Philos Trans R Soc Lond B Biol Sci. 2025 Apr 3;380(1923):20240021. doi: 10.1098/rstb.2024.0021. Epub 2025 Apr 3.

ABSTRACT

Animal vocalizations contain a varying degree of nonlinear phenomena (NLP) caused by irregular or chaotic vocal organ dynamics. Several hypotheses have been proposed to explain NLP presence, from unintentional by-products of poor vocal technique to having a functional communicative role. We aimed to disentangle the role of sex, age and physiological constraints in the occurrence of NLP in the songs of the lemur Indri indri, which are complex harmonic vocal displays organized in phrases. Age and sex affected the presence and type of NLP in songs. In particular, the proportion of the phenomena considered decreased with age, except for subharmonics. Subharmonics potentially mediate the perception of lower pitch, making signallers appear larger. Subharmonics and frequency jumps occurred in lower-pitched notes than regular units, while chaos and sidebands occurred in higher-pitched units. This suggests that different types of NLP can be associated with different vocal constraints. Finally, indris might present short-term vocal fatigue, with units occurring in the last position of a phrase having the highest probability of containing NLP. The presence of NLP in indris might result from proximate causes, such as physiological constraints, and ultimate causes, such as evolutionary pressures, which shaped the communicative role of NLP.This article is part of the theme issue 'Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions'.

PMID:40176518 | DOI:10.1098/rstb.2024.0021

Philos Trans R Soc Lond B Biol Sci. 2025 Apr 3;380(1923):20240019. doi: 10.1098/rstb.2024.0019. Epub 2025 Apr 3.

ABSTRACT

African penguins (Spheniscus demersus) extensively use high-frequency food solicitation signals (begging calls) to request food from parents. We studied the occurrence of nonlinear vocal phenomena (NLP) in begging calls in 91 hand-reared penguin chicks at the Southern African Foundation for the Conservation of Coastal Birds. For each chick, we recorded the begging calls daily, from the hatching of wild abandoned eggs to the release of the chicks into the wild approximately three months later. We found that most (70%) of begging calls contain NLP. The most frequently observed are sidebands (54.1%) and deterministic chaos (71.4%), and these phenomena often coexist (26.5%). We suggest that the aperiodic chaotic features of begging calls assist in increasing adults' attention and avoiding habituation. The occurrence of NLP also depends on the penguins' age, with older chicks producing more NLP in their calls. Moreover, we found that NLP significantly increased in chicks after contracting a respiratory disease (for example, bacterial infections or aspergillosis). Such findings might be useful for the timely diagnosis of penguins needing veterinary treatment, contributing to conservation efforts for this endangered species.This article is part of the theme issue 'Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions'.

PMID:40176507 | DOI:10.1098/rstb.2024.0019

Philos Trans R Soc Lond B Biol Sci. 2025 Apr 3;380(1923):20240009. doi: 10.1098/rstb.2024.0009. Epub 2025 Apr 3.

ABSTRACT

Nonlinear acoustic phenomena (NLP) likely facilitate the expression of distress in animal vocalizations, making calls perceptually rough and hard to ignore. Yet, their function in adult human vocal communication remains poorly understood. Here, to examine the production and perception of acoustic correlates of pain in spontaneous human nonverbal vocalizations, we take advantage of childbirth-a natural context in which labouring women typically produce a range of highly evocative loud vocalizations, including moans and screams-as they experience excruciating pain. We combine acoustic analyses of these real-life pain vocalizations with psychoacoustic experiments involving the playback of natural and synthetic calls to both naïve and expert listeners. We show that vocalizations become acoustically rougher, higher in fundamental frequency (pitch), less stable, louder and longer as child labour progresses, paralleling a rise in women's self-assessed pain. In perception experiments, we show that both naïve listeners and obstetric professionals assign the highest pain ratings to vocalizations produced in the final expulsion phase of labour. Experiments with synthetic vocal stimuli confirm that listeners rely largely on nonlinear phenomena to assess pain. Our study confirms that nonlinear phenomena communicate intense, pain-induced distress in humans, consistent with their widespread function to signal distress and arousal in vertebrate vocal signals.This article is part of the theme issue 'Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions'.

PMID:40176506 | DOI:10.1098/rstb.2024.0009

mBio. 2025 Apr 3:e0077825. doi: 10.1128/mbio.00778-25. Online ahead of print.

NO ABSTRACT

PMID:40176258 | DOI:10.1128/mbio.00778-25

Cardiovasc Diabetol. 2025 Apr 2;24(1):152. doi: 10.1186/s12933-025-02701-z.

ABSTRACT

BACKGROUND: Disruption of lipid metabolism contributes to increased cardiovascular risk in diabetes.

METHODS: We evaluated the associations between serum lipidomic profile and subclinical carotid atherosclerosis (SCA) in type 1 (T1D) and type 2 (T2D) diabetes, and in subjects without diabetes (controls) in a cross-sectional study. All subjects underwent a lipidomic analysis using ultra-high performance liquid chromatography-electrospray ionization tandem mass spectrometry, carotid ultrasound (mode B) to assess SCA, and clinical assessment. Multiple linear regression models were used to assess the association between features and the presence and burden of SCA in subjects with T1D, T2D, and controls separately. Additionally, multiple linear regression models with interaction terms were employed to determine features significantly associated with SCA within risk groups, including smoking habit, hypertension, dyslipidaemia, antiplatelet use and sex. Depending on the population under study, different confounding factors were considered and adjusted for, including sample origin, sex, age, hypertension, dyslipidaemia, body mass index, waist circumference, glycated haemoglobin, glucose levels, smoking habit, diabetes duration, antiplatelet use, and alanine aminotransferase levels.

RESULTS: A total of 513 subjects (151 T1D, 155 T2D, and 207 non-diabetic control) were included, in whom the percentage with SCA was 48.3%, 49.7%, and 46.9%, respectively. A total of 27 unique lipid species were associated with SCA in subjects with T2D, in former/current smokers with T2D, and in individuals with T2D without dyslipidaemia. Phosphatidylcholines and diacylglycerols were the main SCA-associated lipidic classes. Ten different species of phosphatidylcholines were up-regulated, while 4 phosphatidylcholines containing polyunsaturated fatty acids were down-regulated. One diacylglycerol was down-regulated, while the other 3 were positively associated with SCA in individuals with T2D without dyslipidaemia. We discovered several features significantly associated with SCA in individuals with T1D, but only one sterol could be partially annotated.

CONCLUSIONS: We revealed a significant disruption of lipid metabolism associated with SCA in subjects with T2D, and a larger SCA-associated disruption in former/current smokers with T2D and individuals with T2D who do not undergo lipid-lowering treatment.

PMID:40176064 | DOI:10.1186/s12933-025-02701-z

Biotechnol Lett. 2025 Apr 2;47(2):38. doi: 10.1007/s10529-025-03579-3.

ABSTRACT

OBJECTIVE: The aim of this study is to identify therapeutic cargos within mesenchymal stem cell (MSC)-derived small extracellular vesicles (sEVs) for the treatment of liver fibrosis, a condition that poses significant health risks.

RESULTS: sEVs from human umbilical cord-derived MSCs (UCMSCs) and their differentiated hepatocyte-like cells (hpUCMSCs) were found to alleviate liver fibrosis in mouse models, reduce fibrogenic gene expression in the liver, and inhibit hepatic stellate cell (HSC) activation, a central driver of liver fibrosis, in vitro. Deep sequencing identified differentially abundant microRNAs (miRNAs) (high-abundance: 57, low-abundance: 22) in both UCMSC- and hpUCMSC-derived sEVs, compared to HeLa cell-derived sEVs, which lack anti-liver fibrotic activity. Functional enrichment analysis of the high-abundance sEV miRNA targets revealed their involvement in transcriptional regulation, apoptosis, and cancer-related pathways, all of which are linked to liver fibrosis and hepatocellular carcinoma. Notably, many of the top 10 most abundant miRNAs reduced pro-fibrotic marker levels in activated HSCs in vitro.

CONCLUSION: The therapeutic potential of the high-abundance miRNAs shared by UCMSC- and hpUCMSC-derived sEVs in treating liver fibrosis is highlighted.

PMID:40175803 | DOI:10.1007/s10529-025-03579-3

Nat Med. 2025 Apr 2. doi: 10.1038/s41591-025-03610-0. Online ahead of print.

ABSTRACT

The human gut microbiome is most dynamic in early life. Although sweeping changes in taxonomic architecture are well described, it remains unknown how, and to what extent, individual strains colonize and persist and how selective pressures define their genomic architecture. In this study, we combined shotgun sequencing of 1,203 stool samples from 26 mothers and their twins (52 infants), sampled from childbirth to 8 years after birth, with culture-enhanced, deep short-read and long-read stool sequencing from a subset of 10 twins (20 infants) to define transmission, persistence and evolutionary trajectories of gut species from infancy to middle childhood. We constructed 3,995 strain-resolved metagenome-assembled genomes across 399 taxa, and we found that 27.4% persist within individuals. We identified 726 strains shared within families, with Bacteroidales, Oscillospiraceae and Lachnospiraceae, but not Bifidobacteriaceae, vertically transferred. Lastly, we identified weaning as a critical inflection point that accelerates bacterial mutation rates and separates functional profiles of genes accruing mutations.

PMID:40175737 | DOI:10.1038/s41591-025-03610-0

Nature. 2025 Apr 2. doi: 10.1038/s41586-025-08814-5. Online ahead of print.

ABSTRACT

Anthropogenic biodiversity decline threatens the functioning of ecosystems and the many benefits they provide to humanity1. As well as causing species losses in directly affected locations, human influence might also reduce biodiversity in relatively unmodified vegetation if far-reaching anthropogenic effects trigger local extinctions and hinder recolonization. Here we show that local plant diversity is globally negatively related to the level of anthropogenic activity in the surrounding region. Impoverishment of natural vegetation was evident only when we considered community completeness: the proportion of all suitable species in the region that are present at a site. To estimate community completeness, we compared the number of recorded species with the dark diversity-ecologically suitable species that are absent from a site but present in the surrounding region2. In the sampled regions with a minimal human footprint index, an average of 35% of suitable plant species were present locally, compared with less than 20% in highly affected regions. Besides having the potential to uncover overlooked threats to biodiversity, dark diversity also provides guidance for nature conservation. Species in the dark diversity remain regionally present, and their local populations might be restored through measures that improve connectivity between natural vegetation fragments and reduce threats to population persistence.

PMID:40175550 | DOI:10.1038/s41586-025-08814-5

Sci Rep. 2025 Apr 2;15(1):11312. doi: 10.1038/s41598-025-95276-4.

ABSTRACT

Infectious mononucleosis (IM), predominantly caused by primary Epstein-Barr virus (EBV) infection, is a common disease in adolescents and young adults. EBV infection is nearly ubiquitous globally. Although primary EBV infection is asymptomatic in most individuals, IM manifests in a subset infected during adolescence or young adulthood. IM occurrence is linked to sibship structure, and is associated with increased risk of multiple sclerosis, other autoimmune diseases, and cancer later in life. We analyzed 47 biomarkers in 5,526 Danish individuals aged 18-60 years, of whom 604 had a history of IM, examining their associations with IM history up to 48 years after IM diagnosis. No significant long-term associations were observed after adjusting for multiple comparisons. When restricting the analysis to individuals measured within 10 years post-IM diagnosis, a statistically significant increase in CRP levels was observed in females. This association was not driven by oral contraceptive use. No significant associations between sibship structure and biomarker levels were detected. In conclusion, our study shows that while IM may lead to a transient increase in CRP levels in females, it does not result in long-term alterations in plasma biomarkers related to immune function, suggesting other mechanisms may be responsible for the long-term health impacts associated with IM.

PMID:40175486 | DOI:10.1038/s41598-025-95276-4

Microsyst Nanoeng. 2025 Apr 2;11(1):56. doi: 10.1038/s41378-025-00880-z.

ABSTRACT

Chronic kidney disease (CKD) significantly affects people's health and quality of life and presents a high economic burden worldwide. There are well-established biomarkers for CKD diagnosis. However, the existing routine standard tests are lab-based and governed by strict regulations. Creatinine is commonly measured as a filtration biomarker in blood to determine estimated Glomerular Filtration Rate (eGFR), as well as a normalization factor to calculate urinary Albumin-to-Creatinine Ratio (uACR) for CKD evaluation. In this study, we developed a passive flow microreactor for colorimetric urine creatinine measurement (uCR-Chip), which is highly amenable to integration with our previously developed microfluidic urine albumin assay. The combination of the 2-phase pressure compensation (2-PPC) technique and microfluidic channel network design accurately controls the fluidic mixing ratio and chemical reaction. Together with an optimized observation window (OW) design, a uniform and stable detection signal was achieved within 7 min. The color signal was measured by a simple USB microscope-based platform to quantify creatinine concentration in the sample. The combination of the custom in-house photomask production techniques and dry-film photoresist-based lithography enabled rapid iterative design optimization and precise chip fabrication. The developed assay achieved a dynamic linear detection range up to 40 mM and a lower limit of detection (LOD) of 0.521 mM, meeting the clinical precision requirements (comparable to existing point-of-care (PoC) systems). The microreactor was validated using creatinine standards spiked into commercial artificial urine that mimics physiological matrix. Our results showed acceptable recovery rate and low matrix effect, especially for the low creatinine concentration range in comparison to a commercial PoC uACR test. Altogether, the developed uCR-Chip offers a viable PoC test for CKD assessment and provides a potential platform technology to measure various disease biomarkers.

PMID:40175342 | DOI:10.1038/s41378-025-00880-z

Trends Plant Sci. 2025 Apr 1:S1360-1385(25)00063-9. doi: 10.1016/j.tplants.2025.03.003. Online ahead of print.

ABSTRACT

The field of mass spectrometry (MS)-based proteomics is rapidly advancing with technological and computational improvements, including leveraging the power of artificial intelligence (AI) to drive innovation. Such innovation has been particularly apparent in human disease research, where the intersection of these disciplines has pioneered a new age of disease diagnostics and pharmaceutical discovery. However, applications within plant sciences remains woefully under-represented and yet provides exceptional promise and potential to support new, interdisciplinary areas of research. Timely and novel examples of proteomics advancing plant science encompass biotechnology, climatic resiliency, agricultural production systems, and disease management. Herein, we propose new scientific avenues that leverage the power of proteomics and AI within plant science research to drive new discoveries and innovation.

PMID:40175191 | DOI:10.1016/j.tplants.2025.03.003

Adv Pharmacol. 2025;103:287-311. doi: 10.1016/bs.apha.2025.01.012. Epub 2025 Feb 26.

ABSTRACT

Bioinformatics has taken a pivotal place in the life sciences field. Not only does it improve, but it also fine-tunes and complements the wet lab experiments. It has been a driving force in the so-called biological sciences, converting them into hypothesis and data-driven fields. This study highlights the translational impact of bioinformatics on experimental biology and discusses its evolution and the advantages it has brought to advancing biological research. Computational analyses make labor-intensive wet lab work cost-effective by reducing the use of expensive reagents. Genome/proteome-wide studies have become feasible due to the efficiency and speed of bioinformatics tools, which can hardly be compared with wet lab experiments. Computational methods provide the scalability essential for manipulating large and complex data of biological origin. AI-integrated bioinformatics studies can unveil important biological patterns that traditional approaches may otherwise overlook. Bioinformatics contributes to hypothesis formation and experiment design, which is pivotal for modern-day multi-omics and systems biology studies. Integrating bioinformatics in the experimental procedures increases reproducibility and helps reduce human errors. Although today's AI-integrated bioinformatics predictions have significantly improved in accuracy over the years, wet lab validation is still unavoidable for confirming these predictions. Challenges persist in multi-omics data integration and analysis, AI model interpretability, and multiscale modeling. Addressing these shortcomings through the latest developments is essential for advancing our knowledge of disease mechanisms, therapeutic strategies, and precision medicine.

PMID:40175046 | DOI:10.1016/bs.apha.2025.01.012

Adv Pharmacol. 2025;103:231-263. doi: 10.1016/bs.apha.2025.01.003. Epub 2025 Feb 6.

ABSTRACT

Computational precision in drug discovery integrates algorithms and high-performance computing to analyze complex biological data with unprecedented accuracy, revolutionizing the identification of therapeutic targets. This process encompasses diverse computational and experimental approaches that enhance drug discovery's speed and precision. Advanced techniques like next-generation sequencing enable rapid genetic characterization, while proteomics explores protein expression and interactions driving disease progression. In-silico methods, including molecular docking, virtual screening, and pharmacophore modeling, predict interactions between small molecules and biological targets, accelerating early drug candidate identification. Structure-based drug design and molecular dynamics simulations refine drug designs by elucidating target structures and molecular behaviors. Ligand-based methods utilize known chemical properties to anticipate new compound activities. AI and machine learning optimizes data analysis, offering novel insights and improving predictive accuracy. Systems biology and network pharmacology provide a holistic view of biological networks, identifying critical nodes as potential drug targets, which traditional methods might overlook. Computational tools synergize with experimental techniques, enhancing the treatment of complex diseases with personalized medicine by tailoring therapies to individual patients. Ethical and regulatory compliance ensures clinical applicability, bridging computational predictions to effective therapies. This multi-dimensional approach marks a paradigm shift in modern medicine, delivering safer, more effective treatments with precision. By integrating bioinformatics, genomics, and proteomics, computational drug discovery has transformed how therapeutic interventions are developed, ensuring an era of personalized, efficient healthcare.

PMID:40175044 | DOI:10.1016/bs.apha.2025.01.003

Adv Pharmacol. 2025;103:1-22. doi: 10.1016/bs.apha.2025.01.006. Epub 2025 Feb 13.

ABSTRACT

In the current scenario of pandemics, drug discovery and design have undergone a significant transformation due to the integration of advanced computational methodologies. These methodologies utilize sophisticated algorithms, machine learning, artificial intelligence, and high-performance computing to expedite the drug development process, enhances accuracy, and reduces costs. Machine learning and AI have revolutionized predictive modeling, virtual screening, and de novo drug design, allowing for the identification and optimization of novel compounds with desirable properties. Molecular dynamics simulations provide a detailed insight into protein-ligand interactions and conformational changes, facilitating an understanding of drug efficacy at the atomic level. Quantum mechanics/molecular mechanics methods offer precise predictions of binding energies and reaction mechanisms, while structure-based drug design employs docking studies and fragment-based design to improve drug-receptor binding affinities. Network pharmacology and systems biology approaches analyze polypharmacology and biological networks to identify novel drug targets and understand complex interactions. Cheminformatics explores vast chemical spaces and employs data mining to find patterns in large datasets. Computational toxicology predicts adverse effects early in development, reducing reliance on animal testing. Bioinformatics integrates genomic, proteomic, and metabolomics data to discover biomarkers and understand genetic variations affecting drug response. Lastly, cloud computing and big data technologies facilitate high-throughput screening and comprehensive data analysis. Collectively, these computational innovations are driving a paradigm shift in drug discovery and design, making it more efficient, accurate, and cost-effective.

PMID:40175036 | DOI:10.1016/bs.apha.2025.01.006

J Am Coll Radiol. 2025 Mar 31:S1546-1440(25)00195-4. doi: 10.1016/j.jacr.2025.03.006. Online ahead of print.

NO ABSTRACT

PMID:40174871 | DOI:10.1016/j.jacr.2025.03.006

Nephron. 2025 Apr 2:1-11. doi: 10.1159/000544754. Online ahead of print.

ABSTRACT

BACKGROUND: Although there have been reports of relapse or worsening of membranous nephropathy after receiving vaccines against coronavirus disease 2019 (COVID-19), the causal relationship or association between them has not been established. This study aimed to investigate the occurrence of relapse or worsening of membranous nephropathy following inactivated COVID-19 vaccination.

METHODS: Patients who had been diagnosed with membranous nephropathy before receiving their first dose of vaccination, or before March 1, 2021, for unvaccinated patients, were included in the study. All patients were monitored at the Membranous Nephropathy Clinic of Huashan Hospital, Fudan University. The reasons for not receiving vaccines were investigated. The impact of COVID-19 vaccination on membranous nephropathy was assessed by comparing the relapse or worsening of membranous nephropathy within 12 months in vaccinated and unvaccinated patients with proteinuria <3.5 g/d. The baseline variables were balanced using cardinality matching.

RESULTS: A total of 353 patients with membranous nephropathy were included in the study, with 186 (53%) having received inactivated COVID-19 vaccines. Among the 167 unvaccinated participants, 114 (68%) expressed concerns about the possibility of disease relapse, and 47 (28%) were worried about the vaccine's efficacy due to their immunosuppressive therapy. Of the 239 participants with proteinuria <3.5 g/d, 152 were vaccinated, and 16 (11%) experienced a relapse or worsening of the disease during the follow-up period, which was similar to the 14 (16%) observed in the unvaccinated group. Following cardinality matching, there was no difference in the rate of relapse or worsening between the two groups, with 10 (13%) in the vaccinated group and 11 (15%) in the unvaccinated group (hazard ratio 0.98, 95% confidence interval 0.42-2.33).

CONCLUSION: Getting the inactivated COVID-19 vaccine may not increase risk of relapse or worsening in patients with membranous nephropathy.

PMID:40174580 | DOI:10.1159/000544754

Reprod Biomed Online. 2024 Nov 14;50(5):104707. doi: 10.1016/j.rbmo.2024.104707. Online ahead of print.

ABSTRACT

Infertility, adverse pregnancy outcomes and genital infections are global concerns. The reproductive tract microbiome appears to play a crucial role in the physiology of both the female and male reproductive tracts. Despite the presence of thousands of microbes in body fluids shared during unprotected sexual intercourse, they have traditionally been studied separately, with greater emphasis on the female (mostly vaginal) microbiome, and the interaction between these microbiomes in a sexually active couple has been overlooked. This review introduces the concept of the 'seminovaginal microbiome' - the collective microbiota of both partners, transferred and shared during sexual interaction. By synthesizing the existing body of next-generation sequencing-based literature, this review establishes the first holistic view of how these microbiomes interact, influence reproductive health and affect assisted reproductive technique outcomes, as well as the occurrence of microbe-associated diseases such as sexually transmitted infections, prostatitis, bacterial vaginosis and candidiasis. Additionally, the microbial interplay in homosexual couples and transgender individuals is discussed.

PMID:40174296 | DOI:10.1016/j.rbmo.2024.104707

Plant Physiol. 2025 Apr 2:kiaf126. doi: 10.1093/plphys/kiaf126. Online ahead of print.

ABSTRACT

Potato (Solanum tuberosum) is highly water and space efficient but susceptible to abiotic stresses such as heat, drought, and flooding, which are severely exacerbated by climate change. Our understanding of crop acclimation to abiotic stress, however, remains limited. Here, we present a comprehensive molecular and physiological high-throughput profiling of potato (Solanum tuberosum, cv. Désirée) under heat, drought, and waterlogging applied as single stresses or in combinations designed to mimic realistic future scenarios. Stress responses were monitored via daily phenotyping and multi-omics analyses of leaf samples comprising proteomics, targeted transcriptomics, metabolomics, and hormonomics at several timepoints during and after stress treatments. Additionally, critical metabolites of tuber samples were analyzed at the end of the stress period. We performed integrative multi-omics data analysis using a bioinformatic pipeline that we established based on machine learning and knowledge networks. Waterlogging produced the most immediate and dramatic effects on potato plants, interestingly activating ABA responses similar to drought stress. In addition, we observed distinct stress signatures at multiple molecular levels in response to heat or drought and to a combination of both. In response to all treatments, we found a downregulation of photosynthesis at different molecular levels, an accumulation of minor amino acids, and diverse stress-induced hormones. Our integrative multi-omics analysis provides global insights into plant stress responses, facilitating improved breeding strategies toward climate-adapted potato varieties.

PMID:40173380 | DOI:10.1093/plphys/kiaf126

Sci Adv. 2025 Apr 4;11(14):eado0173. doi: 10.1126/sciadv.ado0173. Epub 2025 Apr 2.

ABSTRACT

Understanding the heterogeneity of fibroblasts depends on decoding the complexity of cell subtypes, their origin, distribution, and interactions with other cells. Here, we integrated 249,156 fibroblasts from 73 studies across 10 tissues to present a single-cell atlas of fibroblasts. We provided a high-resolution classification of 18 fibroblast subtypes. In particular, we revealed a previously undescribed cell population, TSPAN8+ chromatin remodeling fibroblasts, characterized by high expression of genes with functions related to histone modification and chromatin remodeling. Moreover, TSPAN8+ chromatin remodeling fibroblasts were detectable in spatial transcriptome data and multiplexed immunofluorescence assays. Compared with other fibroblast subtypes, TSPAN8+ chromatin remodeling fibroblasts exhibited higher scores in cell differentiation and resident fibroblast, mainly interacting with endothelial cells and T cells through ligand VEGFA and receptor F2R, and their presence was associated with poor prognosis. Our analyses comprehensively defined the shared and specific characteristics of fibroblast subtypes across tissues and provided a user-friendly data portal, Fibroblast Atlas.

PMID:40173240 | DOI:10.1126/sciadv.ado0173

Neurodegener Dis Manag. 2025 Apr 2:1-3. doi: 10.1080/17582024.2025.2488230. Online ahead of print.

NO ABSTRACT

PMID:40173153 | DOI:10.1080/17582024.2025.2488230