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Patient and hospital factors associated with disparities in acute stroke treatment in community and academic hospitals.

BACKGROUND: Systemic barriers may affect identification, emergency transportation (EMS), and care coordination for people with stroke. We assessed patient- and hospital-level factors for associations with pre-hospital and emergency department care. We compared trends for patients presenting to an academic medical center (AMC) versus community hospitals (CHs). METHODS: We conducted a retrospective cohort study at an AMC (Tufts Medical Center) with 542 patients aged ≥18 years hospitalized with acute ischemic stroke or transient ischemic attack between 1/1/2018-12/31/2020 who presented directly to AMC or presented to AMC as a transfer from initial contact CHs. Primary outcomes were EMS use, stroke code activation, door-to-CT time, and door-to-needle time. RESULTS: AMC patients identifying as non-Hispanic Asian (odds ratio (OR) = 0.25; 95% confidence interval (CI) = 0.13-0.47) and Hispanic (OR = 0.19; 95% CI = 0.05-0.72) and CH non-Hispanic Black/African-American patients (OR = 0.17; 95% CI = 0.05-0.62) were less likely to use EMS compared to non-Hispanic white patients. Patients with non-English primary language were less likely to use EMS (OR = 0.38; 95% CI = 0.23-0.63) compared to English-speaking patients in both hospital settings. CH Hispanic patients were less likely to have stroke code activation (OR = 0.24; 95% CI = 0.05-0.86) compared to non-Hispanic white patients. CH patients were less likely to have stroke code activation (OR = 0.12; 95% CI = 0.07-0.19), had 31% shorter door-to-CT time (95% CI = 15-43% shorter), and had 29% longer door-to-needle time (95% CI = 5-58% longer). CONCLUSION: Patient-level factors and hospital setting were associated with differences in acute care suggesting opportunities for community outreach on EMS use, interventions to alleviate language barriers, and a need to address systemic biases.

Humans

Exploring determinants of vaccine hesitancy among healthcare professionals: a systematic literature review.

INTRODUCTION: This systematic review aims to assess determinants of vaccine hesitancy (VH) among healthcare professionals, to identify knowledge gaps and inform targeted training programs. RESEARCH DESIGN AND METHODS: A systematic search of PubMed and Scopus was conducted in February 2024. PRISMA criteria were applied, and methodological quality was assessed using a cross-sectional study evaluation tool. Studies addressing HCWs' VH determinants, including knowledge, attitudes, communication, and organizational factors, were included. RESULTS: Out of 1394 records, 221 articles were included. Reported prevalence of VH among HCWs varied across studies, reflecting differences in professional roles, settings, and vaccines studied. Key determinants included gaps in knowledge, personal beliefs, organizational barriers, and communication skills. The review highlights the importance of evidence-based information, continuing education, and effective communication in addressing VH among HCWs. CONCLUSIONS: Educational and organizational interventions are essential to improve HCWs' knowledge, attitudes, and practices regarding vaccination. Strengthening vaccine education, fostering effective communication, and addressing organizational challenges can reduce hesitancy and support HCWs in promoting vaccination among patients. Future initiatives should consider the diversity of educational settings, professional roles, and training requirements across healthcare systems.

Humans

Standardized visual overlays enhance laparoscopic instruction: A mixed-methods evaluation.

Effective communication during laparoscopic procedures is frequently undermined by spatial disorientation and inconsistent terminology between instructors and trainees. This study examined whether standardized visual overlays on endoscopic monitors could enhance communication and learning. We conducted a three-phase mixed-methods study: qualitative observation of 20 laparoscopic teaching cases; a randomized trial of 63 second-year medical students assigned to control, clock, or alphanumeric grid (AG) overlays during three trials of a standardized transfer task; and intraoperative implementation in 44 cases (30 AG, 14 clock) with post-case surveys and qualitative feedback. In simulation, the clock overlay produced the fastest completion times, whereas the AG yielded the lowest error scores, and both overlays outperformed the control. Intraoperatively, the AG was rated higher than the clock for communication clarity, spatial orientation, perceived operative efficiency, and trainee confidence. Standardized visual overlays, particularly the AG, appear to support intraoperative teaching by providing a shared spatial frame of reference.

Laparoscopy

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Dynamics of soil fungal communities restored with biochar from a quarry site.

Quarrying activities have intensified due to population expansion, leading to landscape degradation and ecological destruction. Quarry restoration is usually mandatory in Hong Kong, China. Although biochar is used for sustainable soil amendment, its effectiveness in restoring quarry soil with poor properties has rarely been investigated. A 24-month field study was conducted to evaluate the ecological feasibility of restoring a quarry site by using native species (that is, Castanopsis fissa and Cyclobalanopsis edithiae) and biochar amendment. The results revealed that after 24 months, the application of biochar increased the organic carbon, phosphorus and potassium of the vegetated soil by at least 120 %, 31 % and 12 %, respectively, due to higher cation exchange capacity and better plant growth. The relative abundance of Ascomycota and Basidiomycota increased by 24 % and 47 % with biochar application when C. fissa was planted, which was likely associated with the improved nutrient cycling and soil fertility. Even though adding biochar to bare soil was found to increase the complexity of fungal co-occurrence networks, biochar application only increased fungal diversity in vegetated quarry soil but usually reduced its fungal richness. Moreover, fungal co-occurrence networks in vegetated soil became less complex, suggesting that biochar potentially helped plants to assemble specific, beneficial fungal communities. This effect is most pronounced in the soil planted with C. edithiae, where the structure of fungal communities after 24 months was significantly different from that at other restoration times. This study identifies key fungal phyla enhanced by biochar in quarry soil and provides an effective strategy for facilitating the restoration and management of degraded lands, especially quarry sites.

Charcoal

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation

Long-term petroleum pollution alters soil microbial communities via electron transfer capacity: Evidence from a 35-year chronosequence.

Petroleum pollution poses a serious threat to soil ecosystems, especially in areas surrounding oil wells, where contamination should not be overlooked. Through a 35-year longitudinal study of soils surrounding oil wells, we demonstrate that petroleum hydrocarbons accumulate predominantly in the top 10 cm of soil, reducing the electron acceptor capacity (EAC) by 61.59 % (from 12.68 to 4.87 μmole-/gC) and decreasing the electron transfer capacity (ETC) by 43 %. Structural equation modeling identified ETC as the critical mediator of microbial community shifts, with EAC playing a pivotal role in sustaining redox processes. Notably, hydrocarbon accumulation triggered a microbial succession: The abundance of Actinomycetota (including genera Rhodococcus, Arthrobacter, and Rubrobacter) showed the most significant fluctuations within 2 years, while Pseudomonadota (genera Methylobacter, Thiobacillus, and Pseudomonas), which were dominant in uncontaminated soils, decreased markedly during this period. This transition coincided with peak microbial dysbiosis (microbial dysbiosis index in 2022 reached 31.41 times that of controls). Within two to four years following mild petroleum stress, the bacterial community established a new structural configuration, revealing a crucial window for ecological recovery. The coupling between ETC reduction and microbial succession highlights the pivotal role of electron flux in soil recovery. Our findings establish a mechanistic framework for ETC-targeted restoration strategies to enhance bioremediation in petroleum-contaminated soils.

Soil Microbiology

Messaging Strategies for Tobacco Prevention and Cessation Among People with Depression: A Scoping Review.

INTRODUCTION: Depression is strongly associated with higher tobacco use and lower quit rate; few communication campaigns have been designed with these mental health factors in mind. This scoping review compiles existing research on tobacco prevention and cessation messaging involving people with depression to identify gaps and opportunities for future message development. METHODS: Sources included PubMed, PsycINFO, Scopus, Academic Search Premier, and ProQuest Central (November - December 2024). The 55 studies included examined tobacco prevention or cessation messages and measured depression, depressive symptoms, or mental health as a primary outcome or analytic covariate. Study characteristics, target population, delivery format, message content, theoretical frameworks, outcomes, and gaps were extracted. RESULTS: RCTs made up half (51%) of the included studies, and most (78%) were conducted in the U.S. Nearly half (46%) required participants to have a mental health condition. Interventions most often used interactive (65.5%) or text-based (47.3%) communication and focused on tobacco cessation (89%) rather than vaping (9%). Common outcomes included feasibility or acceptability (37.7%) and point prevalence abstinence (37.7%). Mental health-specific messages showed mixed effectiveness. CONCLUSIONS: Despite progress in integrating mental health into tobacco messaging, targeted interventions for people with depression remain limited. Few studies tested long-term outcomes or used biochemical verification; many relied on untargeted generalized messaging.

Journal Article

A Sentiment-Based Comparison of AI- and Physician-Generated Empathic Statements in Palliative Care.

CONTEXT: Empathic communication promotes trust in patient-provider relationships. As healthcare integrates artificial intelligence (AI) into patient communication, we have yet to understand how these models' communication compares to that of physicians. OBJECTIVES: Our primary objectives were to examine patient preferences for AI-generated vs. palliative care physician-generated empathic statements addressing fear and anxiety around cancer treatment, and to analyze associations between linguistic features and patient preferences. METHODS: We conducted a secondary analysis of the PALL-AI trial, a randomized controlled survey comparing cancer patients' preferences of AI- to physician-generated empathic statements. Physicians and AI were provided the same prompt with a maximum sentence length. Patient preferences for each statement were measured in blinded surveys. We analyzed sentiment of the statements using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and the National Research Council Canada (NRC) Emotion Lexicon. We evaluated associations between sentiment scores and patient preferences using Spearman's correlation coefficients. RESULTS: A total of 105 patients completed blinded surveys, preferring the AI-generated statement 72.4% of the time. VADER sentiment analysis showed all three AI statements displayed positive sentiment, while all three physician statements displayed negative sentiment. Controlling for statement length, AI statements used twice as many positive words as human statements. However, they contained a similar number of negative words. Of the eight NRC emotions, "trust" and "joy" demonstrated the strongest correlations with patient preference. CONCLUSION: Patients preferred AI-generated statements around cancer care over those from palliative care physicians when standardized for prompt and statement length. Analysis shows AI-generated statements contain more positive language which may be the factor driving patient preference toward AI.

Humans

Gut microbiota and metabolic alterations in participants with flatulence identify Faecalibacterium prausnitzii as a key microbial target for clinical intervention.

Flatulence is closely associated with gut dysbiosis, yet the characteristic microbial signatures, metabolic alterations, and actionable intervention targets remain unclear. This limited mechanistic understanding has hindered the development of precise microbiota-based strategies for managing flatulence. Here, we found that participants with flatulence exhibited marked shifts in gut microbial functions and fecal metabolic profiles compared with healthy controls, characterized by enhanced abnormal fermentation, enrichment of oxidative stress-related functions, elevated low-grade inflammatory signatures, and reduced anti-inflammatory and mucosal-protective metabolic features. Faecalibacterium prausnitzii was significantly negatively associated with the high-gas-producing phenotype. In vitro replenishment experiments further validated the role of F. prausnitzii in reducing gas production, promoting butyrate generation, and remodeling butyrate-associated microbial communities. Based on microbial interaction analysis, we identified Bifidobacterium longum CCFM1319 as a candidate strain for targeting F. prausnitzii. In a double-blind, randomized, placebo-controlled clinical trial, supplementation with B. longum CCFM1319 significantly increased intestinal F. prausnitzii abundance and improved flatulence-related symptoms. Collectively, these findings reveal the microbiota and metabolic dysbiosis underlying flatulence, highlight the key regulatory role of F. prausnitzii, and lays the foundation for targeted microbiota-based intervention strategies for flatulence.

Humans

Psychiatric mental health nurse practitioner outcomes after completion of a 1-year postgraduate fellowship.

Psychiatric mental health nurse practitioners (PMHNPs) are an essential and growing part of the health care workforce, especially in community settings. To address PMHNPs' increasing presence in community psychiatry, a 1-year postgraduate PMHNP fellowship in community psychiatry was developed with the goals of enhancing clinical competency and employment retention in underserved public sector settings. Data on 5 cohorts and 31 fellows are presented in this article. PMHNP fellows, preceptors, didactics, and clinical sites were evaluated across several time points including baseline and 6 and 12 months. The program has graduated 100% of fellows with largely positive feedback. Fellows reported significant improvements in competency across the domains of 1) assessment and diagnosis, 2) treatment, and 3) professionalism and leadership. These items were substantiated by clinical preceptors' ratings of fellows' clinical skills from 6-month and 12-month time points. Relatedly, clinical sites, preceptors, and didactics were all rated highly by fellows. After the program, 90.3% of graduates remained working in the public sector including correctional settings, community clinics, and safety net hospitals.

Community psychiatry

Acceptability of alcohol-based hand rub during neonatal care in rural Ugandan households: a qualitative study nested within the BabyGel trial.

BACKGROUND: Poor access to water, sanitation and hygiene exacerbates the spread of infections among newborns. The BabyGel cluster randomised trial assessed the effectiveness of a community-level alcohol-based hand rub with a training component in reducing infection or death rates among newborns in Uganda. OBJECTIVE: Nested in the BabyGel trial, this study investigated the acceptability of the BabyGel intervention among mothers and household members in Eastern Uganda, using the Theoretical Framework of Acceptability. METHODS: In 2022, we conducted individual semistructured interviews with mothers, and group interviews with mothers and other household members, all recruited from intervention-arm clusters. Thematic analysis combined inductive and deductive coding, structured by the framework's seven constructs: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness and self-efficacy. RESULTS: Twenty mothers and 14 household members participated in 10 individual and 10 small group interviews. Participants found the intervention generally acceptable, appreciating its convenience and perceived protection against infection. Many described hand hygiene changes that persisted beyond the intervention period. However, concerns related to its harmful effects, spiritual beliefs and social tensions with visitors occasionally influenced its use. CONCLUSION: Alcohol-based hand rub combined with a training component was generally well accepted, driven by perceived health and practical benefits, although concerns related to safety, belief systems and social dynamics remained. Because data collection coincided with the COVID-19 pandemic, a period of heightened hygiene awareness, the acceptability observed could differ in nonpandemic periods. Culturally adapted education, community engagement and reinforcement of correct use may enhance acceptability and sustainability in similar settings.

Humans

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation

Elucidation of microbial community structure, small-molecule metabolic and flavor profile characteristics in Xuanwei ham under different processing techniques.

This study systematically compared the impacts of traditional (TH) and modern (MH) processing techniques on the physicochemical properties, microbial community structure, metabolome, and volatile aroma compounds of Xuanwei ham. The results showed that the TH group had higher moisture content and water activity, along with a more tender texture, whereas the MH group exhibited greater hardness and chewiness. Microbiological analysis revealed that the interior of the MH group had higher species richness of both fungi and bacteria, while the TH group maintained higher fungal diversity. Metabolomic analysis identified 112 differential metabolites, with sweet amino acids and certain lipids being more enriched in modern ham, whereas traditional ham contained higher levels of umami amino acids, polyunsaturated fatty acids, and flavor compounds such as carnosine. KEGG pathway enrichment indicated that the differences were primarily concentrated in amino acid biosynthesis and metabolism-related pathways. Volatile flavoromics analysis identified 45 odor-active compounds and screened 15 key aroma-active substances. Among them, modern processed ham was significantly enriched in fatty aldehydes such as (E)-2-nonenal, hexanal, nonanal, and octanal, whereas traditional processed ham was characterized by 1-octen-3-ol, (E,E)-2,4-decadienal, methional, acetoin, and benzeneacetaldehyde. Correlation analysis confirmed that dominant microbes in Xuanwei ham were significantly associated with differential metabolites and characteristic aroma compounds, respectively. This study provides a scientific basis for standardizing production processes, enabling precise quality control, and promoting high-quality industrial development of Xuanwei ham.

Animals

Depth-dependent microbial succession and interspecies hydrogen transfer drive pit mud maturation in Chinese strong-flavor baijiu fermentation.

Microbial communities in fermentation pit mud play a key role in determining the quality of Chinese strong-flavor baijiu (CSFB). However, the ecological processes underlying pit mud maturation across spatial and temporal scales remain unclear. In this study, amplicon sequencing and metagenomic analyses were employed to investigate the taxonomic succession, community assembly, and metabolic functions of bacterial and archaeal communities during the transition from fresh pit mud (FPM) to new pit mud (NPM) and old pit mud (OPM). A pronounced depth-dependent succession pattern was observed, with 4 cm representing a critical ecological boundary separating distinct community structures and maturation trajectories. During surface-layer maturation, community assembly shifted from stochastic to deterministic processes, accompanied by homogeneous selection and increasing network complexity. In contrast, stochastic processes remained dominant throughout deep-layer maturation. Metagenomic analyses revealed a functional transition from lactate and acetate production, primarily associated with Lactobacillus in FPM and NPM, to butyrate and caproate production associated with Clostridium and Caproiciproducens in OPM. This functional transition was accompanied by enhanced amino acid metabolism, which was associated with the enrichment of Proteiniphilum and Aminobacterium. Notably, methanogen-mediated interspecies hydrogen transfer (IHT) emerged as a key ecological feature during pit mud maturation. In OPM, IHT networks primarily involving Methanobacterium and Methanosarcina linked methanogenesis with reverse β-oxidation through diverse hydrogen-transfer pathways, reinforcing metabolic interactions underlying caproate production. These findings provide new insights into the ecological mechanisms underlying pit mud maturation and offer a theoretical basis for the directed cultivation of high-quality pit mud in CSFB production.

Hydrogen