Front Bioinform. 2025 Jun 30;5:1632189. doi: 10.3389/fbinf.2025.1632189. eCollection 2025.

ABSTRACT

BACKGROUND: Understanding the structure and function of microbial genomes is crucial for uncovering their ecological roles, evolutionary trajectories, and potential applications in health, biotechnology, agriculture, food production, and environmental science. However, genome reconstruction and annotation remain computationally demanding and technically complex.

RESULTS: We introduce a bioinformatics platform designed explicitly for long-read microbial sequencing data to address these challenges. Developed as a service of the Italian MIRRI ERIC node, the platform provides a comprehensive solution for analyzing both prokaryotic and eukaryotic genomes, from assembly to functional protein annotation. It integrates state-of-the-art tools (e.g., Canu, Flye, BRAKER3, Prokka, InterProScan) within a reproducible, scalable workflow built on the Common Workflow Language and accelerated through high-performance computing infrastructure. A user-friendly web interface ensures accessibility, even for non-specialists.

CONCLUSION: Through case studies involving three environmentally and clinically significant microorganisms, we demonstrate the ability of the platform to produce reliable, biologically meaningful insights, positioning it as a valuable tool for routine genome analysis and advanced microbial research.

PMID:40662129 | PMC:PMC12256462 | DOI:10.3389/fbinf.2025.1632189

Front Immunol. 2025 Jun 30;16:1608101. doi: 10.3389/fimmu.2025.1608101. eCollection 2025.

ABSTRACT

INTRODUCTION: Interleukin-24 (IL-24) is a cytokine belonging to the IL-10 family with immunoregulatory properties. It is known to induce cellular responses in various disease conditions, including inflammatory, infectious diseases, and cancer, in a receptor-dependent and independent manner. IL-24 is induced by both immune and non-immune cells and acts on a vast array of target cells to regulate various biological processes. The antitumor and immunoregulatory properties of IL-24 support its application as a therapeutic agent in a vast array of pathological conditions. Characterizing the molecular events associated with its immunomodulatory properties is essential for evaluating its utility in cancer immunotherapy.

METHODS: The data related to signaling events induced by IL-24 were then manually annotated and cataloged from the literature pertaining to IL-24 signaling. The cataloged molecular events were then manually drawn based on the topology as a signaling pathway map of IL-24.

RESULTS: Based on the data mined from published literature, we assembled IL-24-regulated signaling events linked to its immunoregulatory and anti-tumor activities. The receptor-ligand interaction of IL-24 regulates multiple downstream signaling cascades, leading to antitumor activities alongside inducing inflammatory reactions and anti-infectious processes. We provide a signaling pathway map of IL-24 consisting of 433 mRNAs/proteins and their 613 signaling events.

DISCUSSION: We believe this map would serve as a knowledge base for reference and one-go visualization of the signaling events identified to be induced by IL-24. Moreover, this map is made available (https://ciods.in/il24/) for the researchers to explore the role of IL-24 in various pathophysiological conditions through the gene set enrichment of transcriptomics or proteomics datasets from various disease conditions.

PMID:40661937 | PMC:PMC12257977 | DOI:10.3389/fimmu.2025.1608101

bioRxiv [Preprint]. 2025 Jun 13:2025.06.09.658650. doi: 10.1101/2025.06.09.658650.

ABSTRACT

Reconstructing genome-scale gene regulatory networks (GRNs) remains a difficult problem in systems biology, and many experimental and computational methods have been developed to address this problem. Recent computational methods have aimed to more accurately model GRNs by estimating the hidden Transcription Factor Activity (TFA), from prior knowledge of TF target regulatory connections, encoded as an input directed graph, to relax the assumption that mRNA level of the regulator correlates with the protein activity of the regulator. However, the noise in the prior knowledge can adversely affect the estimated TFA levels and the quality of the downstream inferred GRNs. Here, we present a new approach, MERLIN+P+TFA, that uses prior knowledge-guided sparsity regularization to robustly and accurately estimate TFA and downstream GRNs. We apply our method to simulated and real expression data in yeast and mammalian systems and show improved quality of inferred GRNs for both bulk and single-cell datasets. Regularized TFA offers benefits to a variety of other GRN inference algorithms, including those that have traditionally be used with expression alone, in both bulk and scRNA-seq settings. We used the inferred GRN to prioritize key regulators for the mouse Embryonic Stem Cell (mESC) state and validate 58 regulators experimentally. We identify both known and novel regulators of the mESC state and further validate the targets of 4 known and novel regulators. Our validation experiments suggest that computationally inferred networks can capture functional targets of TFs with higher precision than estimated in current benchmarks, however, it is important to generate context-specific gold standards.

PMID:40661601 | PMC:PMC12259028 | DOI:10.1101/2025.06.09.658650

Analyst. 2025 Jul 15. doi: 10.1039/d5an00394f. Online ahead of print.

ABSTRACT

Caenorhabditis elegans (C. elegans) is a typical model organism that has predominantly relied on growth using a bacterial diet, presenting limitations for automated experimentations (mainly due to the requirement of periodic transfer to new plates), and accuracy of results (because of possible interference by bacterial metabolism in liquid media), which makes flexible manipulation and long-term tracking difficult. C. elegans Maintenance Medium (CeMM), a chemically defined sterile liquid medium, holds the potential to solve these problems. Population-level studies of C. elegans cultured in CeMM have shown that nematode development slows, fecundity declines, lifespan increases, lipid and protein stores decrease, and gene expression changes relative to that on a bacterial diet. However, automated cultivation of C. elegans in CeMM, long-term tracking and phenotyping at single-worm level remains challenging. Here, we developed a chamber-array chip (WormChip-1.8) and an integrated and enclosed microfluidic device, CeMM-WormTracker, with the capability of automating fluid control and worm manipulation for single-worm level tracking and phenotyping of C. elegans grown in CeMM. By using a microscope, the CeMM-WormTracker allows for observation of C. elegans development, motility, reproduction, and survival for a long period of time. Our data demonstrate that it is possible to longitudinally track and phenotype the growth and development of nematodes at single-worm level for at least 75 days within the device, enabling comprehensive monitoring of the whole reproductive period and lifespan in sterile liquid culture, which is difficult for well plate-based experiments. Comparing with the results from 96-well plates, the development, activity, and reproduction of nematodes in the microfluidic device seems more stable. Thus, the CeMM-WormTracker provides feasible solutions for automated and high-throughput experimentations in studies of C. elegans, both on the ground and in orbit.

PMID:40660942 | DOI:10.1039/d5an00394f

Nat Commun. 2025 Jul 14;16(1):6496. doi: 10.1038/s41467-025-61846-3.

ABSTRACT

Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. However, most analytical techniques capture only a single snapshot, disregarding the temporal context. A comprehensive understanding of the temporal heterogeneity of HSCs necessitates live-cell, real-time and non-invasive analysis. Here, we developed a prediction system for HSC diversity by integrating single-HSC ex vivo expansion technology with quantitative phase imaging (QPI)-driven machine learning. By analyzing the cellular kinetics of individual HSCs, we discovered previously undetectable diversity that snapshot analysis cannot resolve. The QPI-driven algorithm quantitatively evaluates stemness at the single-cell level and leverages temporal information to significantly improve prediction accuracy. This platform advances the field from snapshot-based identification of HSCs to dynamic, time-resolved prediction of their functional quality based on past cellular kinetics.

PMID:40659629 | DOI:10.1038/s41467-025-61846-3

G3 (Bethesda). 2025 Jul 14:jkaf156. doi: 10.1093/g3journal/jkaf156. Online ahead of print.

ABSTRACT

Although gene regulation occurs both transcriptionally and post-transcriptionally, systems-level characterizations of RNA-binding proteins (RBPs) are still lacking compared to transcription factors. RNA-binding proteins have gene expression functions that include regulating RNA splicing, localization, translation, and turnover. Mapping the regulatory networks that they are involved in will thus be critical for a comprehensive understanding of gene regulation during development. We updated the wRBP1.0 compendium of putative C. elegans RNA-binding proteins to 928 proteins in WS290 and have catalogued their expression and developmental phenotypes using existing functional genomic resources. Many RBP genes are expressed in a cell type- and developmental stage-specific manner in the embryo, emphasizing that RBPs can contribute to distinct gene expression patterns. In addition, RBPs are highly conserved, and their loss can result in a wide range of developmental defects. This updated compendium will provide a resource for functional studies of RBP regulatory networks in C. elegans.

PMID:40658798 | DOI:10.1093/g3journal/jkaf156

ACS Nano. 2025 Jul 14. doi: 10.1021/acsnano.5c04337. Online ahead of print.

ABSTRACT

Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in precision health strategies for older adults. For this population, effective strategies can be achieved by the integration of wearable devices, nanosensors, and machine learning. Wearable devices enable continuous monitoring of diverse, real-time health metrics, serving as vital tools for collecting comprehensive health data. Nanosensors can be loaded into wearable devices to enhance their performance by significantly improving detection sensitivity and specificity, thereby increasing the accuracy and reliability of the data collected. Meanwhile, machine learning provides powerful methods for rapid and efficient analysis of large-scale health data, driving the optimization of nanosensors as well as wearable devices. This review examines the synergistic roles of wearable devices, nanosensors, and machine learning in the precision health management field, focusing on the value of big health data (i.e., big data in health care). We begin by exploring wearable devices as critical tools for gathering extensive health information, followed by an in-depth discussion of how nanosensors enhance data quality. Subsequently, we highlight the contributions of machine learning algorithms to the precise analysis of big health data and propose several proactive health management strategies from the perspective of "diagnosis-analysis-prevention". Finally, we present perspectives on the future integration of these technologies to advance comprehensive health management, precision diagnostics, and personalized medicine for older individuals.

PMID:40657801 | DOI:10.1021/acsnano.5c04337

Am J Physiol Heart Circ Physiol. 2025 Jul 14. doi: 10.1152/ajpheart.00106.2025. Online ahead of print.

ABSTRACT

Creatine kinase (CK) is considered a crucial energy transfer system in cardiac muscle. Some studies have suggested that reduced CK energy transfer in the heart causes energy starvation, limits cardiac performance, and ultimately leads to heart failure. In agreement with this hypothesis, the hearts from creatine-deficient mice lacking arginine:glycine amidinotransferase (AGAT KO) have been shown, in some experiments, to resemble failing hearts. However, it is unclear if AGAT KO induces changes in cardiomyocyte substructure and Ca2+ cycling that resemble heart failure, including impairment of sarcoplasmic reticulum (SR) Ca2+ release and reuptake. To investigate this, we assessed functional and structural aspects of Ca2+ handling in cardiomyocytes from KO and WT littermates. We found minor, sex-dependent differences in the organization of transverse tubules and ryanodine receptors (RyRs), no differences in the expression and relative phosphorylation of RyR and PLB, but higher S100A1 expression levels. AGAT KO cardiomyocytes exhibited larger and longer Ca2+ transients with the same decay rate as WT. Ca2+ spark frequency and SR Ca2+ content were also increased in KO, while sodium-calcium exchanger activity was unchanged. Thus, our results strongly suggest that SR Ca2+ cycling is augmented in AGAT KO hearts. Although AGAT KO hearts also exhibited increased AMPK activation, suggesting higher levels of AMP/ADP, this did not detectably impair sarcoendoplasmic reticulum Ca2+-ATPase activity. In conclusion, the changes in AGAT KO cardiomyocytes are opposite to those in failing cardiomyocytes, showing that life-long absence of CK energy transfer does not lead to heart failure.

PMID:40657789 | DOI:10.1152/ajpheart.00106.2025

Elife. 2025 Jul 14;14:RP104008. doi: 10.7554/eLife.104008.

ABSTRACT

Generalising information from ourselves to others, and others to ourselves allows for both a dependable source of navigation and adaptability in interpersonal exchange. Disturbances to social development in sensitive periods can cause enduring and distressing damage to lasting healthy relationships. However, identifying the mechanisms of healthy exchange has been difficult. We introduce a theory of self-other generalisation tested with data from a three-phase social value orientation task - the Intentions Game. We involved humans with (n=50) and without (n=53) a diagnosis of borderline personality disorder and assessed whether infractions to self-other generalisation may explain prior findings of disrupted social learning and instability. Healthy controls initially used their preferences to predict others and were influenced by their partners, leading to self-other convergence. In contrast, individuals with borderline personality disorder maintained distinct self-other representations when learning about others. This allowed for equal predictive performance compared to controls despite reduced updating sensitivity. Furthermore, we explored theory-driven individual differences underpinning contagion. Overall, the findings provide a clear explanation of how self-other generalisation constrains and assists learning, and how childhood adversity is associated with separation of internalised beliefs. Our model makes clear predictions about the mechanisms of social information generalisation concerning both joint and individual reward.

PMID:40657727 | DOI:10.7554/eLife.104008

Liver Int. 2025 Aug;45(8):e70224. doi: 10.1111/liv.70224.

ABSTRACT

BACKGROUND AND AIMS: Plastic particles are a global pollution problem, and humans are potentially exposed to them. Ingested plastic particles, microparticles (MPs) and nanoparticles (NPs), predominantly accumulate in the liver and cause hepatotoxicity through oxidative stress and metabolic dysfunction. NPs promote more toxic actions than MPs; however, the mechanisms involved in developing and progressing metabolic dysfunction-associated steatotic liver disease (MASLD) from chronic exposure to NPs remain poorly understood. Hedgehog (Hh) signalling regulates MASLD pathogenesis. Herein, we investigated the pathophysiological effects of NPs in MASLD.

METHODS: Mice were orally administered NPs via drinking water while fed a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) for 12 weeks.

RESULTS: NPs increased lipid accumulation in hepatocytes and apoptosis. Moreover, these actions were enhanced in lipotoxicity-exposed hepatocytes. Chronically exposed NPs accumulated in mice livers and aggravated CDAHFD-induced hepatic damage, especially fibrosis. Activated Hh signalling in the CDAHFD group was elevated by NP treatment. Increased Sonic Hh expression in the hepatocytes of NP-treated mice in the CDAHFD group triggered Hh signalling in hepatic stellate cells (HSCs), which promoted liver fibrosis.

CONCLUSIONS: These results demonstrate that chronic exposure to NPs increases vulnerability to MASLD progression, suggesting that NPs are a potentially harmful factor in the development and progression of liver disease.

PMID:40657663 | DOI:10.1111/liv.70224

F1000Res. 2025 Jun 13;14:10. doi: 10.12688/f1000research.160217.2. eCollection 2025.

ABSTRACT

The enzyme stearoyl-CoA desaturase (SCD1) is a modulator of lipid metabolism by catalyzing the biosynthesis of mono-unsaturated fatty acids from saturated fatty acids. Understanding the specific mechanisms by which SCD1 plays in health and disease can provide novel insides in therapeutic targets, a process that would be facilitated by the availability of high-quality antibodies. Here we have characterized nine SCD1 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

PMID:40657179 | PMC:PMC12246776 | DOI:10.12688/f1000research.160217.2

Biol Sport. 2025 Feb 5;42(3):185-195. doi: 10.5114/biolsport.2025.146790. eCollection 2025 Jul.

ABSTRACT

This randomized controlled trial compared the effectiveness of high-intensity off- and on-bike resistance training (RT) in well-trained cyclists. Thirty-seven cyclists incorporated into their cycling routine a 10-week RT only differing in the exercise used: full squat (off-bike RT, n = 12) or high-intensity all-out pedaling efforts (on-bike RT, n = 12). RT variables like intensity (% maximal dynamic force, MDF), volume, sets, and rest were identical between groups. A third group of cyclists who continued their cycling routine but did not include additional RT stimuli was used as a control (n = 13). The cycling volume at each intensity zone was also matched between the three groups. No significant differences were found between off- and on-bike RT in any parameter. RT groups improved the maximal aerobic power (ES ≥ 0.37) and that attained at the respiratory compensation point (RCP, ES ≥ 0.20). The on-bike RT also significantly enhanced power attained at the ventilatory threshold (ES = 0.24). Off-bike MDF was meaningfully enhanced by both RT groups (ES ≥ 0.16), whereas the on-bike group also significantly increased pedaling MDF (ES = 0.67). Quadriceps size was significantly increased by the off-bike group (ES = 0.22), whereas the on-bike RT also tended to augment this parameter (ES = 0.15) and patellar tendon size (ES = 0.35). Improvements in both RT regimes for time-to-exhaustion capacity (ES ≥ 0.30) were considerable but not significant. The off-bike group tended to increase injury-related symptoms (ES ≥ 0.33). The control group significantly decreased off-and on-bike MDF (ES ≤ -0.40) and quadriceps size (ES = -0.26). These findings suggest that high-intensity on-bike RT is an effective alternative to off-bike RT to safely increase strength, muscle-tendon structure, and cycling performance.

PMID:40657002 | PMC:PMC12244400 | DOI:10.5114/biolsport.2025.146790

Biol Sport. 2025 Mar 24;42(3):303-311. doi: 10.5114/biolsport.2025.147013. eCollection 2025 Jul.

ABSTRACT

Hypnosis is known for its effects on various psychophysiological phenomena, such as perception, emotions, fatigue, and muscle strength. Besides the conflicting evidence on the influence of hypnosis on muscle performance, its role in influencing central or peripheral fatigue remains poorly understood. Here, we investigated the effects of a single hypnosis session, terminated with a precise posthypnotic suggestion, on muscle strength, endurance, and myoelectric activity. Thirty participants (M = 17, F = 13) were divided into a Control (CO) and a Hypnosis group (HY). Handgrip strength and endurance were tested in three pre- and post-training phases: i) holding the handgrip as strongly as possible for 5 seconds (i.e. a measure of muscle strength); ii) after a 1-minute passive pause, holding the handgrip as strongly and as long as possible (i.e. a measure of muscle endurance); iii) after a further 1-minute pause, the first trial was repeated. All these procedures were repeated after a 30-minute rest period during which the CO could use the time freely, the HY was subjected to the hypnosis session. During the experimental procedures, surface EMG was applied to the forearm muscles to assess neuromuscular fatigue. Regardless of a stronger improvement between pre- and post-processing in the HY, we found no interaction effect between the groups. This suggests that a single post-hypnotic suggestion is not sufficient to significantly increase the force exerted over time (i.e., impulse), and that the observed HY improvement may be influenced by highly susceptible participants. Furthermore, despite this difference, we found no change in forearm muscle activation. Our results show that a single hypnosis session negligibly altered muscular performance. These findings contribute to the debate on the topic of hypnosis and fatigue but require further investigation, given the observed tendency of the hypnosis group to delay fatigue.

PMID:40656992 | PMC:PMC12244397 | DOI:10.5114/biolsport.2025.147013

bioRxiv [Preprint]. 2025 May 11:2025.05.09.653024. doi: 10.1101/2025.05.09.653024.

ABSTRACT

SBMLNetwork is an open-source software library that makes the SBML Layout and Render packages practical for standards-based visualization of biochemical models. Current tools often manage model visualization data in custom-designed, tool-specific formats and store it separately from the model itself, hindering interoperability, reproducibility, and the seamless integration of visualization with model data. SBMLNetwork addresses these limitations by building directly on the SBML Layout and Render specifications, automating the generation of standards-compliant visualization data, offering a modular implementation with broad integration support, and providing a robust API tailored to the needs of systems biology researchers. We illustrate the capabilities of SBMLNetwork across key visualization tasks, including SBGN-compliant visualization, application of predefined style templates, layout arrangement to reflect pathway logic, and integration of model data into network diagrams. These examples demonstrate how SBMLNetwork enables high-level visualization features and seamlessly translate user intent into reproducible outputs that support both structural representation and dynamic data visualization within the SBML model. SBMLNetwork is freely available at https://github.com/sys-bio/SBMLNetwork under the MIT license.

PMID:40654664 | PMC:PMC12248005 | DOI:10.1101/2025.05.09.653024

Acta Pharm Sin B. 2025 Jun;15(6):3107-3124. doi: 10.1016/j.apsb.2025.04.009. Epub 2025 Apr 10.

ABSTRACT

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

PMID:40654361 | PMC:PMC12254786 | DOI:10.1016/j.apsb.2025.04.009

Acta Pharm Sin B. 2025 Jun;15(6):3041-3058. doi: 10.1016/j.apsb.2025.04.017. Epub 2025 Apr 22.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

PMID:40654335 | PMC:PMC12254822 | DOI:10.1016/j.apsb.2025.04.017

Comput Methods Programs Biomed. 2025 Jul 8;270:108916. doi: 10.1016/j.cmpb.2025.108916. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: This study explores an extension of the classic Hawk and Dove evolutionary game model by considering the influence of environmental or external resources on the players' fitness. This allows us to model the resulting heterogeneous population dynamics, which is of great importance for simulating cancer population growth and optimizing anti-cancer therapies.

METHODS: To model population heterogeneity, we are using an extension of classical spatial evolutionary game theory by introducing multidimensional spatial evolutionary games (MSEG). This allows for the study of genetic heterogeneity on a multidimensional lattice. The classic Hawk and Dove model is modified to reflect the impact of external resources. Various types and shapes of resource functions were included in the payoff matrix and then simulated to examine their impact on the model's dynamics and population heterogeneity.

RESULTS: The results are presented in time-dependent plots for both mean-field and spatial models. Additionally, spatial 2D and 3D matrices are presented to show the spatial distribution of both phenotypes analyzed in the extended Hawk and Dove model. The results reveal significant differences between the mean-field and spatial models for the same parameter values. Furthermore, differences are observed when comparing models with different resource functions.

CONCLUSION: The two-phenotype model was used to show the influence of external, time- and phenotype-specific resource functions on the dynamics of the game's phenotypes. Moreover, the study highlights that spatial models, which provide more accurate information about population heterogeneity, can yield significantly different results compared to mean-field models.

PMID:40652752 | DOI:10.1016/j.cmpb.2025.108916

Discov Oncol. 2025 Jul 13;16(1):1324. doi: 10.1007/s12672-025-03101-1.

ABSTRACT

BACKGROUND: The genetic mechanisms underlying non-Hodgkin lymphoma (NHL) and Hodgkin lymphoma (HL) remain understudied. While numerous genes associated with these lymphoid tumors have been identified, little research has focused on the genetic networks that directly drive NHL and HL pathogenesis.

METHODS: We conducted integrative genomic analyses, including a transcriptome-wide association study (TWAS), a proteome-wide association study (PWAS), and a summary-data-based Mendelian randomization (SMR), to identify causal genes for NHL and HL. TWAS and PWAS were performed using FUSION software by integrating GWAS data with gene and protein expression weights from large-scale datasets. The SMR analysis utilized cis-eQTL data to assess causal relationships between gene expression and lymphoma risk. Associations were deemed significant at p < 0.05.

RESULTS: The PWAS identified 106 proteins associated with NHL and 67 proteins associated with HL. The TWAS revealed 172 genes linked to NHL risk and 448 genes linked to HL risk. Finally, the SMR analysis highlighted 270 genes associated with NHL risk; there was with no evidence of heterogeneity in the HEIDI test, which supports pleiotropic effects. Key genes that influence NHL risk include KRT1, ERAP2, RMDN1, FAS, and C5, while UNC5B was identified as a significant causal gene for HL. Locus and effect plots were used to validate these findings by highlighting causal variants associated with lymphoma risks.

CONCLUSION: In this study, KRT1, ERAP2, RMDN1, FAS, C5, and UNC5B were identified as potential causal factors in lymphoma risk, underscoring mechanisms such as immune modulation and tumor suppression and providing insights into future therapeutic targets.

PMID:40652422 | DOI:10.1007/s12672-025-03101-1

J Proteome Res. 2025 Jul 13. doi: 10.1021/acs.jproteome.5c00285. Online ahead of print.

ABSTRACT

Early colorectal cancer (CRC) detection among inflammatory bowel disease improves treatment outcomes and survival. A sensitive and specific serum-based tool can bridge the gap between patient presentation and invasive colonoscopy, thereby enhancing early diagnosis. We screened serum biomarkers in colonoscopy-positive (CP, cancer) and colonoscopy-negative (CN, other bowel diseases) individuals, as well as in healthy controls (n = 20 each), to identify CRC-specific markers. Using data-independent acquisition-mass spectrometry, three proteins were identified as uniquely altered in the CP group compared with CN. We found that a serum protein called brain-specific angiogenesis inhibitor I-associated protein 3 was significantly overexpressed in CRC patients, which can distinguish CP patients from CN patients. Additionally, 19 neoantigen peptides specific to the CRC serum proteome were identified. Further validation in an independent set of samples (n = 10 per group) using parallel reaction monitoring was performed for the potential biomarker and neoantigen identified. These proteins were combined with carcinoembryonic antigen into a multiprotein panel, which enhanced diagnostic performance (AUC = 0.758), yielding 67% sensitivity, 64% specificity, and 65% accuracy. These findings support the potential of a targeted serum-based panel for preselecting symptomatic individuals for colonoscopic evaluation. However, further studies are needed in a larger cohort to evaluate clinical utility.

PMID:40652393 | DOI:10.1021/acs.jproteome.5c00285

Microbiome. 2025 Jul 12;13(1):162. doi: 10.1186/s40168-025-02139-1.

ABSTRACT

BACKGROUND: Mobile genetic elements (MGEs) drive horizontal gene transfer and microbial evolution, spreading adaptive genes across microbial communities. While extensively studied in other ecosystems, the role of MGEs in shaping ruminant gastrointestinal microbiomes-especially their impact on diversity, adaptation, and dietary responsiveness-remains largely unexplored. This study systematically profiles MGE distribution and functionality across gastrointestinal regions in multiple ruminant species to advance our understanding of microbial adaptation.

RESULTS: Across 2458 metagenomic samples from eight ruminant species, we identified 4,764,110 MGEs-a ~ 216-fold increase over existing MGE databases. These elements included integrative and conjugative elements, integrons, insertion sequences, phages, and plasmids, with mobilization patterns largely confined to closely related microbial lineages. The distribution of MGEs varied by GIT regions, often reflecting nutritional gradients. In a validation cohort, GH1-carrying plasmids enriched in carbohydrate-active enzymes were found to predominate in the stomach, showing notable responsiveness to forage-based diets. All annotated MGEs have been compiled into a publicly accessible database, rumMGE ( https://rummge.liulab-njau.com ), to support further research.

CONCLUSIONS: This study substantially expands the catalog of known MGEs in ruminants, revealing their diverse roles in microbial evolution and functional adaptation to dietary changes. The findings provide a valuable resource for advancing research on microbial functionality and offer insights with potential applications for enhancing ruminant health and productivity, through strategies aimed at modulating the microbiome in agricultural contexts. Video Abstract.

PMID:40652256 | DOI:10.1186/s40168-025-02139-1