1.Association between small vulnerable newborn phenotypes and the risk of neurodevelopmental delay at the age of 1 year: a prospective cohort study
Jinhua LU ; Songying SHEN ; Wujiangyuan HE ; Fengjuan ZHOU ; Xiaoyan XIA ; Minshan LU ; Jianrong HE ; Huimin XIA ; Xiu QIU ; Wenhao ZHOU
Chinese Journal of Pediatrics 2026;64(1):52-60
Objective:To investigate the association between small vulnerable newborn (SVN) phenotypes and the risk of neurodevelopmental delay at the age of 1 year.Methods:A prospective cohort study was conducted. A total of 25 860 singleton infants from "The Born in Guangzhou Cohort Study" who completed the Gesell developmental scale assessment at 1 year of age between January 2013 and June 2025 were included. Maternal sociodemographic characteristics, and other information were collected using a self-administered questionnaire, and maternal pregnancy-related information and neonatal birth data were extracted from medical records. Global developmental delay (GDD) was defined as a developmental quotient below 86 in ≥3 domains of the Gesell developmental scale, which assesses the adaptive, gross motor, fine motor, language, and personal-social domains. The random forest algorithm was employed for missing data imputation. Based on prematurity, small for gestational age (SGA), and low birth weight (LBW), newborns were categorized into 6 phenotypes: preterm-SGA-LBW, preterm-appropriate for gestational age (AGA)-LBW, preterm-AGA-nonLBW, term-SGA-LBW, term-LBW-only or term-SGA-only, and term-AGA-nonLBW phenotype. Among these, the first 5 were classified as SVN phenotypes, and the last one served as the reference group. Inter-group comparisons were performed using analysis of variance (ANOVA), χ2 tests, or Kruskal-Wallis test, as appropriate.?? Multivariable robust Poisson regression models were applied to analyze the association of different SVN phenotypes with the risks of GDD and developmental delays in specific domains, with stratified analyses by sex. Results:Among the 25 860 infants, 13 719 (53.1%) were male and 12 141 (46.9%) were female. The gestational age at birth was 39.4 (38.6, 40.0) weeks. The overall detection rate of GDD at 1 year of age was 3.7% (962/25 860). The rates of delay across developmental domains, in descending order, language in 8 134 cases (31.5%), gross motor in 4 488 cases (17.4%), personal-social in 1 271 cases (4.9%), adaptive in 1 262 cases (4.9%), and fine motor in 621 cases (2.4%). Compared with the reference group, preterm-AGA-LBW, preterm-SGA-LBW, preterm-AGA-noneLBW, and term-SGA-LBW phenotypes were all associated with an increased risk of GDD, with the adjusted RR (95% CI) of 6.07(5.01-7.35), 4.81(3.11-7.46), 2.10(1.54-2.88) and 1.89(1.29-2.76) respectively.The preterm-AGA-noneLBW phenotype was all associated with an increased risk of delay in gross motor, language and personal-social functional domains (all P<0.05). The term-SGA-LBW phenotype was associated with an increased risk of delay in gross motor, fine motor and personal-social functional domains (all P<0.01). Whereas the term-LBW-only or term-SGA-only phenotype showed no statistically association with developmental delay in any functional domain (all P≥0.05). Conclusion:The combined classification based on gestational age and birth weight helps identify infants at high risk for neurodevelopmental delay at 1 year of age, suggesting that it may offer a reference for the rational allocation of clinical resources.
2.Correlation Analysis of Huanglian Jiedu Wan on Syndrome Improvement and Clinical Biomarkers of "Excess Heat-Toxicity" Based on Machine Learning Model
Qi LI ; Keke LUO ; Baolin BIAN ; Hongyu YU ; Mengxiao WANG ; Mengyao TIAN ; Wen XIA ; Yuan MA ; Xinfang ZHANG ; Pengyue LI ; Nan SI ; Hongjie WANG ; Yanyan ZHOU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):162-173
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.
3.Correlation Analysis of Huanglian Jiedu Wan on Syndrome Improvement and Clinical Biomarkers of "Excess Heat-Toxicity" Based on Machine Learning Model
Qi LI ; Keke LUO ; Baolin BIAN ; Hongyu YU ; Mengxiao WANG ; Mengyao TIAN ; Wen XIA ; Yuan MA ; Xinfang ZHANG ; Pengyue LI ; Nan SI ; Hongjie WANG ; Yanyan ZHOU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):162-173
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.
4.Study on the role of oleuropein in enhancing muscle endurance
Huan LI ; Zhen ZHANG ; Jiayi FENG ; Weidong ZHANG ; Xia LIU
Journal of Pharmaceutical Practice and Service 2026;44(3):126-131
Objective Orosomucoid1 (ORM1) is a novel target in the quest for anti-fatigue pharmacotherapy. Preliminary investigations have illuminated oleuropein (OLE) as a promising candidate molecule, poised to enhance ORM1 expression. To elucidate the influence of OLE on ORM1 protein expression and assess its ramifications on muscle endurance. Methods The impact of OLE on ORM1 protein expressions within hepatocytes and liver tissue was meticulously quantified through Western blotting; the effects of OLE on muscle endurance were evaluated via the rotarod and forced swimming tests; glycogen content within liver and muscle tissues was determined utilizing a specialized kit; and PAS staining was employed to visualize glycogen deposition in the gastrocnemius muscle. Results OLE demonstrated a capacity to elevate ORM1 protein expression in hepatocytes in a time- and dose-dependent manner, concurrently prolonging the duration of swimming and rotarod performance in mice, also in a time- and dose-dependent manner. Furthermore, OLE augmented ORM1 expression in liver tissue, elevated serum ORM1 levels, and enhanced glycogen reserves within the liver and muscle. Conclusion OLE may serve to amplify muscle endurance by elevating ORM1 levels in vivo and augmenting glycogen stores within skeletal muscle.
5.Study on the extraction, separation and purification process of Actinoside E
Fangliang QIAO ; Yiping JIANG ; Tianshuang XIA ; Aijun LIU ; Kai ZHAO ; Hailiang XIN
Journal of Pharmaceutical Practice and Service 2026;44(3):137-143
Objective To optimize the extraction, separation and purification process of Actinoside E. Methods Single factor experiment combined with orthogonal test was used to determine the optimal extraction process of Actinoside E using its content as an index. The extracts were separated and purified by optimizing the chromatographic conditions of macroporous resin, silica gel and ODS column. Results 25 times amount of 55% ethanol with heating reflux at 95℃ for one hour were used as the optimal extraction process of Actinoside E. The optimum separation and purification process was as follows: D101 macroporous resin column was eluted with 7 BV of 50% ethanol, silica gel column was eluted with 5 BV of ethyl acetate-ethanol(10∶1)and 50% methanol eluted fraction was purified repeatedly by ODS column to obtain Actinoside E. The transfer rate of Actinoside E in the whole process was 53.70%, the yield was 0.35%, and the purity was 99.9%. Conclusion The process is stable and viable, which can provide material foundation for the development and utilization of Actinoside E.
6.Analysis of prevalence of depressive symptoms and associated factors among students in Zhejiang Province
SHI Yingyun, GU Fang, XIA Jiayue, LIU Qinye, WEI Xiaoyu, CHEN Fen, WEI Yizhou, LIU Weina
Chinese Journal of School Health 2026;47(2):232-236
Objective:
To investigate the prevalence of depressive symptoms and their associated factors among students in Zhejiang Province, so as to provide evidence for targeted prevention strategies.
Methods:
A stratified cluster random sampling method was used to select 23 829 college students and primary and secondary school students aged 11-22 years in Zhejiang Province from December 2019 to February 2020. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Three machine learning algorithms, including Logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost), were applied to construct predictive models, and key associated factors were identified by comparing model performance.
Results:
The detection rate of depressive symptoms among students in Zhejiang Province was 19.92%; the rates were 17.20% in boys and 22.87% in girls( χ 2=164.89, P <0.05). The CES-D total score was 9.00(4.00,13.00). Multiple Logistic regression analysis revealed that loneliness had the strongest association with depressive symptoms ( AOR =9.58, 95% CI =8.90-10.30), while bullying exposure ( AOR =4.39, 95% CI =4.02-4.80), female students( AOR =1.81, 95% CI =1.68-1.94),never eating breakfast ( AOR = 2.34,95% CI =2.00-2.67) and overweight/obesity( AOR =1.10,95% CI =1.08-1.12) were significant associated factors of depressive symptoms among students (all P <0.05). Analysis based on the XGBoost model produced highly consistent results, identifying the above 5 factors as the core features with the highest correlation strength (all P <0.05).
Conclusions
Female, loneliness, bullying exposure, frequency of weekly breakfast and BMI are strongly associated with depressive symptoms among students. Mental health education for high risk groups should be strengthened, and coordinated prevention efforts between families and schools are recommended.
8.The effect of body mass index and inferior pulmonary ligament division on the residual lung expansion after right upper lobectomy: A retrospective cohort study in a single center
Guang MU ; Wenhao ZHANG ; Hongchang WANG ; Yan GU ; Chenghao FU ; Wentao XUE ; Shiyuan XIE ; Tong WANG ; Ke WEI ; Yang XIA ; Liang CHEN ; Jun WANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(02):261-266
Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2<BMI≤23 kg/m2), a group B (23 kg/m2<BMI≤29 kg/m2) and a group C (BMI>29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.
9.Regulation of TGF-β1/JNK signaling pathway in patients with different types of mitral valve diseases complicated by atrial fibrillation
Chao CHANG ; Bo FU ; Xiaolong ZHU ; Chongjie ZHANG ; Xia ZHAO ; Hong TANG ; Xijun XIAO ; Yunpeng BAI
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(02):291-299
Objective To investigate the regulatory mechanism of transforming growth factor-β1 (TGF-β1) in different types of mitral valvular disease (MVD) with atrial fibrillation (AF). Methods From August 2011 to August 2012, patients with moderate to severe MVD accompanied by AF who required mitral valve replacement at the Department of Cardiovascular Surgery, West China Hospital, Sichuan University, were included. Based on echocardiographic results, patients were divided into two groups: a mitral regurgitation (MR) with AF (MR-AF) group and a mitral stenosis (MS) with AF (MS-AF) group. Left atrial tissue samples were collected during surgery. Techniques such as enzyme-linked immunosorbent assay, real-time fluorescence quantitative polymerase chain reaction, immunohistochemistry, and Western blotting were used to detect key molecules in the TGF-β1/JNK pathway. Results Sixteen patients were enrolled. There were 8 patients in the MR-AF group, including 5 males and 3 females, with an average age of (41.38±11.19) years; and 8 patients in the MS-AF group, including 6 males and 2 females, with an average age of (43.12±5.30) years. The left atrial volume load was higher in MR-AF patients, while the left atrial pressure load was higher in MS-AF patients. In MS-AF patients, the relative expression levels of MAPK9, JUN, CASP3, BAX, and BCL2 mRNA in left atrial tissues were significantly upregulated. The serum TGF-β1 protein level and the relative expression levels of p-JNK, p-c-Jun, and Caspase-3 proteins in the left atrial tissues of the MR-AF group were higher. Myocardial cell damage was more severe in the MS-AF group, and the protein expression level of Bcl-2 was higher. Conclusion Different MVD have distinct hemodynamic characteristics. The myocardium of the left atrium in MR-AF patients is more prone to apoptosis, possibly through the activation of the TGF-β1/JNK signaling pathway.
10.Research and innovative exploration of integrated traditional Chinese and Western medicine in preventing and treating gastric " inflammatory cancer transformation"
Xia DING ; Qi WANG ; Zhaoshen LI
Journal of Beijing University of Traditional Chinese Medicine 2026;49(1):1-9
The development of intestinal-type gastric cancer follows a progression from non-atrophic gastritis — atrophic gastritis — intestinal metaplasia — epithelial dysplasia — gastric cancer,known as the " inflammation-cancer transformation. " Leveraging the advantages of integrated traditional Chinese and Western medicine,while collaborating to inhibit this transformation,remains a research focus and challenge. The incidence of gastric cancer in China has declined with the continuous elucidation of the mechanisms behind inflammation-cancer transformation,innovations in early screening and diagnosis techniques in Western medicine,the establishment of risk stratification and treatment systems,and effective interventions through traditional Chinese medicine. Leveraging the theoretical and practical advantages of the " preventing disease before it occurs" philosophy of traditional Chinese medicine,particularly the concept of " preventing transformation in existing diseases," is essential. This approach emphasizes shifting the focus of prevention and treatment to earlier stages of disease progression. Developing more effective and reliable strategies and innovative drugs that block the dynamic progression of the " inflammation-cancer transformation" in gastric cancer remains a key goal. This article reviews the latest progress in both basic and clinical research in this field,the issues related to high-level clinical research in traditional Chinese medicine,the construction of integrated diagnosis and treatment pathways combining Chinese and Western medicine,the establishment of efficacy evaluation standards,and the elucidation of the integration mechanisms of the complex system of traditional Chinese medicine. It also explores research directions and solutions within the context of multidisciplinary collaboration to provide insights and references to block inflammation-cancer transformation and to construct a gastric cancer prevention and control system with Chinese characteristics,thereby further enhancing the level of gastric cancer prevention and control.


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