Purpose To construct and validate a risk prediction model for in-stent restenosis(ISR)nomogram in patients with superficial femoral artery stent implantation.Materials and Methods 150 cases of superficial femoral artery stent implantation patients who were hospitalized in Department of Cardiovascular Surgery of the Second Affiliated Hospital of Army Medical University from February 2016 to November 2022 were retrospectively analyzed.Risk factors for ISR in patients with superficial femoral artery stent implantation were screened using univariate analysis,least absolute shrinkage and selection operator and multifactorial Logistic regression analysis.Nomograms were produced,Bootstrap method was used for internal validation,consistency index was used for model differentiation assessment,and calibration graphs were used for calibration assessment.Results Fifty-five patients(36.7%)with ISR one year after superficial femoral artery stenting were identified.Univariate analysis,least absolute shrinkage and selection operator and Logistic regression showed a history of stroke(OR=9.152,95%CI 2.957-28.322),chronic kidney disease(OR=14.639,95%CI 2.378-90.115),fibrinogen concentration(OR=8.422,95%CI 3.139-22.594),pre-procedural occlusion(OR=3.604,95%CI 1.446-8.981)and calcified plaque(OR=5.167,95%CI 2.044-13.059)were the best predictors of the occurrence of ISR one year post-procedure in patients with stenting of superficial femoral artery.The consistency index of the prediction model was 0.876(95%CI 0.812-0.939),with specificity and sensitivity of 93.6%and 70.9%,respectively;a Brie score of 0.124,and a consistency index after internal validation of the model of 0.859,respectively.Calibration plots showed that the ideal probability curves and the actual probability curves overlapped with each other well.Conclusion The Nomogram risk prediction model of superficial femoral artery stent restenosis constructed in this study has good differentiation and calibration,and is of good value for clinical prediction of ISR in patients with superficial femoral artery stent implantation.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Purpose To construct and validate a risk prediction model for in-stent restenosis(ISR)nomogram in patients with superficial femoral artery stent implantation.Materials and Methods 150 cases of superficial femoral artery stent implantation patients who were hospitalized in Department of Cardiovascular Surgery of the Second Affiliated Hospital of Army Medical University from February 2016 to November 2022 were retrospectively analyzed.Risk factors for ISR in patients with superficial femoral artery stent implantation were screened using univariate analysis,least absolute shrinkage and selection operator and multifactorial Logistic regression analysis.Nomograms were produced,Bootstrap method was used for internal validation,consistency index was used for model differentiation assessment,and calibration graphs were used for calibration assessment.Results Fifty-five patients(36.7%)with ISR one year after superficial femoral artery stenting were identified.Univariate analysis,least absolute shrinkage and selection operator and Logistic regression showed a history of stroke(OR=9.152,95%CI 2.957-28.322),chronic kidney disease(OR=14.639,95%CI 2.378-90.115),fibrinogen concentration(OR=8.422,95%CI 3.139-22.594),pre-procedural occlusion(OR=3.604,95%CI 1.446-8.981)and calcified plaque(OR=5.167,95%CI 2.044-13.059)were the best predictors of the occurrence of ISR one year post-procedure in patients with stenting of superficial femoral artery.The consistency index of the prediction model was 0.876(95%CI 0.812-0.939),with specificity and sensitivity of 93.6%and 70.9%,respectively;a Brie score of 0.124,and a consistency index after internal validation of the model of 0.859,respectively.Calibration plots showed that the ideal probability curves and the actual probability curves overlapped with each other well.Conclusion The Nomogram risk prediction model of superficial femoral artery stent restenosis constructed in this study has good differentiation and calibration,and is of good value for clinical prediction of ISR in patients with superficial femoral artery stent implantation.

Objective To construct HEK 293T cells that express tardigrade Dsup protein fused with green fluorescent protein copGFP in order to study the effect of Dsup protein on proliferation of HEK 293T cells.Methods The CRISPR/Cas9 gene knock-in system was constructed.The target gene fragments of Dsup,copGFP,EF1α and puromycin were amplified by PCR and inserted into pAAVS1-SFFV to construct the fusion vector of Dsup and copGFP,which was known as pAAVS1-SFFV-Dsup-copGFP-EF1α-Puro.pAAVS1-SFFV-Dsup-copGFP-EF1 α-Puro and pAAVS1-CRISPR-Cas9 vector were co-transfected into HEK 293T cells before Dsup gene was inserted into the AAVS1 region of HEK 293T cells via homologous recombination.The HEK 293T cells expressing Dsup gene were obtained following puromycin selection,flow cytometry sorting and genome identification.The expression of Dsup at mRNA and protein levels and proliferation-related genes(MCM2,MCM4,PCNA,Ki-67)were examined to investigate the effects of Dsup gene on the proliferation of HEK 293T-Dsup-copGFP cells.Results The pAAVS1-SFFV-Dsup-copGFP-EF1α-Puro recombinant vector was constructed,and the HEK 293T-Dsup-copGFP cells with Dsup gene inserted in the AAVS1 region were obtained,where both Dsup mRNA and protein were expressed.The cell proliferation rate of HEK 293T-Dsup-copGFP was higher than that of HEK 293T-Control-copGFP(P＜0.001).Further investigation revealed that the expressions of Ki-67 and MCM4 protein in HEK 293T-Dsup-copGFP were significantly higher than in the control group,indicating that the knock in of Dsup gene might enhance the proliferation ability of human cells by promoting the expression of Ki-67 and MCM4 protein.Conclusion A gene editing vector is constructed,and stable cell line HEK 293T-Dsup-copGFP for Dsup fusion expression with copGFP is established.The expression of Dsup gene in HEK 293T cells can promote cell proliferation,possibly by upregulating the expressions of Ki-67 and MCM4 protein.

Objective:To explore the genetic etiology and clinical outcome of a child with co-morbid progressive IgA nephropathy and COQ8B-associated glomerulopathy. Methods:A child who was admitted to Peking University First Hospital on March 2, 2021 was selected as the study subject. Genomic DNA was extracted from peripheral blood samples from the child and his parents and sister. Whole exome sequencing was carried out, and candidate variant was verified by Sanger sequencing. This study was approved by Medical Ethics Committee of the Peking University First Hospital (Ethics No. 2016[1029]).Results:The child, a 7-year-old boy who had developed proteinuria 8 months before, was diagnosed with IgA nephropathy (M1E1S1T1C1). With steroid, cyclophosphamide, cyclosporine and angiotensin-converting enzyme inhibitor therapy, partial remission of proteinuria was achieved. However, his serum creatinine level had increased from 53.8 mol/L at the onset of disease to 86.7 mol/L after 3.9 years, along with massive proteinuria. Kidney biopsy still indicated IgA nephropathy (M0E0S1T0C0). The child was found to harbor a homozygous c. 737G>A (p.Ser246Asn) missense variant of the COQ8B gene, for which his parents and sister were heterozygous carriers. The variant was predicted to be pathogenic (PS1+ PM2_Supporting+ PM3+ PP3+ PP4) based on the guidelines from the American College of Medical Genetics and Genomics. The child was treated with high-dose coenzyme Q10 in combination with steroid and/or mycophenolate mofetil, though his serum creatinine level still increased to 286 mol/L after 7.3 years, which conformed to a chronic kidney disorder with glomerular filtration rate category of G3b. Conclusion:The homozygous c.737G>A missense variants of the COQ8B gene probably underlay the progressive kidney dysfunction in this child. For children with IgA nephropathy presenting with atypical clinical manifestations, unsatisfactory therapeutic effect, and/or early onset of kidney function decline, coexistence of other diseases should be suspected.

Image-enhanced endoscopy(IEE)is an advanced endoscopic imaging technique utilized to enhance the visualization of mucosal surface patterns and microvascular system features of gastrointestinal lesions,playing a pivotal role in real-time diagnosis.Real-time optical diagnosis can be achieved through various tools and techniques,including narrow band imaging(NBI),Pentax endoscopy(i-SCAN),flexible spectral imaging color enhancement(FICE),blue laser imaging(BLI),and linked-color imaging(LCI).This article provides a comprehensive review on the application progress of IEE in detecting colorectal lesions,aiming to establish a novel theoretical foundation for clinical detection of such lesions.