Robotic telesurgery is a technology that doctors use advanced surgical robots and network communication technology to carry out surgery on patients in different places. Robotic telesurgery can sink high-quality medical resources to serve patients in remote areas， and can also be used for emergency rescue， disaster relief， battlefield and other special occasions to provide patients with timely， effective and high-quality surgical treatment， as well as reducing medical costs and patient transport risks. With the rapid development of the fifth generation wireless network， low latency and high broadband communication are provided for robotic telesurgery， and faster and more accurate real-time data transmission makes it possible to carry out complex surgery remotely. In this review， the current situation of robotic telesurgery at home and abroad is described， and the future of robotic telesurgery is prospected.

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

Objective : To investigate the biological functions and regulatory mechanism of hexokinase(HK2) in driving tumor initiation and development of prostate cancer. Methods: Immunohistochemical staining was employed to assess HK2 expression in benign prostate tissue and prostate cancer tissue. Correlation analyses were performed to elucidate the association of HK2 expression and clinical factors. Western blot analyses were employed to assess HK2 expression in prostate cancer cell lines. Cellular viability was assessed using the MTT assay.In vivotumorigenesis ability of HK2 was evaluated using xenograft animal models. Glucose flux tracing was conducted through isotopic analyses in prostate cancer cells. Results : HK2 expression was elevated in prostate cancer tissues compared to benign prostate tissues(P<0.05). HK2 expression was positively correlated with Gleason Score, prostate-specific antigen(PSA) levels and the presence of metastases(P<0.05). Overexpression ofHK2enhanced cell proliferationin vitro(P<0.01). Knockdown ofHK2decreased tumorigenesisin vivo. HK2 augmented metabolic activity of glycolysis pathway in prostate cancer cells(P<0.05). Conclusion HK2 facilitates tumorigenesis in prostate cancer by upregulating glycolytic activity.

Single-cell metabolite analysis at the small molecule level reveals intercellular heterogeneity and molecular diversity,especially living cell metabolite analysis which can provide more accurate biochemical information.In this study,a comprehensive single-cell metabolomics mass spectrometry analysis platform was constructed based on continuous ultrasonic sample introduction,aiming to improve the utilization rate of single cells and the efficiency of mass spectrometry detection.This platform utilized mechanical motion generated by a miniaturized ultrasound module,which minimally affected cell integrity and viability,enabling cell suspension and dispersion for up to 60 min,with cell viability exceeding 70%.By comparing cell suspension densities and the cell number of mass spectrometry detections between static and ultrasound groups,the results showed that the ultrasound treatment significantly reduced cell sedimentation rate and increased single-cell mass spectrometry detection efficiency.Applying this platform to single-cell analysis of cell line of mouse cerebellar astrocytes(C8D1A)and mouse glioma(GL261)cells achieved clustering and differential analysis of different cell types,demonstrating the method's potential in analyzing cellular heterogeneity and identifying cells.This approach promised to provide new insights and solutions for single-cell analysis.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Objective To investigate the impact of the precise dissection and reconstruction of the prostate apex and bladder neck urethra during radical prostatectomy on the improvement in postoperative urinary control in patients with prostate cancer.Methods A retrospective study was conducted.A total of 131 prostate cancer patients who underwent robot-assisted radical prostatectomy at our institution between January 1,2023 and December 31,2023 were enrolled.The subjects were divided into two groups,with 64 in the experimental group and 67 in the control group.Patients in the experimental group underwent radical prostatectomy in a modified approach,while those in the control group underwent conventional radical prostatectomy.Propensity score matching was employed to match the two groups at a 1-to-l ratio based on age,body mass index(BMI),preoperative prostate specific antigen(PSA),prostate volume,Prostate Imaging Reporting and Data System(PI-RADS)scores,biopsy Gleason score,and preoperative urinary control status.After matching,we compared the preoperative baseline data,surgical margin positivity rates,and urinary control status at 3 months post operation between the two groups.Urinary control was assessed before and after surgery using the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form(ICIQ-UI SF)scale.Results A total of 56 pairs of patients were successfully matched between the experimental group and the control group through 1-to-l propensity score matching.At 3 months after surgery,the median score for ICIQ-SF scale of the experimental group was 7.0 points,while that of the control group was 9.5 points,with the difference being statistical significant(P＜0.05).There was no significant difference in the positive rate of incision margins between the experimental group and the control group.Multiple linear regression analysis showed that both the prostate volume and the Gleason score in the experimental group were positively correlated with the ICIQ-UI SF scores 3 months after surgery(P＜0.05),while the age of patients in the control group was positively correlated with ICIQ-UI SF score 3 months after surgery(P＜0.05).Conclusion Precise dissection and reconstruction of the prostate apex and bladder neck urethra during radical prostatectomy significantly improve the postoperative urinary control of patients at 3 months after surgery.

Humans ; Hemangioma ; Liver Neoplasms ; Fever