Gut microbes reports最新文献

{"title":"Safety and efficacy concerns in Indian probiotics: Insights from whole-genome sequencing and <i>in vitro</i> assessment.","authors":"Irulappan Madhumathi, Vishnukumar Ramesh, Boomiga Rathakrishnan, Baby Abirami, Karthik Gunasekaran, T Sathish Kumar, Priyadharshini Jeyasankar, Gunachandru Raja, Karnan Selvam, Subbulakshmi Rajendran, Ayyanraj Neeravi, Kamini Walia, Balaji Veeraraghavan","doi":"10.1080/29933935.2026.2668863","DOIUrl":"10.1080/29933935.2026.2668863","url":null,"abstract":"<p><p>Acute diarrhea remains a major public health challenge in India, particularly among children, where probiotics are commonly used as adjunctive therapy. However, concerns regarding the quality, safety, and regulatory oversight of commercial probiotic formulations persist. This study evaluated 13 probiotic products marketed in India for antibiotic susceptibility, gastrointestinal survivability, and safety. A combined <i>in vitro</i> and genomic approach was employed, including microbial enumeration, MALDI-TOF identification, MIC testing, time-kill assays, simulated gastrointestinal survival, and whole-genome sequencing to assess strain identity, antimicrobial susceptibility, antimicrobial resistance genes (ARGs), and virulence-associated determinants. Five of the 13 products showed discrepancies between labeled and laboratory-enumerated CFU counts, and some contained contaminants such as <i>Enterococcus faecium</i>. Several bacterial probiotics used outdated nomenclature (e.g., \"LAB\" or <i>Lactobacillus sporogenes</i>), inconsistent with current taxonomy. Bacterial probiotics were found to be susceptible to co-prescribed antibiotics, which may compromise their therapeutic persistence. Whole-genome sequencing identified multiple antimicrobial resistance determinants, including <i>tet(L), erm(34), blaBCL-1</i>, <i>catA10</i>, and <i>ant(4')-Ib</i>. Among these, <i>tet(L), catA10,</i> and <i>ant(4')-Ib</i> showed higher predicted potential for mobilization, supported by literature and the presence of insertion sequence elements in this study. In contrast, <i>erm(34)</i> and <i>blaBCL-1</i> are generally considered chromosomally encoded intrinsic resistance determinants. In contrast, the yeast probiotic <i>Saccharomyces boulardii</i> is intrinsically resistant to antibacterial agents and shows superior gastrointestinal survivability. Overall, inconsistencies in labeling, composition, and genomic safety underscore the need for strain-level labeling, genomic validation, and stronger regulatory oversight to ensure probiotic quality and safety.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2668863"},"PeriodicalIF":0.0,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13178174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147966440","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":"The food matrix as a confounder in diet‒microbiome studies: methodological challenges and research gaps.","authors":"Erin O'Sullivan, Olivia Solano, Julia S Oliveira, Abigail J Johnson, Sushil Dhital, Prasanth K S Pillai, Fernanda Dias, Job Ubbink, Annie W Lin, Levi Teigen","doi":"10.1080/29933935.2026.2671724","DOIUrl":"10.1080/29933935.2026.2671724","url":null,"abstract":"<p><p>Interactions of structural and physicochemical properties of food (e.g. texture, viscosity, and solubility), known as the food matrix, are primary drivers of host digestive kinetics. While the impact of matrix-driven variability on nutrient bioaccessibility, glycemic response, and caloric absorption is well documented, these dynamics are often overlooked in diet-microbiome research. Adequately modeling the spatiotemporal availability of microbial substrate is essential to understanding how dietary patterns impact the microbiome throughout the gastrointestinal tract. This narrative review 1) synthesizes current evidence on how food processing and structure affect human digestion and absorption of macronutrients; 2) illustrates how host digestive kinetics impact forms and quantity of substrate delivered and available to the gut microbiota; and 3) identifies challenges and knowledge gaps in current diet-microbiome research regarding food structure. The challenges and knowledge gaps discussed here call for in vivo models that can better model microbial substrate availability throughout the gastrointestinal tract to improve our understanding of diet-microbiome interactions.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2671724"},"PeriodicalIF":0.0,"publicationDate":"2026-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13178186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147966377","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":"Infection strategies of <i>Salmonella</i>Typhimurium for gut-lumen colonization: Overcoming host defenses, exploiting host responses, and adapting to the enteric niche.","authors":"Tsuyoshi Miki, Masahiro Ito, Takeshi Haneda, Nobuhiko Okada, Yun-Gi Kim","doi":"10.1080/29933935.2026.2671472","DOIUrl":"10.1080/29933935.2026.2671472","url":null,"abstract":"<p><p>Diarrheal disease is a leading cause of child morbidity and mortality globally, largely resulting from contaminated food and water and exposure to enteric pathogens. <i>Salmonella enterica</i> serovar Typhimurium (<i>S</i>Tm) is an enteropathogenic bacterium that infects the gastrointestinal tract using diverse strategies that are still being elucidated. Meanwhile, the gut comprises a complex ecosystem known as the microbiome, which is densely inhabited by microbial communities. The microbiome confers colonization resistance against enteropathogenic bacteria, whereas <i>S</i>Tm can overcome these defenses to establish infection. Here, we review <i>S</i>Tm infection strategies in the gut, with a particular focus on evidence from mouse models. Understanding <i>S</i>Tm virulence mechanism and adaptation strategies may inform the development of targeted interventions to prevent and treat gastrointestinal infection.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2671472"},"PeriodicalIF":0.0,"publicationDate":"2026-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13170390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147944242","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":"<i>In vitro</i> study of ethanol production, ethanol tolerance, and antimicrobial susceptibility of gut microbes associated with liver diseases.","authors":"Anissa Idrissa Abdoulaye, Babacar Mbaye, Reham Magdy Wasfy, Louis Carmarans, Mamadou Beye, Claudia Andrieu, Sofiane Bakour, Aïcha Hamieh, Nicholas Armstrong, Patrick Borentain, Fadi Bittar, Stéphane Ranque, Jean-Marc Rolain, Gregory Dubourg, Jean-Christophe Lagier, Maryam Tidjani Alou, René Gerolami, Matthieu Million","doi":"10.1080/29933935.2026.2664983","DOIUrl":"10.1080/29933935.2026.2664983","url":null,"abstract":"<p><p>Endogenous ethanol (EtOH) production is a newly identified pathophysiological mechanism involved in metabolic dysfunction-associated steatohepatitis (MASH) and liver disease associated with hepatitis B virus (HBV). Therefore, the characterization of EtOH-producing species associated with liver disease could contribute to the development of gut microbiota-targeted approaches. We investigated EtOH production and tolerance, antimicrobial susceptibility and antimicrobial resistance gene(s) in 33 strains isolated in previous culturomics studies and belonging to species enriched in MASH, alcoholic hepatitis (AH) and HBV patients. <i>Enterocloster clostridioformis</i>, <i>Thomasclavelia ramosa</i> and <i>Peptinophilus grossensis</i> were identified as new EtOH-producing species associated with liver diseases. A strong association between EtOH tolerance and production was detected (<i>p</i> < 0.05). Yeast, <i>Enterocloster</i> species (strictly anaerobic bacteria) and <i>Limosilactobacillus fermentum</i> produced the highest concentrations of EtOH (0.8 to 3.3 g/L). The poorly absorbed drugs, amphotericin B, rifaximin and vancomycin together showed high <i>in vitro</i> susceptibility. Furthermore, <i>E. clostridioformis</i> EC38 harbored the <i>vanB</i> operon. New EtOH-producing species associated with liver diseases were identified thanks to culturomics. Notably, most of them are anaerobic bacteria. These findings underscore the need to further investigate anaerobic gut microbiota species enriched in liver diseases with the aim of developing gut microbiota-targeted therapies.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2664983"},"PeriodicalIF":0.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147825599","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":"Capturing static and dynamic dietary patterns for human gut microbiome research: a conceptual framework.","authors":"Julia S Oliveira, Kathyrn S Keim, Richard Evans, Jonathan Kurasch, Cyrus Jahansouz, Levi M Teigen, Annie W Lin","doi":"10.1080/29933935.2026.2665578","DOIUrl":"10.1080/29933935.2026.2665578","url":null,"abstract":"<p><p>There is inconsistency in the evidence regarding the effects of food on the gut microbiome. These inconsistencies arise, in part, from substantial inter- and intraindividual variations in diet. The wide range of foods consumed directly influences substrate availability for the microbiota. By categorizing foods into broad groups and overlooking interactions among food constituents within individual foods, current dietary pattern approaches can obscure food-specific differences needed to understand dietary effects. Differences in habitual and occasional intake further complicate analyses since frequency of food consumption can produce different gut microbiota responses within the same individual. Flexible analytical approaches are needed to capture within-individual food intake frequency and food-specific effects. To address these challenges, this narrative review presents dietary pattern concepts that distinguish static (stable or consistent) and dynamic (fluctuating or episodic) intake of specific foods at the individual level. We performed a literature search in three databases, including Medline, CINAHL, and PsycINFO, to retrieve relevant articles that distinguish the concepts of \"core foods\" and \"secondary foods\" in population-level studies. We adapt these concepts to a microbiome context at the individual level and propose future directions for studies investigating the impact of diet on the gut microbiome.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2665578"},"PeriodicalIF":0.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134412/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147825548","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":"Development of a monoclonal antibody-based approach for selective enrichment of target <i>Bifidobacterium longum</i> from a complex fecal community.","authors":"Gaku Nakato, Hikaru Inoue, Satoshi Onawa, Risako Furukawa, Nozomu Obana, Kazuki Tanaka, Hitosi Agematu, Isaiah Song, Joe Inoue, Shinji Fukuda","doi":"10.1080/29933935.2026.2663732","DOIUrl":"10.1080/29933935.2026.2663732","url":null,"abstract":"<p><p>Individual differences in gut microbiota composition highlight the need for methods capable of selectively enriching host-associated bacteria from complex microbial communities. Conventional cultivation approaches lack the precision required for targeted enrichment, limiting progress in personalized microbiome research. Here, we established a proof-of-concept monoclonal antibody-based strategy for the selective enrichment of a target gut bacterium. We generated a monoclonal antibody (8H2) exhibiting preferential reactivity toward the human-derived <i>Bifidobacterium longum</i> Jih1 and demonstrated that it selectively enriched viable Jih1 cells from a defined bacterial consortium and a human fecal sample. Proteomic and genetic analyses suggested that 8H2 recognizes glutamine synthetase (GS), an enzyme typically localized intracellularly, but detected on the surface of Jih1 cells. This surface association enables antibody binding and facilitates selective enrichment within complex microbial communities. These data support the feasibility of antibody-based, selective enrichment of viable bacteria and suggest potential applications for monitoring individual-associated bacteria in personalized nutrition and microbiome-based interventions.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2663732"},"PeriodicalIF":0.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147825606","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":"The role of gut microbiome in the pathophysiology of PTSD, depression, and anxiety disorders.","authors":"Nto Johnson Nto, Walter Pirovano, Kristien Nel Van Zyl, Stefanie Malan-Müller, Emma Koch, Matsepo Ramaboli, Dineo Madikgetla, Christiaan de Leeuw, Christopher A Lowry, Sian Megan Joanna Hemmings","doi":"10.1080/29933935.2026.2654224","DOIUrl":"10.1080/29933935.2026.2654224","url":null,"abstract":"<p><p>Posttraumatic stress disorder (PTSD), depression, and anxiety disorders are prevalent and often overlapping mental health conditions with complex, multifactorial etiologies. Growing evidence implicates the gut microbiome in their pathophysiology through immune modulation, neurotransmitter regulation, and bidirectional gut-brain signaling. Findings remain fragmented and difficult to reconcile due to differences in study populations, clinical contexts, and analytic methods. This structured narrative review synthesizes current evidence on gut microbial alterations in PTSD, depression, and anxiety, while examining methodological sources of heterogeneity. We searched four databases: PubMed, Scopus, Web of Science, and PsycINFO, and identified 64 eligible studies assessing the gut microbiome composition in these disorders. Sample sizes ranged from small, exploratory cohorts (≈20 participants) to large population-based datasets (>1000 participants), with most studies conducted in China. Stool sampling and DNA extraction protocols varied widely, although 16S rRNA gene amplicon sequencing of the V3-V4 region on Illumina platforms predominated. Alpha-diversity results were inconsistent, whereas beta-diversity analyses distinguished cases from controls. Across these disorders, alterations in microbial composition was observed, including enrichment of proinflammatory and depletion of beneficial bacterial taxa. The current findings indicate that that the gut microbiome represents a promising avenue for biomarker discovery and therapeutic innovation.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2654224"},"PeriodicalIF":0.0,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13085948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147725264","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":"Drug-microbiome interactions: What we know and why predictive translation remains elusive.","authors":"Fatima C Pereira, Sahar El Aidy","doi":"10.1080/29933935.2026.2649166","DOIUrl":"10.1080/29933935.2026.2649166","url":null,"abstract":"<p><p>Medication-induced alterations of the gut microbiome influence drug efficacy, toxicity, and long-term outcomes. Despite extensive evidence for drug-microbe interactions, predictive translation into clinical practice remains limited. Generalization from shifts in taxonomic profiles, mechanistic studies or isolated enzymatic assays is challenging because microbial activity is highly context-dependent. Drug-microbiome interactions are shaped by host factors including pH, transit time, nutrient and cofactor availability, and spatial organization along the gastrointestinal tract. Here, we argue that predictive translation requires measuring functional outputs, site-specific activity, ecological interactions, and host-contextual modulation, rather than static microbial properties.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2649166"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13048560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624877","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":"Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling.","authors":"Maria A Barrera-Suarez, Conan Y Zhao, Lioudmila V Karnatovskaia, Jaeyun Sung","doi":"10.1080/29933935.2026.2650247","DOIUrl":"10.1080/29933935.2026.2650247","url":null,"abstract":"<p><p>Diet-gut microbiome interactions drive substantial inter-individual variability in metabolic responses to food, a fact that challenges the efficacy of uniform dietary recommendations. To address this complexity, advances in multi-omics profiling, dietary assessment technologies, and host clinical phenotyping now generate high-resolution multimodal datasets. However, managing these vast amounts of data necessitates the integration of artificial intelligence (AI) and machine learning (ML) approaches. In this review, we first delineate the multimodal data landscape and its associated computational workflows. These range from the initial preprocessing of heterogeneous inputs (filtering, normalization, dimensionality reduction) to ML modeling strategies designed to address high dimensionality, sparsity, and compositionality through feature engineering and regularization. We then summarize core ML applications, including the classification of habitual dietary patterns from microbiome signatures, prediction of postprandial metabolic responses, responder stratification, and <i>in silico</i> simulation of dietary perturbations. Furthermore, recent randomized controlled trials demonstrate the tangible clinical potential of AI-guided personalization. Next, we highlight composite microbiome health metrics and diet-specific indices, such as GMWI2 and DI-GM. These tools are essential because they condense high-dimensional taxonomic profiles into interpretable wellness scores for monitoring diet-induced shifts. We subsequently examine genome-scale metabolic models and microbiome \"digital twins\" that mechanistically link dietary substrates to community metabolism and host-relevant metabolites. We also discuss emerging hybrid AI-mechanistic frameworks that enhance interpretability, biological plausibility, and scalability. Finally, we outline translational priorities-including the development of diverse longitudinal cohorts, standardized benchmarking, and clinically trustworthy AI-that are required to realize equitable, microbiome-informed precision nutrition.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2650247"},"PeriodicalIF":0.0,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13048606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624870","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":"Cafeteria diet exposure, and not weight gain propensity, impacts gut microbiota of rats - a within laboratory meta-analysis.","authors":"Shyam Prakaash Bhagavata Srinivasan, Michael D Kendig, Kyoko Hasebe, Nadeem O Kaakoush, Margaret J Morris, Sarah-Jane Leigh","doi":"10.1080/29933935.2026.2649442","DOIUrl":"10.1080/29933935.2026.2649442","url":null,"abstract":"<p><p>Preclinical studies have implicated the microbiota in body weight control, but its translation to humans remains uncertain, partly owing to methodological variability in assessing the relationship between diet-induced obesity and microbiota composition. We performed an internal meta-analysis to determine whether the propensity for diet-induced obesity, defined by relative weight gain due to a high-fat, high-sugar \"cafeteria\" diet, is associated with changes in microbiota composition. We collated fecal microbiome data from 12 studies using our validated model of diet-induced obesity (208 male and 74 female Sprague-Dawley rats; 3.5-13 weeks of chow (control) or cafeteria diet) and determined whether the alpha diversity and composition of the gut microbiota differed between obese-prone and obese-resistant rats. We found consistent effects of cafeteria diet exposure on the microbiota, with marked changes in overall composition, and reduced microbial richness and evenness. Furthermore, specific obesity-associated microbial genera, such as <i>Bacteroides</i> and <i>Blautia</i>, were enriched by the cafeteria diet. Critically, alpha diversity measures and the gut microbiota composition did not differ between obese-prone and obese-resistant rats in either diet group. Our findings suggest that while the microbiota is substantially altered by cafeteria diet intake, these changes appear unrelated to individual susceptibility to weight gain, highlighting the role of additional host factors in modulating diet-induced obesity.</p>","PeriodicalId":519879,"journal":{"name":"Gut microbes reports","volume":"3 1","pages":"2649442"},"PeriodicalIF":0.0,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13037442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147597452","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}