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Frontiers in Psychiatry 2021Obsessive compulsive disorder (OCD) can manifest as a debilitating disease with high degrees of co-morbidity as well as clinical and etiological heterogenity. However,... (Review)
Review
Obsessive compulsive disorder (OCD) can manifest as a debilitating disease with high degrees of co-morbidity as well as clinical and etiological heterogenity. However, the underlying pathophysiology is not clearly understood. Computational psychiatry is an emerging field in which behavior and its neural correlates are quantitatively analyzed and computational models are developed to improve understanding of disorders by comparing model predictions to observations. The aim is to more precisely understand psychiatric illnesses. Such computational and theoretical approaches may also enable more personalized treatments. Yet, these methodological approaches are not self-evident for clinicians with a traditional medical background. In this mini-review, we summarize a selection of computational OCD models and computational analysis frameworks, while also considering the model predictions from a perspective of possible personalized treatment. The reviewed computational approaches used dynamical systems frameworks or machine learning methods for modeling, analyzing and classifying patient data. Bayesian interpretations of probability for model selection were also included. The computational dissection of the underlying pathology is expected to narrow the explanatory gap between the phenomenological nosology and the neuropathophysiological background of this heterogeneous disorder. It may also contribute to develop biologically grounded and more informed dimensional taxonomies of psychopathology.
PubMed: 34658945
DOI: 10.3389/fpsyt.2021.687062 -
Nanomaterials (Basel, Switzerland) Jul 2022As the demands for improved performance of integrated circuit (IC) chips continue to increase, while technology scaling driven by Moore's law is becoming extremely... (Review)
Review
As the demands for improved performance of integrated circuit (IC) chips continue to increase, while technology scaling driven by Moore's law is becoming extremely challenging, if not impractical or impossible, heterogeneous integration (HI) emerges as an attractive pathway to further enhance performance of Si-based complementary metal-oxide-semiconductor (CMOS) chips. The underlying basis for using HI technologies and structures is that IC performance goes well beyond classic logic functions; rather, functionalities and complexity of smart chips span across the full information chain, including signal sensing, conditioning, processing, storage, computing, communication, control, and actuation, which are required to facilitate comprehensive human-world interactions. Therefore, HI technologies can bring in more function diversifications to make system chips smarter within acceptable design constraints, including costs. Over the past two decades or so, a large number of HI technologies have been explored to increase heterogeneities in materials, technologies, devices, circuits, and system architectures, making it practically impossible to provide one single comprehensive review of everything in the field in one paper. This article chooses to offer a topical overview of selected HI structures that have been validated in CMOS platforms, including a stacked-via vertical magnetic-cored inductor structure in CMOSs, a metal wall structure in the back end of line (BEOL) of CMOSs to suppress global flying noises, an above-IC graphene nano-electromechanical system (NEMS) switch and nano-crossbar array electrostatic discharge (ESD) protection structure, and graphene ESD interconnects.
PubMed: 35889564
DOI: 10.3390/nano12142340 -
Freshwater suspended particulate matter-Key components and processes in floc formation and dynamics.Water Research Jul 2022Freshwater suspended particulate matter (SPM) plays an important role in many biogeochemical cycles and serves multiple ecosystem functions. Most SPM is present as... (Review)
Review
Freshwater suspended particulate matter (SPM) plays an important role in many biogeochemical cycles and serves multiple ecosystem functions. Most SPM is present as complex floc-like aggregate structures composed of various minerals and organic matter from the molecular to the organism level. Flocs provide habitat for microbes and feed for larger organisms. They constitute microbial bioreactors, with prominent roles in carbon and inorganic nutrient cycles, and transport nutrients as well as pollutants, affecting sediments, inundation zones, and the ocean. Composition, structure, size, and concentration of SPM flocs are subject to high spatiotemporal variability. Floc formation processes and compositional or morphological dynamics can be established around three functional components: phyllosilicates, iron oxides/(oxy)hydroxides (FeOx), and microbial extracellular polymeric substances (EPS). These components and their interactions increase heterogeneity in surface properties, enhancing flocculation. Phyllosilicates exhibit intrinsic heterogeneities in surface charge and hydrophobicity. They are preferential substrates for precipitation or attachment of reactive FeOx. FeOx form patchy coatings on minerals, especially on phyllosilicates, which increase surface charge heterogeneities. Both, phyllosilicates and FeOx strongly adsorb natural organic matter (NOM), preferentially certain EPS. EPS comprise various substances with heterogeneous properties that make them a sticky mixture, enhancing flocculation. Microbial metabolism, and thus EPS release, is supported by the high adsorption capacity and favorable nutrient composition of phyllosilicates, and FeOx supply essential Fe.
Topics: Ecosystem; Flocculation; Fresh Water; Minerals; Particulate Matter; Sewage; Waste Disposal, Fluid
PubMed: 35665676
DOI: 10.1016/j.watres.2022.118655 -
Frontiers in Oncology 2023Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and... (Review)
Review
Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.
PubMed: 37265795
DOI: 10.3389/fonc.2023.1170264 -
Advanced Science (Weinheim,... Feb 2022Intratumor heterogeneity (ITH) stands as one of the main difficulties in the treatment of colorectal cancer (CRC) as it causes the development of resistant clones and...
Intratumor heterogeneity (ITH) stands as one of the main difficulties in the treatment of colorectal cancer (CRC) as it causes the development of resistant clones and leads to heterogeneous drug responses. Here, 12 sets of patient-derived organoids (PDOs) and cell lines (PDCs) isolated from multiple regions of single tumors from 12 patients, capturing ITH by multiregion sampling of individual tumors, are presented. Whole-exome sequencing and RNA sequencing of the 12 sets are performed. The PDOs and PDCs of the 12 sets are also analyzed with a clinically relevant 24-compound library to assess their drug responses. The results reveal unexpectedly widespread subregional heterogeneity among PDOs and PDCs isolated from a single tumor, which is manifested by genetic and transcriptional heterogeneity and strong variance in drug responses, while each PDO still recapitulates the major histologic, genomic, and transcriptomic characteristics of the primary tumor. The data suggest an imminent drawback of single biopsy-originated PDO-based clinical diagnosis in evaluating CRC patient responses. Instead, the results indicate the importance of targeting common somatic driver mutations positioned in the trunk of all tumor subregional clones in parallel with a comprehensive understanding of the molecular ITH of each tumor.
Topics: Colonic Neoplasms; Genomics; Humans; Organoids; Sequence Analysis, RNA; Exome Sequencing
PubMed: 34918496
DOI: 10.1002/advs.202103360 -
Microbiology Spectrum Feb 2022Elucidating phenotypic heterogeneity in clonal bacterial populations is important for both the fundamental understanding of bacterial behavior and the synthetic...
Elucidating phenotypic heterogeneity in clonal bacterial populations is important for both the fundamental understanding of bacterial behavior and the synthetic engineering of bacteria in biotechnology. In this study, we present and validate a high-throughput and high-resolution time-lapse fluorescence microscopy-based strategy to easily and systematically screen for heterogeneously expressed genes in the Bacillus subtilis model bacterium. This screen allows detection of expression patterns at high spatial and temporal resolution, which often escape detection by other approaches, and can readily be extrapolated to other bacteria. A proof-of-concept screening in B. subtilis revealed both recognized and yet unrecognized heterogeneously expressed genes, thereby validating the approach. Differential gene expression among isogenic siblings often leads to phenotypic heterogeneity and the emergence of complex social behavior and functional capacities within clonal bacterial populations. Despite the importance of such features for both the fundamental understanding and synthetic engineering of bacterial behavior, approaches to systematically map such population heterogeneity are scarce. In this context, we have elaborated a new time-lapse fluorescence microscopy-based strategy to easily and systematically screen for such heterogeneously expressed genes in bacteria with high resolution and throughput. A proof-of-concept screening in the Bacillus subtilis model bacterium revealed both recognized and yet unrecognized heterogeneously expressed genes, thereby validating our approach.
Topics: Bacillus subtilis; Bacterial Proteins; Gene Expression Regulation, Bacterial; High-Throughput Screening Assays; Microscopy, Fluorescence; Time-Lapse Imaging
PubMed: 35171018
DOI: 10.1128/spectrum.02045-21 -
BMC Bioinformatics Jun 2018The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues....
BACKGROUND
The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues.
RESULTS
Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database.
CONCLUSIONS
HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.
Topics: Cells; Computational Biology; Databases, Factual; Gene Expression Profiling; Gene Regulatory Networks; Genetic Heterogeneity; Humans; Organ Specificity; Phenotype; Transcription Factors; Transcriptome
PubMed: 29940845
DOI: 10.1186/s12859-018-2190-6 -
The Journal of Clinical Investigation Aug 2022Chimeric antigen receptor (CAR) T cell therapies targeting single antigens have performed poorly in clinical trials for solid tumors due to heterogenous expression of...
Chimeric antigen receptor (CAR) T cell therapies targeting single antigens have performed poorly in clinical trials for solid tumors due to heterogenous expression of tumor-associated antigens (TAAs), limited T cell persistence, and T cell exhaustion. Here, we aimed to identify optimal CARs against glypican 2 (GPC2) or CD276 (B7-H3), which were highly but heterogeneously expressed in neuroblastoma (NB), a lethal extracranial solid tumor of childhood. First, we examined CAR T cell expansion in the presence of targets by digital droplet PCR. Next, using pooled competitive optimization of CAR by cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), termed P-COCC, we simultaneously analyzed protein and transcriptome expression of CAR T cells to identify high-activity CARs. Finally, we performed cytotoxicity assays to identify the most effective CAR against each target and combined the CARs into a bicistronic "OR" CAR (BiCisCAR). BiCisCAR T cells effectively eliminated tumor cells expressing GPC2 or CD276. Furthermore, the BiCisCAR T cells demonstrated prolonged persistence and resistance to exhaustion when compared with CARs targeting a single antigen. This study illustrated that targeting multiple TAAs with BiCisCAR may overcome heterogenous expression of target antigens in solid tumors and identified a potent, clinically relevant CAR against NB. Moreover, our multimodal approach integrating competitive expansion, P-COCC, and cytotoxicity assays is an effective strategy to identify potent CARs among a pool of candidates.
Topics: Antigens, Neoplasm; B7 Antigens; Cell Line, Tumor; Glypicans; Humans; Immunotherapy, Adoptive; Neuroblastoma; Receptors, Antigen, T-Cell; Receptors, Chimeric Antigen; Xenograft Model Antitumor Assays
PubMed: 35852863
DOI: 10.1172/JCI155621 -
Scientific Reports May 2023Atrial fibrillation (AF) is the commonest cardiac arrhythmia, affecting 3 million people in the USA and 8 million in the EU (according to the European Society of...
Atrial fibrillation (AF) is the commonest cardiac arrhythmia, affecting 3 million people in the USA and 8 million in the EU (according to the European Society of Cardiology). So, why is it that even with the best medical care, around a third of the patients are treatment resistant. Extensive research of its etiology showed that AF and its mechanisms are still debatable. Some of the AF origins are ascribed to functional and ionic heterogeneities of the heart tissue and possibly to additional triggering agents. But, have all AF origins been detected? Are all accepted origins, in fact, arrhythmogenic? In order to study these questions and specifically to check our new idea of intermittency as an arrhythmogenesis agent, we chose to employ a mathematical model which was as simple as possible, but which could still be used to observe the basic network processes of AF development. At this point we were not interested in the detailed ionic propagations nor in the actual shapes of the induced action potentials (APs) during the AF outbreaks. The model was checked by its ability to exactly recapture the basic AF developmental stages known from experimental cardiac observations and from more elaborate mathematical models. We use a simple cellular automata 2D mathematical model of N × N matrices to elucidate the field processes leading to AF in a tissue riddled with randomly distributed heterogeneities of different types, under sinus node operation, simulated by an initial line of briefly stimulated cells inducing a propagating wave, and with or without an additional active ectopic action potential pulse, in turn simulated by a transitory operation of a specific cell. Arrhythmogenic contributions, of three different types of local heterogeneities in myocytes and their collaborations, in inducing AF are examined. These are: a heterogeneity created by diffuse fibrosis, a heterogeneity created by myocytes having different refractory periods, and a new heterogeneity type, created by intermittent operation of some myocytes. The developmental stages (target waves and spirals) and the different probabilities of AF occurring under each condition, are shown. This model was established as being capable of reproducing the known AF origins and their basic development stages, and in addition has shown: (1) That diffuse fibrosis on its own is not arrhythmogenic but in combination with other arrhythmogenic agents it can either enhance or limit AF. (2) In general, combinations of heterogeneities can act synergistically, and, most importantly, (3) The new type of intermittency heterogeneity proves to be extremely arrhythmogenic. Both the intermittency risk and the fibrosis role in AF generation were established. Knowledge of the character of these arrhythmogenesis agents can be of real importance in AF treatment.
Topics: Humans; Atrial Fibrillation; Sinoatrial Node; Cardiac Conduction System Disease; Muscle Cells; Cardiovascular Agents; Fibrosis; Heart Atria; Action Potentials; Myocytes, Cardiac
PubMed: 37165085
DOI: 10.1038/s41598-023-33438-y -
Ecology and Evolution Jul 2022The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade-off between digestibility and biomass in forage by selecting vegetation at...
The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade-off between digestibility and biomass in forage by selecting vegetation at intermediate growth. The green wave hypothesis (GWH) extends the FMH to suggest how spatiotemporal heterogeneity in plant quality shapes migratory movements of herbivores. Growing empirical support for these hypotheses mainly comes from studies in vast landscapes with large-scale habitat heterogeneity. It is unclear, however, to what extent ungulates surf green waves in human-altered landscapes with small-scale heterogeneity in terms of land use and topography. We used plant phenological proxies derived from Sentinel 2 satellite data to analyze the habitat selection of 93 collared red deer () in montane and alpine habitats. Using a step selection analysis, we investigated how plant phenology, that is, the instantaneous rate of green-up (IRG) and normalized difference vegetation index (NDVI), and a set of variables describing topography and human presence influenced red deer resource selection in open habitats. We learned that red deer selected areas with high biomass at green-up and avoided habitats with possible exposure to human activity. Additionally, landscape structure and topography strongly influenced spatial behavior of red deer. We further compared cumulative access to high-quality forage across migrant strategies and found migrants gained better access than residents. Many migratory individuals surfed the green wave, and their surfing behavior, however, became less pronounced with decreasing distance to settlements. Within the constraints of topography and human land use, red deer track spring green-up on a fine spatiotemporal scale and follow the green wave across landscapes in migration movements. Thus, they benefit from high-quality forage even in human-dominated landscapes with small-scale heterogeneity and vegetation emerging in a heterogenic, dynamic mosaic.
PubMed: 35813904
DOI: 10.1002/ece3.9048