphorylation (OXPHOS). p53 also decreases glycolysis and cellular reactive oxygen species (ROS) production by inducing a protein called TP53-induced glycolysis and apoptosis regulator (TIGAR). TIGAR blocks glycolysis by degrading fructose-2,6-bisphosphate. This inhibition redirects glucose-6-phosphate into the pentose phosphate pathway, which increases NADPH production increasing the antioxidant defenses. The inactivation of p53 should decrease OXPHOS and increase glycolysis and ROS production in cancer cells [37].
It has been demonstrated that IFC-305 is able to stimulate hepatocytes proliferation in CCl4-induced cirrhotic liver through the upregulation of proliferating cell nuclear antigen (PCNA), HGF, and p53, with an increase in energy and preservation of mitochondrial function [38].
On the other hand, in a sequential model of cirrhosis-HCC induced by diethylnirosamine (DEN), IFC-305 caused a tumor reduction, and this protective effect was associated with decreased cell proliferation in the HCC stage. This effect was associated with a decreased expression of PCNA, thymidylate synthase, HGF and its receptor c-Met, and the induction of the cell cycle inhibitor p27. IFC-305 also induced a diminution of gankyrin expression contributing to restoring p53 protein expression to control levels [39].
How could the same compound IFC-305 have opposing effects on proliferation in normal versus transformed hepatocytes? These could be mediated partly by a differential expression of the HGF-c-Met pathway driven by IFC-305 treatment, and the dual role of HGF/c-Met in cirrhosis and liver tumorigenesis. HGF expression is restricted to cells of mesenchymal origin, whereas the receptor c-Met is expressed in epithelial and endothelial cells. HGF is implicated in cell proliferation, survival, morphogenesis, cell motility, and metastasis. This pathway plays a critical role in tissue protection and regeneration. It has been used as a therapeutic agent in fibrosis of different organs. The protective actions of HGF are associated with promotion of cell proliferation, migration, and morphogenesis that would help tissues reorganization [40]. Its protective role is also related to its anti-inflammatory action and its regulation of the cellular redox state, driven by upregulation of the antioxidant enzymes and glutathione reduced (GSH), as well as by repression of two major pro-oxidant systems: NADPH oxidase and/or Cyp2E1 [41]. Nevertheless, the HGF/c-Met pathway in HCC contributes to tumor development by stimulating cell proliferation, invasion, and metastasis [40]. We observed that, in the cirrhotic liver induced by CCl4, the hepatoprotector IFC-305 incremented HGF expression [38], which could have a protective role in the regenerative capacity of the liver. On the other hand, in DEN-induced HCC, the IFC305 treatment downregulated HGF and c-Met expression, which contribute to liver tumorigenesis reduction [39]. HGF and c-Met can be potentiated by ROS in hepatoma cells [41, 42]. It was described that, in the sequential model of cirrhosis-HCC with DEN, there are dysfunctional mitochondria and the administration of IFC-305 restored the mitochondrial function and regulated parameters implicated in metabolism, as well as the mitochondrial dynamics modified by DEN intoxication [43]. Therefore, the IFC-305 could be suppressing expression of HGF via the improvement of mitochondrial redox in DEN carcinogenesis. On the other hand, the restoration by IFC-305 treatment of the p53 protein expression in CCl4-induced cirrhosis and in DEN-induced carcinogenesis, among other effects, could contribute to the restoration of ATP production by OXPHOS and to the decrease of ROS production. However, the exact molecular mechanism by which IFC-305 causes different effects on hepatocytes proliferation in cirrhosis and HCC requires further clarification.
Mitochondria are responsible for energy metabolism in eukaryotic cells; they generate ATP through oxidative phosphorylation. In addition, an important part of the ATP synthesis is the donation of electrons by the tricarboxylic acids chain (TCA) to the electron transport chain (ETC), constituted by five complexes (I-V), NADH enters complex I and generates NAD+, and complex V forms ATP. Mitochondria regulate the energetic state, the redox state, and the metabolism of the cells, being able to generate the epigenetic intermediaries becoming the main therapeutic target of many kinds of cancer [44].
As a response to stress, the cells acquire a metabolic adaptation, which is an important area of research due to its relationship with different illnesses [45]. In chronic liver diseases like cirrhosis, energetic deficiency and alterations in energy parameters have been demonstrated independently of their etiology [46]. Otto Warburg suggested that mitochondria from tumor cells supply energy through glycolytic flow due to lack of oxygen or genetic-epigenetic alterations that affect oxidative metabolism [47]. Mitochondrial dysfunction is implicated in metabolic reprogramming in HCC. The increased ROS production and the reduced ATP generation may contribute to the HCC malignancy [48]. Metabolic alterations may decrease the levels of acetyl CoA, which also plays an important role as modulator of gene expression [49]. In experimental models, including the CCl4-induced cirrhosis, mitochondrial dysfunction has been demonstrated because impaired mitochondrial respiration and ATP decreased levels have been observed [50, 51]. A metabolic adaptation in response to the ATP diminished levels is increased glycolysis [51]. A consequence of oxidative stress in chronic liver diseases is the decrease in metabolic flux, which includes alterations in the TCA enzymes, such as isocitrate dehydrogenase (IDH), which can produce oncometabolites when it undergoes mutations [52].
The redox state can be represented by the NAD+/NADH ratio, which is regulated by the ETC. Several enzymes depend on NAD+ like sirtuin-1 (Sirt-1), a member of deacetylases, and poly (ADP-ribose) polymerase-1 (PARP-1). A Sirt-1 substrate is the peroxisome proliferator-activated receptor gamma co-activator 1-alpha (PGC-1α), which is upregulated in HCC and is responsible for orchestrating mitochondrial biogenesis, favoring accumulation of defective mitochondria [44]. On the other hand, PARP-1 modulates the transcription and DNA repair; however, in HCC, it is upregulated and is considered a hallmark of cancer [53]. The over-regulation of both enzymes in HCC may deplete the NAD+ that can be related to loss of mitochondrial membrane potential (ψm) and mitochondrial dysfunction [54]. Alterations in ψm induce the process of mitochondrial dynamics as a repair response to possible damage to this organelle. Mitochondrial dynamics depends on two mechanisms: fission and fusion; the first one is caused by various types of stress and requires protein activity such as Drp-1, on the other hand, fusion requires the recovery of ψm and proteins such as mitofusin 1 and 2 (MFN 1 and 2) [44]. Mitochondrial fusion promotes cristae formation and normal mitochondria phenotype [55]. Morphological alterations in mitochondria determined through electronic microscopy in various models of hepatic fibrosis have been described a long time ago [56, 57].
Previously, it has been discussed some of the effects of adenosine (base molecule of IFC-305), which include increase in energy parameters and regulation of the redox state. Considering this background and what has been described regarding the metabolic and mitochondrial changes in chronic liver damage, such as cirrhosis and HCC, it was decided to evaluate whether IFC-305 had any mitochondrial effect in the sequential model of cirrhosis-HCC.
In the sequential model of cirrhosis-HCC, decreased mitochondrial respiration, determined through oxygen consumption, and a decreased ψm were found, which reflected in a diminished ATP synthesis. In fact, the dimeric form (active form) of the F1F0 complex of ATPase is lost [43].
On the other hand, alterations in the mitochondrial redox state were observed, determined through the ratio of the levels of β-hydroxybutyrate/acetoacetate (NAD+/NADH). The activity of NAD-dependent enzymes was also affected, such is the case of IDH and PARP-1; this alteration induced a metabolic adaptation because increased levels of lactate were observed suggesting an increase in aerobic glycolysis [43].
It is known that the mitochondrion is capable of responding to several insults of stress through the activity of various nuclear-encoded proteins like PGC-1α and Sirt-1. However, the over-regulation of these proteins has been associated with the accumulation of dysfunctional mitochondria, as described above. In the model previously described, these proteins were found increased. Dysfunctional mitochondria have been related to their morphology, and we know that morphology is closely linked to dynamism. The ratio of Drp-1/MFN-2, proteins that regulate the mitochondrial dynamics, was increased favoring the fragmented form of mitochondria as verified through electron microscopy [43].
Important findings were observed with the IFC-305 treatment as described in Table 1 [43].
Mitochondrial parameter | Effect |
---|---|
Function | Maintained and recovered:
|
Metabolic |
|
Dynamics | Avoided the accumulation of dysfunctional mitochondria through:
|
Effects of IFC-305 administration in mitochondria in the sequential model of cirrhosis-HCC.
Uncoupled mitochondria depicted lower ATP synthesis due to the altered ψm and complex I activity. Previously, it has been demonstrated that complex I is sensitive to DEN toxicity, as NAD+ linked respiration is inhibited [58]. Recovery of these parameters with IFC-305 treatment was observed, including the activity of NAD+-dependent IDH. The PARP-1 activity inhibition probably favored the NAD+ availability and contributed to the maintenance of the redox state. Mitochondrial function preservation and restoration allowed the normalization of the metabolism observed by lactate levels diminution.
On the other hand, the decreased Sirt-1 and PGC-1α in the groups treated with IFC-305 suggested that abnormal mitochondrial accumulation was inhibited. In fact, mitochondrial dynamics regulation was induced by IFC-305. These results demonstrated mitochondrial impairment through functional, metabolic, and dynamic alterations in HCC, and the hepatoprotector IFC-305 helps to repair them, being a tumor suppressive mechanism.
These findings support the mitochondrial role in the establishment of HCC and the interplay with the nuclear genome as targets in the design of new therapeutic strategies for the HCC treatment. In this regard, the IFC-305 supports that idea and emerges as a new possible HCC therapy through mitochondrial regulation.
According to the above, there is a growing interest to find pharmacological strategies to block the effects of mitochondrial dysfunction in HCC. Regarding this, in the model of HCC induced with DEN, a study was conducted to determine the mitochondrial effects of ginkgolide B in two different pharmaceutical formulations, finding a decrease in the mitochondrial generation of ROS and a decrease in the dissipation of the mitochondrial membrane potential [59]. Moreover, two of the most studied hepatoprotective compounds until now are resveratrol and N-acetylcysteine (NAC) [60]. On the one hand, resveratrol inhibits the formation of hepatocyte nodules in the DEN-induced HCC model plus phenobarbital administration; moreover, it is capable of modulating mitochondrial biogenesis [61]. On the other hand, NAC blocked phosphorylation of β-catenin, JNK, and c-jun activation, avoiding the development of liver damage in HCC transaldolase-deficient mice, a limiting enzyme for the non-oxidative branch of the pentose phosphate pathway, which is, at least in part, responsible for HCC generation [62]; furthermore, NAC stabilizes the mitochondrial membrane potential regulating mitochondrial dynamics [61].
The epigenome can be altered not only by environmental factors, such as exposure to exogenous chemicals [63] but also by changes in the levels of endogenous cofactors and metabolites [64, 65]. The exact correlation between nucleus and mitochondrion allows for the maintenance of mitochondrial structure and function. On the one hand, the nuclear gene expression is regulated by mitochondrial intermediates, like acetyl-CoA, ATP, NAD+, and s-adenosylmethionine, which are the link between the epigenome and calorie availability [47, 66]. In addition to the production of epigenetic substrates, mitochondria may be modified in their DNA (mtDNA). Some mitochondrial genes have been reported as hypermethylated in HCC; for example, mitochondrial ribosomal protein S12 (Mrps12), mitochondria-localized glutamic acid-rich protein (Mgrap), and transmembrane protein 70 (Tmem70) genes [67, 68]. On the other hand, the disruption of the step in the methylation of 5-mC to 5-hmC in the mitochondrial genome leads to the alteration of several OXPHOS genes, such as: NADH dehydrogenase (ubiquinone) 1 subunit C2 (NDUFC2), NADH dehydrogenase (ubiquinone) flavoprotein 1 (NDUFV1), NADH: ubiquinone oxidoreductase subunit S6 (NDUFS6) from complex 1. These modifications, added to the mitochondrial damage by oxidative stress, can favor the loss of ETC function. In addition to that, it has been reported that the mitochondrial genome damage can affect the expression of nuclear genes [69, 70, 71]. Moreover, there is a deregulation of hepatic one carbon, and TCA cycle, therefore it driving the aberrant epigenetics changes [72, 73, 74]. The main consequence of depressing the TCA cycle is the reduced availability of α-ketoglutarate, leading to a decrease in the activity of α-ketoglutarate-dependent proteins, which are responsible for the hydroxylation of many substrates in the cell that are important in epigenomic control [74].
Tumor cell metabolism can be linked to epigenetic changes during carcinogenesis; recent research has focused on epigenetic studies in relation to metabolic pathways [75, 76]. HCC is a heterogeneous disease affected by various lifestyles and environmental factors. Epigenetic alterations are frequently caused by these factors and contribute to hepatocarcinogenesis. During HCC development, different alterations in global DNA methylation have been described; for example, global hypomethylation leads to aberrant overexpression of oncogenes and large chromosomal instability [77, 78].
In cirrhosis and HCC, distinct patterns of aberrant DNA methylation associated with cirrhosis and HCC have been confirmed [79, 80].
The pathophysiology of HCC is multifactorial and involves mitochondrial dysfunction. Mitochondria usually generate relevant modulators of gene expression controlled by epigenetic mechanisms. These alterations induce chromosomic instability that could give advantages to subclones of cells to their outgrowth (Figure 1). Further studies are needed to find therapeutic strategies capable of maintaining and improving the mitochondrial integrity to avoid alterations in the epigenetic regulation of nuclear- and mitochondrial-encoded genes. These effects could suppress failures in cell cycle checkpoints and the uncontrolled proliferation to prevent or reverse HCC as demonstrated for IFC-305.
(A) In the model of liver injury induced by diethylnitrosamine (DEN), the architecture of the liver parenchyma is altered causing an exacerbated proliferation of various transformed clones, where the presence of a large number of tumors randomly distributed in each one is observed in the hepatic lobules. The preneoplastic nodules that form are surrounded by septa of collagen fibers; thus, favoring the evasion of the immune system and an ideal hypoxic microenvironment for the tumor cells. The genomic instability caused by the toxic as well as favoring mutations, for example in p53, and various alterations in different cellular modulators, among them HGF, c-Met, PCNA, gankyrin and p27. It also causes an increase of proteins, deacetylating PGC1-α, and, thus, modifies various nuclear genes exported to the mitochondria, causing accumulation of abnormal and dysfunctional mitochondria. (B) In the model of hepatocarcinoma induced by DEN, the administration of the adenosine derivative, IFC-305, has been shown to have various regulatory effects. The excessive accumulation of collagen fibers in preneoplastic nodules as well as the number and size of tumors are reduced. Also, cell morphology and DNA recover significantly. A decrease in the deacetylase Sirt-1, whose target is PCG1-α, has been observed, which allows the latter to remain acetylated and can be internalized to mitochondria, where it will promote its adequate morphology, dynamics and function. It has also been found that the compound IFC-305 acts on the levels of some important modulators in cancer (p53, HGF, C-Met…), maintaining or returning them to their concentrations under normal conditions. Overall, the aforementioned effects make this compound a possible therapeutic alternative.
This work was supported by Consejo Nacional de Ciencia y Tecnología (240315) and DGAPA-UNAM, grant numbers IN208915 VCS.
The author(s) declared no potential conflicts of interest respect to the research, authorship, and/or publication of this chapter.
HCC | hepatocellular carcinoma |
PARP-1 | poly (ADP-ribose) polymerase-1 |
TACE | transcatheter arterial chemoembolization |
HSC | hepatic stellate cells |
IL-1 | interleukin-1 |
IL-6 | interleukin-6 |
ECM | extracellular matrix |
HGF | hepatocyte growth factor |
IGR | insulin growth factor |
TGF-β | transforming growth factor-β |
MMPs | metalloproteinases |
NAD+ | nicotinamide adenine dinucleotide oxidized |
NADH | nicotinamide adenine dinucleotide reduced |
CCl4 | carbon tetrachloride |
VEGF | Vascular Endothelial Growth Factor |
OXPHOS | oxidative phosphorylation |
SCO2 | chaperone protein “synthesis of cytochrome c oxidase 2” |
ROS | reactive oxygen species |
TIGAR | TP53-induced glycolysis and apoptosis regulator |
PCNA | proliferating cell nuclear antigen |
DEN | diethylnitrosamine |
GSH | glutathione reduced |
TCA | tricarboxylic acids chain |
ETC | electron transport chain |
IDH | isocitrate dehydrogenase |
Sirt-1 | sirtuin-1 |
PGC-1α | peroxisome proliferator-activated receptor gamma coactivator 1-alpha |
ψm | mitochondrial membrane potential |
MFN 1 | mitofusin 1 |
MFN 2 | mitofusin 2 |
NAC | N-acetylcysteine |
mtDNA | mitochondrial DNA |
Mrps12 | mitochondrial ribosomal protein S12 gene |
Mgrap | mitochondria-localized glutamic acid-rich protein gene |
Tmem70 | transmembrane protein 70 gene |
NDUFC2 | NADH dehydrogenase (ubiquinone) 1 subunit C2 |
NDUFV1 | NADH dehydrogenase (ubiquinone) flavoprotein 1 |
NDUFS6 | NADH: ubiquinone oxidoreductase subunit S6 |
Planning for resilience and enabling positive design outcomes requires combinatory methods of working with data, in order to assist decision-makers to develop evidence-based methodologies and easily communicated scenarios. To accomplish this, we need to bring together data and information sets from disparate and vastly divergent disciplines and sources. The impactful rise of technology in urban planning has allowed for the extensive integration of data analysis tools, which promote a better understanding of socioeconomic fluctuation, as well as the active involvement of users in the planning process. In this way, users can participate and impact the planning process toward outcomes, which are more appropriate to their needs [1]. Evaluating urban environments is not only important from the planners’ perspective but also has larger implications for the residents themselves. This shifts our thinking toward democratic environments, where users engage designers by expressing their preferences on how an idea could become part of their lives. This chapter aims to contribute to the discourse on user involvement in design-oriented fields, in our case, urban planning, by analyzing two different approaches of participatory design. The first approach addresses user participation as a research method or an analysis tool and the second as an urban design method. The key aspect to both approaches is open data platforms, as they allow access to the intended audience, researcher, or average user. Both approaches are presented through example case studies that are analyzed and compared based on the type of user participation, amount of user involvement, and type of context they are applied to. The two case studies represent different stages of participatory design, where the first focuses on the integration of human perspective in neighborhood evaluation and the other on active, contextualized user participation in placemaking and neighborhood reformation. Both processes address human perception as an effective means in capturing the dynamics of space, as well as a mean to drive the change itself. User participation is the agency upon which, local resilience is formed by balancing the power between stakeholders and community members. We support that user-centric approaches improve society well-being and user satisfaction, toward more democratic and sustainable urban environments.
In order to improve policy-making and the health of communities, collaborations often extend beyond the level of academic research, to that of the user level. Recent research suggests that researchers create more innovative concepts when taking advantage of user input than working purely with existing data sets. Humans are positioned as the major contributors to changing environments [2]; therefore, human factor should be addressed and included when conceptualizing urban analysis methodologies. This approach has a political dimension of user empowerment and democratization, and it is called participatory design approach. Participatory approaches link together all stakeholders (e.g. employees, researchers, customers, citizens, end users), in an attempt to improve human well-being, user satisfaction, accessibility, sustainability, and livability. As participatory processes are more and more supported by information technology, this enables both sides, users, and researches to understand and collect diverse knowledge, for example, opinions, ideas, objectives, statements, etc.; however, it increases the complexity and the handling of information when it comes to decision-making. Regarding user participation, the possibilities of digitalization should be regarded as an opportunity to accompany the social transformation toward a digital society in the information age of the twenty-first century [3]. A participatory process involves the side of the researcher or organizer and the side of the participants. In this chapter, we present two different directions of the above relationship: indirect user participation and direct user participation. In the first case, the users seek no personal interest in the process; however, they state their opinion regarding a real matter, which is proven useful in understanding urban dynamics. This process involves two stages that depict different processes. The results are then combined in a series of maps. The second case is a deliberate process in which the interested party (citizens) is involved in the policy-making toward the satisfaction of their needs. The process involves the construction of a digital platform that is user driven. This approach builds upon participatory action research by moving beyond participants’ involvement and producing solutions to problems rather than documenting the results as a resource database. Further stages may then focus on community brainstorming, modeling and prototyping, and implementation in community spaces.
Urbanism during the twentieth and beginning of twenty-first century was formed by large-scale centrally planned developments. In the 1960s until early 2000s, several urban analytics models incorporated computational tools that introduced automation and standardization, in order to visualize and understand the urban space. One of the most widespread used tools that revolutionized mapping since the 1960s was geographic information system (GIS), which enabled the association of geo-location with information. GIS systems are able to visualize time and space paths as static models using models of space and time that show the entire path within a geographic space and a fixed domain of time [4]. This has greatly lowered the cost of data accumulation and improved the accuracy of the results [5]. The main data source employed in central urban model is census data from government databases, which with the use of GIS tools can be visualized and mapped.
Central urbanism presents certain challenges, which derive from two sources: the first is related with technical aspects of data sets and data handling and the second with socioeconomical aspects that influence the fluctuation of capital and investments related to urban space and infrastructure.
Centrally planned urbanism refers mainly to the broad picture of the urban environment; as a result, it does not address local details adequately. Centralized, top-down approaches do not derive in resilient conditions as they usually favor certain economic interests. In contradiction to bottom-up approaches, central-based urbanism does not rely on evidence-based methodologies, and therefore they do not involve user participation.
In addition to the above, centralized approaches involve money-oriented developments, which do not respond to local citizens’ needs; in fact, they usually undermine them. As they largely follow the dictates of social and economic elites, they are based around uneven development and exclusion, increasing economic segregation.
Centrally planned urbanism is based on limited data sets and assumptions, which fail to address cities as arrays of social complex relations. Such assumptions engendered vehicular domination over walkability, maximized urban density, and homogenized urban districts all at the expense of residents’ quality of life. It appears that there is hardly any empirical data or residents’ input that provide insight into most central-based master plan developments. Central urban models are guided by a set of specified constraints that perform in a simplified environment disconnected from real facts; thus, they may not capture complex dynamics of socioeconomic flux. One explanation for this is the difficulty of adequately incorporating the breadth of social theory needed to account for the range of urban mechanisms. For instance, even the analysis of the relationships that occur in a park of a business district neighborhood during day and nighttime quickly becomes a complicated problem to describe through census data. These models are constrained by their inability to theoretically ground mechanisms of neighborhood change and translate them into a data set. They are limited by a lack of empirical detail, in their specifications of data attributes.
The challenges listed above derive from the fact that the processes employed mask a great deal of heterogeneity between urban areas. This resulted from deficiencies in the data sets and short time-scale of the analysis, factors that designated the low predictive capacity of the models, and the insufficiency to fully understand neighborhood dynamics, which remain ambiguous and conflicting.
As cities are becoming more instrumented and networked, more data is being generated about the urban environment and its residents, allowing urban designers to access the local scale fabric of the city, opening up new research directions for understanding the city. Going beyond traditional data sources, such as census, which is fairly static and updated only every, designers are encouraged to engage with other types of data that capture the ephemeral side, such as, people’s desires, problematic, trends, etc. It is important for designers and planners to recognize the opportunities for making better sense of public space through technology. One of the key benefits of adopting a data-driven approach to urban analytics surveys is the ability to see a combination of datasets in context with each other and to detect temporal and spatial patterns.
A new generation of researchers has been deriving evidence-based rules for urbanism, which benefits from user participation [6]. These rules replace outdated working assumptions that have created dysfunctional urban conditions. Recent methodologies in urban research validate human scale urbanism and collaborative approaches. In order to provide a better understanding of the contradictory approaches, we will list some of the main challenges of centralized urbanism. Moving beyond the form-oriented framework of centrally based urbanism, we should also refer to certain challenges that the participatory approach entails.
The growing desire of involving participants in the process represents certain challenges that need to be addressed for successful decision-making [7]. Building user participation systems in response to the complexity requires a combination of data, which is fit for use and decision support tools. We list some of the key barriers that are present in user participation approaches.
Complex data user inputs. User data inputs are usually complicated data types. For example, natural language text, descriptions, sketches are a challenge for computers to interpret and also for researchers to translate them into a binary or measurable form. This type of data is also difficult to store, categorize, and visualize in a proper way for future interpretation.
The translation of miscellaneous forms of data input is a labor intense, manual analysis and might result in potentially obscuring part of knowledge that can be drawn from the raw user data.
Ensuring that the user understands the request and is able to provide useful feedback. Abstract requests could result in user distraction, which can complicate the feedback data previously described in the first point. Moreover, researchers will need to consider that the user input should not rely heavily on the users technical skills and prior knowledge of the tools, as this would limit the target user group to a very small pool of people, which would have the expertise.
Citizens are often a resource of small-scale ideas that could improve the livability of their immediate environment. However, it is hard for local people to coordinate and produce visualized results that they could communicate with the authorities. Even so, such proposals are likely to be discarded as they do not represent the stakeholders’ benefits and moreover, large-scale developers make it impossible for citizens to have any influence in urban development.
Based on the above, opening a channel for sharing knowledge and opinions is not necessarily sufficient for building a system that takes the most advantage of user input. The objective is to achieve a balanced relationship between extensive information and clarity, in order to ensure that all the data and their interconnections are handled to their entirety. We need to build human-computer interaction in a way that it facilitates user orientation and comprehension of the framework, defines the scopes of the user and the researcher, and translates the user input into a quantifiable entity. Therefore, we refer to a software workflow/application that ingrates user input in a form of binary data that can be easily quantified, categorized, and visualized. To avoid oversimplification of the process, the insight of the researcher is crucial, in order to extract valuable, subjective information in a simple format.
The first example is a mapping process of the gentrification and displacement rate and livability levels in the neighborhoods of Oakland in the San Francisco Bay Area. Before analyzing the methodology of the example, we should first understand the notions of neighborhood and gentrification as addressed in this chapter, which will provide clarity regarding the reasoning behind the example methodology.
The neighborhood is often understood as the physical building block of the city for both social and political organization [8] and thus combines physical and nonphysical characteristics. Early scholars have described neighborhoods as defined, closed ecosystems, characterized only by their physical elements, such as size, density, demographics, etc. that would get disrupted by external factors, such as new residents. Moreover, neighborhood change has been regarded as a natural process of population relocation and competition for space, until a state of equilibrium could be reestablished. Based on these ideas, neighborhoods were presented as a deterministic model and categorized based on simplified criteria such as their residents’ financial status, etc. However, neighborhoods are not introverted, autonomous clusters, and the mechanisms of neighborhood change do not rely on exclusively external factors. According to Jacobs [1], nowadays, people identify a neighborhood by a landmark in the city because it has become intimate from daily use or encounter. The key that creates the notion of a neighborhood is diversity and identity. She argues that people tend to avoid visiting places that do not represent any variation either in function or esthetics [1]. Although the modern way of living has urged people to be more mobile than previously, people tend to pay attention to district that surrounds their home if it meets the certain criteria that fit their lifestyle. The stability of a neighborhood relies on its capacity to absorb opportunities and sustain its diverse character. In this paper, the term neighborhood can be described as an instance of organized complexity [1].
The notion of gentrification can be described as one category of neighborhood change and is broadly defined as the process of improving and renovating previously deteriorated neighborhoods by the middle or upper class, often by displacing low-income families and small businesses. The first documented use of the term “gentrification” [9] describes the influx of a “gentry” in lower income neighborhoods. Owens identifies nine different types of neighborhoods that are experiencing upgrading: minority urban neighborhoods, affluent neighborhoods, diverse urban neighborhoods, no population neighborhoods, new white suburbs, upper middle-class white suburbs, booming suburbs, and Hispanic enclave neighborhoods [10]. Gentrification does not only rely on a singular cause, as it may emerge when more than one condition is present. It is a complicated process that does not rely on binary and linear explanations. Early studies identified two main categories that cause gentrification: private capital investment for profit-seeking and people flow that refers to individual lifestyle preferences [11]. Gentrification does not necessarily result in negative effects, as it can also operate as a tool for revitalization. When revitalization occurs from existing residents, who seek to improve their neighborhood conditions, the result can be constructive in enforcing the neighborhood stability. This condition is called incumbent upgrading or “unslumming’ as Jacobs [1] defines it. However, when revitalization causes the displacement of current residents and a decline in neighborhood diversity, then neighborhoods gradually become segregated by income, due in part to macrolevel increases in income inequality as well as decline of job opportunities. Hence, neighborhood stability is compromised because the opportunities have been narrowed down to a very limited range of financial status and lifestyle. Displacement, however, is identified as the biggest negative impact of concern resulting from neighborhood revitalization and gentrification. Displacement occurs when any household is forced to move from its residence, usually because of eviction and unaffordable rent increase [12]. However, tracking unwilling displacement can be challenging to categorize, as researchers have faced limitations regarding data availability and data comprehension.
In this case study, we carefully selected and analyzed the various, specific data sets that relate to gentrification and are associated with livability, from authoritative census data categories, such as income, crime, education level, employment rate, urban infrastructure, etc. to more ephemeral and subjective data classifications related to human perception and user input. In order to go beyond the conventions in understanding the dynamics that drive socioeconomic phenomena and construct lived space, we attempted to implement methods that although they are considered disassociated with urban analytics, they offer a strong potential in contributing to this study as it will be analyzed in detail in the following paragraphs.
This case study involves three methods of data accumulation and analysis; the first method is a preliminary census data classification of key GIS data sets that are available from the government and other certified public resources. The second method uses data resources that derive from open data platforms (data that is freely accessible), such as Google API, Google Places, and collective, open-data platforms where users post all kinds of requests (sell and buy, real estate, etc.), such as “
Although the methods differ significantly in the types and source of data being used, it is important to mention that each perspective provides a different lens through which to view transition toward more or less livable and gentrified environments. The data sets collected from the three methods operate at different scales, some at urban scale for the entire San Francisco Bay Area, some at neighborhood scale, and some at street level scale. Each method presents certain advantages and altogether provide a calibrated understanding of the multiple grains of constructed space through top-down and bottom-up methods, as well as to offer a tool of visualizing dynamical characteristics of the urban environment. For example, using a human-based perspective alone may lead us to commit to something, which is entirely subjective, by ignoring holistic factors that emerge at aggregate levels and vice versa. The census data analysis provides an overview of the context over a significant time span (2000–2012) and helps us understand major socioeconomic shifts that affect tenure, which then affects the local market and the standards of living in the area in terms of public infrastructure. The open data analysis depicts the ephemeral layer of relationships that take place in the urban environment, which is impossible to be described by authoritative data; however, it is more relevant to the actual conditions, revealing virtual changes and dynamics for the near future. The third method enriches the process with user personal feedback about ranking the environment of a neighborhood as it currently stands.
Across all three studies, the data has been visualized based on a few basic rules. Changes of degree in a factor are displayed with a gradient of the same color, changes of type are displayed with different colors, and the general vocabulary of visual styles is communicated with dots, lines, and areas [14]. The tools used for the data visualization are “Microsoft Excel” for calculation of delta, median, and average values, “Grasshopper” for processing data input in “.json,” “.csv,” or “.shp” file formats, “Rhinoceros” for processing the output data from “Grasshopper,” “Processing” as a geo-located three-dimensional virtual space, where multiple data sets can be displayed and overlaid at the same time, in order to assess their relationship and “Adobe Suite” for final printed output.
The initial method, which defines the preliminary step of the research, refers to the use of GIS census data analytics. This method aims to depict the urban areas that have undergone changes on authoritative parameters that are associated with the phenomenon of gentrification, such as tenure status, median household income, land value, and employment rate. Moreover, this method queries the livability levels based on parameters related to public infrastructure and the urban quality, such as pedestrian network continuity and status, transportation, walkability, and car dependency street trees and parks, schools, education points, medical and religious spaces. The objective of these data sets integration is to assess whether the built environment is evolving toward an equal state of services and other opportunities or in favor of certain socioeconomic groups over others.
The “Geographic Information System”, or GIS, tools enable the accelerated gathering of data sets of multiple categories. As this method focuses solely on census data and basic population characteristics, the data sets that are useful to the execution of the survey are population, median household income, level of education, transport network, and infrastructure.
Initially, the survey began with a high-level analysis of the San Francisco Bay Area natural morphology and broad population characteristics; therefore, the first data sets that were visualized were green areas, wetlands, urban areas, total population, and land value (Figure 1). Before analyzing more thoroughly the city of San Francisco, we collected some data related to the homeless population community in the city as it is a very apparent phenomenon that appears to be getting aggravated. As the core of the research is focused on depicting and tracing the dynamics of gentrification, we believe that information associated with the homeless population community and then compared with the census data regarding tenure status and land value could provide useful insight (Figure 1).
Geo-located 3D space in the software processing. Natural elements and census data for San Francisco Bay Area. Public resources for homeless population for the city of San Francisco (figure was created by the author) [20, 21, 22].
The second stage of the survey focused solely in the county of San Francisco, as it was considered a suitable context to trace the main changes in demographic characteristics. The data sets that were visualized at this stage of the survey were the range of household income, range of home value, owner-occupied housing, vacant lots, and the ratio of unemployed population against the total population (Figure 2). Green areas in the San Francisco Bay Area that are accessible to the public, such as parks, plazas, etc, were excluded from the calculation as they do not relate to the targeted data sets, and they would have affected the results of the survey.
Census data for the city of San Francisco, total population, income, vacant housing, home value, unemployed population (figure was created by the author) [18].
Although the previously described survey did reveal information on the transition of some neighborhoods in San Francisco, at the next stage of the research, it became apparent that the most applicable scale for census data display would be that of the entire San Francisco Bay Area. The reason for this is that census data has low spatial resolution and therefore refers to large-scale surveys. Hence, the data was recollected for the San Francisco Bay. The census data collected consists of data sets that range from 2000 to 2012 and is related to tenure status, median household income, median home value, and employment rate. For every data set of the above, we calculated the delta value (amount of change or difference) between the years 2000 and 2012 and remapped the values to a numerical range between 0 and 1, which corresponded to a gray scale ranges from white (255, 255, 255) to black (0, 0, 0). White color represents no change, whereas black color represents the highest amount of change. The delta value was plotted in the context of San Francisco Bay Area, and the result is four maps, each for one data set. The four maps, which derived from the process described above, represent the amount of change in tenure, median household income, median home value, and employment rate were weighted and integrated into a single map that represents the amount of change of all four data sets (Figure 3).
San Francisco Bay Area, census GIS data comparison of tenure, median household income, median home value, and employment rate from 2000 to 2012 overlapped with artists’ employment rate (figure was created by the author) [19, 20, 22].
In addition to the data sets related to tenure status, we included the census data of artists’ employment rate as it is considered a key indicator of the early stages of a gentrification process. Surveys in the field of urban renovation have established the artists community as an agent of urban gentrification, for the reason that low-income artists tend to revalorize unproductive spaces because they are affordable and, as a result, increase the attractiveness of the neighborhood. Artists make the first move into post-industrial, post-welfare neighborhoods, and soon they attract the hipster movement before, eventually, being displaced by them and their new middle-class neighbors. Both participate in the cycle of exploring, developing new potential sites for capital investment. Hence, the combined data set of the four census categories is overlapped with artists’ employment rate census data set (Figure 4). Regarding the services that are directly related to the urban quality, such as accidents and pedestrian network continuity and status, transportation, walkability, and car dependency street trees and parks, schools, education points, medical and religious spaces, the data sets are divided in two categories. The first depicts amenities such as access to education, religion, health, and green areas, as well as the street trees that definitely improve the urban environment in terms of walkability, microclimate, and aesthetic. The second depicts car dependency zones, reported car injuries location, pavement condition, and parking spaces (Figures 5–7). The source of the data sets mentioned above was mainly government websites, and the data were provided in.csv format. Data were imported to Microsoft Excel, in order to calculate and process the key indicators that derive from more than one data set and the delta values from the comparison of the data set over a period of time. After the calculation, the information was then imported in grasshopper and processing for visualization in context, as a series of maps.
San Francisco Bay Area, census GIS data comparison from 2000 to 2012 overlapped with businesses related to artists from Google places (figure was created by the author) [19, 20, 22].
Oakland green areas, street trees, transport, and education (figure was created by the author) [17].
Oakland, quality of pedestrian network, pavement condition, injuries, and parking spaces (figure was created by the author) [17].
Oakland, walkability, and car dependency (figure was created by the author) [17].
The database is articulated by tracing certain populations and services categories that reflect activity and flux of the built environment. The targeted data sets involve artists and their recent activity in Oakland, industrial buildings, loft residencies, yoga and fitness studios, fashionable cafes, as well as crime reports from 2010 to 2013 (Figures 8 and 9). The data accumulation derives from open data platforms by defining an equivalent keyword query. The artist population is considered as the frontline of gentrification [2]; therefore, tracing their activity would provide useful insight, combined with a survey on loft residencies, which usually attract the artist community and on certain amenities that appeal to the same target group. The survey on industrial buildings helps in the formation of a forecast model of potential transformation of industrial building envelopes to loft residencies. The chosen data sets describe adequately the artists community in the sense that it is commonly known that upcoming artists are mostly freelancers or seeking for a job, and in order to settle their studio, exhibition space, etc, they actively pursue real state, as well as specific lifestyle preferences. This activity regarding real estate hunting cannot be described by census data, simply because it is volatile and constantly shifting. Methods that employ open data platforms such as Google Places and “
Oakland crime reports, 2010 (left), Oakland crime reports 2013 (right) (figure was created by the author) [23].
Oakland, industrial buildings, lofts/luxury residence, businesses related to artists, yoga and fitness studios, fashionable cafes (figure was created by the author) [23, 24, 25].
Oakland, industrial buildings, lofts/luxury residence, businesses related to artists overlaid with Amazon Mechanical Turk Delta between infrastructure condition and safety (figure was created by the author) [23, 25].
The second method involves a human-based approach, as a crowdsourcing process. In this method, the crowdsourcing process was achieved via a human-based outsourcing platform called “Amazon Mechanical Turk.” The “Amazon Mechanical Turk” platform is a crowdsourcing Internet marketplace, operated by “Amazon,” which enables individuals to coordinate the use of human intelligence and perform tasks that computers are currently unable to perform successfully. It is an on-demand sample of users that executes simple assignments over an agreed period of time. The “Amazon Mechanical Turk” can be associated with the term “Human Computing.”
Initially, and in order to test the feasibility of this method, we processed only few blocks in Emeryville, Oakland, and the questions posted to Amazon Mechanical Turk were very simple and required identification of certain elements and whether they appear in the images. Example elements that were queried are bicycles, lofts, abandoned buildings, and industrial buildings (Figure 11). In the next stage, a large group was given two different sets of questions. The first set of questions is related to human subjectivity, which implies that the users were given a set of subjective questions that were related to the qualitative rating of selected neighborhoods in the San Francisco Bay Area. The questions were communicated in a simple way, by extracting Google Street viewpoints as images and submitting them to the “Amazon Mechanical Turk” system for rating along with a series of questions regarding the content shown in the images. This process takes advantage of human subjectivity when it comes to rating an area based on someone’s personal infrastructure condition (Figure 12), interpretation of safety (Figure 13) and affordability (Figure 14), qualities that vary significantly even among neighboring blocks; however, the amount or the frequency of variation may have a significant role in the overall research. The second set of questions is related to the collection of detail features, such as the presence of expensive loft housing, abandoned buildings, industrial buildings, trees, fitness studios, contemporary and stylish coffee shops. This process is utilizing the same strategy as the first one, by using Google Street viewpoints in order for the participants to identify the presence of any of the feature elements in the content of the images. The identification of these features would be extremely time consuming to collect manually; therefore, this method is proven highly efficient on this aspect. The areas of interest for both sets of questionnaires are Oakland and Emeryville, which were chosen because they are transforming from high concentrated crime areas into urban, entertainment, and commercial attractor points. The questions were submitted to “Amazon Mechanical Turk” as a file in “.json” format and were structured in a way that the answers would be easy to process and to visualize. In particular, the answers to the question would have to be represented either as a numerical scale from 1 to 10, as a binary yes or no option, or a multiple choice (tick the box). We avoided completely answers that would require the user to write lengthy texts (Figure 15). The received answers were in “.json” format, so they were transformed into “.csv” format as in the previous method.
Amazon Mechanical Turk Oakland example maps of bicycles, lofts, abandoned buildings, and industrial buildings (figure was created by the author).
Amazon Mechanical Turk neighborhood rating: neighborhood infrastructure evaluation (figure was created by the author) [25].
Amazon Mechanical Turk neighborhood rating: neighborhood safety evaluation (figure was created by the author) [25].
Amazon Mechanical Turk neighborhood rating: neighborhood affordability evaluation (figure was created by the author) [25].
Amazon Mechanical Turk submitted questionnaire (left) Amazon Mechanical Turk street rating (right) (figure was created by the author) [25].
All data layers were combined and provided the context for a more fine-grained understanding of neighborhood characteristics, conflicts, and relationships that reveal the heterogeneous characteristics of the city [15]. Mapping here is not only addressed as a visualization tool but also as a platform based on which we can make faster and factual assessments [16].
Moving away from the expert urbanist model, which determines the form and functionality of the built environment based on central rules, we argue that engagement with democratic participation can lead to more sustainable and resilient built environments. “Openreblock” platform is an open-ended approach to social justice that offers users active participation and opportunities to reform their immediate environment (Figure 16). By encouraging participatory planning via community mapping by its own citizens, it contributes in improving slum communities and their integration in the broader urban fabric. Some of the immediate benefits are land regularization and security of land ownership, allowance for public services, and connectivity.
“Openreblock”: website main page, interface, graphics (graphic design by Stamen design).
As urban planning should be understood as a communicative, pragmatic, social practice, this tool facilitates intercultural dialog and implementation. “Openreblock” enables users to reorganize slum communities that lack significant public infrastructure, such as access to a public street. The idea of the tool is that citizens have the right to affect the design of their local neighborhood and have access to an open-source methodology for doing so. It is a web-based service for an open-source platform that proposes the least disruptive reformation of the existing street network in order to interconnect slum building blocks that lack access to a public street. This sets the basis for land formalization and property stability, so that urban slum communities become more resilient to future exploitation and natural disasters.
Funded through OpenIDEO, it is the product of major research collaboration by the Santa Fe Institute, Sam Houston State University, UC Berkeley, and Shack/Slum Dwellers International, a global network of community-based organizations representing the urban poor. Shack/Slum Dwellers International is a network of community-based groups from 33 countries representing and communicating the needs of the urban poor, engaging international agencies, and operating on the global stage in order to support and advance local struggles for the last 20 years.
“Openreblock” combines the knowledge of slum communities’ inhabitants with data analytics worldwide to enable each citizen to become an agent of information with the objective to enrich local knowledge and empower their community to pursue faster and more sustainable development outcomes from the local governments.
In order to be able to formalize a strategy on how to evaluate and classify urban fabric typologies, we need to identify some key characteristics that define the character of the urban space. These characteristics should correspond to physical characteristics and relationships between the elements of space, in order to become a quantifiable set of parameters. In our case, the morphology of space that we need to analyze is that of a slum urban block. Although slum communities are diverse in physical appearance, context parcel population, and opportunities, they share common characteristics of organic typology and aggregation of parcels that are a result of unplanned, spontaneous expansion. In most cases, this type of urban development across time results in isolated parcels that do not have access to the street network at all and therefore to any services.
The lack of infrastructure appears to be common to most poor or informal neighborhoods, and some of the challenges that these communities are facing derive partially form this fact. Streets are not only used for transportation, they carry all the necessary infrastructures such as drainage, electrical and communication services that interconnect the neighborhoods.
Based on the above, the key quantifiable set of parameters is the topology of the parcels, which reveals parcels with “blind” sides to a public street. In comparison with normal city block that is accessible from all sides, an isolated block would share a common side with one or more of its neighboring blocks. Thus, we can classify the urban fabric quality of any community block from maps that include spatial parcels and access networks in a way that can be automated. We demonstrate an example below of a morphing procedure between three different typologies of urban blocks that have the same topology (same number of parcels and no isolated parcels, common number of nodes), where we can mathematically transform the parcels from one block typology to the other. The third block typology is the output of the “reblocking” procedure of a slum block in Epworth, Zimbabwe, while the other two are from New York and Cape Town. This small example reflects the concept of urban topology evaluation, as the morphing process would have failed if the Epworth block had isolated parcels (Figure 17).
Topology of a building block-morphing process between three building blocks that share the same topology (figure was created by the author).
Thus, by evaluating the topology of the street network, we can assess more effectively the quality of the neighborhood in terms of public services, connectivity, and social and economic justice in general.
“Openreblock” visualizes access to essential services like water, energy, and sanitation at a neighborhood parcel level. This web-based platform requires user input, in order to operate and uses an algorithm to evaluate the topology of the blocks and the continuity of the street network, identify the parcels that do not have access to a public street, and then propose the least disruptive reorganization of a cluster of slum blocks, so that each parcel gets access to a street. It provides the missing connectivity that reduces travel distances and essentially transforms the parcels configuration to commonly known patterns of city building blocks that have access to streets on all sides. The resulting map reflects the changes in the physical layout of the blocks. The solution corresponding to the absolute minimum number of new streets could be impractical for the citizens themselves for the reason that it does not offer enough flexibility; however, it offers a good basis that is easily perceived by the users, in which they can develop and customize further. The process has been enriched by additional functionality that allows the users to exclude streets from the calculation and customize their priorities prior to the calculation based on what reflects their needs best. This is the kind of local knowledge that emerges from processes that allow active user engagement, and its value is immense for the reformation of the community.
The input required is a map of the properties in the community in a shape file format (.shp). The design system is articulated by specific front-end and back-end processes (Figure 18). The front-end processes are related to the display of the website based on user demand, which constitute the User Interface, and the back-end processes are related to the background processes needed for the calculation, such as reclustering calculation, queuing of tasks being performed, registering a user in a database, and creating a user profile. As the calculations could potentially demand a large amount of time to complete, asynchronous task queue/job queue “Celery” has been utilized to queue the tasks in real-time operation. “Openreblock” front-end processes use “Leaflet” and “Mapbox” libraries for the map display, whereas the back-end processes are built in “Jango” library.
“Openreblock” design system of processes (figure was created by the author).
In order to make the process of the calculation interactive, the steps are being displayed during the calculation, so the user can spot the new paths that are being generated gradually during the calculation. The user can also access and download any of the intermediate steps of the process. The algorithm estimates the location of existing paths and associated construction costs for new streets, making discussion, and comparison of alternative plans easy. It produces a new map that allows each home or workplace to have an address and to obtain urban services (Figure 19). Residents can adjust the tool to their needs by prioritizing processes and use the outcome as an alternative proposal for future replanning, in order to oppress the local government to consider their proposal. Users can optimize the process based on their priorities, such as cost minimization, exclusion of certain paths from the calculation, because they clash with landmarks and width of the new road network for circulation convenience. This allowance for customization is key for local resilience to climate change and socioeconomic development.
Cape Town example. Process of “reblocking.” New road network is gradually formed (graphic design by Stamen design).
Due to the staggering rise of technology, our ability to generate data far exceeds our capacity to comprehend the complexity that is entailed in the process of allocating the right kinds of data, analyzing it and finding meaningful connections between different data sets. As this has become one of the biggest challenges that planners are facing, it is important to employ innovative strategies and attempt to go beyond the conventions in data diagnostics. The core of this paper is devoted to an examination of direct or indirect user participation in understanding and pursuing social cohesion in the urban context.
In recent theoretical and policy debates concerning social correlation with the built environment, human participation has re-emerged as an important asset that could provide insight regarding the dynamics of urban space. In this context of renewal of interest in the local, social interactions, the deployment of notions such as, subjectivity, human scale, and temporality offer a critical review of constrained and narrow-sided methods of visualizing the dynamics of urban space solely from a top-down perspective, that of planners and stakeholders. Beyond its sociopolitical implications, participatory approach in urban planning aims to establish a framework toward a more resilient and sustainable environment that benefits both researchers and citizens. From the researcher’s perspective, the ability to visualize and analyze peoples desires and opinions that reflect their background allows for a culturally enhanced database that captures their common aspects and differences as it was demonstrated on the first case study.
The first case study aims to provide a calibrated understanding of the multiple grains of constructed space through top-down and bottom-up methodologies, as well as to offer a tool of visualizing dynamical characteristics of the urban environment. The research balances the traditional census data analysis with more dynamic layers of collective platforms and crowdsourcing. Whichever methodology is considered more or less descriptive of the reality, it is worth examining all the conduits and corridors available to us, by which changes in the urban context are being delivered.
The results of the three surveys were overlapped and weighted in order to produce a series of maps at different scales that visualize gentrification in the Bay Area. Each method described presents certain advantages. The census data analysis provides an overview of the context over a significant time span (2000–2012) and helps us understand major socioeconomic shifts. The open data analysis depicts the ephemeral layer of relationships that take place in the urban environment, which is impossible to be described by authoritative data; however, it is more relevant to the actual conditions, revealing user demands through open-source platforms. The third method enriches the process with cultural inputs are captured as data and user personal feedback about ranking the environment of a neighborhood as it currently stands. Looking at urban issues through maps can give us several hints about spatial and social transformations, in which we can think upon, as visualized information provokes feedback, either logical or emotional. Throughout this entire process, we can assess certain findings:
Based on the census data analysis, nearly half of the San Francisco Bay Area census tracts are undergoing some form of neighborhood transformation and displacement.
Although varied in their approaches, questions and results, one consistent finding across the three methods is that movers in gentrifying tracts were more likely to be higher income, college educated, and younger in age. This came down to depicting certain categories as indicative that the process of gentrification has already been underway: (a) shift in tenure, (b) influx of households interested in urban living, (c) increase in high-income serving amenities such as music clubs, coffee shops, galleries, etc, (d) rise of educational level.
The data accumulated from the open data research depict a significant artists’ movement regarding art studio rent requests, artwork sale, and creative services in general in the entire Bay Area and especially in San Francisco and Oakland. The San Francisco arts scene has historically overshadowed Oakland; however, in combination with the staggering rise of rent in San Francisco, we can anticipate that the artist movement will intensify in East Bay in a short timeframe.
Studying Oakland at a local street view scale, we can assess that the area is undergoing disperse development that presents high contradictions related to infrastructure condition, affordability, and safety. The results from the crowdsourcing survey vary significantly in building block scale; therefore, any sense of continuity of the same character because of proximity is not necessarily a criterion to rely upon (Figures 11–13).
Moreover, certain redeveloped areas have uniform functional identity, such as Emeryville, as they present excessive duplication of the most profitable uses (malls, restaurants), while San Francisco and Oakland downtowns present excessive duplication of financial functions (bank district).
We notice significant contradictions on the results of the crowed sourced research regarding infrastructure condition, safety, and affordability perception of the participants. Some of the findings depict areas of new development (last 3–4 years) that are yet islanded off because the surrounding area is significantly undermined. However, this contradiction reveals certain dynamics regarding the future, further redevelopment of the area, as well as the areas that accumulate similar features. If we combine the above with the data related to artists’ movement and the real estate requests associated with it, we can anticipate that the areas that are currently popular to the artist community will upgrade and the areas that are still undergoing reanesthetization (industrial, abandoned buildings) will follow (Figure 10).
This new establishment of relationships is replacing almost entirely the previous condition of gradual displacement and gentrification. It evolves rapidly, and although it looks more orderly, visually, as many areas are undergoing significant upgrading, this esthetic ordering might not have a social correlation. Social structure and social stability are inversely proportional to visual order. This condition is known to be establishing in Oakland, which was significantly undermined in the past few years; however, the challenge is not only to identify the problem but also to find the ways to analyze by mapping its characteristics and communicate it visually to its extents. Understanding the shifts of urban space and finding the patterns that drive them is a big challenge. We support that close engagement with users leads us to explore numerous research methods, which have a way of contributing to meaningful connections inside data networks. We find inspiration in the combination of the traditional ways of space categorization by investigating the relationship of home value, income, transportation, etc., with a bottom-up, participative approach in which individuals provide more ephemeral social elements of neighborhoods.
The second case study is a first step in designing a platform that showcases a social and vital problem of undeveloped slum communities. The primary aspect in designing this tool is to understand the problem through the citizens’ perspective, resonate it to a wider audience and formulate methods to represent it effectively.
At the moment, “Openreblock” platform computes and visualizes access to essential utilities such as water, energy, and sanitation at a building block level, along with showcasing how the lack of these may relate to risks or disasters faced by entire communities. The potential contribution of this platform could extend beyond a computational and visualization tool, into a powerful decision-making tool used by both policy makers and slum communities alike, with the objective to improve the lives of the communities through design and data, build partnerships with organizations that could bring innovative solutions and impact stakeholders’ strategies to become more tailored toward what is important for the communities.
From the citizens perspective, the ability to collect their own data, own the process of development, and reshape the urban fabric prompts the residents to participate in its evolvement and grow conscience and care for their neighborhood.
As the above case studies open the possibility to operate at a fine spatial scale, examining the city, and neighborhoods, block by block and building by building, they provide the context for a more fine-grained understanding of community characteristics, conflicts, and relationships that reveal the heterogeneous characteristics of the urban space. We argue that the key in improving policy-making is engaging community members to collaborate and take advantage of the available information, in order to become more active members in the society and become able to respond with their own creativity and capacity. From the researchers and planners perspective, the key would be to find ways to anticipate the infrastructural requirements of user involvement, come up with new tools and ideas that maximize the potential for cooperation, coordination, and creativity, while diminishing friction. The future goal would be to design for a convergence of trajectories of citizens, stakeholders, researchers, environment, and local authorities. This could be a first step toward the equalization of power and influence between citizens and stakeholders, which could lead in the collaborative construction of urban space and the understanding of the unique challenges that the city faces.
The first case study was initiated in the context of the University of California, Berkeley, during the Master of Architecture Program “Studio One: The Data Made Me Do It” 2014–2015, supervised by professor Kyle Steinfeld. The research was continued and concluded by the author at a later stage. The development and design of the digital platform in the second case study is a collaboration between the University of California, Berkeley, and the College of Environmental Design, Stamen Design in San Francisco and the Santa Fe Institute. Contributors from University of Californi, Berkeley, are Nicolas de Monchaux, Carlos Sandoval Olascoaga, Wenzhe Peng, and Eleanna Panagoulia. Design by the Stamen design and technology studio. The source for this site and the topology algorithm can be viewed on GitHub.
The authors declare no conflict of interest.
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