Sci Data. 2025 Jun 20;12(1):1047. doi: 10.1038/s41597-025-05295-z.

ABSTRACT

Physical samples and their associated data and metadata underpin scientific discoveries across disciplines and can enable new science when appropriately archived. However, there are significant gaps in current practices and infrastructure that prevent accurate provenance tracking, reproducibility, and attribution. For most samples, descriptive metadata are often sparse, inaccessible, or absent. Samples and associated data and metadata may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkage or provenance tracking as new information is generated over time. The Earth Science Information Partners (ESIP) Physical Samples Curation Cluster has therefore developed guidance for scientific authors on 'Publishing Open Research Using Physical Samples.' This involved synthesizing existing practices, gathering community feedback, and assessing real-world examples. We identified improvements needed to enable authors to efficiently cite and link Earth science samples and related data, and track their use. Our goal is to help improve discoverability, interoperability, and reuse of physical samples, and associated data and metadata. Though primarily focused on the needs of Earth and environmental sciences, these guidelines are broadly applicable.

PMID:40541980 | DOI:10.1038/s41597-025-05295-z

Cell Syst. 2025 Jun 13:101321. doi: 10.1016/j.cels.2025.101321. Online ahead of print.

ABSTRACT

Responses of endothelial cells to elevated levels of vascular endothelial growth factor (VEGF), frequently accompanying local decrease in oxygen supply, include loosening of cell contacts, rearrangement of cells in vessel remodeling, and ultimately, angiogenic growth. How these complex processes, occurring on diverse time scales, are coordinated and how they are guided by a single key signaling input is still incompletely understood. Here, we show that the various phenotypic responses associated with VEGF signaling are controlled at different steps of a pathway involving sequential activation of Src, tumor endothelial marker 4 (TEM4), YAP, and components of pro-angiogenic Notch signaling. Notably, due to feedback regulation at different pathway levels, the functional outcomes are controlled by oscillations of the pathway components occurring on distinct time scales. Deeper pathway layers integrate faster upstream responses and control progressively slower phenotypic outcomes. This signal-decoding pathway organization can ensure a high degree of complexity in a vital physiological process. A record of this paper's transparent peer review process is included in the supplemental information.

PMID:40541183 | DOI:10.1016/j.cels.2025.101321

Mod Pathol. 2025 Jun 19;38(8):100819. doi: 10.1016/j.modpat.2025.100819. Online ahead of print.

NO ABSTRACT

PMID:40541156 | DOI:10.1016/j.modpat.2025.100819

Genetics. 2025 Jun 20:iyaf118. doi: 10.1093/genetics/iyaf118. Online ahead of print.

ABSTRACT

Epistasis can profoundly influence evolutionary dynamics. Temporal genetic data, consisting of sequences sampled repeatedly from a population over time, provides a unique resource to understand how epistasis shapes evolution. However, detecting epistatic interactions from sequence data is technically challenging. Existing methods for identifying epistasis are computationally demanding, limiting their applicability to real-world data. Here, we present a novel computational method for inferring epistasis that substantially reduces computational costs without sacrificing accuracy. We validated our approach in simulations and applied it to study HIV-1 evolution over multiple years in a data set of 16 individuals. There we observed a strong excess of negative epistatic interactions between beneficial mutations, especially mutations involved in immune escape. Our method is general and could be used to characterize epistasis in other large data sets.

PMID:40540490 | DOI:10.1093/genetics/iyaf118

Elife. 2025 Jun 20;13:RP93191. doi: 10.7554/eLife.93191.

ABSTRACT

Perceptual updating has been hypothesised to rely on a network reset modulated by bursts of ascending neuromodulatory neurotransmitters, such as noradrenaline, abruptly altering the brain's susceptibility to changing sensory activity. To test this hypothesis at a large-scale, we analysed an ambiguous figures task using pupillometry and functional magnetic resonance imaging (fMRI). Behaviourally, qualitative shifts in the perceptual interpretation of an ambiguous image were associated with peaks in pupil diameter, an indirect readout of phasic bursts in neuromodulatory tone. We further hypothesised that stimulus ambiguity drives neuromodulatory tone, leading to heightened neural gain, hastening perceptual switches. To explore this hypothesis computationally, we trained a recurrent neural network (RNN) on an analogous perceptual categorisation task, allowing gain to change dynamically with classification uncertainty. As predicted, higher gain accelerated perceptual switching by transiently destabilising the network's dynamical regime in periods of maximal uncertainty. We leveraged a low-dimensional readout of the RNN dynamics to develop two novel macroscale predictions: perceptual switches should occur with peaks in low-dimensional brain state velocity and with a flattened egocentric energy landscape. Using fMRI, we confirmed these predictions, highlighting the role of the neuromodulatory system in the large-scale network reconfigurations mediating adaptive perceptual updates.

PMID:40540408 | DOI:10.7554/eLife.93191

Chem Biodivers. 2025 Jun 20:e00668. doi: 10.1002/cbdv.202500668. Online ahead of print.

ABSTRACT

In this study, a comprehensive chemical profiling of Cymbopogon citratus metabolites grown in Aceh, Indonesia, was performed by UHPLC-ESI-QTOF-MS/MS on its 80% ethanol extract, and GC-MS on its hydrodistilled essential oil. The samples were also investigated for their anti-inflammatory activity through bovine serum albumin (BSA) protein denaturation inhibition and human red blood cell (HRBC) membrane stabilization techniques. LC-MS/MS analysis of the extract putatively identified 54 compounds, represented by 23 phenolic compounds (flavonoids, flavonoid glycosides, lignans, anthraquinone glycosides, coumarins, and a phenolic acid), 7 carboxylic acids and esters, 7 carbohydrates, 5 amino acids, 5 lipids, 2 steroids, 2 lactones, 2 alkaloids, and 1 monoterpenoid. GC-MS analysis of the essential oil indicated it was mainly made up of monoterpenoids with neral (25.89%) and geranial (49.97%) as the major compounds. The chemical contents identified in the extract and essential oil of the plant grown in Aceh were qualitatively and quantitatively different from samples reported elsewhere. Both extract and essential oil exhibited anti-inflammatory activity by stabilizing the HRBC membrane against hypotonicity-induced hemolysis and inhibited the BSA protein denaturation in a concentration-dependent manner. The anti-inflammatory activity of C. citratus was attributed mainly to the presence of bioactive compounds especially phenolic compounds and monoterpenoids.

PMID:40540303 | DOI:10.1002/cbdv.202500668

J Am Soc Mass Spectrom. 2025 Jun 20. doi: 10.1021/jasms.5c00070. Online ahead of print.

ABSTRACT

Monoclonal antibodies (mAbs) have revolutionized immuno-oncology, with anti-programmed cell death protein 1 (PD1) mAbs emerging as key therapeutic agents in cancer treatment. This study presents the development and application of diethylpyrocarbonate (DEPC) covalent labeling-mass spectrometry (CL-MS) for detailed epitope mapping of anti-PD1 mAbs on PD1. By using DEPC CL-MS, we aimed to identify precise antibody binding sites on PD1 and benchmark its effectiveness against traditional X-ray crystallography. DEPC CL-MS offers high sensitivity and specificity while requiring less sample preparation and shorter analysis times, typically taking days or less, instead of months. PD1 was individually incubated with either nivolumab or a novel anti-human PD1 mAb (CU-MAB), followed by DEPC labeling, to assess DEPC modification extents under both binding and nonbinding conditions using bottom-up LC-MS/MS. Significant changes in DEPC modification at residues S27, S60, S62, S127, and K131 indicated binding sites and conformational shifts upon antibody interaction. These findings showed strong alignment with crystallography (PD1/nivolumab) and AlphaFold structural predictions (PD1/nivolumab and PD1/CU-MAB), highlighting the value of in-solution CL-MS for confirming AlphaFold predictions. This study underscores DEPC CL-MS as an efficient tool for epitope mapping, offering actionable insights into PD1-antibody interactions to drive therapeutic antibody development.

PMID:40540218 | DOI:10.1021/jasms.5c00070

Cardiovasc Drugs Ther. 2025 Jun 20. doi: 10.1007/s10557-025-07739-5. Online ahead of print.

ABSTRACT

PURPOSE: Cardiovascular diseases (CVDs) continue to be the leading cause of death globally, driven by a complex interplay of genetic, epigenetic, and environmental factors. Traditional risk factors alone fail to explain the individual variability in disease susceptibility and progression. Recent advances in genomics and epigenomics have revealed key molecular mechanisms that regulate cardiovascular function, highlighting the importance of gene network dynamics and epigenetic regulation.

METHODS: This review systematically analyzes peer-reviewed literature from the past decade sourced from electronic databases including PubMed and Google Scholar. It compiles the multifaceted roles of DNA methylation, histone modifications, chromatin remodeling, and noncoding RNAs in regulating cardiovascular gene expression, cellular phenotypes, and disease pathogenesis.

RESULTS: DNA methylation influences the transcriptional activity of gene expression associated with atherosclerosis, myocardial infarction, and hypertension, while histone modifications and ATP-dependent chromatin remodeling regulate cardiac hypertrophy, fibrosis, and regeneration. Noncoding RNAs further act as critical regulators of angiogenesis, inflammation, and myocardial remodeling. Therapeutically, these findings have facilitated the development of epigenetic drugs and gene-editing technologies targeting specific molecular pathways involved in CVD progression. Emerging technologies such as CRISPR/Cas9, RNA-based therapies, and small-molecule inhibitors of epigenetic enzymes hold potential for correct abnormal gene expression patterns. Moreover, integrative multi-omics and systems biology approaches are advancing personalized treatment strategies, improving the accuracy and effectiveness of cardiovascular interventions.

CONCLUSION: Collectively, unraveling the complex molecular interactions among gene networks, epigenetic alterations, and targeted therapeutic mapping aims to combat CVD with better precision and efficacy.

PMID:40540082 | DOI:10.1007/s10557-025-07739-5

Environ Sci Technol. 2025 Jun 20. doi: 10.1021/acs.est.5c00636. Online ahead of print.

ABSTRACT

Phytoplankton are the primary producers of marine neurotoxins such as β-N-methylamino-l-alanine (BMAA), which cause seafood poisoning outbreaks in estuarine and coastal regions. BMAA has gained much attention for its pathogenic link to Alzheimer's and Parkinson's disease. However, whether BMAA accumulates in diatoms under fluctuations in estuarine and coastal areas remains largely unknown. In this study, we investigated BMAA biosynthesis in the model diatom Phaeodactylum tricornutum under simulated conditions of fluctuating nitrogen and salinity in estuarine regions. BMAA was detectable in P. tricornutum under all simulated seawater or hyper-eutrophic conditions, although nitrogen source and salinity interactively impact BMAA accumulation. In addition, high-nitrogen wastewater conditions promoted carbon metabolism, including the Calvin cycle, glycolysis, fatty acid biosynthesis, and decreased nitrogen metabolism and BMAA production. Finally, we proposed and elucidated a complete biosynthetic pathway of BMAA originating from glutamate, incorporating catalysis by S-adenosylmethionine (SAM)-dependent methyltransferases in diatoms, as inferred through artificial intelligence-based pathway analysis. This study marks the first attempt to decipher the BMAA metabolic pathway in diatoms, which provides a paradigm shift to identify conditions that trigger toxin production and also provides valuable metrics to address the complexity and unpredictability of monitoring and forecasting algal blooms.

PMID:40539973 | DOI:10.1021/acs.est.5c00636

J Chem Inf Model. 2025 Jun 20. doi: 10.1021/acs.jcim.5c00535. Online ahead of print.

ABSTRACT

A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RNA binding site, a highly conserved COVID-19 target. Twenty-three participating teams comprised of computational chemists and data scientists used protein structure and data from fragment-screening paired with advanced computational and machine learning methods to each predict up to 100 inhibitory ligands. Across all teams, 1957 compounds were predicted and were subsequently procured from commercial catalogs for biophysical assays. Of these compounds, 0.7% were confirmed to bind to Nsp13 in a surface plasmon resonance assay. The six best-performing computational workflows used fragment growing, active learning, or conventional virtual screening with and without complementary deep-learning scoring functions. Follow-up functional assays resulted in identification of two compound scaffolds that bound Nsp13 with a Kd below 10 μM and inhibited in vitro helicase activity. Overall, CACHE #2 participants were successful in identifying hit compound scaffolds targeting Nsp13, a central component of the coronavirus replication-transcription complex. Computational design strategies recurrently successful across the first two CACHE challenges include linking or growing docked or crystallized fragments and docking small and diverse libraries to train ultrafast machine-learning models. The CACHE #2 competition reveals how crowd-sourcing ligand prediction efforts using a distinct array of approaches followed with critical biophysical assays can result in novel lead compounds to advance drug discovery efforts.

PMID:40539604 | DOI:10.1021/acs.jcim.5c00535

Anat Rec (Hoboken). 2025 Jun 20. doi: 10.1002/ar.70011. Online ahead of print.

NO ABSTRACT

PMID:40539471 | DOI:10.1002/ar.70011

Front Bioeng Biotechnol. 2025 Jun 5;13:1578467. doi: 10.3389/fbioe.2025.1578467. eCollection 2025.

ABSTRACT

The brain extracellular matrix (ECM) regulates myelin repair and regeneration following a demyelinating event by interacting with neuronal progenitors and immune cells. Therefore, generation and characterization of decellularized human brain tissue (DHBT) in regions with distinct neuroregenerative capacities are essential to determine factors modulating the cellular regenerative behavior. We have established an effective decellularization protocol for the human neural stem cell (NSC)-rich subventricular zone (SVZ) as well as, frontal cortex (FC) and white matter (WM), and defined region-specific matrisomes with comparative proteomics. Subsequently, as proof-of-concept, survival and differentiation of NSCs and monocytes within the DHBT were investigated. The proteomic analysis of the DHBT confirmed the retention of matrisome proteins such as COL4A1, FBB, NCAN, ANXA2. Unique to the SVZ were LGI3 and C1QB, while annexins, S100A and TGM2 were found in FC; S100B was exclusive to the WM. NSCs cultured within WM and FC acquired an astrocytic phenotype, but both astrocytic and oligodendrocytic phenotypes were promoted by the SVZ DHBT. Moreover, imaging mass cytometry analysis indicated an anti-inflammatory phenotype differentiation of monocytes seeded on SVZ and WM. Thus, the established model is suitable for investigation of ECM properties and assessment of cell-matrix interactions.

PMID:40539096 | PMC:PMC12177465 | DOI:10.3389/fbioe.2025.1578467

Front Cell Dev Biol. 2025 Jun 5;13:1610435. doi: 10.3389/fcell.2025.1610435. eCollection 2025.

ABSTRACT

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD) characterized primarily by immune dysregulation. Its pathogenesis involves multiple factors, including dysregulation of T-cell subsets, hypersecretion of pro-inflammatory cytokines, imbalance in the gut microbiota, and disruption of the intestinal barrier. Among T-cell subsets, abnormal activation of Th1 and Th17 cells, in conjunction with Treg dysfunction, significantly amplifies local pro-inflammatory signals. Pro-inflammatory cytokines, such as TNF-α, IL-6, and IL-17, exacerbate apoptosis and disrupt tight junctions (TJs) in intestinal epithelial cells (IECs), thereby creating favorable conditions for invasion by pathogenic bacteria and their metabolites. Intestinal microecological imbalance not only leads to significant alterations in the structure of the bacterial flora but also involves abnormal fluctuations in its metabolites that directly regulate intestinal immune homeostasis, a factor closely associated with the severity of inflammation and prognosis of ulcerative colitis. Recent studies have demonstrated that in the treatment of UC, traditional Chinese medicine (TCM) achieves a multi-target, multi-pathway integrated intervention by regulating immune cell differentiation, balancing inflammatory factor levels, repairing the intestinal epithelial barrier, and remodeling the structure of the bacterial flora. This article reviews the pathogenic mechanisms underlying immune dysregulation in UC and the advances in research on TCM's role in immune regulation, anti-inflammatory repair, and flora modulation, encompassing the mechanisms of action of individual active ingredients and classic TCM compound formulas. Although some studies have preliminarily confirmed TCM's potential to modulate immunity and repair the intestinal barrier, breakthroughs in mechanism analysis, herb standardization, and large-scale validation remain forthcoming. It is anticipated that the unique advantages of TCM will be translated into a more precise therapeutic strategy for UC through modern molecular and systems biology approaches.

PMID:40538978 | PMC:PMC12176777 | DOI:10.3389/fcell.2025.1610435

RSC Adv. 2025 Jun 19;15(26):20745-20759. doi: 10.1039/d5ra01044f. eCollection 2025 Jun 16.

ABSTRACT

The identification of metabolites in biological samples presents a challenge in untargeted metabolomics, mainly due to limited databases and inadequate chromatography. Current LC columns suffer from high pH instability (silica-based), low efficiencies and pressure limitations (polymer-based), or inadequate retention of polar/semi-polar metabolites (reverse-phase). In this study, a comprehensive LC-MS workflow was developed to address these limitations using a novel zwitterionic HILIC (Z-HILIC), high-resolution MS, deep-scan data-dependent acquisition (DDA), and a large chemical library comprising 990 standards. The method performance was evaluated and compared with a widely-used ZIC-pHILIC method. Z-HILIC detected 707 (71%) of the standards compared to 543 (55%) standards with the ZIC-pHILIC showing enhanced resolution, sensitivity, selectivity and retention time (RT) distribution. In triple-negative Hs578T breast cancer cell extracts spiked with the standards, Z-HILIC annotated 79.1% of the detected standards versus 66.6% with ZIC-pHILIC, demonstrating improved sensitivity, stability, and reduced matrix effects for metabolite profiling. Deep-scan DDA of the spiked cell extracts increased the number of the identified metabolites using RT, m/z and MS/MS by more than 80% compared to standard DDA. The workflow was used to investigate the metabolic signature of doxorubicin-treated Hs578T cells (n = 15). The analysis resulted in identifying 173 metabolites, of which 26 metabolites and 20 metabolic pathways were significantly altered in doxorubicin treated cells compared to controls. These pathways were associated with oxidative stress, mitochondrial dysfunction, and impaired biosynthesis, consistent with prior knowledge about the action of doxorubicin. This comprehensive workflow promises to enhance metabolite profiling across diverse metabolomics studies.

PMID:40538746 | PMC:PMC12177712 | DOI:10.1039/d5ra01044f

Brief Bioinform. 2025 May 1;26(3):bbaf270. doi: 10.1093/bib/bbaf270.

ABSTRACT

Studying phenotype-specific regulatory mechanisms is crucial to understanding the molecular basis of diseases and other complex traits. However, existing approaches for constructing multi-omic regulatory networks MO-RN are scarce, and most cannot integrate diverse omics modalities, incorporate prior biological knowledge, or infer phenotype-specific networks. To address these challenges, we present MORE (Multi-Omics REgulation), a novel R package for inferring multi-modal regulatory networks. MORE is available at https://github.com/BiostatOmics/MORE and supports any number and type of omics layers while optionally incorporating prior regulatory knowledge. Leveraging advanced regression-based models and variable selection techniques, MORE identifies significant regulatory relationships. This tool also provides useful functionalities for the biological interpretation of MO-RN: network visualisations, differential regulatory networks, and functional enrichment analyses of key network features. We evaluated MORE on simulated multi-omic datasets and benchmarked it against state-of-the-art tools. Our tool consistently outperformed other methods regarding accuracy in identifying significant regulators, model goodness-of-fit, and computational efficiency. We further applied MORE to a multi-omic ovarian cancer dataset to uncover tumour subtype-specific regulatory mechanisms associated with distinct survival outcomes. This analysis revealed differential regulatory patterns to understand the molecular basis of each subtype. By addressing the limitations of methods for multi-omic network inference, MORE represents a valuable resource for studying regulatory systems. Its ability to construct phenotype-specific regulatory networks with high accuracy and interpretability positions it as a useful resource for researchers seeking to unravel the complexities of molecular interactions and regulatory mechanisms across diverse biological contexts.

PMID:40538029 | DOI:10.1093/bib/bbaf270

Dev Dyn. 2025 Jun 19. doi: 10.1002/dvdy.70054. Online ahead of print.

ABSTRACT

BACKGROUND: Schwann cells provide peripheral nerve trophic support, myelinate axons, and assist in repair. However, Schwann cell repair capacity is limited by chronic injury, disease, and aging. Schwann cell reprogramming is a cellular conversion strategy that could provide a renewable cell supply to repair injured nerves. Here, we developed a plasmid-based approach to test the Schwann cell conversion potential of four glial transcription factors.

RESULTS: We employed four transcription factors implicated in Schwann cell differentiation and repair: Sox10, Sox2, Jun, and Pax3. Expression vectors were generated for Sox10 alone and two triple transcription factor combinations: Jun-Pax3-Sox2 (triple 1, T1) and Sox10-Jun-Sox2 (triple 2, T2). Mouse embryonic fibroblasts (MEFs) were transfected with these vectors, transferred to glial inductive media, and Schwann cell-marker expression was in assessed by immunostaining, flow cytometry, and qPCR. All expression vectors repressed fibroblast-specific gene expression. However, T2 was most efficient at generating O4+ Schwann cell-like cells, which had some capacity to myelinate denervated axons from explanted dorsal root ganglia. In comparison, T1 more efficiently induced repair Schwann cell-marker expression in converted O4+ cells.

CONCLUSIONS: T1 and T2 convert MEFs to Schwann cells with different efficacies and gene expression profiles, and may provide cell-based therapies for peripheral nerve repair.

PMID:40538023 | DOI:10.1002/dvdy.70054

J Microbiol Biotechnol. 2025 Jun 12;35:e2503021. doi: 10.4014/jmb.2503.03021.

ABSTRACT

Chlorella, a genus of single-celled green algae, is widely industrially cultivated as a dietary supplement ingredient due to its high protein content and various nutrients. In this study, the immune-stimulating effect of solvent fractions prepared from Chlorella vulgaris (CV) and Chlorella protothecoides (CP) was evaluated through the expression of immune-related factors, such as TNF-α and IFN-γ in T cells obtained from mice. Both Chlorella species showed immunostimulatory effects in hexane and butanol fractions, but CV increased TNF-α only, while CP elevated both TNF-α and IFN-γ. In addition, the lipid profile of Chlorella was characterized using non-selective LC-MS/MS-based metabolomic analysis. According to the lipidomic results, the two species differed in lipid composition, with PC 32:1, PC 32:2, PC 34:5, DGDG 34:4, and DGDG 34:5 being enriched in the active fractions of CV, and PC 34:1, PC 34:2, PC O-15:2 and DGTS 34:4 being abundant in the fractions of CP. Furthermore, 5'-methylthioadenosine (MTA), which was detected in both Chlorella species, also exhibited immunostimulatory properties.

PMID:40537895 | DOI:10.4014/jmb.2503.03021

Geroscience. 2025 Jun 19. doi: 10.1007/s11357-025-01736-0. Online ahead of print.

ABSTRACT

Lung cancer is a leading cause of cancer-related mortality worldwide. As an age-related disease, its pathogenesis is shaped by several molecular hallmarks of aging, including impaired DNA repair and diminished stress resilience. The transcription factor NRF2 (nuclear factor erythroid 2-related factor 2) is a master regulator of oxidative stress defense and cellular survival. While NRF2 activation is protective in aging tissues, it may also be exploited by cancer cells to promote tumor progression and therapy resistance. This study aims to evaluate whether NRF2 pathway activation predicts clinical outcomes in lung cancer, with potential implications for the use of NRF2-inducing compounds. We analyzed transcriptomic and survival data from 2167 lung cancer patients using the KM Plotter database. A validated 14-gene NRF2 activation signature was used to stratify tumors by NRF2 pathway activity. Associations with overall survival (OS), first progression (FP), and post-progression survival (PPS) were assessed using Cox regression models and Kaplan-Meier analysis. High NRF2 signature expression was significantly associated with poorer OS (HR = 1.59, p = 1.3E-9), FP (HR = 1.61, p = 2.6E-5), and PPS (HR = 1.6, p = 0.002). The negative prognostic effect was most pronounced in patients with adenocarcinoma, node-negative disease, and in female patients. These findings highlight the dual role of NRF2 in promoting stress resilience and enabling cancer cell survival. NRF2 activation is a predictor of poor clinical outcomes in lung cancer. Given the widespread use of NRF2-inducing compounds such as resveratrol and sulforaphane, these findings raise important concerns about their safety in individuals at risk for or living with cancer. Our results underscore the importance of context-specific evaluation of NRF2-targeted interventions and caution against the indiscriminate use of NRF2-activating agents in aging populations, particularly in individuals at risk for lung cancer.

PMID:40537696 | DOI:10.1007/s11357-025-01736-0

Am J Reprod Immunol. 2025 Jun;93(6):e70115. doi: 10.1111/aji.70115.

ABSTRACT

PROBLEM: Recurrent spontaneous abortion (RSA) is defined as two or more consecutive spontaneous abortions in the first 24 weeks of pregnancy. However, the detailed molecular mechanisms behind RSA remain unclear.

METHOD OF STUDY: We used bioinformatics and systems biology approaches to analyze the underlying molecular mechanisms to provide new insights into the biology of M1 macrophage exosome differentially expressed genes (DEGs) in RSA patients and to identify potential drugs to treat RSA. The trophoblast (HTR-8) was co-cultured with the M1 macrophage exosomes induced by THP-1, and the cell model was constructed for transcriptome sequencing analysis and data source construction. Functional enrichment and pathway analysis of DEGs among the three groups were performed. In addition, differential expression of key genes was verified by RT-qPCR.

RESULTS: We obtained 172 DEGs from the sequencing data. Metabolic and immune-related pathways and functions are the main pathways of its enrichment. FOCX1, GATA2, YY1, TFAP2A, MEFF2A, and STAT3 are the major transcription factors (TFs) of M1 macrophage exosomes in RSA. Hsa-mir-106b-5p, hsa-mir-149-3p, and hsa-mir-520a-3p are associated with RSA. Finally, the DEGS-disease and DEGS-drug interaction networks are predicted. Gene Ontology (GO) and Kyoto Genome Encyclopedia (KEGG) enrichment analysis revealed clusters and targets associated with maternal and fetal interface immune tolerance in RSA M1 macrophage exosomes.

CONCLUSIONS: The candidate targets and drugs obtained from M1-type macrophage exosomes in this study may contribute to the effective treatment of RSA.

PMID:40536920 | DOI:10.1111/aji.70115

New Phytol. 2025 Jun 19. doi: 10.1111/nph.70324. Online ahead of print.

NO ABSTRACT

PMID:40536155 | DOI:10.1111/nph.70324