Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background: Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM). Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently. Results: Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy. Conclusion AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

Background: Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM). Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently. Results: Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy. Conclusion AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background: Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM). Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently. Results: Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy. Conclusion AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background: Automated insulin delivery (AID) systems studies are upsurging, half of which were published in the last 5 years. We aimed to evaluate the efficacy and safety of AID systems in patients with type 1 diabetes mellitus (T1DM). Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov until August 31, 2023. Randomized clinical trials that compared AID systems with other insulin-based treatments in patients with T1DM were considered eligible. Studies characteristics and glycemic metrics was extracted by three researchers independently. Results: Sixty-five trials (3,623 patients) were included. The percentage of time in range (TIR) was 11.74% (95% confidence interval [CI], 9.37 to 14.12; P<0.001) higher with AID systems compared with control treatments. Patients on AID systems had more pronounced improvement of time below range when diabetes duration was more than 20 years (–1.80% vs. –0.86%, P=0.031) and baseline glycosylated hemoglobin lower than 7.5% (–1.93% vs. –0.87%, P=0.033). Dual-hormone full closed-loop systems revealed a greater improvement in TIR compared with hybrid closed-loop systems (–19.64% vs. –10.87%). Notably, glycemia risk index (GRI) (–3.74; 95% CI, –6.34 to –1.14; P<0.01) was also improved with AID therapy. Conclusion AID systems showed significant advantages compared to other insulin-based treatments in improving glucose control represented by TIR and GRI in patients with T1DM, with more favorable effect in euglycemia by dual-hormone full closedloop systems as well as less hypoglycemia for patients who are within target for glycemic control and have longer diabetes duration.

OBJECTIVE: To investigate the effectiveness of Holosight robotic navigation-assisted percutaneous cannulated screw fixation for femoral neck fractures. METHODS: A retrospective analysis was conducted on 65 patients with femoral neck fractures treated with cannulated screw fixation between January 2022 and February 2024. Among them, 31 patients underwent robotic navigation-assisted screw placement (navigation group), while 34 underwent conventional freehand percutaneous screw fixation (freehand group). Baseline characteristics, including age, gender, fracture side, injury mechanism, Garden classification, Pauwels classification, and time from injury to operation, showed no significant differences between the two groups ( P>0.05). The operation time, intraoperative blood loss, fluoroscopy frequency, fracture healing time, and complications were recorded and compared, and hip function was evaluated by Harris score at last follow-up. Postoperative anteroposterior and lateral hip X-ray films were taken to assess screw distribution accuracy, including deviation from the femoral neck axis, inter-screw parallelism, and distance from screws to the femoral neck cortex. RESULTS: No significant difference was observed in operation time between the two groups ( P>0.05). However, the navigation group demonstrated superior outcomes in intraoperative blood loss, fluoroscopy frequency, deviation from the femoral neck axis, inter-screw parallelism, and distance from screws to the femoral neck cortex ( P<0.05). No incision infections or deep vein thrombosis occurred. All patients were followed up 12-18 months (mean, 16 months). In the freehand group, 1 case suffered from cannulated screw dislodgement and nonunion secondary to osteonecrosis of femoral head at 1 year after operation, 1 case suffered from screw penetration secondary to osteonecrosis of femoral head at 5 months after operation; and 1 case suffered from nonunion secondary to osteonecrosis of femoral head at 6 months after operation in the navigation group. All the 3 patients underwent internal fixators removal and total hip arthroplasty. There was no significant difference in the incidence of complications between the two groups ( P>0.05). The fracture healing time and hip Harris score at last follow-up in the navigation group were significantly better than those in the freehand group ( P<0.05). CONCLUSION Compared to freehand percutaneous screw fixation, Holosight robotic navigation-assisted cannulated screw fixation for femoral neck fractures achieves higher precision, reduced intraoperative radiation exposure, smaller incisions, and superior postoperative hip function recovery.
Humans ; Femoral Neck Fractures/diagnostic imaging* ; Bone Screws ; Fracture Fixation, Internal/instrumentation* ; Male ; Female ; Retrospective Studies ; Robotic Surgical Procedures/methods* ; Middle Aged ; Aged ; Adult ; Treatment Outcome ; Operative Time ; Fracture Healing ; Surgery, Computer-Assisted/methods* ; Fluoroscopy

Objective:To investigate the efficacy of liver wedge resection and liver Ⅳb and Ⅴ segmentectomy for T2 gallbladder carcinoma (GBC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 168 patients who underwent radical resection of T2 GBC in The First Affiliated Hospital of Xi′an Jiaotong University from January 2011 to December 2021 were collected. There were 59 males and 109 females, aged (65±10)years. Of 168 patients, there were 112 cases in T2a stage and 56 cases in T2b stage. Of 112 patients in T2a stage, 73 cases underwent liver wedge resection and 39 cases underwent liver Ⅳb and Ⅴ segmentectomy. Of 56 patients in T2b stage, 27 cases underwent liver wedge resection and 29 cases underwent liver Ⅳb and Ⅴ segmen-tectomy. Measurement data with normal distribution were represented as Mean± SD, and measure-ment data with skewed distribution were represented as M(range). Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the Mann-Whitney U test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX proportional risk model was used for univariate and multivariate analyses. Results:(1) Clinical data analysis of patients undergoing different extent of hepatic resection for T2 GBC. There was no significant difference in gender, age, cholecystoli-thiasis, preoperative total bilirubin, carcinoembryonic antigen, CA19-9, CA125, incidental GBC, perineural invasion, microvascular invasion, pathological differentiation, histopathological subtypes, N staging, TNM staging between patients with T2a and T2b GBC who underwent different extent of hepatic resection ( P>0.05). (2) Prognostic analysis of T2 GBC patients undergoing different extent of hepatic resection. The 1-, 3- and 5-year cumulative disease-free survival rates of T2 GBC patients undergoing liver wedge resection were 78.0%, 60.1% and 51.4%, respectively, versus 86.8%, 80.0% and 68.0% of T2 GBC patients undergoing liver Ⅳb and Ⅴ segmentectomy, showing a significant difference between them ( χ2 =5.205, P<0.05). The 1-, 3-, and 5-year cumulative overall survival rates of T2 GBC patients undergoing liver wedge resection were 85.0%, 62.5%, and 55.1%, respectively, versus 92.6%, 81.6%, and 68.8% for T2 GBC patients undergoing liver Ⅳb and Ⅴ segmentectomy, showing a significant difference in cumulative overall survival rate between them ( χ2=4.351, P<0.05). The 1-, 3-, and 5-year cumulative disease-free survival rates of T2b GBC patients undergoing liver wedge resection were 70.4%, 45.9% and 39.2%, respectively, versus 89.7%, 71.3% and 54.0% of T2b GBC patients undergoing liver Ⅳb and Ⅴ segmentectomy, showing a significant difference between them ( χ2=5.047, P<0.05). The 1-, 3-, and 5-year cumulative overall survival rates of T2b GBC patients undergoing liver wedge resection were 81.5%, 53.2%, and 41.0%, respectively, versus 89.7%, 77.0%, and 60.7% of T2b GBC patients undergoing liver Ⅳb and Ⅴ segmentectomy, showing no significant difference in cumulative overall survival rate between them ( χ2=4.014, P<0.05). (3) Analysis of factors influencing prognosis of patients undergoing radical resection for T2 GBC. Results of multivariate analysis showed that CA19-9>39.0 U/mL, perineural invasion, N1 and N2 stage were independent risk factors influencing disease-free survival time of patients undergoing radical resection for T2 GBC ( hazard ratio=2.736, 3.496, 2.638, 17.440, 95% confidence interval as 1.195-6.266, 1.213-10.073, 1.429-4.869, 8.362-36.374, P<0.05). Liver Ⅳb and Ⅴ segmentectomy was an independent protective factor influencing disease-free survival time of patients undergoing radical resection for T2 GBC ( hazard ratio=0.418, 95% confidence interval as 0.230-0.759, P<0.05). CA19-9 >39.0 U/mL, perineural invasion, ⅡB stage, ⅢB stage and ⅣB stage of TNM staging were independent risk factors influencing overall survival time of patients undergoing radical resection for T2 GBC ( hazard ratio=2.740, 3.210, 2.037, 3.439, 24.466, 95% confidence interval as 1.127-6.664, 1.049-9.819, 1.004-4.125, 1.730-6.846, 10.733-55.842, P<0.05). Liver Ⅳb and Ⅴ segmentectomy was an independent protective factor influencing overall survival time of patients undergoing radical resec-tion for T2 GBC ( hazard ratio=0.476, 95% confidence interval as 0.261-0.867, P<0.05). (4) Analysis of postoperative complications in patients undergoing different extent of hepatic resection for T2 GBC. There was no significant difference in postoperative complications of patients with T2a and T2b GBC undergoing liver wedge resection or liver Ⅳb and Ⅴ segmentectomy ( P>0.05). Conclusions:Compared to liver wedge resection, liver Ⅳb and Ⅴ segmentectomy can effectively prolong the disease-free survival overall survival time of T2b GBC patients. There is no significant difference in the major complications. Liver Ⅳb and Ⅴ segmentectomy is an independent protective factor for prognosis of patients undergoing radical resection for T2 GBC.

Objective:To construct a communication strategy and implementation method for advanced cancer patients based on two communication models widely used at home and abroad, so as to reduce the difficulty of clinical disease notification.Methods:From January to October 2022, based on the communication model of SPIKES (Setting, Perception, Invitation, Knowledge, Empathy, Summary) and NURSE(Name, Understand, Respect, Support, Explore), combined with literature analysis, qualitative interviews, and expert argumentation, the communication strategy items of advanced cancer patients were constructed.Results:A total of 18 articles were included in the literature analysis. Qualitative interviews were conducted with 20 interviewees (including 4 doctors, 11 nurses, and 5 patients),6 males, 14 females, aged (35.94 ± 8.03) years old. A total of 8 experts participated in the demonstration, 2 males and 6 females, aged (41.88 ± 6.58) years old. Finally, the specific items and words of the disease notification process and communication strategies of advanced cancer patients in line with China ′s clinical practice were constructed. A total of 3 first-level items, 16 second-level items, 53 third-level items, and speech techniques were constructed, including pre-communication preparation, regular communication strategies, and poor communication disposal strategies. The importance score of the item was 4.50 to 5.00, and the coefficient of variation of the item was 0 to 0.12. Conclusions:The communication strategy of advanced cancer patients based on the communication model is scientific and feasible, and can be used as a tool to inform advanced cancer patients.