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.

Macroautophagy (referred to as autophagy hereafter) is a major intracellular lysosomal degradation pathway that is responsible for the degradation of misfolded/damaged proteins and organelles. Previous studies showed that autophagy protects against acetaminophen (APAP)-induced injury (AILI) via selective removal of damaged mitochondria and APAP protein adducts. The lysosome is a critical organelle sitting at the end stage of autophagy for autophagic degradation via fusion with autophagosomes. In the present study, we showed that transcription factor EB (TFEB), a master transcription factor for lysosomal biogenesis, was impaired by APAP resulting in decreased lysosomal biogenesis in mouse livers. Genetic loss-of and gain-of function of hepatic TFEB exacerbated or protected against AILI, respectively. Mechanistically, overexpression of TFEB increased clearance of APAP protein adducts and mitochondria biogenesis as well as SQSTM1/p62-dependent non-canonical nuclear factor erythroid 2-related factor 2 (NRF2) activation to protect against AILI. We also performed an unbiased cell-based imaging high-throughput chemical screening on TFEB and identified a group of TFEB agonists. Among these agonists, salinomycin, an anticoccidial and antibacterial agent, activated TFEB and protected against AILI in mice. In conclusion, genetic and pharmacological activating TFEB may be a promising approach for protecting against AILI.

Aim To investigate the role of metabolites of eicosapentaenoic acid (EPA) in promoting the transdifferentiation of pancreatic α cells to β cells. Methods Male C57BL/6J mice were injected intraperitoneally with 60 mg/kg streptozocin (STZ) for five consecutive days to establish a type 1 diabetes (T1DM) mouse model. After two weeks, they were randomly divided into model groups and 97% EPA diet intervention group, 75% fish oil (50% EPA +25% DHA) diet intervention group, and random blood glucose was detected every week; after the model expired, the regeneration of pancreatic β cells in mouse pancreas was observed by immunofluorescence staining. The islets of mice (obtained by crossing GCG

Objective To study the stress change characteristics of the cervical disc after removing different ranges of the uncinate process by establishing a three⁃dimensional finite element model of the C

In the past few decades, microbubbles were widely used as ultrasound contrast agents in the field of tumor imaging. With the development of research, ultrasound targeted microbubble destruction technology combined with drug-loaded microbubbles can achieve precise drug release and play a therapeutic role. As a micron-scale carrier, microbubbles are difficult to penetrate the endothelial cell space of tumors, and nano-scale drug delivery system—nanobubbles came into being. The structure of the two is similar, but the difference in size highlights the unique advantages of nanobubbles in drug delivery. Based on the classification principle of shell materials, this review summarized micro/nanobubbles used for ultrasound diagnosis or treatment and discussed the possible development directions, providing references for the subsequent development.

Objective To explore the efficacy and safety of ticagrelor de-escalation and nicorandil therapy in elderly patients with acute coronary syndrome(ACS)after percutaneous coronary intervention(PCI).Methods A total of 300 elderly patients with ACS were selected from the Sixth and Seventh Medical Center of Chinese PLA General Hospital and Beijing Chaoyang Integrative Medicine Emergency Rescue and First Aid Hospital from November 2016 to June 2019,including 153 males and 147 females,aged>65 years old.All the patients received PCI,and all had double antiplatelet therapy(DAPT)scores≥2 and a new DAPT(PRECISE-DAPT)score of≥25.All patients were divided into two groups by random number table method before operation:ticagrelor group(n=146,ticagrelor 180 mg load dose followed by PCI,and ticagrelor 90 mg bid after surgery)and ticagrelor de-escalation + nicorandil group(n=154,ticagrelor 180 mg load dose followed by PCI,ticagrelor 90 mg bid+nicorandil 5 mg tid after surgery,changed to ticagrelor 60 mg bid+ nicorandil 5 mg tid 6 months later).Follow-up was 12 months.The composite end points of cardiovascular death,myocardial infarction and stroke,the composite end points of mild hemorrhage,minor hemorrhage,other major hemorrhage and major fatal/life-threatening hemorrhage as defined by the PLATO study,and the composite end points of cardiovascular death,myocardial infarction,stroke and bleeding within 12 months in the two groups were observed.Results The comparison of general baseline data between the two groups showed no statistically significant difference(P>0.05).There was also no significant difference in the composite end points of cardiovascular death,myocardial infarction and stroke between the two groups(P>0.05).The cumulative incidence of bleeding events in ticagrelor de-escalation + nicorandil group was significantly lower than that in ticagrelor group(P<0.05),while the composite end points of cardiovascular death,myocardial infarction,stroke and bleeding were also significantly lower than those in tecagrelor group(P<0.05).Conclusion In elderly patients with ACS,the treatment of ticagrelor de-escalation + nicorandil after PCI may not increase the incidence of ischemic events such as cardiovascular death,myocardial infarction or stroke,and it may reduce the incidence of hemorrhagic events.

Gliomas are the most common primary intracranial tumors in adults, among which high-grade glioma patients are characterized by short survival and poor prognosis. The diagnosis, treatment, evaluation of effective treatments, and prognosis prediction of high-grade gliomas are of great significance for improving patient survival. Conventional enhanced magnetic resonance imaging has deficiencies in delineating tumor extent, identifying tumor progression and treatment-related changes. Therefore, there is a broad consensus to incorporate amino acid PET, and ¹⁸F-FET PET inparticular, into the diagnostic and therapeutic process of high-grade gliomas. In this article, we review the new research progress of ¹⁸F-FET PET in the diagnosis and treatment of adult high-grade glioma in recent years.

Humans ; Aged ; Lung Diseases ; Pneumonia/drug therapy* ; Adrenal Cortex Hormones/therapeutic use* ; Pulmonary Disease, Chronic Obstructive/drug therapy* ; Administration, Inhalation ; Community-Acquired Infections/drug therapy*