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PubMed1991

Multilocus genetic structure of ancestral Spanish and colonial Californian populations of Avena barbata.

We have applied a multivariate log-linear technique to the analysis of interlocus allelic associations among 14 allozyme loci in a sample of 4011 plants from 42 Spanish populations of Avena barbata. The loci fell into three natural groups of five, five, and four loci. The five loci of the first group are invariant, or nearly so, throughout the range of the species. The genetic organization of the loci of this set is defined by a single five-locus genotype; each allele of this predominant genotype is a "wild-type" allele that contributes favorably to adaptedness in all single-locus and multilocus configurations regardless of environment. Although allelic diversity is high in Spain for the nine loci of the second and third sets, log-linear analyses showed that these loci are tied together in Spanish populations through complex networks of overlapping lower-order interlocus interactions. The ancestral Spanish and colonial Californian gene pools are closely similar in allelic composition on a locus-by-locus basis; however, Spanish allelic configurations at two-locus and higher-order levels are usually different from and much less tightly organized than in Californian populations. We conclude that the major force involved in the evolution of the colonial populations was selection that led to reorganization, at the interlocus level, of the ancestral Spanish allelic ingredients into different multilocus genotypes adapted to Californian habitats.

California↗

PubMed1991

[The formation of the microcirculatory bed of the neuromuscular systems of the tongue in human prenatal ontogeny].

A complex of adequate neurohistological and injection methods with use of mathematical analysis of the data obtained has been performed to study prenatal and early postnatal periods of ontogenesis of the microcirculatory bed of the human tongue neuromuscular systems. Certain changes of the degree in organization and structural-functional integration have been revealed; they demonstrate periodicity of the morphological changes of the vasculo-neural complex of the extra- and intrafusal part of the muscular tissue. In the neuromuscular spindles the microvascular network of capillaries is formed, their volumetric part changes in the process of development in greater degree than the microvascular bed of the extrafusal muscular fibers. In formation of the microcirculatory vascular bed of the neuromuscular spindles not only capillaries, getting into them together with nervous fibers, but also microvessels of the surrounding muscle tissue participate. This determines a higher level of the vascularization degree of the intrafusal muscle fibers.

Gestational Age↗

PubMed1982

[Nuclear organization of the oocytes from atretic follicles of the lake frog].

Oocytes of Rana ridibunda were examined by light and electron microscopy. A peculiarity of these oocytes is the availability of the vast local growings of the inner nuclear membrane, their expansion into the nucleus and the formation of cluster accumulations of membrane structures - intranuclear vesicles filled with fibrillar protein material. In the regions of nuclear membrane expansion some disturbances in the nuclear envelope are noted: disappearance of nuclear pores, replacement of membranes by filamentous material, and formation of nuclear membrane gaps. It is suggested that growings of the inner nuclear membrane are related to the isolation of cytoplasmic proteins penetrating into the nucleus. A general pattern of the karyospheric structure, characteristic of the normal developing oocytes, remains unchanged during degeneration as well. The karyosphere is a complex consisting of the central protein body (CPB), chromosomes associated with this body and numerous nucleoli surrounding the chromosomes. Some differences in details of the structure of karyosphere in the examined oocytes are revealed. Thus, the CPB in these oocytes consists of pseudomembranes, but autonomous pore complexes here occur seldom. The chromosomes have a tendency to fuse forming in some cases a unique network of the chromatin material associated with the material of CPB. In the contact zone the transfer of chromatin fibrils into pseudomembranes is observed. The nucleoli bear no granules and demonstrate a segregation of the fibrillar material. As the result, DNA-containing material of the fibrillar centre appears at the periphery of nucleoli. Analysis of our own and literature evidence on the morphology of the oocyte nuclei from the atretic follicles of different vertebrates, and on the structure of ciliate micronuclei degenerating during conjugation allows a conclusion on the identical response of sexual cells to different stimuli evoking degeneration.

Animals↗

PubMed1988

Nonlinear systems analysis of the hippocampal perforant path-dentate projection. I. Theoretical and interpretational considerations.

1. Nonlinear systems analytic procedures, based on an orthogonalized functional power series approach, were developed for study of the transformational properties of the hippocampal formation. As a testing stimulus, the procedures utilize a train of electrical impulses with randomly varying interimpulse intervals. The specific case was considered of applying such a stimulus to the perforant path, a major afferent to the hippocampal dentate gyrus that arises from the entorhinal cortex. Resulting field potentials evoked within the dentate gyrus are recorded to all impulses in the train. Computational algorithms based on cross-correlations determine the relationship between the interimpulse interval within the random train and amplitude of the evoked dentate potentials. The calculations, which reduce to averaging procedures, were derived for first- and second-order terms, or kernels, of the orthogonalized functional power series. 2. It is proposed that such an approach can be applied to a single component of the complex field potential evoked in the dentate gyrus. This component, the population spike, reflects the action potential discharge of dentate granule cells. Thus, a field potential component for which the underlying neuronal generator is well-known can be analyzed with respect to the transformational characteristics of the network of neurons that influence that generator. Other components of the complex field potential produced by other generators can be ignored. It is shown that this adaptation has the effect of greatly simplifying both the computation and presentation of kernels. 3. As a further consequence of this adaptation, the resulting first- and second-order kernels were shown to have specific interpretations. The first-order kernel represents the average response of the orthodromically driven granule cells to the set of stimuli comprising the random impulse train. The second-order kernel quantitatively characterizes the nonlinearity of the granule cell response, and may be interpreted as a generalized recovery function; i.e., the first input of any pair of stimuli in the train activates the newtork, and the second input tests the modulatory influence of the network excited by the initial input. 4. Most past investigations of nonlinearities of the perforant path-dentate projection have utilized pairs of stimulus impulses. We show here that, for a second-order system, the expected results from paired impulse experiments may be predicted from second-order kernels. Disagreement between the measured and predicted results reflects interactions of a higher order, and thus, greater system complexity.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1992

Predicting responses of nonlinear neurons in monkey striate cortex to complex patterns.

The overwhelming majority of neurons in primate visual cortex are nonlinear. For those cells, the techniques of linear system analysis, used with some success to model retinal ganglion cells and striate simple cells, are of limited applicability. As a start toward understanding the properties of nonlinear visual neurons, we have recorded responses of striate complex cells to hundreds of images, including both simple stimuli (bars and sinusoids) as well as complex stimuli (random textures and 3-D shaded surfaces). The latter set tended to give the strongest response. We created a neural network model for each neuron using an iterative optimization algorithm. The recorded responses to some stimulus patterns (the training set) were used to create the model, while responses to other patterns were reserved for testing the networks. The networks predicted recorded responses to training set patterns with a median correlation of 0.95. They were able to predict responses to test stimuli not in the training set with a correlation of 0.78 overall, and a correlation of 0.65 for complex stimuli considered alone. Thus, they were able to capture much of the input/output transfer function of the neurons, even for complex patterns. Examining connection strengths within each network, different parts of the network appeared to handle information at different spatial scales. To gain further insights, the network models were inverted to construct "optimal" stimuli for each cell, and their receptive fields were mapped with high-resolution spots. The receptive field properties of complex cells could not be reduced to any simpler mathematical formulation than the network models themselves.

Animals↗

PubMed2025

CNV-Finder: Streamlining Copy Number Variation Discovery.

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is significant in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates efficient prioritization of samples for time-consuming or costly subsequent analyses such as Multiplex Ligation-dependent Probe Amplification (MLPA), short-read, and long-read whole genome sequencing. We incorporate four genes to establish our methods-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), and alpha-Synuclein (SNCA)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Progressive Supranuclear Palsy (PSP), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using visual inspection, MLPA, short-read, and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied size, probe density, and noise. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

Copy Number Variation (CNV)↗

PubMed1991

The cell envelope of the hyperthermophilic archaebacterium Pyrobaculum organotrphum consists of two regularly arrayed protein layers: three-dimensional structure of the outer layer.

The cell envelope of the hyperthermophilic sulphur-reducing archaebacterium Pyrobaculum organotrophum H10 was found to be composed of two distinct hexagonally arranged crystalline protein arrays. Electron microscopic analysis of freeze-etched cells and isolated envelopes in conjunction with image processing showed that the inner layer (lattice centre-to-centre spacing 27.9 nm) is essentially identical to the protein array of Pyrobaculum islandicum GEO3, a complex, rigid structure implicated in the maintenance of cell shape. The outer layer has clear p6 symmetry and a lattice spacing of 20.6 nm. Its three-dimensional structure was reconstructed from a negative stain tilt series of an intact double-layered envelope using Fourier filtration to separate the desired information from the other lattices present. The outer layer is a unique, porous network of blocklike dimers disposed around six-fold axes, and exhibits minimal asymmetry between its inner and outer faces. It appears to be rather loosely associated with the outer surface of the inner layer. In most H10 envelopes, the inner layer is orientated with one base vector exactly perpendicular to the long axis of the cell, so that the cylindrical portion is composed of a series of parallel cell-girdling hoops of hexameric morphological units. All the other known Pyrobaculum strains were found to have a GEO3-type envelope structure, consisting of a single rigid protein array and a fibrous capsule. Although H10 does not possess a capsule, fibrils appear to be sandwiched between the two protein layers.

Archaea↗

PubMed1991

A population-based study of functional status and social support networks of elderly patients newly diagnosed with cancer.

We assessed the functional status and social support networks of 799 men and women aged 65 years or older newly diagnosed with cancer and living in six New Mexico counties. Functional limitations included depending on others for transportation (33%) and mental incompetence or poor recent memory (42%). The percentage of patients with functional limitation increased sharply with increasing age. In a substantial number of patients there was also evidence for poor social support networks; 26.5% of subjects lived alone and 38.9% had no children living in the vicinity. In a multiple logistic regression analysis, the predictors of having a poor social support network included non-Hispanic white ethnicity, advanced age, low income, and being a recent migrant to the area. Subjects with functional limitations were more likely to have poor social support networks than subjects without such limitations. The deleterious combination of impaired functional status and a limited social support network may explain why elderly cancer patients are at increased risk for not receiving appropriate therapy. Given the potential complexities involving the evaluation and appropriate treatment of cancer, care must be taken to adequately assess functional status and support mechanisms of older patients, and to provide adequate support to ensure compliance with treatment.

Activities of Daily Living↗

PubMed2026

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans↗

PubMed2026

Screening and identification of the ncRNA-mRNA regulatory network associated with DNA methylation in goose embryonic myoblasts.

BACKGROUND: Local goose breeds Shitou and Wuzong exhibit distinct growth rates, implying divergent embryonic muscle development. This study used embryonic myoblasts from the Magang goose, an established model with superior growth traits, to explore the underlying common regulatory mechanisms. Extending our previous findings that 5-AZA (DNA methylation inhibitor) and BC339 (DNA hydroxylation inhibitor) oppositely affect myoblast proliferation and differentiation, we performed whole-transcriptome sequencing on inhibitor-treated goose embryonic myoblasts. This aimed to identify DNA methylation-mediated ncRNA-mRNA networks governing myoblast fate, with key interactions being functionally validated. RESULT: 5-AZA significantly promotes cell proliferation and differentiation by inhibiting DNA methyltransferase activity and reducing DNA methylation levels, whereas BC339 significantly suppresses cell proliferation and differentiation by inhibiting demethylation and increasing DNA methylation levels. Specifically, we identified 6,309 mRNAs, 579 lncRNAs, 194 miRNAs, and 825 circRNAs that were differentially expressed in response to 5-AZA and BC339 treatment. Based on GO and KEGG enrichment analyses, differentially expressed genes related to muscle development were selected to construct a ceRNA network. This network comprises 5 differentially expressed lncRNAs (DELs: MSTRG.17572.1, XR_001211738.1, MSTRG.1886.1, XR_001212555.1, MSTRG.8995.2), 2 differentially expressed circRNAs (DECs: novel_circ_029953, novel_circ_017636), 11 differentially expressed miRNAs (DEMs: miR-383-x, miR-10174-y, miR-191-x, miR-24-x, miR-9619-y, novel-m0303-5p, novel-m0105-3p, miR-204-x, miR-211-z, novel-m0075, miR-26-y), 5 differentially expressed genes (DEGs: KIF3A, CCND1, PPM1A, Table 2, TGFBR1), forming a total of 24 interactions. This study identified miR-9619-y as a critical negative regulator of goose embryonic myoblast development through targeted inhibition of CCND1. Dual-luciferase reporter assays confirmed the direct binding of miR-9619-y to the 3'-untranslated region of CCND1. Functional experiments demonstrated that overexpression of miR-9619-y significantly reduced the EdU-positive cell ratio and myotube area percentage, accompanied by cell cycle arrest at the G0/G1 phase. Conversely, inhibition of miR-9619-y promoted myoblast proliferation and differentiation while decreasing the proportion of cells in G0/G1 phase. During the proliferation stage, miR-9619-y overexpression significantly suppressed CCND1 expression at both mRNA and protein levels, down-regulated MyoD expression, and reduced Myf5 mRNA abundance; whereas miR-9619-y inhibition up-regulated these genes and their corresponding proteins. During the differentiation stage, overexpression of miR-9619-y similarly decreased the mRNA levels of CCND1, Myh1, and MyoG, as well as the protein levels of MyHC and CCND1, with inhibition producing the opposite effects. CONCLUSION: In this study, we predicted a ceRNA network based on bioinformatics analysis governing goose embryonic myoblast development, identifying key molecular components including mRNAs, miRNAs, lncRNAs, and circRNAs, along with 24 regulatory axes. Functional experiments further demonstrated that miR-9619-y arrests cell cycle progression and negatively regulates the proliferation and differentiation of goose embryonic myoblasts, as evidenced by its impact on both the mRNA and protein expression of key myogenic factors through targeted inhibition of CCND1. These findings, together with the bioinformatically predicted ceRNA network, suggest potential complex post-transcriptional regulatory mechanisms underlying myogenesis in geese and offer candidate molecular targets for genetic improvement of meat production performance in waterfowl breeding programs.

Animals↗

PubMed1979

[Organizational characteristics of health care problems and the problems of industrial health services. I. Problems of organizational "morphology"].

The major part of industrial health care facilities act in frames of territorial health care complexes (ZOZ). It is unquestionable that ZOZ's organizational features influence fundamentally the efficiency of industrial health care activity. It is assumed that an analysis of these characteristics enables formulation of hypotheses regarding organizational conditions of effective activity of industrial health care. In part I the author analyses two ZOZ's features: 1) organizational components 2) flexibility of organizational structure. The author comes to the conclusion that the flexible structure enables composition of health care facilities network which fit the existing needs. If any needs remain unsatisfied it is a result of either shortage in resources or mismanagement.

Occupational Medicine↗

PubMed2024

Chemical proteomics to study metabolism, a reductionist approach applied at the systems level.

Cellular metabolism encompasses a complex array of interconnected biochemical pathways that are required for cellular homeostasis. When dysregulated, metabolism underlies multiple human pathologies. At the heart of metabolic networks are enzymes that have been historically studied through a reductionist lens, and more recently, using high throughput approaches including genomics and proteomics. Merging these two divergent viewpoints are chemical proteomic technologies, including activity-based protein profiling, which combines chemical probes specific to distinct enzyme families or amino acid residues with proteomic analysis. This enables the study of metabolism at the network level with the precision of powerful biochemical approaches. Herein, we provide a primer on how chemical proteomic technologies custom-built for studying metabolism have unearthed fundamental principles in metabolic control. In parallel, these technologies have leap-frogged drug discovery through identification of novel targets and drug specificity. Collectively, chemical proteomics technologies appear to do the impossible: uniting systematic analysis with a reductionist approach.

Humans↗

PubMed2026

The insulin-like growth factor 2 mRNA-binding protein 2 affects tumor cell metabolism via mitochondrial transporter activity and lipid alterations.

The insulin-like growth factor 2 mRNA-binding protein (IGF2BP) family is overexpressed in cancer and associated with poor prognosis. IGF2BP2 has been linked to single metabolic alterations by acting on its RNA targets. Here, we used a comprehensive approach to elucidate the effects of IGF2BP2 on primary and lipid metabolism. 13C-metabolic flux analysis (MFA) combined with RNA-Seq data revealed that IGF2BP2 affects mitochondrial fluxes by regulating the expression of several mitochondrial transporters, such as mitochondrial pyruvate carrier 1 (MPC1) and uncoupling protein 2 (UCP2). Methyl pyruvate reversed the gene expression patterns of UCP2 and CPT1A in HCT116 IGF2BP2 knockout (KO) cells by bypassing MPC1. Interestingly, an altered expression of the transporter UCP2 was also observed in a patient-derived tumor organoid (PDO), in which IGF2BP2 was knocked down. The altered glutamine metabolism seen in the 13C-MFA and the citrate label data derived from extracted mitochondria confirm a rerouting of glutamine almost exclusively into the mitochondria and a reduction of glycolytic carbon intake into the mitochondria. Due to changes in palmitate labeling patterns, lipid stainings were performed, suggesting lipid accumulation in KO cells. A lipidomic analysis revealed altered compositions across almost all lipid species. Further, lipogenic genes involved in fatty acid and cholesterol metabolism were differentially expressed. Most of the differentially expressed genes are potential direct targets of IGF2BP2 based on publicly available IGF2BP2 CLIP data. Overall, these results show the influence of IGF2BP2 on the central carbon metabolism of cancer cells, primarily through its effects on MPC1 and the resulting effects on UCP2. The complex interaction of IGF2BP2 with the metabolic network provides important insights into tumor metabolism, particularly relevant to tumor growth and resistance to therapy.

Journal Article↗

PubMed1991

Induction of granulocyte and granulocyte-macrophage colony-stimulating factors from human monocytes stimulated by Fc fragments of human IgG.

The effect of human IgG on human haemopoiesis has been studied in vitro. Dialysed purified IgG stimulated haemopoietic colony growth by bone marrow mononuclear cells (MNC) but not by monocyte-depleted MNC. Culture media, conditioned by IgG-stimulated peripheral blood MNC, augmented formation of neutrophil-macrophage, eosinophil, and megakaryocyte colonies by monocyte-depleted marrow MNC. Serum-free IgG-conditioned media also contained colony-stimulating activity (CSA). IgG Fc fragments and heat-aggregated IgG promoted the secretion of CSA, but F(ab')2 fragments, Fab fragments or ultracentrifuged IgG did not. In the cell-selection studies, CSA was produced by highly enriched monocytes following stimulation with Fc fragments. The antiserum against human granulocyte colony-stimulating factor (G-CSF) and/or granulocyte-macrophage CSF (GM-CSF) neutralized the CSA produced by Fc fragment-activated monocytes. Enzyme immunoassays showed G-CSF and GM-CSF in media conditioned by monocytes stimulated with the Fc fragments, heat-aggregated IgG and anti-D-sensitized red blood cells (RBC). Northern hybridization analysis showed mRNA encoding G-CSF and GM-CSF in RNA extracted from MNC and monocytes cultured with the Fc fragments, but not in the RNA from unstimulated cells or monocyte-depleted MNC. These results indicate that IgG Fc fragments, aggregated IgG and antigen-antibody complexes induce monocytes to produce G-CSF and GM-CSF in vitro. The CSFs release induced by IgG may be involved in the in vivo regulatory network in haemopoiesis.

Cell Division↗

PubMed1979

Acoustical analysis of the auditory system of the cricket Teleogryllus commodus (Walker).

The basic auditory physiology of crickets, and particularly of Teleogryllus commodus (Walker) is examined and its behavior simulated by electrical analog networks, beginning from the simplest possible model and progressing by stages to the full system found in the real insect. It is found that the attenuation of sound in the auditory trachea plays a crucial role in the mechanism for directional hearing in even the simplest model and that the tracheal diameter is in fact appropriate to produce the desired attenuation. In a more complex model in which it is recognized that the auditory system probably responds to pressure changes in the tracheal sacs underlying the tympana rather than simply to tympanic motion, it is found that the phase shift produced by the combined effects of the central septum and the adjoining cavities leading to the spiracles is also important to hearing directionality. The final model which includes both tympana and spiracles is able to simulate both the hearing directionality and, in part, the frequency selectivity of the system. It appears, however, that a large measure of the observed frequency selectivity is due to some form of selectivity in the neural transducers themselves rather than in the simple acoustic components of the system.

Acoustics↗

PubMed2026

Research on identification of key genes and immune-metabolic mechanisms in atrial fibrillation through integrated multi-cohort transcriptomic analysis and machine learning.

This study aimed to integrate multiple datasets for the identification of atrial fibrillation (AF)-related differentially expressed genes (DEGs), analyze their underlying mechanisms through functional enrichment and machine learning, construct diagnostic models, and explore immune-metabolic interactions to provide novel biomarkers and theoretical foundations. Gene expression datasets were integrated and normalized, with batch effects removed using principal component analysis. Differential expression analysis, functional enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways), and machine learning-based feature gene selection and model construction were performed. Shapley additive explanations analysis was utilized to interpret the constructed models, while gene set enrichment analysis, gene set variation analysis, and immune cell infiltration analysis were conducted to investigate the associations between feature genes and immune infiltration. After integrating and normalizing gene expression data and eliminating batch effects via principal component analysis, 6 DEGs were identified, including 4 upregulated and 2 down-regulated ones. Functional enrichment analysis showed these DEGs were significantly enriched in neuro-related biological processes and pathways, indicating their key roles in AF pathogenesis. Five key feature genes were selected using LASSO, random forest, and support vector machine-recursive feature elimination algorithms. They had significant expression differences between the AF and control groups (P < .001) and were located on distinct chromosomes. The constructed random forest and support vector machine models performed excellently (area under the curve ≥ 0.85). Shapley additive explanations analysis revealed TNNI1 contributed most to model prediction, with its expression significantly positively correlated with immune cell infiltration. Gene set enrichment analysis and gene set variation analysis analyses further showed feature genes participated in AF pathogenesis by regulating immune modulation, metabolic pathways, and autophagy. Immune cell infiltration analysis found altered proportions of T-cell subsets and M0 macrophages in the AF group, along with complex links between feature gene expression and immune cell function. This study systematically elucidated the unique gene expression patterns and key regulatory pathways associated with AF, clarifying the crucial roles of feature genes in immune regulation, metabolic imbalance, and cellular dysfunction. These findings provide a theoretical basis and potential therapeutic targets for understanding AF pathogenesis and developing targeted treatment strategies.

Atrial Fibrillation↗

PubMed2026

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

Animals↗

PubMed2026

Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.

PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, this study aimed to clarify their association, identify the toxic targets of DEHP, and elucidate the underlying molecular mechanisms. METHODS: Multiple integrated approaches were employed, including Gene Expression Omnibus (GEO) data analysis, network toxicology, molecular docking, and machine learning. STRING and Cytoscape tools were utilized to identify key targets, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functional enrichment of intersecting targets. Machine learning and SHAP analysis were applied to screen core targets in GC. Molecular docking was performed to evaluate the binding affinity of DEHP toward core targets, and 200 ns molecular dynamics simulations were further conducted for representative complexes to validate their dynamic stability. RESULTS: A total of 18 key targets were identified using STRING and Cytoscape. GO and KEGG enrichment analyses demonstrated that these intersecting targets were primarily enriched in the extracellular region, as well as the Calcium signaling pathway and cAMP signaling pathway. Through machine learning analyses, 7 key genes (ADRB2, ESRRG, GRIA4, IL13RA2, NR3C2, PLA2G1B, and SULT2A1) were identified as core targets in GC through machine learning analyses. Molecular docking simulations revealed strong binding specificity between DEHP and the target proteins. Among them, NR3C2 and ADRB2 exhibited relatively high predictive importance in the machine learning models. DEHP showed favorable binding affinity toward these core targets, and molecular dynamics simulations further confirmed that ADRB2-DEHP and NR3C2-DEHP complexes maintained stable conformations throughout the simulation. CONCLUSIONS: Our findings identified GC associated genes that were computationally predicted as potential targets of DEHP. These results indicated structural compatibility between DEHP and its target proteins but did not prove that DEHP exposure accounts for the gene expression changes in GC.

Molecular Docking Simulation↗