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 explore a definition of healthy longevity in the Chinese population based on the Delphi method.Methods:Through a comprehensive literature review and expert consultation, the dimensions in the definition of healthy longevity were identified, and a preliminary list of questions was created. Experts in clinical medicine, public health, basic research, and the elderly care service industry, who had been working in the field of geriatric health for at least 5 years, were invited to participate in the Delphi survey from August to December 2022. The survey questionnaires were administered via email in two rounds, and experts were asked to select the optimal options from the provided questions. The active coefficients were expressed by the response rate, and a consensus was reached when the largest number of experts agreed for single-choice questions and more than 70% agreed for multiple-choice questions.Results:In the two rounds, the active coefficients were 96.00% (24/25) and 79.17% (19/24), respectively, and a consensus was finally reached on nine items, including age, physical health, common metabolic indicators, mental health, cognitive function, functional ability, social activity, self-rated health, and subjective well-being. Following discussions among the research team and experts, a final definition of healthy longevity was determined. Healthy longevity could refer to a state of good physical, psychological, cognitive function and social adaptation, as well as subjective well-being, in individuals aged 90 and above. Specifically, individuals with healthy longevity should be free from diseases associated with high disability rates and mortality, such as stroke, cancer, and Parkinson′s disease. They should also maintain reasonable levels of common non-communicable disease indicators, such as blood pressure and blood glucose, and exhibit favorable mental health and cognitive function using validated measurement tools. In addition, individuals with healthy longevity should engage in social interactions with friends and relatives, care for family members, and go out to do things. Meanwhile, with the ability to complete the visual and hearing functions of daily life and communication, and the ability to complete basic activities such as walking, eating, bathing, toileting, dressing, continence of urination, and bowel movement independently, they could rate themselves to be in good health and experience a relatively high level of life satisfaction.Conclusion:A definition of healthy longevity in the Chinese population is established through the two-round Delphi consultation.

Objective:To explore the implementation strategies for promoting healthy longevity among the elderly population in China based on the Delphi method.Methods:Through literature review and expert discussion, a framework for implementation strategies to achieve healthy longevity among the elderly was determined, and a preliminary checklist of implementation strategies was developed. The Delphi method was employed from August to December 2022, inviting 25 experts from various disciplines such as clinical medicine, public health, basic research, and the elderly care services industry. Experts were sent consultation questionnaires via email to assess the importance, feasibility, judgment basis and familiarity of each implementation strategy. Active coefficient, authority coefficient, and harmony coefficient were analyzed to ultimately determine the important and feasible implementation strategies for healthy longevity that were suitable for the Chinese elderly population.Results:The expert active coefficients of the two rounds were 96.00% (24/25) and 79.17% (19/24). The authority coefficients were (0.76±0.19) and (0.77±0.17). The average scores of importance were (4.32±0.84) and (4.36±0.82), and the corresponding scores of feasibility were (3.72±1.04) and (3.80±0.92). The harmony coefficients for the importance score were 0.269 ( χ 2=594.084, P<0.001) and 0.159 ( χ 2=193.624, P<0.001). The harmony coefficients for feasibility scores were 0.205 ( χ 2=452.008, P<0.001) and 0.167 ( χ 2=202.878, P<0.001). The final eight implementation strategies were identified after two rounds of consultation. Conclusion:Through two rounds of Delphi consultations, eight important and feasible implementation strategies for promoting healthy longevity that are suitable for the Chinese context have been proposed.

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.

Objective:To explore a definition of healthy longevity in the Chinese population based on the Delphi method.Methods:Through a comprehensive literature review and expert consultation, the dimensions in the definition of healthy longevity were identified, and a preliminary list of questions was created. Experts in clinical medicine, public health, basic research, and the elderly care service industry, who had been working in the field of geriatric health for at least 5 years, were invited to participate in the Delphi survey from August to December 2022. The survey questionnaires were administered via email in two rounds, and experts were asked to select the optimal options from the provided questions. The active coefficients were expressed by the response rate, and a consensus was reached when the largest number of experts agreed for single-choice questions and more than 70% agreed for multiple-choice questions.Results:In the two rounds, the active coefficients were 96.00% (24/25) and 79.17% (19/24), respectively, and a consensus was finally reached on nine items, including age, physical health, common metabolic indicators, mental health, cognitive function, functional ability, social activity, self-rated health, and subjective well-being. Following discussions among the research team and experts, a final definition of healthy longevity was determined. Healthy longevity could refer to a state of good physical, psychological, cognitive function and social adaptation, as well as subjective well-being, in individuals aged 90 and above. Specifically, individuals with healthy longevity should be free from diseases associated with high disability rates and mortality, such as stroke, cancer, and Parkinson′s disease. They should also maintain reasonable levels of common non-communicable disease indicators, such as blood pressure and blood glucose, and exhibit favorable mental health and cognitive function using validated measurement tools. In addition, individuals with healthy longevity should engage in social interactions with friends and relatives, care for family members, and go out to do things. Meanwhile, with the ability to complete the visual and hearing functions of daily life and communication, and the ability to complete basic activities such as walking, eating, bathing, toileting, dressing, continence of urination, and bowel movement independently, they could rate themselves to be in good health and experience a relatively high level of life satisfaction.Conclusion:A definition of healthy longevity in the Chinese population is established through the two-round Delphi consultation.

Objective:To explore the implementation strategies for promoting healthy longevity among the elderly population in China based on the Delphi method.Methods:Through literature review and expert discussion, a framework for implementation strategies to achieve healthy longevity among the elderly was determined, and a preliminary checklist of implementation strategies was developed. The Delphi method was employed from August to December 2022, inviting 25 experts from various disciplines such as clinical medicine, public health, basic research, and the elderly care services industry. Experts were sent consultation questionnaires via email to assess the importance, feasibility, judgment basis and familiarity of each implementation strategy. Active coefficient, authority coefficient, and harmony coefficient were analyzed to ultimately determine the important and feasible implementation strategies for healthy longevity that were suitable for the Chinese elderly population.Results:The expert active coefficients of the two rounds were 96.00% (24/25) and 79.17% (19/24). The authority coefficients were (0.76±0.19) and (0.77±0.17). The average scores of importance were (4.32±0.84) and (4.36±0.82), and the corresponding scores of feasibility were (3.72±1.04) and (3.80±0.92). The harmony coefficients for the importance score were 0.269 ( χ 2=594.084, P<0.001) and 0.159 ( χ 2=193.624, P<0.001). The harmony coefficients for feasibility scores were 0.205 ( χ 2=452.008, P<0.001) and 0.167 ( χ 2=202.878, P<0.001). The final eight implementation strategies were identified after two rounds of consultation. Conclusion:Through two rounds of Delphi consultations, eight important and feasible implementation strategies for promoting healthy longevity that are suitable for the Chinese context have been proposed.