ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

Objective: To explore the association of vegetables and fruits intake with depressive symptoms among multi ethnic first year junior high school students in Yunnan Province, so as to provide data support for preventing and reducing depressive symptoms among first year junior high school students. Methods: From October to December 2022, a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas in Yunnan Province (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County), to investigate with a questionnaire. The Dietary Frequency Questionnaire was used to collect dietary behavior datas, and the Chinese version of Depression Anxiety Stress Scale-21 (DASS-21) was used to assess depressive symptoms. The generalized linear model was used to analyze the association of vegetable and fruit intake with depressive symptoms in students, and stratified analysis was performed according to ethnicity. Results: The detection rate of depressive symptoms among first year junior high school students in Yunnan Province was 29.5%. The detection rates of depressive symptoms in Han and minority first year junior high school students were 26.9% and 31.6%. After controlling for demographic variables such as gender, age, family residence and other confounding factors, the generalized linear model analysis results showed that the intake of leafy vegetables ( β= -0.07 , 95%CI =-0.12 to -0.01), flat fruits ( β=-0.06, 95%CI =-0.12 to -0.00) and hot natured fruits ( β=0.11, 95%CI = 0.04- 0.17) were associated with depressive symptoms in Han first year junior high school students (all P <0.05). The intake of melon and fruit vegetables ( β=-0.06, 95%CI =-0.11 to -0.01) and hot natured fruits ( β=0.06, 95%CI =0.01-0.12) were associated with depressive symptoms in ethnic minority first year junior high school students (both P <0.05). Conclusions The intake of vegetables and fruits among multi ethnic first year junior high school students in Yunnan Province is related to the risk of depressive symptoms. It is suggested to strengthen the consumption guidance and education of vegetables and fruits to prevent depressive symptoms among first year junior high school students.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

Systemic lupus erythematosus （SLE）， a refractory autoimmune disease， is among the dominant diseases where traditional Chinese medicine （TCM） shows advantages in the field of rheumatology and immunology. The China-Japan Friendship Hospital hosted the "46^th Youth Salon on Dominant Diseases （Systemic Lupus Erythematosus）" organized by the China Association of Chinese Medicine， which led to a consensus on "the advantages， challenges， interdisciplinary approaches， and translational achievements of integrated TCM and Western medical approaches in the diagnosis and treatment of SLE." The diagnosis and treatment of SLE currently face several challenges， such as frequent misdiagnosis and missed diagnosis in the early stages， difficulty in achieving treatment targets， multiple side effects from pharmacotherapy， and the lack of management strategies for special populations， all of which hinder the fulfillment of the clinical needs of patients. Integrated TCM and Western medical approaches can improve clinical symptoms such as skin erythema， aversion to cold and cold limbs， fatigue， dry mouth， restlessness， and heat sensation in the palms and soles， thereby improving patients' quality of life. The approaches also help consolidate the efficacy of conventional Western medicine， slow disease progression， reduce relapse rates， address multi-organ involvement， and prevent or treat complications. Additionally， they enhance efficacy and reduce toxicity， prevent the side effects of Western medications， help reduce hormone use， and offer distinct advantages in the individualized intervention of special populations， contributing to the whole-process management of the disease. However， evidence-based medical support for this integrated approach remains limited， and the quality of available evidence is generally low. Common evaluation systems and modern research methodologies should be adopted to clarify the efficacy of TCM in SLE treatment. Efforts should be made to carry out high-quality evidence-based medical research， strengthen the development of fundamental and pharmacological research， and further explain the distinct advantages of TCM in the diagnosis and treatment of SLE. Future efforts should focus on advancing the integration of TCM and modern medicine， incorporating multi-omics technologies， individualized stratification， and other precision medicine concepts， in combination with artificial intelligence. Moreover， interdisciplinary collaboration should be promoted to utilize modern technology in exploring the essence of TCM theories and screening effective formulae， thereby comprehensively improving the diagnosis and treatment of SLE through integrated TCM and Western medical approaches.

Mitochondrial dysfunction is a critical factor in the pathogenesis of Alzheimer's disease (AD). The mitochondrial contact site and cristae organizing system (MICOS) plays a pivotal role in shaping the inner mitochondrial membrane, forming cristae junctions and establishing interaction sites between the inner and outer mitochondrial membranes and thereby serving as a cornerstone of mitochondrial structure and function. In the past decade, MICOS abnormalities have been extensively linked to AD pathogenesis. In particular, dysregulated expression of MICOS subunits and mutations in MICOS-related genes have been identified in AD, often in association with hallmark pathological features such as amyloid-β plaque accumulation, neurofibrillary tangle formation, and neuronal apoptosis. Furthermore, MICOS subunits interact with several etiologically relevant proteins, significantly influencing AD progression. The intricate crosstalk between these proteins and MICOS subunits underscores the relevance of MICOS dysfunction in AD. Therapeutic strategies targeting MICOS subunits or their interacting proteins may offer novel approaches for AD treatment. In the present review, we introduce current understanding of MICOS structures and functions, highlight MICOS pathogenesis in AD, and summarize the available MICOS-targeting drugs potentially useful for AD.

Objective To investigate the research competency among undergraduate interns of rehabilitation therapy.Methods In July,2024,a total of 81 undergraduate rehabilitation therapy interns from Department of Rehabilitation Medicine,Guangdong Provincial People's Hospital were self-rated the research competency,using research com-petency and activities,level 1 of World Health Organization rehabilitation competency framework.Semi-struc-tured interviews were conducted to investigate the willingness and difficulties to participate in research.Results The self-rated competencies were the lowest in behavior of C2.3 Assists in assessing rehabilitation service user needs and priorities for research,and Activity of A2 Disseminating evidence.For interviews,72 students would participate in researches,primarily motivated by career advancement and postgraduate admission competition.The main difficulties included insufficient faculty mentorship(n=48),limitation in knowledge(n=43)and diffi-culties in formulating scientific questions(n=43).Conclusion Most rehabilitation therapy undergraduates would like to participate in researches,but are suboptimal in re-search competency due to personal and environmental constraints.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Objective:To investigate the effects of long non coding RNA KCNQ1OT1(LncRNA KCNQ1OT1)on the migration and invasion of oral squamous cell carcinoma(OSCC)cells by regulating the microRNA-875-5p(miR-875-5p)/ETS like transcription factor 4(ELK4)axis.Methods:QRT-PCR was applied to detect the mRNA levels of LncRNA KCNQ1OT1,miR-875-5p,and ELK4 in OSCC cell lines(HSC-3,PE/CA-PJ15,HN13)and tissues.The dual luciferase assay was applied to detect the targeting relationship between LncRNA KCNQ1OT1 and miR-875-5p,and target relationship between miR-875-5p and ELK4.HSC-3 cells were used in control group,sh-NC group,sh-KCNQ1OT1 group,sh-KCNQ1OT1+anti-NC group,sh-KCNQ1OT1+anti-miR-875-5p group,miR-NC group,miR-875-5p mimic group,miR-875-5p mimic+pcDNA-NC group,and miR-875-5p mimic+ELK4 group.The migration and invasion abilities of HSC-3 cells were detected.Immunoblotting was applied to detect the protein expression of ELK4,MMP-2,MMP-9 and epithelial mesenchymal transition(EMT)(E-Cadherin,N-Cadherin,Vimentin).The nude mouse transplant tumor was applied to verify the effect of LncRNA KCNQ1OT1 on OSCC transplant tumors.Results:LncRNA KCNQ1OT1 and ELK4 mRNA expression increased in OSCC tissues and cancer cell lines,while miR-875-5p expression decreased(P＜0.05).Database predictions show that miR-875-5p specifically bound to LncRNAs KCNQ1OT1 and ELK4,respectively.Compared with the sh-NC group,the numbers of cell migration and cell invasion,the expression of LncRNA KCNQ1OT1,ELK4,MMP-2,MMP-9,N-Cadherin,and Vimentin in the sh-KC-NQ1OT1 group were lower,while the expression of miR-875-5p and E-Cadherin was higher(P＜0.05).Compared with the sh-KC-NQ1OT1+anti-NC group,the expression of miR-875-5p and E-Cadherin in the sh-KCNQ1OT1+anti-miR-875-5p group was lower,while the numbers of cell migration and cell invasion,the expression of ELK4,MMP-2,MMP-9,N-Cadherin,and Vimentin were higher(P＜0.05).Compared with the miR-NC group,the expression of miR-875-5p and E-Cadherin in the miR-875-5p mimic group was higher,while the numbers of cell migration and cell invasion,the expression of ELK4,MMP-2,MMP-9,N-Cadherin,and Vim-entin were lower(P＜0.05).Compared with the miR-875-5p mimic+pcDNA-NC group,the numbers of cell migration and cell inva-sion,the expression of ELK4,MMP-2,MMP-9,N-Cadherin,and Vimentin in the miR-875-5p mimic+ELK4 group were higher,while the expression of E-Cadherin was lower(P＜0.05).The transplant tumor volume and weight of the sh-KCNQ1OT1 group were smaller than those of the sh-NC group,the mRNA and protein expression levels of LncRNA KCNQ1OT1,ELK4 were lower than those of the sh-NC group,and the expression level of miR-875-5p was higher than that of the sh-NC group(P＜0.05).Conclusion:Inhibition of LncRNA KCNQ1OT1 can target the miR-875-5p/ELK4 axis to inhibit migration,invasion,and EMT of OSCC cells.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Background: Influenza A viruses (IAVs) are the major pathogens associated with respiratory infections which can result in extensive pathological damage in lungs and serious complications. Isorhamnetin, an abundant natural flavonoid in fruits and medicinal plants, has recently been shown to have strong antioxidative, anti-inflammatory, and antiviral effects. Objective: This study investigated the pharmacological effects of isorhamnetin on viral pneumonia and explored the underlying mechanisms by in vivo and in vitro experiments. Materials and methods: In the present study, the protective effect of isorhamnetin against IAV was evaluated by the cytopathogenic effect assay, cell counting kit-8 assay, real-time polymerase chain reaction, and immunofluorescence assay in vitro. Then the pathological damage associated with pneumonia was examined by calculating the pulmonary index and performing micro-CT and hematoxylin-eosin staining in vivo. Thereafter, the related protein or gene levels of factors in the mitogen-activated protein kinase (MAPK) and nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) signaling pathways were determined by Western blot and immunofluorescence staining. Results: Isorhamnetin exerted significant anti-influenza effects and inhibited the expression of viral RNA in A549 cells, counteracting oxidative stress and apoptosis by suppressing the production of reactive oxygen species and caspase-3. The in vivo experiment results showed that isorhamnetin (20 and 40 mg/kg) caused a significant decrease in the pulmonary index, ameliorated pathological damage in the lung tissue, decreased viral load and NA activity, and reduced cytokines and nuclear factors. Furthermore, isorhamnetin could counteract the B cell lymphoma-2/B cell lymphoma-2–associated X protein (Bax) imbalance induced by PR8, suppress activation of the MAPK pathway, and upregulate the expression of Nrf2 and HO-1. Conclusions: Isorhamnetin can protect against viral pneumonia by activating the Nrf2/HO-1 pathway and suppressing the MAPK path-way. This study deciphers the pharmacological mechanism of isorhamnetin in alleviating pathological damage in viral pneumonia and provides rationale for the application of isorhamnetin in influenza treatment.