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.

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.

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:To explore the diagnosis and clinical characteristics of multi-slice spiral computed tomography angiography(MSCTA)on acute aortic syndrome(AAS).Methods:A total of 185 patients with suspected AAS who were treated in Fuyang People's Hospital from June 2020 to July 2022 were selected,and the diagnostic results of digital vascular subtraction(DSA)were taken as the"gold standard".Before confirmation,MSCT plain scan and MSCTA examination were conducted,and the positively and negatively predictive values of MSCT plain scan and MSCTA were calculated by using four-cell table method.The area under curve(AUC)values,sensitivities and specificities of MSCT plain scan and MSCTA in diagnosing AAS were analyzed by using receiver operating characteristic(ROC)curve model.Results:As the gold standard of DSA diagnostic results,82 cases of 185 patients with suspected AAS were confirmed as AAS.The positively and negatively predictive values of MSCT plain scan were 68.35%and 73.58%,respectively.The positively and negatively predictive value of MSCTA examination were 96.30%and 96.15%,respectively.The diagnostic accuracy of MSCTA was significantly higher than that of MSCT plain scan(x2=42.092,P<0.05).The detection rates of laceration locations(ascending aorta,aortic arch and descending aorta)in MSCTA were significantly higher than that in MSCT plain scan(x2=6.788,4.000,12.974,P<0.05),respectively.ROC curve analysis showed that the AUC values of MSCT plain scan and MSCTA were respectively 0.698 and 0.946 in diagnosing AAS.Conclusion:MSCTA has a higher efficiency in diagnosing AAS,and AAS mostly includes the aortic dissection separation and aortic intramural hematoma.

Objective:To analyze and evaluate the expressions and clinical value of tuftelin (TUFT1) and Krüppel-like factor 5 (KLF5) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) tissues.Method:KLF5 mRNA and TUFT1 mRNA transcriptional status in cancer and non-cancer groups were compared according to the Cancer Genome Atlas (TCGA) database. The differences and prognostic value between the groups were analyzed. Postoperative liver cancer and its paired pericancerous tissues, with the approval of the ethics committee, were collected to build tissue chips. The expression of KLF5 and TUFT1 and their intracellular localization were verified by immunohistochemistry. Tissue expression and clinicopathological characteristics were analyzed by immunoblotting. SPSS software was used to analyze the relationship between SPSS and patient prognosis.Results:The transcription level of TUFT1 or KLF5 mRNA was significantly higher in the HCC group than the non-cancer group ( P ?

Objective To observe the effect of dulaglutide combined with insulin aspart and metformin on blood glucose,pancreatic beta-cell status and physique in elderly patients with type 2 diabetes mellitus(T2DM)and obesity.Methods Elderly patients with T2DM and obesity were divided into the control group and the treatment group according to the queue method.Both groups were given intensive insulin therapy with insulin aspart injection at 0.4-0.6 U·kg-1·d-1 and oral administration of 0.5 g of metformin tablets,tid.A week later,the treatment of control group was switched to sequential therapy with insulin glargine injection at an initial dose of 0.4-0.6 U·kg-1·d-1,qn.The dose was adjusted according to blood glucose concentration.During this period,0.5 g of metformin tablets was administrated,tid,for 12 consecutive weeks.Meanwhile,treatment of the treatment group was switched to sequential therapy with 1.5 mg of dulaglutide injection,once a week.During this period,0.5 g of metformin tablets was administrated,tid,for 12 consecutive weeks.The two groups were compared in terms of clinical efficacy,blood glucose level[glycosylated hemoglobin(HbAlc),fasting plasma glucose(FPG)],pancreatic beta-cell status[fasting insulin(FINS),homeostasis model assessment-β(HOMA-β)and homeostasis model assessment-insulin resistance index(HOMA-IR)],and physical parameters[waist circumference and body mass index(BMI)].Safety was evaluated.Results Fifty-three cases and fifty-one cases were included in the treatment group and the control group,respectively.After treatment,the total effective rates of the treatment group and the control group were 98.11％(52 cases/53 cases)and 84.31％(43 cases/51 cases),and the difference was statistically significant(P＜0.05).After treatment,HbAlc in the treatment and the control group were(7.01±0.75)％and(7.63±0.82)％;FPG levels were(6.23±0.70)and(6.62±0.74)mmol·L-1;FINS levels were(5.25±1.06)and(6.48±1.12)mU·L-1;HOMA-β were 32.62±6.53 and 27.19±5.18;HOMA-IR were 1.31±0.25 and 1.65±0.28;waist circumference were(82.31±6.04)and(85.79±6.82)cm;BMI were(27.14±1.23)and(27.91±1.15)kg·m-2.The differences in above indicators between the treatment group and the control group were statistically significant(all P＜0.05).Adverse drug reactions in the treatment group mainly included nausea,vomiting and skin rash.Adverse drug reactions in the control group mainly included nausea and vomiting.The total incidence rates of adverse drug reactions in the treatment and the control group were 11.32％and 9.80％,without statistically significant difference(P＞0.05).Conclusion Dulaglutide combined with insulin aspart and metformin can effectively improve blood glucose,lipids,inflammation and pancreatic β-cell status in elderly patients with T2DM and obesity,reduce glycemic excursions,and promote decreases in waist circumference and BMI,with good safety.

The cerebellum is heavily connected with other brain regions, sub-serving not only motor but also nonmotor functions. Genetic mutations leading to cerebellar dysfunction are associated with mental diseases, but cerebellar outputs have not been systematically studied in this context. Here, we present three dimensional distributions of 50,168 target neurons of cerebellar nuclei (CN) from wild-type mice and Nlgn3R451C mutant mice, a mouse model for autism. Our results derived from 36 target nuclei show that the projections from CN to thalamus, midbrain and brainstem are differentially affected by Nlgn3R451C mutation. Importantly, Nlgn3R451C mutation altered the innervation power of CN→zona incerta (ZI) pathway, and chemogenetic inhibition of a neuronal subpopulation in the ZI that receives inputs from the CN rescues social defects in Nlgn3R451C mice. Our study highlights potential role of cerebellar outputs in the pathogenesis of autism and provides potential new therapeutic strategy for this disease.
Animals ; Mice ; Disease Models, Animal ; Cerebellar Nuclei ; Autistic Disorder/pathology* ; Neurons/metabolism* ; Mutation ; Nerve Tissue Proteins/metabolism* ; Male ; Membrane Proteins ; Cell Adhesion Molecules, Neuronal

With the deepening of the global new military revolution,the research on advanced information technology for the search and rescue of combat casualties is increasing.How to accurately and intelligently perceive and locate injured individuals in real time has become a research focus.Based on our previous study results of combat casualty intelligent perception system,this paper makes an in-depth study on problems such as deployment mode,operation mechanism,and application verification,and preliminary results have achieved in combat casualty perception,accurate positioning,guided search and rescue,field rescue coordination,as well as visual command and control.Finally,verification and analysis are performed on the application effects of the system,and the feasibility and value of the system are elaborated.

The UPLC-MS/MS was established for the determination of acetyl-11-keto-beta-boswellic acid(AKBA) and β-boswellic acid(β-BA), the main active components of Olibanum and Myrrha extracts in Xihuang Formula, in rat plasma and urine. The effects of compatibility on the pharmacokinetic behaviors of AKBA and β-BA in rats were investigated, and the differences in pharmacokinetic behaviors between healthy rats and rats with precancerous lesions of breast cancer were compared. The results showed that compared with RM-NH and RM-SH groups, the AUC_(0-t) and AUC_(0-∞) of β-BA increased(P<0.05 or P<0.01), T_(max) decreased(P<0.05 or P<0.01), and C_(max) increased(P<0.01) after compatibility. The trends of AKBA and β-BA were the same. Compared with RM-SH group, the T_(max) decreased(P<0.05), C_(max) increased(P<0.01), and the absorption rate increased in the normal group of Xihuang Formula. The results of urinary excretion showed that there was a decreasing trend in the urinary excretion rate and total urinary excretion of β-BA and AKBA after compatibility, but there was no statistical difference. Compared with normal group of Xihuang Formula, the AUC_(0-t) and AUC_(0-∞) of β-BA increased(P<0.05), T_(max) increased(P<0.05), and the clearance rate decreased in the breast precancerous lesion group. AUC_(0-t) and AUC_(0-∞) of AKBA showed an increasing trend, the in vivo retention time was prolonged, and the clearance rate was reduced, but there was no significant difference compared with the normal group. The cumulative urinary excretion and urinary excretion rate of β-BA and AKBA decreased under pathological conditions, indicating that pathological conditions could affect the in vivo process of β-BA and AKBA, and reduce their excretion in the form of prototype drugs, showing different pharmacokine-tic characteristics from normal physiological conditions. In this study, UPLC-MS/MS analysis method was established, which was sui-table for in vivo pharmacokinetic analysis of β-BA and AKBA. This study laid a foundation for the development of new dosage forms of Xihuang Formula.
Rats ; Animals ; Chromatography, Liquid ; Tandem Mass Spectrometry ; Drugs, Chinese Herbal ; Precancerous Conditions ; Triterpenes/pharmacology*

BACKGROUND: Islet transplantation is currently considered the most promising method for treating insulin-dependent diabetes. The two most-studied artificial islets are alginate-encapsulated b cells or b cell spheroids. As three-dimensional (3D) models, both artificial islets have better insulin secretory functions and transplantation efficiencies than cells in twodimensional (2D) monolayer culture. However, the effects of these two methods have not been compared yet. Therefore, in this study, cells from the mouse islet b cell line Min6 were constructed as scaffold-free spheroids or alginate-encapsulated dispersed cells. METHODS: MIN6 cell spheroids were prepared by using Agarose-base microwell arrays. The insulin secretion level was determined by mouse insulin ELISA kit, and the gene and protein expression status of the MIN6 were performed by Quantitative polymerase chain reaction and immunoblot, respectively. RESULTS: Both 3D cultures effectively promoted the proliferation and glucose-stimulated insulin release (GSIS) of MIN6 cells compared to 2D adherent cells. Furthermore, 1% alginate-encapsulated MIN6 cells demonstrated more significant effects than the spheroids. In general, three pancreatic genes were expressed at higher levels in response to the 3D culture than to the 2D culture, and pancreatic/duodenal homeobox-1 (PDX1) expression was higher in the cells encapsulated in 1% alginate than that in the spheroids. A western blot analysis showed that 1% alginate-encapsulated MIN6 cells activated the phosphoinositide 3-kinase (PI3K)/serine/threonine protein kinase (AKT)/forkhead transcription factor FKHR (FoxO1) pathway more than the spheroids, 0.5% alginate-, or 2% alginate-encapsulated cells did. The 3D MIN6 culture, therefore, showed improved effects compared to the 2D culture, and the 1% alginate-encapsulated MIN6 cells exhibited better effects than the spheroids. The upregulation of PDX1 expression through the activation of the PI3K/AKT/FoxO1 pathway may mediate the improved cell proliferation and GSIS in 1% alginate-encapsulated MIN6 cells. CONCLUSION This study may contribute to the construction of in vitro culture systems for pancreatic islets to meet clinical requirements.