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.

Objective: To investigate the association between injury prevention knowledge level and injury occurrence among primary and secondary school students in Dongguan, so as to provide scientific basis for formulating targeted and evidence based intervention strategies for child injury. Methods: From March to April 2024, stratified cluster random sampling method was applied to select 5 988 primary and secondary school students in grades 4-9 for a survey. The Revised Questionnaire for the 2016-2020 Child Injury Prevention Project (senior version) was used to collect demographic characteristics, family and caregiver information, injury event characteristics, and knowledge, attitude, and practice related to injury prevention. Mann-Whitney U test was used for inter group comparison. Propensity score matching (PSM) was applied to balance confounders, and conditional Logistic regression was used to analyze the association between injury prevention knowledge score and injury occurrence among primary and secondary school students, and a restricted cubic spline (RCS) model was employed to test the dose response relationship. Furthermore, interaction terms were introduced to examine the moderating effects of sex, grade level, and caregiver’s educational level. Results: The overall incidence of injuries among primary and secondary school students was 18.15%. The knowledge score of injury prevention was significantly lower in the injury group [20.0(18.0,22.0)] than in the non injury group [21.0(19.0,22.0)] ( Z = 8.24 , P <0.01). After PSM, 1 068 pairs were successfully matched, and the standardized mean difference for all covariates was <0.1. An increase in injury prevention awareness scores was associated with a reduced risk of injury occurrence among primary and secondary school students ( OR =0.92, P <0.05). The RCS analysis showed an approximately linear negative association between injury prevention knowledge score and injury risk among primary and secondary school students ( P non linear =0.72), with a decreased injury risk when score exceeded 24 ( OR = 0.69, P <0.05). Subgroup analyses indicated that the negative correlation between cognitive level and the risk of injury was common in different gender, grade and caregivers educational level groups ( OR =0.87- 0.93 , all P <0.05). Sensitivity analyses yielded results consistent with the primary analysis. Conclusions The incidence of injuries among primary and secondary school students in Dongguan City is relatively high. Injury prevention knowledge level is negatively associated with injury occurrence risk, exhibiting an approximately linear dose response relationship.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.

Through the dismantlement,analysis,and sorting of the method of clearing collaterals and nourishing yin in the differentiation of syndromes in Wenbing Tiaobian written by WU Tang,a renowned physician of the Qing Dynasty.This article concluded that WU Tang's clinical application of clearing collaterals can be divided into clearing the qi collateral heat,clearing the blood collateral stasis,and clearing collateral stagnant heat.The yin-nourishing method specifically includes the sweet-cold fluid-restoring,sour-sweet yin-generating,sweet-bitter yin qi-nourishing,sweet-moistening fluid-preserving,heat-clearing fluid-protecting,and emergency purgative yin-preserving methods.Our team explored the application of this approach in tumor treatment based on the academic perspective of"strengthening healthy qi to treat cancer"and in combination with the"clearing collaterals and nourishing yin"method.It proposes that within the relationship between"strengthening healthy qi to treat cancer"and the"clearing collaterals and nourishing yin"method,"nourishing yin to strengthen healthy qi"often serves as the foundation of tumor treatment,whereas"clearing collaterals to eliminate pathogens"acts as an auxiliary measure.This paper summarizes our team's clinical experience and evidence in further treating cancerous diseases based on this theory,citing examples such as Qinghao Biejia Decoction,Xijiao Dihuang Decoction,Zhibai Dihuang Pill,our team's empirical formulas,and the specialized use of medications for cancerous diseases.The further application of this method in cancer diseases can be expanded to improve the clinical effect by summarizing the theory of"strengthening healthy qi to treat cancer"and improving the understanding of clearing collaterals and nourishing yin.

AIM:To investigate the effect of dyes,Remazol BrOrange yellow(RBY)and erythrosine(ERY),on the outcomes of immunoblotting analysis when used for staining the concentrate gel in sodium dodecyl sulfate-polyacryl-amide gel electrophoresis(SDS-PAGE).METHODS:Polyacrylamide gels were divided into five groups:the control group(prepared according to the conventional kit protocol),the RBY-stained group with a final concentration of 0.08 g/L,the RBY-stained group with a final concentration of 0.16 g/L,the ERY-stained group with a final concentration of 0.08 g/L,and the ERY-stained group with a final concentration of 0.8 g/L.Gels were prepared and subjected to electro-phoresis,followed by coomassie brilliant blue staining to visualize protein bands.Subsequently,proteins were transferred to PVDF membranes,which were then blocked,incubated with primary and secondary antibodies,washed,and finally ex-posed for imaging to observe the target protein vinculin bands.RESULTS:Compared with the unstained concentrate gel,the loading wells of the RBY or ERY pre-stained concentrate gel were more clearly visible.Analysis of the gels stained with coomassie brilliant blue after electrophoresis and marker visualization showed no significant different in protein elec-trophoretic mobility between prestained and unstained gels.Comparative analysis of the immunoblotting also indicated that the detection of protein samples transferred to PVDF membranes was unaffected.CONCLUSION:Prestaining concen-trate gels with RBY or ERY can enhance the efficiency of gel-based electrophoresis and immunoblotting analysis.

Objective:To analyze the evaluation value of contrast-enhanced ultrasound (CEUS) combined with automatic volumetric ultrasound in the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer.Methods:A retrospective study was conducted on 98 female patients with breast cancer admitted to Shaanxi Provincial Cancer Hospital from January to December 2022. All patients received 4 cycles of NAC, and underwent conventional ultrasound, automatic volumetric ultrasound, CEUS, and histopathological examination before and after treatment. Based on the post-treatment histopathological efficacy, patients were divided into the effective group ( n=67) and the ineffective group ( n=31). The CEUS and automatic volumetric ultrasound parameters before and after treatment, as well as the evaluation efficacy of these two types of parameters for NAC efficacy in breast cancer, were compared. The value of CEUS combined with automatic volumetric ultrasound in evaluating NAC efficacy for breast cancer was analyzed. Results:After NAC treatment, the CEUS parameters [time to peak (TTP) and arrival time (AT) of contrast agent] were longer than those before treatment, while the peak intensity (PI) was lower than that before treatment (all P<0.05); the automatic volumetric ultrasound parameters (tumor volume, area, thickness, length, and width) after NAC treatment were all smaller than those before treatment (all P<0.05). After treatment, the PI, volume, area, thickness, length, and width in the effective group were significantly smaller than those in the ineffective group, while the TTP and AT were significantly longer than those in the ineffective group (all P<0.05). Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of CEUS parameters and automatic volumetric ultrasound parameters for predicting effective NAC efficacy in breast cancer was 0.837(0.749-0.904) and 0.864(0.780-0.925), respectively, with no statistically significant difference between the two ( P=0.674). The AUC of the combined parameters for predicting effective NAC efficacy was 0.942(0.875-0.979), which was significantly higher than that of CEUS parameters or automatic volumetric ultrasound parameters alone ( Z=2.947, 2.135, P=0.003, 0.033). Conclusions:The combination of CEUS and automatic volumetric ultrasound parameters has high value in the efficacy evaluation of NAC for breast cancer and can be used as a clinical reference.

Through the dismantlement,analysis,and sorting of the method of clearing collaterals and nourishing yin in the differentiation of syndromes in Wenbing Tiaobian written by WU Tang,a renowned physician of the Qing Dynasty.This article concluded that WU Tang's clinical application of clearing collaterals can be divided into clearing the qi collateral heat,clearing the blood collateral stasis,and clearing collateral stagnant heat.The yin-nourishing method specifically includes the sweet-cold fluid-restoring,sour-sweet yin-generating,sweet-bitter yin qi-nourishing,sweet-moistening fluid-preserving,heat-clearing fluid-protecting,and emergency purgative yin-preserving methods.Our team explored the application of this approach in tumor treatment based on the academic perspective of"strengthening healthy qi to treat cancer"and in combination with the"clearing collaterals and nourishing yin"method.It proposes that within the relationship between"strengthening healthy qi to treat cancer"and the"clearing collaterals and nourishing yin"method,"nourishing yin to strengthen healthy qi"often serves as the foundation of tumor treatment,whereas"clearing collaterals to eliminate pathogens"acts as an auxiliary measure.This paper summarizes our team's clinical experience and evidence in further treating cancerous diseases based on this theory,citing examples such as Qinghao Biejia Decoction,Xijiao Dihuang Decoction,Zhibai Dihuang Pill,our team's empirical formulas,and the specialized use of medications for cancerous diseases.The further application of this method in cancer diseases can be expanded to improve the clinical effect by summarizing the theory of"strengthening healthy qi to treat cancer"and improving the understanding of clearing collaterals and nourishing yin.

AIM:To investigate the effect of dyes,Remazol BrOrange yellow(RBY)and erythrosine(ERY),on the outcomes of immunoblotting analysis when used for staining the concentrate gel in sodium dodecyl sulfate-polyacryl-amide gel electrophoresis(SDS-PAGE).METHODS:Polyacrylamide gels were divided into five groups:the control group(prepared according to the conventional kit protocol),the RBY-stained group with a final concentration of 0.08 g/L,the RBY-stained group with a final concentration of 0.16 g/L,the ERY-stained group with a final concentration of 0.08 g/L,and the ERY-stained group with a final concentration of 0.8 g/L.Gels were prepared and subjected to electro-phoresis,followed by coomassie brilliant blue staining to visualize protein bands.Subsequently,proteins were transferred to PVDF membranes,which were then blocked,incubated with primary and secondary antibodies,washed,and finally ex-posed for imaging to observe the target protein vinculin bands.RESULTS:Compared with the unstained concentrate gel,the loading wells of the RBY or ERY pre-stained concentrate gel were more clearly visible.Analysis of the gels stained with coomassie brilliant blue after electrophoresis and marker visualization showed no significant different in protein elec-trophoretic mobility between prestained and unstained gels.Comparative analysis of the immunoblotting also indicated that the detection of protein samples transferred to PVDF membranes was unaffected.CONCLUSION:Prestaining concen-trate gels with RBY or ERY can enhance the efficiency of gel-based electrophoresis and immunoblotting analysis.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.

The persistent high prevalence and poor survival outcomes of lung cancer underscore the urgent need for innovative therapeutic modalities. Here, we present a novel multifunctional delivery platform for the synergistic treatment of lung malignancies, combining in situ-triggerable photodynamic therapy (PDT) with radiotherapy. The new platform CLL was developed by loading a new reactive oxygen species (ROS)-triggerable photosensitizer, luminol-conjugated chlorin e6 (Ce6), into liposomes. CLL can be activated through the bioluminescence resonance energy transfer effect under oxidative stress, thereby producing singlet oxygen for targeted tumor treatment without external irradiation. In vitro studies showed significant cytotoxic effects of CLL in both 4T1 and A549 tumor cells. Furthermore, a PDT-radiopharmaceutical combination nanotherapy CLL-¹⁷⁷Lu was engineered by incorporating the radionuclide ¹⁷⁷Lu into CLL. CLL-¹⁷⁷Lu demonstrated synergistic antitumor effects in 4T1 and A549 tumor cells, as well as in mouse models of 4T1 breast cancer lung metastasis or A549 tumor xenografts. Mechanistically, CLL-¹⁷⁷Lu can induce singlet oxygen/ROS generation, enhance tumor cell apoptosis, and promote M1 macrophage-mediated immunotherapy. Preliminary assessments showed a favorable profile for CLL-¹⁷⁷Lu, highlighting its potential as a promising nanotherapy for cancer treatment. Additionally, CLL can serve as a versatile platform for delivering a range of therapies to achieve synergistic antitumor effects.