ObjectiveThis study aims to systematically analyze the blood-absorbed components and metabolic profiles of Xiebaisan（XBS） in normal and chronic bronchitis （CB） mice using ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS）， while comparing differences between the two states. MethodsThirty female BABL/c mice were randomly divided into the normal group， the normal drug administration group， the CB group， the CB drug administration group and the dexamethasone group， with 6 mice in each group. The CB mouse model was established by inducing with ovalbumin （OVA）. The mice in the normal drug administration group and the CB drug administration group started to be gavaged with XBS（13.2 g·kg^-1） from the 21^st day， and the dexamethasone group mice were simultaneously gavaged with dexamethasone （0.5 mg·kg^-1） until the end of the 35^th day of the experiment. Subsequently， serum samples were collected and evaluated for their efficacy， based on the pharmacological evaluation indicators， to determine the efficacy of XBS in treating CB. Then the UPLC-Q-Exactive Orbitrap MS was employed to identify and analyze the chemical constituents， blood-absorbed components， and metabolites of XBS. Chemometric analysis was conducted to reveal metabolic profile differences under "dual states". Concurrently， Real-time PCR technology was utilized to detect the expression levels of key liver metabolic enzymes CYP2E1， CYP3A1， UGT1A1， and UGT1A6. ResultsA total of 28 prototype components and 158 metabolites （including 48 phase Ⅰ metabolites and 110 phase Ⅱ metabolites） of XBS were unambiguously identified in the serum of normal mice. Additionally， a comprehensive characterization was performed on a total of 32 prototype components and 178 metabolites （including 50 phase Ⅰ metabolites and 128 phase Ⅱ metabolites） of XBS in the serum of CB mice. Among them， 27 prototype components were detected in both states， including 12 flavonoids， 2 alkaloids， 3 triterpenes， 4 organic acids， 3 amides， 1 stilbene and 2 other compounds. The chemometrics analysis revealed no significant difference in the prototype components and metabolites of XBS between normal and CB mice； however， there was a significant increase in the in-vivo exposure of XBS in CB mice. Compared to normal mice， the levels of phase Ⅰ metabolites such as oxidation， reduction and methylation of blood components of XBS as well as phase Ⅱ metabolites of glucuronidation showed significant changes in CB mice. Real-time PCR further confirmed that these alterations were attributed to the upregulation of CYP2E1 （P<0.05）， CYP3A1 （P>0.05）， UGT1A1 （P<0.01） and UGT1A6 （P<0.01） enzymes expression in the liver of CB mice. ConclusionThis study elucidated the disparities in the levels of the blood-absorbed components and metabolic profiles of XBS in normal and CB mice， especially in oxidation， reduction， methylation in phase Ⅰ metabolism and glucoaldehyde acidification in phase Ⅱ metabolism. And there are related to the differences in the expression levels of phase Ⅰ and phase Ⅱ metabolic enzymes CYP2E1， CYP3A1， UGT1A1 and UGT1A6 in the liver.

ObjectiveTo construct an actor-network for integrating physical activity into rehabilitation services based on the World Health Organization Rehabilitation in Health Service System framework and actor-network theory (ANT). MethodsContent analysis was employed using the six building blocks of health service systems as the theoretical framework. Actors related to rehabilitation services were extracted and categorized into a rehabilitation actor pool, while a physical activity actor pool was formed based on four major physical activity scenarios. Actors from both pools were integrated, deduplicated and classified to form a final list of integrated actors. Using ANT, the construction process of the actor network integrating physical activity into rehabilitation was analyzed through the four stages of translation: problematization, interessment, enrollment and mobilization. ResultsA dynamic integration network was constructed, comprising human actors (patients, rehabilitation professionals, researchers, sports coaches, government departments, medical institutions, community organizations and industry media, etc.) and non-human actors (assistive devices, sports infrastructure, smart equipment, information systems, online exercise guidance systems, laws and regulations, strategic documents, and exercise prescriptions, etc.). The study identified maximizing rehabilitation outcomes as the mandatory passage point and elaborated on the critical role of government departments as focal actors in coordinating various stakeholders. ConclusionThe integration of physical activity into rehabilitation services is a dynamic network constructed by diverse actors through a process of translation. ANT provides an operational theoretical framework for cross-departmental governance of rehabilitation policies in China, promotes the spatial expansion of the rehabilitation field, and drives its transformation toward a networked and ecological system. The government needs to play a leading role in facilitating role reconstruction and synergy among heterogeneous actors in both the sports and rehabilitation sectors through mechanism design, to create a bidirectional empowerment mechanism that fosters mutual progress and ensures the sustainable development of integrated services.

Objective To explore the latent profile characteristics, influencing factors of personal social capital among community-dwelling older adults and their differences in the degree of geriatric depression. Methods A cross-sectional survey was conducted among 1,026 community-dwelling older adults. Latent profile analysis was used to explore the latent profiles of personal social capital, and the predictors of different latent profiles were examined. Results Four latent profiles were identified and labeled as ^“Impoverished social capital type^”, ^“Moderate social capital type", ^“Abundant social capital type^” and ^“Extremely low bonding - extremely high bridging social capital exclusive type^”. The influencing factors included per capita monthly household income (χ²=3.500, P=0.015), whether taking long-term medication (χ²=9.587, P=0.022), whether drinking alcohol (χ²=23.942, P＜0.001), whether doing physical exercise (χ²=20.876, P＜0.001), and whether participating in social activities (χ²=40.135, P＜0.001), with statistically significant differences. Community-dwelling older adults with low frequency of physical exercise, low frequency of social participation and not taking long-term medication were more likely to belong to the ^“extremely low bonding - extremely high bridging social capital exclusive type^”. The degree of geriatric depression (F=12.385, P＜0.001), aging attitude (F=33.008, P＜0.001) and negative aging perception (F=81.481, P＜0.001) in this subgroup were relatively serious, with statistically significant differences. Conclusion The government and communities can formulate personalized intervention measures based on the influencing factors of latent profiles to effectively suppress the development of depression among community-dwelling older adults, improve aging attitudes and the positivity of aging perception, and promote healthy aging.

ObjectiveTo screen and identify the key proteins of Monkeypox Virus （MPXV） that regulate the NOD-like receptor family pyrin domain containing 3 （NLRP3） inflammasome. MethodsUsing the genomic sequence of the domestic epidemic strain of MPXV as a template to construct an expression plasmid library containing 82 viral genes. To screen for viral genes that significantly inhibit the production of interleukin-1β （IL-1β）， the expression plasmids encoding NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， cysteine protease-1（Caspase-1）， and pro-IL-1β-Luc reporter gene were co-transfected into HEK293T cells， along with the viral gene plasmids. The signal of the NLRP3 inflammasome was monitored by measuring luciferase activity in the cell supernatant. The inhibition effects were further confirmed by Western Blot （WB）， and the interactions between the viral proteins and the components of the NLRP3 inflammasome were determined by Co-immunoprecipitation （Co-IP）. Additionally， site-directed mutagenesis was performed to identify the specific interaction motifs. ResultsAn NLRP3 inflammasome signal screening system were successfully established and optimized. Screening the MPXV plasmids using this system revealed that B10R most significantly inhibits IL-1β maturation in a dose-dependent manner （P＜0.000 1）. Further characterization demonstrated that B10R interacts directly with pro-IL-1β. Notably， the C-terminal motif mutant of B10R （B10Rmut-C， T96A， Y97A， I98A） lost its ability to interact with pro-IL-1β. ConclusionsThe MPXV B10R protein interacts with pro-IL-1β， thereby inhibiting the IL-1β maturation. The C-terminal motif （T96， Y97， I98） of the B10R protein is crucial for function. This study provides important clues and a foundation for further elucidating the molecular mechanisms by which MPXV regulates the NLRP3 inflammasome.

ObjectiveTo investigate the incidence， glucolipid metabolism characteristics， and associated factors of postoperative overweight/obesity in children and adolescent with craniopharyngioma. MethodsA retrospective study was conducted using follow-up data from 44 patients （aged 0-18 years） diagnosed with craniopharyngioma who underwent surgical treatment and received follow-up care at Sun Yat-sen Memorial Hospital， Sun Yat-sen University， between January 2006 and February 2024. The incidence and glucolipid metabolism characteristics of overweight/obesity were summarized， and potential influencing factors were analyzed. ResultsA total of 44 patients were enrolled. The mean age at surgery was （8.57 ± 4.25） years， and the mean age at last follow-up was （16.02 ± 5.36 ）years. The mean follow-up duration was （7.45 ± 4.64） years （range， 8 months to 17.5 years）. The preoperative incidence of overweight/obesity was 40.91% （predominantly overweight， 27.27%）， which increased to 68.18% postoperatively （predominantly obesity， 50.00%）. Postoperatively， all patients （44/44， 100%） underwent fasting plasma glucose （FPG） testing， among whom 2 （4.55%） had impaired fasting glucose （IFG）. Fasting insulin （FINS） was measured in 20 patients， and insulin resistance was identified in 11 （55.00%）. Oral glucose tolerance testing （OGTT） with insulin release assessment was performed in 12 patients， and all （100%） exhibited abnormal insulin secretion， including 5 （41.67%） with hyperinsulinemia and 3 （25.00%） diagnosed with diabetes mellitus （DM）. All patients （44/44， 100%） underwent lipid profile assessment. The incidence of dyslipidemia was 81.82% （36/44）， including elevated non-high-density lipoprotein cholesterol （29/44， 65.91%）， hypertriglyceridemia （29/44， 65.91%）， low high-density lipoprotein cholesterol （22/44， 50.00%）， and mixed hyperlipidemia （13/44， 29.55%）. Logistic regression analysis indicated that preoperative overweight/obesity and postoperative abnormal glucose metabolism were significant factors associated with postoperative overweight/obesity. Compared with normal-weight patients， those with postoperative overweight/obesity had higher FINS levels （14.22 mU/L vs. 3.57 mU/L）， higher insulin resistance index（HOMA-IR） （2.88 vs. 0.52）， and a higher incidence of abnormal glucose metabolism （77.78% vs. 23.08%）. However， no significant difference was observed in the incidence of dyslipidemia （94.44% vs. 73.08%）. ConclusionsChildren and adolescent with craniopharyngioma exhibit a higher incidence of overweight/obesity than healthy peers preoperatively， which becomes more pronounced after surgery. This is accompanied by a high incidence of glucolipid metabolic disorders， placing these patients at increased risk of metabolic syndrome， which warrants clinical attention and regular metabolic assessment. In patients who develop postoperative obesity， particular attention should be given to the risk of glucose metabolism abnormalities， and further monitoring of glucose homeostasis is recommended.

BackgroundSchizophrenia is a highly heterogeneous disease with different clinical subtypes. Artificial intelligence technology represented by deep learning models has provided considerable benefits for the electroencephalogram （EEG）-based schizophrenia diagnosis， treatment and research， however， to date little research has been conducted regarding any of these benefits among Chinese schizophrenic patients. ObjectiveTo investigate the application of deep learning techniques utilizing EEG parameters for the diagnosis of first-episode schizophrenia and grading of EEG abnormalities in patients， with the aim of contributing to improved clinical diagnosis and treatment strategies for the disorder. MethodsFrom January 2020 to January 2023， a total of 130 patients with first-episode schizophrenia who met the diagnostic criteria of International Classification of Diseases， tenth edition （ICD-10）， and attended at the Third People's Hospital of Fuyang， along with 150 health checkup examinees， were enrolled. All of them underwent EEG examination. An optimized long short-term memory （LSTM） deep learning model was developed utilizing EEG signals. Ten-fold cross-validation method was employed to evaluate the model's performance. The dataset was then split into two components： a training set （90%） for LSTM model development and a test set （10%） for validation. The accuracy， recall rate， precision， F1-score， schizophrenia diagnosis and EEG abnormality grading were used as evaluation indicators， and the results of the proposed model were compared to the assessments made by experienced psychiatrists. ResultsFor schizophrenia diagnosis， the modeling group achieved the following performance metrics： precision （94.40±3.03）%， recall rate （94.30±3.23）%， accuracy （94.60±2.22）%， and F1-score （94.20±2.20）%. In the validation group， the corresponding metrics were precision （90.90±2.85）%， recall rate （92.20±1.14）%， accuracy （92.20±1.69）%， and F1-score （91.50±1.78）%. Statistical analysis revealed no significant differences between the LSTM diagnostic model and the experienced psychiatrists in terms of precision， recall rate， accuracy， and F1-score for schizophrenia diagnosis （χ²=1.500， 0.750， 2.722， 1.056， P>0.05）. The modeling group demonstrated an accuracy rate of （91.71±1.73）% in grading EEG abnormalities. For Grade 1 abnormalities， the modeling group reported a precision of （96.40±2.39）%， a recall rate of （94.77±1.40）%， and an F1-score of （95.55±1.14）%. In the case of Grade 2 abnormalities， the precision was （85.89±2.04）%， the recall rate was （88.10±6.18）%， and the F1-score was （87.06±3.12）%. For the more severe Grade 3 abnormalities， the modeling group's precision was （79.61±7.33）%， the recall rate was （81.79±9.87）%， and the F1-score was （80.41±6.79）%. Additionally， the validation group exhibited an accuracy rate of （85.61±6.16）%. The precision， recall rate， and F1-score for Grade 1 abnormalities were （91.43±6.25）%， （92.64±9.65）% and （91.56±4.83）%， respectively. For Grade 2 abnormalities， these metrics were （71.17±19.02）%， （77.64±17.24）% and （71.88±11.33）%. In the case of Grade 3 abnormalities， the precision was （90.00±21.08）%， the recall rate was （80.00±25.82）%， and the F1-score was （81.67±19.95）%. There was no significant difference in the accuracy， recall， accuracy and F1 value between LSTM model and senior doctors in evaluating the abnormal degree of EEG in schizophrenia （χ²=0.098， 0.036， 0.020， 0.336， P>0.05）. The LSTM model takes less time to diagnose schizophrenia and EEG abnormalities than senior doctors， and the differences were statistically significant （t=57.147， 43.104， P<0.01）. ConclusionThe study utilizes an EEG-based LSTM deep learning model for diagnosing first-episode schizophrenia and grading EEG abnormalities， and the model not only matches the performance of experienced psychiatrists but also significantly reduces the time required for diagnosis.

This study investigated the regulatory potential of salidroside (SAL), a primary active compound in Rhodiola rosea L., on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha (HIF-1a) pathway in osteoblasts. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were employed to validate whether the receptor activator of nuclear factor-?B ligand (RANKL) is the downstream target gene of HIF-1a in osteoblasts. The study also utilized lipopolysaccharide (LPS)-induced mouse osteolysis to examine the impact of SAL on osteolysis in vivo. Furthermore, conditioned medium (CM) from SAL-pretreated osteoblasts was used to investigate the paracrine effects on osteoclastogenesis through the HIF-1a pathway. Hypoxic condition-induced overexpression of HIF-1a upregulated RANKL levels by binding to the RANKL promoter and enhancing transcription in osteoblastic cells. In vivo, SAL significantly alleviated bone tissue hypoxia and decreased the expression of HIF-1a by downregulating the expression of RANKL, vascular endothelial growth factor (VEGF), interleukin 6 (IL-6), and angiopoietin-like 4 (ANGPTL4). In the paracrine experiment, conditioned media from SAL-pretreated osteoblasts inhibited differentiation through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. RANKL emerges as the downstream target gene regulated by HIF-1a in osteoblasts. SAL significantly alleviates bone tissue hypoxia and bone loss in LPS-induced osteolysis through the HIF-1a/RANKL, VEGF, IL-6, and ANGPTL4 pathways. SAL inhibits osteoclast differentiation by regulating osteoblast paracrine secretion.
Animals ; Osteoblasts/cytology* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Glucosides/administration & dosage* ; Cell Differentiation/drug effects* ; Phenols/administration & dosage* ; Mice ; Osteoclasts/metabolism* ; RANK Ligand/genetics* ; Rhodiola/chemistry* ; Osteogenesis/drug effects* ; Signal Transduction/drug effects* ; Interleukin-6/genetics* ; Male ; RAW 264.7 Cells ; Osteolysis/genetics* ; Humans ; Mice, Inbred C57BL

Objective To explore the potential clinical value of the ratio of glycated albumin to albumin(GA/ALB)in the occurrence of heart failure(HF)among patients with coronary atherosclerotic heart disease(CHD).Methods A total of 337 CHD patients admitted to the Department of Cardiology in Shanxi Provincial People's Hospital from July 2023 to June 2024 were selected in this study.CHD patients were divided into HF group and non-HF group based on whether they progressed to HF.The clinical data and laboratory parame-ters of the two groups were compared.Restricted cubic spline curve was used to analyze the relationship be-tween GA/ALB levels and the risk of HF in CHD patients.Receiver operating characteristic curve was applied to evaluate the diagnostic efficacy of GA/ALB,GA,platelet to lymphocyte ratio(PLR),and monocyte to lym-phocyte ratio(MLR)in CHD patients with the occurrence of HF.Logistic regression was used to explore the relationship between serum GA/ALB levels and the risk of CHD patients occurrence of HF,and to analyze the degree of influence and stability of subgroup variables on results.Results There were statistically significant differences in GA/ALB,GA,PLR,MLR,and other indicators between the HF group and the non-HF group in CHD patients(P＜0.05).A non-linear relationship was observed between GA/ALB levels and the risk of HF in CHD patients.When the value of GA/ALB multiplied by 10 was less than 5.751,the risk of HF in CHD pa-tients increased with the increase of GA/ALB levels(P＜0.001).GA/ALB was an effective predictor for HF occurrence in CHD patients.Multivariable Logistic regression model showed that GA/ALB was an independ-ent risk factor for CHD patients with occurrence of HF.Subgroup analysis also confirmed the stability of GA/ALB in predicting the occurrence of HF in CHD patients.Conclusion GA/ALB is an independent risk factor for the occurrence of HF in CHD patients,and monitoring GA/ALB levels provides predictive value for the oc-currence of HF in these patients.

Hypoxia-related diseases,such as altitude sickness,acute lung injury,and heart failure,have emerged as significant public health challenges worldwide and are strongly associated with increased mortality risks.These conditions tend to cause functional impairment and structural alterations in multiple organs,primarily due to inadequate oxygen supply or the inability of tissues to utilize oxygen effectively.To elucidate the pathophysiological mechanisms underlying hypoxia-associated diseases and to explore potential therapeutic strategies,researchers have employed animal models to conduct extensive mechanistic studies and drug development trials.In this review,we provide a comprehensive overview of the methods used to construct animal models for various hypoxia-related diseases.We made a thorough evaluation of the strengths,weaknesses,limitations,and applicability of each approach.In particular,we focus on modeling strategies for key pathologies such as altitude sickness,acute lung injury,pulmonary hypertension,and heart failure,discussing their respective advantages and restrains.Furthermore,we examined the potential application of gene editing technologies in optimizing animal models,especially its role in enhancing the accuracy and reproducibility of the models.The integration of these advanced technologies holds great promise for developing animal models with improved specificity and simulation of key features of diseases,which will serve as a solid foundation for basic research,drug screening,and preclinical trials concerning hypoxia-related diseases.Herein,we present a systematic summary and future outlook of animal models for hypoxia-related diseases,ultimately providing theoretical support for developing clinical treatment strategies and improving patient outcomes.

Objective To investigate the clinical and radiological features of patients with different phenotypes of multiple system atrophy （MSA）. Methods A total of 400 patients with MSA who attended the outpatient service or were hospitalized in Department of Neurology，Chinese PLA General Hospital，were enrolled，among whom there were 294 patients with MSA-cerebellar type （MSA-C） and 106 patients with MSA-Parkinsonian type （MSA-P）. The t-test and the chi-square test were used to analyze the clinical manifestations，radiological features，and blood biochemical indicators of the two groups. Results As for clinical manifestations，there were significant differences in cerebellar symptoms，constipation，and Babinski sign between MSA-C patients and MSA-P patients （P<0.05）. As for radiological features，positron emission tomography/computed tomography （PET/CT） showed that MSA-P patients had a typical reduction in DAT uptake in the putamen and the caudate nucleus，while magnetic resonance imaging showed that compared with the MSA-C group，the MSA-P group had a significantly higher proportion of patients with putamen fissure sign or white matter demyelination； for MSA-C patients，PET/CT showed cerebellar hypometabolism，and magnetic resonance imaging showed the cross sign and high signal intensity in the pontine arm，as well as a significantly higher proportion of patients cerebellar and pontine atrophy than MSA-P patients （P<0.05）. As for laboratory markers，MSA-P patients had a significantly lower level of uric acid than MSA-C patients （P=0.029）. Conclusion Patients with different subtypes of MSA have specific clinical features，radiological features，and uric acid level，which has a certain significance in the accurate diagnosis of MSA.