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PubMed2026

Shared genetic architecture and therapeutic targets across paediatric immune-mediated diseases.

OBJECTIVES: Paediatric-onset immune-mediated inflammatory diseases (IMIDs), including juvenile idiopathic arthritis and related rheumatic diseases, remain genetically undercharacterised. We aimed to define shared and category-specific genetic architecture across paediatric IMIDs, compare signals with adult IMIDs, and identify therapeutic opportunities. METHODS: We analysed 24 paediatric IMIDs classified as autoimmune, polygenic-autoinflammatory, mixed-pattern, or allergic. Genome-wide association analyses included 18,086 cases and 131,019 controls of European ancestry. We estimated single nucleotide polymorphism (SNP)-based heritability, genetic correlations, and polygenic overlap; performed subset-based meta-analysis; and conducted functional annotation, gene prioritisation, pathway and protein network analyses, adult-IMID comparison, and drug-target prioritisation. RESULTS: SNP-based heritability ranged from 28.9% for allergic IMIDs to 61.9% for autoimmune IMIDs. Genetic correlation and polygenic modelling supported partial sharing across categories with category-specific components. Meta-analysis identified 39 genome-wide significant loci outside the Major Histocompatibility Complex (MHC) region, including 15 previously unreported loci; 19 loci were shared between categories. Gene-prioritisation and protein interaction analyses identified a core MHC-centred antigen-presentation network, with category-enriched modules involving complement, innate/barrier pathways, epithelial biology, and type 2 immunity. Enriched pathways included nuclear factor κB signalling, T helper 17 related pathways, Janus kinase-signal transducer and activator of transcription signalling, programmed cell death protein 1/programmed death‑ligand 1, cytotoxic T‑lymphocyte associated protein 4 regulation, and osteoclast differentiation, several of which are relevant to rheumatic diseases. Paediatric IMIDs shared broad polygenic architecture with adult IMIDs, whereas top-ranked genes converged strongly with adult rheumatic diseases. Priority Index analysis identified 178 high-scoring genes, including 43 approved or investigational IMID drug targets. CONCLUSIONS: Paediatric-onset IMIDs share core pathways with adult forms but exhibit distinct genetic architecture shaped by age-specific immune and neurodevelopmental biology. These findings provide a genomic framework for paediatric precision medicine, guiding classification, risk prediction, and therapeutic development.

Humans↗
PubMed1976

The structure of kinetoplast DNA. 2. Characterization of a novel component of high complexity present in the kinetoplast DNA network of Crithidia luciliae.

1. Degradation of highly purified kinetoplast DNA (kDNA) networks with restriction endonucleases yields "extra" bands in agarose gels that are absent from digests of mini-circles. Each of the five endonucleases tested, i.e. AluI, HapII, EcoRI, Hsu and HindII + III, yields a unique set of "extra" bands. The "extra" bands consist of linear DNA; they are not mini-circle oligomers and their added molecular weight, calculated from mobility in gels, are around 2 X 10(7). Double digests with two restriction endonucleases yield a new set of "extra" bands, showing that the "extra" bands obtained with different enzymes are all derived from the same complex component of kDNA. In digests of 32P-labelled kDNA an average of 2.3% of the radioactivity is recovered in the "extra" bands. 2. Treatment of kDNA networks with the single-strand-specific S1 nuclease of Aspergillus oryzae preferentially releases a linear DNA with a molecular weight of 26 X 10(6), calculated from mobility in gels. We present evidence that the 'extra' bands obtained with restriction endonucleases are derived from this component. 3. DNA-DNA renaturation analysis of fragmented kDNA shows the presence of a minor complex component with a complexity of about 3 X 10(7), making up less than 10% of the total kDNA. 4. From these results we conclude that 3--5% of the kDNA consists of a homogeneous class of maxi-circles catenated in the mini-circle network. The molecular weight of these maxi-circles is about 26 X 10(6) and they contain a unique, non-repetitive, non-mini-circle nucleotide sequence. This component is a prime candidate for the true mitochondrial DNA of trypanosomes.

Animals↗
PubMed1975

Neurons from fetal rat brain in a new cell culture system: a multidisciplinary analysis.

A new culture system for cells from the mammalian brain was developed by a modification of a previously established technique. This modification involved the use of fluorodeoxyuridine and adult horse serum. The cultures contained large, easily visualized neurons both isolated from other neurons and in networks of varying complexity. These cells were large enough to permit reliable intracellular electrophysiologic recording and were often sufficiently dispersed to allow examination of membrane responses to iontophoretically applied neurotransmitter candidates. Many responses characteristic of central neurons in situ were seen, including evoked and spontaneous action potentials, complex patterns of inhibitory and excitatory post-synaptic potentials, and neurotransmitter-induced membrane responses. These preparations were examined by phase contrast microscopy, by light microscopy after silver impregnation and by Nomarski interference optics. Total choline acetyltransferase (CAT) activity was little changed and specific activity was increased in the new culture system as compared with the earilier system. Conditions which gave the highest specific activity of CAT also provided the best cultures from the standpoint of electrophysiologic and morphologic analysis. This new approach will allow, in culture, detailed multidisciplinary analyses of individual neurons and small networks of neurons from the mammalian brain.

Acetylcholine↗
PubMed2025

Transmission of extended spectrum β-lactamase-producing Escherichia coli and antimicrobial resistance gene flow across One Health compartments in eastern Africa: a whole-genome sequence analysis from a prospective cohort study.

BACKGROUND: The One Health paradigm considers interdependence of human, animal, and environmental health. However, there is little evidence from high-income countries to support the importance of a One Health approach to addressing spread of antimicrobial resistance (AMR). Given AMR is a global threat, understanding how the close interactions of humans with animals and the environment in low-income settings affect the spread of AMR is important. We aimed to investigate diversity and transmission of extended spectrum β-lactamase (ESBL)-producing Escherichia coli across household-linked One Health compartments using genomic data. METHODS: We sequenced whole genomes of ESBL-producing E coli isolates from humans, animals, and the environment from a prospective, longitudinal cohort study conducted in Malawi (April 29, 2019, to Dec 3, 2020) and Uganda (July 16, 2020, to Aug 6, 2021). In the cohort study, 259 households were enrolled at baseline in Malawi and 92 in Uganda from a mix of urban, peri-urban, and rural areas. Households were followed up at months 1, 3, and 6 in Malawi and at months 1, 2, and 4 in Uganda. Samples collected at each visit included human and animal stool, environmental samples from hand-contact areas, food, and water, and broader environmental samples such as river water. Samples were cultured in buffered peptone water and then ESBL chromogenic agar to isolate ESBL-producing E coli. ESBL-producing E coli isolates underwent whole-genome sequencing. We performed phylogenetic analyses, and in-silico multi-locus sequence typing, characterised AMR determinants and linked genotypes with sample location, ecological source, and other covariates. We performed fine-scale single nucleotide polymorphism (SNP) and network analysis to infer strain and plasmid transmission across ecological compartments. The primary outcome was colonisation with ESBL-producing E coli. Secondary outcomes were genomic clusters and ESBL genomic determinants within and between One Health compartments. FINDINGS: We found high diversity of ESBL-producing E coli, with 170 sequence types and 166 genomic clusters identified from 2344 genomes, including 1814 genomes from Malawi (907 human, 221 animal, and 686 environmental) and 530 genomes from Uganda (380 human, 147 animal, and three environmental). Sequence type (ST)131 dominated in Malawi (209 [11·5%] of 1814 genomes), and ST10 dominated in Uganda (45 [8·5%] of 530 genomes). Common ESBL genes blaCTX-M-15 (1604 [68·4%] of 2344 genomes) and blaCTX-M-27 (336 [14·3%] of 2344 genomes) were carried on a complex network of 55 and 30 different plasmids. This diversity of plasmids presented multiple pathways for dissemination and revealed high force of selection. Phylogenetic analyses revealed common intermixing of isolates between humans, animals, and the environment. SNP transmission analysis revealed ecologically overlapping clusters, suggesting ESBL-producing E coli co-circulation both within and between compartments with frequent spillover events. Applying a five-SNP threshold, we inferred 463 human-environment transmission events, 146 human-animal events, and 142 animal-environment events. INTERPRETATION: Our work suggests that a One Health approach is crucial to addressing AMR in eastern Africa. Improving water, sanitation, and hygiene systems will create a safer environment, reduce spillovers of AMR bacteria between compartments, and eventually reduce AMR reservoirs in the environment and in animals. FUNDING: Medical Research Council, National Institute for Health and Care Research, and Wellcome Trust.

Humans↗
PubMed2026

Functional analysis of Candida albicans protein kinases identifies Crk1 as a modulator of epithelial cell damage.

UNLABELLED: The commensal and pathogenic lifestyles of the opportunistic fungal pathogen Candida albicans require complex signaling networks regulated by protein kinases. To investigate the role of C. albicans protein kinases at the intestinal epithelial interface, we screened a comprehensive protein kinase deletion library for the capacity of the mutants to damage intestinal epithelial cells (IEC). Mutants showing altered IEC cytotoxicity relative to the wild type were further analyzed for their growth and morphology, focusing on hyper-damaging strains to identify kinases that rather prevent host cell damage. Deletion of CRK1 caused increased IEC-specific damage, despite slower growth, reduced hyphal length, and reduced adhesion as compared to wild-type cells. While tissue invasion levels and the formation of transcellular tunnels of the crk1Δ/Δ mutant were increased, the translocation capacity through the IEC barrier was reduced. Transcriptional and metabolic profiling suggested a role for Crk1 in metabolic adaptation to carbon and nitrogen sources, which was validated by showing that high glucose and amino acids are required for crk1Δ/Δ to cause increased IEC damage. Deletion of CRK1 rendered C. albicans more susceptible to cell wall and membrane stressors, but caused higher resistance to a catalase-specific and histidine biosynthesis inhibitor. This phenotypic pattern of medium- and epithelial cell type-specific cytotoxicity displayed by a C. albicans protein kinase mutant suggests that Crk1 regulates processes linked to carbon and amino acid metabolism that are relevant to interactions with intestinal epithelial cells. IMPORTANCE: Microbial signal transduction pathways regulate adaptation to changing environmental conditions and facilitate the success of many microbes during interactions with their hosts. The fungal pathobiont Candida albicans exists as a harmless commensal on mucosal surfaces of most humans but can also cause superficial and invasive infections under certain circumstances. Both lifestyles require complex signaling networks, predominantly regulated by protein kinases. The C. albicans genome was predicted to encode 108 protein kinases, yet nearly 50% remain uncharacterized. We aimed to dissect the role of C. albicans protein kinases during the transition from commensal to pathogen. We showed that multiple protein kinase genes are involved in epithelial cell damage. Particularly, the protein kinase gene Crk1 was of interest because deletion of CRK1 caused increased damage to intestinal epithelial cells under distinct conditions. Our study links Crk1 with regulation of metabolic processes relevant for commensalism and pathogenicity of C. albicans.

Candida albicans↗
PubMed2026

Toward Class Imbalance and Uncertainty in Powder XRD Analysis: A Dual-Channel Fusion Network for Space Group Classification.

Accurate identification of space groups from powder X-ray diffraction (pXRD) is essential for understanding crystal structures and accelerating materials discovery. However, this task remains highly challenging due to inherent peak overlap, experimental noise, and the complexity of the 230-class classification problem. To address the critical issues of class imbalance and data scarcity, we first design a general physics-informed data augmentation pipeline. We then propose a dual-channel fusion uncertainty-aware network (DFUN) for automated space group classification. The DFUN architecture integrates two complementary feature representations: convolutional features extracted directly from raw diffraction profiles and domain-specific peak descriptors. These distinct representations are adaptively fused through a gating mechanism. Furthermore, to mitigate the inherent long-tailed distribution of crystallographic data, we employ a hybrid loss function that combines Focal Loss with Label Smoothing. Finally, we incorporate Monte Carlo Dropout to provide predictive uncertainty estimation, thereby enabling not only accurate classification but also a crucial assessment of the model's reliability. Evaluated on large-scale simulated data and two public data sets (opXRD and RRUFF), DFUN outperforms the evaluated baseline methods across the reported metrics. The framework also provides uncertainty-aware predictions, establishing DFUN as a robust and interpretable solution for high-throughput automated crystallographic analysis from powder diffraction.

Uncertainty↗
PubMed1977

Heterogeneity of the kinetoplast DNA molecules of Trypanosoma cruzi.

Kinetoplast DNA (kDNA) of the culture form of Trypanosoma cruzi is cleaved by restriction endonucleases (HpaII, HindII, EcoRI, and HaeIII). The analysis of the cleavage patterns proves that the minicircles (free circulargenome units) are heterogeneous in base sequences. The same results are obtained with the complex kDNA network which is composed of the association of minicircles and linear molecules. Kinetic studies of the renaturation of kDNA previously cleaved by HpaII into fragments of the genome unit size show at least two populations of molecules. About 75% of these molecules correspond to the fast renaturing population having the molecular complexity of the minicircles. The molecules of the slow renaturing population have a much higher molecular complexity than the minicircles and do not seem to be related to the majority of the long linear molecules.

Chemical Phenomena↗
PubMed1979

Health-seeking behavior and social networks of the aged living in single-room occupancy hotels.

The elderly who reside in single-room occupancy (SRO) hotels often have been depicted as "isolates," lacking the interest or ability to engage primary or secondary support systems. This characterization has not enhanced understanding of how the SRO aged are able to survive in the community. With the use of network analysis techniques, this study demonstrates the inaccuracy of the assertion that these old persons lack significant social support. The data pointed to differences in network size, complexity, intensity, connectedness, and directionality in relation to varying degrees of physical and psychiatric health.

Aged↗
PubMed1979

[Quantitation of myelofibrosis in blood diseases by electronic image analysis (author's transl)].

Normal and pathologic reticulin networks colored black by silver nitrate can be automatically quantitated by electronic image analysis. By using this technique, different parameters can be obtained, such as the average density, the surface of network meshes, the thickness of the fibers, the complexity of the reticulum, and the heterogeneity of the myelofibrosis distribution. All of these parameters were obtained in 83 osteomedullar biopsies of blood diseases (primary splenomegaly, chronic myeloid leukemia, polycythermia vera, acute leukemia, and aplastic anemia). We have shown that there is no relation between the different parameters obtained and the medullary richness, hematopoietic center, or patient survival. On the other hand, the histomorphometric parameters can be used to distinguish acute leukemia and chronic myeloid leukemia myelofibrosis, while the parameters in primary splenomegaly are shown to be very heterogeneous.

Acute Disease↗
PubMed1992

Isolated cells in the study of the molecular mechanisms of reperfusion injury.

Isolated cells make it possible to study mechanisms of cell and tissue injury under well-defined conditions, including the interaction of different cells in coculture experiments. Isolated cells, either in suspension or in monolayer cultures, have also been used to study the mechanism of reperfusion injury--in this case better termed as reoxygenation injury in view of the experimental approach taken. In hepatocytes, Kupffer, and endothelial cells, reoxygenation injury resulted in necrosis primarily mediated by reactive oxygen species released by various sources such as mitochondria (hepatocytes) and NADPH oxidase (Kupffer cells). In contrast, contracture was a characteristic feature of reoxygenation injury occurring in cardiomyocytes without loss of cytosolic enzymes. Beside reactive oxygen species, Kupffer cells were activated to release prostanoids and a decrease in endothelial cell-mediated fibrinolysis occurred upon reoxygenation. Reoxygenation injury in endothelial cells was significantly increased when neutrophils were added at the time of reoxygenation, presumably due to additional generation of reactive oxygen species and the release of proteases. As exemplified for the liver, these experiments suggest a mechanism of reperfusion injury in which the various cell types of a given tissue differ significantly in their response to hypoxia-reoxygenation but in which they interact with each other in a complex pathobiochemical network via various mediators such as cytokines, and tissue damaging effector molecules such as reactive oxygen species. Future experiments with isolated cells will allow detailed analysis of the underlying molecular mechanisms.

Cells, Cultured↗
PubMed2022

A graph-based approach for the visualisation and analysis of bacterial pangenomes.

BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. RESULTS: Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. CONCLUSIONS: We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data.

Bacteria↗
PubMed2025

FACS-Proteomics strategy toward extracellular vesicles single-phenotype characterization in biological fluids: exploring the role of leukocyte-derived EVs in multiple sclerosis.

BACKGROUND: The isolation and proteomics characterization of extracellular vesicles (EVs) from body fluids is challenging due to their vast heterogeneity. We have recently demonstrated that Fluorescence-activated Cell Sorting (FACS) efficiently isolates the whole EV circulating compartment directly from untouched body fluids enabling a comprehensive EV proteomics analysis. RESULTS: Here, we characterized, for the first time, a single-phenotype EV subset by sorting leukocyte-derived EVs (Leuko EVs) from peripheral blood and tears of healthy volunteers. Using an optimized and patented staining protocol of the whole EV compartment we identified and excluded non-EV particles, debris and damaged EVs. We further isolated, using an anti-CD45 antibody, Leuko EVs (CD45+ EVs), reaching a high level of purity (> 90%). Purified Leuko EVs were characterized using atomic force microscopy, nanoparticle tracking, and shotgun proteomics analysis revealing a similar coded protein cargo in both biological fluids. Subsequently, the same workflow was applied to tears from Relapsing-Remitting Multiple Sclerosis (RRMS) patients, revealing a Leuko EVs protein cargo enrichment that reflects the neuroinflammatory condition characteristics of RRMS. This enrichment was evidenced by the activation of upstream regulators TGFB1 and NFE2L2, which are associated with inflammatory responses. Additionally, the analysis identified markers indicative of endothelial cell proliferation and the development of enhanced vascular networks, with AGNPT2 and VEGF emerging as activated upstream regulators. These findings indicate the complex interplay between inflammation and angiogenesis in RRMS. CONCLUSIONS: In conclusion, our combined FACS-Proteomics strategy offers a promising approach for biomarker discovery, analysing cell-specific EV phenotypes directly from untouched body fluids, advancing the clinical value of tears EVs and improving the understanding of EV-mediated processes in vivo. Data are available via ProteomeXchange with the identifier PXD049036 and in EV-TRACK knowledgebase with ID: EV240150.

Humans↗
PubMed2026

Genes associated with translation and oxidative phosphorylation as components of the translational response in nodulated and water-restricted soybean.

BACKGROUND: Soybean primarily acquires nitrogen through symbiosis with nitrogen-fixing bacteria. Water deficit (WD) is a major stress limiting crop yield. Nodulation may enhance drought tolerance in legumes by modulating nitrogen and hormone metabolism, osmotic adjustment, and antioxidant defenses; however, the molecular basis underlying the differential WD responses between N-fix and N-fed plants remain unclear. Translational control of gene expression is a key regulatory mechanism during stress. RESULTS: We compared the transcriptome and translatome of soybean roots from N-fix and N-fed plants exposed to WD across four combined treatments. N-fix plants under WD exhibited more complex responses in terms of total differentially expressed genes (DEGs) compared to N-fed plants. This increased complexity was also evident among translationally regulated DEGs and differentially expressed transcription factors, whose involvement in WD responses of N-fix plants is novel. Co-expression network analysis identified modules associated with core biological processes encompassing nodulation, WD, and notably, their interplay was particularly prominent in Module 1, which was enriched in genes related to ribosomal protein synthesis and oxidative phosphorylation (OXPHOS). Guilt-by-Association analysis enabled the prediction of novel functions for differentially expressed, uncharacterized hub genes related to stress and/or nodulation responses. CONCLUSIONS: Translational regulation of genes involved in OXPHOS and translation initiation emerged as a central response in N-fix plants under WD. These findings reveal distinct molecular adaptations in N-fix soybean roots facing WD and highlight translational control as a key regulatory layer. We also identified promising candidate genes-including transcription factors and uncharacterized hub genes under translational regulation-that represent potential targets for improving drought tolerance in legumes once validated functionally.

Glycine max↗
PubMed2025

Target and biomarker exploration portal for drug discovery.

MOTIVATION: The discovery of novel drug targets and precision biomarkers remains a major challenge in drug development, with traditional differential expression analysis often overlooking key regulatory proteins. Here, we present a novel, web-based bioinformatics tool, the Target and Biomarker Exploration Portal (TBEP), designed to accelerate the drug discovery process by integrating large-scale biomedical data with network analysis techniques. RESULTS: TBEP harnesses machine-learning approaches to mine and combine multimodal datasets, including human genetics, functional genomics, and protein-protein interaction networks, to decode causal disease mechanisms and uncover novel therapeutic targets and precision biomarkers for specific phenotypes. A unique feature of the tool is its ability to process large-scale data in real-time, facilitated by an efficient cloud-based architecture. Additionally, the tool incorporates an integrated large language model (LLM), which assists researchers in exploring and interpreting complex biological relationships within the generated networks and multi-omics data using natural language (English). By offering an intuitive, interactive interface, the LLM enhances the exploration of biological insights, making it easier for scientists to derive actionable conclusions. This powerful integration of network analysis, multi-omics data, and LLM provides a robust framework for accelerating the identification of novel drug targets. AVAILABILITY AND IMPLEMENTATION: The tool is publicly available at https://tbep.missouri.edu. The source code, documentation and installation instructions are available at GitHub repository: https://github.com/mizzoudbl/tbep.

Drug Discovery↗
PubMed2025

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

MOTIVATION: Gene-environment (G-E) interaction analysis is crucial in cancer research, offering insights into how genetic and environmental factors jointly influence cancer outcomes. Most existing G-E interaction methods are regression-based, which may lack flexibility to capture complex data patterns. Recent advances have investigated deep neural network-based G-E models. However, these methods may be more vulnerable to information deficiency due to challenges such as limited sample size and high dimensionality. Apart from genetic and environmental data, pathological images have emerged as a widely accessible and informative resource for cancer modeling, presenting its potential to enhance G-E modeling. RESULTS: We propose the pathological imaging-assisted neural additive model for G-E analysis (GE-IA-NAM). The flexible and interpretable additive network architecture is adopted to account for individualized effects associated with genetic factors, environmental factors, and their interactions. To improve G-E modeling, an assisted-learning strategy is investigated, which adopts a joint analysis to integrate information from pathological images. Simulations and the analysis of lung and skin cancer datasets from The Cancer Genome Atlas demonstrate the competitive performance of the proposed method. AVAILABILITY AND IMPLEMENTATION: Python code implementing the proposed method is available at https://github.com/Mr-maoge/NAM-IA-GE. The data that support the findings in this article are openly available in TCGA (The Cancer Genome Atlas) at https://portal.gdc.cancer.gov/.

Gene-Environment Interaction↗
PubMed1992

Evolution of the capsid protein genes of foot-and-mouth disease virus: antigenic variation without accumulation of amino acid substitutions over six decades.

The genetic diversification of foot-and-mouth disease virus (FMDV) of serotype C over a 6-decade period was studied by comparing nucleotide sequences of the capsid protein-coding regions of viruses isolated in Europe, South America, and The Philippines. Phylogenetic trees were derived for VP1 and P1 (VP1, VP2, VP3, and VP4) RNAs by using the least-squares method. Confidence intervals of the derived phylogeny (significance levels of nodes and standard deviations of branch lengths) were placed by application of the bootstrap resampling method. These procedures defined six highly significant major evolutionary lineages and a complex network of sublines for the isolates from South America. In contrast, European isolates are considerably more homogeneous, probably because of the vaccine origin of several of them. The phylogenetic analysis suggests that FMDV CGC Ger/26 (one of the earliest FMDV isolates available) belonged to an evolutionary line which is now apparently extinct. Attempts to date the origin (ancestor) of the FMDVs analyzed met with considerable uncertainty, mainly owing to the stasis noted in European viruses. Remarkably, the evolution of the capsid genes of FMDV was essentially associated with linear accumulation of silent mutations but continuous accumulation of amino acid substitutions was not observed. Thus, the antigenic variation attained by FMDV type C over 6 decades was due to fluctuations among limited combinations of amino acid residues without net accumulation of amino acid replacements over time.

Amino Acid Sequence↗
PubMed1992

Parallel distributed processing and neuropsychology: a neural network model of Wisconsin Card Sorting and verbal fluency.

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.

Attention↗
PubMed1992

Heat shock-induced redistribution of a 160-kDa nuclear matrix protein.

In this paper we describe a 160-kDa protein (p160) which is present in the nuclear matrix of rat, mouse, and human cells. Biochemical and ultrastructural analysis shows that p160 is associated with the internal matrix and is not present in the lamina-pore complex. Immunoelectron microscopy shows that the protein is part of the extranucleolar, fibrogranular network of the nuclear matrix. During an in vivo 42 degrees C heat treatment of HeLa cells, A431 human epidermoid cells, and T24 human bladder carcinoma cells, p160 transiently formed large clusters inside the nucleus. These p160 clusters are associated with the nuclear matrix network, as judged by immunolabeling on isolated nuclear matrices. The percentage of cells showing p160 clusters increased proportionally with longer heat treatments, reaching a maximum after a period of 3 h. At this time 70 +/- 5% of the cells displayed these clusters. Clustering decreased after longer heat treatments and the anti-p160 staining pattern became diffuse granular again. Other nuclear components, such as the A1 antigen of hnRNP (ribonucleoprotein), the Sm antigen of snRNPs, and lamins A and C, did not cluster during the 42 degrees C treatment, indicating that this reallocation is characteristic for the p160 matrix protein. These results demonstrate that p160 is an internal nuclear matrix element with a dynamic spatial distribution.

Animals↗