Communications medicine最新文献

{"title":"Addressing the challenge of antimicrobial resistance.","authors":"Timothy M Rawson, Luke Sp Moore, Mohammed Lamorde","doi":"10.1038/s43856-025-00758-1","DOIUrl":"10.1038/s43856-025-00758-1","url":null,"abstract":"","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"67"},"PeriodicalIF":5.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11885620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data.","authors":"Leonid Mill, Oliver Aust, Jochen A Ackermann, Philipp Burger, Monica Pascual, Katrin Palumbo-Zerr, Gerhard Krönke, Stefan Uderhardt, Georg Schett, Christoph S Clemen, Christian Holtzhausen, Samir Jabari, Rolf Schröder, Andreas Maier, Anika Grüneboom","doi":"10.1038/s43856-025-00777-y","DOIUrl":"10.1038/s43856-025-00777-y","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI), specifically Deep learning (DL), has revolutionized biomedical image analysis, but its efficacy is limited by the need for representative, high-quality large datasets with manual annotations. While latest research on synthetic data using AI-based generative models has shown promising results to tackle this problem, several challenges such as lack of interpretability and need for vast amounts of real data remain. This study aims to introduce a new approach-SYNTA-for the generation of photo-realistic synthetic biomedical image data to address the challenges associated with state-of-the art generative models and DL-based image analysis.</p><p><strong>Methods: </strong>The SYNTA method employs a fully parametric approach to create photo-realistic synthetic training datasets tailored to specific biomedical tasks. Its applicability is tested in the context of muscle histopathology and skeletal muscle analysis. This new approach is evaluated for two real-world datasets to validate its applicability to solve complex image analysis tasks on real data.</p><p><strong>Results: </strong>Here we show that SYNTA enables expert-level segmentation of unseen real-world biomedical data using only synthetic training data. By addressing the lack of representative and high-quality real-world training data, SYNTA achieves robust performance in muscle histopathology image analysis, offering a scalable, controllable and interpretable alternative to generative models such as Generative Adversarial Networks (GANs) or Diffusion Models.</p><p><strong>Conclusions: </strong>SYNTA demonstrates great potential to accelerate and improve biomedical image analysis. Its ability to generate high-quality photo-realistic synthetic data reduces reliance on extensive collection of data and manual annotations, paving the way for advancements in histopathology and medical research.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"64"},"PeriodicalIF":5.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11885816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Treatment modalities for patients with Persistent Spinal Pain Syndrome Type II: A systematic review and network meta-analysis.","authors":"Lisa Goudman, Marc Russo, Julie G Pilitsis, Sam Eldabe, Rui V Duarte, Maxime Billot, Manuel Roulaud, Philippe Rigoard, Maarten Moens","doi":"10.1038/s43856-025-00778-x","DOIUrl":"10.1038/s43856-025-00778-x","url":null,"abstract":"<p><strong>Background: </strong>Appropriate management of patients with Persistent Spinal Pain Syndrome Type 2 (PSPS-T2) remains challenging. The need for robust evidence for treatment modalities is urgently pressing. The aim of this systematic review and network meta-analysis (NMA) is to compare different treatment modalities for patients with PSPS-T2 on pain intensity.</p><p><strong>Methods: </strong>The study protocol was prospectively registered (PROSPERO;CRD42022360160). Four different databases were consulted from database inception to December 18th, 2023. Randomised controlled trials of interventions for PSPS-T2 were included. The revised Cochrane Risk of Bias Tool was used to assess risk of bias. A NMA with standardized mean differences was calculated with pairwise comparisons between all treatment modalities.</p><p><strong>Results: </strong>Here we include 49 studies in the systematic review and 13 in NMA. A high risk of bias is indicated for 65.3% of the studies. Half of the studies investigate neuromodulation (mainly Spinal Cord Stimulation), 16 explore minimal invasive treatment options (predominantly epidural injections), 6 studies focus on conservative treatments (physiotherapy/cognitive training and medication) and 2 on reoperation. Comparison of neuromodulation versus a combination of conservative and minimal invasive options results in an effect size of 0.45 (95% CI: 0.14-0.76), clearly favouring neuromodulation (z = 2.88; p = 0.004). Additionally, neuromodulation results in a standardised mean difference of 0.36 (95% CI: 0.18-0.53) compared to placebo/sham (z = 4.03; p < 0.0001). No statistically significant difference is found between conservative options and neuromodulation.</p><p><strong>Conclusions: </strong>Neuromodulation, followed by conservative treatment options, seems to be the most effective treatment option to obtain pain relief in patients with PSPS-T2. Nevertheless, a personalized approach tailored to individual patient needs is essential for optimizing outcomes, since interventions should be adjusted based on the failure or success of prior therapies.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"63"},"PeriodicalIF":5.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11882973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physician clinical decision modification and bias assessment in a randomized controlled trial of AI assistance.","authors":"Ethan Goh, Bryan Bunning, Elaine C Khoong, Robert J Gallo, Arnold Milstein, Damon Centola, Jonathan H Chen","doi":"10.1038/s43856-025-00781-2","DOIUrl":"10.1038/s43856-025-00781-2","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence assistance in clinical decision making shows promise, but concerns exist about potential exacerbation of demographic biases in healthcare. This study aims to evaluate how physician clinical decisions and biases are influenced by AI assistance in a chest pain triage scenario.</p><p><strong>Methods: </strong>A randomized, pre post-intervention study was conducted with 50 US-licensed physicians who reviewed standardized chest pain video vignettes featuring either a white male or Black female patient. Participants answered clinical questions about triage, risk assessment, and treatment before and after receiving GPT-4 generated recommendations. Clinical decision accuracy was evaluated against evidence-based guidelines.</p><p><strong>Results: </strong>Here we show that physicians are willing to modify their clinical decisions based on GPT-4 assistance, leading to improved accuracy scores from 47% to 65% in the white male patient group and 63% to 80% in the Black female patient group. The accuracy improvement occurs without introducing or exacerbating demographic biases, with both groups showing similar magnitudes of improvement (18%). A post-study survey indicates that 90% of physicians expect AI tools to play a significant role in future clinical decision making.</p><p><strong>Conclusions: </strong>Physician clinical decision making can be augmented by AI assistance while maintaining equitable care across patient demographics. These findings suggest a path forward for AI clinical decision support that improves medical care without amplifying healthcare disparities.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"59"},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"5-hydroxymethylcytosine sequencing of plasma cell-free DNA identifies epigenomic features in prostate cancer patients receiving androgen deprivation therapies.","authors":"Qianxia Li, Chiang-Ching Huang, Shane Huang, Yijun Tian, Jinyong Huang, Amirreza Bitaraf, Xiaowei Dong, Marja T Nevalainen, Manishkumar Patel, Jodie Wong, Jingsong Zhang, Brandon J Manley, Jong Y Park, Manish Kohli, Elizabeth M Gore, Deepak Kilari, Liang Wang","doi":"10.1038/s43856-025-00783-0","DOIUrl":"10.1038/s43856-025-00783-0","url":null,"abstract":"<p><strong>Background: </strong>We evaluated whether 5hmC signatures in cell-free DNA (cfDNA) are associated with treatment failure to androgen-deprivation therapies (ADT) among men with hormone-naive prostate cancer.</p><p><strong>Methods: </strong>We collected a total of 139 serial plasma samples from 55 prostate cancer patients receiving ADT at 3 time points including baseline (before initiating ADT, n = 55); 3 months (after initiating ADT, n = 55); and disease progression (n = 15) within 24 months or 24 months if no progression was detected (n = 14). We used selective chemical labeling sequencing to quantify 5hmC abundance across the genome and Kaplan-Meier analysis to assess survival association.</p><p><strong>Results: </strong>Here we show a significant 5hmC difference in 1642 of 23433 genes between patients with and without progression (false discovery rate [FDR] < 0.1) in baseline plasma samples. Patients with progression demonstrate significant 5hmC enrichments in multiple hallmark gene sets, with androgen responses as the top enriched gene-set (FDR = 1.19E-13). We further show a significant association between high activity scores in these gene sets and poor progression-free survival (P < 0.05), even after adjusting for circulating tumor DNA fraction and prostate-specific antigen values. Additionally, our longitudinal analysis shows that the high activity score is significantly reduced after 3 months of initiating ADT (P = 0.0004) but returns to higher levels when the disease progresses (P = 0.0317).</p><p><strong>Conclusions: </strong>5hmC-based activity scores from gene-sets involved in AR responses show great potential in assessing treatment resistance, monitoring disease progression, and identifying patients who would benefit from upfront treatment intensification. However, further studies are needed to validate these findings.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"61"},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nationwide analysis of sex differences in waiting times for cataract surgery in Sweden between 2010 and 2022.","authors":"Philip Jute, Gustav Stålhammar","doi":"10.1038/s43856-025-00782-1","DOIUrl":"10.1038/s43856-025-00782-1","url":null,"abstract":"<p><strong>Background: </strong>Sex-based disparities in healthcare access remain a global challenge. We aimed to investigate differences in waiting times for cataract surgery between males and females in Sweden, hypothesizing that such disparities might persist even within a universal healthcare system.</p><p><strong>Methods: </strong>We performed a nationwide retrospective cohort study using data from the Swedish National Cataract Register, which includes over 93% of all cataract surgeries. A total of 1,413,652 patients over 40 years of age who underwent cataract surgery between 2010 and 2022 were included. Exclusions were applied to those with waiting times exceeding 24 months and those residing outside Sweden. The primary outcome was waiting time between preoperative assessment and surgery, stratified by visual acuity, region, and demographic and clinical factors.</p><p><strong>Results: </strong>Here we show a mean waiting time of 64 days (standard deviation 126) for females and 60 days (standard deviation 102) for males (P < 0.001). This difference persists across all visual acuity strata and regions. A linear mixed-effects model with region as a random intercept indicates that males have a 3.3-day shorter waiting time compared to females (P < 0.001). Multivariate hazards regression identifies female sex, older age, specific comorbidities, and region of residence as significant predictors of longer waiting times. Although overall waiting times decrease over the study period, the sex-based gap remains consistent.</p><p><strong>Conclusions: </strong>We observe a persistent, albeit small, difference in waiting times favoring males. These findings highlight a systemic disparity that warrants further investigation and targeted interventions to ensure equitable access to cataract care.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"60"},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution spatial prediction of anemia risk among children aged 6 to 59 months in low- and middle-income countries.","authors":"Johannes Seiler, Mattias Wetscher, Kenneth Harttgen, Jürg Utzinger, Nikolaus Umlauf","doi":"10.1038/s43856-025-00765-2","DOIUrl":"10.1038/s43856-025-00765-2","url":null,"abstract":"<p><strong>Background: </strong>Anemia, a severe condition among children associated with adverse health effects such as impaired growth, limited physical and cognitive development, and increased mortality risk, remains widespread, particularly in low- and middle-income countries. This study combines Demographic and Health Surveys data with remotely sensed climate, demographic, environmental, and geo-spatial information, creating a data set comprising about 750,000 observations on childhood anemia from 37 countries. It is used to provide high-resolution spatio-temporal estimates of all forms of childhood anemia between 2005 and 2020.</p><p><strong>Methods: </strong>Employing full probabilistic Bayesian distributional regression models, the research accurately predicts age-specific and spatially varying anemia risks. These models enable the assessment of the complete distribution of hemoglobin levels. Additionally, this analysis also provides predictions at a high resolution, allowing precise monitoring of this indicator, aligned with Sustainable Development Goal (SDG) 2.</p><p><strong>Results: </strong>This analysis provides high-resolution estimates for all forms of anemia and reveals and identifies striking disparities within and between countries. Based on these estimates, the prevalence of anemia decreased from 65.0% [62.6%-67.4%] in sub-Saharan Africa and 63.1% [60.6%-65.5%] in South Asia in 2010 to 63.4% [60.7%-66.0%] in sub-Saharan Africa and 58.8% [56.4%-61.3%] in South Asia in 2020. This translates into approximately 98.7 [94.5-102.8] million and 95.1 [91.1-99.0] million affected children aged 6 to 59 months in 2020, respectively, making it a major public health concern.</p><p><strong>Conclusions: </strong>Our approach facilitates the monitoring of age-specific spatio-temporal dynamics and the identification of hotspots related to this important global public health issue. To our knowledge, this represents the first high-resolution mapping of anemia risk in children. In addition, these results reveal striking disparities between and within countries and highlight the influence of socio-economic and environmental factors on this condition. The findings can guide efforts to improve health systems, promote education, and implement interventions that break the cycle of poverty and anemia.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"57"},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880423/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data linkage multiplies research insights across diverse healthcare sectors.","authors":"T S Karin Eisinger-Mathason, Jonah Leshin, Varun Lahoti, Doug B Fridsma, Vera Mucaj, Abel N Kho","doi":"10.1038/s43856-025-00769-y","DOIUrl":"10.1038/s43856-025-00769-y","url":null,"abstract":"<p><p>In all fields of study, as well as government and commerce, high-quality data enables informed decision-making. Linking data from disparate sources multiplies the opportunities for novel insights and evidence-based decision-making for an increasingly large range of administrative, clinical, research, and population health use cases. In recent years, novel methods, including privacy-preserving record linkage methods, have emerged. However, regardless of the method, successful data linkage is highly dependent on data quality and completeness and has to be balanced by the increased risk of re-identification of the subsequently linked data. Opportunities for the future include sharing tools for responsible linkage across silos, enhancing data to improve quality and completeness, and ensuring linkage leverages inclusive and representative datasets to ensure a balance between individual privacy and representation in research and novel discoveries. Here we provide a brief overview of the history and current state of data linkage, highlight the opportunities created by linked population data across critical research sectors, and describe the technology and policies that govern its usage.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"58"},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metformin-regulated glucose flux from the circulation to the intestinal lumen.","authors":"Kazuhiko Sakaguchi, Kenji Sugawara, Yusei Hosokawa, Jun Ito, Yasuko Morita, Hiroshi Mizuma, Yasuyoshi Watanabe, Yuichi Kimura, Shunsuke Aburaya, Masatomo Takahashi, Yoshihiro Izumi, Takeshi Bamba, Hisako Komada, Tomoko Yamada, Yushi Hirota, Masaru Yoshida, Munenobu Nogami, Takamichi Murakami, Wataru Ogawa","doi":"10.1038/s43856-025-00755-4","DOIUrl":"10.1038/s43856-025-00755-4","url":null,"abstract":"<p><strong>Background: </strong>Through a retrospective analysis of existing FDG PET-MRI images, we recently demonstrated that metformin increases the accumulation of FDG in the intestinal lumen, suggesting that metformin stimulates glucose excretion into the intestine. However, the details of this phenomenon remain unclear. We here investigate the detailed dynamics of intestinal glucose excretion, including the rate of excretion and the metabolism of excreted glucose, in both the presence and absence of metformin.</p><p><strong>Methods: </strong>We quantified intestinal glucose excretion using newly developed FDG PET-MRI-based bioimaging in individuals with type 2 diabetes, both treated and untreated with metformin. The metabolism of excreted glucose was analyzed through mass spectrometry of fecal samples from mice intravenously injected with ¹³C-labeled glucose.</p><p><strong>Results: </strong>Continuous FDG PET/MRI image taking reveals that FDG is initially observed in the jejunum, suggesting its involvement in FDG excretion. Metformin-treated individuals excrete a significant amount of glucose (~1.65 g h^-1 per body) into the intestinal lumen. In individuals not receiving metformin, a certain amount of glucose (~0.41 g h^-1per body) is also excreted into the intestinal lumen, indicating its physiological importance. Intravenous injection of ¹³C-labeled glucose in mice increases the content of ¹³C in short-chain fatty acids (SCFAs) extracted from feces, and metformin increased the incorporation of ¹³C into SCFAs.</p><p><strong>Conclusions: </strong>A previously unrecognized, substantial flux of glucose from the circulation to the intestinal lumen exists, which likely contributes to the symbiosis between gut microbiota and the host. This flux represents a potential target of metformin's action in humans.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"44"},"PeriodicalIF":5.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep proteome profiling of metabolic dysfunction-associated steatotic liver disease.","authors":"Felix Boel, Vyacheslav Akimov, Mathias Teuchler, Mike Krogh Terkelsen, Charlotte Wilhelmina Wernberg, Frederik Tibert Larsen, Philip Hallenborg, Mette Munk Lauridsen, Aleksander Krag, Susanne Mandrup, Kim Ravnskjær, Blagoy Blagoev","doi":"10.1038/s43856-025-00780-3","DOIUrl":"10.1038/s43856-025-00780-3","url":null,"abstract":"<p><strong>Background: </strong>Metabolic dysfunction-associated steatotic liver disease (MASLD) affects roughly 1 in 3 adults and is a leading cause of liver transplants and liver related mortality. A deeper understanding of disease pathogenesis is essential to assist in developing blood-based biomarkers.</p><p><strong>Methods: </strong>Here, we use data-independent acquisition mass spectrometry to assess disease-state associated protein profiles in human liver, blood plasma, and white adipose tissue (WAT).</p><p><strong>Results: </strong>In liver, we find that MASLD is associated with an increased abundance of proteins involved in immune response and extracellular matrix (ECM) and a decrease in proteins involved in metabolism. Cell type deconvolution of the proteome indicates liver endothelial and hepatic stellate cells are the main source of ECM rearrangements, and hepatocytes are the major contributor to the changes in liver metabolism. In the blood, profiles of several MASLD-associated proteins correlate with expression in WAT rather than liver and so could serve as suitable liver disease predictors in a multi-protein panel marker. Moreover, our proteomics-based logistic regression models perform better than existing methods for predicting MASLD and liver fibrosis from human blood samples.</p><p><strong>Conclusions: </strong>Our comprehensive proteomic analysis deepens the understanding of liver function and MASLD pathology by elucidating key cellular mechanisms and multi-organ interactions, and demonstrates the robustness of a proteomics-based biomarker panel to enhance diagnosis of MASLD and significant fibrosis.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"56"},"PeriodicalIF":5.4,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}