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 relationship between autistic trait and pain empathy among college students, as well as the mediating role of personal pain perception.Methods:From October to December 2023, a cross-sectional survey was conducted among 1 195 college students using the autism spectrum quotient, pain sensitivity questionnaire, fear of pain questionnaire, pain catastrophizing scale and empathy for pain scale.SPSS 27.0 software was used for descriptive statistics and correlation analysis.A structural equation model was constructed using Mplus 8.3 to examine the mediating effect of personal pain perception, which was composed of pain sensitivity, fear and catastrophizing cognition.Results:Autistic trait(22.00(18.00, 26.00))was significantly positively correlated with pain sensitivity (55.00(43.00, 70.00)), fair of pain (69.00(60.00, 78.00)), and pain catastrophizing cognition (16.00(8.00, 23.00)) ( r=0.112, 0.154, 0.204, all P<0.001).Autistic trait was also significantly positively correlated with affective distress(62.00(46.00, 80.00), r=0.162, P<0.001) and vicarious pain (14.00(8.00, 20.00), r=0.096, P<0.001) of pain empathy.Pain sensitivity, fear of pain and pain catastrophizing cognition were significantly positively correlated with affective distress( r=0.244, 0.332, 0.375, all P<0.001) and vicarious pain ( r=0.210, 0.232, 0.285, all P<0.001) of pain empathy.The effects of autistic trait on affective distress and vicarious pain dimensions of pain empathy were fully mediated by personal pain perception, with the mediating effects of 0.115( P<0.001, 95% CI=0.073-0.165) and 0.085( P<0.001, 95% CI=0.053-0.124). Conclusions:The autistic trait of college students can predict the affective distress and vicarious pain of pain empathy indirectly through personal pain perception.

Objectives:To develop a risk prediction model for sudden cardiac arrest(CA)in children with congenital heart disease(CHD)after surgery and validate its predictive efficacy,providing a reference for the prevention of CA and risk stratification.Methods:Medical records were retrospectively analyzed from 5 029 children who were hospitalized in Fuwai Hospital,Chinese Academy of Medical Sciences from January 1,2020 to May 31,2022 and underwent CHD surgery.The patients were divided into two groups:those who experienced CA after surgery(n=33)and those who did not(n=4 996).A random forest model for predicting the risk of postoperative CA was established on the training dataset using R software,and the predictive effect of the model was evaluated on the validation dataset using indicators of predictive accuracy,sensitivity,specificity,positive predictive value,negative predictive value.Results:The incidence of CA in this center was 0.66%,survival rate is 72.73%.Using the random forest algorithm,the importance of risk factors for sudden CA after CHD surgery was ranked by variable importance scoring,with the following top 6 important predictive variables:blood pressure,lactate levels,heart rate,cardiac rhythm,arterial oxygen partial pressure,and blood oxygen saturation on the first day after surgery.The model established by the random forest algorithm on the training set was validated on the test set,yielding a predictive accuracy of 99.8%,specificity of 87.5%,sensitivity of 99.9%,kappa coefficient of 0.8225,positive predictive value of 99.9%,and negative predictive value of 77.8%.Conclusions:The established prediction model of sudden CA in children with CHD after surgery had good performance.It might help medical staffon decision making of early intervention,preventing the occurrence of CA,and improving the outcomes of children with high risk of CA post surgery.

Objective To explore the expert consensus on perinatal care management of infants with congenital heart disease(hereinafter referred to as"Consensus")in order to promote the standardization of integrated nursing.Methods The literature was systematically searched and several discussions were organized within the group to compile the first draft of the Consensus.From January to March 2024,20 experts in the clinical nursing,nursing management,clinical medicine and other fields of congenital heart disease were solicited through 2 rounds of Delphi,and 8 experts were invited to conduct a validation to revise the items to form the final Consensus.Results The recovery rates of the 2 rounds of questionnaires were 100％;the experts'authority coefficient was 0.89;the Kendall's W were 0.172,0.211,with statistical significance(P＜0.05).The Consensus included 8 first-level subjects,namely prenatal examination and consultation,postpartum screening,standardized referral,preoperative nursing,intraoperative nursing,postoperative nursing,other disease screening,health education and discharge follow-up.Conclusion The Consensus is scientific and rigorous,and it can provide a reference basis for clinical nursing staff to carry out the care and management of newborns with congenital heart disease.

Objective:To explore the relationship between autistic trait and pain empathy among college students, as well as the mediating role of personal pain perception.Methods:From October to December 2023, a cross-sectional survey was conducted among 1 195 college students using the autism spectrum quotient, pain sensitivity questionnaire, fear of pain questionnaire, pain catastrophizing scale and empathy for pain scale.SPSS 27.0 software was used for descriptive statistics and correlation analysis.A structural equation model was constructed using Mplus 8.3 to examine the mediating effect of personal pain perception, which was composed of pain sensitivity, fear and catastrophizing cognition.Results:Autistic trait(22.00(18.00, 26.00))was significantly positively correlated with pain sensitivity (55.00(43.00, 70.00)), fair of pain (69.00(60.00, 78.00)), and pain catastrophizing cognition (16.00(8.00, 23.00)) ( r=0.112, 0.154, 0.204, all P<0.001).Autistic trait was also significantly positively correlated with affective distress(62.00(46.00, 80.00), r=0.162, P<0.001) and vicarious pain (14.00(8.00, 20.00), r=0.096, P<0.001) of pain empathy.Pain sensitivity, fear of pain and pain catastrophizing cognition were significantly positively correlated with affective distress( r=0.244, 0.332, 0.375, all P<0.001) and vicarious pain ( r=0.210, 0.232, 0.285, all P<0.001) of pain empathy.The effects of autistic trait on affective distress and vicarious pain dimensions of pain empathy were fully mediated by personal pain perception, with the mediating effects of 0.115( P<0.001, 95% CI=0.073-0.165) and 0.085( P<0.001, 95% CI=0.053-0.124). Conclusions:The autistic trait of college students can predict the affective distress and vicarious pain of pain empathy indirectly through personal pain perception.

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 analyze the status of outdoor activities on weekends among children and adolescents of different educational stages in Shanghai and their impact on myopia, so as to provide a basis for formulating more specific prevention and control protocol of myopia. Methods: From September to October 2022, a stratified cluster random sampling method was employed to select 84 schools (27 kindergartens, 21 primary schools, 15 junior high schools and 21 high schools) across Shanghai, enrolling a total of 28 654 children and adolescents aged 4 to 18 for the study. Ophthalmic examinations were conducted to ascertain the prevalence of myopia among children and adolescents. Additionally, a questionnaire survey was administered to collect data on outdoor activity duration and associated factors. Multivariate Logistic regression analysis was utilized to investigate the associated factors of outdoor activity levels on weekends. Results: The overall myopia detection rate among children and adolescents was 58.4%, with a higher rate observed in girls (59.2%) compared to boys (57.6%). The myopia detection rates for children and adolescents with an average daily outdoor activity duration of ≥2 h and <2 h on weekends were 54.6% and 68.8%, and the differences were statistically significant ( χ 2=8.12,460.89, P <0.01). Multivariable Logistic regression analysis revealed that girls ( OR =0.80), those with a myopic parent ( OR =0.68), schools from urban districts ( OR =0.72), higher education stages (primary school: OR =0.65, junior high school: OR =0.24, high school: OR =0.14) and spending≥2 h/d on homework during weekends ( OR =0.57) among children and adolescents were less likely to engage in outdoor activities for ≥2 h on weekends ( P <0.01). After incorporating gender, parental myopia status, educational stage, school location, average daily duration on weekends for spending on homework, electronic product usage and outdoor activities as dependent variables in a multivariate Logistic regression analysis, the results showed that children and adolescents with an average outdoor activity duration for ≥2 h on weekends had a lower risk of myopia ( OR =0.86, P < 0.01). Conclusions The level of outdoor activity among children and adolescents on weekends needs to be improved. Outdoor activities on weekends is an associated factor for myopia among children and adolescents. Particularly, girls, those with myopic parents, schools from urban districts, and spending long hours on homework during weekends among children and adolescents require increased attention.

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 sort out the management system of clinical trial drugs in our hospital,and analyze the construction and practical experience of the information system in the whole process management of clinical trial drugs,and to further improve the efficiency and quality of clinical trials.Methods Based on the original management of clinical trial drugs,an information system in line with the situation of our hospital was applied to manage the whole process of clinical trial drugs.Results Compared with the traditional management,the information system can automatically record the data of inbound and outbound storage,distribution,retrieval and return of trial drugs in real time,pre-review the prescriptions and randomized documents of clinical trial drugs,and realise paperless office.Conclusions The information system can ensure the safety,accuracy and traceability of the data of drugs used in clinical trial.The system can also save resources,improve the efficiency and quality of clinical trial management.

Objective:To investigate the impact of different target sites, number of treatments, and age on setup errors in dual-isocenter radiotherapy for breast cancer, and to provide a basis for planning target volume (PTV) margin expansion.Methods:A retrospective analysis was conducted on data from 15 patients with left-sided breast cancer who underwent dual-isocenter breath-hold radiotherapy in the Department of Radiotherapy Oncology at the Second Hospital of Hebei Medical University from May 2021 to May 2023. Setup errors were acquired using a Varian TrueBeam STX linear accelerator. Patients were grouped by target site (supraclavicular/chest wall), treatment phase (early/late), and age (younger/older). Non-parametric tests were used to analyze differences in setup errors in : vertical (Vrt), longitudinal (Lng), lateral (Lat) directions, and pitch, roll, and rotation (Rtn) angles. The formula proposed by van Herk was applied to calculate PTV margins.Results:The Vrt direction setup error in the supraclavicular region (0.2 cm) was smaller than that in the chest wall region (0.26 cm), but errors and margin expansions in other directions were larger ( P<0.05 for Lng and Lat directions). No significant correlation was observed in Vrt direction errors between the two sites ( P=0.062), while significant correlations were found in the other directions and angles (all P<0.05). As treatment progressed, setup errors increased in the Vrt and Rtn directions for the supraclavicular region, and in the Vrt, Lng, Lat directions and Rtn angle for the chest wall region. Among these, only the increase in Lat direction error for the chest wall region was statistically significant ( P=0.028). The PTV margins in the late phase group (except for the Lat direction of the supraclavicular region) were greater than or equal to those in the early phase group. Elderly patients had significantly larger setup errors than younger patients in Vrt, Lng, and Lat directions for the supraclavicular region, as well as in Vrt and Lat directions for the chest wall region (all P<0.05). Conclusions:In dual-isocenter radiotherapy for breast cancer, the supraclavicular region requires larger PTV margins than the chest wall region, and elderly patients require greater margins overall. Mid-course rescanning is recommended. If cone-beam CT guidance cannot be ensured for every session, expansion of PTV margins should be considered for the supraclavicular region and elderly patients to reduce the risk of geographic miss.