1.Pathogenic Mechanisms of Spleen Deficiency-Phlegm Dampness in Obesity and Traditional Chinese Medicine Prevention and Treatment Strategies:from the Perspective of Immune Inflammation
Yumei LI ; Peng XU ; Xiaowan WANG ; Shudong CHEN ; Le YANG ; Lihua HUANG ; Chuang LI ; Qinchi HE ; Xiangxi ZENG ; Juanjuan WANG ; Wei MAO ; Ruimin TIAN
Journal of Traditional Chinese Medicine 2026;67(1):31-37
Based on spleen deficiency-phlegm dampness as the core pathogenesis of obesity, and integrating recent advances in modern medicine regarding the key role of immune inflammation in obesity, this paper proposes a multidimensional pathogenic network of "obesity-spleen deficiency-phlegm dampness-immune imbalance". Various traditional Chinese medicine (TCM) herbs that strengthen the spleen, regulate qi, and resolve phlegm and dampness can treat obesity by improving spleen-stomach transport and transformation, promoting water-damp metabolism, and regulating immune homeostasis. This highlights immune inflammation as an important entry point to elucidate the TCM concepts of "spleen deficiency-phlegm dampness" and the therapeutic principle of "strengthening the spleen and eliminating dampness to treat obesity". By systematically analyzing the intrinsic connection between "spleen deficiency generating dampness, internal accumulation of phlegm dampness" and immune dysregulation in obesity, this paper aims to provide theoretical support for TCM treatment of obesity based on dampness.
2.The effects of galangin on the apoptosis and autophagy of gastric cancer NCI-N87 cells through regulating the AMPK/mTOR/ULK1 signaling pathway
GUO Fang ; CHEN Wei ; LIU Meng ; ZOU Yanli ; TIAN Xia
Chinese Journal of Cancer Biotherapy 2026;33(1):59-65
[摘 要] 目的:探讨高良姜素(Gal)调控AMPK/mTOR/ULK1信号通路对胃癌细胞凋亡和自噬的影响及其机制。方法:将胃癌NCI-N87细胞分为对照组、多索吗啡(DM)组、Gal低剂量(Gal-L)组、Gal高剂量(Gal-H)组、Gal-H + DM组。采用MTT法、流式细胞术、划痕愈合实验和Transwell实验分别检测各组细胞的增殖、凋亡、迁移和侵袭能力,WB法检测PCNA、C-caspase-3、免疫逃逸相关蛋白(B7H1)、EMT和AMPK/mTOR/ULK1信号通路蛋白的表达水平。建立裸鼠NCI-N87细胞移植瘤模型,观察Gal和5-FU对移植瘤的抑制效果。结果:与对照组比较,DM组NCI-N87细胞增殖活性、划痕愈合率和侵袭细胞数、N-cadherin、vimentin、PCNA、B7H1、p62和p-mTOR/mTOR蛋白表达均显著升高(均P < 0.05),细胞凋亡率、C-caspase-3、E-cadherin、LC3Ⅱ/LC3Ⅰ、p-AMPK/AMPK和p-ULK1/ULK1蛋白表达均显著降低(均P < 0.05);Gal-L组和Gal-H组NCI-N87细胞的增殖活性、划痕愈合率和侵袭细胞数、N-cadherin、vimentin、PCNA、B7H1、p62和p-mTOR/mTOR蛋白表达均显著降低(均P < 0.05),细胞凋亡率、C-caspase-3、E-cadherin、LC3Ⅱ/LC3Ⅰ、p-AMPK/AMPK和p-ULK1/ULK1蛋白表达均显著升高(均P < 0.05);DM可部分逆转Gal对NCI-N87细胞恶性生物学行为的抑制作用(P < 0.05);与对照组比较,Gal组和5-FU组裸鼠移植瘤体积和质量均显著降低,肿瘤组织细胞凋亡率显著升高(P < 0.05)。结论:Gal可促进胃癌NCI-N87细胞自噬和凋亡,抑制其增殖、迁移和侵袭,可能与激活AMPK/mTOR/ULK1信号通路有关。
3.Effect of Runmu Dihuang Decoction on Perimenopausal Dry Eye in Rats with Liver-kidney Yin Deficiency Syndrome Based on SIRT3/HIF-1α/NF-κB Signaling Pathway
Sainan TIAN ; Wei MA ; Yao CHEN ; Yu CAO ; Guicheng LIU ; Pei LIU ; Junxian LEI ; Qinghua PENG ; Jun PENG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(7):201-210
ObjectiveTo investigate the mechanisms of Runmu Dihuang decoction (RMDHD) in treating perimenopausal dry eye with liver-kidney Yin deficiency syndrome based on the silent information regulator 3 (SIRT3)/hypoxia-inducible factor-1α (HIF-1α)/nuclear factor-κB (NF-κB) signaling pathway. MethodsSixty female Sprague-Dawley rats were randomly divided into six groups (n=10 per group): Sham operation group, model group, sodium hyaluronate eye drop group, and low-, medium-, and high-dose RMDHD groups (5.625, 11.25, 22.50 g·kg-1). Except for the sham operation group, all rats underwent bilateral ovariectomy and were administered 0.1% benzalkonium chloride eye drops combined with long-term chronic irritation to establish a perimenopausal dry eye model with liver-kidney Yin deficiency syndrome. Drug administration began in the 11th week after modeling and continued for 21 days. General conditions, screen-grip test scores, tear secretion volume, tear film breakup time (TFBUT), and corneal fluorescein staining were recorded. Serum levels of reactive oxygen species (ROS), follicle-stimulating hormone (FSH), estradiol (E2), and progesterone (PROG) were measured by enzyme-linked immunosorbent assay (ELISA). Pathological changes in the lacrimal glands, corneas, and uteri were observed using hematoxylin-eosin (HE) staining. Protein expression levels of SIRT3, HIF-1α, phosphorylated NF-κB p65 (p-NF-κB p65), and total NF-κB p65 in the lacrimal glands were detected by Western blot. The expression of inflammatory cytokines interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) in the lacrimal glands was assessed by immunohistochemistry (IHC). ResultsAfter model establishment, no significant differences were observed among the groups except the sham operation group. Compared with the sham operation group, the other groups exhibited slowed movement, dull responses, increased irritability, reduced body weight, elevated rectal temperature, decreased screen-grip test scores, reduced tear secretion, and significantly shortened TFBUT (P<0.05). After treatment, compared with the model group, the sodium hyaluronate eye drop group and all RMDHD groups showed improved general conditions, significantly increased tear secretion (P<0.05), prolonged TFBUT (P<0.05), and elevated screen-grip test scores (P<0.05). Serum ROS and FSH levels were significantly decreased, while E2 and PROG levels were significantly increased (P<0.05). Pathological damage to the cornea, lacrimal glands, and uterus was ameliorated. In addition, protein expression levels of SIRT3 and HIF-1α in the lacrimal glands were significantly upregulated (P<0.05), whereas the expression of p-NF-κB p65, IL-1β, and TNF-α was significantly downregulated (P<0.05). ConclusionRMDHD increases tear secretion and TFBUT, improves lacrimal gland and corneal injury, and alleviates dry eye symptoms in a perimenopausal dry eye rat model with liver-kidney Yin deficiency syndrome. The underlying mechanism may be related to regulation of the SIRT3/HIF-1α/NF-κB signaling pathway, inhibition of oxidative stress and inflammatory responses, and reduction of ocular surface tissue damage.
4.Investigation on the microclimate of primary and secondary school classrooms in five provinces and municipalities of China in winter
Chinese Journal of School Health 2026;47(2):158-162
Objective:
To understand the microclimate in primary and secondary school classrooms for the study period during the winter heating season, so as to provide a reference for the revision and improvement of relevant health standards.
Methods:
In December 2024, stratified random sampling was used to select 30 primary and secondary schools and 180 classrooms from the northern regions with centralized heating (Liaoning Province, Tianjin City) and the southern regions without centralized heating (Shanghai City, Anhui Province, and Jiangxi Province). Indoor temperature, relative humidity, wind speed, CO 2 and other indicators were measured on site. Variance analysis, t-test, Mann-Whitney U test and Kruskal-Wallis H test were used to analyze the differences in the microclimate of classrooms among regions and urban and rural differences.
Results:
The average temperature in the middle of the classrooms tested on site was (16.47±4.72)℃, and the variance analysis showed that the difference between the regions was statistically significant ( F=27.80, P <0.01). Among them, Tianjin had the highest average temperature of (20.43± 2.12 )℃, followed by Liaoning (19.03±2.23)℃, Shanghai (15.33±5.32)℃, Anhui (12.79±1.74)℃, and Jiangxi (11.69± 1.68 )℃. Horizontal temperature difference was 0.90 (0.50, 1.60)℃, the vertical temperature difference was 0.20 (0.10,0.60)℃, the average relative humidity was (44.39±16.16)%, the wind speed was 0.03(0.01,0.11)m/s, and the differences among different provinces and cities were statistically significant ( H/F =40.62, 82.69, 95.06, 55.28, all P <0.01). The average CO 2 volume concentration in urban areas of Tianjin, Liaoning, and Shanghai was 0.21(0.16,0.30)%, and there was no statistically significant difference ( H=4.65, P =0.10). There were grade differences in relative humidity ( F =3.71, 6.21) and CO 2 ( H =14.72, 12.92) in the north and the south (all P <0.05). In addition, the temperature, relative humidity, wind speed and CO 2 in the middle of the classroom were 42.8%, 67.8%, 100.0% and 22.2% respectively.
Conclusions
The temperature in the middle of the classroom in the non centralized heating area is lower than the standard, the relative humidity of classroom in the centralized heating area is lower than the standard,and the CO 2 in the classroom in winter is lower than the standard. It is recommended to install heating facilities in schools with low temperatures to increase the temperature and increase the frequency of ventilation in classrooms or adopt mechanical ventilation strategies to reduce CO 2 volume concentration.
5.The Mechanisms of Quercetin in Improving Alzheimer’s Disease
Yu-Meng ZHANG ; Yu-Shan TIAN ; Jie LI ; Wen-Jun MU ; Chang-Feng YIN ; Huan CHEN ; Hong-Wei HOU
Progress in Biochemistry and Biophysics 2025;52(2):334-347
Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.
6.PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in nasopharyngeal carcinoma
Ranran FENG ; Yilin GUO ; Meilin CHEN ; Ziying TIAN ; Yijun LIU ; Su JIANG ; Jieyu ZHOU ; Qingluan LIU ; Xiayu LI ; Wei XIONG ; Lei SHI ; Songqing FAN ; Guiyuan LI ; Wenling ZHANG
Journal of Pathology and Translational Medicine 2025;59(1):68-83
Background:
Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear.
Methods:
We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP).
Results:
We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin.
Conclusions
PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.
7.PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in nasopharyngeal carcinoma
Ranran FENG ; Yilin GUO ; Meilin CHEN ; Ziying TIAN ; Yijun LIU ; Su JIANG ; Jieyu ZHOU ; Qingluan LIU ; Xiayu LI ; Wei XIONG ; Lei SHI ; Songqing FAN ; Guiyuan LI ; Wenling ZHANG
Journal of Pathology and Translational Medicine 2025;59(1):68-83
Background:
Nasopharyngeal carcinoma (NPC) is characterized by high programmed death-ligand 1 (PD-L1) expression and abundant infiltration of non-malignant lymphocytes, which renders patients potentially suitable candidates for immune checkpoint blockade therapies. Palate, lung, and nasal epithelium clone (PLUNC) inhibit the growth of NPC cells and enhance cellular apoptosis and differentiation. Currently, the relationship between PLUNC (as a tumor-suppressor) and PD-L1 in NPC is unclear.
Methods:
We collected clinical samples of NPC to verify the relationship between PLUNC and PD-L1. PLUNC plasmid was transfected into NPC cells, and the variation of PD-L1 was verified by western blot and immunofluorescence. In NPC cells, we verified the relationship of PD-L1, activating transcription factor 3 (ATF3), and β-catenin by western blot and immunofluorescence. Later, we further verified that PLUNC regulates PD-L1 through β-catenin. Finally, the effect of PLUNC on β-catenin was verified by co-immunoprecipitation (Co-IP).
Results:
We found that PLUNC expression was lower in NPC tissues than in paracancer tissues. PD-L1 expression was opposite to that of PLUNC. Western blot and immunofluorescence showed that β-catenin could upregulate ATF3 and PD-L1, while PLUNC could downregulate ATF3/PD-L1 by inhibiting the expression of β-catenin. PLUNC inhibits the entry of β-catenin into the nucleus. Co-IP experiments demonstrated that PLUNC inhibited the interaction of DEAD-box helicase 17 (DDX17) and β-catenin.
Conclusions
PLUNC downregulates the expression of PD-L1 by inhibiting the interaction of DDX17/β-catenin in NPC.
8.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
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.
9.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
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.
10.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
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.


Result Analysis
Print
Save
E-mail