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 investigate the improvement effects and mechanism of Xiangsha yiwei tang on gastric mucosal injury in rats with chronic atrophic gastritis （CAG）. METHODS Rats were randomly assigned into normal control group， model group， Xiangsha yiwei tang low-， medium- and high-dose groups （6， 12， 18 g/kg， calculated by crude drug）， and high-dose group of Xiangsha yiwei tang+740 Y-P [Xiangsha yiwei tang 18 g/kg+transforming growth factor β1/phosphatidyl inositol 3 kinase/ protein kinase B（TGF-β1/PI3K/Akt） pathway activator group 740 Y-P 10 mg/kg]， with 18 rats in each group. Rats in each group were administered the corresponding drugs via oral gavage or injection， once daily， for 4 consecutive weeks. Gastric mucosal blood flow， the levels of serum gastrointestinal hormones [including motilin （MTL）， gastrin （GAS）， and pepsinogen （PP）]， as well as inflammatory cytokines [including tumor necrosis factor- α （TNF- α）， interleukin-1β （IL-1β）， IL-6] in rats were measured. Pathological damage to gastric mucosal tissue was observed in rats； the apoptotic rate of gastric mucosal cells was detected. The expressions of TGF-β1/PI3K/Akt signaling pathway-related proteins and apoptosis-related proteins [including B-cell lymphoma-2 （Bcl-2） and Bcl-2-associated X protein （Bax）] in the gastric mucosal tissues of rats were assessed. RESULTS Compared with normal control group， model group had abnormal gastric mucosal tissue structure， with shedding of gastric mucosal epithelial cells， and prominent infiltration of inflammatory cells. Gastric mucosal blood flow， the serum levels of MTL， GAS， PP， and Bcl-2 protein expression were lowered significantly， while serum levels of TNF-α， IL-1β and IL-6， apoptosis rate， protein expressions of Bax and TGF-β1， the phosphorylations of PI3K and Akt were increased significantly （P＜0.05）. Compared with model group， Xiangsha yiwei decoction groups exhibited attenuated histopathological injuries in gastric mucosal tissues， reduced inflammatory cell infiltration， and significant improvements in the aforementioned quantitative parameters （P＜0.05）. Compared with high-dose group of Xiangsha yiwei tang， high-dose group of Xiangsha yiwei decoction combined with 740 Y-P exhibited significantly aggravated histopathological injuries in gastric mucosal tissues， and the aforementioned quantitative parameters were markedly reversed （P＜0.05）. CONCLUSIONS Xiangsha yiwei tang can alleviate gastric mucosal damage in CAG rats， and its mechanism of action is related to the inhibition of TGF-β1/PI3K/Akt signaling pathway.

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.

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

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.

Humans ; Spinal Fractures/etiology* ; Fractures, Compression/etiology* ; Osteoporotic Fractures/complications* ; Vertebroplasty/adverse effects* ; Bone Diseases, Metabolic/complications* ; Punctures/adverse effects* ; Treatment Outcome ; Bone Cements ; Retrospective Studies