Objective: The treatment of asymmetric maxillary hypoplasia and dental crowding secondary to unilateral cleft lip and palate (UCLP) is often challenging.This study introduced an asymmetric tooth-borne distractor in anterior maxillary segmental distraction osteogenesis and used three-dimensional finite element analysis to evaluate its potential for clinical application in cases of asymmetrical maxillary hypoplasia. Methods: A cone-beam computed tomography scan of a late adolescent with UCLP was used to construct a three-dimensional finite element model of the teeth and maxillary structures. An asymmetric distractor model was used to simulate conventional distraction osteogenesis and asymmetric distraction osteogenesis (ADO) to evaluate the resultant stress distribution and displacement. Results: Postoperatively, both distraction methods resulted in anterior maxillary segment advancement with a slight upward movement. ADO yielded a greater increase in the dental arch length on the cleft side and induced rotation of the anterior maxillary segment, potentially improving midline deviation. Both methods showed similar stress distributions, with higher stress concentrations on the cleft side. Conclusions ADO may offer clinical advantages in correcting asymmetrical maxillary hypoplasia in patients with UCLP by facilitating asymmetrical expansion and rotation of the maxilla. Further research is needed to generalize these findings to other clinical presentations.

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.

Objective: The treatment of asymmetric maxillary hypoplasia and dental crowding secondary to unilateral cleft lip and palate (UCLP) is often challenging.This study introduced an asymmetric tooth-borne distractor in anterior maxillary segmental distraction osteogenesis and used three-dimensional finite element analysis to evaluate its potential for clinical application in cases of asymmetrical maxillary hypoplasia. Methods: A cone-beam computed tomography scan of a late adolescent with UCLP was used to construct a three-dimensional finite element model of the teeth and maxillary structures. An asymmetric distractor model was used to simulate conventional distraction osteogenesis and asymmetric distraction osteogenesis (ADO) to evaluate the resultant stress distribution and displacement. Results: Postoperatively, both distraction methods resulted in anterior maxillary segment advancement with a slight upward movement. ADO yielded a greater increase in the dental arch length on the cleft side and induced rotation of the anterior maxillary segment, potentially improving midline deviation. Both methods showed similar stress distributions, with higher stress concentrations on the cleft side. Conclusions ADO may offer clinical advantages in correcting asymmetrical maxillary hypoplasia in patients with UCLP by facilitating asymmetrical expansion and rotation of the maxilla. Further research is needed to generalize these findings to other clinical presentations.

Objective: The treatment of asymmetric maxillary hypoplasia and dental crowding secondary to unilateral cleft lip and palate (UCLP) is often challenging.This study introduced an asymmetric tooth-borne distractor in anterior maxillary segmental distraction osteogenesis and used three-dimensional finite element analysis to evaluate its potential for clinical application in cases of asymmetrical maxillary hypoplasia. Methods: A cone-beam computed tomography scan of a late adolescent with UCLP was used to construct a three-dimensional finite element model of the teeth and maxillary structures. An asymmetric distractor model was used to simulate conventional distraction osteogenesis and asymmetric distraction osteogenesis (ADO) to evaluate the resultant stress distribution and displacement. Results: Postoperatively, both distraction methods resulted in anterior maxillary segment advancement with a slight upward movement. ADO yielded a greater increase in the dental arch length on the cleft side and induced rotation of the anterior maxillary segment, potentially improving midline deviation. Both methods showed similar stress distributions, with higher stress concentrations on the cleft side. Conclusions ADO may offer clinical advantages in correcting asymmetrical maxillary hypoplasia in patients with UCLP by facilitating asymmetrical expansion and rotation of the maxilla. Further research is needed to generalize these findings to other clinical presentations.

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: The treatment of asymmetric maxillary hypoplasia and dental crowding secondary to unilateral cleft lip and palate (UCLP) is often challenging.This study introduced an asymmetric tooth-borne distractor in anterior maxillary segmental distraction osteogenesis and used three-dimensional finite element analysis to evaluate its potential for clinical application in cases of asymmetrical maxillary hypoplasia. Methods: A cone-beam computed tomography scan of a late adolescent with UCLP was used to construct a three-dimensional finite element model of the teeth and maxillary structures. An asymmetric distractor model was used to simulate conventional distraction osteogenesis and asymmetric distraction osteogenesis (ADO) to evaluate the resultant stress distribution and displacement. Results: Postoperatively, both distraction methods resulted in anterior maxillary segment advancement with a slight upward movement. ADO yielded a greater increase in the dental arch length on the cleft side and induced rotation of the anterior maxillary segment, potentially improving midline deviation. Both methods showed similar stress distributions, with higher stress concentrations on the cleft side. Conclusions ADO may offer clinical advantages in correcting asymmetrical maxillary hypoplasia in patients with UCLP by facilitating asymmetrical expansion and rotation of the maxilla. Further research is needed to generalize these findings to other clinical presentations.

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.