Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Spermatogenesis is a highly ordered and spatiotemporally regulated developmental process in the male reproductive system, during which spermatogonial stem cells (SSCs), supported by the seminiferous tubule microenvironment, sequentially undergo mitosis, meiosis, and spermiogenesis to ultimately generate structurally intact spermatozoa. This complex process is accompanied by extensive transcriptional reprogramming, chromatin remodeling, and finely tuned post-transcriptional regulation. Precise control of RNA fate is therefore essential for maintaining the continuity and fidelity of spermatogenesis, and its disruption represents a major molecular basis of male infertility. N⁶-methyladenosine (m⁶A), the most abundant internal RNA modification in eukaryotes, has emerged as a critical regulator of post-transcriptional gene expression. m⁶A methyltransferases (“writers”) catalyze the addition of a methyl group to the N⁶ position of adenosine, m⁶A demethylases (“erasers”) remove the modification, and m⁶A-binding proteins (“readers”) recognize m⁶A-modified transcripts. Through the coordinated actions of these factors, m⁶A regulates transcript fate at multiple levels, including RNA splicing, nuclear export, stability, translation, and decay. Emerging evidence indicates that m⁶A-mediated regulation is essential across multiple stages of spermatogenesis, including SSC self-renewal and differentiation, meiotic progression, maintenance of chromosomal stability, and sperm morphogenesis. Beyond its intrinsic functions in germ cells, m⁶A also contributes to the regulation of the testicular microenvironment. In sertoli cells, m⁶A is involved in maintaining blood-testis barrier integrity, RNA processing, and paracrine signaling, thereby providing structural and metabolic support for germ cell development. In Leydig cells, m⁶A regulates steroidogenesis, particularly testosterone synthesis, and participates in cellular stress responses and metabolic homeostasis. Through these mechanisms, m⁶A indirectly influences spermatogenesis by modulating the functional state of testicular somatic cells, highlighting an integrated regulatory mode that combines cell-intrinsic and microenvironment-mediated effects. Notably, distinct classes of m⁶A regulators exhibit pronounced stage-specific functions and coordinated division of labor, collectively forming a multilayered and dynamic regulatory network. Writers often display dosage- and temporal window-dependent effects; erasers contribute to stage-specific demethylation and functional compensation; while readers function through a “switch-buffer” dual-layer architecture, and RNA-binding proteins (RBPs) participate in substrate selection and post-transcriptional regulation. Importantly, emerging evidence suggests that some m⁶A-related proteins can function through noncanonical mechanisms independent of m⁶A recognition, such as intrinsic RNA-binding activity, helicase function, or ribonucleoprotein complex assembly, thereby expanding the functional landscape of the m⁶A regulatory system. Dysregulation of m⁶A machinery can lead to multiple spermatogenic defects, including impaired SSC self-renewal, meiotic arrest, abnormal chromatin remodeling, and defective sperm formation, ultimately resulting in male infertility. Despite substantial advances, several critical questions remain unresolved, including the distinction between m⁶A-dependent and -independent mechanisms, the spatiotemporal dynamics of m⁶A modifications at single-cell resolution, and the coordination and antagonism among different regulatory factors. In this review, we systematically summarize the dual regulation of spermatogenesis by germ cell-intrinsic mechanisms and the testicular microenvironment, and delineate the molecular mechanisms and stage-specific functions of the dynamic m⁶A regulatory network. We further discuss the current limitations in the field and propose feasible experimental strategies for future investigation. Collectively, this work aims to provide a comprehensive framework for understanding the epitranscriptomic regulation of spermatogenesis and to offer theoretical insights into the pathogenesis and clinical management of male infertility.

Spermatogenesis is a highly ordered and spatiotemporally regulated developmental process in the male reproductive system, during which spermatogonial stem cells (SSCs), supported by the seminiferous tubule microenvironment, sequentially undergo mitosis, meiosis, and spermiogenesis to ultimately generate structurally intact spermatozoa. This complex process is accompanied by extensive transcriptional reprogramming, chromatin remodeling, and finely tuned post-transcriptional regulation. Precise control of RNA fate is therefore essential for maintaining the continuity and fidelity of spermatogenesis, and its disruption represents a major molecular basis of male infertility. N⁶-methyladenosine (m⁶A), the most abundant internal RNA modification in eukaryotes, has emerged as a critical regulator of post-transcriptional gene expression. m⁶A methyltransferases (“writers”) catalyze the addition of a methyl group to the N⁶ position of adenosine, m⁶A demethylases (“erasers”) remove the modification, and m⁶A-binding proteins (“readers”) recognize m⁶A-modified transcripts. Through the coordinated actions of these factors, m⁶A regulates transcript fate at multiple levels, including RNA splicing, nuclear export, stability, translation, and decay. Emerging evidence indicates that m⁶A-mediated regulation is essential across multiple stages of spermatogenesis, including SSC self-renewal and differentiation, meiotic progression, maintenance of chromosomal stability, and sperm morphogenesis. Beyond its intrinsic functions in germ cells, m⁶A also contributes to the regulation of the testicular microenvironment. In sertoli cells, m⁶A is involved in maintaining blood-testis barrier integrity, RNA processing, and paracrine signaling, thereby providing structural and metabolic support for germ cell development. In Leydig cells, m⁶A regulates steroidogenesis, particularly testosterone synthesis, and participates in cellular stress responses and metabolic homeostasis. Through these mechanisms, m⁶A indirectly influences spermatogenesis by modulating the functional state of testicular somatic cells, highlighting an integrated regulatory mode that combines cell-intrinsic and microenvironment-mediated effects. Notably, distinct classes of m⁶A regulators exhibit pronounced stage-specific functions and coordinated division of labor, collectively forming a multilayered and dynamic regulatory network. Writers often display dosage- and temporal window-dependent effects; erasers contribute to stage-specific demethylation and functional compensation; while readers function through a “switch-buffer” dual-layer architecture, and RNA-binding proteins (RBPs) participate in substrate selection and post-transcriptional regulation. Importantly, emerging evidence suggests that some m⁶A-related proteins can function through noncanonical mechanisms independent of m⁶A recognition, such as intrinsic RNA-binding activity, helicase function, or ribonucleoprotein complex assembly, thereby expanding the functional landscape of the m⁶A regulatory system. Dysregulation of m⁶A machinery can lead to multiple spermatogenic defects, including impaired SSC self-renewal, meiotic arrest, abnormal chromatin remodeling, and defective sperm formation, ultimately resulting in male infertility. Despite substantial advances, several critical questions remain unresolved, including the distinction between m⁶A-dependent and -independent mechanisms, the spatiotemporal dynamics of m⁶A modifications at single-cell resolution, and the coordination and antagonism among different regulatory factors. In this review, we systematically summarize the dual regulation of spermatogenesis by germ cell-intrinsic mechanisms and the testicular microenvironment, and delineate the molecular mechanisms and stage-specific functions of the dynamic m⁶A regulatory network. We further discuss the current limitations in the field and propose feasible experimental strategies for future investigation. Collectively, this work aims to provide a comprehensive framework for understanding the epitranscriptomic regulation of spermatogenesis and to offer theoretical insights into the pathogenesis and clinical management of male infertility.

Recently, male reproductive health has attracted extensive attention, with the adverse effects of circadian disruption on male fertility gradually gaining recognition. However, the mechanism by which circadian disruption leads to damage to male reproductive system remains unclear. In this review, we first summarized the dual regulatory roles of circadian clock genes on the male reproductive system: (1) circadian regulation of testosterone synthesis via the hypothalamic-pituitary-testicular (HPT) and hypothalamic-pituitary-adrenal (HPA) axes; (2) non-circadian regulation of spermatogenesis. Next, we further listed the possible mechanisms by which circadian disruption impairs male fertility, including interference with the oscillatory function of the reproductive system, i.e., synchronization of the HPT axis, crosstalk between the HPT axis and the HPA axis, as well as direct damage to germ cells by disturbing the non-oscillatory function of the reproductive system. Future research using spatiotemporal omics, epigenomic assays, and neural circuit mapping in studying the male reproductive system may provide new clues to systematically unravel the mechanisms by which circadian disruption affects male reproductive system through circadian clock genes.
Male ; Humans ; Animals ; Circadian Clocks/physiology* ; Hypothalamo-Hypophyseal System/physiology* ; Circadian Rhythm/genetics* ; Spermatogenesis/physiology* ; Pituitary-Adrenal System/physiology* ; Testis/physiology* ; Testosterone/biosynthesis* ; CLOCK Proteins ; Infertility, Male/physiopathology*

This study investigated the effects and action mechanism of tannins from Galla chinensis cream(TGCC) on the skin wound of rat tail. Male Sprague Dawley(SD) rats were randomly divided into a control group, model group, model+low-dose TGCC(50 mg per rat) group, model+high-dose TGCC group(100 mg per rat), and model+TGC+FAK inhibitor(Y15) cream(100 mg+10 mg per rat) group, with 10 rats in each group. After the rat tail skin injury model was successfully constructed, in the treatment group, corresponding drugs were applied to the wound surface, while in the control and model groups, the same amount of cream base as the TGCC group was applied by the same method. Then, sterile gauze was wrapped around the wound edge, and these operations were performed three times a day for 28 consecutive days. The wound healing status at the third, seventh, eleventh, fourteenth, twenty-first, and twenty-eighth days was recorded, and the wound healing rate and healing time were calculated. On the day after the last dose of medication, rat serum and tail skin wound tissue were collected for analyzing the activities of serum alanine aminotransferase(ALT), aspartate aminotransferase(AST), creatinine(CREA), urea, reactive oxygen species(ROS), interferon gamma(IFN-γ), interleukin(IL)-1β, IL-6, IL-4, IL-10, tumor necrosis factor(TNF)-α, as well as catalase(CAT), glutathione(GSH), lactate dehydrogenase(LDH), malondialdehyde(MDA), myeloperoxidase(MPO), superoxide dismutase(SOD), total antioxidant capacity(T-AOC), platelet endothelial cell adhesion molecule-1(CD31), and leukocyte differentiation antigen 34(CD34) in the wound tissue of rat tail skin. Hematoxylin-eosin, Masson, and sirius red staining were used to observe the morphological changes in the wound tissue of rat tail skin. The thickness of the epidermis, the number of fibroblasts and blood vessels, and the contents of collagen fibers, typeⅠ collagen(COLⅠ), and COLⅢ were calculated. The mRNA expressions of keratin 10(KRT10), KRT14, vascular endothelial growth factor(VEGF), fibroblast growth factor(FGF), epidermal growth factor(EGF), CD31, CD34, matrix metallopeptidase-2(MMP-2), MMP-9, COLⅠ, COLⅢ, desmin, fibroblast specific protein 1(FSP1), IFN-γ, IL-1β, TNF-α, IL-4, IL-6, and IL-10 in skin wound tissue were determined by quantitative real-time polymerase chain reaction(PCR). Western blot was utilized to detect the protein expressions of KRT10, KRT14, VEGF, FGF, EGF, MMP-2, MMP-9, COLⅠ, COLⅢ, desmin, FSP1, focal adhesion kinase(FAK), phosphorylated focal adhesion kinase(p-FAK), phosphatidylin-ositol-3-kinase(PI3K), phosphorylated phosphatidylin-ositol-3-kinase(p-PI3K), protein kinase B(Akt), phosphorylated protein kinase B(p-Akt), mammalian target of rapamycin(mTOR), and phosphorylated mammalian target of rapamycin(p-mTOR). The results manifest that TGCC can dramatically elevate the healing rate of rat tail wounds and shorten wound healing time. Besides, it can reduce serum ROS levels, the contents of MDA, MPO, and LDH in the rat skin wound tissue, as well as the serum IFN-γ, IL-1β, IL-6, and TNF-α levels and the mRNA expression levels of IFN-γ, IL-1β, IL-6, and TNF-α in the skin wound tissue. It can elevate the activities of CAT, GSH, SOD, and T-AOC in wound tissue, the IL-4 and IL-10 contents in serum, and the mRNA expressions of IL-4 and IL-10 in the wound tissue. In addition, TGGC can inhibit inflammatory cell infiltration and increase the epidermal thickness, counts of fibroblasts and blood vessels, and contents of collagen fibers, COLⅠ, and COLⅢ. Besides, TGCC can elevate the mRNA and protein expressions of epidermal differentiation markers(KRT10 and KRT14), endothelial cell markers(CD31 and CD34), angiogenesis and fibroblast proliferation, differentiation markers(VEGF, FGF, EGF, COLⅠ, COLⅢ, desmin, and FSP1), reduce the mRNA and protein expressions of gelatinases(MMP-2 and MMP-9), and increase protein expressions of p-FAK, p-PI3K, p-Akt, p-mTOR, as well as ratios of p-FAK/FAK, p-PI3K/PI3K, p-Akt/Akt, and p-mTOR/mTOR. These results suggest that TGCC can significantly facilitate skin wound healing, and its mechanism may be related to the activation of the FAK/PI3K/Akt/mTOR signaling pathway, inhibition of inflammatory cell infiltration in skin wound tissue, elevation of epidermal thickness, counts of fibroblasts and vessels, and contents of collagen fiber, COLⅠ, and COLⅢ, and reduction of MMP-2 and MMP-9 expressions, thus accelerating wound healing.
Animals ; Male ; Wound Healing/drug effects* ; Rats ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; TOR Serine-Threonine Kinases/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Skin/metabolism* ; Proto-Oncogene Proteins c-akt/genetics* ; Tannins/pharmacology* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Focal Adhesion Kinase 1/genetics*

This study aims to investigate the mechanism by which resveratrol(RES) alleviates cerebral vascular endothelial damage in sepsis-associated encephalopathy(SAE) through network pharmacology and animal experiments. By using network pharmacology, the study identified common targets and genes associated with RES and SAE and constructed a protein-protein interaction( PPI) network. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed to pinpoint key signaling pathways, followed by molecular docking validation. In the animal experiments, a cecum ligation and puncture(CLP) method was employed to induce SAE in mice. The mice were randomly assigned to the sham group, CLP group, and medium-dose and high-dose groups of RES. The sham group underwent open surgery without CLP, and the CLP group received an intraperitoneal injection of 0. 9% sodium chloride solution after surgery. The medium-dose and high-dose groups of RES were injected intraperitoneally with 40 mg·kg-1 and 60 mg·kg~(-1) of RES after modeling, respectively, and samples were collected 12 hours later. Neurological function scores were assessed, and the wet-dry weight ratio of brain tissue was detected. Serum superoxide dismutase(SOD), catalase( CAT) activity, and malondialdehyde( MDA) content were measured by oxidative stress kit. Histopathological changes in brain tissue were examined using hematoxylin-eosin(HE) staining. Transmission electron microscopy was employed to evaluate tight cell junctions and mitochondrial ultrastructure changes in cerebral vascular endothelium. Western blot analysis was performed to detect the expression of zonula occludens1( ZO-1), occludin, claudins-5, optic atrophy 1( OPA1), mitofusin 2(Mfn2), dynamin-related protein 1(Drp1), fission 1(Fis1), and hypoxia-inducible factor-1α(HIF-1α). Network pharmacology identified 76 intersecting targets for RES and SAE, with the top five core targets being EGFR, PTGS2, ESR1, HIF-1α, and APP. GO enrichment analysis showed that RES participated in the SAE mechanism through oxidative stress reaction. KEGG enrichment analysis indicated that RES participated in SAE therapy through HIF-1α, Rap1, and other signaling pathways. Molecular docking results showed favorable docking activity between RES and key targets such as HIF-1α. Animal experiment results demonstrated that compared to the sham group, the CLP group exhibited reduced nervous reflexes, decreased water content in brain tissue, as well as serum SOD and CAT activity, and increased MDA content. In addition, the CLP group exhibited disrupted tight junctions in cerebral vascular endothelium and abnormal mitochondrial morphology. The protein expression levels of Drp1, Fis1, and HIF-1α in brain tissue were increased, while those of ZO-1, occludin, claudin-5, Mfn2, and OPA1 were decreased. In contrast, the medium-dose and high-dose groups of RES showed improved neurological function, increased water content in brain tissue and SOD and CAT activity, and decreased MDA content. Cell morphology in brain tissue, tight junctions between endothelial cells, and mitochondrial structure were improved. The protein expressions of Drp1, Fis1, and HIF-1α were decreased, while those of ZO-1, occludin, claudin-5, Mfn2, and OPA1 were increased. This study suggested that RES could ameliorate cerebrovascular endothelial barrier function and maintain mitochondrial homeostasis by inhibiting oxidative stress after SAE damage, potentially through modulation of the HIF-1α signaling pathway.
Animals ; Mice ; Network Pharmacology ; Resveratrol/administration & dosage* ; Male ; Sepsis-Associated Encephalopathy/genetics* ; Signal Transduction/drug effects* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Endothelium, Vascular/metabolism* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Humans ; Sepsis/complications* ; Oxidative Stress/drug effects*

A high-performance liquid chromatography method using pre-column derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate was developed to determine the content of 15 amino acids in the medicinal snakes Bungarus Parvus, Agkistrodon, and Zaocys. The results showed that the total amino acid(TAA) content ranged from 277.13 to 515.05 mg·g~(-1), with the top four amino acids in all three species being glutamic acid(Glu), glycine(Gly), aspartic acid(Asp), and lysine(Lys). The essential amino acid(EAA) content ranged from 74.56 to 203.94 mg·g~(-1), with Agkistrodon exhibiting the highest content. The non-essential amino acid(NEAA), semi-essential amino acid(semi-EAA), and medicinal amino acid(MAA) content ranged from 189.06 to 318.23, 12.89 to 33.53, and 179.83 to 342.33 mg·g~(-1), respectively, with Zaocys having the highest content in these categories. Amino acid nutritional value was evaluated using the amino acid ratio(RAA), amino acid ratio coefficient(RCAA), and amino acid ratio coefficient score(SRCAA), and the results indicated that all three medicinal snakes possessed good nutritional value. The amino acid composition was similar across the species, though significant differences in content were observed. Based on these differences, an orthogonal partial least squares-discriminant analysis(OPLS-DA) model was established, which could clearly distinguish between the three medicinal snake species. The key differences in amino acid content included Gly, tyrosine(Tyr), Glu, and serine(Ser), which may be related to the observed clinical application differences among the species. Further research into the mechanisms of these differential amino acids is expected to provide more insights into the clinical application disparities of these three medicinal snake species.
Amino Acids/chemistry* ; Animals ; Nutritive Value ; Chromatography, High Pressure Liquid ; Snakes/classification* ; Bungarus

OBJECTIVES: To investigate the genomic characteristics and prognostic factors of juvenile myelomonocytic leukemia (JMML) with RAS mutations. METHODS: A retrospective analysis was conducted on the clinical data of JMML children with RAS mutations treated at the Hematology Hospital of Chinese Academy of Medical Sciences, from January 2008 to November 2022. RESULTS: A total of 34 children were included, with 17 cases (50%) having isolated NRAS mutations, 9 cases (27%) having isolated KRAS mutations, and 8 cases (24%) having compound mutations. Compared to children with isolated NRAS mutations, those with NRAS compound mutations showed statistically significant differences in age at onset, platelet count, and fetal hemoglobin proportion (P<0.05). Cox proportional hazards regression model analysis revealed that hematopoietic stem cell transplantation (HSCT) and hepatomegaly (≥2 cm below the costal margin) were factors affecting the survival rate of JMML children with RAS mutations (P<0.05); hepatomegaly was a factor affecting survival in the non-HSCT group (P<0.05). CONCLUSIONS Children with NRAS compound mutations have a later onset age compared to those with isolated NRAS mutations. At initial diagnosis, children with NRAS compound mutations have poorer peripheral platelet and fetal hemoglobin levels than those with isolated NRAS mutations. Liver size at initial diagnosis is related to the prognosis of JMML children with RAS mutations. HSCT can improve the prognosis of JMML children with RAS mutations.
Humans ; Leukemia, Myelomonocytic, Juvenile/therapy* ; Mutation ; Male ; Female ; Child, Preschool ; Retrospective Studies ; Child ; Infant ; GTP Phosphohydrolases/genetics* ; Membrane Proteins/genetics* ; Adolescent ; Hematopoietic Stem Cell Transplantation ; Proportional Hazards Models ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.