With the popularization of 5G communication technology and the continuous upgrade of robot-assisted surgery system,telesurgery has developed rapidly.However,there are few of reports about this technique in single-port laparoscopic gynecological surgery.On April 19,2024,the surgeons at the Second Affiliated Hospital of Naval Medical University in Shanghai successfully implemented robot-assisted single-port laparoscopic bilateral adnexectomy for a patient who was admitted to the Naval Hospital of the Eastern Theater Command in Zhoushan,Zhejiang Province through 5G communication technology.The operation time was 90 min,intraoperative bleeding was 20 ml,and no intraoperative complications occurred.There were no adverse events caused by robots such as robot system failure and instrument failure,or adverse events caused by remote communication such as network interruption and network attack.Intraoperative user datagram protocol(UDP)real-time monitoring data showed an average delay of 108 ms(range,105-111 ms)and a packet loss rate of 0.04%.The surgeons had a slight sense of delay when the operation amplitude was too large.There was no obvious stalling which affected the process of the operation.The patient was able to move around on the first day after surgery,and the catheter was removed.No postoperative complications occurred.The patient was discharged from the hospital on the second day after surgery.Postoperative pathological results revealed left fallopian tube ovarian serous cystadenofibroma,fallopian tubal tissue;right fallopian tube ovarian,sent for examination as ovarian and fallopian tube tissue.There were no complaints of discomfort during reexamination one month after surgery,and the umbilical incision healed well.This case is an attempt of telesurgery in the field of gynecology,and provides experiences for the further development of this technique.

Metabolic associated fatty liver disease(MAFLD)is a type of fatty liver disease associated with systemic metabolic disorders,and its prevalence has been increasing year by year,becoming a major challenge to global public health.The development of MAFLD is associated with various factors,including obesity,dyslipidemia,diabetes and other factors.Excessive body fat,particularly increased visceral adiposity,contributes to hepatic fat accumulation.Abnormal blood lipid levels can also disrupt liver fat metabolism.The risk of MAFLD in patients with diabetes is greatly increased due to insulin resistance and other problems.Dietary interventions are considered an effective strategy for the prevention and treatment of MAFLD.In recent years,several dietary patterns,such as low-carbohydrate diets,intermittent fasting,and the Mediterranean diet,have been applied in clinical practice.Their primary mechanisms include reducing oxidative stress,regulating gut microbiota,and inducing fat autophagy.However,the responses to different dietary patterns vary among individuals due to differences in genes,lifestyle,and disease severity.Therefore,systematically evaluating the effects and mechanisms of these dietary patterns in the prevention and treatment of MAFLD has significant clinical importance.This review compares the effects of different dietary patterns on improving liver function,hepatic fat content,blood glucose,and lipid levels,and analyzes their underlying mechanisms of intervention,to explore how to select personalized dietary strategies based on individual differences.It is intended to provide new insights for the precise prevention and treatment of MAFLD,thereby improving patients' outcomes and alleviating the burden on public health.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

Metabolic associated fatty liver disease(MAFLD)is a type of fatty liver disease associated with systemic metabolic disorders,and its prevalence has been increasing year by year,becoming a major challenge to global public health.The development of MAFLD is associated with various factors,including obesity,dyslipidemia,diabetes and other factors.Excessive body fat,particularly increased visceral adiposity,contributes to hepatic fat accumulation.Abnormal blood lipid levels can also disrupt liver fat metabolism.The risk of MAFLD in patients with diabetes is greatly increased due to insulin resistance and other problems.Dietary interventions are considered an effective strategy for the prevention and treatment of MAFLD.In recent years,several dietary patterns,such as low-carbohydrate diets,intermittent fasting,and the Mediterranean diet,have been applied in clinical practice.Their primary mechanisms include reducing oxidative stress,regulating gut microbiota,and inducing fat autophagy.However,the responses to different dietary patterns vary among individuals due to differences in genes,lifestyle,and disease severity.Therefore,systematically evaluating the effects and mechanisms of these dietary patterns in the prevention and treatment of MAFLD has significant clinical importance.This review compares the effects of different dietary patterns on improving liver function,hepatic fat content,blood glucose,and lipid levels,and analyzes their underlying mechanisms of intervention,to explore how to select personalized dietary strategies based on individual differences.It is intended to provide new insights for the precise prevention and treatment of MAFLD,thereby improving patients' outcomes and alleviating the burden on public health.

Objective To explore the diagnosis and treatment experience of malignant peritoneal mesothelioma by analyzing the clinical characteristics of patients with single center peritoneal mesothelioma.Methods Retrospec-tively analyze the clinical data,including age and treatment regimens,of 99 patients with malignant peritoneal mes-othelioma admitted to Peking Union Medical College Hospital from June 2012 to July 2023.Kaplan-Meier for surviv-al analysis and Logistic and Cox regression were applied to assess the impact of factors like age and treatment regi-mens on survival time.Results The median age of diagnosis for 99 patients with peritoneal mesothelioma was 56 years,of which 82 were pathologically diagnosed.Among them,38 cases(51.4%)underwent tumor cell reduction surgery,and 57 cases(77.0%)underwent systemic or local treatment.The median survival time for all patients was 43 years.The age of diagnosis may affect the prognosis of patients with malignant mesothelioma,and those aged≥65 at the time of diagnosis have a worse prognosis.Conclusions Malignant peritoneal mesothelioma is a rare but invasive malignant tumor with a poor prognosis.There is still a need to develop novo drugs and comprehensive treat-ment strategies.

Objective:To investigate the effective ingredients and molecular mechanisms of Qizao oral liquid in the treatment of lead poisoning through network pharmacology and molecular docking technology.Methods:December 2023, the effective ingredients and their corresponding targets of Qizao oral liquid were searched from the TCM Systems Pharmacology database. Swiss Target Prediction was used to predict corresponding potential target genes of compounds. Targets associated with lead poisoning were obtained from GeneCards and OMIM databases. Cytoscape 3.10.1 software was employed to construct a components and corresponding target network as well as a components and corresponding target network, followed by visualization and cluster analysis. GO and KEGG enrichment analyses were conducted using the Metascape database, resulting in the generation of a signaling pathway-target network diagram. Molecular docking analysis between the principal compounds and target proteins was performed using Autodock 4.2.6 and Pymol 2.2.0 software to validate their underlying molecular mechanisms.Results:A total of 114 active chemical components, 361 potential targets, 2501 lead poisoning targets, and 191 intersection targets of "Qizao oral liquid and lead poisoning" were screened. Further analysis revealed that there were 2091 entries for GO biological processes and 202 KEGG signaling pathways. Enrichment analysis showed that the key targets were mainly enriched in cancer, lipid and atherosclerosis, PI3K-Akt signaling pathways. Molecular docking showed that there were 14 combinations with binding energy<-5 kcal/mol, among which PIK3R1-β-sitosterol binding energy was -9.71 kcal/mol.Conclusion:The primary active components found in Qizao oral liquid, such as β-sitosterol, nuciferine, stephanine, and stigmasterol, have the potential to modulate key targets including PIK3R1, AKT1, TP53, and NFKB1. These components are capable of influencing the PI3K-Akt signaling pathway as well as lipid and atherosclerosis pathways in order to mitigate the adverse effects of lead exposure.

Objective:To investigate the effective ingredients and molecular mechanisms of Qizao oral liquid in the treatment of lead poisoning through network pharmacology and molecular docking technology.Methods:December 2023, the effective ingredients and their corresponding targets of Qizao oral liquid were searched from the TCM Systems Pharmacology database. Swiss Target Prediction was used to predict corresponding potential target genes of compounds. Targets associated with lead poisoning were obtained from GeneCards and OMIM databases. Cytoscape 3.10.1 software was employed to construct a components and corresponding target network as well as a components and corresponding target network, followed by visualization and cluster analysis. GO and KEGG enrichment analyses were conducted using the Metascape database, resulting in the generation of a signaling pathway-target network diagram. Molecular docking analysis between the principal compounds and target proteins was performed using Autodock 4.2.6 and Pymol 2.2.0 software to validate their underlying molecular mechanisms.Results:A total of 114 active chemical components, 361 potential targets, 2501 lead poisoning targets, and 191 intersection targets of "Qizao oral liquid and lead poisoning" were screened. Further analysis revealed that there were 2091 entries for GO biological processes and 202 KEGG signaling pathways. Enrichment analysis showed that the key targets were mainly enriched in cancer, lipid and atherosclerosis, PI3K-Akt signaling pathways. Molecular docking showed that there were 14 combinations with binding energy<-5 kcal/mol, among which PIK3R1-β-sitosterol binding energy was -9.71 kcal/mol.Conclusion:The primary active components found in Qizao oral liquid, such as β-sitosterol, nuciferine, stephanine, and stigmasterol, have the potential to modulate key targets including PIK3R1, AKT1, TP53, and NFKB1. These components are capable of influencing the PI3K-Akt signaling pathway as well as lipid and atherosclerosis pathways in order to mitigate the adverse effects of lead exposure.

Objective:To investigate the value of 99Tc m-hydrazinonicotinamide (HYNIC)-prostate specific membrane antigen(PSMA) SPECT/CT imaging in biochemical recurrence of prostate cancer (PCa). Methods:From January 2018 to March 2023, 112 patients with biochemical recurrence of PCa (age (72.6±6.1) years) who underwent 99Tc m-HYNIC-PSMA SPECT/CT imaging in Henan Provincial People′s Hospital were retrospectively analyzed. According to the level of prostate specific antigen (PSA), patients were divided into 0.2 μg/L2 μg/L group. According to the Gleason score, patients were divided into Gleason score≥8 group and Gleason score <8 group. The detection rate between groups was analyzed by χ2 test, and the difference of the PSA level between groups was compared by Mann-Whitney U test. Results:PSMA imaging was positive in 77 cases and negative in 35 cases, with the detection rate of 68.8%(77/112). The detection rates of local recurrence, lymph node metastasis, bone metastasis and lung metastasis were 8.9%(10/112), 43.8%(49/112), 28.6%(32/112) and 0.9%(1/112), respectively. The detection rates of 0.2 μg/L2 μg/L groups were 44.7%(21/47), 8/12 and 90.6%(48/53), respectively ( χ2=24.44, P<0.001). The detection rates of Gleason score ≥8 group and <8 group were 76.4%(55/72) and 55.0%(22/40) ( χ2=5.47, P=0.032); the PSA level between the two groups was statistically different (3.11(0.75, 5.91) and 0.84(0.44, 2.92) μg/L; z=-2.99, P=0.003). Of the patients with PSMA positive imaging, 84.4%(65/77) changed their treatment regimen and 15.6%(12/77) continued to observe or maintain the original treatment plan. Of the patients with PSMA negative imaging, 40.0%(14/35) changed the treatment plan, 51.4%(18/35) continued to observe or maintain the original treatment plan, and 8.6%(3/35) discontinued the original treatment because no tumor metastasis was found. Conclusion:99Tc m-HYNIC-PSMA SPECT/CT imaging can provide reference for the lesion detection, treatment decision-making and follow-up observation of biochemical recurrence of PCa.

Alzheimer's disease is a common central neurodegenerative disease， mainly manifested by cognitive impairment and non-cognitive neuropsychiatric symptoms that severely affect patients' daily life and behavioral functioning. The pathogenesis of Alzheimer's disease is still unclear， and the western medicine currently used to treat Alzheimer's disease is only symptomatic， with a single pathway， limited efficacy， and many side effects. In recent years， with the deepening of research on Alzheimer's disease， the study and application of traditional Chinese medicine （TCM） in the treatment of Alzheimer's disease have gradually increased. Several studies have shown that TCM and its effective components can exert anti-Alzheimer's disease effects by regulating molecular mechanisms such as pathological protein production and aggregation， oxidative stress， neuroinflammation， ferroptosis， mitochondrial dysfunction， neurogenesis and neurotransmission， and brain-gut axis. This paper summarized the research progress of TCM in the treatment of Alzheimer's disease in recent years， so as to provide a reference for further study of the specific mechanism of TCM in the prevention and treatment of Alzheimer's disease and the discovery of effective components of TCM.

Objective Bioinformatics and machine learning were used to identify associations between key genes in obesity and osteoarthritis(OA)and immune infiltrating cells.Methods Three datasets GSE55235,GSE44000 and GSE151839 were screened from the gene expression omnibus(GEO)database,and differentially expressed genes(DEGs)were obtained by R software,and their potential biological functions were explored through gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)signaling pathway enrichment analysis.The minimum absolute contraction and selection operator(LASSO)regression algorithm combined with support vector machine(SVM)was used to screen characteristic genes,the diagnostic value of key genes was verified by receiver operating characteristic(ROC)curve,and the immune infiltration was assessed by CIBERSORT algorithm.The mRNA-miRNA regulatory network was constructed using NetworkAnalyst database to predict target miRNA and Cytoscape software,and the correlation between key genes and immune infiltration was analyzed.Results GO gene enrichment analysis obtained 99 DEGs.Cellular activation in the immune system and immune response is highly enriched.KEGG pathway analysis showed significant enrichment of interleukin(IL-17),nuclear factor-κB(NF-κB),B-cell receptor and chemokine signaling pathways.Two key diagnostic genes(MXRA5 and MYC)were identified based on machine learning.Immunoinfiltration analysis showed that MXRA5 was associated with resting and activated CD4 memory T cells,activated NK cells,resting and activated mast cells,and M0 macrophages.In addition,MYC is associated with resting and activated CD4 memory T cells,plasma cells,activated NK cells,resting and activated mast cells,M2 macrophages,and eosinophils.CD4+cells,NK cells and mast cells were significantly associated with these two pivot genes.Conclusion Two key immune-related genes were identified through bioinformatics analysis,which may provide new targets for the treatment of obesity-related OA.