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.

ObjectiveTo investigate the effects of Schisandrae Chinensis Fructus lignans on schizophrenia induced by dizocilpine maleate （MK-801） in mice and to clarify its mechanism. MethodsMale mice of 4-6 weeks old were randomized into blank， model， positive drug， and low-， medium-， and high-dose （40， 80， 160 mg·kg^-1， respectively） Schisandrae Chinensis Fructus lignans groups. The blank group was administrated with distilled water， and the other groups were injected with 0.5 mg·kg^-1 MK-801 to induce schizophrenia symptoms. Meanwhile， risperidone was injected at 0.2 mg·kg^-1 in the positive drug group， and mice in the intervention groups were injected with corresponding drugs for 14 consecutive days. The behavioral changes of mice were observed by autonomous activity test， open field test， forced swimming test， and water maze test. The levels of dopamine （DA） and 5-hydroxytryptamine （5-HT） in the brain and tumor necrosis factor-α （TNF-α） and nuclear factor-κB （NF-κB） in peripheral blood were quantified by enzyme-linked immunosorbent assay （ELISA）. The changes in the prefrontal lobe of mice were observed by hematoxylin-eosin staining， and the changes of the hippocampal tissue were observed by Nissl staining. The protein levels of silencing information regulatory factor 1 （SIRT1） and forkhead box protein O3a （FoxO3a） in the hippocampus of mice were determined by Western blot. ResultsCompared with the model group， low， medium， and high doses of Schisandrae Chinensis Fructus lignans reduced the total number of autonomous activities， total distance in the open field test， immobile time in the forced swimming test， and levels of TNF-α and NF-κB in peripheral blood （P<0.05）， while increasing the number of platform crossings in the water maze test and DA and 5-HT levels in the brain tissue （P<0.05）. Compared with the model group， risperidone and low， medium， and high doses of Schisandrae Chinensis Fructus lignans improve the neural cell morphology in the CA1 region， with full cells in neatly dense arrangement and exhibiting clear membrane boundary. Schisandrae Chinensis Fructus lignans inhibited the expression of SIRT 1 and FoxO3a in the hippocampus （P<0.05）. ConclusionTo sum up， Schisandrae Chinensis Fructus lignans may improve the behavior of schizophrenic mice by activating the SIRT1/FoxO3a signaling pathway to exert neuroprotective effects.

ObjectiveThis study aims to elucidate the potential mechanism of Zuojinwan in improving liver fibrosis through hepatic tissue metabolomics analysis. MethodsTwenty-four mice were randomly allocated into normal group， model group ， positive drug group （silymarin， 100 mg·kg^-1）， and Zuojinwan group （Zuojinwan solution， 2.5 g·kg^-1）， with per group six mice. Liver fibrosis model was induced via intraperitoneal injection of olive oil solution with 10% carbon tetrachloride （CCl₄） （0.5 μL·g^-1， three times weekly for 8 weeks） in all groups except the normal group. During the final 4 weeks， the silymarin group received silymarin （100 mg·kg^-1） by gavage thrice weekly， while the Zuojinwan group was administered Zuojinwan solution （2.5 g·kg^-1） under the same regimen. After the last administration， the levels of liver fibrosis indicators and liver injury markers in serum were detected. The pathological morphological changes of the liver tissues were observed. The levels of liver fibrosis markers α-smooth muscle actin （α-SMA） and Collagen Ⅰ（ColⅠ） were detected. Metabolomics was analyzed on mice's liver tissues. The mice's serum was collected for metabolomics analysis. ResultsCompared with the model group， Zuojinwan significantly improved indicators related to liver fibrosis and liver injury. Compared with the normal group， the model group showed significantly elevated levels of fibrosis markers such as laminin （LN）， hyaluronic acid （HA）， procollagen typeⅢ （PC-Ⅲ）， and type Ⅳ Collagen （Ⅳ-C）， while liver injury indicators such as alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， alkaline phosphatase （ALP）， lactate dehydrogenase （LDH）， and total bilirubin （TBIL）， exhibited a marked upward trend （P<0.05）. Compared with the model group， the silymarin group showed a significant decrease in the aforementioned indicators （P<0.05）. Notably， compared with the model group， the Zuojinwan group exhibited a significant reduction in all these indicators （P<0.05）， with efficacy comparable to that of the silymarin group. Zuojinwan reduced mRNA and protein levels of α-SMA and ColⅠ in the liver tissue. Metabolomics results revealed that compared with the model group， Zuojiinwan significantly reduced levels of glucose metabolism-related metabolites such as D-fructose 1，6-bisphosphate （FBP）， nicotinamide adenine dinucleotide phosphate （NADPH）， sodium beta-D-fructose 6-phosphate （F6P）， dihydroxyacetone phosphate （DHAP）， fumaric acid， and D-glucose 6-phosphate （G6P） （P<0.05）. Serum enzyme-linked immunosorbent assay （ELISA） was used to detect glucose metabolism indicators and further validate the regulatory effect of Zuojinwan on glucose metabolism. ConclusionThese results suggest that Zuojinwan may improve liver fibrosis by regulating the dysregulated levels of glucose metabolism during the progression of liver fibrosis.

By systematically reviewing the concept evolution of pre-chronic obstructive pulmonary disease （pre-COPD） and the research status of traditional Chinese medicine （TCM）， as well as considering the clinical practice， this paper puts forward the strategies for the prevention and treatment of pre-COPD with TCM. These strategies include identifying high-risk groups by combining TCM syndrome and constitution， advocating the principle of "treating disease before it arises" and promoting the combination of syndrome differentiation and constitution evaluation to achieve individualized intervention， promoting collaboration between TCM and western medicine， supported by digital and intelligent technologies， to establish a whole-process management mode of "hospital-community-family". The aim is to realize the early diagnosis， early intervention and whole-process management of pre-COPD， thereby helping reduce the incidence of COPD.

The ethical review of clinical research involving mental disorders in the ethical governance of scientific and technological has obvious particularities， especially in the field of artificial intelligence and brain-computer interfaces which are reflected in the impact on mental autonomy， the impaired informed consent ability of participants with severe mental disorders in research， and other aspects. In addition， the stigma of illness， the use of placebo， and psychological assessment methods in clinical research have also drawn attention to the ethical review of psychiatry. In 2020， the Beijing Municipal Health Commission issued the Guidelines for Ethical Review of Clinical Research Involving Mental Disorders （Guidelines）. Shen Yucun’s Psychiatry， compiled in 2023， revised the application of the Guidelines in the context of ethical governance. An analysis was conducted on the purpose and significance of its issuance and revision， its scope of application， the principal responsibility of ethical review in medical and health institutions， and the key content of ethical review in psychiatry， to improve the quality of ethical review in clinical research involving mental disorders and promote the standardized development of clinical research in psychiatry.

As biological sample biobanks progressively demonstrate their significant value in the field of biomedical research， they also pose challenges to existing social norms and ethical rules， making the normative issue of informed consent of participants highly concerned. The current research has insufficient exploration of informed consent in the collection， preservation， utilization， and other links of the sample. In response to the complexity and diversity of each link， it is advocated to refine informed consent strategies to ensure comprehensive protection of participants’ rights and interests. Given the continuity and dynamism of informed consent， it is recommended to establish a flexible review mechanism to address changes in research content， increased risks， and changes in participant capabilities， ensuring the ethical legitimacy of the research and the autonomy in making decisions of participants. Meanwhile， it is emphasized to fully confirm informed consent before sample entry into the bank， adopt suitable consent forms for outbound utilization and waste disposal， and pay special attention to ethical and legal issues related to human genetic resources.

Objective·To develop a nomogram prediction model and an online risk calculator,and to predict the continence of patients after robot-assisted laparoscopic radical prostatectomy(RARP).Methods·A total of 604 prostate cancer patients who underwent RARP and had preoperative prostate magnetic resonance imaging at the Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine from September 2022 to December 2024 were analyzed and included.All patients were randomly resampled and divided into a training set(n=420)and a validation set(n=184)at a ratio of 7∶3.The patients'continence was followed up every month from the first month after the operation.The least absolute shrinkage and selection operator(LASSO)model was applied to screen the features.A Logistic multivariate regression analysis was used to establish a prediction model integrating the features selected from the LASSO analysis.The receiver operator characteristic(ROC)curve was drawn to predict the recovery of continence in patients after RARP,and the areas under the curve were compared by the DeLong test to evaluate the discrimination of the model.Calibration curves and decision curve analysis(DCA)were used to evaluate the calibration and clinical utility the model.Results·According to the postoperative continence follow-up data of the patients,the continence rate of the patients at 3 months after the operation was 58.28%(352/604).The length of the membranous urethra,the thickness of the right levator ani muscle,and blood loss were identified as independent predictors of early postoperative(3-month)incontinence by Logistic multivariate regression analysis of the training set.The area under the ROC curve was calculated as 0.976(0.954,0.998)for the training set and 0.977(0.945,1.000)for the validation set,demonstrating good discrimination of this model.No significant difference between the ROC curves of the training set and the validation set was confirmed by the DeLong test(P=0.949).A good goodness of fit of this model was demonstrated by the Hosmer-Lemeshow test(P=0.179).The clinical utility of the nomogram prediction model was indicated by the DCA plot.This nomogram prediction model was incorporated into an online calculator(https://yitingd.shinyapps.io/DynNomapp).Conclusion·This study developed and validated a nomogram prediction model that can effectively predict the early continence of patients after RARP.The length of the membranous urethra,the thickness of the right levator ani muscle,and the intraoperative blood loss are significant independent predictors of early postoperative incontinence.

Precision management of breast cancer is essential for improving patient outcomes.Radiomics enables high-throughput extraction of quantitative imaging features that reflect tumor biological behavior and heterogeneity from medical imaging data.With the rapid advancement of artificial intelligence(AI),particularly deep learning,feature extraction capability and model performance in radiomics have been significantly enhanced.Based on multimodal imaging modalities such as MRI,ultrasound and mammography,AI-and radiomics-based models can address key clinical challenges including tumor diagnosis,staging,molecular subtype prediction and therapeutic response assessment,thereby facilitating precision breast cancer care.This review summarizes recent advances in AI-driven radiomics for breast cancer diagnosis and treatment and discusses future application prospects and challenges toward clinical translation.

Purpose To evaluate the diagnostic value of 18F-fluorodeoxyglucose(18F-FDG)PET/CT in differentiating primary lung cancer(PLC)from metastatic pulmonary breast cancer in breast cancer patients with solitary pulmonary lesion(SPL).Materials and Methods This retrospective analysis included 58 breast cancer patients with SPL in the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2015 to August 2024.All patients had pathologically confirmed breast cancer with SPL and underwent PET/CT scans,including 36 cases of PLC and 22 cases of metastatic pulmonary breast cancer.Differences in clinical pathological features,high resolution CT morphological,and PET metabolic characteristics were analyzed.Multivariate Logistic regression was utilized to investigate independent predictive factors for SPL diagnosis.Results Statistically significant differences were observed between lesion density,nodule-lung interface,bubble sign,vascular convergence sign and pleural indentation sign(χ2=9.420,7.000,8.487,all P<0.05).PET/CT metabolic analysis revealed a significant difference in maximum standardized uptake value(SUVmax)between the two groups(Z=4.613,P<0.001).Multivariate analysis showed that bubble sign,pleural indentation sign and lower SUVmax were independent predictors for PLC.With an SUVmax threshold of 2.5,the area under the receiver operating curve(AUC)was 0.862,with a sensitivity of 90.9%,specificity of 77.8%and an accuracy of 82.8%.Combined analysis of high resolution CT and SUVmax demonstrated the highest diagnostic efficacy,with an area under the curve of 0.937,sensitivity of 90.9%,specificity of 94.4%and accuracy of 93.1%.Conclusion The presence of bubble sign,pleural indentation and SUVmax<2.5 suggests a high likelihood of PLC.Combined high resolution CT imaging features and PET metabolic characteristics significantly improve diagnostic accuracy for SPLs in breast cancer patients.

With the rapid development of artificial intelligence （AI） technology， the ethical governance of AI has gained increasing attention. The Recommendation on the Ethics of Artificial Intelligence was issued by the United Nations Educational， Scientific and Cultural Organization in 2021， which clarified several principles for the ethical governance of AI. In the field of rehabilitation medicine， the research and application of AI technology have significantly improved patients’ quality of life and survival. However， due to the specificity of the service population in rehabilitation medicine， which is mostly for the sick， injured， disabled， and elderly， a series of complex ethical issues have also arisen. This paper analyzed in detail the ethical issues and challenges encountered in the research and application of AI technology in the field of rehabilitation medicine from various aspects， such as informed consent， security of privacy and data， patients’ physical and mental rehabilitation， compliance regulation， protection of specific groups， and promotion of equity. According to the principles of the Recommendation on the Ethics of Artificial Intelligence and others， response strategies were proposed， including multi-party collaboration and interdisciplinary cooperation， improving and refining relevant laws and regulations， strengthening ethical education across society， establishing accountability mechanisms， increasing investment， promoting equity， and other measures， to promote the healthy development of research and application of AI technology in the field of rehabilitation， as well as benefit humanity.