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.

ObjectiveTo investigate the value of Fried Frailty Phenotype （FFP）， liver frailty index （LFI）， and Short Physical Performance Battery （SPPB） in predicting 2-year all-cause mortality and decompensation events in patients with liver cirrhosis. MethodsA total of 277 patients with liver cirrhosis who were hospitalized in Beijing Friendship Hospital， Capital Medical University， from December 2020 to December 2021 were enrolled， and FFP， LFI， and SPPB were used to assess the state of frailty. Based on the scores of each tool， these patients were divided into frail and non-frail groups. These three tools were compared in terms of consistency and independent predictive performance. The primary endpoints were 2-year all-cause mortality rate and composite endpoints （death+decompensation events）， and the Cox regression analysis， the receiver operating characteristic （ROC） curve， net reclassification index （NRI）， and integrated discrimination improvement （IDI） index were used to analyze the predictive value of the three tools. Normally distributed continuous data were compared between two groups using the independent samples t-test， while non-normally distributed continuous data were compared using the Mann-Whitney U test. Categorical data were compared between groups using the chi-square test or Fisher’s exact test. The agreement among different frailty tools was evaluated using Cohen’s Kappa statistic. The Kaplan-Meier survival curve was plotted， and a survival analysis was performed using the log-rank test. ResultsThe prevalence rate of frailty assessed by FFP， LFI， and SPPB was 37.2%， 22.4%， and 20.2%， respectively， with a moderate consistency between FFP and LFI/SPPB （κ=0.57， 95% confidence interval ［CI］： 0.47 — 0.67； κ=0.51， 95%CI： 0.41 — 0.62） and a relatively high consistency between LFI and SPPB （κ=0.87， 95%CI： 0.80 — 0.94）. Compared with the non-frailty group， the frailty group had significantly higher all-cause mortality rate and incidence rate of composite endpoints （P0.001）. After multivariate adjustment， FFP， LFI， and SPPB had a hazard ratio of 2.42（95%CI： 1.51 — 5.11）， 2.21（95%CI： 1.11 — 4.42）， and 2.21（95%CI： 1.14 — 4.30）， respectively， in predicting all-cause mortality， as well as a hazard ratio of 2.51（95%CI： 1.61 — 3.91）， 2.40（95%CI： 1.51 — 3.80）， and 2.20（95%CI： 1.39 — 3.47）， respectively， in predicting composite endpoints. Compared with Child-Pugh score， FFP had a significantly greater area under the ROC curve （AUC） in predicting all-cause mortality （0.79 vs 0.69， P=0.032） and composite endpoints （0.75 vs 0.68， P=0.044）. Frailty assessment tools combined with Child-Pugh score significantly improved the performance in predicting all-cause mortality and composite endpoints， with an AUC of 0.81 — 0.82 and 0.77 — 0.78， respectively （P0.05）. NRI and IDI analyses further confirmed the improvement of the combined model in classification （all P0.001）. ConclusionFFP， LFI， and SPPB can independently predict adverse outcomes in patients with liver cirrhosis， among which FFP has the best predictive performance， and the combination of frailty assessment tools with Child-Pugh score can significantly enhance the accuracy of prognostic evaluation.

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 investigate the clinical efficacy and safety of ferric derisomaltose injection versus iron sucrose injection in the treatment of iron deficiency anemia (IDA) .Methods:A total of 120 patients with iron deficiency anemia admitted from June 2021 to March 2023 were given intravenous iron supplementation with ferric derisomaltose to assess the efficacy and safety of hemoglobin (HGB) elevation before and after treatment. Simultaneously, the clinical effects of iron supplementation with iron sucrose were compared to those of inpatient patients during the same period.Results:Baseline values were comparable in both groups. Within 12 weeks of treatment, the elevated HGB level in the ferric derisomaltose group was higher than that of the iron sucrose group, with a statistical difference at all time points, and the proportion of HGB increased over 20 g/L in the patients treated for 4 weeks was higher (98.7%, 75.9% ). During the treatment with ferric derisomaltose and iron sucrose, the proportion of mild adverse reactions in the ferric derisomaltose group was slightly lower than that of the iron sucrose group, and neither group experienced any serious adverse reactions. The patients responded well to the infusion treatment, with no reports of pain or pigmentation at the injection site.Conclusion:The treatment of IDA patients with ferric derisomaltose has a satisfactory curative effect, with the advantages of rapidity, accuracy, and safety. Therefore, it is worthy of widespread clinical use.

Objective:This study aimed at investigating the efficacy and safety of eltrombopag in the treatment of adult primary immune thrombocytopenia (ITP) and evaluated the factors influencing its efficacy and side effects.Methods:A total of 198 patients with adult ITP who were admitted to Tianjin Medical University General Hospital between January 2018 and March 2022 were retrospectively analyzed. The efficacy of each starting dose of eltrombopag was evaluated, and adverse events were analyzed. The factors influencing efficacy were investigated, including sex, age, adult ITP type, platelet antibodies, and combined drug treatments.Results:Of the 198 patients, 70 males and 128 females with a median age of 45 years (18-88 years) were included; 130 (65.7%) had newly diagnosed adult ITP, 25 (12.6%) had persistent adult ITP, and 43 (21.7%) had chronic adult ITP. The bleeding event scores at baseline were assessed; 84.3% had scores of<4 and 15.7% had scores of ≥4. The eltrombopag response rate (initial response) at 6 weeks was 78.8% (complete response [CR]: 49.0%; CR1: 14.6%; CR2: 15.2%). The median response time to eltrombopag was 7 (7, 14) days. The initial response rates to 25, 50, and 75 mg eltrombopag were 74.1%, 85.9%, and 60.0%, respectively ( P=0.031). The initial response rate to the 50 mg dose was significantly higher than that of the 25-mg and 75-mg doses. Two patients received 100 mg as the starting dose, and their initial response was 0. Regarding dose adjustment, 70.7% of the patients remained on the starting dose, 8.6% underwent dose adjustment to 50 mg, and 6.1% underwent dose adjustment to 75 mg. Another two patients underwent dose adjustment to 100 mg. After dose adjustment, the persistent response rates were 83.6%, 85.3%, and 85.7% for the 25-, 50-, and 75-mg doses, respectively, with no significant difference. After dose adjustment, the sustained efficacy rate for the 100-mg dose (4 patients) was 100.0%. After 6 weeks of treatment with eltrombopag, the overall bleeding score of patients with ITP decreased. The number of patients with a score of ≥4 decreased to 0, the number of patients with a score of<4 decreased, and there was no significant change in the number of patients with a score of 1-2. The most common adverse event associated with eltrombopag was impaired liver function (7.7%). No thrombosis events or other adverse events were observed. ITP type and number of megakaryocytes significantly affected the initial response to eltrombopag. The initial response rates to eltrombopag for newly diagnosed adult ITP, persistent adult ITP, and chronic adult ITP were 85.3%, 56.0%, and 76.2%, respectively ( P=0.003). For megakaryocytes, the initial response rates were 61.8%, 87.1%, and 84.3% ( P=0.009) for the decreased, normal, and increased megakaryocyte groups, respectively. Conclusion:Eltrombopag, as a second-line or higher treatment for adult ITP, has a rapid onset of action and good safety. The initial response rate is significantly higher with a dose of 50 mg than with a dose of 25 mg. Patients with newly diagnosed ITP and those with normal or increased megakaryocyte numbers have a higher initial response rate to eltrombopag.

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 distribution of airborne pollen in Cangzhou,to analyze the correlation between pollen characteristics,meteorological factors and the rate of allergic rhinitis visits,and to provide a reference basis for the precise prevention and treatment of allergic rhinitis in Cangzhou.METHODS The gravity deposition method was applied to collect daily airborne pollen from the monitoring sites in Cangzhou from March to October 2022 and record the pollen species and quantities.We also collected information on allergic rhinitis patients who visited the ENT Department of Cangzhou Central Hospital during the same period and meteorological data(daily maximum temperature,minimum temperature,maximum relative humidity,maximum precipitation,and maximum wind speed at ground level)during the same period,and analyzed the relationship between the number of AR patients'visits,the amount of pollen,and the meteorological factors.RESULTS 1.A total of 229 pollen exposures were collected from March to October 2022,totaling 19 368 pollen grains,of which 18 750 grains of pollen could be identified in 19 families and 618 grains were difficult to identify the families.2.There were two peaks of pollen during the period,in April and September respectively.Spring pollen to tree-based category,to the pine family,willow willow family,Xylariaceae(ash)most often;summer pollen volume has declined,but still tree-based category;fall pollen to herbaceous category,to the Asteraceae Artemisia,mulberry,Gramineae most often.3.The pollen concentration in Cangzhou City was negatively correlated with maximum humidity,maximum precipitation,maximum temperature,and minimum temperature.Maximum wind speed at ground level was positively correlated with pollen concentration.4.Pollen concentration was positively correlated with the number of visits.The correlation analysis between daily medical visits from June to October and air pollen concentration showed a significant positive correlation,while the results from March to May showed no significant correlation.CONCLUSION The peak of airborne pollen dispersal in April and September in Cangzhou.Spring and summer pollen is dominated by tree species,and the dominant pollen is Pinaceae,Willow genus of Populus,and Xylariaceae(ash genus);fall pollen is dominated by herbaceous species,and the dominant pollen is Artemisia,Asteraceae,Mulberry,and Gramineae.Meteorological factors are important factors affecting pollen concentration.Within a certain range,the lower the maximum humidity,the lowest maximum precipitation,the lower the highest or the lowest temperature,the higher the pollen concentration,and the pollen concentration is more affected by the lowest temperature.There is a correlation between pollen concentration and the number of AR patients'visits from June to October,which can be used as an environmental early warning indicator of the prevalence of AR.

Objective:To develop a prediction tool for 6-year incident risk of frailty among Chinese older adults aged 65 years or above.Methods:Data from the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018 was used, including 13 676 older adults aged 65 years or above who were free of frailty at baseline. Key predictors of frailty were identified via the least absolute shrinkage and selection operator (LASSO) method, and were thereafter used to predict the incident frailty based on the Cox proportional hazards regression model. The model was internally validated by 2 000 Bootstrap resamples and evaluated for the performance of discrimination and calibration using the area under the receiver operating characteristic curve (AUC) and calibration curve, respectively. The net benefit of the developed prediction tool was evaluated by decision-curve analysis.Results:The M( Q1, Q3) age and follow-up time of the participants were 81.0 (71.0, 90.0) years and 6.0 (4.1, 9.2) years, respectively. A total of 4 126 older persons (30.2%) were recorded with frailty incidents during the follow-up, with the corresponding incidence density of 41.8/1 000 person-years. A total of 15 key predictors of frailty were selected by LASSO, namely, age, sex, race, education years, meat consumption, tea drinking, performing housework, raising domestic animals, playing cards or mahjong, and baseline status of visual function, activities of the daily living score, instrumental activities of the daily living score, hypertension, heart disease, and self-rated health. The prediction model was internally validated with an AUC of 0.802, with the max Youden's index of 0.467 at a risk threshold of 19.0%. The calibration curve showed high consistency between predicted probabilities and observed proportions of frailty events. The decision curve indicated that higher net benefits could be obtained via the prediction model than did strategies based on intervention in all or none participants for any risk threshold less than 59%, and the model-based net benefit was estimated to be 0.10 at a risk threshold of 19.0%. Conclusions:The herein developed 6-year incident risk prediction model of frailty, based on easily accessible questionnaires and physical examination variables, has good predictive performance. It has application potential in identifying populations at high risk of incident frailty.