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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↗
PubMed1996

A self-organizing model of "color blob" formation.

This paper explores the possibility that the formation of color blobs in primate striate cortex can be partly explained through the process of activity-based self-organization. We present a simulation of a highly simplified model of visual processing along the parvocellular pathway, that combines precortical color processing, excitatory and inhibitory cortical interactions, and Hebbian learning. The model self-organizes in response to natural color images and develops islands of unoriented, color-selective cells within a sea of contrast-sensitive, orientation-selective cells. By way of understanding this topography, a principal component analysis of the color inputs presented to the network reveals that the optimal linear coding of these inputs keeps color information and contrast information separate.

Animals↗
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↗
PubMed1982

Freeze-fracture analysis of the interendothelial junctions in the blood vessels of the iris in Macaca mulatta.

The interendothelial cell junctions in the blood vessels of the rhesus monkey iris were examined by both conventional electron microscopy and the freeze-fracturing technique. Endothelial cells of iris blood vessels were joined by two types of intercellular junctions: zonular tight junctions and gap junctions. The zonulae occludentes were represented by a complex network of branching and anastomosing strands that remained preferentially associated with the E fracture face. They varied in complexity from a single strand to eight or more but usually consisted of from two to four strands. Small gap junctions were inserted within the tight junctional network. Junctions similar to those typical of muscular and visceral venules were absent. Thus the intercellular clefts of all iris vessels are closed by zonulae occludentes that exhibit a degree of complexity intermediate between the endothelial junctions of the cerebral cortex and those of striated muscles and viscera. This finding strongly suggests that the blood vessels of the iris participate only minimally in aqueous humor dynamics.

Animals↗
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↗
PubMed1995

Murine chromosomal location of five bHLH-Zip transcription factor genes.

The genes for the bHLH-Zip transcription factors Tfap4, Mxi1, Tcfeb, Usf1, and Usf2 have been mapped in mouse by interspecific backcross analysis. Mxi1, Usf1, and Usf2 have been mapped previously by in situ hybridization, but their positions on the meiotic linkage map had not been determined. The other two genes have not previously been mapped in mouse. These transcription factors belong to a growing family of transcriptional regulators, some of which are known to form a complex network of interacting proteins that control cell proliferation and apoptosis. As expected, based on mapping studies of other bHLH-Zip genes, these loci were well distributed among mouse chromosomes. In addition, some of the probes used in this study detected multiple, independently segregating loci, suggesting the possible existence of additional family members or species-specific pseudogenes.

Animals↗
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↗
PubMed1981

Towards professional autonomy: a commentary on "Expectations and disappointments' in development of the Royal College of Nursing.

The Royal College of Nursing of the United Kingdom has been engaged over recent years in a unique process of organizational change. Since 1973 sustained efforts have been made to mobilise widespread membership participation in shaping a new college structure which enables the Rcn to function effectively in representing the profession and in developing expertise on all aspects of nursing. A critical element has been creation of a network of "Rcn Centres' to provide a professional forum in each locality. A recent study by Bridget Ramsay has followed up this process. Its title, Expectations and Disappointments, reflects the mixed views of those involved on the progress which has been made. This article provides a commentary on Ramsay's analysis against the background of the complex situation of the Rcn in the early 1970s and the considerations which led the College to adopt an innovative approach to change. Particular attention is given to the influences which have made the growth of an active and integrated "Rcn at local level' quite problematic. It is suggested that the course Rcn development has taken in part reflects important elements in the nursing culture which members learn from their work in hospitals. Accordingly the Rcn experience has wider implications for the profession, not least for contemporary efforts, to achieve the greater professional autonomy necessary for nurses to implement more individualized patient care.

Humans↗
PubMedDate not supplied

[Nonspecific brain structures and specialization in the central nervous system].

It has been demonstrated that corticofugal influences may exert selective control of single sensory signals which converge on the neurons of the striatum and other non-specific structures of the brain. This finding suggests that complex sensory image may be formed not by assembling separate elementary signals, but rather by a selective control of these signals into a total sensory inflow within the network brain structures. This conclusion is confirmed by comparative anatomical data. In the phylogenesis of vertebrates, brain structures differentiate presumably into both the specific ones which perform the analysis of only the given kind of information, and those (conventionally described as non-specific) which are specialized on sensory integration and exhibit functional polymodality.

Animals↗
PubMed2026

Episode clustering in phylogenetic networks.

MOTIVATION: The classical duplication episode clustering (EC) model introduced by Guigó et al. in the 1990s provides a foundational approach for inferring genomic duplication events crucial to understanding genome evolution. This model clusters single gene duplications from a collection of gene trees at locations in the species tree to minimize the total number of such locations, called duplication episodes. However, it does not capture reticulate evolutionary histories. RESULTS: Here, we introduce NetEC, a novel extension of this problem to phylogenetic networks. To solve NetEC, we first develop a polynomial-time dynamic programming (DP) algorithm for testing whether a given set of network nodes can serve as episode locations. We then propose a main inference algorithm that utilizes this DP component to optimize the episode count; while the feasibility test runs in polynomial time, the full optimization has exponential worst-case complexity, and an optional heuristic mode is provided for larger instances. We also propose an extended episode analysis procedure that identifies additional genomic duplication candidates below reticulation nodes, complementing the main algorithm by resolving potential upward clustering of duplications induced by reticulation. We evaluate our method on simulated data and on an empirical Pandanales dataset comprising over 29 000 gene trees, demonstrating exact and accurate inference of genomic duplication events even in the presence of multiple reticulations. AVAILABILITY AND IMPLEMENTATION: All experiments were conducted using the NetEC tool (https://github.com/ppgorecki/netec), with all input data, scripts, and parameter settings for reproduction available in the same repository.

Phylogeny↗
PubMedDate not supplied

Application of fractal geometry techniques to the study of trabecular bone.

It is well recognized that both trabecular bone density and structure affect the overall bone quality and strength. In this study the aim is to quantify variations in the structural network of trabeculae using the concepts of fractal geometry. Fractal objects are objects that appear statistically similar over a range of scales. Typically fractals do not have smooth surfaces, but instead have rather complex structures with highly convoluted surfaces. Associated with every fractal is a characteristic dimension, called the fractal dimension. In this study, techniques of fractal analysis were used to characterize the trabecular bone matrix on digital images acquired by quantitative computed tomography (QCT) of dried excised human vertebral bodies (density ranging from 76-220 mg/cc) and photomicrography of transiliac crest biopsies. An automatic boundary tracking algorithm was used to identify the trabecular-bone and bone marrow interface, and a box-counting algorithm was used to estimate the fractal dimension of the trabecular boundary. Using this technique for fractal objects, if the boundary being analyzed is covered with boxes of differing sizes, epsilon, then the number of boxes N required to cover the surface increases indefinitely according to the relation N = epsilon-D, where D is the fractal dimension. Using this relationship in a preliminary study on five specimens we have found that the trabecular-bone boundary is fractal in nature. Using photomicrographs of iliac crest biopsies, it is found that the fractal dimension changes with the fractional trabecular bone content.(ABSTRACT TRUNCATED AT 250 WORDS)

Bone Density↗
PubMed1993

[Nuclear matrix-intermediate filament scaffold of cybrid cells crossed between rabbit reticulocytes and K562 cells].

To elucidate the role of the mammalian erythroid cytoplasmic factor on erythroid cell denucleation, cybridization of neo gene transferred rabbit reticulocytes with human K562 erythroleukemia cells was performed, the structure and composition of the nuclear matrix-intermediate filaments (NM-IF) system of the reticulocytes, K562 cells and the cybrids between them, the K-RRneo Cells, were studied by employing the techniques of selective extraction and whole mount electron microscopy. It was shown that regional condensation of nuclear matrix with a thinned nuclear lamina were seen in the cybrids, while the intermediate filaments exhibited a network pattern reorganization comparatively similar with those of reticulocytes but different from the radiation pattern of the K562 cells. SDS-PAGE and western blot analysis also revealed that the proteins affinity to vimentin antibody in the cybrids migrate in a pattern similar with that of the rabbit reticulocytes, both of them with only residual depolymerized vimentin complex but not the polymerized vimentin band of 55 kd. These results suggested that the factors in the cytoplasm of the rabbit reticulocytes might function through a mechanism of vimentin depolymerization or blockage of gene expression, which finally resulted in destruction of intermediate filaments that facilitates the expellation of nucleus from cytoplasm.

Animals↗
PubMed2025

N6-methyladenine identification using deep learning and discriminative feature integration.

N6-methyladenine (6 mA) is a pivotal DNA modification that plays a crucial role in epigenetic regulation, gene expression, and various biological processes. With advancements in sequencing technologies and computational biology, there is an increasing focus on developing accurate methods for 6 mA site identification to enhance early detection and understand its biological significance. Despite the rapid progress of machine learning in bioinformatics, accurately detecting 6 mA sites remains a challenge due to the limited generalizability and efficiency of existing approaches. In this study, we present Deep-N6mA, a novel Deep Neural Network (DNN) model incorporating optimal hybrid features for precise 6 mA site identification. The proposed framework captures complex patterns from DNA sequences through a comprehensive feature extraction process, leveraging k-mer, Dinucleotide-based Cross Covariance (DCC), Trinucleotide-based Auto Covariance (TAC), Pseudo Single Nucleotide Composition (PseSNC), Pseudo Dinucleotide Composition (PseDNC), and Pseudo Trinucleotide Composition (PseTNC). To optimize computational efficiency and eliminate irrelevant or noisy features, an unsupervised Principal Component Analysis (PCA) algorithm is employed, ensuring the selection of the most informative features. A multilayer DNN serves as the classification algorithm to identify N6-methyladenine sites accurately. The robustness and generalizability of Deep-N6mA were rigorously validated using fivefold cross-validation on two benchmark datasets. Experimental results reveal that Deep-N6mA achieves an average accuracy of 97.70% on the F. vesca dataset and 95.75% on the R. chinensis dataset, outperforming existing methods by 4.12% and 4.55%, respectively. These findings underscore the effectiveness of Deep-N6mA as a reliable tool for early 6 mA site detection, contributing to epigenetic research and advancing the field of computational biology.

Deep Learning↗
PubMed1988

Analysis of lettuce necrotic yellows virus structural proteins with monoclonal antibodies and concanavalin A.

Three major structural proteins of lettuce necrotic yellow virus (LNYV) were identified by discontinuous polyacrylamide gel electrophoresis (PAGE) to have Mr approximately 78,000 (G), 57,000 (N), and 19,000 (M). Unreduced G and M proteins had faster mobilities in PAGE indicating the presence of disulfide bonds. The G protein was shown to be glycosylated with a complex network of oligosaccharides containing beta-N-acetylchitobiose N-linked to asparagine residues of the protein. Up to 17 additional minor bands were also detected in silver-stained electrophoretograms. In Western immunoblots, 9 of these (Mr approximately 27,000-220,000) were recognized by a monoclonal antibody to the N protein and another 6 (Mr approximately 58,000-180,000) with a monoclonal antibody to the G protein, indicating that they were degradation products or aggregates of these two viral proteins. Two minor silver-stained bands failed to react with either of the monoclonal antibodies, but were recognized by polyclonal anti-LNYV serum and are probably the L (Mr approximately 190,000) and NS (Mr approximately 38,000) viral proteins.

Antibodies, Monoclonal↗
PubMed1987

Immunocytochemical localization of cathepsins B and H in rat liver.

Light and electron microscopic localization of cathepsins B and H in rat liver was investigated by immunoenzyme and protein A-gold techniques. For light microscopy (LM), semi-thin sections of the Epon-embedded material were stained by the immunoenzyme technique after removal of epoxy resin. For electron microscopy (EM), ultra-thin sections of the Lowicryl K4M-embedded material were stained by the protein A-gold technique. By LM, reaction deposits for cathepsins B and H were present in the cytoplasmic granules of parenchymal cells and endothelial cells, and Kupffer cells. The sinus-lining cells and the parenchymal cells showed the similar staining intensity. By EM, gold particles were present exclusively in lysosomes of all the cell types cited above. The same results were obtained from quantitative analysis. In addition, Golgi complexes themselves were mostly negative but some small vesicles on the trans side of them were labeled for these proteinases. The results indicate that cathepsins B and H are present in the lysosomes of rat liver and that these enzymes seem to be transported by small vesicles from endoplasmic reticulum to lysosomes via tubuloreticular network of the trans Golgi region.

Animals↗
PubMed1995

Neural correlates of working memory in a visual letter monitoring task: an fMRI study.

Complex mental operations rely on the coordinated activity of widely distributed brain regions constituting neurocognitive networks. Using multislice echoplanar functional magnetic resonance imaging (fMRI) we have contrasted regional brain activity during a control and an experimental condition which differed with respect to the demands placed on verbal working memory. Subjects were seven right-handed healthy male volunteers. Analysis of group and individual data revealed activation in the anterior and posterior parasagittal cortex in all subjects, left parietal cortex (six subjects) and left dorsolateral prefontal cortex (five subjects). These results suggest that verbal working memory is subserved by a neurocognitive network comprising cortical regions involved in attention, executive function and short term mnemonic processes.

Adult↗