Objective To investigate the role of activating transcription factor 4 (ATF4) in benign prostatic hyperplasia (BPH) in order to elucidate the molecular mechanism underlying BPH progression. Methods Firstly, we analyzed the correlation between the expression of ATF4 and the volume of prostate transition zone in BPH tissues using publicly available datasets. Subsequently, we explored the potential association among ATF4, epithelial-mesenchymal transition (EMT) and BPH through single-cell RNA sequencing (scRNA-seq). Finally, we validated the findings by silencing ATF4 and treating BPH cells with ATF4 protein inhibitors, followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR), CCK-8 assay, and Western blot. Results The expression of ATF4 in BPH tissues exhibited a significant positive correlation with the volume of prostate transition zone (r=0.64, P＜0.05). scRNA-seq analysis revealed that ATF4 was significantly upregulated in the prostate epithelial cells of BPH patients (P＜0.05), and its expression demonstrated a significant positive correlation with the Hallmark EMT singscore (r=0.14, P＜0.05). In vitro experiments further indicated that knockdown of ATF4 led to a significant reduction in the proliferative activity of BPH-1 cells (P＜0.05). Similarly, inhibition of ATF4 activity resulted in a marked decrease in the proliferative capacity and EMT of BPH-1 cells (P＜0.05). Conclusion ATF4 may exert a promoting effect on BPH by modulating the EMT signaling pathway;therefore, ATF4 may serve as a novel therapeutic target of BPH.

Purpose To evaluate the effectiveness of deep learning image reconstruction(DLIR)algorithms in reconstructing lumbar vertebrae images from abdominal CT scans,aiming to reduce radiation dose and eliminate the need for repeat lumbar CT examinations.Materials and Methods A retrospective collection was conducted from March to May 2024 in the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine.Thirty-two patients who underwent both abdominal and lumbar CT scans in a supine head-first position were enrolled.The abdominal CT(DLIR group)utilized a tube voltage of 120 kVp and a current of 200 mA with high-intensity DLIR for lumbar reconstruction.The standard lumbar CT(lumbar group)used the same voltage with a tube current of 260 mA and was reconstructed using 60%weighted adaptive statistical iterative reconstruction.Objective assessments was used to measure the CT values,noise(standard deviation,SD value),signal-to-noise ratio and contrast-to-noise ratio(excluding adipose tissue)at the third lumbar vertebral pedicle level and the L2/L3 intervertebral disc level for muscle,adipose tissue,cancellous bone,intervertebral discs,dura mater and cortical bone.Subjective assessments employed a five-point scale to evaluate image contrast,noise and sharpness.Results The volume CT dose index in lumbar group and DLIR group were 15.25 mGy and 11.74 mGy,respectively.There was no statistical difference in CT values between the structures of both groups(all P>0.05).Compared with the lumbar group,the DLIR group showed significant reductions in SD values across the measured tissues by 31.09%,35.66%,13.48%,27.82%,24.93%and 15.09%(t=5.09-7.21,all P<0.05).The signal-to-noise ratio improved by 36.40%,52.31%,16.56%,34.13%,38.39%and 18.81%,and the contrast-to-noise ratio improved by 51.70%,51.32%,36.24%,34.47%and 53.56%(t=-9.58--4.23,all P<0.001).The DLIR group significantly outperformed the lumbar group in image contrast[4.45(4.00,5.00)points vs.4.75(4.00,5.00)points],image noise[4.06(4.00,4.00)points vs.4.39(4.00,5.00)points],and spatial resolution of fine structures[4.00(4.00,4.00)points vs.4.27(4.00,5.00)points](Z=-3.80,-4.38,-3.55,all P<0.001).Conclusion Using high-intensity DLIR for abdominal examinations can achieve high-quality lumbar CT images with a 25%reduction in radiation dose,enabling simultaneous abdominal and lumbar scanning in a single session.

Objective To explore the mechanism of primary care physicians' willingness to adopt smart healthcare in H City,Anhui Province,and to provide a basis for decision-making to promote their practice effectively.Methods It use the rooting theory to obtain the key elements and combine the UTAUT model and the information stem success model to construct a theory model of factors influencing primary care physicians' willingness to adopt smart health-care.Data were collected through questionnaires,and structural equation modeling and fuzzy sets were used to ana-lyze the influence pathways and antecedent constructs qualitatively and empirically.Results Performance quality,ef-fort expectation,social influence,convenience,system quality,and information quality had a significant positive ef-fect on willingness to use,and effort expectation positively influenced willingness to use through performance expec-tation(P＜0.05).The core conditions of information quality and system quality could constitute the five combined in-fluence pathways in both models.Conclusion Measures can be taken to enhance the adoption willingness of primary care doctors,such as strengthening the collaborative governance of multiple actors,strengthening the design of the top-level system,and exploring and cultivating"opinion leaders".

Objective:To explore the predictive value of miR-21 combined with high mobility group box-1 protein (HMGB1) for postoperative prognosis in patients with hypertensive intracerebral hemorrhage (HICH).Methods:A total of 137 HICH patients (HICH group) admitted to the Central Hospital of Yongzhou from March 2021 to March 2023 were retrospectively selected, and 60 healthy subjects undergoing physical examination in the same hospital during the same period were enrolled as the control group. Serum miR-21 and HMGB1 levels were compared between the two groups, and differences in serum miR-21 and HMGB1 levels among HICH patients with different disease severities and prognoses were analyzed. Univariate and multivariate logistic regression analyses were used to screen influencing factors for postoperative prognosis in HICH patients, and receiver operating characteristic (ROC) curve was applied to evaluate the predictive value of miR-21 combined with HMGB1 for postoperative prognosis.Results:The relative expression level of serum miR-21 on postoperative day 1 in the HICH group was significantly lower than that in the control group ( P<0.05), while the HMGB1 level was significantly higher ( P<0.05). With the aggravation of HICH severity, the relative expression of serum miR-21 significantly decreased (all P<0.05), while the HMGB1 level significantly increased (all P<0.05). The relative expression of serum miR-21 in the good prognosis group was significantly higher than that in the poor prognosis group ( P<0.05), while the HMGB1 level was significantly lower ( P<0.05). Univariate and multivariate logistic regression analyses showed that miR-21, HMGB1, preoperative Glasgow Coma Scale (GCS) score, and preoperative hematoma volume were influencing factors for postoperative prognosis in HICH patients (all P<0.05). ROC curve showed that the areas under the curve (AUC) of miR-21 and HMGB1 for predicting poor postoperative prognosis in HICH patients were 0.925 and 0.913, respectively, while the AUC of miR-21 combined with HMGB1 was 0.950. Conclusions:Peripheral blood miR-21 is significantly decreased and HMGB1 level is significantly increased in HICH patients. miR-21 combined with HMGB1 has a good predictive value for poor postoperative prognosis in patients with hypertensive intracerebral hemorrhage.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Iatrogenic bile duct injury(IBDI)is a common type of bile duct injury,most frequently occurring during cholecystectomy.With the widespread use of laparoscopic cholecystectomy,its incidence is significantly higher than that of open surgery,and the number of complex cases combined with vascular injury(VI)has been increasing,posing greater challenges for diagnosis and treatment.In severe cases,it may result in hepatic ischemia and atrophy.Hepaticojejunostomy is the standard reconstructive procedure after bile duct injury,whereas hepatectomy may be required when VI is involved.We report the case of a 53-year-old woman who was admitted with bile leakage following cholecystectomy.After two multidisciplinary team(MDT)discussions,preoperative evaluation revealed injury to the right hepatic artery and a portal vein branch,accompanied by atrophy of the right anterior lobe.Based on intraoperative findings,the patient underwent right hepatectomy combined with Roux-en-Y hepaticojejunostomy of the left hepatic duct.Postoperative recovery was uneventful,and the patient remained symptom-free during a 6-month follow-up.By reviewing the diagnosis and management of this case in conjunction with relevant literature,we summarize the clinical features,treatment strategies,and the value of MDT management in complex IBDI,aiming to provide reference for clinical practice.

Objective To explore the relationship between systemic immune-inflammation index(SⅡ)at admission and occurrence of early neurological deterioration(END)in patients with branch atheromatous disease(BAD).Methods A retrospective analysis was performed on 326 BAD patients admitted in Department of Neurology of Handan Central Hospital from October 2021 to February 2024.Based on occurrence of END or not,they were divided into END group(97 cases)and non-END group(229 cases).Clinical data of the patients were collected,and multivari-ate logistic regression analysis was used to identify the END risk variables in BAD patients.ROC curve was plotted to evaluate the value of NIHSS score,hs-CRP and SⅡ in predicting the inci-dence of END in the patients.Results Significantly advanced age,higher NIHSS score at admis-sion,and elevated hs-CRP level,neutrophil count and SⅡ,but lower platelet and lymphocyte counts were observed in the END group than the non-END group(P＜0.05,P＜0.01).Multi vari-ate logistic regression analysis indicated that NIHSS score at admission(OR=1.134,95％CI:1.050-1.226,P=0.001),hs-CRP(OR=1.131,95％CI:1.024-1.249,P=0.015),and SⅡ(OR=1.001,95％CI:1.001-1.002,P=0.003)were independent risk factors for END in BAD patients.The AUC value of SⅡ in the prediction of END was 0.660,which was significantly higher than that of NIHSS score and hs-CRP in BAD patients(P＜0.05).Conclusion SⅡ is an independent risk factor for END in BAD patients,and SⅡ at admission has a certain predictive value for the oc-currence of END in these patients.

Objective To explore the mechanism of primary care physicians' willingness to adopt smart healthcare in H City,Anhui Province,and to provide a basis for decision-making to promote their practice effectively.Methods It use the rooting theory to obtain the key elements and combine the UTAUT model and the information stem success model to construct a theory model of factors influencing primary care physicians' willingness to adopt smart health-care.Data were collected through questionnaires,and structural equation modeling and fuzzy sets were used to ana-lyze the influence pathways and antecedent constructs qualitatively and empirically.Results Performance quality,ef-fort expectation,social influence,convenience,system quality,and information quality had a significant positive ef-fect on willingness to use,and effort expectation positively influenced willingness to use through performance expec-tation(P＜0.05).The core conditions of information quality and system quality could constitute the five combined in-fluence pathways in both models.Conclusion Measures can be taken to enhance the adoption willingness of primary care doctors,such as strengthening the collaborative governance of multiple actors,strengthening the design of the top-level system,and exploring and cultivating"opinion leaders".

Objective:To explore the predictive value of miR-21 combined with high mobility group box-1 protein (HMGB1) for postoperative prognosis in patients with hypertensive intracerebral hemorrhage (HICH).Methods:A total of 137 HICH patients (HICH group) admitted to the Central Hospital of Yongzhou from March 2021 to March 2023 were retrospectively selected, and 60 healthy subjects undergoing physical examination in the same hospital during the same period were enrolled as the control group. Serum miR-21 and HMGB1 levels were compared between the two groups, and differences in serum miR-21 and HMGB1 levels among HICH patients with different disease severities and prognoses were analyzed. Univariate and multivariate logistic regression analyses were used to screen influencing factors for postoperative prognosis in HICH patients, and receiver operating characteristic (ROC) curve was applied to evaluate the predictive value of miR-21 combined with HMGB1 for postoperative prognosis.Results:The relative expression level of serum miR-21 on postoperative day 1 in the HICH group was significantly lower than that in the control group ( P<0.05), while the HMGB1 level was significantly higher ( P<0.05). With the aggravation of HICH severity, the relative expression of serum miR-21 significantly decreased (all P<0.05), while the HMGB1 level significantly increased (all P<0.05). The relative expression of serum miR-21 in the good prognosis group was significantly higher than that in the poor prognosis group ( P<0.05), while the HMGB1 level was significantly lower ( P<0.05). Univariate and multivariate logistic regression analyses showed that miR-21, HMGB1, preoperative Glasgow Coma Scale (GCS) score, and preoperative hematoma volume were influencing factors for postoperative prognosis in HICH patients (all P<0.05). ROC curve showed that the areas under the curve (AUC) of miR-21 and HMGB1 for predicting poor postoperative prognosis in HICH patients were 0.925 and 0.913, respectively, while the AUC of miR-21 combined with HMGB1 was 0.950. Conclusions:Peripheral blood miR-21 is significantly decreased and HMGB1 level is significantly increased in HICH patients. miR-21 combined with HMGB1 has a good predictive value for poor postoperative prognosis in patients with hypertensive intracerebral hemorrhage.

Cushing′s syndrome refers to a group of disorders caused by excessive secretion of adrenal glucocorticoid due to various underlying etiologies. Among these, ACTH-dependent Cushing′s syndrome, in which the source of ACTH-secretion remains unclear for extended periods, poses significant challenges in clinical management. This article presents a patient with ACTH-dependent Cushing′s syndrome where the ACTH-secreting source could not be definitively localized from our hospital. Additionally, the article reviews recent advancements in the diagnosis and treatment of such cases, both domestically and internationally, with the aim of enhancing clinicians′ understanding and improving the management of this condition.