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PubMed2026

Gut bacteria associated with an atherogenic TMAO-dietary pattern and choline-rich foods among aging women.

BACKGROUND AND AIMS: Choline can be metabolized by gut bacteria with a choline utilization gene, CutC, as identified through genome sequencing studies. This metabolism produces trimethylamine, the precursor to the atherosclerotic metabolite trimethylamine N-oxide (TMAO). Bacterial species involved in trimethylamine production in free-living humans have been under-investigated. We previously developed the TMAO dietary pattern (TMAO-DP), which is predictive of plasma TMAO and choline. We evaluated associations between the TMAO-DP, dietary choline, and choline-rich foods (fish, red meat, eggs) with the abundance of species with CutC. We also explored associations between the TMAO-DP and microbiome diversity. METHODS AND RESULTS: This cross-sectional analysis included 287 women (mean age = 79.6 years) from the Women's Health Initiative. Diet was assessed using a food frequency questionnaire. Stool samples were collected and the V3-V4 regions of the 16S ribosomal RNA were sequenced. Adjusted linear regression models evaluated associations between the TMAO-DP with the CLR-transformed abundance of species with CutC and with alpha-diversity indices. For beta-diversity, PERMANOVA examined measures of Aitchison distance within and between quartiles of the TMAO-DP. Associations between dietary choline and choline-rich foods with the abundance of species were evaluated using linear regression. The TMAO-DP was associated with Acidaminococcus intestini [Beta (SE): 0.23 (0.09), p-value = 0.035] and Desulfovibrio desulfuricans [Beta (SE): 0.16 (0.6), p = 0.035]. The TMAO-DP was not associated with alpha- or beta-diversity. CONCLUSION: This study provides evidence that Desulfovibrio desulfuricans and Acidaminococcus intestini, two species identified as having CutC by gene sequencing, may produce trimethylamine from diet in free-living women.

Humans↗

PubMed2026

Lactiplantibacillus plantarum SLpl116 attenuates OVA-induced food allergy with ecological restoration of the gut microbiota and immune rebalancing.

Gut dysbiosis is increasingly recognized as a key contributor to food allergy, yet probiotic strains capable of restoring allergic microbiota and rebalancing host immunity remain limited. Here, we identified Lactiplantibacillus plantarum SLpl116 through a multi-criteria screening pipeline integrating anti-allergic activity, safety, and processing stability, and evaluated its efficacy in a prophylactic ovalbumin (OVA)-induced murine food allergy model. SLpl116 significantly attenuated allergic symptoms, including diarrhea and hypothermia, and suppressed serum IgE, IgG1, OVA-specific immunoglobulins, and mucosal mast cell protease-1. It was also associated with suppression of Th2-related responses and enhancement of systemic Th1-associated signaling, indicating restoration of Th1/Th2 immune balance. Microbiome analysis showed that SLpl116 was associated with ecological restoration of the dysbiotic gut community, including suppression of allergy-associated taxa such as Alistipes finegoldii and Bacteroides and enrichment of beneficial commensals, particularly Lachnospiraceae. Correlation analysis supported an association between microbial reconfiguration and immune rebalancing, while PICRUSt2-based functional prediction suggested enriched butyrate-associated metabolic potential in the effective strain groups. Comparative genome-informed analysis further indicated that SLpl116 possessed distinctive phenotype-linked features, providing a plausible molecular rationale for its favorable phenotype. Together, these findings identify SLpl116 as a promising strain-level probiotic candidate associated with direct immune rebalancing and microbiome-associated ecological restoration.

Journal Article↗

PubMed2026

A Risk Score for Polycystic Ovary Syndrome Based on Meta-Analysis and Machine Learning of Gut Microbiota Signatures.

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine and metabolic disorder among reproductive-age women, in which emerging evidence suggests a substantial role played by the gut microbiota. To comprehensively evaluate gut microbiota alterations in PCOS and identify microbial biomarkers through integrated analysis, a systematic search of PubMed, Web of Science, and Embase was conducted for studies employing 16S rRNA gene sequencing of fecal samples from PCOS cohorts. Ten eligible PCOS cohorts, comprising 858 individuals, were included in the study, from which a risk score was derived using a 20-gene gut microbial signature associated with PCOS. Meta-analysis at the genus level identified that Subdoligranulum, NK4A214_group, and Collinsella significantly decreased, and Bacteroides increased in PCOS across multiple cohorts. Machine learning analysis identified a 20-genus microbial signature using the least absolute shrinkage and selection operator (LASSO) method, which was used to construct a risk score with an AUC of 0.835 in diagnosis prediction. Network analysis further identified Negativibacillus and Lachnospiraceae_UCG_010 as potential driver microbes in PCOS. The analysis in this study highlights key alterations in the gut microbiota across PCOS cohorts. The identified gut microbial signature and derived LASSO-based risk model offer novel insights and a potential tool for PCOS diagnosis.

Polycystic Ovary Syndrome↗

PubMed2026

Ruminosignatures associated with methane emissions and feed efficiency across geographies and cattle breeds.

The cattle rumen microbiota represents a complex and dynamic ecosystem whose organization and relationship to host phenotypes are important for food security and environmental sustainability. We analyzed rumen microbiota profiles from 2496 cattle representing five breeds and production systems across five countries, identifying microbial co-abundance groups termed Ruminosignatures. We detected 14 distinct Ruminosignatures, including 2 observed across all populations dominated by Prevotella and UBA2810. Additional Ruminosignatures showed breed- and diet-specific patterns and collectively explained 96%-99% of variance in rumen microbial composition. Integrative cross-country analysis confirmed 10 out of 14 Ruminosignatures identified in cohort-specific analyses. Several Ruminosignatures were associated with methane emissions and feed efficiency traits and were partially under host genetic control, with heritability estimates ranging from 0.09 to 0.58. Structural equation modeling revealed consistent negative genetic and phenotypic correlations between the UBA2810-dominated Ruminosignature (RS_UBA2) and methane emissions across cohorts (rg = -0.40 to -0.65), with structural coefficients concordant in sign across all populations, supporting the expected direction of phenotypic response to selection on RS_UBA2. Meta-analysis confirmed positive associations of RS_UBA2 with average daily gain and negative associations with methane-related traits and feed conversion ratio. Functional genome-based predictions suggested RS_UBA2 may reduce methanogenesis through alternative hydrogen utilization pathways competing with methanogenic archaea. Production system type influenced both Ruminosignature occurrence and relationships with host phenotypes, emphasizing the relevance of context-specific strategies for microbiome modulation. Our findings highlight the potential of the Ruminosignatures framework for microbiome-informed breeding programs aimed at improving feed efficiency while reducing the environmental impact of cattle production.

Animals↗

PubMed2026

Harnessing Probiotic LAB and Bacteriocins for Clean-Label Food Processing and Biopreservation: Omics, Molecular Innovations and Industrial Applications.

The persistence of microbial agents in foods, especially spore forming bacteria is one of the most significant challenges to food preservation and safety, undermining product quality, shelf life, and consumer health. The use of traditional control methods, including thermal processing and chemical preservatives, are increasingly limited by consumer demands for minimally processed foods, and the emergence of resistant microbial strains. Advances have been made in the use of probiotics like lactic acid bacteria (LAB) and their biometabolites like bacteriocins in food processing and preservation, particularly to control biofilm and endospore forming pathogens including Bacillus sp., Listeria sp., Staphylococcus sp., Clostridium sp., E. coli etc. in foods and food processing plants/surfaces. Given the ability of these organisms to cause foodborne illness and form resilient biofilms in the food processing ecosystem and their resistance to the conventional method of their elimination, the antimicrobial peptides (bacteriocins) are gaining increasing prominence as useful alternatives to synthetic antimicrobials in enhancing food safety and combating the threats of these pathogens. This review addresses current information on the inhibition of persistent microbial spoilage contaminants, biofilm-forming pathogens, and spore formers of interest to the food industry using LAB and their bacteriocins. Current developments in isolation, characterization, and mode of action of bacteriocins are explored, including synergistic activity with other preservative hurdle techniques such as encapsulation, and nanobiotechnology. Importantly, there is a focus on the utilization of molecular and omics-based approaches to enable a better understanding of bacteriocin biosynthesis, gene regulation, host-microbe interactions and gut microbiome regulation potential of probiotic LABs, permitting the rational development of targeted and strain-specific interventions. Developments in the incorporation of bacteriocin-producing LAB into functional starter cultures and bio-protective products, and challenges in stability, regulatory approval, and scalability for industrial use, are also discussed in the paper. Despite their considerable potential, broader translation remains constrained by regulatory requirements, production and formulation costs, variable efficacy in complex food matrices, and the limited validation of many candidate bacteriocins beyond laboratory and model-food systems. Collectively, these advances position LAB and their bacteriocins at the leading edge of developing sustainable, clean-label, and efficacious functional foods and food preservation systems. Their functionality can be expanded by integrating genomics, synthetic biology, and predictive modeling for the maximization of their biopreservative potential in diverse food matrices and in gut microbiota modulation.

Bioactive Peptides↗

PubMed2026

Predictive Biomarkers for Immune Checkpoint Inhibitor Efficacy: Challenges, Innovations, and a Pathway to Precision Medicine in the Era of Cancer Immunotherapy.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed oncology practice. However, treatment response remains heterogeneous, rendering predictive biomarkers critical for optimal patient care. The 3 established biomarkers, programmed death-ligand 1, tumor mutational burden (TMB), and microsatellite instability-high/deficient mismatch repair, are approved and clinically validated but are modest predictors of benefit. As a result, multiple novel predictive biomarkers remain under investigation. CONTENT: This review highlights established and investigational predictive ICI efficacy biomarkers. For established biomarkers, we describe biology, assay modalities, approved companion diagnostics, landmark studies, and notable limitations. Due to the multisystem nature of antitumor immune effects, investigational biomarkers span multiple domains, including tumor genomic biomarkers (e.g., mutational signatures, TMB, neoantigen clonality), tumor microenvironment (e.g., tumor-infiltrating lymphocytes [TILs], tertiary lymphoid structures), systemic immune biomarkers (e.g., cytokines, autoantibodies, glycoproteins, peripheral blood mononuclear cells), and the microbiome (e.g., gastrointestinal microbial diversity, responder-enriched taxa). SUMMARY: The established biomarkers PD-L1, TMB, and microsatellite instability-high/deficient mismatch repair inform ICI use in clinical practice but have important limitations. Multiple investigational biomarkers show promise in refining patient selection and optimizing therapy. Moving forward, increased assay harmonization, prospective validation, and standardized parameters may improve performance. Composite models integrating complementary signals across domains may further individualize treatment and lead to an era of personalized cancer immunotherapy.

Humans↗

PubMed2026

Potential contribution of the microbiota-gut-brain axis to doxorubicin-associated cognitive impairment: Mechanisms, evidence, and therapeutic opportunities.

Chemotherapy-induced cognitive impairment (CICI), often termed chemobrain, is a clinically important complication of cancer treatment that can affect memory, attention, executive function, and processing speed during and after therapy. Doxorubicin is of particular mechanistic interest because brain parenchymal exposure is limited, yet preclinical studies consistently identify neuroinflammatory, oxidative, vascular, and synaptic abnormalities after treatment. This critical narrative review evaluates whether intestinal injury and disruption of the microbiota-gut-brain axis may contribute to these central effects. Preclinical evidence indicates that doxorubicin can alter microbial community structure, injure the intestinal barrier, modify SCFA-associated taxa or predicted functions, alter selected metabolite profiles, and promote systemic inflammatory and metabolic signaling. These peripheral changes could interact with brain endothelial cells, glia, mitochondria, hippocampal neurogenesis, and synaptic-plasticity pathways. However, the proposed doxorubicin-gut-brain pathway remains a predominantly preclinical and incompletely tested framework. No longitudinal human study has yet established, within the same patients, the temporal sequence linking doxorubicin exposure, microbiome or metabolome changes, systemic inflammation, and objective cognitive outcomes. Existing animal studies also vary in dose, regimen, tumor context, sampling time, microbiome methodology, and control of behavioral or microbiological confounders, while causal rescue experiments remain limited. Key priorities are therefore longitudinal human cohorts with pretreatment baselines and repeated multi-omics and cognitive assessments; animal studies that test temporal precedence and causal rescue or pathway blockade in the same model; mediation analyses that determine whether microbial or metabolic changes lie between treatment and cognitive dysfunction; and mechanism-informed clinical trials that demonstrate target engagement, cognitive benefit, oncology safety, and preservation of antitumor efficacy. Microbiome-directed interventions are promising but remain investigational for doxorubicin-associated CICI.

blood–brain barrier↗

PubMed2026

Ecological Restoration of the Soil-Like Function in the Bauxite Residue: Natural Microbiomes Mediated Molecular Transformation of Dissolved Organic Matter.

Soilization of bauxite residues offers a scalable route for long-term carbon management and ecological restoration. However, the microbial processes that transform exogenous organic inputs into stable soil-like carbon pools remain poorly resolved. Here, we combined cross-ecosystem meta-analysis, machine-learning prediction, native synthetic community (SynCom) construction, 13C-labeled straw microcosms, field validation, Fourier transform ion cyclotron resonance mass spectrometry, and genome-resolved metagenomics to unravel microbiome-mediated carbon transformation at the dissolved organic matter (DOM) molecular scale. Our meta-analysis revealed that alkaline industrial wastes retained soil-like DOM signatures but were enriched in microbial humic- and protein-like components, indicating active yet incomplete carbon processing. Guided by these patterns, native SynCom inoculation increased 13C incorporation into total organic carbon (TOC) and dissolved organic carbon (DOC), enlarged biodegradable and adsorbable DOC fractions, and shifted DOM from recalcitrant aromatic pools toward oxygenated carbohydrate-, tannin-, and phenolic-like molecular classes. Genome-resolved analyses linked this transformation to complementary polymer degradation and nutrient-cycling functions across fungal and bacterial guilds, including enriched carbohydrate-active enzymes in straw-carbon-utilizing metagenome-assembled genomes. Null model and thermodynamic analyses further showed that microbial communities were constrained by homogeneous selection, whereas DOM molecules were diversified through variable selection and redox-dependent transformation. Field-scale validation confirmed that SynCom promoted TOC and DOC accumulation and humic-like, high-density DOM fractions under alkaline conditions. Together, these findings establish a mechanistic framework in which functional microbiomes couple plant carbon depolymerization, DOM molecular diversification, and mineral-interactive carbon stabilization, providing a microbiome-guided strategy for carbon sequestration and soilization in the bauxite residue.

Soil↗

PubMed2025

Health-associated key gut microbiota drives the variation in community metabolic interactions in non-human primates.

Gut microbiota often undergo metabolic cross-feeding and resource competition. However, our understanding of global variations in these interactions and their implications for host health remain elusive. By analyzing a microbial genome catalog from 841 fecal metagenomes across 53 primate species worldwide, we identified key microbiota assigned to two taxa, i.e., Bacillota_A and Pseudomonadota, which well predicted the trade-off of community-level interaction types between metabolic competition and cooperation. Specifically, Bacillota_A species were inherently competitive and amino acid auxotrophic and typically found in anaerobic habitats. In contrast, members of Pseudomonadota were inherently cooperative, siderophore producers, and more abundant in aerobic conditions. Random forest models successfully distinguished unhealthy gut samples from healthy samples through the key competitive and cooperative microbiota, suggesting potential links between community metabolic interactions and host health. Together, this study enhances our mechanistic understanding of microbial interaction dynamism within complex gut ecosystems, offering new targets for understanding host health.

Animals↗

PubMed2026

An Acetyltransferase Conferring Self-Resistance of the Producer to Lasso Peptide Antibiotic Lariocidin.

The soil microbiome, a reservoir of antibiotic-producing bacteria, also harbors resistance determinants encoded within antibiotic biosynthetic gene clusters (BGCs). Studying self-resistance mechanisms, which have evolved in producers to protect against their own toxic metabolites, provides critical insights into the evolution of resistance and the potential vulnerabilities of new antibiotics and can facilitate the production of natural products in heterologous hosts. Here, we describe the self-resistance mechanism to lariocidin (LAR), a recently discovered lasso peptide antibiotic that inhibits the ribosomal machinery and exhibits antibacterial activity against key pathogens. We identified and characterized an N-acetyltransferase enzyme (LrcE) encoded within the LAR BGC that mediates self-resistance in LAR-producing Paenibacillus sp. M2. LrcE is a member of the GCN5-related N-acetyltransferase (GNAT) superfamily and performs site-specific acetylation of LAR at a critical lysine residue. This modification disrupts ribosomal binding, thereby reducing LAR's antibacterial activity. Using in silico modeling, we predicted a conserved acetyl-CoA-binding motif and an LAR-binding region on LrcE. Bioinformatic analysis revealed LrcE homologues in environmental but not clinically relevant pathogens, suggesting a limited risk of horizontal gene transfer and, therefore, supporting the further development of LAR as a next-generation antibiotic.

Anti-Bacterial Agents↗

PubMed2026

Microbial Interactions with Protein Intake and Preterm Infant Body Composition: Secondary Analysis of a Randomized Trial.

BACKGROUND: Enteral protein supplementation improves preterm infant growth and may impact body composition and the gut microbiota. OBJECTIVES: This study aimed to identify the effects of additional enteral protein supplementation on the gut microbiota and microbial and clinical drivers of body composition. METHODS: Secondary analysis of a masked randomized trial of additional enteral protein vs. standard fortification in preterm infants born at 25 to 28 weeks of gestation (NCT03586102) was conducted. Stool samples at weeks 4 and 8 underwent 16S rRNA sequencing; functional potential was predicted by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2). Body composition was measured by air-displacement plethysmography at 36 wk postmenstrual age (PMA). Least absolute shrinkage and selection operator (LASSO) regression with multivariable linear regression identified body composition predictors. RESULTS: Among 46 infants, gestational age (P = 0.16) and sex (P = 0.55) did not differ between groups. The protein group had higher week 4 Shannon diversity than standard fortification (median 1.2 vs. 0.87, P = 0.049). Week 4 Shannon diversity was positively correlated with fat-free mass z-score at 36 wk PMA (r2 = 0.34, P = 0.02). Adjusting for covariates, the protein group had higher Peptoniphilus (β = 1.6, Padj = 0.10) and lower Vibrio centered log-ratio abundance (β = -0.98, Padj = 0.10); 62 predicted metabolic pathways were lower in the protein group (false discovery rate < 0.20). In combined LASSO models, Bacillus abundance at week 4 was the strongest predictor of fat-free mass z-score (β = -0.17, P < 0.001; R2 = 0.80) and fat mass z-score (β = -0.31, P < 0.001; R2 = 0.66). CONCLUSIONS: Additional protein supplementation is associated with fat-free mass z-score and alterations to the gut microbiota. Clinical variables and microbial variables are key predictors of body composition, suggesting that nutrition, clinical factors, and the gut microbiota jointly contribute to body composition in extremely preterm infants. This study was registered at clinicaltrials.gov as NCT03586102 https://clinicaltrials.gov/study/NCT03586102 (registered in March 2020).

Humans↗

PubMed2025

Exploring phage-host interactions in Burkholderia cepacia complex bacterium to reveal host factors and phage resistance genes using CRISPRi functional genomics and transcriptomics.

Complex interactions of bacteriophages with their bacterial hosts determine phage host range and infectivity. While phage defense systems and host factors have been identified in model bacteria, they remain challenging to predict in non-model bacteria. In this paper, we integrate functional genomics and transcriptomics to investigate phage-host interactions, revealing active phage resistance and host factor genes in Burkholderia cenocepacia K56-2. Burkholderia cepacia complex species are commonly found in soil and are opportunistic pathogens in immunocompromised patients. We studied infection of B. cenocepacia K56-2 with Bcep176, a temperate phage isolated from Burkholderia multivorans. A genome-wide dCas9 knockdown library targeting B. cenocepacia K56-2 was constructed, and a pooled infection experiment identified 63 novel genes or operons coding for candidate host factors or phage resistance genes. The activities of a subset of candidate host factor and resistance genes were validated via single-gene knockdowns. Transcriptomics of B. cenocepacia K56-2 during Bcep176 infection revealed that expression of genes coding for host factor and resistance candidates identified in this screen was significantly altered during infection by 4 h post-infection. Identifying which bacterial genes are involved in phage infection is important to understand the ecological niches of B. cenocepacia and its phages, and for designing phage therapies.IMPORTANCEBurkholderia cepacia complex bacteria are opportunistic pathogens inherently resistant to antibiotics, and phage therapy is a promising alternative treatment for chronically infected patients. Burkholderia bacteria are also ubiquitous in soil microbiomes. To develop improved phage therapies for pathogenic Burkholderia bacteria, or engineer phages for applications, such as microbiome editing, it's essential to know the bacterial host factors required by the phage to kill bacteria, as well as how the bacteria prevent phage infection. This work identified 65 genes involved in phage-host interactions in Burkholderia cenocepacia K56-2 and tracked their expression during infection. These findings establish a knowledge base to select and engineer phages infecting or transducing Burkholderia bacteria.

Bacteriophages↗

PubMed2026

A three-metabolite microbiota-associated signature for early risk stratification of gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes and long-term metabolic and cardiovascular risk. However, oral glucose tolerance testing at 24-28 gestational weeks limits early risk stratification. Gut microbiota-associated metabolites may reflect early metabolic abnormalities, including those relevant to cardiometabolic health, but robust early-pregnancy biomarkers remain limited. METHODS: We conducted a multicenter nested case-control and prospective study involving 2,693 pregnant women. Untargeted metabolomics and metagenomics were integrated to identify GDM-associated metabolites and gut microbial alterations. Three consistently dysregulated metabolites, 3-hydroxydecanoic acid, γ-Glu-Leu, and propionic acid, were quantified by targeted LC-MS/MS. Candidate algorithms were compared using repeated 10-fold cross-validation, and a final generalized linear model was externally and prospectively validated. RESULTS: Women who later developed GDM showed an adverse early-pregnancy metabolic profile, including higher BMI, triglycerides, and platelet count. Untargeted metabolomics identified 14 persistently altered metabolites enriched in energy, oxidative stress, and amino acid metabolism pathways. Metagenomics revealed taxonomic restructuring and coordinated microbiota-metabolite associations. The three-metabolite model achieved AUCs of 0.838 (95% CI, 0.791-0.885) in training, 0.840 (95% CI, 0.769-0.911) in internal validation, 0.955 (95% CI, 0.925-0.985) and 0.917 (95% CI, 0.875-0.958) in two external cohorts, and 0.969 (95% CI, 0.937-1.000) in the prospective cohort. CONCLUSION: Early microbiota-associated metabolic dysregulation is detectable before routine GDM diagnosis. This compact three-metabolite panel may support early GDM risk stratification and provides metabolic evidence relevant to broader cardiometabolic risk assessment in pregnancy.

Humans↗

PubMed2026

The Mediating Role of Immune Cells in the Genetically Predicted Relationship between Gut Microbiota and Puerperal Sepsis: A Mendelian Randomization Study.

INTRODUCTION: The causal relationship between gut microbiota and puerperal sepsis (PS) remains unclear, and there is a lack of in-depth research regarding the potential mediating role of immune cells in this context. OBJECTIVE: This study aims to investigate the causal relationship between gut microbiota and PS using Mendelian randomization (MR) analysis and to assess the mediating effects of immune cells on the risk of PS onset through mediation analysis. MATERIALS AND METHODS: We selected data from large-scale genome-wide association studies (GWAS) involving 473 gut microbiota species, 731 immune cell phenotypes, and PS datasets. Univariate MR (UVMR) analysis was employed to explore the causal relationship between gut microbiota and PS, with the primary statistical method being inverse variance weighting (IVW). Multiple statistical models were applied for sensitivity analysis to minimize the confounding effects of horizontal pleiotropy and heterogeneity. Subsequently, a two-step mediation MR analysis was conducted to evaluate whether immune cells mediate the relationship between gut microbiota and PS. RESULTS AND DISCUSSION: Analysis using various statistical models indicated that 11 gut microbiota species (e.g., Azorhizobium, Bacillus velezensis, CAG-245 sp000435175, Lentimicrobiaceae, and Providencia) exhibited a causal relationship with PS. Further reverse causal analysis between PS and gut microbiota ruled out the possibility of reverse causality. The two-step mediation MR analysis demonstrated that the percentage of IgD-CD27- B cells (10.26%) and CD62L- monocytes (17.29%) partially mediated the effect of CAG-245 sp000435175 on PS risk. CONCLUSION: This study provides evidence of a causal relationship between the abundance of certain gut microbiota species and PS, while also revealing a potential mediating role of immune cells. These findings offer valuable theoretical insights into personalized treatment strategies and the development of novel diagnostic biomarkers for PS.

Humans↗