ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

BACKGROUND:Previous studies have found that neohesperidin can delay bone loss in ovariectomized mice and has the potential to treat osteoporosis,but its specific mechanism of action remains to be explored. OBJECTIVE:To explore the key targets and possible mechanisms of neohesperidin in the treatment of osteoporosis based on bioinformatics and cell experiments in vitro. METHODS:The gene expression dataset related to osteoporosis was obtained from GEO database,and the differentially expressed genes were screened and analyzed in R language.The osteoporosis-related targets were screened from GeneCards and DisGeNET databases,and the neohesperidin-related targets were screened from ChEMBL and PubChem databases,and the common targets were obtained by intersection of the three.The String database was used to construct the PPI network of intersection genes,and the key targets were screened.The DAVID database was used for GO and KEGG enrichment analysis.The AutoDock software was used to verify the molecular docking between the neohesperidin and the target protein.The effect of neohesperidin on osteogenic differentiation of C57 mouse bone marrow mesenchymal stem cells was detected.Complete medium was used as blank control group;osteogenic induction medium was used as the control group;and osteogenic induction medium containing different concentrations of neohesperidin(25,50 μmol/L)was used as experimental group.The expression of alkaline phosphatase,the degree of mineralization,the expression of osteogenic-related genes and target genes during osteogenic differentiation of cells were measured at corresponding time points. RESULTS AND CONCLUSION:(1)9 253 differentially expressed genes,2 161 osteoporosis-related targets,and 326 neohesperidin-related targets were screened.There were 53 common targets among the three.All 53 genes were up-regulated in osteoporosis samples.The PPI network screened the target gene PRKACA of research significance.GO function and KEGG pathway enrichment analysis showed that neohesperidin's treatment of osteoporosis through PRKACA target mainly depended on biological processes such as protein phosphorylation and protein autophosphorylation,acting on endocrine resistance,proteoglycan in cancer,and estrogen signaling pathway to play a therapeutic role.Molecular docking results showed that neohesperidin had a certain binding ability to the protein corresponding to the target PRKACA.(2)The results of alkaline phosphatase staining showed that neohesperidin could promote the expression of alkaline phosphatase in the early stage of osteogenic differentiation of mesenchymal stem cells.Alizarin red staining showed that neohesperidin could promote the mineralization of osteogenic differentiation of mesenchymal stem cells.RT-qPCR results showed that neohesperidin could increase the mRNA expression of alkaline phosphatase,PRKACA,and osteocalcin.(3)These results indicate that neohesperidin may promote osteogenic differentiation through PRKACA target on the estrogen signaling pathway to prevent and treat osteoporosis.

Objective: To examine the relationship between self-management behaviors and time perspective among patients with comorbid diabetes, so as to provide the evidence for improving self-management behaviors among patients with comorbid diabetes. Methods: The patients with comorbid diabetes who were registered in the chronic disease health management system of Minhang District, Shanghai Municipality in 2021, followed up regularly, and lived in Meilong Town were recruited. Demographic information and family history of diabetes were collected through questionnaire surveys. Time perspective and self-management behaviors were assessed using the Zimbardo Time Perspective Inventory and Diabetes Self-Management Behavior Scale, respectively. The relationship between self-management behaviors and time perspective was analyzed using a multivariable ordinal logistic regression model. Results: A total of 907 patients with comorbid diabetes were enrolled, including 472 males (52.04%) and 435 females (47.96%). There were 652 cases aged 65 years and above, accounting for 71.89%. In terms of the types of time perspective, 280 patients were future-oriented (30.87%), 236 were balanced (26.02%), 162 were sensation-seeking (17.86%), 123 were fatalistic (13.56%), and 106 were negative (11.69%). In terms of the self-management behaviors, 46 patients were good (5.07%), 643 were moderate (70.89%), and 218 were poor (24.04%). Multivariable ordinal logistic regression analysis showed that after adjusting for age, gender, educational level, marital status, occupation status, monthly income, and family history of diabetes, the patients with comorbid diabetes who had a future-oriented time perspective had better self-management behaviors (OR=1.874, 95%CI: 1.204-2.915). Conclusion The self-management behaviors among patients with comorbid diabetes are moderate to poor, and patients with a future-oriented time perspective can better engage in self-management behaviors.

Stroke ranks as the third leading cause of death and the fourth leading cause of disability worldwide. Its high disability rate and prolonged recovery period not only severely impact patients' quality of life but also impose a significant burden on families and society. Primary prevention is the cornerstone of stroke control, as early intervention on risk factors can effectively reduce its incidence. Therefore, the development of predictive models for first-ever stroke risk holds substantial clinical value. In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. Second, there is a need to diversify data types and optimize model architectures to construct more comprehensive and precise predictive models. Lastly, particular attention should be given to the clinical validation of models in real-world settings. This not only enhances the robustness and generalizability of the models but also promotes physicians' understanding of predictive models, which is crucial for their application and dissemination.

Objective: To analyze the latent tuberculosis infection and preventive treatment in the school tuberculosis epidemic, so as to provide theoretical and technical support for tuberculosis prevention and control in schools. Methods: Information on latent infection, preventive treatment and tuberculosis incidence were collected from five tuberculosis outbreaks in schools in Hunan Province from January to December 2023. Statistical analysis was conducted by using Chisquare test and Fishers exact test. Results: The prevalence of tuberculosis patients in close contacts (7.69%) and the latent infection rate of Mycobacterium tuberculosis (31.87%) were higher than those in nonclose contacts (0.12%, 6.29%), and the differences were statistically significant (P＜0.01). The subsequent incidence of close contacts with latent infection was higher (8.62%) than that of nonclose contacts (0), the rate of close contacts receiving prophylactic treatment (63.30%) was higher than that of nonclose contacts (47.37%), and the proportion of close contacts receiving prophylactic treatment (68.12%) was higher than that of nonclose contacts (45.56%), and the differences were statistically significant (P＜0.05). The latent infection rate of Mycobacterium tuberculosis in college students (13.58%) was higher than that in middle school students (7.08%) (χ2=37.77, P<0.01). The proportion of college students receiving preventive treatment (100.00%) was higher than that of middle school students (40.34%), and the subsequent incidence of latent infection (6.67%) was higher than that of middle school students (0.54%); the rate of middle school students who should receive preventive treatment (70.41%) was higher than that of college students (30.77%), and the rate of middle school students who received preventive treatment (100.00%) was higher than that of college students (62.50%), and the differences were statistically significant (P<0.01). Among the latent infected persons, 144 who completed preventive treatment did not get sick, and 10 of the 177 who did not complete preventive treatment got sick, with an incidence rate of 5.65%. The incidence rate of close contacts (19.23%) was higher than that of nonclose contacts (0) (P<0.01). There was no significant difference in the incidence of pulmonary tuberculosis between university (8.18%) and middle school (1.49%) among latent infected persons who did not complete preventive treatment (P=0.09). Conclusion Actively promoting preventive treatment for latent infections, especially among close contacts, and ensuring that all eligible individuals receive treatment can reduce tuberculosis incidence in schools and help control the scale of school tuberculosis outbreaks.

OBJECTIVE: To determine whether monotropein has an anticancer effect and explore its potential mechanisms against colorectal cancer (CRC) through network pharmacology and molecular docking combined with experimental verification. METHODS: Network pharmacology and molecular docking were used to predict potential targets of monotropein against CRC. Cell counting kit assay, plate monoclonal assay and microscopic observation were used to investigate the antiproliferative effects of monotropein on CRC cells HCT116, HT29 and LoVo. Flow cytometry and scratch assay were used to analyze apoptosis and cell cycle, as well as cell migration, respectively in HCT116, HT29, and LoVo cells. Western blotting was used to detect the expression of proteins related to apoptosis, cell cycle, and cell migration, and the expression of proteins key to the Akt pathway. RESULTS: The Gene Ontology and Reactome enrichment analyses indicated that the anticancer potential of monotropein against CRC might be involved in multiple cancer-related signaling pathways. Among these pathways, RAC-beta serine/threonine-protein kinase (Akt1, Akt2), cyclin-dependent kinase 6 (CDK6), matrix metalloproteinase-9 (MMP9), epidermal growth factor receptor (EGFR), cell division control protein 42 homolog (CDC42) were shown as the potential anticancer targets of monotropein against CRC. Molecular docking suggested that monotropein may interact with the 6 targets (Akt1, Akt2, CDK6, MMP9, EGFR, CDC42). Subsequently, cell activity of HCT116, HT29 and LoVo cell lines were significantly suppressed by monotropein (P<0.05). Furthermore, our research revealed that monotropein induced cell apoptosis by inhibiting Bcl-2 and increasing Bax, induced G₁-S cycle arrest in colorectal cancer by decreasing the expressions of CyclinD1, CDK4 and CDK6, inhibited cell migration by suppressing the expressions of CDC42 and MMP9 (P<0.05), and might play an anticancer role through Akt signaling pathway. CONCLUSION Monotropein exerts its antitumor effects primarily by arresting the cell cycle, causing cell apoptosis, and inhibiting cell migration. This indicates a high potential for developing novel medication for treating CRC.
Humans ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation ; Matrix Metalloproteinase 9 ; Molecular Docking Simulation ; Cell Cycle ; ErbB Receptors ; Apoptosis ; Colorectal Neoplasms/pathology* ; Cell Line, Tumor

Yigongsan is derived from Xiaoer Yaozheng Zhijue written by QIAN Yi in the Northern Song dynasty， which is the No. 3 formula in the Catalogue of Ancient Famous Classical Formulas（The Second Batch of Pediatrics） released by the National Administration of Traditional Chinese Medicine（TCM） in September 2022， and it can be developed as a class 3.1 new TCM drug. By referring to ancient medical books and modern literature， this study conducted herbal textual research on Yigongsan from five aspects， including historical evolution， origin and processing， dosage conversion， usage and preparation methods， and functional application， then formed the key information table of this formula， in order to provide reference for the development of reference samples and preparations of Yigongsan. Based on the results of the study， it is recommended that Panax ginseng should be removed the basal part of stem（rhizoma）， Poria cocos should be removed the peel， Citrus reticulata should be cut into shreds and Glycyrrhiza uralensis should be used. According to 4.13 g/Qian（钱）， 1 g/slice for ginger， 3 g for each jujube and 300 mL/Zhan（盏）， the doses of Ginseng Radix， Poria， Atractylodis Macrocephalae Rhizoma， Glycyrrhizae Radix et Rhizoma， Citri Reticulatae Pericarpium， Zingiberis Rhizoma Recens， Jujubae Fructus were 1.652， 1.652， 1.652， 1.652， 1.652， 5， 6 g， and the total amount was 19.26 g. The decocting method was to crush the medicinal materials into fine powder with 50-80 mesh， add 300 mL of water and decoct to 210 mL for each dose， then remove the dregs and take it warmly. This formula was recorded in ancient books as the main treatment for the cold-deficiency of spleen and stomach， and Qi stagnation in children with vomiting and diarrhea and lack of appetite. It has been flexibly applied by later generations of physicians， and is often used to treat anorexia， inflammation of the digestive tract， diarrhea and other diseases in children.

Umbilical cord mesenchymal stem cells (UC-MSCs) have been widely used in regenerative medicine, but there is limited research on the stability of UC-MSCs formulation during production. This study aims to assess the stability of the cell stock solution and intermediate product throughout the production process, as well as the final product following reconstitution, in order to offer guidance for the manufacturing process and serve as a reference for formulation reconstitution methods. Three batches of cell formulation were produced and stored under low temperature (2-8 ℃) and room temperature (20-26 ℃) during cell stock solution and intermediate product stages. The storage time intervals for cell stock solution were 0, 2, 4, and 6 h, while for intermediate products, the intervals were 0, 1, 2, and 3 h. The evaluation items included visual inspection, viable cell concentration, cell viability, cell surface markers, lymphocyte proliferation inhibition rate, and sterility. Additionally, dilution and culture stability studies were performed after reconstitution of the cell product. The reconstitution diluents included 0.9% sodium chloride injection, 0.9% sodium chloride injection + 1% human serum albumin, and 0.9% sodium chloride injection + 2% human serum albumin, with dilution ratios of 10-fold and 40-fold. The storage time intervals after dilution were 0, 1, 2, 3, and 4 h. The reconstitution culture media included DMEM medium, DMEM + 2% platelet lysate, 0.9% sodium chloride injection, and 0.9% sodium chloride injection + 1% human serum albumin, and the culture duration was 24 h. The evaluation items were viable cell concentration and cell viability. The results showed that the cell stock solution remained stable for up to 6 h under both low temperature (2-8 ℃) and room temperature (20-26 ℃) conditions, while the intermediate product remained stable for up to 3 h under the same conditions. After formulation reconstitution, using sodium chloride injection diluted with 1% or 2% human serum albumin maintained a viability of over 80% within 4 h. It was observed that different dilution factors had an impact on cell viability. After formulation reconstitution, cultivation in medium with 2% platelet lysate resulted in a cell viability of over 80% after 24 h. In conclusion, the stability of cell stock solution within 6 h and intermediate product within 3 h meets the requirements. The addition of 1% or 2% human serum albumin in the reconstitution diluent can better protect the post-reconstitution cell viability.