ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

Colorectal cancer （CRC） is one of the most common cancers， with its incidence ranking high among cancers. It stands as the second leading cause of cancer-related death worldwide. In the early stages， CRC lacks specific symptoms， and most patients are diagnosed at advanced stages， making it a major research focus in the field of gastrointestinal tumors. Currently， clinical CRC treatments face several common challenges， including high surgical risks， frequent metastasis and recurrence， drug resistance， and significant side effects from chemotherapy and radiation therapy. With the development and application of traditional Chinese medicine （TCM）， it has been found that TCM and its active ingredients can effectively inhibit CRC cell proliferation， invasion， migration， and angiogenesis， and promote apoptosis and autophagy， thereby slowing the progression of CRC. This has become a key focus of CRC treatment research. Salvia Miltiorrhiza has multiple pharmacological effects， including activating blood circulation to dispel blood stasis， unlocking meridians to relieve pain， clearing heat to calm irritability， and cooling blood to reduce abscesses. It contains a variety of chemical components， including diterpenoids， phenolic acids， flavonoids， polysaccharides， nitrogen-containing compounds， steroids， and lactone compounds. This review summarized the molecular mechanisms of Salvia miltiorrhiza and its active ingredients in the treatment of CRC. It is found that these ingredients exert anti-CRC effects through various molecular mechanisms， including cell cycle arrest， promotion of apoptosis， inhibition of cell invasion and migration， induction of autophagy， suppression of tumor angiogenesis， and remodeling of the tumor microenvironment. The review aims to provide new insights for the drug development and clinical application of Salvia miltiorrhiza in CRC treatment.

Background Per- and poly-fluoroalkyl substances (PFAS) can influence gestational diabetes mellitus (GDM); however, current studies on their association are limited and have yielded inconsistent findings. Objective To investigate the association between maternal exposure to PFAS, as measured by urinary concentrations in early pregnancy, and the risk of developing GDM. Methods Based on the Wuhu Birth Cohort in Anhui Province conducted between 2020 and 2023, this study included 1910 pregnant women. Urine samples were collected during the first trimester, and a 75 g oral glucose tolerance test (OGTT) was completed at 24–28 gestational weeks. The concentrations of six PFAS in urine were measured using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Participants were categorized into low, medium, and high exposure groups according to tertiles of individual PFAS concentrations. Logistic regression analysis was employed to assess the potential impact of early-pregnancy PFAS exposure levels on the risk of GDM, with stratified analyses by maternal age and fetal sex. A generalized weighted quantile sum regression (gWQS) model was applied to evaluate the relative weight distribution of the six PFAS in their mixture effect. Results The logistic regression results revealed that both medium exposure to perfluorohexane sulfonate (PFHxS) (OR=1.475, 95%CI: 1.040, 2.093) and high exposure to perfluorononanoic acid (PFNA) (OR=1.430, 95%CI: 1.013, 2.018) were positively associated with diagnosed GDM. This association was more pronounced among women older than 28 years. Among pregnant women carrying male fetuses, high-level exposures to per fluorohexanoic acid (PFHxA) (OR=1.708, 95%CI: 1.006, 2.899) and PFHxS (OR=2.116, 95%CI: 1.247, 3.584) showed positive associations with diagnosed GDM. In contrast, among those carrying female fetuses, moderate perfluorooctanesulfonic acid (PFOS) exposure was associated with a lower risk of GDM (OR=0.542, 95%CI: 0.311, 0.946). The gWQS results demonstrated that PFOS (0.48) and perfluorobutane sulfonate (PFBS) (0.34) contributed the most to the mixture effect. Conclusion Early-pregnancy exposure to PFAS (particularly PFHxS and PFNA) may be an etiological factor for GDM, with maternal age and fetal sex potentially acting as effect modifiers in this association.

In the context of the modernization of traditional Chinese medicine （TCM）， the inheritance of the experiences of famous doctors faces significant challenges due to its complex nonlinear characteristics and dynamic evolution. There are still issues in the current inheritance system， such as the homogenization of talent cultivation models， lack of standardized mentoring practices， and monotonous evaluation method， which hinder the systematic inheritance and innovative development of famous doctors' experiences. Based on a systematic review of the current state of artificial intelligence （AI）-assisted inheritance of famous doctors' experiences， this study explores innovative pathways for deep integration of modern information technologies with famous doctors' experiences from key dimensions， including data authenticity assurance， interdisciplinary collaboration mechanisms， and the establishment of dynamic inheritance standards. It proposes a paradigm shift in the inheritance of TCM famous doctors' experiences in the AI era， aiming to build a new TCM inheritance system of "digital intelligence empowerment and cross-disciplinary innovation"， providing theoretical support and practical pathways for the inheritance of famous doctors' experiences in TCM.

Background: Murraya, a genus of shrubs and trees in the Rutaceae family, consists of approximately 9 species in China with significant medicinal and horticultural value. However, the phylogeny and taxonomy of Murraya species remain controversial, particularly with respect to Murraya exotica and M. paniculata. Objective: This study aimed to provide insights into the taxonomy, phylogeny, and identification of Murraya. Methods: In this study, the chloroplast (CP) genomes of 7 Murraya species were sequenced, assembled, and subjected to comparative and phylogenetic analyses. Results: The CP genomes of Murraya ranged from 158,573 to 160,817 bp in length and encoded 112 unique genes, including 78 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Similar to other angiosperms, the inverted repeat regions of the CP genomes exhibited lower sequence divergence than the single-copy regions, and coding regions were more conserved than noncoding regions. Comparative analysis identified several highly variable regions (eg, matK, ycf1, ndhI-ndhA, trnH-GUG-psbA, rpl32-trnL) that could serve as molecular markers for species identification in Murraya. Among these, the ycf1 gene was validated as a useful marker for distinguishing M. exotica from M. paniculata. Positive selection was detected in 10 genes, including rbcL, psaJ, ndhD, ndhF, rpl2, rpl20, ycf1, accD, ccsA, and rpl32. Phylogenetic analysis based on CP genomes supported the recognition of M. exotica and M. paniculata as independent species. Moreover, the phylogenetic trees indicated that Murraya is not monophyletic, with sect. Bergera showing a closer relationship to Clausena. Molecular dating results suggested that the diversification of M. paniculata, M. alata, and M. exotica occurred approximately 9.11 Mya (95% highest posterior density: 4.90-13.87 Mya). Conclusion: These findings provide valuable CP genome data for clarifying the phylogenetic relationships between M. exotica and M. paniculata, and for advancing the study of DNA markers and the evolutionary history of Murraya.

Objective: To analyze the situation of blood return in medical institutions in Qingdao, and provide a reference basis for improving blood utilization efficiency. Methods: Data on whole blood donations, and the distribution and return of various blood components from 2022 to 2024 at the Qingdao Central Blood Station were collected. The overall trend of blood return, return situation of various blood components, main reasons for blood return, and related influencing factors were analyzed. Results: The average blood return rate from 2022 to 2024 was 1.43‰ (1 249/875 007), showing an overall downward trend (P<0.05). The return rate of red blood cell (RBC) components increased year by year over the three years, while those of plasma components and cryoprecipitated antihemophilic factors decreased. Regarding the reasons for blood return, the return rates due to direct antiglobulin test (DAT) positivity and unexpected antibody positivity increased year by year, whereas those due to leakage and other reasons decreased. Univariate analysis of the causes of RBC components return showed that DAT positivity rates differed significantly by sex, age, and blood type, but not by donation season; unexpected antibody positivity rate differed significantly by sex, but not by age, blood type, or donation season. Multivariate analysis indicated that female gender, age>30 years, and blood type A or AB were independent risk factors for DAT positivity, while female gender was an independent risk factor for unexpected antibody positivity. The return rate due to DAT positivity differed significantly among medical institutions of different levels, while that due to unexpected antibody positivity did not show a significant difference. Some donors who tested positive for DAT (76.92%, 60/78) or unexpected antibody (71.15%, 37/52) became antibody-negative upon subsequent donations. Comparing RBC donors with DAT positivity who became negative upon subsequent donations with those who remained positive, the difference in donation interval was statistically significant. Conclusion: Over the past three years, the overall blood return rate in Qingdao has declined, but the return rate of RBC components has increased. Further investigation and targeted interventions are needed to enhance the utilization of blood resources and ensure safe clinical blood transfusion.

ObjectiveTo understand the mental health literacy levels and influencing factors among middle school students in Minhang District, Shanghai, and to provide a basis for formulating mental health promotion strategies. MethodsA multi-stage stratified cluster sampling method was adopted. From September to October 2023, middle school students (including junior and senior high school) from 14 streets, towns, and industrial zones in Minhang District, Shanghai, were recruited to participate in a questionnaire survey. The survey collected demographic information and employed the Adolescent Mental Health Literacy Assessment Scale. This scale comprises four dimensions (knowledge, recognition ability, attitude, and behavior) with a total of 22 items, using a Likert 5-point scale (1‒5 points), giving a maximum total score of 110 points. Reverse-scored items were inverted, and the sum of all item scores constituted the total scale score, with higher scores indicating better mental health literacy. A total score of ≥88 points was defined as having adequate mental health literacy. Multiple linear regression was used to analyze the factors influencing mental health literacy. ResultsThe average mental health literacy score of the 3 963 middle school students in Minhang District of Shanghai City was (85.42±11.27) points, with 45.22% of students having adequate mental health literacy. Univariate analyses showed that female students, junior high school students, and those without stressful events or physical illnesses in the past three months had higher total scores of mental health literacy. Statistically significant differences in total scores were also observed among students with different family economic statuses, parental education levels, frequency of physical exercise, parental relationships, father‑child relationships, and mother‑child relationships (all P<0.05). Multiple linear regression analyses showed that middle school students who were female, had better family economic conditions, higher maternal education levels (university degree or above), and harmonious mother-child relationships had higher mental health literacy scores. In contrast, high school students and those middle school students who participated in less physical activity had lower mental health literacy scores. Multivariate logistic regression analyses indicated that students who were female (OR=1.336, 95%CI: 1.174‒1.520), had superior family economic status (OR=2.000, 95%CI: 1.101‒3.725), had mothers with a university education level (OR=1.501, 95%CI: 1.217‒1.856), had lost one parent (OR=2.189, 95%CI: 1.176~4.158), or reported harmonious mother‑child relationships (OR=2.052, 95%CI: 1.432‒2.987) were more likely to meet the criteria for mental health literacy, whereas those who rarely engaged in physical exercise (OR=0.502, 95%CI: 0.358‒0.694) were less likely to have adequate mental health literacy. Stratified analyses showed that mental health literacy levels among junior high school students were positively correlated with being female, having a mother with a university education level, and having a mother‑child relationship that was average or harmonious and having a harmonious father‑child relationship, and negatively correlated with occasional or rare participation in physical exercise. Among senior high school students, mental health literacy levels were positively correlated with being female, having good or superior family economic status, having a mother with a university education level or above, and having a harmonious mother‑child relationship. ConclusionThe rate of adequate mental health literacy among middle school students in Minhang District, Shanghai, was approximately 45.22%. Gender, grade level, family economic status, maternal education level, physical activity participation, and mother-child relationship are independent factors associated with the level of mental health literacy among middle school students. Mother-child relationship and physical activity are potential intervention entry points. It is recommended to implement targeted health promotion initiatives focusing on key groups, such as high school boys, students from economically disadvantaged families, and those with insufficient physical activity.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.