ObjectiveTo establish an ultra-performance liquid fingerprint and multi-components determination method for Naomaili granules. To evaluate the quality of different batches by chemometrics， and the anti-neuroinflammatory effects of water extract and main components of Naomaili granules were tested in vitro. MethodsThe similarity and common peaks of 27 batches of Naomaili granules were evaluated by using Ultra performance liquid chromatography （UPLC） fingerprint detection. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） technology was used to determine the content of the index components in Naomaili granules and to evaluate the quality of different batches of Naomaili granules by chemometrics. LPS-induced BV-2 cell inflammation model was used to investigate the anti-neuroinflammatory effects of the water extract and main components of Naomaili granules. ResultsThe similarity of fingerprints of 27 batches of samples was > 0.90. A total of 32 common peaks were calibrated， and 23 of them were identified and assigned. In 27 batches of Naomaili granules， the mass fractions of 14 components that were stachydrine hydrochloride， leonurine hydrochloride， calycosin-7-O-glucoside， calycosin，tanshinoneⅠ， cryptotanshinone， tanshinoneⅡ_A， ginsenoside Rb₁， notoginsenoside R₁， ginsenoside Rg₁， paeoniflorin， albiflorin， lactiflorin， and salvianolic acid B were found to be 2.902-3.498， 0.233-0.343， 0.111-0.301， 0.07-0.152， 0.136-0.228， 0.195-0.390， 0.324-0.482， 1.056-1.435， 0.271-0.397， 1.318-1.649， 3.038-4.059， 2.263-3.455， 0.152-0.232， 2.931-3.991 mg∙g^-1， respectively. Multivariate statistical analysis showed that paeoniflorin， ginsenoside Rg₁， ginsenoside Rb₁ and staphylline hydrochloride were quality difference markers to control the stability of the preparation. The results of bioactive experiment showed that the water extract of Naomaili granules and the eight main components with high content in the prescription had a dose-dependent inhibitory effect on the release of NO in the cell supernatant. Among them， salvianolic acid B and ginsenoside Rb₁ had strong anti-inflammatory activity， with IC₅₀ values of （36.11±0.15） mg∙L^-1 and （27.24±0.54） mg∙L^-1， respectively. ConclusionThe quality evaluation method of Naomaili granules established in this study was accurate and reproducible. Four quality difference markers were screened out， and eight key pharmacodynamic substances of Naomaili granules against neuroinflammation were screened out by in vitro cell experiments.

Pan vascular disease （PVD） is a systemic vascular disorder that has become the leading cause of death among the Chinese residents， and there is currently a lack of effective systemic treatment options. Clinical practice has found that the traditional Chinese medicine （TCM） method of kidney tonification can effectively intervene in PVD and target key pathological mechanisms of PVD recognized in Western medicine. Accordingly， this paper conducts research from the following three aspects： First， it clarifies that immune dysregulation， metabolic disorders， and genetic susceptibility constitute the core pathological mechanisms of PVD in Western medicine. Typical pathological manifestations include progressive vascular endothelial injury， lipid deposition， and plaque formation， ultimately leading to multi-organ damage and dysfunction. PVD activates pathways such as the NOD-like receptor thermal protein domain-associated protein 3 （NLRP3） inflammasome， triggering immune dysregulation； it also induces disorders of mitochondrial energy metabolism， water-salt metabolism， and hormonal metabolism， synergizing with genetic susceptibility factors （e.g.， apolipoprotein E gene） to accelerate vascular homeostasis imbalance. Second， this study analyzes the intrinsic relationship between the TCM theory of "kidney deficiency" and the "immune-metabolic-genetic" axis， revealing the theoretical basis for kidney tonification in intervening PVD. The kidney stores essence， governs bones， and produces marrow， which is related to the generation and differentiation of immune cells. It regulates Qi transformation and governs water， overseeing material and energy metabolism. The kidney is the root of congenital essence and governs reproduction， closely related to genetic mechanisms. Third， by integrating modern clinical research， this study elaborates on the unique advantages and clinical value of kidney tonification in targeting the "immune-metabolic-genetic" axis of heart， brain， and kidney organs. Traditional kidney-tonifying formulas and their active ingredients improve immune-inflammatory responses， enhance material and energy metabolism homeostasis， and modulate epigenetic pathways through multiple pathways， targeting various pathways to intervene in PVD. This study systematically elucidates the scientific connotation of kidney tonification in treating PVD， providing theoretical support and practical guidance for integrated TCM-Western medicine approaches and contributing to innovation and improvement in diagnostic and treatment strategies for PVD.

ObjectiveTaking Aurantii Fructus Immaturus juice（AFI）-processed Atractylodis Macrocephalae Rhizoma（AMR） as an example， this study aims to systematically compare the volatile and non-volatile components of AMR and its processed products， investigate the key differential components， evaluate their anti-inflammatory activities， and elucidate the synergistic mechanism of processing. MethodsThe chemical compositions of volatile and non-volatile components in AMR and AFI-processed AMR were systematically characterized using gas chromatography-mass spectrometry（GC-MS） and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， with relative mass fractions and response values determined separately. Volatile components were identified through searches in the National Institute of Standards and Technology（NIST）17 database， comparison with retention index（RI） and fragmentation pattern matching. Non-volatile components were identified by searching Waters Traditional Chinese Medicine （TCM） spectral library， in conjunction with PubChem and MassBank， characteristic fragmentation patterns and response values were also used to support identification. Differential components were screened using principal component analysis（PCA）， orthogonal partial least squares-discriminant analysis（OPLS-DA）， with variable importance in the projection（VIP） value >1. Components with high log₂fold change（FC） among major differential groups were selected as those exhibiting significant changes before and after processing. The anti-inflammatory activity of the differential compounds was evaluated by assessing their effects on nitric oxide（NO） production in a lipopolysaccharide（LPS）-induced RAW264.7 macrophage model. Enzyme-linked immunosorbent assay（ELISA） was used to detect the effects of the differential components on tumor necrosis factor（TNF）-α， interleukin（IL）-1β， IL-6， and monocyte chemotactic protein（MCP）-1 levels， and immunofluorescence（IF） was employed to assess their effects on nuclear transcription factor（NF）-κB p65 translocation， thereby elucidating the underlying molecular mechanisms. ResultsA total of 36 compounds were identified in the volatile components of AMR and AFI-processed AMR， among which， sesquiterpenes and monoterpenes were significantly increased after processing. In the non-volatile components， 36 compounds were identified， and the main differential components were flavonoids， sesquiterpenoids， and triterpenoids. Flavonoids were the primary differential components distinguishing AMR from its processed products， representing compounds directly introduced during processing. Five compounds， including atractylenolide Ⅲ， tangeritin， nobiletin， hesperidin and narirutin， were selected as representatives of three classes based on their most prominent differential expression among different compound types for subsequent anti-inflammatory activity studies. The results showed that 100 μmol·L^-1 tangerine and narirutin could significantly inhibit LPS-induced NO production（P<0.01） in a concentration-dependent manner. Tangeritin was able to significantly inhibit the levels of TNF-α and MCP-1 secreted by RAW264.7（P<0.05）， while narirutin significantly inhibited the levels of TNF-α， IL-1β， MCP-1 and IL-6（P<0.01）. IF revealed that both tangeritin and narirutin significantly blocked the translocation of NF-κB p65 from the cytoplasm to the nucleus. ConclusionAFI-processed AMR significantly alters the chemical composition profile of AMR， and the newly introduced flavonoid components during processing may be key to its enhanced anti-inflammatory effects.

ObjectiveTo investigate the current situation of mutual recognition for ethical review outcomes in multicenter clinical research across 10 contracting medical institutions in Guangdong Province， analyze existing issues and propose improvement recommendations， thereby promoting the standardized management of mutual recognition for ethical review outcomes in medical institutions. MethodsData from 381 multicenter clinical studies conducted in these 10 medical institutions from January 24 to October 31， 2024， were collected. Text visualization was performed using Python and the WordCloud library， and statistical analyses were conducted with SPSS 25.0. ResultsOf the 381 studies investigated， industry-sponsored clinical trials （ISTs） accounted for 51.71%， while investigator-initiated clinical trials （IITs） constituted 48.29%. The proportions of ethical committees serving as primary reviewers and collaborative reviewers were 33.33% and 66.67%， respectively. The confirmation methods of mutual recognition outcomes were primarily expedited reviews （50.66%） and meeting reviews （49.34%）， and no cases of “direct confirmation” were found. The Chi-square test revealed statistically significant differences in review confirmation methods based on project type （χ²=14.851， P<0.001） and ethics committee role （χ²= 69.435， P<0.001）. The frequency distribution trend of the contingency table showed that IST projects and primary ethics committees preferred to employ meeting review （58.88% and 79.53% respectively， both higher than the average level of 49.34%）， while IIT projects and the collaborative ethics committees more frequently utilized expedited review （60.87% and 65.75% respectively， both higher than the average level of 50.66%）. ConclusionThe confirmation methods of mutual recognition for ethical review outcomes in multicenter clinical research are significantly associated with the role of the ethics committee and the type of project. It is recommended to improve management systems， enhance information construction and personnel training， as well as clarify mutual recognition responsibilities and strengthen supervision. This aims to ensure review quality while improving mutual recognition efficiency， thereby safeguarding the rights and interests of research participants.

Parkinson’s disease (PD) is a common neurodegenerative disorder with profound impact on patients’ quality of life and long-term health, and early detection and intervention are particularly critical. In recent years, the search for precise and reliable biomarkers has become one of the key strategies to effectively address the clinical challenges of PD. In this paper, we systematically evaluated potential biomarkers, including proteins, metabolites, epigenetic markers, and exosomes, in the peripheral blood of PD patients. Protein markers are one of the main directions of biomarker research in PD. In particular, α‑synuclein and its phosphorylated form play a key role in the pathological process of PD. It has been shown that aggregation of α-synuclein may be associated with pathologic protein deposition in PD and may be a potential marker for early diagnosis of PD. In terms of metabolites, uric acid, as a metabolite, plays an important role in oxidative stress and neuroprotection in PD. It has been found that changes in uric acid levels may be associated with the onset and progression of PD, showing its potential as an early diagnostic marker. Epigenetic markers, such as DNA methylation modifications and miRNAs, have also attracted much attention in Parkinson’s disease research. Changes in these markers may affect the expression of PD-related genes and have an important impact on the onset and progression of the disease, providing new research perspectives for the early diagnosis of PD. In addition, exosomes, as a potential biomarker carrier for PD, are able to carry a variety of biomolecules involved in intercellular communication and pathological regulation. Studies have shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide a new breakthrough for early diagnosis. It has been shown that exosomes may play an important role in the pathogenesis of PD, and their detection in blood may provide new breakthroughs in early diagnosis. In summary, through in-depth evaluation of biomarkers in the peripheral blood of PD patients, this paper demonstrates the important potential of these markers in the early diagnosis of PD and in the study of pathological mechanisms. Future studies will continue to explore the clinical application value of these biomarkers to promote the early detection of PD and individualized treatment strategies.

[摘 要] 目的：探究浸润性复层产生黏液的复层上皮癌（ISMC）的临床组织及分子病理特征。方法： 回顾性分析2018年1月至2024年4月间安徽医科大学安庆医学中心/安庆市立医院及皖南医学院第一附属医院/弋矶山医院的病理数据库的11例ISMC和4例产生黏液的复层上皮内病变（SMILE）的临床病理资料、免疫组化、阿利新蓝（AB）/过碘酸雪夫（PAS）染色、分子学检测及PD-L1表达情况。结果：ISMC患者多表现为阴道不规则流血。细胞质内含有黏液的细胞呈复层排列，周围呈栅栏状，肿瘤细胞可呈印戒样或胞质透明。ISMC不仅存在单纯型，也可呈混合型。ISMC具有高侵袭性的生物学特性。CK7、p16，p40和（或）p63表达呈癌巢周栅栏状阳性或局灶表达。AB/PAS染色阳性。人乳头状病毒（HPV）检测结果：ISMC中HPV16/18阳性（1/4），术前检测出HPV16/18阳性（4/6）；SMILE组织中HPV阴性。ISMC均表达PD-L1。成功随访8例ISMC患者，时间4~39个月（平均20.50月），4例SMILE患者，时间1~25个月（平均8.25月），随访患者均存活，1例ISMC术后出现多脏器转移。结论：ISMC具有独特的形态学特征及免疫表型，表现为高侵袭性和不良预后。所有ISMC均呈PD-L1阳性，提示所有患者均可从PD-L1免疫治疗中获益。

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

BACKGROUND:Carboxylesterase 1 and inflammatory factors play a crucial role in regulating lipid metabolism and glucose homeostasis.However,the effects of different exercise intensity interventions on carboxylesterase 1 and inflammatory factors in skeletal muscle of type 2 diabetic rats remain to be revealed. OBJECTIVE:To investigate the effects of different exercise intensity interventions on carboxylesterase 1 and inflammatory factors in skeletal muscle of type 2 diabetic rats. METHODS:Thirty-two 8-week-old male Sprague-Dawley rats were randomly divided into normal control group(n=12)and modeling group(n=20)after 1 week of adaptive feeding.Rat models of type 2 diabetes mellitus were prepared by high-fat diet and single injection of streptozotocin.After successful modeling,the rats were randomly divided into diabetic control group(n=6),moderate-intensity exercise group(n=6)and high-intensity intermittent exercise group(n=6).The latter two groups were subjected to treadmill training at corresponding intensities,once a day,50 minutes each,and 5 days per week.Exercise intervention in each group was carried out for 6 weeks.After the intervention,ELISA was used to detect blood glucose and blood lipids of rats.The morphological changes of skeletal muscle were observed by hematoxylin-eosin staining.The mRNA expression levels of carboxylesterase 1 and inflammatory cytokines were detected by real-time quantitative PCR.The protein expression levels of carboxylesterase 1 and inflammatory cytokines were detected by western blot and immunofluorescence. RESULTS AND CONCLUSION:Compared with the normal control group,fasting blood glucose,triglyceride,low-density lipoprotein cholesterol,insulin resistance index in the diabetic control group were significantly increased(P<0.01),insulin activity was decreased(P<0.05),and the mRNA and protein levels of carboxylesterase 1,never in mitosis gene A related kinase 7(NEK7)and interleukin 18 in skeletal muscle tissue were upregulated(P<0.05).Compared with the diabetic control group,fasting blood glucose,triglyceride,low-density lipoprotein cholesterol,and insulin resistance index in the moderate-intensity exercise group and high-intensity intermittent exercise group were down-regulated(P<0.05),and insulin activity was increased(P<0.05).Moreover,compared with the diabetic control group,the mRNA level of NEK7 and the protein levels of carboxylesterase 1,NEK7 and interleukin 18 in skeletal muscle were decreased in the moderate-intensity exercise group(P<0.05),while the mRNA levels of carboxylesterase 1,NEK7,NOD-like receptor heat protein domain associated protein 3 and interleukin 18 and the protein levels of carboxylesterase 1 and interleukin 18 in skeletal muscle were downregulated in the high-intensity intermittent exercise group(P<0.05).Hematoxylin-eosin staining showed that compared with the diabetic control group,the cavities of myofibers in the moderate-intensity exercise group became smaller,the number of internal cavities was reduced,and the cellular structure tended to be more intact;the myocytes of rats in the high-intensity intermittent exercise group were loosely arranged,with irregular tissue shape and increased cavities in myofibers.To conclude,both moderate-intensity exercise and high-intensity intermittent exercise can reduce blood glucose,lipid,insulin resistance and carboxylesterase 1 levels in type 2 diabetic rats.Moderate-intensity exercise can significantly reduce the expression level of NEK7 protein in skeletal muscle,while high-intensity intermittent exercise can significantly reduce the expression level of interleukin 18 protein in skeletal muscle.In addition,the level of carboxylesterase 1 is closely related to the levels of NEK7 and interleukin 18.