1.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
2.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
3.Multicenter machine learning-based construction of a model for predicting potential organ donors and validation with decision curve analysis
Xu WANG ; Wenxiu LI ; Fenghua WANG ; Shuli WU ; Dong JIA ; Xin GE ; Zhihua SHAN ; Tongzuo LI
Organ Transplantation 2026;17(1):106-115
Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.
4.Analysis of Changes on Volatile Components of Ligusticum sinense cv. Chaxiong Rhizome Before and After Wine Processing Based on Electronic Nose and HS-GC-MS
Wen ZHANG ; Peng ZHENG ; Jiangshan ZHANG ; Xiaolin XIAO ; Zaodan WU ; Li XIN ; Wenhui GONG ; Jinlian ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(2):173-181
ObjectiveBy comparing the composition and content of volatile components in raw products, wine-washed products and wine-fried products of Ligusticum sinense cv. Chaxiong rhizome(LSCR), to investigate the influence of wine processing on the volatile components of LSCR, in order to provide a basis for the development of quality standards for LSCR and its processed products. MethodsElectronic nose was used to identify the odors of LSCR, wine-washed and wine-fried LSCR, and their volatile components were detected by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the relative mass fractions of these components were determined by peak area normalization method. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were performed on the obtained sample data by SIMCA 14.1 software, and the differential components of LSCR, wine-washed and wine-fried LSCR were screened according to the variable importance in the projection(VIP) value>1. Pearson correlation analysis was used to explore the relationship between volatile differential flavor components and electronic nose sensors. ResultsElectronic nose detection results showed that there were significant differences in the odors of LSCR, wine-washed and wine-fried LSCR, mainly reflected in the sensors S2, S4, S5, S6, S11, S12, S13. And a total of 62 compounds were identified from LSCR and its wine-processed products, among which 46, 50 and 51 compounds were identified from LSCR, wine-fried and wine-washed LSCR, respectively. There were 21 differential components between the raw products and wine-fried products, of which 10 components were increased and 11 were decreased after processing. There were 20 differential components between the raw products and wine-washed products, of which 11 constituents increased and 9 decreased after processing. There were 17 differential components between the wine-wash products and wine-fried products. Compared with the wine-washed products, the contents of 13 components in the wine-fried products increased, and the contents of 4 components decreased. The increasing trend of the content of phthalides in the wine-washed products was more obvious than that in the wine-fried products, but the content of total volatile components was higher in the wine-fried products than the wine-washed products. Correlation analysis showed that there were different degrees of correlation between the 7 differential sensors of electronic nose and 24 differential volatile components, mainly phthalides and olefins. ConclusionThe odor and the content of volatile components in LSCR changed obviously after wine processing, and n-butylphthalide, Z-butylidenephthalide and E-ligustilide can be used as the candidate differential markers of volatile components in LSCR before and after wine processing.
5.Overview and implications of the cohort construction for autism spectrum disorders based on Internet recruitment
CHEN Xin, GAO Hui, WU De, TAO Fangbiao
Chinese Journal of School Health 2025;46(2):157-161
Abstract
The construction of autism spectrum disorders (ASD) specialty cohorts in China is still in its infancy, and the cost effectiveness is insufficient when relying on diagnostic and treatment processes of child health care to collect ample and high quality data. After 2000, the United States Simons Foundation s ASD Research Initiative, the Early ASD Risk Longitudinal Investigation (EARLI), and the British ASD Study of Infant Siblings (BASIS), which have been built based on Internet recruitment, have provided new insight for the construction of large sample ASD specialty cohorts in China. Future research can further explore and optimize the methods of Internet recruitment, and establish a more comprehensive and accurate ASD specialty cohorts.
6.Study of adsorption of coated aldehyde oxy-starch on the indexes of renal failure
Qian WU ; Cai-fen WANG ; Ning-ning PENG ; Qin NIE ; Tian-fu LI ; Jian-yu LIU ; Xiang-yi SONG ; Jian LIU ; Su-ping WU ; Ji-wen ZHANG ; Li-xin SUN
Acta Pharmaceutica Sinica 2025;60(2):498-505
The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure
7.Study on the modeling method of general model of Yaobitong capsule intermediates quality analysis based on near infrared spectroscopy
Le-ting SI ; Xin ZHANG ; Yong-chao ZHANG ; Jiang-yan ZHANG ; Jun WANG ; Yong CHEN ; Xue-song LIU ; Yong-jiang WU
Acta Pharmaceutica Sinica 2025;60(2):471-478
The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.
8.Pharmacological effects of Yindan Pinggan capsules in treating intrahepatic cholestasis
Shu-xin CAO ; Feng HUANG ; Fang WU ; Rong-rong HE
Acta Pharmaceutica Sinica 2025;60(2):417-426
This study aimed to investigate the therapeutic effect of Yindan Pinggan capsules (YDPG) on intrahepatic cholestasis (IHC) through animal experiments, while utilizing network pharmacology and molecular docking techniques to explore its potential mechanisms. Initially, the therapeutic effect of YDPG on an
9.Research progress of antifungal drugs from natural sources
Shao-jie CHU ; Yan ZHENG ; Shuang-shuang SU ; Xue-song WU ; Hong YAN ; Shao-xin CHEN ; Hong-bo WANG
Acta Pharmaceutica Sinica 2025;60(1):48-57
As the number of patients with compromised immune function increases and fungal resistance develops, so does the risk of contracting deadly fungi in humans. Both fungi and humans are eukaryotes, so identifying unique targets for antifungal drug development is difficult. In addition, the existing antifungal drugs are limited by toxicity, drug interaction and drug resistance in practical application, which leads to the increasing incidence and fatal rate of fungal infections. Therefore, it is urgent to develop new antifungal drugs. The semi-synthetic technology using microbial fermentation products from natural sources as lead compounds has become the most used method in structural modification of antifungal drugs due to its advantages of few reaction steps and easy operation. This paper will introduce the current status of natural antifungal drugs in clinical use, as well as the latest progress in the research and development of new semi-synthetic antifungal drugs, and summarize their mechanism of action, structural modifications, advantages and disadvantages, so as to provide reference for the subsequent development of new antifungal drugs.
10.Effect of intracellular and extracellular vesicles derived from periodontal ligament stem cells on the osteogenic differentiation ability of periodontal ligament stem cells under an inflammatory microenvironment
LIU Haotian ; YAN Fuhua ; WU Yu ; TONG Xin ; ZHANG Qian
Journal of Prevention and Treatment for Stomatological Diseases 2025;33(4):268-277
Objective:
To examine the effect of intracellular vesicles (IVs) and extracellular vesicles (EVs) that originated from periodontal ligament stem cells (PDLSCs) on the osteogenic differentiation of PDLSCs within a lipopolysaccharide (LPS)-simulated inflammatory microenvironment, and to provide new insights for the application of IVs in the repair and regeneration of periodontal tissue in periodontitis.
Methods:
Ethical approval was obtained from the institution. Human-origin PDLSCs were extracted, and the IVs and EVs from PDLSCs at the 3rd-6th passages were gathered and identified using transmission electron microscopy, nano flow cytometry (Nano FCM) analysis, and Western Blot. The 3rd-6th generations of PDLSCs were categorized into the following groups: Control group, LPS group, LPS + 100 μg/mL EVs group (LPS+EVs group), and LPS + 100 μg/mL IVs group (LPS+IVs group). The effects of the IVs and EVs on the anti-inflammatory and osteogenic differentiation of PDLSCs in an inflammatory microenvironment were assessed by using a Cell Counting Kit-8 (CCK-8), enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (qRT-PCR), Western Blot, alkaline phosphatase (ALP) staining, and alizarin red staining (ARS).
Results:
Under transmission electron microscopy, the IVs and EVs derived from PDLSCs displayed a double-layer membrane structure. NanoFCM analysis revealed that the average diameters of the IVs and EVs were 79.6 nm and 82.1 nm, respectively. Western Blot analysis indicated that the surface proteins CD9, CD63, and CD81 of the IVs and EVs were positively expressed, while calnexin was negatively expressed, indicating that IVs and EVs were successfully obtained. Compared with the Control group, the proliferation of PDLSCs in the LPS group was reduced, while the levels of inflammatory cytokine interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the cell supernatant were increased, the mRNA expressions of osteogenic differentiation-related genes, including osteoblast-related genes runt-related transcription factor 2 (RUNX2), alkaline phosphatase (ALP), osteocalcin (OCN) of PDLSCs were reduced, the protein expressions of RUNX2 and osteopontin (OPN) were also decreased (P<0.05); compared with the LPS group, the proliferation of PDLSCs in the LPS+EVs group and LPS+IVs group were significantly increased, while the levels of IL-6, TNF-α were significantly reduced, and the mRNA expressions of RUNX2, ALP, OCN were significantly increased, the protein expressions of RUNX2 and OPN were also significantly increased (P<0.05). Further, in the inflammatory microenvironment, Compared with EVs, IVs more significantly promote the proliferation of PDLSCs, inhibit TNF-α expression, enhance the expression of RUNX2 mRNA, upregulate the expression of RUNX2 and OPN proteins, increase ALP activity, and promote the formation of mineralized nodules (P<0.05).
Conclusion
IVs and EVs derived from PDLSCs can boost the proliferation of PDLSCs in an inflammatory microenvironment, inhibit the expression of inflammatory factors, and advance the osteogenic differentiation of PDLSCs. The anti-inflammatory and osteogenic effects of IVs are superior to those of EVs.


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