This study investigated the role of the nuclear factor of activated T cells c3 (NFATc3) in vascular smooth muscle cells (VSMCs) during aortic aneurysm and dissection (AAD) progression and the underlying molecular mechanisms. Cytoplasmic and nuclear NFATc3 levels were elevated in human and mouse AAD. VSMC-NFATc3 deletion reduced thoracic AAD (TAAD) and abdominal aortic aneurysm (AAA) progression in mice, contrary to VSMC-NFATc3 overexpression. VSMC-NFATc3 deletion reduced extracellular matrix (ECM) degradation and maintained the VSMC contractile phenotype. Nuclear NFATc3 targeted and transcriptionally upregulated matrix metalloproteinase 9 (MMP9) and MMP2, promoting ECM degradation and AAD development. NFATc3 promoted VSMC phenotypic switching by binding to eukaryotic elongation factor 2 (eEF2) and inhibiting its phosphorylation in the VSMC cytoplasm. Restoring eEF2 reversed the beneficial effects in VSMC-specific NFATc3-knockout mice. Cabamiquine-targets eEF2 and inhibits protein synthesis-inhibited AAD development and progression in VSMC-NFATc3-overexpressing mice. VSMC-NFATc3 promoted VSMC switch and ECM degradation while exacerbating AAD development, making it a novel potential therapeutic target for preventing and treating AAD.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Purpose To summarize the clinical pathological and immunohistochemical characteristics of esophage-al carcinoma with ductal differentiation of esophageal gland,and analyze the somatic mutation characteristics,key driv-ing mutation genes,and significantly mutated genes based on whole exome sequencing.Methods The clinicopatho-logical features of 9 cases of esophageal carcinoma with esophageal duct differentiation were retrospectively analyzed,and the immunohistochemistry EnVision two-step method was used to stain them,and 3 of the samples were subjected to whole exome sequencing and data analysis.Results Among the 9 patients,6 were males and 3 were females.The average age was 68.3 years old(61-80 years old).All 9 cases were located in the middle-lower segment of the e-sophagus.The diameter of the lesion was from 1.5 cm to 3.5 cm.Most areas of the tumor had a double-layer epithelial structure,including the inner layer of luminal epithelium and the outer layer of basal epithelium.Focal areas could be seen with keratinization and mucinous cells.Immunohistochemistry showed that CK7 was positive in the inner epitheli-um,while p63 was positive in the outer basal epithelium.S-100,SOX10 and c-myb were all negative,and p53 was mutated(diffuse strongly positive).The results of whole exome sequencing analysis showed somatic mutation character-istics(796 SNV,37 InDel,482 CNV),key driving mutation genes(12),and significantly mutated genes(TP53).No intraepithelial neoplasia was observed on the surface squamous epithelium of all cases,and no Barrett's esophagus or ectopic gastric mucosa was observed.The average follow-up time was 21.9 months(8 days-51 months),with 8 ca-ses surviving and 1 case dying of severe pulmonary infection 8 days after surgery.Conclusion Esophageal carcinoma with ductal differentiation of esophageal gland is a rare epithelial derived malignant tumor of the esophagus,character-ized by unique morphological,immunohistochemical,and molecular changes.

Purpose To summarize the clinical pathological and immunohistochemical characteristics of esophage-al carcinoma with ductal differentiation of esophageal gland,and analyze the somatic mutation characteristics,key driv-ing mutation genes,and significantly mutated genes based on whole exome sequencing.Methods The clinicopatho-logical features of 9 cases of esophageal carcinoma with esophageal duct differentiation were retrospectively analyzed,and the immunohistochemistry EnVision two-step method was used to stain them,and 3 of the samples were subjected to whole exome sequencing and data analysis.Results Among the 9 patients,6 were males and 3 were females.The average age was 68.3 years old(61-80 years old).All 9 cases were located in the middle-lower segment of the e-sophagus.The diameter of the lesion was from 1.5 cm to 3.5 cm.Most areas of the tumor had a double-layer epithelial structure,including the inner layer of luminal epithelium and the outer layer of basal epithelium.Focal areas could be seen with keratinization and mucinous cells.Immunohistochemistry showed that CK7 was positive in the inner epitheli-um,while p63 was positive in the outer basal epithelium.S-100,SOX10 and c-myb were all negative,and p53 was mutated(diffuse strongly positive).The results of whole exome sequencing analysis showed somatic mutation character-istics(796 SNV,37 InDel,482 CNV),key driving mutation genes(12),and significantly mutated genes(TP53).No intraepithelial neoplasia was observed on the surface squamous epithelium of all cases,and no Barrett's esophagus or ectopic gastric mucosa was observed.The average follow-up time was 21.9 months(8 days-51 months),with 8 ca-ses surviving and 1 case dying of severe pulmonary infection 8 days after surgery.Conclusion Esophageal carcinoma with ductal differentiation of esophageal gland is a rare epithelial derived malignant tumor of the esophagus,character-ized by unique morphological,immunohistochemical,and molecular changes.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To monitor the dynamic changes of radiation-induced parotid damage using T2 ? mapping.Methods Thirty-four patients with nasopharyngeal carcinoma (NPC)were enrolled.All patients underwent T1 WI,T2 WI and T2 ? mapping for bilateral parotid glands at pre-RT (2 weeks before radiotherapy),mid-RT (5 weeks after the beginning of radiotherapy)and post-RT (4 weeks after the completion of radiotherapy).Parotid MR parameters,mean radiation dose and xerostomia degrees of the patients at different time points were recorded.Furthermore,nine healthy volunteers were enrolled,who undergone T2 ? mapping twice with an interval of 4 weeks in order to analyze the reproducibility of T2 ? value.Results From pre-RT to mid-RT and post-RT,parotid volume decreased [atrophy rates,(25.34±11.33)％ and (25.74±9.93)％,respectively]and T2 ? values decreased [change rates,(-5.63±8.86)％ and (-4.81±10.67)％, respectively]significantly (all P < 0.01 ).Parotid normalized T1 signal intensity decreased significantly from pre-RT to post-RT [change rate,(-7.43±10.61)％,P =0.007],and the change rate was correlated inversely with mean radiation dose significantly (r =-0.646, P <0.001).Parotid volume and T2 ? value changed correspondingly with xerostomia degrees of the patients during radiotherapy.Parotid MR parameters showed excellent reproducibility (intraclass correlation coefficient,0.843 -0.993).Conclusion The dynamic changes of radiation-induced parotid damage in patients with NPC can be noninvasively evaluated by routine MRI and T2 ? mapping.

Objective To compare and analyze the supply of blood collection and clinical blood demand in Hangzhou during 2011-2016,and to put forward some countermeasures and suggestions.Methods The related data of blood collection in blood center and the indexs of clinical blood demand in all hospitals in Hangzhou were collected during 2011-2016,and the growth rates of both of them were compared and analyzed.Results 1) The data of blood collection and supply was the lowest in 2012,and then increased year by year.The average annual growth of platelet collection and supply was 8.09％ and 8.47％,respectively,and the other indicators grew relatively gently.In 2016,the rate of blood donation reached 18.28 per thousand people.At the same period,the number of staff in institutions was basically stable.2) During 2011-2016,the blood demand of all hospitals in Hangzhoa maintained rapid growth.In Hangzhou,the number of hospitals increased by 10.65％ annually,and until 2016,there was an increase of 65.87％ over 2011.The average annual growth of the number of beds,the number of emergency patients and the number of inpatients increased by 10.21％,6.09％ and 11.40％ respectively.The growth rate of number of inpatients was higher than that of outpatient and emergency departments.Hospital employees remained at an average annual growth rate of nearly 10％.3) The clinical demand for blood increased significantly more higher than the growth of blood collection and supply.Conclusion Speed up the pace of the construction of blood supply,and keep pace with the construction of hospitals.Strengthening the publicity,health education and promotion models,in order to encourage more people,who are eligible for blood donation,to join the blood donation.And also strengthening personnel team building,improving overall work efficiency and level.

Objective To explore the value of gemstone spectral imaging (GSI)in quantitative evaluation of Lauren classification of gastric cancer.Methods Fifty-two patients with gastric cancer confirmed by gastroscopy underwent contrast-enhanced spectral CT imaging preoperatively.The monoergic and iodine-based images were obtained by GSI Viewer software,CT value and iodine concentration (IC)of the lesions were measured,and normalized iodine concentration (NIC)was calculated.With the reference of postoperative pathology,data were analyzed by LSD method of one-way analysis of variance.Results The IC,NIC,spectrum curve slope of 40-70 keV,40-140 keV and 70-140 keV energy range of intestinal type,mixed type and diffuse type carcinoma in the arterial phase were 12.86±6.80 (100 μg/mL),0.13±0.06 ,2.50±1.26 ,0.99±0.51 ,0.34±0.20 ,18.54±6.49 (100 μg/mL),0.19±0.07, 3.56±1.24,1.42±0.50,0.50±0.18 and 24.52±9.68 (100 μg/mL),0.24±0.09,4.73±1.76,1.90±0.73,0.68±0.29,respectively. The values of intestinal type were all significantly lower than those of diffuse type (P <0.05).Comparison between intestinal-mixed type and mixed-diffuse type,the other parameters were no significant differences except IC between intestinal-mixed type (P=0.037).Conclusion The slope of spectrum curve,iodine concentration,and normalized iodine concentration could be helpful for preoperative evaluation of Lauren classification of gastric cancer.

Objective To assess the histological characteristics of cervical cancer using intravoxel incoherent motion magnetic resonance imaging ( IVIMMRI) and to investigate the performance of IVIMMRI in evaluation of the efficacy of concurrent chemoradiotherapy in the treatment of intermediate/advanced cervical cancer. Methods Pelvic MRI scans, containing T2WI, IVIM (14 b values, b=0?1 000 s/mm2), and contrast?enhanced T1 scans were performed in 23 patients pathologically diagnosed with intermediate/advanced cervical cancer ( stage ≥Ⅱb ) before chemoradiotherapy, after two and four weeks of treatment, and at the end of treatment. The IVIMMRI data were processed with the bi?exponential model to generate three parameters, containing pure diffusion coefficient ( D ) , pseudodiffusion coefficient ( D?) , and perfusion fraction ( f ) . Apparent diffusion coefficient ( ADC ) was obtained using the mono?exponential model. The IVIMMRI parameters were measured at each time point and their dynamics and correlation were analyzed. Results The ADC, D, and f values were significantly higher after complete treatment ( 0?96 × 10-3 vs. 1?77 × 10-3 mm2/s, P=0?000;0?76 × 10-3 vs. 1.34± 0?12 × 10-3 mm2/s, P=0?000;0?14% vs. 0?24%, P=0?012). The above three values significantly increased after two weeks of treatment (all P=0?000) and kept increasing until the end of the treatment. In contrast, the D? value was reduced from the second week to the end of the treatment. Conclusions IVIMMRI can monitor the dynamic functional changes and early tumor responses during chemoradiotherapy for cervical cancer, which holds promise for clinical application.