Objective To discuss the safety and efficacy of straight light beam greenlight photoselective vaporesection of the prostate (PVRP) and photoselective vaporization of the prostate (PVP) in treatment of benign prostatic hyperplasia. Methods 113 cases of BPH were randomly divided into two groups, 62 cases in PVRP group and 51cases in PVP group. Clinical data was collected and compared between the two groups, including pre-operation and six month after operation international prostate symptom score (IPSS), quality of life (QOL), urine flow rate (Qmax), postvoid residual urine (PVR), as well as operational time, operative bleeding volume, bladder irrigation time, indwelling catheter time after operation and complications after operation. Results All the patients were operated successfully without serious complications. There was significant difference in operative time [(49.4 ± 18.9) min vs (75.1 ± 20.7) min (P < 0.05)] between the two groups. There were no significant difference in blood loss and bladder washing time after operation. The Qmax after 6 months of surgery, PVR, IPSS, QOL of the two groups had significantly improved compared with preoperative (P < 0.05), while the difference between the two groups had no significance in statistics (P > 0.05). Conclusions Treatment of straight light beam greenlight PVRP and PVP are safe and effective for BPH. Straight light beam greenlight PVRP has the advantages of shorter operation time.

Objective:To compare the clinical efficacy of minimally invasive anterior column screw placement assisted by orthopedic robot with anterior subcutaneous internal fixation (INFIX) in the treatment of unstable pelvic fracture.Methods:A retrospective cohort study was conducted to analyze 42 patients (25 males and 17 females; aged 16-68 years [(41.8±3.2)years] with unstable pelvic fracture admitted to Guizhou Provincial People′s Hospital from June 2018 to December 2021. Anterior column screw group ( n=22) received orthopedic robot-assisted anterior column screw fixation of anterior pelvic ring fracture, and INFIX group ( n=20) received subcutaneous INFIX of anterior pelvic ring fracture. Posterior pelvic ring injuries were treated with closed reduction and percutaneous sacroiliac screw internal fixation. The operation time of anterior pelvic ring fixation, intraoperative blood loss, intraoperative fluoroscopy times, off-bed activity time when the visual analogue scale (VAS) was<3 points during weight-bearing and fracture healing time were compared between the two groups. The quality of pelvic fracture reduction was assessed according to the Matta scoring criteria at 2 days after surgery. The Majeed functional score was used to assess the functional status at the last follow-up. Intraoperative and postoperative complications were observed in both groups. Results:All patients were followed up for 6-24 months [(11.3±0.5)months].The operation time of anterior pelvic ring fixation was (33.4±2.6)minutes in anterior column screw group and (30.2±2.9)minutes in INFIX group ( P>0.05). The intraoperative blood loss was (15.9±3.1)ml in anterior column screw group and (41.4±6.2)ml in INFIX group ( P<0.01). The intraoperative fluoroscopy times were 12.2±2.4 in anterior column screw group and 14.7±2.5 in INFIX group ( P>0.05). The off-bed activity time was (3.2±0.4) weeks in anterior column screw group and (6.6±1.2)weeks in INFIX group ( P<0.01). The fracture healing time was (12.7±1.4)weeks in anterior column screw group and (16.2±1.9) weeks in INFIX group ( P<0.01). According to Matta scoring criteria, the excellent and good rate of posterior pelvic ring reduction quality was 100% in both groups, while the excellent and good rate of the quality of anterior pelvic ring reduction was 100% (excellent in 16 patients and good in 6) in anterior column screw group compared with 90.0% (excellent in 11 patients, good in 7, and fair in 2) in INFIX group ( P<0.05). During the final follow-up, the excellent and good rate of Majeed functional score was 90.9% (excellent in 16 patients, good in 4 and fair in 2) in anterior column screw group, significantly different from 80.0% (excellent in 10 patients, good in 6 and fair in 4) in INFIX group ( P<0.05). During the operation, no important tissue injuries such as blood vessels, nerves or spermatic cord occurred in either group. In anterior column screw group, no postoperative complications such as infection, spermatic cord injury or implant breakage occurred; in INFIX group, there were 2 patients with incision fat liquefaction, 4 with lateral femoral cutaneous nerve symptoms and 1 with heterotopic ossification, without the occurrence of implant breakage. Conclusion:Compared with anterior subcutaneous INFIX, orthopedic robot-assisted anterior column screw internal fixation for the treatment of unstable pelvic fracture has advantages of less bleeding, earlier tambulation, faster fracture healing, better fracture reduction quality, more satisfied postoperative functional recovery, and fewer complications.

Objective:To explore the value of nodal integrated topological attributes (NITA) based on machine learning model in identifying schizophrenia.Methods:A total of 56 patients with first-onset schizophrenia admitted to Department of Psychiatry, Second Affiliated Hospital of Xinxiang Medical University from January 2022 to August 2023 and 56 healthy volunteers recruited from community were selected. Functional MRI data were collected, and brain functional networks were constructed after preprocessing. Global and nodal topological attributes were extracted using graph theory as training features. Participants were divided into training set (46 schizophrenia patients and 46 heathy volunteers) and testing set (10 schizophrenia patients and 10 heathy volunteers). Random Forest Classifier (RFC), Support Vector Machine (SVM), and Gradient Boosting Tree (XGBoost) models were fitted to global and nodal topological attributes in the training set to calculate the accuracy, recall rate, F1 value, and area under receiver operating characteristic curve (AUC) of each model. Generalization ability was analyzed based on the performance of testing set, and excellent topological attributes were screened out. Selected topological attributes were reduced to one-dimensional features through principal component analysis,and then fitted to the above models, and feature-adapted model was selected based on the performances of training and testing sets. Statistical analysis of the new dimensional features of each brain region of schizophrenia patients and heathy volunteers was performed. Combined with false discovery rate (FDR), new dimension features with significant differences were selected and fitted with the adapted model.Results:In the training set, machine learning models using node topological attributes achieved higher accuracy, recall rate, F1 scores, and AUC compared with those using global topological attributes. In the test set, the SVM model using node topological attributes showed stable generalizability (accuracy=75.00%, recall rate=100.00%, F1 score=0.80, AUC=0.92). The node topological attribute metrics were down-dimensionally named NITA. Based on validation results of SVM model using NITA in the training set (accuracy of 77.00%, recall of 72.00%, F1 value of 0.76, AUC of 0.86) and performance in the testing set (accuracy of 66.67%, recall of 83.33%, F1 value of 0.71, AUC of 0.61), SVM was selected as the adapted model. NITA in the right middle frontal gyrus ventrolateral area, left inferior frontal gyrus dorsal area, right precentral gyrus caudal ventrolateral area, left superior temporal gyrus rostral area, right fusiform gyrus lateroventral area, right inferior parietal lobule rostrodorsal area, left occipital polar cortex showed significant difference between patients and volunteers ( P<0.05, FDR-corrected). The optimal model (FDR-PCAN-SVM) obtained via NITA being trained on corresponding brain area reached an accuracy of 93.74%, recall rate of 98.00%, F1 value of 0.94, and AUC of 0.96 in the training set and accuracy of 83.33%, recall rate of 66.67%, F1 value of 0.80, and AUC of 0.92 in the testing set. Conclusion:NITA may serve as a potential image biomarker for schizophrenia identification; brain regions with abnormal NITA is key nodes in information exchange and integration within the brain networks in schizophrenia patients.

Objective To conduct a comparative analysis of the biomechanical characteristics of the lower limbs during stair descent in patients with hemiplegia using different method to provide theoretical references for reducing fall risk during stair descent.Methods Ten healthy subjects and 20 patients with hemiplegia were selected,and their kinematic and dynamic data during stair descent were collected using the Qualisys Motion capture system and the Kistler three-dimensional dynamometer.Their biomechanical characteristics and fall risks were also analyzed.Results Compared with that of healthy subjects and patients that step on the healthy side(SHS),the range of motion(ROM)of the affected side in the lower-limb joints of patients that step on the affected side(SAS)was smaller.SHS reduced the flexion and extension ranges of the healthy side of the knee joint,and the ROM of the affected side in the lower-limb joints of SHS patients was greater than that of SAS patients.The ground reaction force(GRF)curve changes of SAS patients in left and right directions during stair descent were relatively consistent with those of normal subjects.The maximum vertical GRF of the affected side in SAS patients at the moment of landing was 1.05 times the body weight,whereas that of the healthy side was 1.25 times the body weight,which was lower than that of normal subjects(1.5 times the body weight).The maximum vertical GRF of the healthy side in SHS patients at the moment of landing was 1.85 times the body weight,which was higher than that of SAS patients and normal subjects.Conclusions Compared with that of SAS patients,the affected limb side of SHS patients has a greater ROM and vertical GRF at the moment of landing during stair descent,making SHS difficult to master.SAS is most consistent with the biomechanical characteristics during stair descent of patients with hemiplegia.

Objective To predict the torque on the affected side of the hip,knee,and ankle joints in stroke patients during walking using principal component analysis(PCA)and backpropagation(BP)neural networks.Methods Kinematic and dynamic data from 30 stroke patients were synchronously collected using an 8-lens Qualisys infrared point high-speed motion capture system and Kistler three-dimensional(3D)force measurement platform.The torques of the hip,knee,and ankle joints in the stroke patients were calculated using OpenSim,and the initial variables with a cumulative contribution rate of 99％were screened using PCA.The normalized root mean square error(NRMSE),root mean square error(RMSE),mean absolute percentage error(MAPE),mean absolute error(MAE),and R2 were used as evaluation indicators for the PCA-BP model.The consistency between the calculated joint torque and predicted torque was evaluated using Kendall's W coefficient.Results PCA data showed that the trunk,pelvis,and affected sides of the hip,knee,and ankle joints had a significant impact on the torque of the affected sides of the hip,knee,and ankle joints on the x,y,and z axes(sagittal,coronal,and vertical axes,respectively).The NRMSE between predicted and measured values was 5.14％-8.86％,RMSE was 0.184-0.371,MAPE was 3.5％-4.0％,MAE was 0.143-0.248,and R was 0.998-0.999.Conclusions The established PCA-BP model can accurately predict the torque of the hip,knee,and ankle joints in stroke patients during walking,with a significantly shortened measurement time.This model can replace traditional joint torque calculation in the gait analysis of stroke patients,provides a new approach to obtaining biomechanical data of stroke patients,and is an effective method for the clinical treatment of stroke patients.

[Abstract] Objective: To explore the expression of long non-coding RNA (lncRNA) GTSE1-AS1 in prostate cancer tissues and the mechanism that affects the proliferation and invasion of LNCaP cells. Methods: From November 2017 to December 2018, 68 pairs of prostate cancer tissue and para-cancerous tissue specimens were resected from prostate cancer patients at the Department of Urology of Luoyang Central Hospital Affiliated to Zhengzhou University; in addition, prostate cancer cell lines LNCaP, PC-3, C4-2B, 22Rv1, DU-145 and normal prostate follicular epithelial RWPE-1 cells were also chosen for this study. qPCR was used to detect the expression level of GTSE1-AS1 in cancer tissues and cell lines. The GTSE1-AS1 over-expression plasmid (experimental group) and negative control plasmid (control group) were respectively transfected into LNCap cells. MTT assay and Transwell chamber method were used to detect the effect of GTSE1-AS1 over-expression on the proliferation and invasion ability of LNCaP cells, respectively. The targeting relationship among GTSE1-AS1 and miR-324-3P as well as FBXW7 (F-frame/WD repeat domain protein 7) was verified by bioinformatics tools and dual-luciferin reporter gene assay. The effect of GTSE1-AS1 over-expression on downstream gene and protein expression was detected by qPCR and WB assay. Results: The expression level of GTSE1-AS1 in prostate cancer tissues was significantly lower than that in para-cancerous tissues (P<0.01), and the expression of GTSE1-AS1 in prostate cancer cell lines was significantly lower than that in RWPE-1 cells (P<0.05 or P<0.01). Over-expression of GTSE1-AS1 significantly inhibited the proliferation and invasion (P<0.05 or P<0.01) of LNCaP cells. Dual-luciferin reporter gene assay confirmed the complementary binding between GTSE1-AS1 and miR-324-3p as well as between miR-324-3p and FBXW7. Over-expression of GTSE1-AS1 significantly reduced the expression of miR-324-3p in LNCaP cells (P<0.01), and promoted the mRNA and protein expressions of FBXW7 (all P<0.01). Conclusion: GTSE1-AS1 is under-expressed in prostate cancer tissues and cell lines. Over-expression of GTSE1-AS1 can inhibit the proliferation and invasion of LNCaP cells, the mechanism of which may be related with the inhibition of miR-324-3p to further promote FBXW7 expression.

The typical hallmark of tumor evolution is metabolic dysregulation. In addition to secreting immunoregulatory metabolites, tumor cells and various immune cells display different metabolic pathways and plasticity. Harnessing the metabolic differences to reduce the tumor and immunosuppressive cells while enhancing the activity of positive immunoregulatory cells is a promising strategy. We develop a nanoplatform (CLCeMOF) based on cerium metal-organic framework (CeMOF) by lactate oxidase (LOX) modification and glutaminase inhibitor (CB839) loading. The cascade catalytic reactions induced by CLCeMOF generate reactive oxygen species "storm" to elicit immune responses. Meanwhile, LOX-mediated metabolite lactate exhaustion relieves the immunosuppressive tumor microenvironment, preparing the ground for intracellular regulation. Most noticeably, the immunometabolic checkpoint blockade therapy, as a result of glutamine antagonism, is exploited for overall cell mobilization. It is found that CLCeMOF inhibited glutamine metabolism-dependent cells (tumor cells, immunosuppressive cells, etc.), increased infiltration of dendritic cells, and especially reprogrammed CD8⁺ T lymphocytes with considerable metabolic flexibility toward a highly activated, long-lived, and memory-like phenotype. Such an idea intervenes both metabolite (lactate) and cellular metabolic pathway, which essentially alters overall cell fates toward the desired situation. Collectively, the metabolic intervention strategy is bound to break the evolutionary adaptability of tumors for reinforced immunotherapy.