Objective: To explore the assocation of the family environment and depressive symptoms among primary and middle school students, so as to provide suggestions for further maximizing the utility of family environment in the growth of primary and secondary school students, as well as prevention and intervention of depressive symptoms among children and adolescents. Methods: From June to July 2024, through a multistage cluster random sampling method, 8 800 primary and middle school students aged 10 to 18 from 36 schools in 3 cities (Datong, Lvliang, Linfen) in Shanxi Province. A self designed questionnaire was used to conduct a family environment survey, including family socioeconomic conditions, family structure, family parenting behavior, family member health behavior, etc; and the depression symptoms of primary and secondary school students were investigated by Patient Health Questionnaire-9. The χ 2 test and binary Logistic regression to method were used to analyze the association of the family environment with depressive symptoms among primary and secondary school students, and to analyze gender and urban-rural heterogeneity in this association. Results: The detection rate of depressive symptoms among primary and middle school students was 46.7% ( n = 4 111 ). Among them, the detection rates of depressive symptoms for male and female students were 45.7% and 47.7% respectively, and the detection rates for rural and urban students were 48.0% and 44.9% respectively. The results of binary Logistic regression model showed that in the family environment, factors such as the father s education level (junior high school: OR =0.84), self assessed family socio economic status (average: OR =0.78, good: OR =0.80), parental support and understanding (yes: OR = 0.55 ), family atmosphere (harmonious: OR =0.66), living arrangement (living only with father or mother: OR =1.31, living with parents and grandparents: OR =1.19), and family rearing style (combining punishment and reward: OR =1.42, punishment only: OR =1.25) were related to depressive symptoms in primary and middle school students in Shanxi Province ( P <0.05). From the perspective of gender heterogeneity, the living arrangement (living only with father or mother: OR =1.67, others: OR =1.67) had a statistically significant association with depressive symptoms in male students ( P <0.05). From the perspective of urban rural heterogeneity, the living arrangement (living only with father or mother: OR =1.38) had a statistically significant association with depressive symptoms in rural primary and middle school students ( P <0.05). Conclusions The family environment has an important impact on depressive symptoms in primary and middle school students. Family functioning should be fully exerted to prevent depressive symptoms in primary and middle school students.

Objective To compare the ability of single-phase,dual-phase,and triphasic models in forecasting postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD)using radiomics based on triphasic enhanced CT.Methods A total of 181 patients who underwent multi-phase enhanced CT prior to PD were retrospectively selected,and the collection phase included non-contrast,arterial phase(AP),and equilibrium phase(EP).3D Slicer software was utilized to segment the region of interest(ROI)for the postoperative pancreatic remnant on each phase.Radiomics feature extraction was performed using R software,followed by feature selection through least absolute shrinkage and selection operator(LASSO)regression with five-fold cross-validation to prevent model overfitting.The effective features selected were combined in a weighted linear manner to obtain a Radiomics score(Radscore).The patients were divided into training set and test set in a 7︰3 ratio.Logistic regression was employed to construct seven POPF prediction models(three single-phase,three dual-phase,and one triphasic models)based on different phase combinations.The diagnostic performance of the models was evaluated using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,accuracy(ACC),sensitivity(SEN),and specificity(SPE).The DeLong test was applied to compare the differences in AUC among different models.Results After LASSO regression,24 effective features associated with POPF were selected from different phases.In the test set,the triphasic model exhibited the highest AUC and ACC(AUC=0.76,ACC=0.808).The calibration curve demonstrated the strongest agreement between the estimated probabilities and observed probabilities for the triphasic model.The decision curve analysis(DCA)curve indicated that the triphasic model had the largest threshold range with a higher net benefit.Conclusion Compared with single-phase and dual-phase models,the triphasic model based on enhanced CT provides better prediction of POPF after PD,aiding clinical decision-making and improve prognosis.

Objective:To investigate the prevalence of flight fatigue among helicopter flying personnel and analyze its contributors in order to provide data for related interventions.Methods:A cross-sectional study was conducted among 404 helicopter flying personnel between October 8, 2021 and July 31, 2022. Data was collected using a self-designed questionnaire, involving the demography of these subjects, sleep-related factors, flight fatigue, perceived causes of fatigue and coping strategies. The Pittsburgh Sleep Quality Index (PSQI), National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Modified Fatigue Impact Scale (MFI-20) were used to assess sleep quality, mental workload, and levels of flight fatigue over the past month. The total scores of MFI-20 were compared across demographic groups, and correlations with PSQI and NASA-TLX scores were analyzed. Multiple linear regression was performed to identify the determinants of flight fatigue.Results:①Demography: among the 404 helicopter flying personnel, 92.8% (375/404) were pilots and 7.2% (29/404) navigators. As for years of service, 41.6% (168/404) served less than 5 years, while 58.4% (236/404) served more than 5 years. 37.9% (153/404) had a family history of insomnia. 18.8% (76/404) did not habitually nap, 68.9% (226/328) napped for ≤30 min, 31.1% (102/328) napped over 30 min, and 18.3% (74/404) had insomnia over the past month. As for helicopter flying personnel, 75.5% (305/404) reported experiencing fatigue, with 69.1% (279/404) attributing it to flight-related factors and 51.5% (208/404) using coffee as a countermeasure.②Scale scores: the total score of PSQI was [5 (3, 7)], while the highest daytime dysfunction score was [1(0, 2)]. The total score of NASA-TLX was [39.19 (26.57, 51.97)], and the effort score was the highest [10.31(5.07, 14.60)]. The total score of MFI-20 averaged (47.28±14.88), with the mental fatigue score being the highest [(10.03±4.42)]. ③Comparisons of MFI-20 total scores: flying personnel with ≤5 years of flying experience had higher MFI-20 total scores than those with >5 years, and those with a family history of insomnia had higher scores than those without ( t=3.35, 2.44, P=0.001, 0.015). Individuals with insomnia over the past month had higher scores than non-insomniacs ( t=3.33, P=0.001). Significant differences in MFI-20 scores were observed based on nap duration ( F=19.95, P<0.001). Non-nappers had higher scores than those napping for ≤30 min ( P=0.005). Flying personnel who napped for >30 min had higher scores than those did not ( P=0.043) or napped for ≤30 min ( P<0.001). ④Correlation analysis: the total score of MFI-20 was positively correlated with sleep quality, sleep latency, sleep disturbances, hypnotic medications, daytime dysfunction, and the total score of PSQI ( r=0.118-0.226, all P<0.05), but negatively with sleep duration ( r=-0.136, P=0.006). The total score of MFI-20 was positively correlated with mental demand, physical demand, and the total score of NASA-TLX ( r=0.119, 0.168, 0.184, P=0.017, 0.001, <0.001). ⑤Multiple linear regression analysis: the determinants of flight fatigue included aircraft types ( B=-4.956, 95% CI:-8.124--1.788), nap duration ( B=3.693, 95% CI: 1.267-6.119), sleep latency ( B=2.371, 95% CI: 0.229-4.513), sleep duration ( B=-7.383, 95% CI:-10.008--4.758), daytime dysfunction ( B=5.003, 95% CI: 2.967-7.039) and physical workload ( B=0.611, 95% CI: 0.324-0.898). Conclusions:Helicopter flying personnel are vulnerable to flight fatigue, which is strongly linked to sleep quality and mental workload. It is crucial to address flying personnel′s self-perceived fatigue, care about fatigue manifestations across aircraft types, and implement targeted interventions to improve sleep quality and reduce mental workload.

Objective To compare the ability of single-phase,dual-phase,and triphasic models in forecasting postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD)using radiomics based on triphasic enhanced CT.Methods A total of 181 patients who underwent multi-phase enhanced CT prior to PD were retrospectively selected,and the collection phase included non-contrast,arterial phase(AP),and equilibrium phase(EP).3D Slicer software was utilized to segment the region of interest(ROI)for the postoperative pancreatic remnant on each phase.Radiomics feature extraction was performed using R software,followed by feature selection through least absolute shrinkage and selection operator(LASSO)regression with five-fold cross-validation to prevent model overfitting.The effective features selected were combined in a weighted linear manner to obtain a Radiomics score(Radscore).The patients were divided into training set and test set in a 7︰3 ratio.Logistic regression was employed to construct seven POPF prediction models(three single-phase,three dual-phase,and one triphasic models)based on different phase combinations.The diagnostic performance of the models was evaluated using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,accuracy(ACC),sensitivity(SEN),and specificity(SPE).The DeLong test was applied to compare the differences in AUC among different models.Results After LASSO regression,24 effective features associated with POPF were selected from different phases.In the test set,the triphasic model exhibited the highest AUC and ACC(AUC=0.76,ACC=0.808).The calibration curve demonstrated the strongest agreement between the estimated probabilities and observed probabilities for the triphasic model.The decision curve analysis(DCA)curve indicated that the triphasic model had the largest threshold range with a higher net benefit.Conclusion Compared with single-phase and dual-phase models,the triphasic model based on enhanced CT provides better prediction of POPF after PD,aiding clinical decision-making and improve prognosis.

Objective:To investigate the prevalence of flight fatigue among helicopter flying personnel and analyze its contributors in order to provide data for related interventions.Methods:A cross-sectional study was conducted among 404 helicopter flying personnel between October 8, 2021 and July 31, 2022. Data was collected using a self-designed questionnaire, involving the demography of these subjects, sleep-related factors, flight fatigue, perceived causes of fatigue and coping strategies. The Pittsburgh Sleep Quality Index (PSQI), National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Modified Fatigue Impact Scale (MFI-20) were used to assess sleep quality, mental workload, and levels of flight fatigue over the past month. The total scores of MFI-20 were compared across demographic groups, and correlations with PSQI and NASA-TLX scores were analyzed. Multiple linear regression was performed to identify the determinants of flight fatigue.Results:①Demography: among the 404 helicopter flying personnel, 92.8% (375/404) were pilots and 7.2% (29/404) navigators. As for years of service, 41.6% (168/404) served less than 5 years, while 58.4% (236/404) served more than 5 years. 37.9% (153/404) had a family history of insomnia. 18.8% (76/404) did not habitually nap, 68.9% (226/328) napped for ≤30 min, 31.1% (102/328) napped over 30 min, and 18.3% (74/404) had insomnia over the past month. As for helicopter flying personnel, 75.5% (305/404) reported experiencing fatigue, with 69.1% (279/404) attributing it to flight-related factors and 51.5% (208/404) using coffee as a countermeasure.②Scale scores: the total score of PSQI was [5 (3, 7)], while the highest daytime dysfunction score was [1(0, 2)]. The total score of NASA-TLX was [39.19 (26.57, 51.97)], and the effort score was the highest [10.31(5.07, 14.60)]. The total score of MFI-20 averaged (47.28±14.88), with the mental fatigue score being the highest [(10.03±4.42)]. ③Comparisons of MFI-20 total scores: flying personnel with ≤5 years of flying experience had higher MFI-20 total scores than those with >5 years, and those with a family history of insomnia had higher scores than those without ( t=3.35, 2.44, P=0.001, 0.015). Individuals with insomnia over the past month had higher scores than non-insomniacs ( t=3.33, P=0.001). Significant differences in MFI-20 scores were observed based on nap duration ( F=19.95, P<0.001). Non-nappers had higher scores than those napping for ≤30 min ( P=0.005). Flying personnel who napped for >30 min had higher scores than those did not ( P=0.043) or napped for ≤30 min ( P<0.001). ④Correlation analysis: the total score of MFI-20 was positively correlated with sleep quality, sleep latency, sleep disturbances, hypnotic medications, daytime dysfunction, and the total score of PSQI ( r=0.118-0.226, all P<0.05), but negatively with sleep duration ( r=-0.136, P=0.006). The total score of MFI-20 was positively correlated with mental demand, physical demand, and the total score of NASA-TLX ( r=0.119, 0.168, 0.184, P=0.017, 0.001, <0.001). ⑤Multiple linear regression analysis: the determinants of flight fatigue included aircraft types ( B=-4.956, 95% CI:-8.124--1.788), nap duration ( B=3.693, 95% CI: 1.267-6.119), sleep latency ( B=2.371, 95% CI: 0.229-4.513), sleep duration ( B=-7.383, 95% CI:-10.008--4.758), daytime dysfunction ( B=5.003, 95% CI: 2.967-7.039) and physical workload ( B=0.611, 95% CI: 0.324-0.898). Conclusions:Helicopter flying personnel are vulnerable to flight fatigue, which is strongly linked to sleep quality and mental workload. It is crucial to address flying personnel′s self-perceived fatigue, care about fatigue manifestations across aircraft types, and implement targeted interventions to improve sleep quality and reduce mental workload.

Objective: Our study was aimed to construct a predictive model to advance ovarian cancer diagnosis by machine learning. Methods: A retrospective analysis of patients with pelvic/adnexal/ovarian mass was performed. Potential features related to ovarian cancer were obtained as many as possible.The optimal machine learning algorithm was selected among six candidates through 5-fold cross validation. Top 20 features having the most powerful predictive significance were ranked by Shapley Additive Interpretation (Shap) method. Clinical validation was further performed to confirm whether our model could advance diagnosis of ovarian cancer. Results: A total of 9,799 patients were collected. The inclusion criteria included age >18 years old, the first diagnosis being pelvic/adnexal/ovarian mass of undetermined significance, and pathological report indispensable. Four hundred and thirty-eight dimensional features were obtained after filtration. LightGBM showed the best performance with accuracy 88%.Among the top 20 features, 55% belonged to laboratory test report, 35% came from imaging examination report, and 10% were attributed to basic demographics and main symptom.Age, CA125, and risk of ovarian malignancy algorithm were the top three. Our predictive model performed stably in testing and clinical validation datasets, and was found to advance the diagnosis of ovarian cancer about 17 days before clinical pathological examination. Conclusion LightGBM was the optimal algorithm for our predictive model with accuracy of 88%. Laboratory test and imaging examination played essential roles in diagnosing ovarian cancer. Our model could advance the diagnosis of ovarian cancer before clinical pathological examination.

Objective: To investigate factors associated with life satisfaction among adolescents who have been relocated for poverty alleviation,so as to provide scientific evidence to support adolescent physical and mental well being. Methods: A multi stage stratified random sampling was conducted from June to August 2023 across 24 relocation sites in 8 counties of 4 cities in Shanxi Province. A total of 631 adolescents aged 10-19 were surveyed regarding personal characteristics, family environment, health behaviors, mental health, and social capital. Univariate analysis of variance and binary Logistic regression were used to explore the influencing factors. Results: The life satisfaction rate of the relocated adolescents was 63.9%(403/631), and the average score of life satisfaction was (23.21±6.28). The Logistic regression analysis showed that, significant factors affecting life satisfaction of the relocated adolescents included age (17-19 years old: AOR= 0.54 , 95%CI =0.33-0.88), subjective family economic status (moderate: AOR=1.70, 95%CI =1.04-2.76; good: AOR=6.95, 95%CI =1.85-26.16), sleep quality (good: AOR=1.61, 95%CI =1.09-2.38), depression ( AOR=0.94, 95%CI =0.90-0.99), and social capital ( AOR=1.17, 95%CI =1.10-1.23)( P <0.05). Conclusions The satisfaction of 17-19 year old adolescents who have relocated for poverty alleviation is relatively low, while those with better family economic status, high sleep quality, low depression level and rich social capital showed high life satisfaction. Targeted interventions by families, communities, schools, and social institutions are recommended to improve adolescents quality of life.

OBJECTIVE To investigate the potential therapeutic effect of the sporoderm-removed Ganoderma lucidum spore tablet "Xianzhi No.3" from the perspective of immunomodulation and cardioprotection. METHODS Chemical components of the sporoderm-removed Ganoderma lucidum spore tablet "Xianzhi No.3" were analyzed by UPLC-Q-TOF-MS and colorimetric methods. Examined tablet’s effects on zebrafish models of macrophage reduction, heart failure, H2O2-induced oxidative stress in myocardial and endothelial cells, and a microglial inflammation model induced by lipopolysaccharide. Immune regulation and cardioprotective effects were evaluated through multiple indicators, including macrophage formation and phagocytosis abilities, anti-neuroinflammation ability, cardiac systolic and diastolic functions, and anti-oxidative stress injury ability in myocardial and endothelial cells. RESULTS The sporoderm-removed Ganoderma lucidum spore tablet "Xianzhi No.3" improved macrophage formation and phagocytosis, cardiac systolic and diastolic functions, reduced neuroinflammation, and alleviated oxidative stress in myocardial and endothelial cells, resulting in immunomodulatory and cardioprotective effects. CONCLUSION The sporoderm-removed Ganoderma lucidum spore tablet "Xianzhi No.3" maybe a potential therapeutic agent for regulating the immune system and protecting cardiac function.

BACKGROUND:Scaffold materials serve as platforms that provide space and structure,playing a crucial role in the regeneration of cartilage tissue.Scholars from around the world are exploring different approaches to fabricate more ideal scaffold materials. OBJECTIVE:To review the design principles and preparation methods of cartilage scaffolds,and to further explore the advantages and limitations of various preparation methods. METHODS:Literature searches were conducted on the databases of CNKI,WanFang Data,PubMed,and FMRS from 1998 to 2023.The search terms were"cartilage repair,cartilage tissue engineering,cartilage scaffold materials,preparation"in Chinese and English.A total of 57 articles were ultimately reviewed. RESULTS AND CONCLUSION:(1)The articular cartilage has a unique structure and limited self-repair capacity after injury.Even if self-repair occurs,the newly formed cartilage is typically fibrocartilage,which is far inferior to normal articular cartilage in terms of structure and mechanical properties.It is difficult to maintain normal function and often leads to degenerative changes.Currently,the design and fabrication of scaffold materials for cartilage repair need to consider the following aspects:biocompatibility and biodegradability,suitable pore structure and porosity,appropriate mechanical properties,and bioactivity.(2)Research on the preparation of cartilage scaffolds has made significant progress,continuously introducing new preparation methods and optimization strategies.These methods have their advantages and disadvantages,providing more possibilities for customized preparation and functional design of cartilage scaffolds according to specific requirements.

BACKGROUND:Bone formation is the process by which osteoblasts synthesize and secrete osteoid and promote its mineralization,which generally involves mechanical signal transduction.Osteoblasts are primarily regulated by mechanical factors such as gravity,compressive stress,tensile stress,fluid shear stress,and hydrostatic pressure in vivo,and different mechanical stimuli modulate the proliferation,differentiation,and apoptosis of osteoblasts through various mechanisms,including hormones,cytoskeletal proteins,and microRNAs.By clarifying the effects of biomechanical forces on osteoblasts,it provides ideas and a reference basis for the treatment of osteometabolic diseases involving osteoblasts. OBJECTIVE:To review the effects of different biomechanical forces on the biological characteristics of osteoblasts. METHODS:We conducted a literature search using PubMed,Web of Science,FMRS,CNKI,and WanFang databases for relevant publications published from 2000 to 2023,covering basic research and tissue engineering studies related to the effects of biomechanical forces on osteoblasts.Ultimately,a total of 70 articles were reviewed. RESULTS AND CONCLUSION:Different biomechanical forces have an impact on the biological characteristics of osteoblasts,including proliferation,differentiation,and apoptosis,and these effects are dependent on the intensity and duration of the applied force.Specifically,the effects are as follows:(1)Under microgravity conditions,osteoblast proliferation and differentiation are inhibited,resulting in a decrease in bone density and the development of osteoporosis.(2)Compared to microgravity,hypergravity has a promoting effect on osteoblast proliferation.(3)The effects of compressive stress on osteoblasts are dependent on the loading intensity and time.Appropriate compressive stress can promote osteoblast proliferation and differentiation,which is beneficial for bone tissue formation and repair,while excessive compressive stress can cause osteoblast apoptosis and bone tissue destruction.(4)The biological effects of different types of tensile stress on osteoblasts differ.Studies have shown that a strain rate within the range of 0-12%has a promoting effect on osteoblast proliferation.(5)Fluid shear stress can promote osteoblast proliferation and differentiation and enhance the bone-inducing effect of biomaterials.(6)Static hydrostatic pressure can affect the biological behavior of osteoblasts,including proliferation,differentiation,and apoptosis,and these effects are closely related to the time and intensity of the pressure.Understanding the effects of different biomechanical forces on osteoblasts is of great significance for a deeper understanding of bone growth and maintenance mechanisms.