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PubMed1978

Schizophrenia and social networks: ex-patients in the inner city.

A high level of social contacts has been recognized as one of the main predictors of outcome in schizophrenia. However, a variety of issues concerning the sociability of schizophrenics still need to be clarified. Focusing on ex-mental patients residing in a large Manhattan hotel, an analysis is made of the relationship between several social network variables, psychopathology, and rehospitalization. The findings indicate that: (1) Schizophrenics have significantly fewer linkages than nonpsychotics, but even the most impaired schizophrenics are not totally isolated. (2) Within the schizophrenic spectrum there are differences with respect to network size, complexity, directionality, and interconnectedness. (3) Rehospitalization is dependent upon two factors, degree of psychopathology and hotel network size.

Adult↗
PubMed1990

Inhibition of glycoprotein processing blocks assembly of spicules during development of the sea urchin embryo.

Previous studies have implicated an 130-kD glycoprotein containing complex, N-linked oligosaccharide chain(s) in the process of spicule formation in sea urchin embryos. To ascertain whether the processing of high mannose oligosaccharides to complex oligosaccharides is necessary for spiculogenesis, intact embryos and cultures of spicule-forming primary mesenchyme cells were treated with glycoprotein processing inhibitors. In both the embryonic and cell culture systems 1-deoxymannojirimycin (1-MMN) and, to a lesser extent, 1-deoxynojirimycin (1-DNJ) inhibited spicule formation. These inhibitors did not affect gastrulation in whole embryos or filopodial network formation in cell cultures. Swainsonine (SWSN) and castanospermine (CSTP) had no effect in either system. Further analysis revealed the following: (a) 1-MMN entered the embryos and blocked glycoprotein processing in the 24-h period before spicule formation as assessed by a twofold increase in endoglycosidase H sensitivity among newly synthesized glycoproteins upon addition of 1-MMN; (b) 1-MMN did not affect general protein synthesis until after its effects on spicule formation were observed; (c) Immunoblot analysis with an antibody directed towards the polypeptide chain of the 130-kD protein (mAb A3) demonstrated that 1-MMN did not affect the level of the polypeptide that is known to be synthesized just before spicule formation; (d) 1-MMN and 1-DNJ almost completely abolished (greater than 95%) the appearance of mAb 1223 reactive complex oligosaccharide moiety associated with the 130-kD glycoprotein; CSTP and SWSN had much less of an effect on expression of this epitope. These results indicate that the conversion of high mannose oligosaccharides to complex oligosaccharides is required for spiculogenesis in sea urchin embryos and they suggest that the 130-kD protein is one of these essential complex glycoproteins.

1-Deoxynojirimycin↗
PubMed1989

Circuit analysis of the oscillatory state in glycolysis.

The oscillatory state of glycolysis in yeast extracts has been analysed by methods known from electronic circuit studies. The time course of the reactions are calculated by the method of least squares from experimentally determined sets of the concentrations of most of the metabolites. The dynamics of the glycolytic network of reactions can then be represented in terms of flow versus driving force (current versus voltage in the corresponding electronic circuit). The analysis of the dynamics leads to the conclusion that glycolysis is switched on and off in a pulsed manner during the oscillatory state. The resulting pulsed flow cannot only be measured with glycolytic end products, like carbon dioxide or ethanol, but can also readily be demonstrated by diagrams of reaction rates of single enzymic steps even in the initial stages of the glycolytic sequence. An analytic method widely applied to electronic circuits also proved to be useful in the study of the dynamics of a complex enzymic network.

Data Interpretation, Statistical↗
PubMed1987

Characteristics of neuronal systems in the visual cortex.

The coupling complexity of cortical areas makes it very difficult to analyse them experimentally. Studies of model systems provide the possibility of adapting the analysis to the available data base and elaborating the fundamental properties that depend on the structure of the system. We propose a model system of variable complexity that is spatially two-dimensional and time-dependent, uses feedback for iteration and smoothing, includes the mapping of the cortical networks and can be nonlinear as the case requires. Combining such elementary systems on the basis of neuroanatomical findings enables us to simulate cortical mappings and to interpret neurophysiological data. The decisive factor is that the dynamics of the system and the neuroanatomically based spatial coupling are closely connected with each other.

Animals↗
PubMed1990

Air pollution from traffic in topographically complex locations.

In the UK, many improvements and modifications to the road system are made in urban areas where the network of roads and the surrounding area are often complex. In these locations, the emission and dispersion of vehicle exhaust are complicated by the diversity of the vehicle operating conditions and of the airflow patterns. A series of air pollution surveys have taken place at successively more complex sites. A preliminary analysis of the results has been carried out to determine the features that are most important in determining local pollution levels. These will be considered in the future development of methods of predicting pollution levels that are more accurate in topographically complex locations.

Air Pollution↗
PubMed2025

CoxKAN: Kolmogorov-Arnold networks for interpretable, high-performance survival analysis.

MOTIVATION: Survival analysis is a branch of statistics that is crucial in medicine for modeling the time to critical events such as death or relapse, in order to improve treatment strategies and patient outcomes. Selecting survival models often involves a trade-off between performance and interpretability; deep learning models offer high performance but lack the transparency of more traditional approaches. This poses a significant issue in medicine, where practitioners are reluctant to use black-box models for critical patient decisions. RESULTS: We introduce CoxKAN, a Cox proportional hazards Kolmogorov-Arnold Network for interpretable, high-performance survival analysis. Kolmogorov-Arnold Networks (KANs) were recently proposed as an interpretable and accurate alternative to multi-layer perceptrons. We evaluated CoxKAN on four synthetic and nine real datasets, including five cohorts with clinical data and four with genomics biomarkers. In synthetic experiments, CoxKAN accurately recovered interpretable hazard function formulae and excelled in automatic feature selection. Evaluations on real datasets showed that CoxKAN consistently outperformed the traditional Cox proportional hazards model (by up to 4% in C-index) and matched or surpassed the performance of deep learning-based models. Importantly, CoxKAN revealed complex interactions between predictor variables and uncovered symbolic formulae, which are key capabilities that other survival analysis methods lack, to provide clear insights into the impact of key biomarkers on patient risk. AVAILABILITY AND IMPLEMENTATION: CoxKAN is available at GitHub and Zenodo.

Humans↗
PubMedDate not supplied

[Evaluation of the obstructive factor and its importance in the caval and ilio-caval postphlebitic syndrome].

As regards venous haemodynamic disorders, former caval and ilio-caval phlebites constitute a separate group in the vast structure of phlebitic after-effects. The wealth of collaterals (reminder of the physio-pathology) and the slightest affection of the upper venous system in the case of high isolated thrombosis show that they may be effectively compensated. This idea, already apparent in certain clinical and phlebographical findings, is confirmed by functional investigations, and especially by plethysmography under venous occlusion. It is this method that we have used in this study. We have retained only the lesions of the ilio-caval system considered some way away from the acute stage of the thrombosis (gap of more than 6 months). A first approach, using rheoplethysmography, confirms that the obstructive syndrome associated with caval obstruction alone is generally well compensated by the development of an efficient collateral circulation, and that disorders of venous return, evaluated by the outflow index, are mainly to be seen when the caval obstruction is associated with deterioration of the subinguinal venous system. A second approach showed, by means of a more far-reaching analysis of the parameters using a constrictive mercury gauge that besides venous repermeation and supply through the collateral network a role was played by venous distensibility disorders induced by phlebitis... The maintenance of satisfactory distensibility could therefore come into play as a contributory factor in compensation phenomena. These facts confirm the complexity of post-phlebitic illness; phlebography gives only an incomplete insight into the functional repercussions of the obstructive syndrome; the exection of functional experiments demonstrate that often apparently significant venous obstructions are in fact quite well compensated.

Humans↗
PubMed1990

An object-oriented database for protein structure analysis.

An object-oriented database system has been developed which is being used to store protein structure data. The database can be queried using the logic programming language Prolog or the query language Daplex. Queries retrieve information by navigating through a network of objects which represent the primary, secondary and tertiary structures of proteins. Routines written in both Prolog and Daplex can integrate complex calculations with the retrieval of data from the database, and can also be stored in the database for sharing among users. Thus object-oriented databases are better suited to prototyping applications and answering complex queries about protein structure than relational databases. This system has been used to find loops of varying length and anchor positions when modelling homologous protein structures.

Amino Acid Sequence↗
PubMed2026

A 3D in vitro co-culture model to investigate tumor-endothelial interactions in Neurofibromatosis type 2-associated meningiomas.

BACKGROUND: Neurofibromatosis type 2 (NF2)-associated meningiomas and schwannomas are vascular tumors, and while vascular endothelial growth factor (VEGF) inhibition with bevacizumab has benefited some NF2-related schwannomas, most NF2-associated meningiomas remain nonresponsive. METHODS: Leveraging our transcriptomic data, we performed Gene Ontology (GO) analysis comparing NF2-deficient meningioma cells with NF2-expressing arachnoid cells (ACs). We then established a 3D in vitro angiogenesis model by co-culturing NF2-null meningioma cells with human umbilical vein endothelial cells (HUVECs). Endothelial sprouting was assessed by CD31/PECAM immunostaining. Effects of third-generation mechanistic target of rapamycin complex 1 (mTORC1)-selective inhibitor RMC-6272 as well as APLN knock-out using CRISPR-Cas9 gene editing were also examined. RESULTS: GO analysis identified vascular development among the top significantly upregulated pathways in NF2-deficient cells. In 3D co-culture, ECs formed radially sprouting tube-like networks from the spheroid surface, and our data supports an angiogenesis phenotype driven by meningioma cells. Given these results along with hyperactivation of mTORC1 upon NF2-deficiency, we examined whether RMC-6272 disrupts meningioma-driven angiogenesis. RMC-6272 potently suppressed EC sprouting. Cross-referencing baseline transcriptomic data, we identified Apelin (APLN), the ligand for APLN receptor (APLNR), as a basally upregulated angiogenic factor in NF2-deficient meningiomas. Quantitative RT-PCR (qRT-PCR) confirmed increased APLN expression in NF2-null immortalized and patient-derived meningioma lines, with reduced expression upon mTORC1 inhibition. Apelin-13 stimulation enhanced sprouting, whereas APLN deletion reduced endothelial sprouting. CONCLUSIONS: Here we establish a 3D-tumoroid model and implicate tumor-derived Apelin as an important contributor to NF2-associated meningioma angiogenesis. Our data also suggest that APLN expression is regulated, at least in part, by mTORC1. Together, these results provide a preclinical platform for investigating angiogenic vulnerabilities beyond VEGF in NF2-deficient meningiomas.

3D tumoroid model↗
PubMed1986

[Ultrastructure of the blood lymphoid cells and the dynamics of cellular immunity indices in chronic lympholeukemia patients during immunocorrection with T-activin].

Fourteen patients with chronic lymphoid leukemia who received treatment with T-activin given in courses (800-1100 micrograms) were examined for ultrastructure of blood lymphoid cells and the time-course of changes in humoral immunity. The patients had not received chemotherapy or hormonal treatment before. During the treatment with T-activin, no chemotherapeutic remedies were administered. After immunocorrection chemotherapy and hormones were prescribed when necessary. In the patients, the number of E-RFC (T cells) rose, whereas the number of B cells carrying surface immunoglobulins and the number of Em-RFC decreased. At the same time the prolonged use of T-activin brought about an increase in the number of B cells containing heavy chains of immunoglobulins M, G and A in the cytoplasm, while no considerable rise of serum immunoglobulins M, G and A was detected. Ultrastructural studies made during the use T-activin demonstrated a double rise in the number of lymphoplasmocytes, and in that of wide-plasma lymphocytes. The latter ones measuring 10 to 12 microns showed hypertrophy of Golgi's complexes and of the endoplasmic network. It is suggested that administration of T-activin for the B cell version of chronic lympholeukemia produces the differentiation of B cells, accompanied by the appearance in the cytoplasm of heavy chains of immunoglobulins M, G and A, which is supported by immunological and morphological analysis.

Adjuvants, Immunologic↗
PubMed1986

Vitamin C interaction with cobalt-ammine cations. Synthesis, spectroscopic and structural characterization of cobalt-pentammine and cobalt-tetrammine sugar complexes containing L-ascorbate anion.

Interaction between [Co(NH3)5Cl]Cl2, [Co(NH3)4Cl2]Cl and L-ascorbic acid has been investigated in aqueous solution and solid complexes of the type [Co(NH3)5 ascorbate]Cl2 X H2O and [Co(NH3)4 ascorbate]Cl2 X H2O have been isolated and characterized by 13C-NMR, FT-IR and electron absorption spectroscopy. Spectroscopic and other evidence suggested that the sugar anion binds monodentately in the [Co(NH3)5 ascorbate]2+ cation via the ionized O3 oxygen atom and bidentately in [Co(NH3)4 ascorbate]2+ through the O1 and O4 oxygen atoms, resulting in a six-coordinate geometry around the Co(III) ion. The intermolecular sugar hydrogen-bonding network is perturbed upon sugar metalation and the sugar moiety shows a similar conformation to that of the sodium ascorbate compound in these series of cobalt-ammine complexes.

Ascorbic Acid↗
PubMed2025

Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms.

BACKGROUND: Keloid disorder (KD) encompasses a spectrum of fibroproliferative dermal conditions, the pathogenesis remains complex and incompletely understood. This study sought to identify biomarkers and potential therapeutic targets for KD through an integrative bioinformatics approach and machine learning analysis of RNA sequencing data. METHODS: RNA sequencing was performed on skin tissue samples from 13 patients with KD and 14 healthy controls. Using weighted gene co-expression network analysis and differential expression analysis revealed differentially expressed key module genes, and the CytoHubba plugin identified candidate genes. Subsequently analyzed using least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) methods to pinpoint feature genes associated with KD. Following this, biomarkers were determined through expression level validation, enrichment analysis, and immune infiltration analysis. RESULTS: A total of 420 differentially expressed key module genes were identified, and the top 10 genes with DMNC values were selected as candidate genes. Five feature genes were selected through LASSO and SVM-RFE, with NID2, MFAP2, COL8A1, and P4HA3 showing significant expression differences between KD and control samples, along with consistent expression patterns across datasets, identified as potential biomarkers. These four biomarkers were proved to possess high diagnostic potential, and they were found to exhibit significant positive correlations with one another. Functional enrichment analysis indicated that the primary KEGG pathways associated with these biomarkers included "steroid hormone biosynthesis" and "cytokine-cytokine receptor interaction." Moreover, immune infiltration analysis revealed that the four biomarkers were negatively correlated with type 17 T helper cells and positively correlated with 15 immune cell types, including activated B cells and central memory CD4 T cells. CONCLUSION: In conclusion, NID2, MFAP2, COL8A1, and P4HA3 were identified as key biomarkers for KD, offering new avenues for more targeted and effective diagnostic and therapeutic strategies for managing this condition.

Humans↗
PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗
PubMed2025

Glaucoma and brain functional networks: a bidirectional Mendelian randomisation study.

OBJECTIVE: Glaucoma is a complex neurodegenerative ocular disorder accompanied by brain functional abnormalities that extend beyond the visual system. However, the causal association between the two remains unclear at present. This study aimed to investigate the potential causal relationships between glaucoma and brain functional networks in order to provide novel insights into the neuropathic mechanism of glaucoma. METHODS AND ANALYSIS: Based on the genome-wide association studies data of glaucoma and resting-state functional MRI (Rs-fMRI), a bidirectional Mendelian randomisation (MR) analysis was conducted between glaucoma and brain functional networks. Inverse variance weighting was applied as the primary method to estimate causality with false discovery rate correction. Additional sensitivity analyses were conducted to evaluate the robustness of the results. RESULTS: Forward MR analysis suggested that glaucoma was causally associated with two brain networks between the subcortical cerebellum and the attention or visual network (p=0.022), as well as the default mode and central executive network (p=0.008), but without significance after false discovery rate correction (q>0.1). Reverse MR analysis revealed 19 Rs-fMRI traits related to glaucoma risk, including the salience or central executive network in the frontal region (p=0.0005, q=0.08) and the motor network (p=0.0009, q=0.08) with significant causality. CONCLUSIONS: This MR study revealed potentially causal relationships between glaucoma and brain functional networks. Especially, the functional connectivity of the motor network between the postcentral or precentral areas may potentially lead to increased risk of glaucoma.

Humans↗
PubMed2025

A Digital Tool for Clinical Evidence-Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study.

BACKGROUND: Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code. OBJECTIVE: This study aims to develop a digital tool that characterizes the overall population and differences between clinical trial eligible and ineligible populations from the clinical populations of a disease or condition regarding demography (eg, age, gender, ethnicity), comorbidity, coprescription, hospitalization, and mortality. Currently, the process is complex, onerous, and time-consuming, whereas a real-time tool may be used to rapidly inform a guideline developer's judgment about the applicability of evidence. METHODS: The National Institute for Health and Care Excellence-particularly the gout guideline development group-and the Scottish Intercollegiate Guidelines Network guideline developers were consulted to gather their requirements and evidential data needs when developing guidelines. An R Shiny (R Foundation for Statistical Computing) tool was designed and developed using electronic primary health care data linked with hospitalization and mortality data built upon an optimized data architecture. Disclosure control mechanisms were built into the tool to ensure data confidentiality. The tool was deployed within a Trusted Research Environment, allowing only trusted preapproved researchers to conduct analysis. RESULTS: The tool supports 128 chronic health conditions as index conditions and 161 conditions as comorbidities (33 in addition to the 128 index conditions). It enables 2 types of analyses via the graphic interface: overall population and stratified by user-defined eligibility criteria. The analyses produce an overview of statistical tables (eg, age, gender) of the index condition population and, within the overview groupings, produce details on, for example, electronic frailty index, comorbidities, and coprescriptions. The disclosure control mechanism is integral to the tool, limiting tabular counts to meet local governance needs. An exemplary result for gout as an index condition is presented to demonstrate the tool's functionality. Guideline developers from the National Institute for Health and Care Excellence and the Scottish Intercollegiate Guidelines Network provided positive feedback on the tool. CONCLUSIONS: The tool is a proof-of-concept, and the user feedback has demonstrated that this is a step toward computer-interpretable guideline development. Using the digital tool can potentially improve evidence-driven guideline development through the availability of real-world data in real time.

Humans↗
PubMed2026

Accelerated long-read variant calling with Clair3 for whole-genome sequencing.

SUMMARY: The rapid growth of genomic data and increasing adoption of long-read sequencing technologies have rendered variant calling one of the most computationally demanding tasks in genomic analysis. Although deep learning-based methods currently outperform conventional approaches in distinguishing true variants from complex sequencing noise, they impose prohibitive computational and time requirements. To address this limitation, we present a computational framework based on Clair3 that integrates parallelized feature generation, enhanced variant phasing, in-memory read haplotagging, and GPU-accelerated neural network inference to accelerate variant calling. By dynamically optimizing the use of both GPU and CPU resources, our method achieves substantial runtime improvements without compromising accuracy. We evaluated our framework across a range of sequencing depths, diverse samples, and multiple hardware configurations. Our results demonstrate that the optimized pipeline completes variant calling for a 30× whole-genome sequence in 12-20 minutes using standard computational resources (32 CPU threads and one NVIDIA GPU), and in 12-15 minutes on an Apple Mac Studio (32 threads), which is ∼10-20-fold speedup compared with its initial release. In addition to exceptional efficiency, our method maintains state-of-the-art accuracy, achieving SNP F1-scores of 99.32% and 99.70% on 30× ONT and PacBio GIAB HG003 datasets, respectively. This work introduces a rapid, accurate, and scalable variant calling framework that effectively supports large-cohort genomic studies and time-sensitive clinical applications. AVAILABILITY AND IMPLEMENTATION: The accelerated implementation of Clair3 is open source and available at: https://github.com/HKU-BAL/Clair3/tree/gpu.

Whole Genome Sequencing↗
PubMed1989

An 'electronic' extramural course in epidemiology and medical statistics.

This article describes an extramural university course in epidemiology and medical statistics taught using a computer conferencing system, microcomputers and data communications. Computer conferencing was shown to be a powerful, yet quite easily mastered, vehicle for distance education. It allows health personnel unable to attend regular classes due to geographical or time constraints, to take part in an interactive learning environment at low cost. This overcomes part of the intellectual and social isolation associated with traditional correspondence courses. Teaching of epidemiology and medical statistics is well suited to computer conferencing, even if the asynchronicity of the medium makes discussion of the most complex statistical concepts a little cumbersome. Computer conferencing may also prove to be a useful tool for teaching other medical and health related subjects.

Computer Communication Networks↗