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.

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*

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.

Objective To investigate the effect of high-frequency irreversible electroporation(H-FIRE)in the ablation of pig pancreatic tissue.Methods Laparotomy was conducted in this study,and needle electrodes were used to release electric pulses in 12 pigs.Three sets of parameters were established for ablation at the low,medium,and high values of field strength(1 000 V/cm,1 500 V/cm,and 2 500 V/cm).The groups were compared in terms of the data including postoperative recovery,ablation area,and histopathological features to validate the safety and efficacy of H-FIRE in the ablation of porcine pancreatic tissue.The paired t-test was used for comparison of continuous data between two groups.Results All pigs in the experiment survived and showed a good effect of ablation.The histopathological analysis of all groups showed thorough and effective ablation,with a clear boundary between the ablated area and the normal tissue area.The mean ablation area in the low,medium,and high field strength groups was 30.96±3.73 mm2,51.93±25.26 mm2,and 108.90±55.23 mm2,respectively,and the high and medium field strength groups had a significantly larger ablation area than the low field strength group(both P<0.05),while there was no significant difference in ablation area between the medium and high field strength groups(P>0.05).Conclusion H-FIRE ablation is safe and effective for porcine pancreatic tissue under specific ablation parameters.

Rare diseases still lack effective treatments, and the development of drugs for rare diseases (known as orphan drugs) is an urgent medical problem. As natural active ingredients in living organisms, some biomacromolecule drugs have good biocompatibility, low immunogenicity, and high targeting. They have become one of the most promising fields in drug research and development in the 21st century. However, there are still many obstacles in terms of in vivo delivery. In view of the unique advantages of nanocarriers prepared from polymers, lipids, organic biomimetic and inorganic materials in drug delivery, researchers are committed to building an efficient delivery system with versatility and synergy to solve the bottleneck issues in treating rare diseases with biomacromolecule drugs. Therefore, this article reviews the research progress of nanocarrier delivering proteins, peptides and nucleic acids in the field of rare disease treatment in the past ten years, which provides ideas for researches on biomacromolecule drug nanosystems in the field of treatment of rare diseases.

Objective To understand the change in distribution and antimicrobial resistance of bacteria isolated from blood specimens of Hunan Province,and provide for the initial diagnosis and treatment of clinical bloodstream infection(BSI).Methods Data reported from member units of Hunan Province Antimicrobial Resistance Survei-llance System from 2012 to 2021 were collected.Bacterial antimicrobial resistance surveillance method was imple-mented according to the technical scheme of China Antimicrobial Resistance Surveillance System(CARSS).Bacteria from blood specimens and bacterial antimicrobial susceptibility testing results were analyzed by WHONET 5.6 soft-ware and SPSS 27.0 software.Results A total of 207 054 bacterial strains were isolated from blood specimens from member units in Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021,including 107 135(51.7％)Gram-positive bacteria and 99 919(48.3％)Gram-negative bacteria.There was no change in the top 6 pathogenic bacteria from 2012 to 2021,with Escherichia coli(n=51 537,24.9％)ranking first,followed by Staphylococcus epidermidis(n=29 115,14.1％),Staphylococcus aureus(n=17 402,8.4％),Klebsiella pneu-moniae(17 325,8.4％),Pseudomonas aeruginosa(n=4 010,1.9％)and Acinetobacter baumannii(n=3 598,1.7％).The detection rate of methicillin-resistant Staphylococcus aureus(MRSA)decreased from 30.3％in 2015 to 20.7％in 2021,while the detection rate of methicillin-resistant coagulase-negative Staphylococcus(MRCNS)showed an upward trend year by year(57.9％-66.8％).No Staphylococcus was found to be resistant to vancomy-cin,linezolid,and teicoplanin.Among Gram-negative bacteria,constituent ratios of Escherichia coli and Klebsiella pneumoniae were 43.9％-53.9％and 14.2％-19.5％,respectively,both showing an upward trend(both P＜0.001).Constituent ratios of Pseudomonas aeruginosa and Acinetobacter baumannii were 3.6％-5.1％and 3.0％-4.5％,respectively,both showing a downward trend year by year(both P＜0.001).From 2012 to 2021,resistance rates of Escherichia coli to imipenem and ertapenem were 1.0％-2.0％and 0.6％-1.1％,respectively;presenting a downward trend(P＜0.001).The resistant rates of Klebsiella pneumoniae to meropenem and ertapenem were 7.4％-13.7％and 4.8％-6.4％,respectively,presenting a downward trend(both P＜0.001).The resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannii to carbapenem antibiotics were 7.1％-15.6％and 34.7％-45.7％,respectively.The trend of resistance to carbapenem antibiotics was relatively stable,but has de-creased compared with 2012-2016.The resistance rates of Escherichia coli to the third-generation cephalosporins from 2012 to 2021 were 41.0％-65.4％,showing a downward trend year by year.Conclusion The constituent ra-tio of Gram-negative bacillus from blood specimens in Hunan Province has been increasing year by year,while the detection rate of carbapenem-resistant Gram-negative bacillus remained relatively stable in the past 5 years,and the detection rate of coagulase-negative Staphylococcus has shown a downward trend.

Objective To investigate changes in the distribution and antimicrobial resistance of bacteria isolated from cerebrospinal fluid(CSF)specimens in Hunan Province,and provide reference for correct clinical diagnosis and rational antimicrobial use.Methods Data reported by member units of Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021 were collected according to China Antimicrobial Resistance Surveillance Sys-tem(CARSS)technical scheme.Data of bacteria isolated from CSF specimens and antimicrobial susceptibility tes-ting results were analyzed with WHONET 5.6 and SPSS 20.0 software.Results A total of 11 837 bacterial strains were isolated from CSF specimens from member units of Hunan Province Antimicrobial Resistance Surveillance Sys-tem from 2012 to 2021.The top 5 strains were coagulase-negative Staphylococcus(n=6 397,54.0％),Acineto-bacter baumannii(n=764,6.5％),Staphylococcus aureus(n=606,5.1％),Enterococcus faecium(n=465,3.9％),and Escherichia coli(n=447,3.8％).The detection rates of methicillin-resistant coagulase-negative Staphyloco-ccus(MRCNS)and methicillin-resistant Staphylococcus aureus(MRSA)were 58.9％-66.3％and 34.4％-62.1％,respectively.No Staphylococcus spp.were found to be resistant to vancomycin,linezolid,and teicoplanin.The de-tection rate of Enterococcus faecium was higher than that of Enterococcus faecalis,and the resistance rates of En-terococcus f aecium to penicillin,ampicillin,high concentration streptomycin and levofloxacin were all higher than those of Enterococcus faecalis(all P=0.001).Resistance rate of Streptococcus pneumoniae to penicillin was 85.0％,at a high level.Resistance rate of Escherichia coli to ceftriaxone was＞60％,while resistance rates to enzyme inhibitors and carbapenem antibiotics were low.Resistance rate of Klebsiella pneumoniae to ceftriaxone was＞60％,to en-zyme inhibitors piperacillin/tazobactam and cefoperazone/sulbactam was＞30％,to carbapenem imipenem and me-ropenem was about 30％.Resistance rates of Acinetobacter baumannii to most tested antimicrobial agents were＞60％,to imipenem and meropenem were 59.0％-79.4％,to polymyxin B was low.Conclusion Among the bac-teria isolated from CSF specimens,coagulase-negative Staphylococcus accounts for the largest proportion,and the overall resistance of pathogenic bacteria is relatively serious.Bacterial antimicrobial resistance surveillance is very important for the effective treatment of central nerve system infection.

Objective To investigate the distribution and antimicrobial susceptibility of clinically isolated bacteria from intensive care units(ICUs)in hospitals of Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021.Methods According to China Antimicrobial Resistance Surveillance System,data of clinically isolated bacterial strains and antimicrobial susceptibility testing results of bacteria from ICUs reported by all member units of Hunan Province Antimicrobial Resistance Surveillance System were analyzed with WHONET 2022 software.Results From 2012 to 2021,the total number of bacteria isolated from ICUs of member units of the Hunan Province Antimi-crobial Resistance Surveillance System was 5 777-22 369,with Gram-negative bacteria accounting for 76.1％-78.0％annually.Staphylococcus aureus ranked first among isolated Gram-positive bacteria each year.The top 5 bacteria among Gram-negative bacteria were Acinetobacter baumannii,Klebsiella pneumoniae,Escherichia coli,Pseudo-monas aeruginosa,and Stenotrophomonas maltophilia.Detection rate of methicillin-resistant Staphylococcus aureus showed a downward trend year by year.No Staphylococcus spp.were found to be resistant to vancomycin,teico-planin and linezolid.Detection rates of vancomycin-resistant Enterococcus faecalis and vancomycin-resistant Entero-coccus faecium were 0.6-1.1％and 0.6％-2.2％,respectively.Resistance rates of Escherichia coli and Kleb-siella pneumoniae to imipenem were 3.1％-5.7％and 7.7％-20.9％,respectively.Resistance rates of Pseudo-monasaeruginosa and Acinetobacter baumannii to imipenem were 24.6％-40.1％and 76.1％-80.9％,respective-ly.Detection rates of carbapenem-resistant Pseudomonas aeruginosa declined year by year.Acinetobacter baumannii maintained high susceptibility to polymyxin B,with resistance rate＜10％.Conclusion Antimicrobial resistance of bacteria from ICUs is serious.Carbapenem-resistant Enterobacteriales has an upward trend after 2019.It is nece-ssary to strengthen the surveillance of bacterial resistance and carry out multidisciplinary collaboration.