ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Myasthenia gravis(MG)is an autoimmune disease characterized primarily by skeletal muscle weakness and,in severe cases,respiratory involvement.Western medical treatment predominantly relies on immunosuppressants,but long-term administration often leads to notable side effects.In contrast,traditional Chinese medicine(TCM)offers the advantage of multi-target interventions.However,the pathogenesis of MG has not been fully elucidated,and the establishment of animal models that accurately reflect the clinical characteristics of both Chinese and Western medicine is essential for mechanism research and new drug development.This paper systematically reviews the etiology and pathogenesis,diagnostic criteria,and progress of animal model research for MG from both Chinese and Western medicine perspectives.In Western medicine,the pathogenesis of MG is closely related to genetic susceptibility,environmental factors,and autoantibody-mediated postsynaptic membrane damage.In TCM,MG is classified under the category of"flaccidity syndrome",attributed to congenital deficiencies and acquired malnourishment.Western diagnostic criteria involve a combination of clinical symptoms,fatigue testing,serum antibody assays,and electrophysiological evaluation.In contrast,TCM diagnosis emphasizes the integration of primary and secondary symptoms with tongue and pulse pattern differentiation.Currently available animal models mainly include experimental autoimmune myasthenia gravis(EAMG)and passive transfer myasthenia gravis(PTMG).The Toredo acetylcholine receptor(AChR)induced EAMG model aligns well with Western diagnostic criteria,but poorly matches secondary symptoms in TCM.The synthetic AChR peptide model is widely used,but shows low conformity with TCM syndromes.Models induced by muscle-specific tyrosine kinase(MuSK),low-density lipoprotein receptor-related protein 4(LRP4),and transgenic models demonstrate high innovation but exhibit low clinical conformity.Evaluation of these models requires integration of behavioral,electrophysiological,and immunological indicators.However,a systematic framework for modelling TCM syndromes is still lacking.Future research should integrate TCM-based etiological modelling methods with the Western pathological mechanisms to construct disease-syndrome combination models.Additionally,it is crucial to establish a TCM syndrome evaluation system based on"validation by prescription",as well as to improve the scientific rigor and practicality of animal models by the incorporation of emerging technologies.This review provides a theoretical foundation for optimizing MG animal model design,advancing the research on the combination of Chinese and Western medicine,and supporting efficacy assessment and mechanism exploration of Chinese herbal prescriptions.

Myasthenia gravis(MG)is an autoimmune disease characterized primarily by skeletal muscle weakness and,in severe cases,respiratory involvement.Western medical treatment predominantly relies on immunosuppressants,but long-term administration often leads to notable side effects.In contrast,traditional Chinese medicine(TCM)offers the advantage of multi-target interventions.However,the pathogenesis of MG has not been fully elucidated,and the establishment of animal models that accurately reflect the clinical characteristics of both Chinese and Western medicine is essential for mechanism research and new drug development.This paper systematically reviews the etiology and pathogenesis,diagnostic criteria,and progress of animal model research for MG from both Chinese and Western medicine perspectives.In Western medicine,the pathogenesis of MG is closely related to genetic susceptibility,environmental factors,and autoantibody-mediated postsynaptic membrane damage.In TCM,MG is classified under the category of"flaccidity syndrome",attributed to congenital deficiencies and acquired malnourishment.Western diagnostic criteria involve a combination of clinical symptoms,fatigue testing,serum antibody assays,and electrophysiological evaluation.In contrast,TCM diagnosis emphasizes the integration of primary and secondary symptoms with tongue and pulse pattern differentiation.Currently available animal models mainly include experimental autoimmune myasthenia gravis(EAMG)and passive transfer myasthenia gravis(PTMG).The Toredo acetylcholine receptor(AChR)induced EAMG model aligns well with Western diagnostic criteria,but poorly matches secondary symptoms in TCM.The synthetic AChR peptide model is widely used,but shows low conformity with TCM syndromes.Models induced by muscle-specific tyrosine kinase(MuSK),low-density lipoprotein receptor-related protein 4(LRP4),and transgenic models demonstrate high innovation but exhibit low clinical conformity.Evaluation of these models requires integration of behavioral,electrophysiological,and immunological indicators.However,a systematic framework for modelling TCM syndromes is still lacking.Future research should integrate TCM-based etiological modelling methods with the Western pathological mechanisms to construct disease-syndrome combination models.Additionally,it is crucial to establish a TCM syndrome evaluation system based on"validation by prescription",as well as to improve the scientific rigor and practicality of animal models by the incorporation of emerging technologies.This review provides a theoretical foundation for optimizing MG animal model design,advancing the research on the combination of Chinese and Western medicine,and supporting efficacy assessment and mechanism exploration of Chinese herbal prescriptions.

Aim To investigate the changes in hepatic lactylation during liver regeneration and its impact on regeneration.Methods A partial hepatectomy(PHx)mouse model was used to study liver regenera-tion.Sodium oxamate was administered intraperitoneal-ly to inhibit lactate dehydrogenase,and blood and liver tissues were collected at different time points post-sur-gery.The histopathological status was observed using HE staining.Proliferating cell nuclear antigen(PC-NA)levels were detected by immunohistochemistry.Lactylation was assessed using immunofluorescence.Liver LDH enzyme activity,lactate levels and serum alanine aminotransferase(ALT)and aspartate trans-aminase(AST)levels were measured using assay kits.Results After PHx,the liver volume of mice gradual-ly increased,returning to preoperative size on day 7.PCNA levels peaked at 48 hours post-surgery.Liver tissue lactate levels increased to approximately 1.5 times the preoperative level at 12 hours post-surgery and remained elevated until day 7.The lactylation lev-el in hepatocytes peaked at 24 hours post-surgery,gradually declined after 48 hours,and returned to pre-operative levels on day 7.Compared to the PHx group,the sodium oxamate(750 mg·kg-1)+PHx group showed significantly reduced lactylation levels in hepa-tocytes and a smaller liver regeneration volume on day 7.Conclusion Lactylation regulates hepatocyte pro-liferation and promotes liver regeneration after PHx.

Objective:This study examines the impact of integrated healthcare and elderly care policy pilots on paid work among older adults.Methods:Using CHARLS panel data(2013-2020),we employed a difference-in-differences(DID)model to assess the policy effects.Results:The results indicate a 10.3%average increase in paid work among older adults in pilot areas.Mechanism analysis reveals that health status mediated this effect,while social security exhibited a suppression effect.The policy significantly increased participation in agricultural work,non-agricultural employment,and self-employed farming but reduced participation in hired agricultural labor.Heterogeneity analysis shows stronger effects in rural and central-western regions.Conclusion and Suggestions:The integrated care policy effectively promotes older adults'paid work engagement.We recommend strengthening service systems,implementing phased benefit improvements with work incentives,expanding pilot coverage in rural and central-western regions,and fostering health-labor policy coordination.

Objective To compare the biomechanical characteristics of small-angle rotation force versus traditional buccal-lingual force in the extraction of vertically impacted mandibular third molars with single conical roots by a three-dimensional finite element analysis.Methods A patient with a vertical mandibular third molar featuring a conical single root was selected.Spiral CT data were acquired and three-dimensional finite element analysis models were constructed using software including MIMICS,Geomagic Wrap,and Solidworks.ANSYS was utilized to simulate both the small-angle rotation and buccal-lingual forces for tooth extraction.Comparative an-alyses of the biomechanical characteristics of these two forces were conducted by measuring Von-Mises stress and strain distribution.Results In the small-anglerotation force,high-stress and strain areas of tooth,periodontal ligament,and alveolar bone were predomi-nantly concentrated at the cervical region and the upper half of the root,with a more uniform distribution and a broader horizontal diffu-sion range compared to the vertical diffusion range.In the buccal-lingual force,high-stress and strain areas were primarily located at the cervical region and the lower half of the root,particularly at the apical area,with a broader vertical diffusion range compared to the hor-izontal diffusion range.The lingual cortical plate and alveolar bone experienced significantly lower stress in the small-angle rotation force than that in the buccal-lingual force.The overall stress values within the periodontal ligament were markedly higher in the small-angle rotation force,with a more uniform distribution.Conclusion The small-angle rotation force is more likely to tear the periodontal liga-ment and reduce trauma associated with tooth extraction compared to the buccal-lingual force in surgical extraction of vertically impacted mandibular third molars with single conical roots.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

Objective:To investigate the longitudinal patterns and influencing factors of platelet counts among healthy adults in Sichuan Province from 2010 to 2021, and to inform the establishment of region-specific reference intervals for platelet counts.Methods:This study is a retrospective study. A total of 7 808 healthy adults who underwent annual physical examinations at West China Hospital, Sichuan University, between January 2010 and December 2021 were included. All participants were permanent Chengdu residents and completed consecutive complete blood count tests. Group-based trajectory modeling (GBTM) was used to identify distinct trajectories of platelet count over the ten-year period. One-way analyses were then conducted to compare baseline demographic characteristics (sex and age) among the different trajectory groups.Results:Among 7 808 participants, 4 589 (58.8%) were male and 3 219 (41.2%) were female. Four platelet count trajectories were identified by GBTM: steadily increasing group [27.4% (2 139/7 808)], early increase-plateau group [44.1% (3 445/7 808)], early decrease-subsequent increase group [5.4% (422/7 808)], and steadily decreasing group [23.1% (1 802/7 808)], with an average growth rate of 3.3%, 1.6%, 0.7%, and -0.6%, respectively. There were statistically significant differences in both sex and age distributions among the four trajectory groups. Sex-distribution differed significantly across the four trajectory groups ( χ2=73.3, P<0.001). The male proportions in the four trajectory groups were 59.6% (1 275/2 139), 62.8% (2 165/3 445), 48.1% (203/422), and 52.5% (946/1 802), respectively. The baseline ages were 45 (36, 55), 43 (35, 53), 50 (40, 60), and 47 (39, 58) years, respectively (H=121.0, P<0.001). Conclusions:Healthy adults in Sichuan Province exhibit four longitudinal trajectories of platelet counts: steadily increasing, early increase-plateau, early decrease-subsequent increase, and steadily decreasing. The two trajectories characterized by rising platelet counts (steadily increasing group and early increase-plateau group) exhibited higher male predominance and lower median ages, whereas the early decrease-subsequent increase group and the steadily decreasing group exhibited lower male proportions and higher median ages. Therefore, while establishing reference intervals and developing health management strategies for platelet counts, it is essential to account for the sex, age characteristics and the population′s dynamic changes.

The chemical constituents from leaves of Cyclocarya paliurus were isolated and purified by chromatography on silica gel, C_(18) reverse-phase silica gel, and Sephadex LH-20 gel, as well as semi-preparative high-performance liquid chromatography. Six compounds were identified by UV, IR, NMR, MS, calculated ECD, and comparison with literature data as cyclopaloside D(1), boscialin(2),(5R,6S)-6-hydroxy-6-[(E)-3-hydroxybut-1-enyl]-1,1,5-trimethylcyclohexanone(3), 3S,5R-dihydroxy-6R,7-megastigmadien-9-one(4), 3S,5R-dihydroxy-6S,7-megastigmadien-9-one(5), and gingerglycolipid A(6), respectively. Among them, compound 1 was identified as a new tetralone glycoside, and compounds 2-6 were isolated from leaves of C. paliurus for the first time. Furthermore, compound 1 exhibited strong antioxidant activity, with the IC_(50) of(454.20±31.81)μmol·L~(-1) and(881.82±42.31)μmol·L~(-1) in scavenging DPPH and ABTS free radicals, respectively.
Plant Leaves/chemistry* ; Glycosides/isolation & purification* ; Juglandaceae/chemistry* ; Tetralones/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification*