Objective To investigate the current status of family resilience of children with cancer and analyze its influencing factors,to provide a basis for medical staff to formulate intervention plans.Methods Using a convenient sampling method,children with cancer who were hospitalized in 2 tertiary hospitals in Henan Province from January to April 2024 were selected for the survey.A general information questionnaire,family resilience assessment scale,quality of life family version,ZBI caregiver burden interview,and social support rating scale were used to understand the current status of family resilience of children with cancer and to explore the related influencing factors by univariate analysis and multiple stepwise linear regression analysis.Results A total of 280 questionnaires were distributed and 265 valid questionnaires were recovered,with a valid questionnaire recovery rate of 94.64％.The total score of family resilience for primary caregivers of children with cancer was(185.63±30.66).The multiple stepwise linear regression analysis results showed that the children's self-care ability,caregiver's work status,family care burden,and social support level were the influencing factors for family resilience of children with cancer(P＜0.05),and the explanatory variance was 51.3％.Conclusion The family resilience of children with cancer is at a medium level.The worse the children's self-care ability and the heavier the family care burden,the worse the family resilience;the caregiver's work status and good social support are helpful for the family resilience of children with cancer.Healthcare workers should develop intervention programs to address these factors to enhance the family resilience of children with cancer.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective To explore the potential categories of health risk behaviors among students aged 11 to 18 years in Minhang District,Shanghai in order to identify the influencing factors of health risk behaviors among different categories of students.Methods Using stratified cluster sampling techniques,a random selection of 1 690 middle school students from Minhang District,Shanghai,were chosen as the study sample.Data was collected using the"Shanghai Adolescent Health-Related Behavior Survey Questionnaire"to assess participants'scores on six categories of health risk behaviors.Latent profile analysis(LPA)was employed to cluster students'health risk behaviors,and a multifactorial Logistic regression model was used to analyze the related influencing factors.Results The health risk behaviors of students aged 11 to 18 in Minhang District,Shanghai,were categorized into 3 groups:Class 1,comprising 915 students(54.14%),with moderate to low scores in health risk behaviors,named"the group with moderately low levels of various health risk behaviors";Class 2,comprising 539 students(31.89%),with higher scores in psychological addiction,named"the group with psychological addiction as the prominent health risk behavior";Class 3,comprising 236 students(13.97%),with higher scores in substance addiction,named"the group with substance addiction as the prominent health risk behavior".The results of the univariate analysis for the three potential categories of student health risk behaviors show that there are statistically significant differences in the 3 potential categories of health risk behaviors among students of different schools,ages,ethnicities,and boarding situations(P<0.05).The analysis results of the multivariate Logistic regression indicate that compared to junior high school students,both senior high school students and vocational high school students have a higher risk of exhibiting unhealthy behaviors characterized by psychological addiction and substance addiction,with all differences being statistically significant(P<0.05).Conclusion The latent profile analysis reveals three distinct categories of health risk behaviors among students aged 11 to 18 years in Minhang District,Shanghai,with significant distribution differences among students from diverse backgrounds.Consequently,it is recommended that tailored health education and intervention measures be implemented for students with different school characteristics and at various educational stages.

AIM:To establish a cell model of visceral hypersensitivity and nerve hyperplasia in irritable bowel syndrome(IBS)by conducting an in vitro co-culture of mouse P815 mast cells and N2a nerve cells and explore its possible mechanism.METHODS:Enzyme-linked immunosorbent assay(ELISA)with three replicates was used to confirm the C48/80-induced P815 degranulation.The length of neurites was observed under bright field microscopy to determine the number of differentiated neurons,thereby selecting the concentration of retinoic acid(RA)for stimulating the differentia-tion of N2a cells,with four replicates.A co-culture system of P815 and N2a cells was established using Transwell cham-bers with four replicates.The following groups were established:N2a cells cultured alone,N2a cells co-cultured with P815 cells,N2a cells co-cultured with P815 cells plus C48/80,and N2a cells plus RA group.After co-culturing,the num-ber of differentiated N2a cells was observed under bright field.The expression of nerve growth factor(NGF),tyrosine ki-nase receptor A(TRKA),growth-associated protein-43(GAP43),neuron-specific enolase(NSE),synapsin(SYN),and postsynaptic density protein-95(PSD-95)at both protein and gene levels in N2a cells was detected using Western blot and polymerase chain reaction(PCR),with four replicates.RESULTS:The best condition for N2a differentiation was stimulation with 10 μmol/L RA for 24 hours,whereas the best condition for degranulation was stimulation of P815 cells with 20 mg/L C48/80 for 24 hours.Compared with N2a cells cultured alone,the differentiation ratio of the N2a+P815+C48/80 and N2a+RA groups was significantly increased(P<0.01),and the protein and mRNA expressions of NGF,TRKA,GAP43,NSE,SYN,and PSD-95 were significantly increased(P<0.05).CONCLUSION:Our results revealed that mast cell degranulation enhances the level of nerve hyperplasia in enteric nerve cells and promotes changes in nerve structure and function.Synaptic remodeling regulated by abnormal expression of key proteins such as NGF,TRKA,and GAP43 is involved in the nerve hyperplasia induced by mast cell degranulation.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Objective:To investigate the effects of moxibustion,filiform needle acupuncture,and electroacupuncture on synovial hypoxia and expression of synovial fibrosis markers[transforming growth factor(TGF)-β and collagen alpha-1(Ⅰ)chain(COL1A1)]in knee osteoarthritis(KOA)rats.Methods:Fifty Sprague-Dawley rats were randomly divided into a normal group,a model group,a moxibustion group,an acupuncture group,and an electroacupuncture group,with 10 rats in each group.Except for the normal group,rats in the other four groups were injected with sodium iodoacetate into the right knee joint cavity to establish KOA models.The right Futu(ST32)and Zusanli(ST36)were selected in the moxibustion,acupuncture,and electroacupuncture groups to perform the mild moxibustion with moxa sticks,filiform needle acupuncture,or electroacupuncture,respectively.Each intervention lasted 15 min,once every other day,and continued for 4 weeks,with a total of 14 interventions.The Lequesne score was used to evaluate the degree of knee dysfunction before and after intervention,and the rat's right knee joint diameter was measured to evaluate the degree of knee swelling.Morphological changes of the right knee joint synovial tissue were observed using hematoxylin-eosin staining.Hypoxia probe immunofluorescence staining was used to observe the degree of synovial hypoxia in rats.Western blotting was used to detect the protein expression levels of hypoxia-inducible factor(HIF)-1α,TGF-β,and COL1A1 in the synovial tissue of the right knee joints.Results:Before intervention,the Lequesne score and the right knee joint diameter in the other four groups increased significantly compared to the normal group(P<0.01).After intervention,the Lequesne score and the right knee joint diameter increased significantly in the model group compared to the normal group(P<0.01)together with worsened cartilage deformation and osteophytes,inflammatory cell infiltration and fibrosis in synovial tissue,and hypoxia degree,and the expression levels of HIF-1α,TGF-β,and COL1A1 proteins in the knee joint synovial tissue of rats increased(P<0.01).The Lequesne score and the right knee joint diameter decreased significantly(P<0.01 or P<0.05),the cartilage morphology was normal without obvious osteophytes,and the hypoxia degree reduced in the three intervention groups compared to the model group.Among them,the moxibustion group had the most notable improvement in hypoxia,synovial tissue fibrosis,angiogenesis,and inflammatory cell infiltration.The expression levels of HIF-1α,TGF-β,and COL1A1 proteins decreased in the moxibustion and electroacupuncture groups(P<0.01),and the expression levels of HIF-1α and TGF-β proteins were decreased in the acupuncture group(P<0.01).Conclusion:Moxibustion,filiform needle acupuncture,and electroacupuncture improve knee joint function and reduce knee joint swelling in KOA rats.The mechanism may be to improve synovial fibrosis of the knee joint by regulating HIF-1α;moxibustion has the best effect on improving hypoxia among the three interventions,but the effect of filiform needle acupuncture on COL1A1 is not significant.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Objective To investigate the current status of family resilience of children with cancer and analyze its influencing factors,to provide a basis for medical staff to formulate intervention plans.Methods Using a convenient sampling method,children with cancer who were hospitalized in 2 tertiary hospitals in Henan Province from January to April 2024 were selected for the survey.A general information questionnaire,family resilience assessment scale,quality of life family version,ZBI caregiver burden interview,and social support rating scale were used to understand the current status of family resilience of children with cancer and to explore the related influencing factors by univariate analysis and multiple stepwise linear regression analysis.Results A total of 280 questionnaires were distributed and 265 valid questionnaires were recovered,with a valid questionnaire recovery rate of 94.64％.The total score of family resilience for primary caregivers of children with cancer was(185.63±30.66).The multiple stepwise linear regression analysis results showed that the children's self-care ability,caregiver's work status,family care burden,and social support level were the influencing factors for family resilience of children with cancer(P＜0.05),and the explanatory variance was 51.3％.Conclusion The family resilience of children with cancer is at a medium level.The worse the children's self-care ability and the heavier the family care burden,the worse the family resilience;the caregiver's work status and good social support are helpful for the family resilience of children with cancer.Healthcare workers should develop intervention programs to address these factors to enhance the family resilience of children with cancer.

Objective To explore the potential categories of health risk behaviors among students aged 11 to 18 years in Minhang District,Shanghai in order to identify the influencing factors of health risk behaviors among different categories of students.Methods Using stratified cluster sampling techniques,a random selection of 1 690 middle school students from Minhang District,Shanghai,were chosen as the study sample.Data was collected using the"Shanghai Adolescent Health-Related Behavior Survey Questionnaire"to assess participants'scores on six categories of health risk behaviors.Latent profile analysis(LPA)was employed to cluster students'health risk behaviors,and a multifactorial Logistic regression model was used to analyze the related influencing factors.Results The health risk behaviors of students aged 11 to 18 in Minhang District,Shanghai,were categorized into 3 groups:Class 1,comprising 915 students(54.14%),with moderate to low scores in health risk behaviors,named"the group with moderately low levels of various health risk behaviors";Class 2,comprising 539 students(31.89%),with higher scores in psychological addiction,named"the group with psychological addiction as the prominent health risk behavior";Class 3,comprising 236 students(13.97%),with higher scores in substance addiction,named"the group with substance addiction as the prominent health risk behavior".The results of the univariate analysis for the three potential categories of student health risk behaviors show that there are statistically significant differences in the 3 potential categories of health risk behaviors among students of different schools,ages,ethnicities,and boarding situations(P<0.05).The analysis results of the multivariate Logistic regression indicate that compared to junior high school students,both senior high school students and vocational high school students have a higher risk of exhibiting unhealthy behaviors characterized by psychological addiction and substance addiction,with all differences being statistically significant(P<0.05).Conclusion The latent profile analysis reveals three distinct categories of health risk behaviors among students aged 11 to 18 years in Minhang District,Shanghai,with significant distribution differences among students from diverse backgrounds.Consequently,it is recommended that tailored health education and intervention measures be implemented for students with different school characteristics and at various educational stages.