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Abstract This study investigated the effect of dietary interventions targeting gut microbiota on exercise performance in mice. Analysis of the gut microbiota of individuals with varying levels of physical activity revealed enrichment of Eubacterium rectale and Faecalibacterium prausnitzii in the active population. Through in vitro fecal fermentation experiments, dietary factor combinations that promote the abundance of these bacteria were identified. Dietary interventions, including E. rectale supplementation, FAG combination (gavage of Fructus Arctii extract, Agaricus blazei Murrill polysaccharides, and galactooligosaccharides mixture), and CFG combination (gavage of curcumin, Fructus Arctii extract, and galactooligosaccharides mixture), significantly improved mouse exercise performance, increased glycogen accumulation, regulated serum biochemical parameters, and increased short‐chain fatty acid and fatty acid amide levels in feces. Metagenomic sequencing revealed alterations in the composition of the gut microbiota. Fecal metabolome analysis highlighted changes in metabolites related to lipids, organic acids, nucleic acids, and carbohydrates. These findings suggest that E. rectale and dietary interventions positively affect exercise performance by modulating the gut microbiota and associated metabolites.

Abstract Disruption of the bone metabolic balance with advancing age leads to an escalating prevalence of bone‐related diseases, significantly compromising individuals’ quality of life. The gut microbiota actively participates in the regulation of bone metabolism, and perturbations in the gut microbiota can exacerbate bone diseases by compromising gut barrier integrity. Determining the microbial taxa involved in bone loss could offer valuable insights into the development of alternative therapies and nutritional interventions for disease management. Therefore, based on metagenomic and 16S ribosomal RNA data, this study analyzed the gut microbiota structure of 488 individuals with different bone masses (NC, normal; ON, osteopenia; OP, osteoporosis) to identify significant associations between the gut microbiota and bone loss. The results showed that at the genus and species levels, the microbiota diversity of the ON population increased, whereas that of the OP population decreased. Bacteroides were significantly enriched in the OP population, whereas the beneficial bacteria Bifidobacterium, Akkermansia, and lactobacilli decreased. Subsequent analyses revealed no significant variation in different bone populations in terms of Bifidobacterium levels, whereas lactobacilli exhibited diverse responses across distinct bone populations. The administration of lactobacilli effectively enhanced lumbar spine bone mineral density and modulated the gut microbiota structure in a population with unhealthy bone mass. This study contributes to the validation of the association between the gut microbiota and bone mass, enhances our understanding of the potential impact of probiotics (lactobacilli) on bone mass, and establishes a robust scientific basis for the application of probiotics in the regulation of bone mass.

Abstract Prevotella copri, which is divided into four clades, exerts bidirectional effects on host health. These effects include positive improvements in the allergy response and insulin sensitivity. However, P. copri sometimes has adverse effects on host health, and it has been found to be positively correlated with inflammation, insulin resistance, and diarrhea. The interaction between P. copri and these diseases is influenced by the host's diet. The capacity of P. copri to metabolize dietary glycans, as well as the effects of its degradation products, such as short‐chain fatty acids and succinic acid, appear to underlie its dual impact on the host. This duality suggests that manipulating the host's diet to increase the abundance of P. copri may be an effective strategy to improve disease outcomes. Here, we illustrate the characteristics and genetic traits of P. copri related to dietary metabolism are and summarize the health effects of P. copri on the host and methods to regulate its abundance, thus providing suggestions for the development and practical application of P. copri.

Cathartic colon (CC), a form of constipation induced by the chronic abuse and dependence on stimulant laxatives. The application of probiotics to alleviate related diseases has become the research hotspot. In this study, a CC model was constructed by intragastric administration of senna extract, and Lactobacillus paracasei CCFM1164 was used as a positive control to screen strains that can alleviate this constipation. The findings indicate that Lactobacillus paracasei FZJJH2L6 effectively mitigates cathartic colon. The potential mechanisms were explored from the perspectives of enteric nerve repair and intestinal barrier restoration. Results demonstrated that Lactobacillus paracasei FZJJH2L6 increased the content of propionic acid in feces by increasing the relative abundance of short-chain fatty acids-producing bacteria. This upregulated acetylcholine and 5-hydroxytryptamine levels in the colon, reduced intestinal inflammation, repaired the intestinal mechanical barrier, and ultimately alleviated CC. This study provides a theoretical basis for the use of probiotics in alleviating cathartic colon.

Lactic acid bacteria derived extracellular vesicles (LAB-EVs) are nano-sized and carry a variety of biological cargoes. LAB-EVs have proven to be potential mediators of intercellular communication, serving not only the parental bacteria but also the host cell in both physiology and pathology. LAB-EVs are therapeutically beneficial in various diseases through a cell-free strategy. Particularly, EVs secreted from probiotics can exert health-promoting effects on humans. Additionally, the excitement around LAB-EVs has extended to their use as nano-sized drug carriers, since they can traverse biological barriers. Nevertheless, significant challenges in terms of isolation, characterization, and safety must be addressed to ensure the clinical application of LAB-EVs. Therefore, this review emphasizes the isolation and purification methods of LAB-EVs. We also introduce the biogenesis, cargo sorting, and functions of LAB-EVs. The biological regulatory factors of LAB-EVs are summarized and discussed. Special attention is given to the interaction between LAB-EVs and the host, their ability to maintain intestinal homeostasis, and the immunity and inflammation they induce in diverse diseases. Furthermore, we summarize the characterization of LAB-EV cargoes by advanced analytical methods such as proteomics. Finally, we discuss the challenges and opportunities of LAB-EVs as a means of diagnosis and treatment in clinical translation. In conclusion, this review scrutinizes current knowledge and provides guidelines for proposing new perspectives for future research in the field of LAB-EVs.

ABSTRACTAge-related changes in the microbiome have been reported in previous studies; however, direct evidence for their association with frailty is lacking. Here, we introduce biological age based on gut microbiota (gAge), an integrated prediction model that integrates gut microbiota data from different perspectives with potential background factors for aging assessment. Simulation results show that, compared with a single model, the ensemble model can not only significantly improve the prediction accuracy, but also make full use of the data in unpaired samples. From this, we identified markers associated with age development and grouped markers into accelerated aging and mitigated aging according to their effect on the prediction. Importantly, the application of gAge to an elderly cohort with different frailty levels confirmed that gAge and its predictive residuals are closely related to the individual’s health status and frailty stage, and age-related markers overlap significantly with disease and frailty characteristics. Furthermore, we applied the gAge prediction model to another independent cohort of the elderly population for aging assessment and found that gAge could effectively represent the aging population. Overall, our study explains the association between the gut microbiota and frailty, providing potential targets for the development of gut microbiota-based targeted intervention strategies for aging.

ABSTRACTBifidobacterium longum subsp. infantis is a prevalent member of the gut microbiota of breastfed infants. In this study, the effects of human breastmilk-derived B.longum subsp. infantis CCFM1269 on bone formation in developing BALB/c mice were investigated. Newborn female and male mice were assigned to control group (administered saline), CCFM1269 group (administered B. longum subsp. infantis CCFM1269, 1 × 109 CFU/mouse/day) and I5TI group (administered B. longum subsp. infantis I5TI, 1 × 109 CFU/mouse/day) from 1-week-old to 3-, 4- and 5-week old. B. longum subsp. infantis I5TI served as a negative control in this study. The results demonstrated that B. longum subsp. infantis CCFM1269 promoted bone formation in growing mice by modulating the composition of the gut microbiota and metabolites. The expression of genes and proteins in the PI3K/AKT pathway was stimulated by B. longum subsp. infantis CCFM1269 through the GH/IGF-1 axis in growing mice. This finding suggests B. longum subsp. infantis CCFM1269 may be useful for modulating bone metabolism during growth.

Abstract Throughout the life span of a host, bifidobacteria have shown superior colonization and glycan abilities. Complex glycans, such as human milk oligosaccharides and plant glycans, that reach the colon are directly internalized by the transport system of bifidobacteria, cleaved into simple structures by extracellular glycosyl hydrolase, and transported to cells for fermentation. The glycan utilization of bifidobacteria introduces cross-feeding activities between bifidobacterial strains and other microbiota, which are influenced by host nutrition and regulate gut homeostasis. This review discusses bifidobacterial glycan utilization strategies, focusing on the cross-feeding involved in bifidobacteria and its potential health benefits. Furthermore, the impact of cross-feeding on the gut trophic niche of bifidobacteria and host health is also highlighted. This review provides novel insights into the interactions between microbe-microbe and host-microbe.

Abstract The increasing incidence of autism spectrum disorder (ASD) worldwide poses serious social and family problems. Various risk factors for ASD are gradually being recognized, and there are also various options for the treatment of ASD. It is worth noting that dietary interventions have been shown to have a positive effect in terms of mitigating and preventing some psychiatric disorders, such as epilepsy, Parkinson's disease, and ASD, and they are gradually receiving attention as a safe adjuvant treatment. In this review, based on the current understanding of the pathogenic factors and intervention strategies for ASD, different dietary patterns that can be selected for children with ASD are discussed in depth. Moreover, a review was conducted on the use of dietary factors, such as natural products from food sources, prebiotics, and probiotics, as effective supplements to existing dietary patterns. As increasing evidence shows that maternal risk factors, such as obesity, diabetes, and hypertension, are associated with an increased risk of ASD in offspring, dietary suggestions are also made for pregnant woman with ASD‐related risk factors to counteract the impact of these risk factors. With compensation from food‐derived natural products, prebiotics, and probiotics, suitable dietary patterns can further enhance the effectiveness of dietary interventions for ASD. In addition, dietary recommendations for pregnant woman may reduce the potential impact of obesity, diabetes, and hypertension and may help to prevent the occurrence of ASD to the maximum extent possible.

Abstract Purpose The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa. Material and Methods A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic. Results The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively. Conclusions MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.

Objective To explore the therapeutic effect of levosimendan in patients with prolonged ventilator weaning and cardiac dysfunction. Method Patients with prolonged ventilator weaning and cardiac dysfunction were randomly allocated to receive conventional treatment (control group) or intravenous infusion of levosimendan for 24 h based on conventional treatment (levosimendan group). Weaning success rates were then compared between the two groups. The study was retrospectively registered with Research Registry (ID No. researchregistry10304). Results A total of 40 patients were included (20 per group). Within 3 days after initiation of treatment, significantly more cases were successfully weaned in the levosimendan group versus control group (eight versus four cases, respectively). Among the eight patients who underwent pulse indicator continuous cardiac output monitoring in the levosimendan group, the global ejection fraction increased 24 h after treatment, and the cardiac function index and cardiac index increased 72 h after treatment. Conclusion For patients requiring prolonged mechanical ventilation who have concomitant cardiac dysfunction, levosimendan may be considered to increase the probability of weaning success.

Abstract O‐glycosylation is an ancient yet underappreciated protein posttranslational modification, on which many bacteria and viruses heavily rely to perform critical biological functions involved in numerous infectious diseases or even cancer. But due to the innate complexity of O‐glycosylation, research techniques have been limited to study its exact role in viral attachment and entry, assembly and exit, spreading in the host cells, and the innate and adaptive immunity of the host. Recently, the advent of many newly developed methodologies (e.g., mass spectrometry, chemical biology tools, and molecular dynamics simulations) has renewed and rekindled the interest in viral‐related O‐glycosylation in both viral proteins and host cells, which is further fueled by the COVID‐19 pandemic. In this review, we summarize recent advances in viral‐related O‐glycosylation, with a particular emphasis on the mucin‐type O‐linked α‐N‐acetylgalactosamine (O‐GalNAc) on viral proteins and the intracellular O‐linked β‐N‐acetylglucosamine (O‐GlcNAc) modifications on host proteins. We hope to provide valuable insights into the development of antiviral reagents or vaccines for better prevention or treatment of infectious diseases.

Akkermansia muciniphila play an important in ameliorating obesity but is not allowed for direct consumption in most countries. To date, microbiota-directed foods selectively promote the targeted human gut microbes, providing a strategy for A. muciniphila enhancement. Multiple studies have indicated the potential regulation of the polyphenol on A. muciniphila. Therefore, a polyphenol screening based on A. muciniphila upregulation was performed in mice. Chlorogenic acid (CGA) exhibited a greater response to A. muciniphila upregulation. Furthermore, we found that CGA did not directly promote A. muciniphila growth or mucin secretion. Microbiome and metabolomics revealed that the increased abundance of A. muciniphila resulted from the inhibition of CGA on Desulfovibrio and Alistipes and the influence of docosahexaenoic acid, β-hydroxybutyrate, and N-acetyl-lactosamine. Finally, to confirm the regulation of CGA on A. muciniphila under disease conditions, high-fat diet-fed mice were established. The results showed CGA promoted A. muciniphila growth, and we expectedly found that CGA suppressed the augment in body weight of mice, significantly attenuated adipose tissue abnormality, provided liver protection and improved gut barrier integrity. These results suggest that CGA inhibits the development of obesity. Overall, our results indicate that microbiota-directed food is a promising approach for the treatment of obesity.

Abstract Bifidobacteria are key gut commensals that confer various health benefits and are commonly used as probiotics. However, little is known about the population-level variation in gut bifidobacterial composition and its affecting factors. Therefore, we analyzed Bifidobacterium species with amplicon sequencing of the groEL gene on fecal samples of 1674 healthy individuals, who belonged to eight ethnic groups and resided in 60 counties/cities of 28 provinces across China. We found that the composition of the bifidobacterial community was associated with geographical factors, demographic characteristics, staple food type, and urbanization. First, geography, which reflects a mixed effect of other variables, explained the largest variation in the bifidobacterial profile. Second, middle adolescence (age 14–17) and age 30 were two key change points in the bifidobacterial community development, and a bifidobacterial community resembling that of adults occurred in middle adolescence, which is much later than the maturation of the whole gut microbial community at approximately age 3. Third, each ethnicity showed a distinct bifidobacterial profile, and the remarkable amount of unknown Bifidobacterium species in the Tibetan gut suggested undiscovered biodiversity. Fourth, wheat as the main staple food promoted the flourish of B. adolescentis and B. longum. Fifth, alpha diversity of the bifidobacterial community decreased with urbanization. Collectively, our findings provide insight into the environmental and host factors that shape the human gut bifidobacterial community, which is fundamental for precision probiotics.

Abstract Background Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. Methods We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. Results NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). Conclusions By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace

Stachyose is a prebiotic that traditionally extracted from plants, such as vegetable. It has been demonstrated to alleviate intestinal inflammation by regulating gut microbiota, but the mechanism has been unclear. This research aims to detect the potential mechanism of stachyose in alleviating the severity of ulcerative colitis (UC). The results indicated that the administration of stachyose could recover the body weight, protect against the colonic tissue damage, reduce the pro-inflammatory cytokines levels, and reverse the histological abnormalities in UC mice. Oral stachyose could restore DSS-induced disturbance in intestinal bacteria. Besides, the metabolome result of serum samples showed that stachyose treatment significantly altered serum metabolites against inflammatory responses in colitis mice. Also, a significant correlation can be found between 23 metabolite biomarkers and 18 differential genera. Our results provided a strong foundation for the future study of the protective role of stachyose in maintaining intestinal homeostasis.

Influenza and other respiratory infections cause annual epidemics worldwide, with high incidence and mortality rates reported among immunocompromised infants and elderly individuals. Probiotics can modulate the immune system through their bacterial compositions and metabolites, affecting influenza infections and effectively responding to viral mutations. Therefore, we evaluated the anti-influenza effects of mixed probiotics administered orally before and after influenza infection. The results showed that the mixed probiotics consisting of Lacticaseibacillus rhamnosus CCFM1279, Limosilactobacillus reuteri CCFM1145, and Lacticaseibacillus casei CCFM1127 inhibited viral replication and reduced lung inflammatory damage against influenza. In addition, the mixed-probiotics treatment activated the systemic immune response of the host. The gut microbiota analysis revealed a notable increase in the abundance of Alistipes and Rikenella following mixed-probiotic supplementation. The metabolomic analysis indicated a significant increase in adenosine levels, which was positively correlated with the abundance of Parvibacter. These findings highlight the effectiveness of mixed probiotics in fighting influenza viruses and suggest that certain gut microbiota and their metabolites may play a significant role in influencing the outcomes of influenza infections.

The mechanism of metabolites produced by lactic acid bacteria in mediating microbial interactions has been difficult to ascertain. This study comparatively evaluated the antimicrobial effect of the novel bacterium Pediococcus acidilactici CCFM18 and explored the global chemical view of its interactions with indicator bacteria. P. acidilactici CCFM18 had sufficiently strong antimicrobial activity to effectively inhibit the growth of the indicator bacteria and enhance their intracellular reactive oxygen species (ROS) level. The emerging technique of matrix-assisted laser desorption ionization–time-of-flight (MALDI-TOF) imaging mass spectrometry indicated that P. acidilactici CCFM18 increased the production of pediocin PA-1 and the penocin A profile during its interaction with the indicator bacteria, thus differing from P. acidilactici CCFM28 (a commonly used laboratory strain). Strikingly, the production of coagulin A was triggered only by signaling molecules made by the competing strain L. thermophilus, suggesting an idiosyncratic response from P. acidilactici CCFM18. Bioinformatic mining of the P. acidilactici CCFM18 draft genome sequence revealed gene loci that code for the complex secondary metabolites analyzed via MSI. Taken together, these results illustrate that chemical interactions between P. acidilactici CCFM18 and indicator bacteria exhibit high complexity and specificity and can drive P. acidilactici CCFM18 to produce different secondary metabolites.

An increasing number of studies have indicated that gut microbiota and its metabolites are crucial in the development of hyperlipidemia. Bifidobacterium longum (B. longum) CCFM1077 has been shown to have lipid-lowering effects in animals. This study aimed to evaluate the potential of B. longum CCFM1077 in lowering the lipid levels in patients with hyperlipidemia and investigate the effect of this bacterium on serum lipid abnormalities, gut microbiota, and fecal metabolites in these patients. This study was a six-week, randomized, double-blind, and placebo-controlled pilot clinical trial. Subjects with hyperlipidemia (N = 62) were randomly assigned to receive placebo (N = 31) or B. longum CCFM1077 (1 × 1010 colony-forming units (CFUs) per day; N = 31). Serum lipid levels including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), total triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) were examined at the baseline and interventional endpoints. Changes in the gut microbiota composition and diversity were measured based on 16S ribosomal RNA (rRNA) sequencing of the V3–V4 region at the end of the intervention period. Non-targeted metabolomics of the feces was performed using ultra-performance liquid chromatography (UPLC)-Q-Exactive Orbitrap/mass spectrometer. Oral administration of B. longum CCFM1077 for six weeks significantly decreased the serum levels of TC (p

Abstract Nucleotides ingested from breast milk and complementary foods during infancy play a vital role in the development of the immune and nervous system, as well as the maturation of gut function, and are considered a “special dietary nutrient.” Based on the existing research progress and theoretical basis, this review takes the distribution of dietary nucleotides (NTs) in the early life (after birth to the age of 3 years) diet and the in vivo metabolism/absorption process as the starting point and expounds on its potential impact and mechanism of action on early gastrointestinal and brain development. With the understanding of gut microbiota (GM), the interaction between dietary factors and GM has become a focus of food research. It is of great significance to reexamine the biological effects of early dietary nucleotide intake on infant gut–brain development from the perspective of the GM–gut–brain axis. This paper reveals the potential relationship between the NTs–GM–gut–brain axis and provides new ideas and theories for the research and application of NTs in the field of infant nutrition.

Abstract Bone loss caused by microgravity severely damages the health of astronauts; however, no effective countermeasures exist. Microalgae are microscopic algae rich in protein, polysaccharide, and other nutrients, which can provide astronauts with safe food and oxygen supply in the space ecosystem. Recent studies have demonstrated that microalgae can potentially reduce bone loss in primary osteoporosis. Here, a hindlimb suspension (HLS) mouse (C57BL/6J) model was used to investigate the potential effects of five different microalgae in preventing microgravity‐induced bone loss. The results showed that long‐term administration of 300 mg/kg body weight/day Spirulina platensis (SP) significantly reduced bone loss and increased trabecular number and bone strength. In addition, mice in the HLS group also exhibited disordered gut microbiota with increased Firmicutes/Bacteroidetes, decreased fecal short‐chain fatty acids levels, and increased levels of colonic proinflammatory cytokines interleukin‐6 and tumor necrosis factor‐α. To a certain extent, SP reduced these changes and maintained homeostasis of the intestinal environment. These results suggest that SP has a potential enhancing effect on resistance to bone loss in HLS mice.

Akkermansia muciniphila, one of the most promising next-generation probiotics, was reported to exhibit beneficial modulatory effects on the gut barrier. However, the strain-specific and underlying regulatory mechanisms of this species on gut barrier function were not well studied. Therefore, this study evaluated the protective effect of A. muciniphila strains on the intestinal barrier and investigated the mode of action and material basis of this modulatory effect. We first confirmed the strain-specific effects of A. muciniphila on intestinal barrier regulation and found that this phenomenon may be explained by the different abilities of strains to affect tight junction protein expression in enterocytes. Comparative genomic analysis proved that the ability of A. muciniphila to regulate the intestinal barrier was exerted in part by the functional genes (such as COG0438, COG0463, and COG2244) related to the synthesis of cellular surface proteins. The role of these surface proteins in intestinal barrier regulation was further verified by strain-comparative experiments in animal and cell models and surface protein removal trials. This study confirmed the different effects of A. muciniphila strains on gut barrier modulation and provided molecular and genetic targets for the screening of A. muciniphila strains with superior protection against gut barrier dysfunction.

Abstract Background The gut microbiome is closely associated with health status, and any microbiota dysbiosis could considerably impact the host’s health. In addition, many active consortium projects have generated many reference datasets available for large-scale retrospective research. However, a comprehensive monitoring framework that analyzes health status and quantitatively present bacteria-to-health contribution has not been thoroughly investigated. Methods We systematically developed a statistical monitoring diagram for personalized health status prediction and analysis. Our framework comprises three elements: (1) a statistical monitoring model was established, the health index was constructed, and the health boundary was defined; (2) healthy patterns were identified among healthy people and analyzed using contrast learning; (3) the contribution of each bacterium to the health index of the diseased population was analyzed. Furthermore, we investigated disease proximity using the contribution spectrum and discovered multiple multi-disease-related targets. Results We demonstrated and evaluated the effectiveness of the proposed monitoring framework for tracking personalized health status through comprehensive real-data analysis using the multi-study cohort and another validation cohort. A statistical monitoring model was developed based on 92 microbial taxa. In both the discovery and validation sets, our approach achieved balanced accuracies of 0.7132 and 0.7026, and AUC of 0.80 and 0.76, respectively. Four health patterns were identified in healthy populations, highlighting variations in species composition and metabolic function across these patterns. Furthermore, a reasonable correlation was found between the proposed health index and host physiological indicators, diversity, and functional redundancy. The health index significantly correlated with Shannon diversity ( $$\rho = 0.07$$ ρ = 0.07 ) and species richness ( $$\rho = 0.44$$ ρ = 0.44 ) in the healthy samples. However, in samples from individuals with diseases, the health index significantly correlated with age ( $$\rho = 0.12$$ ρ = 0.12 ), species richness ( $$\rho = 0.46$$ ρ = 0.46 ), and functional redundancy ( $$\rho = - 0.16$$ ρ = - 0.16 ). Personalized diagnosis is achieved by analyzing the contribution of each bacterium to the health index. We identified high-contribution species shared across multiple diseases by analyzing the contribution spectrum of these diseases. Conclusions Our research revealed that the proposed monitoring framework could promote a deep understanding of healthy microbiomes and unhealthy variations and served as a bridge toward individualized therapy target discovery and precise modulation. Video Abstract

This meta-analysis of randomized controlled trials aimed to evaluate the effects of probiotic supplementation on glucose homeostasis in patients with polycystic ovary syndrome (PCOS). The meta-analysis was performed in accordance with the Cochrane Handbook guidelines and relevant the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement criteria. Of 825 identified reports, 11 randomized clinical trials were included in the meta-analysis. An analysis of pooled extracted data revealed that supplementation with probiotics significantly decreased fasting blood glucose (FBG, n = 7; standardized mean difference (SMD) = −0.40; 95 % confidence interval (CI): −2.02, −0.02; P = 0.04) and insulin levels (n = 6; SMD = −0.57; 95 % CI: −0.89, −0.25; P = 0.0004) and the homeostatic model assessment of insulin resistance (n = 7; SMD = −0.64; 95 % CI: −0.96, −0.31; P = 0.0001) while increasing the quantitative insulin sensitivity check index (QUICKI, n = 5; SMD = 0.58; 95 % CI: 0.08, 1.09; P = 0.02) in patients with PCOS. The FBG-reducing effect decreased as the baseline body mass index (BMI) and mean age of the participants increased. Indeed, a greater number of bacterial species and a higher bacterial dose were shown to reduce QUICKI effectively. The systematic review indicated that probiotic supplementation may help to control glucose homeostasis in adults with polycystic ovarian syndrome.

This study aims to integrate research in the field of aerobics and mental health through the visualization analysis method of the CiteSpace map, to clarify the impact of aerobics on mental health and stress levels. Firstly, based on the literature method, pieces of literature related to aerobics and mental health are searched and collected. Secondly, the visualization analysis method of the CiteSpace map is employed to summarize and analyze the contents of the literature, involving statistical analysis of the annual number of publications, analysis of author characteristics, and analysis of publishing institution characteristics. In addition, keyword co-occurrence analysis and keyword cluster analysis are also conducted in related research fields. Among them, the Log-Likelihood Ratio is used in keyword cluster analysis. Finally, the results are analyzed using the visualization analysis method of the CiteSpace map and the statistics-based comprehensive results. The results demonstrate that in the recent 20 years, the average annual number of articles in related fields exceeds 190. The high-yield authors are distributed in economically developed areas, and the cooperation among authors is scattered. In the keyword clustering results, a total of 77 cluster labels are obtained. The Q value of the clustering module is 0.89, and the average clustering profile silhouette (S) value is 0.92, indicating that the clustering structure is significant and the results are reasonable. The aerobics cluster contains the most closely related keywords, covering mental health and stress levels. Data analysis based on existing studies reveals that aerobics has a significant impact on mental health and stress levels. Individuals participating in aerobics show obvious improvement in mental health inventory (MHI) scores (t(100) = 4.32, p

Abstract Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a ‘poor man’s crop’, finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

Recent studies have revealed the potency of probiotics in alleviating metabolic diseases associated with intestinal barrier dysfunction. However, an efficient model for screening probiotic strains against specific metabolic diseases has not been well developed. In the present study, a Caco-2 cell monolayer membrane model treated with tumor necrosis factor (TNF)-α or alcohol was used to evaluate the effect of 139 Lactobacillus strains on intestinal barrier function in vitro. We then selected 11 Lactobacillus strains with different regulatory abilities on the gut barrier to determine their effect against ovariectomy-induced osteoporosis or chronic alcoholic liver injury in vivo. Our results showed that the Pearson coefficient between the data of cell and animal models were 0.82 and −0.97 for the protection of probiotics against osteoporosis and alcoholic liver disease, respectively, suggesting the reliability of the cell model to simulate the in vivo protective effects of probiotics. This study established a potential in vitro approach based on a Caco-2 cell monolayer membrane model for the efficient screening of potential probiotics against specific metabolic diseases such as osteoporosis and chronic alcoholic liver disease.

Human milk oligosaccharides (HMO) that promote the growth of beneficial gut microbes in infants are abundant in human milk. Streptococcus, one of the dominant genera in human milk microbiota, is also highly prevalent in the infant gut microbiota, possibly due to its adeptness at utilizing HMOs. While previous studies have mainly focused on HMO interactions with gut bacteria like Bifidobacterium and Bacteroides spp., the interaction with Streptococcus spp. has not been fully explored. In this study, Streptococcus spp. was isolated from human milk and identified to exhibit extensive capabilities in utilizing HMOs. Their consumption rates of 2′-fucosyllactose (2′-FL), 6′-sialyllactose (6′-SL), and lacto-N-tetraose (LNT) closely matched those of Bifidobacterium longum subsp. infantis ATCC 15697. Furthermore, we assessed the safety-related genes in the genomes of the Streptococcus species capable of utilizing HMOs, revealing potential virulence and resistance genes. In addition, no haemolytic activity was observed. These findings expand the knowledge of metabolic interactions and networks within the microbiota of human milk and the early life human gut.

Asthma is a prevalent respiratory disease. The present study is designed to determine whether gut microbiota-derived tryptophan metabolites alleviate allergic asthma inflammation in ovalbumin (OVA)-induced mice and explore the effect and potential mechanism therein. Asthma model mice were constructed by OVA treatment, and kynurenine (KYN), indole-3-lactic acid (ILA), in-dole-3-carbaldehyde (I3C), and indole acetic acid (IAA) were administered by intraperitoneal injection. The percent survival, weight and asthma symptom score of mice were recorded. The total immunoglobulin E and OVA-specific (s)IgE in the serum and the inflammatory cytokines in the bronchoalveolar lavage fluid (BALF) were detected by the corresponding ELISA kits. The composition of the gut microbiota and tryptophan-targeted metabolism in mouse feces were analyzed using 16S rRNA gene sequencing and targeted metabolomics, respectively. The four tryptophan metabolites improved the percent survival, weight and asthma symptoms of mice, and reduced the inflammatory cells in lung tissues, especially I3C. I3C and IAA significantly (p < 0.05) downregulated the levels of OVA-IgE and inflammatory cytokines. KYN was observed to help restore gut microbiota diversity. Additionally, I3C, KYN, and ILA increased the relative abundance of Anaeroplasma, Akkermansia, and Ruminococcus_1, respectively, which were connected with tryptophan metabolic pathways. IAA also enhanced capability of tryptophan metabolism by the gut microbiota, restoring tryptophan metabolism and increasing production of other tryptophan metabolites. These findings suggest that tryptophan metabolites may modulate asthma through the gut microbiota, offering potential benefits for clinical asthma management.

ABSTRACTCholestasis is a condition characterized by the abnormal production or excretion of bile, and it can be induced by a variety of causes, the factors of which are extremely complex. Although great progress has been made in understanding cholestasis pathogenesis, the specific mechanisms remain unclear. Therefore, it is important to understand and distinguish cholestasis from different etiologies, which will also provide indispensable theoretical support for the development of corresponding therapeutic drugs. At present, the treatment of cholestasis mainly involves several bile acids (BAs) and their derivatives, most of which are in the clinical stage of development. Multiple lines of evidence indicate that ecological disorders of the gut microbiota are strongly related to the occurrence of cholestasis, in which BAs also play a pivotal role. Recent studies indicate that probiotics seem to have certain effects on cholestasis, but further confirmation from clinical trials is required. This paper reviews the etiology of and therapeutic strategies for cholestasis; summarizes the similarities and differences in inducement, symptoms, and mechanisms of related diseases; and provides information about the latest pharmacological therapies currently available and those under research for cholestasis. We also reviewed the highly intertwined relationship between gut microbiota-BA-cholestasis, revealing the potential role and possible mechanism of probiotics in the treatment of cholestasis.

Abstract Inflammatory bowel diseases (IBDs) are chronic inflammatory diseases of the gastrointestinal tract that have become a global health burden. Studies have revealed that Latilactobacillus sakei can effectively alleviate various immune diseases, including colitis, rheumatoid arthritis, and metabolic disorders. Here, we obtained 72 strains of L. sakei from 120 fermentation and fecal samples across China. In total, 16 strains from different sources were initially screened in an in vitro Caco‐2 model induced by dextran sulfate sodium. Subsequently, six strains (four exhibiting effectiveness and two exhibiting ineffectiveness) were selected for further validation in an in vivo colitis mouse model. The results demonstrated that L. sakei strains exhibited varying degrees of amelioration of the colitis disease process. Notably, L. sakei CCFM1267, the most effective strain, significantly restored colon length and tight‐junction protein expression, and reduced the levels of cytokines and associated inflammatory enzymes. Moreover, L. sakei CCFM1267 upregulated the abundance of Enterorhabdus, Alloprevotella, and Roseburia, leading to increased levels of acetic acid and propionic acid. Conversely, the other four strains (L. sakei QJSSZ1L4, QJSSZ4L10, QGZZYRHMT1L6, and QGZZYRHMT2L6) only exhibited a partial remission effect, while L. sakei QJSNT1L10 displayed minimal impact. Therefore, L. sakei CCFM1267 and QJSNT1L10 were selected for further exploration of the mechanisms underlying their differential mitigating effects. Comparative genomics analysis revealed significant variations between the two strains, particularly in genes associated with carbohydrate‐active enzymes, such as the glycoside hydrolase family, which potentially contribute to the diverse profiles of short‐chain fatty acids in vivo. Additionally, metabolome analysis demonstrated that acetylcholine and indole‐3‐acetic acid were the main differentiating metabolites of the two strains. Therefore, the strains of L. sakei exhibited varying degrees of effectiveness in alleviating IBD‐related symptoms, and the possible reasons for these variations were attributed to discrepancies in the carbohydrate‐active enzymes and metabolites among the strains.

Introduction: Major depressive disorder (MDD) is a leading global psychiatric disease. MDD is highly comorbid with gastrointestinal abnormalities, such as gut motility dysfunction. An effective strategy to manage depression and its accompanying gastrointestinal symptoms is warranted. Objectives: Three probiotic strains (Bifidobacterium breve CCFM1025, Bifidobacterium longum CCFM687, and Pediococcus acidilactici CCFM6432) had previously been validated in mice to possess antidepressant-like potential. This study investigated the potential psychotropic effects of a combined three-strain probiotic intervention for human MDD patients. The mechanism of action was further investigated in the stress-induced depression mice model. Methods: MDD patients were given a freeze-dried, mixed probiotic formula for four weeks. The patients’ psychometric and gastrointestinal conditions were evaluated using clinical rating scales before and after treatment. Their gut microbiome was also analysed using 16S rRNA gene amplicon sequencing. The mechanisms underlying the beneficial probiotic effects were determined using a chronic stress-induced depressive mouse model. Results: Multi-probiotics significantly reduced depression scores, and to a greater extent than the placebo (based on the Hamilton Depression Rating, Montgomery-Asberg Depression Rating, and Brief Psychiatric Rating Scales). Multi-probiotics also significantly improved the patients’ gastrointestinal functions (based on self-evaluation using the Gastrointestinal Symptom Rating Scale). Serotonergic system modification was demonstrated as the key mechanism behind the probiotics’ benefits for the brain and the gut. Conclusion: Our findings suggest a novel and promising treatment to manage MDD and accompanying gut motility problems, and provide options for treating other gut-brain axis-related disorders.

As a large amount of data is increasingly generated from edge devices,such as smart homes,mobile phones,and wearable devices,it becomes crucial for many applications to deploy machine learning modes across edge devices.The execution speed of the deployed model is a key element to ensure service quality.Considering a highly heterogeneous edge deployment scenario,deep learning compiling is a novel approach that aims to solve this problem.It defines models using certain DSLs and generates efficient code implementations on different hardware devices.However,there are still two aspects that are not yet thoroughly investigated yet.The first is the optimization of memory-intensive operations,and the second problem is the heterogeneity of the deployment target.To that end,in this work,we propose a system solution that optimizes memory-intensive operation,optimizes the subgraph distribution,and enables the compiling and deployment of DNN models on multiple targets.The evaluation results show the performance of our proposed system.

Abstract Background The gut microbiome has proven to be an important factor affecting obesity; however, it remains a challenge to identify consistent biomarkers across geographic locations and perform precisely targeted modulation for obese individuals. Results This study proposed a systematic machine learning framework and applied it to 870 human stool metagenomes across five countries to obtain comprehensive regional shared biomarkers and conduct a personalized modulation analysis. In our pipeline, a heterogeneous ensemble feature selection diagram is first developed to determine an optimal subset of biomarkers through the aggregation of multiple techniques. Subsequently, a deep reinforcement learning method was established to alter the targeted composition to the desired healthy target. In this manner, we can realize personalized modulation by counterfactual inference. Consequently, a total of 42 species were identified as regional shared biomarkers, and they showed good performance in distinguishing obese people from the healthy group (area under curve (AUC) =0.85) when demonstrated on validation datasets. In addition, by pooling all counterfactual explanations, we found that Akkermansia muciniphila, Faecalibacterium prausnitzii, Prevotella copri, Bacteroides dorei, Bacteroides eggerthii, Alistipes finegoldii, Alistipes shahii, Eubacterium sp. _CAG_180, and Roseburia hominis may be potential broad-spectrum targets with consistent modulation in the multi-regional obese population. Conclusions This article shows that based on our proposed machine-learning framework, we can obtain more comprehensive and accurate biomarkers and provide modulation analysis for the obese population. Moreover, our machine-learning framework will also be very useful for other researchers to further obtain biomarkers and perform counterfactual modulation analysis in different diseases.

Emerging evidence shows that some Lactobacillus fermentum (L. fermentum) strains can contribute to the prevention and treatment of ulcerative colitis (UC). In this study, 105 isolates of L. fermentum strains were separated from fecal samples of populations in different regions in China and their draft genomes were sequenced. Pan-genomic and phylogenetic characterizations of these strains and four model strains (L. fermentum 3872, CECT5716, IFO3956, and VRI003) were performed. Phylogenetic analysis indicated that there was no significant adaptive evolution between the genomes of L. fermentum strains and the geographical location, sex, ethnicity, and age of the hosts. Three L. fermentum strains (FWXBH115, FGDLZR121, and FXJCJ61) from different branches of the phylogenetic tree and strain type L. fermentum CECT5716 were selected and their anti-inflammatory and immune modulatory activities in a dextran sulphate sodium (DSS)-induced colitis mouse model were further investigated. Both L. fermentum FXJCJ61 and CECT5716 significantly alleviated UC by reducing all colitis-associated histological indices, maintaining mucosal integrity, and stimulating replenishment of short-chain fatty acids (SCFAs), while the other two strains failed to offer similar protection. The anti-inflammatory mechanisms of L. fermentum FXJCJ61 and CECT5716 were related to the inhibition of nuclear factor kappa-B (NF-κB) signaling pathway activation and enhancement of interleukin 10 (IL-10) production. Comparative genomic analysis of these strains identified candidate genes that may contribute to the anti-inflammatory effects of specific L. fermentum strains.

IntroductionThe use of cosmetics has become a habit for women. However, their influence on the microbial diversity of the skin has rarely been studied.MethodsHerein, the effect of cosmetics containing complex polysaccharides on the skin bacterial microbiota of female forehead and cheek areas was analyzed. Eighty volunteers were recruited and split into two groups (40 people each); one group was treated with cosmetics containing complex polysaccharides and the other with basic cream for 28 days. Skin samples were collected using sterilized cotton swabs, and 16S rDNA high-throughput sequencing was used to analyze the changes in skin bacterial microbiota composition before and after the intervention.Results and discussionA total of twenty-four phyla were detected in the forehead and cheek skin samples of 80 volunteers, the top three of which were Proteobacteria, Firmicutes, and Actinobacteria. The main genera of the forehead skin bacterial microbiota were Cutibacterium (11.1%), Acinetobacter (10.4%), Enterococcus (8.9%), Ralstonia (8.8%), and Staphylococcus (8.7%), while those of the cheek skin bacterial microbiota were Staphylococcus (20.0%), Ralstonia (8.7%), Propionibacterium (7.9%), Acinetobacter (7.2%), and Bifidobacterium (6.0%). Compared with basic cream, the use of cosmetics containing complex polysaccharides significantly increased the relative abundance of Staphylococcus and Bacillus in the forehead and cheek and reduced the relative abundance of Propionibacterium and Bifidobacterium. Thus, cosmetics containing complex polysaccharides could modify the composition of skin bacterial microbiota, which may help to maintain stable conditions of the skin.