ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ （AngⅡ） and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment， AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h， and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 （CCK-8） to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay （ELISA） was used to detect the content of B-type natriuretic peptide （BNP） in cell culture supernatant， and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently， the experiment was divided into a blank group （20% blank serum）， a model group （20% blank serum + 5×10^-5 mol·L^-1 AngⅡ）， low-， medium-， and high-dose （5%， 10% and 20%） serum containing Zhenwutang groups， an autophagy inhibitor group （1×10^-4 mol·L^-1 3-MA）， and autophagy inducer group （1×10^-7 mol·L^-1 rapamycin）. The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe （Lyso Tracker） and mitochondrial probe （Mito Tracker） co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect Caspase-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， Bcl-2-related X protein （Bax）， and cytochrome C （Cyt C） in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase （Parkin）， phosphatase and tensin homolog （PTEN）-induced kinase 1 （PINK1）， and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3， cleaved Caspase-9， Bax， Bcl-2， and Cyt C in apoptosis-related pathways， phosphorylated ubiquitin ligase （p-Parkin）， phosphorylated PTEN-induced kinase 1 （p-PINK1）， p62， and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways， and the change of microtubule-associated protein 1 light chain 3 （LC3） Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10^-5 mol·L^-1， the cell activity was the lowest， and there was no cytotoxicity. At this concentration， the surface area of cardiomyocytes was significantly increased （P<0.01）， and the content of BNP in the supernatant of culture medium was significantly increased （P<0.05）. Therefore， AngⅡ with a concentration of 5×10^-5 mol·L^-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group， the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate （P<0.01） and significantly decreased mitochondrial membrane potential （P<0.01）. The results of immunofluorescence co-localization showed that compared with the blank group， the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group， the relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 in the model group was significantly up-regulated （P<0.01）， while the relative mRNA expression of Bcl-2， Parkin， and PINK1 was significantly down-regulated （P<0.01）. In addition， the relative protein expression of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 was significantly up-regulated （P<0.01）. The LC3Ⅱ/Ⅰ was significantly decreased， and the relative protein expression of Bcl-2， p-Parkin， p-PINK1， and Beclin1 was significantly down-regulated （P<0.01）. Compared with the model group， the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate （P<0.01）， and the decrease ratio of mitochondrial membrane potential is significantly lowered （P<0.01） in a dose-dependent manner. Additionally， both red and green fluorescence spots became more in these groups. In the 3-MA group， the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax， Caspase-3， Caspase-9， Cyt C， and p62 was significantly down-regulated （P<0.05， P<0.01）， while that of Bcl-2， Parkin， and PINK1 was significantly up-regulated （P<0.01）. In the serum containing Zhenwutang groups， the relative protein expression levels of Bax， cleaved Caspase-3， cleaved Caspase-9， Cyt C， and p62 were significantly down-regulated （P<0.05，P<0.01）. The LC3Ⅱ/Ⅰ was significantly increased， and the relative protein expression levels of Bcl-2， p-Parkin， p-PINK1， and Beclin1 were significantly up-regulated （P<0.01）. ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.

Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.

Understory planting of medicinal plants is a new planting mode that connects Chinese herbal medicine(CHM) with forest resources.The complex and variable understory environmental factors will inevitably affect the yield and quality of understory CHM.This research summarized the research progress on understory planting of medicinal plants based on forest types and environmental factors within the forest from the perspectives of understory light, air temperature and humidity, soil characteristics, and the interaction between crops within the forest.The results showed that the complex and variable light, temperature and humidity, and soil factors(such as fertility, acidity and alkalinity, and microorganisms) under the forest could affect the yield and quality of medicinal plants to varying degrees through physiological activities such as photosynthesis and respiration, resulting in a significant increase or decrease in yield and quality compared to open field cultivation.In addition, the competition or mutual benefit between different crops within the forest could lead to differences in the yield and quality of understory medicinal plants compared to open field cultivation.A reasonable combination of planting could achieve resource sharing and complementary advantages.Therefore, conducting systematic research on the effects of understory environmental factors on the yield and content of medicinal plants with different growth and development characteristics can provide theoretical guidance and technical references for formulating comprehensive strategies for understory planting of medicinal plants, such as selecting suitable medicinal plant varieties, optimizing planting density, and conducting reasonable forest management, thus contributing to the sustainable development and ecological protection of CHM.
Plants, Medicinal/growth & development* ; Forests ; Soil/chemistry* ; Environment ; Ecosystem ; Temperature

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring. MethodsIn this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations. ResultsClinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands. Conclusion20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.

Probiotics play a crucial role in colon cancer treatment by metabolizing prebiotics to generate short-chain fatty acids (SCFAs). Colon cancer patients are frequently propositioned to supplement with probiotics to enhance the conversion and utilization of prebiotics. Nevertheless, the delivery and colonization of probiotics is hindered by the harsh conditions of gastrointestinal tract (GIT). Here, we devised a straightforward yet potent modified prebiotic-based "shield" (Gelatin-Inulin, GI), employing dietary inulin and natural polymer gelatin crosslinked via hydrogen bonding for enveloping Lactobacillus reuteri (Lr) to formulate synbiotic hydrogel capsules (Lr@Gl). The GI "shield" serves as a dynamic barrier, augmenting the resistance of Lr to gastric acid and facilitating its bioactivity and adherence in the GIT, synergizing with Lr to elicit an anti-tumor effect. Simultaneously, Lr@GI demonstrates anti-tumor effects by depleting glutathione to release reactive oxygen species, accompanied by the activation of NLRP3 (NOD-like receptor family pyrin domain containing 3), and the induction M1 macrophage polarization. Furthermore, Lr@GI can not only promote the recovery of intestinal barrier but also regulate intestinal flora, promoting the production of SCFAs and further exerting anti-tumor effect. Crucially, Lr@GI also potentiates the anti-tumor effect of 5-Fluorouracil. The construction and synergistic anti-tumor mechanism of synbiotic hydrogel capsules system provide valuable insights for gut microbial tumor therapy.

OBJECTIVES: To explore the mechanism of Lacticaseibacillus paracasei E6 for improving vinorelbine-induced immunosuppression in zebrafish. METHODS: The intestinal colonization of L. paracasei E6 labeled by fluorescein isothiocyanate (FITC) in zebrafish was observed under fluorescence microscope. In a zebrafish model of vinorelbine-induced immunosuppression, the immunomodulatory activity of L. paracasei E6 was assessed by analyzing macrophage and neutrophil counts in the caudal hematopoietic tissue (CHT), the number of T-lymphocyte, and the expressions of interleukin-12 (IL-12) and interferon-γ (IFN-γ). The contents of short-chain fatty acids (SCFAs) in L. paracasei E6 fermentation supernatant and the metabolites of L. paracasei E6 in zebrafish were detected by LC-MS/MS-based targeted metabolomics. The immunomodulatory effects of the SCFAs including sodium acetate, sodium propionate and sodium butyrate were evaluated in the zebrafish model of immunosuppression. RESULTS: After inoculation, green fluorescence of FITC-labeled L. paracasei E6 was clearly observed in the intestinal ball, midgut and posterior gut regions of zebrafish. In the immunocompromised zebrafish model, L. paracasei E6 significantly alleviated the reduction of macrophage and neutrophil counts in the CHT, increased the fluorescence intensity of T-lymphocytes, and promoted the expressions of IL-12 and IFN-γ. Compared with MRS medium, L. paracasei E6 fermentation supernatant showed significantly higher levels of acetic acid, propionic acid and butyric acid, which were also detected in immunocompromised zebrafish following treatment with L. paracasei E6. Treatment of the zebrafish model with sodium acetate and sodium propionate significantly increased macrophage and neutrophil counts in the CHT and effectively inhibited vinorelbine-induced reduction of thymus T cells. CONCLUSIONS L. paracasei E6 can improve vinorelbine-induced immunosuppression in zebrafish through its SCFA metabolites acetic acid and propionic acid.
Animals ; Zebrafish/immunology* ; Acetic Acid/metabolism* ; Propionates/metabolism* ; Fatty Acids, Volatile/metabolism*