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 impact of whole blood organophosphate esters (OPEs) flame retardant exposure on thyroid function-related hormones in healthy older adults.Methods:In this panel study, five repeated population-based epidemiological surveys and biological sample collection were conducted from September 2018 to January 2019, with 76 healthy older adults aged 60-69 years in the Dianliu Community of Jinan, Shandong Province. Information on the sociodemographic characteristics, diet, and health status of the respondents was systematically gathered through questionnaires and physical examinations. Fasting venous blood was collected to determine the levels of OPEs, thyroid-stimulating hormone (TSH), triiodothyronine (T 3), and thyroxine (T 4). A linear mixed-effects model was used to analyze the impact of OPEs exposure on thyroid function-related hormones in healthy older adults. Results:Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 350 person visits. The age of the study participants was (65.07±2.76) years, with 38 participants of both sexes. A total of eight OPEs were included with a detection rate exceeding 50%, and the M ( Q 1, Q3) for ∑OPEs was 3.85 (2.33, 5.74) ng/ml, with alkyl-OPEs being the major type of OPEs with an M ( Q 1, Q3) of 1.27 (0.64, 2.50) ng/ml. The M ( Q 1, Q3) for TSH, T 3, and T 4 was 3.74 (2.55, 5.69) μIU/ml, 1.32 (1.10, 1.60) ng/ml, and 45.04 (36.96, 53.27) ng/ml, respectively. Linear mixed-effects model showed that TSH was significantly decreased by 9.93% (95% CI:-15.17%, -4.36%) and 11.14% (95% CI:-15.94%, -6.06%) in older adults for each quartile level increase in TnBP and TEHP exposures, respectively. Gender-stratified analysis indicated that TEHP exposure was negatively associated with TSH levels in male older adults, whereas a decrease in TSH levels among female older adults was associated with TnBP exposure. Conclusion:Exposure to whole blood OPEs is associated with decreased TSH levels among healthy older adults, with notable gender differences.

Objective:To explore the impact of whole blood organophosphate esters (OPEs) flame retardant exposure on thyroid function-related hormones in healthy older adults.Methods:In this panel study, five repeated population-based epidemiological surveys and biological sample collection were conducted from September 2018 to January 2019, with 76 healthy older adults aged 60-69 years in the Dianliu Community of Jinan, Shandong Province. Information on the sociodemographic characteristics, diet, and health status of the respondents was systematically gathered through questionnaires and physical examinations. Fasting venous blood was collected to determine the levels of OPEs, thyroid-stimulating hormone (TSH), triiodothyronine (T 3), and thyroxine (T 4). A linear mixed-effects model was used to analyze the impact of OPEs exposure on thyroid function-related hormones in healthy older adults. Results:Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 350 person visits. The age of the study participants was (65.07±2.76) years, with 38 participants of both sexes. A total of eight OPEs were included with a detection rate exceeding 50%, and the M ( Q 1, Q3) for ∑OPEs was 3.85 (2.33, 5.74) ng/ml, with alkyl-OPEs being the major type of OPEs with an M ( Q 1, Q3) of 1.27 (0.64, 2.50) ng/ml. The M ( Q 1, Q3) for TSH, T 3, and T 4 was 3.74 (2.55, 5.69) μIU/ml, 1.32 (1.10, 1.60) ng/ml, and 45.04 (36.96, 53.27) ng/ml, respectively. Linear mixed-effects model showed that TSH was significantly decreased by 9.93% (95% CI:-15.17%, -4.36%) and 11.14% (95% CI:-15.94%, -6.06%) in older adults for each quartile level increase in TnBP and TEHP exposures, respectively. Gender-stratified analysis indicated that TEHP exposure was negatively associated with TSH levels in male older adults, whereas a decrease in TSH levels among female older adults was associated with TnBP exposure. Conclusion:Exposure to whole blood OPEs is associated with decreased TSH levels among healthy older adults, with notable gender differences.

Xiaoxuming decoction is one of the classical prescriptions in ancient times,mainly used for treating stroke syndrome,with significant therapeutic effects.Recent studies have found that it is also effective for other neurological diseases besides stroke,such as facial paralysis and vertigo,but there are few reports on related achievements,lacking systematic organization and summary.This article systematically summarizes the application practice and mechanism of Xiaoxuming decoction in the above-mentioned diseases,aiming to provide a solid foundation and scientific reference for deepening the exploration of Xiaoxuming decoction in the field of nervous system disease.

Objective:To analyze the distribution and drug resistance of pathogens of bacterial bloodstream infection in patients with hematological diseases in the Department of Hematology of Tianjin Medical University General Hospital, and to provide etiological data for clinical empirical anti-infection treatment.Methods:A retrospective analysis was conducted on the general clinical information, pathogenic bacteria and drug susceptibility test results of patients with hematological diseases diagnosed with bacterial bloodstream infection by menstrual blood culture in our center from January 2016 to December 2022.Results:Patients included 498 inpatients, with a total of 639 bacterial strains. Among the patients, 86.9% patients had malignancies, and 76.7% had agranulocytosis. Symptoms of concurrent infections, including those of the respiratory tract, oral mucosa, skin and soft tissues, and abdominal sources were observed in 68.3% patients. Gram-negative bacteria (G -) accounted for 79.0% of the isolated bacteria, and gram-positive bacteria (G +) accounted for 21.0%. The top five isolated pathogens were Klebsiella pneumoniae (22.5%), Escherichia coli (20.8%), Pseudomonas aeruginosa (15.0%), Enterococcus faecium (5.5%), and Stenotrophomonas maltophilum (5.0%). Escherichia coli exhibited a decreasing trend of resistance to quinolones, cephalosporins, and carbapenems. Klebsiella pneumoniae exhibited increasing rates of resistance to quinolones and cephalosporins between 2016 and 2018, but the rated decreased after 2019. The resistance rate to carbapenems exhibited by Pseudomonas aeruginosa was approximately 20%. Carbapenem-resistant strains of Pseudomonas aeruginosa strains were first detected in 2017, with a peak resistance rate of 35.7%, detected in 2019. A 60.0% resistance rate to methicillin was observed in methicillin-resistant coagulase-negative staphylococci (MRCNS), and one case of linezolid-resistant MRCNS was detected. Conclusions:Pathogenic bacteria of bacterial bloodstream infections were widely distributed in our center, and precautions are warranted against carbapenem resistant P. aeruginosa and Klebsiella pneumoniae.

Objective:To explore the effect of NOD-like receptor thermal protein 3 ( NLRP3) knockout in γ-aminobutyric acid (GABA)-ergic neurons in the hippocampal CA1 area on improving cognitive dysfunction in mice after traumatic brain injury (TBI). Methods:Forty-eight healthy male NLRP3 flox/flox mice weighing 25-28 g were randomly divided into 4 groups ( n=12): sham-operated+control virus group (SV group), sham-operated+ NLRP3 specific knockout group (SG group), TBI+control virus group (TV group), TBI+ NLRP3 specific knockout group (TG group). TBI in the TV and TG groups was established by free-fall method, while surgical procedures such as scalp incision and cranial window opening without impact were given to the SV and SG groups. Adenovirus was injected into the hippocampal CA1 area of SG and TG groups 21 d before TBI to induce NLRP3 specific knockout in GABA-ergic neurons in the hippocampal CA1 area; empty virus was injected into the CA1 area of SV and TV groups. Cognitive function was evaluated using novel object recognition test 30 and 31 d after TBI, and learning and memory functions were assessed using Morris water maze test 32-36 d after TBI. Field potentials in the hippocampal CA1 area were recorded during novel object recognition 31 d after TBI. After behavioral tests, these mice were sacrificed. Immunofluorescent staining was used to detect the fluorescent intensity of microtubule-associated protein2 (MAP2), glutamic acid decarboxylase 67 (GAD67), and postsynaptic density protein 95 (PSD95) in the hippocampal CA1 area, as well as percentage of pyroptosis-associated inflammatory factor interleukin-18 (IL-18)/GAD67 double-positive neurons in total GAD67 positive neurons. Results:Compared with the SV and SG groups, the TV and TG groups had decreased novel object recognition index, decreased number of platform crossings during the experimental period, increased escape latency on day 3 and day 4 of the training period in Morris water maze test, decreased θ and γ oscillation power in the hippocampal CA1 area during novel object recognition, decreased fluorescent intensity of MAP2, GAD67, and PSD95 in the hippocampal CA1 area, increased percentage of IL-18/GAD67 double-positive neurons, with significant differences ( P<0.05). Compared with the TV group, the TG group had increased novel object recognition index, increased number of platform crossings in Morris water maze test, decreased escape latency during the training period, increased θ and γ oscillation power in the hippocampal CA1 area during novel object recognition, increased fluorescence intensity of MAP2, GAD67, and PSD95 in the hippocampal CA1 area, decreased percentage of IL-18/GAD67 double-positive neurons, with significant differences ( P<0.05). Conclusion:Specific inhibition of NLRP3 expression in GABA-ergic neurons in the hippocampal CA1 area can improve cognitive dysfunction in mice after TBI, whose mechanism may be related to inhibited GABA-ergic neuronal pyroptosis in the hippocampal CA1 area.

Objective To analyze the medication rule of Traditional Chinese Medicine(TCM)in treating diabetes nephropathy(DN)and to explore the interaction between core components and key targets.Methods Based on the ancient and modern medical case cloud platform,the medication rules of TCMs and the drug pairs with the highest frequency in treating DN were summarized.Then the network pharmacology approach was utilized to analyze the pharmacodynamic material basis and mechanisms of the highest frequency-drug pairs.The potential targets were predicted by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)databases.TTD,DISGENET,and GENECARD databases were used to obtain the related targets of DN and screen out the potential targets for DN.In order to clarify the relationships between the active ingredients,the core targets,and pathways,STRING and Cytoscape 3.7.1 software were used to construct the protein-protein interaction(PPI)network and core drugs-ingredients-targets-disease interaction network,DAVID database was screened for Kyoto Encyclopedia of Genes and Gnomes(KEGG)enrichment analysis of core targets.Sybyl 2.1 software and biofilm interference verify the combined capacity between the core ingredients and key targets.Results Among 183 prescriptions,Astragali Radix had the highest use frequency and average dose,43 times and 37 g,respectively,followed by Salviae miltiorrhizae Radix and Poria cocos.To find the core combined with the highest confidence in association analysis was astragalus,salvia miltiorrhiza,and tuckahoe.Correlation analysis indicates that the core combination with the highest confidence was Astragali Radix-Salviae miltiorrhizae Radix-Poria cocos.Network pharmacologic showed 89 potential targets and 15 key signaling pathways for the treatment of DN by the drug pair.TNF signaling pathway,Nod-like receptor signaling pathway,and MAPK signaling pathway were disease-related pathways,and IL-6,TNF,and vascular endothelial growth factor A(VEGFA)were core targets.Isorhamnetin and quercetin of the drug pair had high binding ability with IL6,the scores were 8.2 and 7.4,respectively,and the dissociation constants(KD)were 5.6×10-5 mol·L-1 and 6.8×10-5 mol·L-1,respectively.Conclusion This study preliminarily finds the prescription rule of treating DN with Astragali Radix-Salviae miltiorrhizae Radix-Poria cocos as the core drug pair,isorhamnetin,and quercetin are probably the main active compounds of this drug pair in DN treatment,which provides a basis for clinical treatment and drug discovery of DN.