J Transl Med. 2025 Jul 11;23(1):782. doi: 10.1186/s12967-025-06799-3.

ABSTRACT

Ischemic stroke, the most prevalent type of stroke globally, poses significant challenges due to its high incidence, morbidity, and long-term disability. Microglia, the resident immune cells of the central nervous system (CNS), play a dual role in the context of ischemic stroke. While they contribute to neuroinflammation by releasing pro-inflammatory cytokines and exacerbating neuronal injury, they also facilitate tissue repair, angiogenesis, and restoration of the blood-brain barrier (BBB) integrity through the secretion of anti-inflammatory and neurotrophic factors. Triggering receptor expressed on myeloid cells 2 (TREM2), predominantly expressed on microglia, is a critical regulator of microglial proliferation, survival, phagocytosis, polarization, inflammation, and metabolism. TREM2 has emerged as a key modulator of immune responses in ischemic stroke. This review provides a comprehensive examination of the multifaceted roles of TREM2 in microglial biology during ischemic stroke, integrating current insights into its molecular mechanisms. Furthermore, it highlights TREM2's potential as a transformative therapeutic target, advancing our understanding of neuroimmune regulation and promoting recovery after stroke.

PMID:40646506 | DOI:10.1186/s12967-025-06799-3

Nat Comput Sci. 2025 Jul 11. doi: 10.1038/s43588-025-00832-7. Online ahead of print.

ABSTRACT

Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutions enhances statistical power but raises serious privacy concerns. Here we introduce FedProt, the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data, which utilizes federated learning and additive secret sharing. In the absence of a multicenter patient-derived dataset for evaluation, we created two: one at five centers from E. coli experiments and one at three centers from human serum. Evaluations using these datasets confirm that FedProt achieves accuracy equivalent to the DEqMS method applied to pooled data, with completely negligible absolute differences no greater than 4 × 10-12. By contrast, -log10P computed by the most accurate meta-analysis methods diverged from the centralized analysis results by up to 25-26.

PMID:40646319 | DOI:10.1038/s43588-025-00832-7

Nat Plants. 2025 Jul 11. doi: 10.1038/s41477-025-02070-1. Online ahead of print.

NO ABSTRACT

PMID:40646268 | DOI:10.1038/s41477-025-02070-1

Nat Commun. 2025 Jul 11;16(1):6425. doi: 10.1038/s41467-025-61555-x.

ABSTRACT

Although vaccines and treatments have strengthened our ability to combat the COVID-19 pandemic, new variants of SARS-CoV-2 continue to emerge in human populations. Because the evolution of SARS-CoV-2 is driven by mutation, a better understanding of its mutation rate and spectrum could improve our ability to forecast the trajectory of the pandemic. Here, we use circular RNA consensus sequencing (CirSeq) to determine the mutation rate of six SARS-CoV-2 variants and perform a short-term evolution experiment to determine the impact of these mutations on viral fitness. Our analyses indicate that the SARS-CoV-2 genome mutates at a rate of ∼1.5 × 10-6/base per viral passage and that the spectrum is dominated by C → U transitions. Moreover, we find that the mutation rate is significantly reduced in regions that form base-pairing interactions and that mutations that affect these secondary structures are especially harmful to viral fitness. In this work, we show that the biased mutation spectrum of SARS-CoV-2 is likely a result of frequent cytidine deamination and that the secondary structure of the virus plays an important role in this process, providing new insight into the parameters that guide viral evolution and highlighting fundamental weaknesses of the virus that may be exploited for therapeutic purposes.

PMID:40645940 | DOI:10.1038/s41467-025-61555-x

Matrix Biol. 2025 Jul 9:S0945-053X(25)00060-5. doi: 10.1016/j.matbio.2025.07.001. Online ahead of print.

ABSTRACT

Basement membranes (BMs) are dense extracellular matrix scaffolds that support cells. Their composition, structure and dynamic regulation are vital for tissue health and altered in human disease. The expansion of experimental and analytical techniques has generated large multiomic datasets that include BM components; however, the organising principles of BM component assembly and the regulation of BMs remain poorly understood. There are over 160 curated BM proteins, including core, ubiquitous components such as type IV collagen and laminin isoforms, as well as tissue-restricted components, and there is increasing experimental evidence of BM protein-protein interactions. Here we describe and compare multiomic, protein-protein interaction, and BM curation databases and discuss the application of systems biology approaches including network analysis, Boolean networks and Ordinary Differential Equations to integrate data and model BM organisation. Applying computational modelling strategies to BM datasets may reveal unknown organising principles of BM assembly and regulation and predict mechanisms of dysregulation in BM-associated diseases.

PMID:40645607 | DOI:10.1016/j.matbio.2025.07.001

Int J Biol Macromol. 2025 Jul 9:145777. doi: 10.1016/j.ijbiomac.2025.145777. Online ahead of print.

ABSTRACT

Sterility mosaic disease (SMD) presents a significant challenge to pigeonpea cultivation in the Indian subcontinent, potentially leading to total crop failure. The development of diagnostic molecular markers for SMD resistance can aid in improving SMD-resistant varieties. In this context, a QTL-seq approach identified genomic regions associated with SMD resistance using a recombinant inbred line generated from ICP8863 × ICPL87119. In total, 6105 high-confidence variants were identified in the genomic region, smdCc04 based on the delta SNP index. A genomic region smdCc04 on chromosome Cc04 spans 3.2 Mb (9.3-12.5 Mb) comprises 6 missense variants and eight inDels. A total of 211 candidate genes were identified from this region. 1 bp insertion, 21 bp insertion, 9 bp deletion, and 3 bp insertion at different intronic positions in 22 susceptible line leads to downregulation of Dormancy/auxin associated protein (Ccsmd04) resulting in loss of signaling in disease resistance pathways. The identified sites recognize four important disease and plant growth related transcription factors. A total of 4 InDels and 8 SNPs were validated from smdCc04 genomic regions using whole genome re-sequencing data and kompititive allele specific polymerase chain reaction (KASP) genotyping in resistant and susceptible pigeonpea lines respectively. These markers will be used in pigeonpea breeding programs.

PMID:40645248 | DOI:10.1016/j.ijbiomac.2025.145777

Cell Rep Methods. 2025 Jul 3:101104. doi: 10.1016/j.crmeth.2025.101104. Online ahead of print.

ABSTRACT

Protein turnover is a critical component of gene expression regulation and cellular homeostasis, yet methods for measuring turnover rates that are scalable and applicable to different models are still needed. We introduce an improved D2O (heavy water) labeling strategy to investigate the landscape of protein turnover in cell culture, with accurate calibration of per-residue deuterium incorporation in multiple cell types. Applying this method, we mapped the proteome-wide turnover landscape of pluripotent and differentiating human induced pluripotent stem cells (hiPSCs). Our analysis highlights the role of APC/C (anaphase-promoting complex/cyclosome) and SPOP (speckle-type POZ protein) degrons in the fast turnover of cell-cycle-related and DNA-binding hiPSC proteins. Upon pluripotency exit, many short-lived hiPSC proteins are depleted, while RNA-binding and -splicing proteins become hyperdynamic. The ability to identify fast-turnover proteins also facilitates secretome profiling, as exemplified in hiPSC-cardiomyocyte and primary human cardiac fibroblast analysis. This method is broadly applicable to protein turnover studies in primary, pluripotent, and transformed cells.

PMID:40645189 | DOI:10.1016/j.crmeth.2025.101104

PLoS Comput Biol. 2025 Jul 11;21(7):e1012395. doi: 10.1371/journal.pcbi.1012395. Online ahead of print.

ABSTRACT

Foot and Mouth Disease (FMD) affects cloven-hoofed animals globally and has become a major economic burden for many countries around the world. Countries that have had recent FMD outbreaks are prohibited from exporting most meat products; this has major economic consequences for farmers in those countries, particularly farmers that experience outbreaks or are near outbreaks. Reducing the number of FMD outbreaks in countries where the disease is endemic is an important challenge that could drastically improve the livelihoods of millions of people. As a result, significant effort is expended on surveillance; but there is a concern that uninformative surveillance strategies may waste resources that could be better used on control management. Rapid detection through sentinel surveillance may be a useful tool to reduce the scale and burden of outbreaks. In this study, we use an extensive outbreak and cattle shipment network dataset from the Republic of Türkiye to retrospectively test three possible strategies for sentinel surveillance allocation in countries with endemic FMD and minimal existing FMD surveillance infrastructure that differ in their data requirements: ranging from low to high data needs, we allocate limited surveillance to [1] farms that frequently send and receive shipments of animals (Network Connectivity), [2] farms near other farms with past outbreaks (Spatial Proximity) and [3] farms that receive many shipments from other farms with past outbreaks (Network Proximity). We determine that all of these surveillance methods find a similar number of outbreaks - 2-4.5 times more outbreaks than were detected by surveying farms at random. On average across surveillance efforts, the Network Proximity and Network Connectivity methods each find a similar number of outbreaks and the Spatial Proximity method always finds the fewest outbreaks. Since the Network Proximity method does not outperform the other methods, these results indicate that incorporating both cattle shipment data and outbreak data provides only marginal benefit over the less data-intensive surveillance allocation methods for this objective. We also find that these methods all find more outbreaks when outbreaks are rare. This is encouraging, as early detection is critical for outbreak management. Overall, since the Spatial Proximity and Network Connectivity methods find a similar proportion of outbreaks, and are less data-intensive than the Network Proximity method, countries with endemic FMD whose resources are constrained could prioritize allocating sentinels based on whichever of those two methods requires less additional data collection.

PMID:40644517 | DOI:10.1371/journal.pcbi.1012395

PLoS Comput Biol. 2025 Jul 11;21(7):e1013281. doi: 10.1371/journal.pcbi.1013281. eCollection 2025 Jul.

NO ABSTRACT

PMID:40644463 | DOI:10.1371/journal.pcbi.1013281

PLoS Biol. 2025 Jul 11;23(7):e3003197. doi: 10.1371/journal.pbio.3003197. eCollection 2025 Jul.

ABSTRACT

In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-h period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified rhythmic fluctuations in cilia length across five brain regions: the nucleus accumbens core, somatosensory cortex, and the dorsomedial, ventromedial, and arcuate hypothalamic nuclei. Our findings present novel insights into the brain cilia dynamics, and highlight the need for further investigation into cilia's role in the brain's response to environmental changes and regulation of oscillatory physiological processes.

PMID:40644366 | DOI:10.1371/journal.pbio.3003197

J Thromb Thrombolysis. 2025 Jul 11. doi: 10.1007/s11239-025-03144-9. Online ahead of print.

NO ABSTRACT

PMID:40643736 | DOI:10.1007/s11239-025-03144-9

J Med Chem. 2025 Jul 11. doi: 10.1021/acs.jmedchem.5c00919. Online ahead of print.

ABSTRACT

Due to limited treatment options, liver failure remains a major challenge in modern medicine. With the validation of mitogen-activated protein kinase kinase 4 (MKK4, also known as MEK4 or MAP2K4) as a regulator of hepatocyte regeneration, a promising target for curative treatment of degenerative liver diseases was recently identified via in vivo RNAi experiments. The field of small molecules targeting MKK4 is of growing interest. Several MKK4 inhibitors with differing scaffolds are known, but few have reasonable selectivity profiles and drug-like properties. To further explore the space of drug-like MKK4 scaffolds, we performed a broad screening campaign and identified BI-D1870 as a promising candidate. The dihydropteridinone BI-D1870 is an unselective ribosomal S6 kinase inhibitor with broad off-target activity. In the study presented herein, we report a successful off-to-on target strategy that led to the development of highly selective 1,4-dihydropyrido[3,4-b]pyrazin-3(2H)-one inhibitors of MKK4.

PMID:40643363 | DOI:10.1021/acs.jmedchem.5c00919

Adv Sci (Weinh). 2025 Jul 11:e01727. doi: 10.1002/advs.202501727. Online ahead of print.

ABSTRACT

The Schlafen (SLFN) genes are induced by interferons, underscoring their roles in the immune response and viral replication inhibition. SLFN14, a member of SLFN family, is associated with multiple human diseases; however, neither its functions nor its disease mechanisms are fully understood. Herein, human SLFN14 biochemically is characterized, demonstrating that it specifically cleaves RNAs containing short duplex regions, such as hairpin RNAs and tRNAs, but does not have ATPase or helicase activity. Cryogenic electron microscopy structures of SLFN14 apoenzyme (2.84 Å) and SLFN14-hairpin RNA complex (2.88 Å) are determined, revealing that SLFN14 assembles into a ring-like dimer and dimerization is mainly mediated by hydrophobic contacts. Two N-terminal RNase domains of SLFN14 are organized head-to-tail, forming an RNA-binding groove that can accommodate a 12-bp hairpin RNA. The hairpin RNA is recognized mainly through phosphate backbone interactions. Further, SLFN14 is shown to inhibits HIV-1 pseudovirus replication. The anti-HIV-1 activity of SLFN14 is via codon-usage-dependent translational inhibition and impairment of the programmed -1 ribosomal frameshifting, with an efficiency comparable to that of Shiftless. Using tRNA PCR arrays, SLFN14 and SLFN11 are found to decrease both nuclear-encoded and mitochondrial tRNAs in cells. Together, these results provide novel insights into the function of SLFN14 and its role in HIV-1 restriction.

PMID:40642785 | DOI:10.1002/advs.202501727

F1000Res. 2025 May 20;12:287. doi: 10.12688/f1000research.129064.2. eCollection 2023.

ABSTRACT

Neglected tropical diseases (NTDs) continue to affect the livelihood of individuals in countries in the Southeast Asia and Western Pacific region. These diseases have been long existing and have caused devastating health problems and economic decline to people in low- and middle-income (developing) countries. An estimated 1.7 billion of the world's population suffer one or more NTDs annually, this puts approximately one in five individuals at risk for NTDs. In addition to health and social impact, NTDs inflict significant financial burden to patients, close relatives, and are responsible for billions of dollars lost in revenue from reduced labor productivity in developing countries alone. There is an urgent need to better improve the control and eradication or elimination efforts towards NTDs. This can be achieved by utilizing machine learning tools to better the surveillance, prediction and detection program, and combat NTDs through the discovery of new therapeutics against these pathogens. This review surveys the current application of machine learning tools for NTDs and the challenges to elevate the state-of-the-art of NTDs surveillance, management, and treatment.

PMID:40642109 | PMC:PMC12242132 | DOI:10.12688/f1000research.129064.2

Front Microbiol. 2025 Jun 26;16:1618177. doi: 10.3389/fmicb.2025.1618177. eCollection 2025.

ABSTRACT

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, and its pathogenesis involves complex interactions between the host and the microbiome. The integration of multi-omics has important value in revealing the mechanism of host-microbiome interaction. It is a key tool for promoting accurate diagnosis and guiding dynamic treatment strategies in sepsis. However, multi-omics data integration faces technical challenges, such as data heterogeneity and platform variability, as well as analytical hurdles, such as the "curse of dimensionality." Fortunately, researchers have developed two integration strategies: data-driven and knowledge-guided approaches, which employ various dimensionality reduction techniques and integration methods to handle multi-omics datasets. This review discusses the applications of multi-omics technologies in host-microbiome interactions in sepsis, highlighting their potential in identifying novel diagnostic biomarkers and developing personalized and dynamic treatment strategies. It also summarizes commonly used systems biology resources and computational tools for data integration; the review outlines the challenges in this field and proposes potential directions for future studies.

PMID:40641871 | PMC:PMC12241168 | DOI:10.3389/fmicb.2025.1618177

Am J Primatol. 2025 Jul;87(7):e70061. doi: 10.1002/ajp.70061.

ABSTRACT

In social animals, aggression is a group matter not involving only the opponents. Witnessing a conflict can induce tension and distress in bystanders (i.e., individuals not involved in either the conflict or post-conflict affiliation with the aggressor and aggressee). For this reason, bystanders can engage in post-conflict affiliative exchanges to reduce tension and distress, a phenomenon known as Quadratic Post-Conflict Affiliation (QPCA). This study investigated the occurrence of QPCA in a group of chimpanzees (Pan troglodytes, N = 15) housed at ZooParc de Beauval, France. Our findings confirmed the presence of QPCA in chimpanzees under study (group QPCA tendency: 5.60% ± 2.55 SE). QPCA was primarily directed towards males, who usually tended to be more influenced by the ongoing aggression and could potentially redirect further aggression towards bystanders. High-ranking bystanders were contacted more frequently than low-ranking ones, as the former can potentially provide immediate protection against other aggressors and offer greater tolerance. Additionally, bystanders were less frequently targeted by aggression when QPCA was present than when it was absent. Thus, QPCA may function as a protective mechanism against aggression by other group members by reducing the chance that bystanders become victims for redirected aggression (Bystander Protection Hypothesis). However, QPCA failed in reducing the levels of bystanders' anxiety-related behaviors. In conclusion, QPCA may be one of the behavioral strategies used by chimpanzees to navigate social challenges, maintain group cohesion, and mitigate aggression.

PMID:40641451 | DOI:10.1002/ajp.70061

Mov Disord. 2025 Jul 11. doi: 10.1002/mds.30287. Online ahead of print.

NO ABSTRACT

PMID:40641343 | DOI:10.1002/mds.30287

J Chem Inf Model. 2025 Jul 10. doi: 10.1021/acs.jcim.5c00860. Online ahead of print.

ABSTRACT

Proinflammatory peptides (PIPs) play a crucial role in immune response modulation by orchestrating cytokine release and leukocyte recruitment. Accurate identification of PIPs is essential for understanding inflammation-related diseases and developing therapeutic interventions. Traditional experimental methods for PIP identification are labor-intensive and low-throughput, necessitating the development of robust computational approaches. In this study, we propose StackPIP, a novel machine learning framework that leverages a stacking-based ensemble strategy to enhance PIP prediction. StackPIP integrates multiple peptide descriptors capturing compositional, order, and physicochemical properties, coupled with 12 machine learning algorithms to construct a high-performing computational framework. Experimental results demonstrate that StackPIP outperforms existing computational methods, surpassing the accuracy of previous state-of-the-art approaches by nearly 5% while achieving balanced prediction results. Furthermore, an interpretability analysis was conducted to elucidate the critical sequence characteristics contributing to the proinflammatory activity. To facilitate accessibility, we have developed a user-friendly web server, enabling researchers to efficiently utilize StackPIP for PIP identification, which is freely available at https://awi.cuhk.edu.cn/~biosequence/StackPIP/index.php.

PMID:40641221 | DOI:10.1021/acs.jcim.5c00860

Arthritis Res Ther. 2025 Jul 10;27(1):146. doi: 10.1186/s13075-025-03595-8.

ABSTRACT

OBJECTIVE: A major unmet need for Systemic Sclerosis (SSc) clinical management is the absence of well validated biomarkers for early diagnosis of SSc-associated interstitial lung disease (SSc-ILD). The objective of this study was to identify proteins contained within serum exosomes that may serve as potential biomarkers to differentiate patients with Diffuse SSc without SSc-ILD from patients with Diffuse SSc with SSc-ILD employing aptamer-based proteomics.

METHODS: Serum exosomes were isolated from two cohorts of patients. The first cohort included 15 patients with Diffuse SSc without SSc-ILD and 14 patients with Diffuse SSc with SSc-ILD and the second cohort included 12 patients with Diffuse SSc with SSc-ILD and 12 patients with Diffuse SSc without SSc-ILD. SOMAscan aptamer proteomics was performed with the first cohort and quantified the concentration levels of 1,305 proteins. Significant associations of differentially elevated or reduced proteins (p < 0.05 |FC|>1.2) discriminating between the two SSc clinical subsets were assessed. Validation of the results obtained from the proteomics analysis of the first cohort was performed with the second cohort.

RESULTS: The aptamer proteomic analysis identified 29 proteins increased and 9 proteins decreased in SSc with SSc-ILD as compared to SSc without SSc-ILD. Principal component analysis using the 20 most significantly differentially expressed proteins resulted in excellent separation of the two SSc clinical subsets. Most of the differentially increased proteins converged around enhanced inflammatory responses, immune cell activation, cell death, and abnormal vascular functions and several of them displayed a highly significant correlation with the CO Diffusion Capacity Levels.

CONCLUSION: Aptamer proteomic analysis of circulating exosomes from patients with Diffuse SSc with and without SSc-ILD identified several biologically plausible biomarkers that may be of value to differentiate these two SSc clinical subsets.

PMID:40640963 | DOI:10.1186/s13075-025-03595-8

Crit Care. 2025 Jul 10;29(1):294. doi: 10.1186/s13054-025-05539-9.

NO ABSTRACT

PMID:40640937 | DOI:10.1186/s13054-025-05539-9