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Aminopeptidase when in its integral form interacts with lecithin to form a stable lipoprotein complex. The reconstituted system is a single-bilayer vesicle about 30 nm in diameter. The hydrophobic part of the amphipathic hydrolase is incorporated in the lecithin bilayer with the portion carrying enzymic activity oriented towards the external aqueous phase. This part can be detached by proteases.
Adult pigeons received dantrolene sodium, a skeletal muscle relaxant which blocks the release of calcium during excitation-contraction coupling, for 12 to 16 weeks. The pectoralis muscles of these birds were analyzed for changes occurring in the various fiber types of the muscle. Both histochemistry (ATPase and SDH activity) and electron microscopy (mitochondrial and lipid volume percentages) differentiated two fiber types. The two fiber-types consisted of fast-twitch glycolytic fibers (FG) and fast-twitch oxidative-glycolytic (FOG) fibers. After dantrolene treatment some FG fibers showed little or no ATPase activity. Dantrolene treatment also produced a disappearance of thick filaments in some FG fibers. We infer that the fibers without thick filaments are the ones lacking ATPase activity. The FOG fibers were nearly normal. Since drug-fed birds lose weight, a few birds were starved to determine whether the filament loss was related solely to the bird's loss in weight. No fibers in starved birds showed reduced ATPase activity or loss of thick filaments. In fibers that showed thick filament disappearance, the I-bands remained organized and intact, suggesting that the I-band maintains its integrity without interaction with the thick filaments. Changes in activity patterns may cause loss of thick filaments by inhibiting either their synthesis or assembly.
Remodeling of the immune microenvironment is a critical determinant of tissue regeneration, yet the molecular programs associated with the enhanced therapeutic activity of hypoxia-preconditioned extracellular vesicles remain incompletely defined. In this study, we investigated the regenerative and immunomodulatory effects of hypoxia-preconditioned tendon stem cell-derived extracellular vesicles (Hypo-EVs) and employed transcriptomic profiling to identify molecular signatures associated with their biological activity. The therapeutic effects of Hypo-EVs were evaluated using a rat patellar tendon defect model and lipopolysaccharide-stimulated RAW 264.7 macrophages. Histological analysis, immunostaining, biomechanical testing, and reverse transcription-quantitative polymerase chain reaction were performed to assess tendon healing and macrophage polarization, while RNA sequencing was conducted in macrophages treated with Hypo-EVs or normoxia-derived EVs, followed by Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes pathway analyses. Hypo-EVs significantly alleviated local inflammatory responses, improved collagen organization and biomechanical properties of repaired tendons, and promoted macrophage polarization toward a reparative M2 phenotype both in vivo and in vitro. Consistent with these biological effects, transcriptomic profiling revealed extensive remodeling of inflammation-related gene expression programs, including significant suppression of NF-κB, TNF, IL-17, and cytokine-cytokine receptor interaction pathways. Integrative bioinformatic analyses identified an NF-κB-associated immune-regulatory signature that distinguished Hypo-EV-treated macrophages from those receiving normoxic EVs. Mechanistically, Hypo-EVs attenuated NF-κB activation, as evidenced by reduced phosphorylation of p65 and IκBα, whereas TNF-α-mediated NF-κB activation partially diminished their macrophage-repolarizing effects. Collectively, these findings demonstrate that hypoxic preconditioning enhances the immunomodulatory and regenerative functions of tendon stem cell-derived EVs. Transcriptomic analyses identified an NF-κB-associated immune-regulatory signature linked to the biological activity of Hypo-EVs, providing a molecular framework for understanding EV-mediated immune modulation and supporting the development of transcriptome-guided molecular signatures for regenerative therapies targeting tendon immune homeostasis.
The anatomy of the small ocellar interneurons in the brain of the acridid grasshopper Schistocerca vaga was revealed by cobalt-filling the three ocellar nerves and subsequent reconstructions from silver-intensified (Timm's method) serial sections. In total, 61 small ocellar interneurons were repeatedly identified with arborizations in many areas of the brain and optic lobe, including in particular the posterior neuropil, ocellar tracts, protocerebral bridge, lobula, ventral bridge and tritocerebral crotch, calyces, and antenno-glomerular tracts. Each ocellar nerve contains the axons of small cells that arborize in the other two ocellar tracts; these tracts are sites of ocellar integration. Direct interactions between the ocelli and compound eyes are suggested by the projections of small ocellar interneurons into the proximal lobula. Small cell arborizations from all three ocelli are distributed actoss much of the protocerebral bridge, implying a role for the bridge as an ocellar neuropil within the brain. Four of the small interneurons could be seen in whole-mount preparations and are demonstrated to be identical in five species of acridid grasshoppers of two different subfamilies: Schistocera vaga, S. gregaria, Gastrimargus africanus, Trimerotropis pallidipennis, and Arphia conspersa.
The BRCA2 tumour suppressor protein preserves genomic integrity via interactions with the DNA-strand exchange RAD51 protein in homology-directed repair. The RAD51-binding TR2 motif at the BRCA2 C-terminus is essential for protection and restart of stalled replication forks. Biochemical evidence shows that TR2 recognises filamentous RAD51, but existing models of TR2 binding to RAD51 lack a structural basis. Here we used cryo-electron microscopy and structure-guided mutagenesis to elucidate the mechanism of TR2 binding to nucleoprotein filaments of human RAD51. We find that TR2 binds across the protomer interface in the filament, acting as a brace for adjacent RAD51 molecules. TR2 targets an acidic-patch motif on human RAD51 that serves as a recruitment hub in fission yeast Rad51 for recombination mediators Rad52 and Rad55-Rad57. Our findings provide a structural rationale for RAD51 filament stabilisation by BRCA2 and reveal a common recruitment mechanism of recombination mediators to the RAD51 filament.
Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.
Appropriate flowering time is important for rice regional adaptation and optimum rice production, but little is known about the omics of heading date in rice. Here, we studied omics including transcriptome, proteome and transcriptional factors to identify regulatory genes related to flowering time. A total of 1402 differentially expressed genes (DEGs, 721 up-regulated and 681 down-regulated) were detected in wild and mutant. These transcripts are classified according to biological processes, cellular components, and molecular functions. Among these differentially expressed genes, many transcription factor genes demonstrated multiple regulatory pathways involved in flowering time. Gene expression analysis showed that Os03g0122600 (OsMADS50), Os08g0105000 (Ehd3), Os06g0275000 (Hd1) were expressed higher and Os06g0199500 (OsHAL3), Os06g0498800 (OsMFT1), Os08g0105000 (Ehd3), Os06g0157700 (Hd3a), and Os02g0731700 (Ghd2), were expressed lower in wild compared to mutant, which are the key genes that regulate the flowering in rice. In addition, Ghd7 interacted with Os10g30860 and Os12g08260 using yeast two-hybrid assay. We identified 28 potential Ghd7 transcriptional regulators using the transcription factor-centered yeast one hybrid (TF-Centered Y1H) assay. Taken together, this study developed a new set of genomic resources to identify and characterize genes, proteins, and motifs associated with flowering time.
MOTIVATION: The genome interacts with itself within the volume of the cell nucleus to process information. These interactions mediate signal integration, gene regulation, and cell identity. The identification of new therapeutic targets from non-coding disease-associated variants relies critically on correctly assigning variants to genes through 3D interactions. Experimental techniques in 3D genomics, such as HiC and HiChIP, allow the mapping of interactions through sequencing. Bioinformatics for 3D genomics contends primarily with contact matrices that contain interaction frequencies for all possible element pairs, and BEDPE files that store element pairs that interact. Whereas the tools available for processing linear genomic data are mature, operating on contact matrices and BEDPE files remains cumbersome, opaque, and error-prone, as researchers have had to shoehorn tools originally designed for linear data. A genome arithmetic designed from the ground up for 3D genomics does not yet exist. RESULTS: We present AQuA Tools, a suite of shell- and R-based command-line tools that provide a set of core operations on contact matrices and BEDPE files motivated by key questions in population genetics, cancer research, and precision medicine. We have designed our core operations to be clear, reliable, intuitive and versatile. Core operations can be chained together along with standard UNIX commands. Our goal is to make AQuA Tools easy for the novice to learn and the go-to choice for power users. We hope our tools will motivate more researchers to use 3D genomic data in their projects. AVAILABILITY AND IMPLEMENTATION: We provide and maintain AQuA Tools at https://github.com/axiotl/aqua-tools.
Specific cell-factor interactions provide a basic mechanism for differentiation of myeloid and lymphoid cells. Evidence at the present time indicates that factor-producing cells, factor and factor-responding cells are integrated into an interacting network to produce various specific differentiatied functions. To elucidate the mechanisms of such interactions in the differentiation of T lymphocyte, a systematic study was carried out to characterize a liquid suspension culture system for T progenitor cells from human peripheral blood or bone marrow. T progenitor cells were assayed either by their membrane properties or by their ability to form colonies in semisolid media. T lymphocyte growth stimulators (TL-GS) were isolated from phytohemagglutin (PHA)-stimulated human T lymphocyte conditioned medium. TL-GS were capable of selectively supporting growth for four months or longer of T progenitor cells. This system should facilitate the study of cell-factor interactions mediating the proliferation and differentiation of T lymphocytes.
BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4 > 0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.
Organ-on-a-Chip (OOC) technology offers a powerful platform for replicating human tissue-specific microenvironments, thereby narrowing the translational gap between conventional biomedical models and actual human physiology. Concurrently, omics technologies deliver comprehensive molecular-level insights into biological systems. This review highlights the transformative potential of integrating OOC platforms with high-throughput omics methodologies. We systematically examine the classification, structural configurations, and engineering principles underlying OOC systems, alongside the defining attributes of key omics domains-genomics, transcriptomics, proteomics, and metabolomics. The convergence of dynamic OOC models with advanced omics technologies enables high-resolution, multi-dimensional analyses across numerous biomedical applications, including drug metabolism, disease mechanisms, environmental toxicity assessments, and host-microbiome interactions. This interdisciplinary integration is driving a paradigm shift in precision and translational medicine. However, several challenges remain to be addressed, such as the development of whole-organ mimetics, adaptation of sample collection techniques, and real-time artificial intelligence-based integration of biosensor data with multi-omics datasets. Addressing these hurdles will be vital for unlocking the full potential of this technological synergy in biomedical science.
SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server improves an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/dgidb/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.
SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server greatly enhances an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/griffithlab/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.
UNLABELLED: FOXA1 is a pioneer transcription factor essential for chromatin accessibility and transcriptional regulation in hormone-driven cancers. In breast cancer, FOXA1 plays a central role in facilitating nuclear receptor binding, reprogramming enhancer landscapes, and promoting transcriptional changes associated with therapy resistance. Whereas FOXA1's function has been primarily studied in the context of estrogen receptor-α (ER), its broader protein interaction network remains incompletely defined. In this study, we systematically map FOXA1-interacting proteins in ER-positive breast cancer cells using proximity-dependent biotin labeling (miniTurbo) combined with quantitative LC-MS/MS proteomics. We engineered MCF-7 cell lines stably expressing miniTurbo-tagged FOXA1 at either the N-terminus or C-terminus to ensure comprehensive coverage of interaction interfaces. This approach recovered known FOXA1 partners, including AR, MLL3, YAP1, and GATA3, and identified 157 previously unreported FOXA1 interactors. Notably, 42 of these novel partners, including NR2C2, were significantly associated with poor relapse-free survival in patients with ER-positive breast cancer. To demonstrate the utility of this resource, we characterized the FOXA1-NR2C2 interaction in depth. Integrating chromatin immunoprecipitation sequencing and RNA sequencing, we show that FOXA1 and NR2C2 co-occupy a subset of genomic regions and drive co-regulated transcriptional programs involved in tumor progression. Our study reveals an expanded FOXA1 interactome and new insights into its functional network in breast cancer, providing candidate proteins for further exploration as biomarkers or therapeutic targets. IMPLICATIONS: These findings expand the FOXA1 interactome in breast cancer and uncover new candidate proteins with potential as biomarkers and therapeutic targets in hormone-driven tumors.
OBJECTIVE: Active participation in preoperative anesthesia preparation is crucial to ensure safe and efficient care. Compliance with preoperative instructions improves clinical outcomes, enhances patient satisfaction and optimizes use of healthcare resources. As digital communication becomes increasingly integrated into healthcare, interactive digital tools such as smartphone applications and Short Message Service (SMS) reminders may offer a valuable means of engaging patients in their own care. In this review, we evaluated the role of digital tools in guiding patients during their preoperative care pathway for anesthesia. METHODS: Following registration (CRD420250655119), we conducted a systematic review of studies evaluating the use of smartphone applications or SMS reminders designed to support preoperative preparation for anesthesia or procedural sedation in adult patients undergoing elective procedures. The primary outcome was compliance with preoperative instructions. Secondary outcomes included rate of late cancellations, patient satisfaction and cost-effectiveness. Studies were eligible if they reported at least one of these outcomes. RESULTS: Ten studies (1 RCT and 9 observational studies), including 11501 participants, were identified. Compliance with preoperative instructions was assessed in 8 studies, most of which reported higher compliance in patients receiving digital interventions across multiple instruction domains, although statistical significance was not consistently observed. Evidence suggested a beneficial effect on reducing late cancellations and improving patient satisfaction. However, results varied across study designs, and data on cost-effectiveness were limited. CONCLUSIONS: Digital tools for preoperative anesthesia guidance were associated with higher compliance and showed potential reduction of late cancellations and increase of patient satisfaction. However, the current evidence is predominantly observational and heterogeneous, limiting the strength of conclusions. PRACTICAL IMPLICATIONS: With healthcare systems under pressure, digital technologies may offer a scalable and patient-centered care solution to support preoperative anesthesia preparation. Nonetheless, further high-quality research is needed to evaluate their long-term clinical, economic and equity implications.
OBJECTIVE: To study the potential pathogenic mechanisms of bisphenol A (BPA) in polycystic ovary syndrome (PCOS) using an integrative computational strategy. DESIGN: Integrative computational study combining network toxicology, Mendelian randomization (MR), and molecular docking. SUBJECTS: For MR analysis, genetic data were sourced from large European-ancestry cohorts, including plasma protein quantitative trait loci data and genome-wide association study summary statistics for PCOS (3,045 cases and 267,780 controls). EXPOSURE: In silico exposure to BPA for target prediction; genetically predicted plasma protein levels for causal inference. MAIN OUTCOME MEASURES: Identification of overlapping targets between BPA and PCOS; functional enrichment pathways; causal effects of prioritized proteins on PCOS risk (odds ratios with 95% confidence intervals); binding affinities between BPA and core targets (kcal/mol). RESULTS: Network toxicology identified 310 overlapping targets between BPA and PCOS. Enrichment analyses revealed significant involvement in endocrine signaling, inflammatory pathways (eg, IL-17), and cellular processes. MR demonstrated that genetically elevated levels of RET, CXCL8, HTR6, MMP1, MMP9, NTRK1, and TNNI2 were significantly associated with increased PCOS risk, whereas higher PSAP and SHBG levels were protective. Molecular docking confirmed stable binding between BPA and all nine key targets, with strongest affinity for SHBG (-8.4 kcal/mol), followed by NTRK1, TNNI2, and RET. CONCLUSION: This integrative investigation suggests that BPA may contribute to PCOS pathogenesis through multitarget interactions involving inflammatory mediators, endocrine regulators, and tissue remodeling proteins. The findings provide prioritized targets and mechanistic insights for future experimental validation and environmental risk assessment.
Host structural variations (SVs) are critical in cancer development but their landscape and interaction with HPV integration in cervical carcinogenesis remain unclear. In this study, we performed Nanopore long-read sequencing on five HPV-positive cervical cancer tissues and two cell lines to profile host SVs. We identified thousands of SVs and statistically demonstrated their significant enrichment in genomic windows ±25 to ±50 kb from HPV integration sites. Cross-sample analysis revealed 60 shared SVs, including a recurrent deletion within the PIAS1 gene. Multi-omics integration (Hi-C, H3K27ac ChIP-seq, and TCGA data) showed that this deletion is associated with reduced PIAS1 expression, disruption of local topologically associating domains, advanced pathological tumor stage, and poorer overall survival. Functional assays confirmed that PIAS1 deficiency inhibits cervical cancer cell proliferation and migration. Our findings identify a PIAS1 deletion as a candidate driver event, and underscore the pivotal role of host genomic instability in HPV-associated oncogenesis.
Gene deletion is traditionally viewed as a nonadaptive mechanism that eliminates functional redundancy, yet emerging evidence indicates that it disproportionately affects tissue-specific duplicates with unique functions. Here, we test whether gene deletion preferentially removes weakly constrained, degenerating duplicates or instead eliminates functionally active duplicates through an adaptive process. To identify the evolutionary and functional factors that determine which duplicates are lost, we systematically analyzed 100 gene deletion events in Drosophila by integrating sequence, expression, interaction, and structural data. We uncovered a strong bias toward the loss of younger child copies among functionally unique duplicates, whereas no such bias was observed for redundant duplicates. Contrary to expectations under relaxed constraint, deleted functionally unique genes evolve more slowly, show higher expression, engage in more protein-protein interactions, and do not exhibit elevated structural divergence or intrinsic disorder relative to redundant duplicates. When compared with single-copy genes, deleted functionally unique genes display similar evolutionary rates, slightly lower expression, greater network connectivity, comparable structural divergence, and lower intrinsic disorder. These patterns suggest that deletion frequently affects functionally active rather than degenerate genes. Collectively, our results support the hypothesis that gene deletion in Drosophila can represent an adaptive process acting on transiently functional duplicates, potentially driven by either genome streamlining or context-dependent deleterious effects.