Zoledronic acid (ZA), a nitrogen-containing bisphosphonate with established clinical utility in osteoporosis management, exhibits emerging antitumor potential in estrogen receptor-positive breast cancer. However, the molecular mechanisms underlying its nonapoptotic anticancer effects remain poorly characterized. This study revealed that ZA induced ferroptosis in ER+ breast cancer cells through dual suppression of cystine-glutamate antiporter SLC7A11 and glutathione peroxidase 4 (GPX4), key repressors of ferroptosis. Pharmacological inhibition of ferroptosis using Ferrostatin-1 significantly attenuated ZA-induced cytotoxicity, while combinatorial treatment with the GPX4 inhibitor RSL3 synergistically enhanced lipid peroxidation and cell death. Mechanistically, ZA activated the Hippo-YAP signaling pathway, promoting YAP phosphorylation, proteasomal degradation, and cytoplasmic retention, thereby silencing SLC7A11 and GPX4. We established a novel metabolic vulnerability in hormone-responsive malignancies.These findings position ZA as a bifunctional ferroptosis inducer in ER+ breast cancer, offering a promising strategy to overcome endocrine resistance.

ObjectiveTo explore the function and related molecular mechanisms of magnoflorine against colon cancer via network pharmacology， molecular docking， and in vitro cell experiments. MethodsIn this study， the canonical SMILES of magnoflorine was obtained from the PubChem database， and the potential targets of magnoflorine were predicted by the Swiss Target Prediction database， while the disease targets of colon cancer were obtained from the DisGeNET， GeneCards and OMIM databases. The intersecting targets between magnoflorine's predicted targets and colon cancer disease targets were taken， and a protein-protein interaction （PPI） network was constructed and analyzed. The DAVID online database was employed to conduct Gene Ontology （GO） and KEGG pathway enrichment analyses on core targets. The top five key targets screened were docked with magnoflorine using AutoDock software. Finally， cellular experiments including CCK-8 assays， EdU experiments， cell scratch assays， and Transwell assays were conducted to validate the results from network pharmacology and molecular docking. Results44 key targets of magnoflorine in resisting colon cancer were acquired. The molecular docking results showed that magnoflorine had a strong binding activity with the core target signal transducer and activator of transcription 3 （STAT3） in the top five of the PPI network. Cellular experiments confirmed that magnoflorine could inhibit the proliferation and migration of colon cancer cells by suppressing the JAK/STAT3 signaling pathway. ConclusionMagnoflorine may inhibit the proliferation and migration of colon cancer cells by regulating the JAK/STAT3 signaling pathway.

OBJECTIVE To optimize the preparation process of Pollen Typhae dripping pills.METHODS Using appearance morphology， roundness， tailing phenomenon， adhesion condition， friability， and total flavonoids content of Pollen Typhae as evaluation indicators， the analytic hierarchy process-entropy weight method （AHP-EWM） hybrid weighting method was employed to determine the weight coefficients of each indicator and calculate the comprehensive score as the response value. The effects of matrix type and ratio， drug-to-matrix ratio， and condensation temperature on the forming process of dripping pills were respectively investigated， through single-factor experiments and Box-Behnken response surface methodology and the optimal process was optimized and validated. The cumulative dissolution rate of Pollen Typhae dripping pills within 150 min was determined and compared with that of total flavonoid extract from Pollen Typhae .RESULTS The optimal preparation process for Pollen Typhae dripping pills was determined as follows： the ratio of PEG4000 to PEG6000 was 2∶1， the drug-to-matrix ratio was 1∶2， and the condensation temperature was 17.5 ℃. The measured average comprehensive score of dripping pills prepared under these conditions was 9.208 （RSD＝0.91%， n ＝3）， with a relative error of 0.83% compared to the predicted value of 9.285. The release mechanism of Pollen Typhae dripping pills was Fickian diffusion controlled deceleration release. The initial dissolution rate was fast， and the dissolution rate decreased in the middle and later stages. The total flavonoid extract from Pollen Typhae was released rapidly in the initial dissolution stage and quickly entered the plateau phase. Their maximum dissolution rates were 95.96% and 84.07%， respectively.CONCLUSIONS The optimized preparation process for Pollen Typhae dripping pills was stable and reliable. The dissolution rate of Pollen Typhae dripping pills prepared by optimized process was higher than that of the total flavonoid extract from Pollen Typhae .

ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

ObjectiveTo investigate the value of different noninvasive diagnostic models in the diagnosis of esophageal and gastric varices since there is a high risk of esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and to provide a basis for the early diagnosis of esophageal and gastric varices. MethodsA total of 108 patients with significant portal hypertension due to compensated hepatitis B cirrhosis who attended Guangdong Provincial Hospital of Traditional Chinese Medicine from November 2017 to November 2023 were enrolled， and according to the presence or absence of esophageal and gastric varices under gastroscopy， they were divided into esophageal and gastric varices group （GOV group） and non-esophageal and gastric varices group （NGOV group）. Related data were collected， including age， sex， imaging findings， and laboratory markers. The chi-square test was used for comparison of categorical data between groups； the least significant difference t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. The receiver operating characteristic （ROC） curve was plotted to evaluate the diagnostic value of five scoring models， i.e.， fibrosis-4 （FIB-4）， LOK index， LPRI， aspartate aminotransferase-to-platelet ratio index （APRI）， and aspartate aminotransferase/alanine aminotransferase ratio （AAR）. The binary logistic regression method was used to establish a combined model， and the area under the ROC curve （AUC） was compared between the combined model and each scoring model used alone. The Delong test was used to compare the AUC value between any two noninvasive diagnostic models. ResultsThere were 55 patients in the GOV group and 53 patients in the NGOV group. Compared with the NGOV group， the GOV group had a significantly higher age （52.64±1.44 years vs 47.96±1.68 years， t=0.453， P<0.05） and significantly lower levels of alanine aminotransferase ［42.00 （24.00 — 17.00） U/L vs 82.00 （46.00 — 271.00） U/L， Z=-3.065， P<0.05］， aspartate aminotransferase ［44.00 （32.00 — 96.00） U/L vs 62.00 （42.50 — 154.50） U/L，Z=-2.351， P<0.05］， and platelet count ［100.00 （69.00 — 120.00）×10⁹/L vs 119.00 （108.50 — 140.50）×10⁹/L， Z=-3.667， P<0.05］. The ROC curve analysis showed that FIB-4， LOK index， LPRI， and AAR used alone had an accuracy of 0.667， 0.681， 0.730， and 0.639， respectively， in the diagnosis of esophageal and gastric varices （all P<0.05）， and the positive diagnostic rates of GOV were 69.97%， 65.28%， 67.33%， and 58.86%， respectively， with no significant differences in AUC values （all P>0.05）， while APRI used alone had no diagnostic value （P>0.05）. A combined model （LAF） was established based on the binary logistic regression analysis and had an AUC of 0.805 and a positive diagnostic rate of GOV of 75.80%， with a significantly higher AUC than FIB-4， LOK index， LPRI， and AAR used alone （Z=-2.773，-2.479，-2.206， and-2.672， all P<0.05）. ConclusionFIB-4， LOK index， LPRI， and AAR have a similar diagnostic value for esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and APRI alone has no diagnostic value. The combined model LAF had the best diagnostic efficacy， which provides a certain reference for clinical promotion and application.

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

Objective: To explore the distribution of traditional Chinese medicine (TCM) syndromes in patients with interstitial lung disease (ILD) and its influencing factors. Methods: This cross-sectional study included 385 patients with ILD admitted to the First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine) from January 2018 to June 2022. Data on sex, age, body mass index, smoking history, respiratory rate, hospitalization time, treatment cost, whether velcro rales can be heard, comorbidities with rheumatic immune diseases, TCM four examination information, and clinical examination results, including CT imaging, D-dimer level, and lung function-related indicators, were collected. The distribution pattern of TCM syndromes in patients with ILD and the association between TCM syndromes and clinical indicators were analyzed using the cluster analysis and binary Logistic regression analysis. Results: Among the 385 patients with ILD, sticky phlegm (59.74%) and shortness of breath (56.10%) were common symptoms, while greasy tongue coating (55.32%), red tongue (52.73%), and slippery and rapid pulse (25.71%) were common tongue and pulse manifestations. The patients were divided into five syndromes using cluster analysis: syndrome of phlegm-heat stagnation in the lung (36.62%), syndrome of turbid phlegm obstructing lung (29.35%), syndrome of deficiency of both qi and yin (12.99%), syndrome of qi deficiency of lung and kidney (11.95%), and syndrome of phlegm and blood stasis obstructing lung (9.09%). The D-dimer level was lower in patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of qi deficiency of lung and kidney than in those with syndrome of phlegm and blood stasis obstructing lung (P<0.05). The percentage of predicted forced vital capacity (FVC%pred) of patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of phlegm and blood stasis obstructing lung was higher than in those with syndrome of qi deficiency of lung and kidney (P<0.05). Among patients aged 60 and above, those with syndrome of phlegm-heat stagnation in the lung, syndrome of phlegm and blood stasis obstructing lung, and syndrome of deficiency of both qi and yin containing dual pathogenic syndrome elements were more likely to experience moderate to severe pulmonary diffusion impairment than those with syndrome of turbid phlegm obstructing lung and syndrome of qi deficiency of lung and kidney containing single pathogenic syndrome elements (P<0.05). The Logistic regression showed that the FVC%pred was an influential factor for syndrome of qi deficiency of lung and kidney, and the area under the receiver operating characteristic (ROC) curve (AUC) between FVC%pred and the formation of syndrome of qi deficiency of lung and kidney was 0.676 (95%CI: 0.598-0.755), P=0.002. The sensitivity was 0.431, the specificity was 0.966, and the best threshold on the ROC curve of 0.397 was 79.1%. The D-dimer level was an influential factor in the formation of syndrome of phlegm and blood stasis obstructing lung. The AUC between D-dimer level and the formation of syndrome of phlegm and blood stasis obstructing lung was 0.729 (95%CI: 0.655-0.802), P<0.001. The sensitivity was 0.914, the specificity was 0.523, and the best threshold on the ROC curve of 0.437 was 0.675 mg/L. Conclusion syndrome of phlegm-heat stagnation in the lung and syndrome of turbid phlegm obstructing lung are common among patients with ILD. Complex pathological syndromes are more likely to exacerbate pulmonary diffusion dysfunction. The FVC%pred can assist in differentiating syndrome of qi deficiency of lung and kidney, whereas the D-dimer level can assist in differentiating syndrome of phlegm and blood stasis obstructing lung.

Objective To study the tongue manifestation of patients with different syndromes in non-small cell lung cancer(NSCLC)and the correlation between tongue characteristics of different syndromes and tumor markers and coagulation indicators.Methods Totally 497 patients with NSCLC were grouped according to syndrome differentiation,and the differences in tongue characteristics of different syndromes were compared.Bivariate correlation analysis was used to study the correlation between tongue characteristics and serum tumor markers and coagulation indicators in patients with NSCLC of different syndromes.Results Compared with healthy people of different syndromes,in TB-a,yin deficiency and phlegm-heat syndrome>healthy group>qi-yin deficiency syndrome>spleen deficiency and phlegm-dampness syndrome>lung stagnation and phlegm-stasis syndrome(P<0.001).In TB-L,healthy group>spleen deficiency and phlegm-dampness syndrome>qi-yin deficiency syndrome>lung stagnation and phlegm-stasis syndrome>yin deficiency and phlegm-heat syndrome(P<0.001).In TB-b,yin deficiency and phlegm-heat syndrome>qi-yin deficiency syndrome>spleen deficiency and phlegm-dampness syndrome>healthy group>lung stagnation and phlegm-stasis syndrome(P<0.001).Yin deficiency and phlegm-heat syndrome had the highest TB-a and the lowest Per-all.Spleen deficiency and phlegm-dampness syndrome had the highest TB-L and Per-all.Lung stagnation and phlegm-stasis syndrome had lower TB-b and TC-b than other groups,lower TB-a than the healthy group,and a high Per-all index(P<0.05).In terms of tumor markers,Per-all in spleen deficiency and phlegm-dampness syndrome was positively correlated with Ca199,Ca50 and Ca242(P<0.05).In terms of coagulation indicators,the tongue texture index of lung stagnation and phlegm-stasis syndrome had a high correlation with the coagulation indicator Fg(P<0.01).Conclusion Different TCM syndromes of NSCLC have their own typical tongue characteristics.Tongue manifestations of different syndromes are correlated with tumor markers and coagulation indicators,respectively,which can reflect changes in clinical status.

Objective To evaluate the advantages of a real-time computer endoscopy-assisted system(EndoAngel)for colorectal lesions detection in colonoscopy.Methods 2 000 patients who underwent EndoAngel assisted colonoscopy and conventional colonoscopy were selected for the study in a single-center,self-controlled study.According to different examination methods,the patients were divided into artificial intelligence(AI)group and traditional colonoscopy group,each with 1 000 cases.The results were statistically analyzed and compared with the polyp detection rate and adenoma detection rate of the two groups using pathological diagnosis as the gold standard.Further subgroup analysis will be conducted based on the seniority of the operating physicians.Results AI group's polyp detection rate was higher(39.3％)than conventional colonoscopy group polyp detection rate(29.0％),with statistically significant difference(x2=23.59,P=0.000).Of these,the detection rates of hyperplastic polyps and adenomatous polyps were 19.1％and 25.2％,which were significantly higher than those of 12.4％and 20.8％in the conventional colonoscopy group,and the differences were statistically significant(x2=16.92,P=0.000;x2=5.46,P=0.019).Further subgroup analysis of the two groups by physician seniority,the polyp detection rate of AI low seniority group(36.6％)was higher than that of conventional colonoscopy low seniority group(20.40％),with a statistically significant difference(x2=32.20,P=0.000).Among them,the detection rates of hyperplastic polyp(17.8％)and adenomatous polyp(23.6％)in AI low seniority group were higher than those in the conventional colonoscopy low seniority group(12.8％vs 13.6％),and the differences were significant(x2=4.82,P=0.028;x2=16.51,P=0.000).There were no significant differences in adenomatous polyp detection rates between the two groups of senior physicians.Conclusion EndoAngel assisted system can improve the polyp detection rate of colonoscopy,especially for the effect of low seniority physicians is more significant.