Proteolysis-targeting chimeras (PROTACs) have emerged as a promising therapeutic strategy for targeted protein degradation. However, the clinical application of PROTACs may be hindered by off-target toxicity resulting from non-tissue-specific protein degradation and ingenious prodrug strategies may open new avenues to addressing this concern. Herein, we propose a light-induced positive feedback strategy to use photodynamic therapy (PDT) to improve the activation efficiency of PROTAC prodrugs, monitor PROTAC release, and combine PROTAC to induce tumor cell apoptosis. In the hypoxic tumor microenvironment, the azo bond in AZO-PRO selectively cleaves, triggering the release of the potent protein degrader PRO and the multifunctional photosensitizer. Once activated, the fluoresce signal of the photosensitizer dramatically recovers, allowing monitoring of prodrug activation. Additionally, upon irradicating the tumor site using near-infrared (NIR) laser, PDT exacerbates tumor hypoxia, further promoting AZO-PRO activation. Our work introduces a novel approach to efficiently track and activate PROTAC prodrugs, enhance their antitumor efficacy, and mitigate off-target systemic toxicity.

Objective:To investigate the clinical value of 18F-NaF PET/CT coronary plague imaging in evaluating the long-term prognosis of patients with coronary artery disease (CAD). Methods:A retrospective cohort study was conducted among 54 patients (37 males and 17 females, aged (57.2±9.8) years) diagnosed with CAD from a multicenter study between September 2015 and October 2022. All patients underwent 18F-NaF PET/CT and coronary angiography (CAG) within 1 week, and the PET/CT imaging was performed at the First Hospital of Shanxi Medical University. Major adverse cardiovascular events (MACE) were followed up. ROC curves were established to obtain the optimal thresholds of SUV max and accumulated SUV max of all lesions of main coronary artery branches (S-SUV max) for predicting MACE. Cox proportional risk model and Kaplan-Meier method (log-rank test) were used to analyze the predictive value of PET parameters for MACE. Differences in metabolic parameters between 2 groups were compared by Mann-Whitney U test. Results:The median follow-up time of the 54 patients was 6.0(1.8, 6.6) years, and 13(24.1%) patients developed MACE, including 7 deaths, 5 myocardial infarction and 1 severe arrhythmia. S-SUV max in MACE group was significantly higher than that in the non-MACE group (2.64(2.08, 4.49) vs 1.83(0.95, 2.90); Z=-2.04, P=0.041). ROC curve showed that the optimal threshold of S-SUV max for MACE prediction was 2.05 (AUC=0.690). Multivariate Cox analysis showed that S-SUV max was a strong predictor of MACE (hazard ratio ( HR)=2.434(95% CI: 1.547-3.828), P<0.001). ROC curve showed that the optimal threshold of SUV max to predict MACE was 0.55 (AUC=0.659), and univariate Cox analysis showed that SUV max was a factor to predict MACE ( HR=10.192 (95% CI: 2.667-38.953), P=0.001). In 25 patients with incomplete revascularization (ICR), Kaplan-Meier analysis showed that the incidence of MACE in patients with positive 18F-NaF uptake (single medium stenosis (40%-70%) with SUV max≥0.55) was significantly higher than that in patients with negative 18F-NaF uptake (5/14 vs 0/11; χ2=6.07, P=0.014). Conclusions:18F-NaF PET/CT can be used as an independent predictor of MACE in patients with CAD and can quantitatively assess the long-term progression of moderate coronary artery stenosis. In the future, it is expected to be a new non-invasive way to guide the revascularization treatment decision of multi-vessel CAD.

Objective To explore the risk factors of adverse pregnancy outcomes in the patients with cervical incompetence(CI),and to establish a risk warning model of adverse pregnancy outcomes in CI pa-tients based on decision tree model.Methods The clinical data of 159 patients with CI admitted and treated in this hospital from February 2022 to April 2023 were retrospectively analyzed,and the risk factors for adverse pregnancy outcomes were screened and the decision tree model for postoperative adverse pregnancy outcomes was constructed.The internal verification method was 5-fold cross-validation.Results The incidence rate of adverse pregnancy outcome was 22.64%.The pregnant weeks of cervical cerclage,amniotic cystocele,multiple cervical cerclage,preoperative cervical length and amniotic fluid sediment were all influential factors for ad-verse pregnancy outcome occurrence(P＜0.05).The amniotic fluid sediment was the most important factor affecting the postoperative adverse pregnancy outcome in CI patients,and the preoperative cervical length had little influence on the postoperative adverse pregnancy outcomes in CI patients.The area under the curve(AUC)value of logistic regression model was slightly higher than that of the decision tree model.The accura-cy rate of the 5-fold cross-validation model was 78.3%.Conclusion During clinical treatment,the above two models can be combined to find the influencing factors of postoperative adverse pregnancy outcomes in CI pa-tients from different aspects,and provide references for clinical medical staff to evaluate the disease condition of CI patients and formulate the intervention plans.

Objective To identify the key biomarkers for diagnosing chronic obstructive pulmonary disease(COPD)complicated with pulmonary arterial hypertension(PAH)using bioinformatics,and validate their clinical significance.Methods High-throughput sequencing data analysis was employed to identify differentially expressed genes(DEGs)in COPD-PAH.Functional enrichment analysis was then conducted to explore the biological functions of these DEGs.Machine learning methods,including least absolute shrinkage and selection operator(LASSO),random forest(RF),and support vector machine-recursive feature elimination(SVM-RFE),were utilized to screen 5 potential biomarkers.Single-cell analysis was performed to reveal the expression patterns of these key genes in macrophages.The clinical significance of these biomarkers was further validated using peripheral blood mononuclear cells(PBMC)data.A mouse model of COPD-PAH was established using hypoxia exposure.Sixteen mice(either sexes,8 weeks old,weighing 20～22 g)were randomly divided into a hypoxia group[O2(10.0±0.5)%,COPD-PAH,n=8]and a normoxia group(COPD,n=8).Immunofluorescence assay was used to label the key biomarkers,and their expression levels were quantified.Results A total of 28 DEGs(|Log2FC|≥2,P<0.05)were identified in COPD-PAH patients.Functional enrichment analysis indicated that DEGs in COPD were primarily associated with major histocompatibility complex(MHC)Ⅱ and cell division,and involved in lysosomes,oxidative phosphorylation,and cell cycle pathways(P<0.05).Machine learning identified 5 potential biomarkers(GRN,KLF4,SHTN1,LRP1,and GPNMB),and subsequent single-cell analysis revealed that these markers exhibited reverse expression patterns during disease progression.A nomogram model constructed based on PBMC data yielded an area under the curve(AUC)of 0.907 in diagnosing COPD-PAH.GRN,KLF4,SHTN1,LRP1 and GPNMB were significantly upregulated in the COPD-PAH group(P<0.05).Conclusion GRN,KLF4,SHTN1,LRP1 and GPNMB are identified as key biomarkers for the prediction and diagnosis of COPD-PAH,which providing new insights for the clinical and treatment of the condition.

Objective:To strengthen the management of low-value consumables in public hospitals by introducing the Supply Processing Distribution(SPD)management model,and to explore refined operational management strategies and path optimization for low-value consumables.Methods:The SPD management model was introduced,and the entire process of hospital consumables was refinedly managed using third-party supply chain information management platforms,visualized tertiary department warehouses,Radio Frequency Identification(RFID)technology and intelligent cabinet systems,Unique Device Identification(UDI)coding,"four-code integration"and other supporting technologies.Results:Based on the analysis of the current situation in the target Hospital,specific measures related to the management of low-value consumables were introduced after the introduction of the SPD model.Conclusion:It provides a reference and guidance for the hospital's medical consumables management department to promote refined management of medical consumables under the SPD model.

Objective:To strengthen the management of low-value consumables in public hospitals by introducing the Supply Processing Distribution(SPD)management model,and to explore refined operational management strategies and path optimization for low-value consumables.Methods:The SPD management model was introduced,and the entire process of hospital consumables was refinedly managed using third-party supply chain information management platforms,visualized tertiary department warehouses,Radio Frequency Identification(RFID)technology and intelligent cabinet systems,Unique Device Identification(UDI)coding,"four-code integration"and other supporting technologies.Results:Based on the analysis of the current situation in the target Hospital,specific measures related to the management of low-value consumables were introduced after the introduction of the SPD model.Conclusion:It provides a reference and guidance for the hospital's medical consumables management department to promote refined management of medical consumables under the SPD model.

Objective:To investigate the clinical value of 18F-NaF PET/CT coronary plague imaging in evaluating the long-term prognosis of patients with coronary artery disease (CAD). Methods:A retrospective cohort study was conducted among 54 patients (37 males and 17 females, aged (57.2±9.8) years) diagnosed with CAD from a multicenter study between September 2015 and October 2022. All patients underwent 18F-NaF PET/CT and coronary angiography (CAG) within 1 week, and the PET/CT imaging was performed at the First Hospital of Shanxi Medical University. Major adverse cardiovascular events (MACE) were followed up. ROC curves were established to obtain the optimal thresholds of SUV max and accumulated SUV max of all lesions of main coronary artery branches (S-SUV max) for predicting MACE. Cox proportional risk model and Kaplan-Meier method (log-rank test) were used to analyze the predictive value of PET parameters for MACE. Differences in metabolic parameters between 2 groups were compared by Mann-Whitney U test. Results:The median follow-up time of the 54 patients was 6.0(1.8, 6.6) years, and 13(24.1%) patients developed MACE, including 7 deaths, 5 myocardial infarction and 1 severe arrhythmia. S-SUV max in MACE group was significantly higher than that in the non-MACE group (2.64(2.08, 4.49) vs 1.83(0.95, 2.90); Z=-2.04, P=0.041). ROC curve showed that the optimal threshold of S-SUV max for MACE prediction was 2.05 (AUC=0.690). Multivariate Cox analysis showed that S-SUV max was a strong predictor of MACE (hazard ratio ( HR)=2.434(95% CI: 1.547-3.828), P<0.001). ROC curve showed that the optimal threshold of SUV max to predict MACE was 0.55 (AUC=0.659), and univariate Cox analysis showed that SUV max was a factor to predict MACE ( HR=10.192 (95% CI: 2.667-38.953), P=0.001). In 25 patients with incomplete revascularization (ICR), Kaplan-Meier analysis showed that the incidence of MACE in patients with positive 18F-NaF uptake (single medium stenosis (40%-70%) with SUV max≥0.55) was significantly higher than that in patients with negative 18F-NaF uptake (5/14 vs 0/11; χ2=6.07, P=0.014). Conclusions:18F-NaF PET/CT can be used as an independent predictor of MACE in patients with CAD and can quantitatively assess the long-term progression of moderate coronary artery stenosis. In the future, it is expected to be a new non-invasive way to guide the revascularization treatment decision of multi-vessel CAD.