Objective:To explore the abnormal patterns of brain functional network connectivity in depression adolescents and their diagnostic value in adolescent depression.Methods:A total of 94 depression adolescents (adolescent depression group) admitted to Outpatient Department of Psychiatric Imaging, West China Hospital, Sichuan University from January 2020 to December 2022 were selected. In addition, 78 age- and gender-matched healthy adolescents were recruited from local community advertisements at the same time-period as healthy control group. Resting-state functional magnetic resonance imaging was performed; after image preprocessing, group-level spatial independent component analysis was performed to identify the intrinsic network connectivity, and differences in network connectivity between the two groups were compared. Functional connectivity edges were employed as classification features, and feature ranking and screening were then performed. A support vector machine (SVM) with linear kernel function was used to construct a classification model, and receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of this classification model in adolescent depression.Results:No significant difference was noted in age, gender, years of education, and body mass index between the two groups ( P>0.05). Compared with the healthy control group, the adolescent depression group had significantly decreased functional connectivity intensity within and between the networks of sensorimotor network (SMN), visual network (VN), auditory network (AN), default mode network (DMN), and cognitive control network (CCN), and significantly increased functional connectivity intensity within CCN ( P<0.05). When using the 75 top-ranked functional connectivity features, this classification model had the best performance (accuracy rate: 70.35%, sensitivity: 70.21%, specificity: 71.80%, P<0.001). ROC curve showed that area under the curve of this classification model in diagnosing adolescent depression was 0.724 (95% CI: 0.648-0.800, P<0.001). A total of 51 consistent functional connectivities were identified and they were mainly located within or between the networks of SMN, VN, AN, DMN, and CCN. Conclusion:The abnormal resting-state brain functional connectivity in depression adolescents can provide imaging basis for their clinical diagnosis.

Objective:To explore the abnormal patterns of brain functional network connectivity in depression adolescents and their diagnostic value in adolescent depression.Methods:A total of 94 depression adolescents (adolescent depression group) admitted to Outpatient Department of Psychiatric Imaging, West China Hospital, Sichuan University from January 2020 to December 2022 were selected. In addition, 78 age- and gender-matched healthy adolescents were recruited from local community advertisements at the same time-period as healthy control group. Resting-state functional magnetic resonance imaging was performed; after image preprocessing, group-level spatial independent component analysis was performed to identify the intrinsic network connectivity, and differences in network connectivity between the two groups were compared. Functional connectivity edges were employed as classification features, and feature ranking and screening were then performed. A support vector machine (SVM) with linear kernel function was used to construct a classification model, and receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of this classification model in adolescent depression.Results:No significant difference was noted in age, gender, years of education, and body mass index between the two groups ( P>0.05). Compared with the healthy control group, the adolescent depression group had significantly decreased functional connectivity intensity within and between the networks of sensorimotor network (SMN), visual network (VN), auditory network (AN), default mode network (DMN), and cognitive control network (CCN), and significantly increased functional connectivity intensity within CCN ( P<0.05). When using the 75 top-ranked functional connectivity features, this classification model had the best performance (accuracy rate: 70.35%, sensitivity: 70.21%, specificity: 71.80%, P<0.001). ROC curve showed that area under the curve of this classification model in diagnosing adolescent depression was 0.724 (95% CI: 0.648-0.800, P<0.001). A total of 51 consistent functional connectivities were identified and they were mainly located within or between the networks of SMN, VN, AN, DMN, and CCN. Conclusion:The abnormal resting-state brain functional connectivity in depression adolescents can provide imaging basis for their clinical diagnosis.

Purpose To elucidate the clinicopathological characteristics of primary malignant giant cell tumor of bone(PMGCTB)with mainly osteosarcoma-like morphology.Meth-ods Clinicopathologic features of 7 cases of PMGCTB were ret-rospectively analyzed.Results Among 7 patients with PMGCTB,there were 4 females and 3 males,aged between 9 and 66 years(mean age 39.5 years,median age 35 years).The distal femur emerged as the most frequent site to be involved(3/6).The main clinical manifestations included pain and swelling at the original site of the tumor.Radiological findings indicated osteolytic lesions,often combined with sclerotic areas;most ca-ses showed cortical bone destruction and soft tissue masses(5/7).Histologically,the majority of tumors exhibited typical mor-phological features of osteosarcoma with a few or without osteo-clast-like multinucleated giant cells.Positive immunoreaction with H3F3A G34W was confirmed in 6 cases and with H3F3A G34V in 1 case.SATB2 and p63 were positive in all cases,p53 was proved to be wild type,the Ki67 proliferation index ranged approximately from 10％to 50％.H3F3A p.G34W mutation was detected in 6 cases and only 1 case harboring H3F3A p.G34V mutation.Conclusion PMGCTB is exceedingly rare and difficult for accurate diagnosis,especially for those with atypical morphological features.A comprehensive analysis involving ra-diological,immunophenotypic,and molecular detection is neces-sary to rule out other high-grade sarcomas.

Good sleep is essential for children′s physical and mental health, growth, and development.Adequate and high-quality sleep positively impacts children′s quality of life, memory, learning, attention, mood, and behavior.Children of different ages have different sleep needs.Children have various sleep problems in different cultures.Therefore, it is significant to guide children to get healthy sleep by popularizing the sleep problems of Chinese children of all ages and in all dimensions.Based on China′s social and cultural background, this paper summarizes the contents related to children′s sleep physiology, good sleep habits, common sleep problems, sleep apnea disorders, hypnagogic sleep, narcolepsy, insomnia, and other issues that interfere with children′s sleep.Chinese sleep experts summarize and interpret the 100 sleep health problems of children that medical workers and parents are most concerned about.To promote children′s sleep health and popularize solutions to sleep problems.

Objective To explore the changes of insula function integration in patients with chronic insomnia (CI) using functional connectivity (FC) analysis in resting-state fMRI. Methods Totally 22 patients with CI (CI group) and 23 healthy volunteers (control group) underwent resting-state fMRI. The templates based on Chinese brains (Chinese2020) were used for spatial standardization. The bilateral insulae were selected as ROIs, and FC analysis was performed with other voxels to obtain brain regions with abnormal FC between the two groups. Correlation analysis was performed between the brain regions with abnormal FC and clinical parameters. Results Compared with control group, the increased FC brain regions with right insula in CI group included bilateral hippocampus, bilateral parahippocampus, bilateral frontal middle gyrus, right temporal middle gyrus, right precentral gyrus, left temporal inferior gyrus, left fusiform gyrus and left posterior lobe of cerebellum (all P<0.05, number of voxel cluster ≥10, AlphaSim correction), while the increased FC brain regions with left insula in CI group included bilateral hippocampus, bilateral parahippocampus, left fusiform gyrus, left temporal inferior gyrus, left posterior lobe of cerebellum and right anterior lobe of cerebellum (all P<0.05, number of voxel cluster ≥10, AlphaSim correction). Correlation analysis showed the scores of instantaneous memory in CI group were positively correlated with FC of the right insula-right hippocampus, right insula-left hippocampus, left insula-right hippocampus and left insula-left hippocampus (r=0.580, 0.668, 0.454, 0.562, all P<0.05). Conclusion FC is abnormal between the bilateral insulae and multiple brain regions in CI patients, therefore providing neuroimaging evidence for understanding emotional regulation, cognitive impairment, daytime dysfunction and impaired memory mechanisms in CI.

Objective To explore the changes of brain functional network in insomnia disorder (ID) during resting-state with voxel-based degree centrality (DC).Methods Forty-five subjects underwent resting-state fMRI scans,including 22 patients with ID (ID group) and 23 sex-,age-,and education-matched healthy volunteers (control group).The subjects' sleep quality and emotion state were assessed with Pittsburgh sleep quality index (PSQI),Hamilton anxiety scale and Hamilton depression scale.The resting-state fMRI data were analyzed with voxel-based DC.The intra-and inter-groups parameters were compared using t-test.Correlation analysis was performed between DC values of ID group and clinical parameters.Results Compared with control group,DC values increased in left parahippocampal gyrus,left hippocampus and bilateral precuneus (all P＜0.05),while decreased in left middle occipital lobe,left precuneus,left inferior frontal gyrus and left middle frontal gyrus in ID group (all P＜0.05).DC values of the left hippocampus in ID patients showed significantly negative correlation with the score of Pittsburgh sleep quality index (r=-0.46,P=0.047).Conclusion ID patients have abnormal DC distribution of brain functional network,therefore providing basis for understanding pathophysiological mechanisms of ID.

Objective To compare the ischemia-modified albumin(IMA)level between T2DM and AMI,and to discuss the possible mechanism and pathology process.Methods According to the decrease of power of albumin binding cobalt along with the increase of ischemia-modified albumin,the automated continuous detection of free cobalt in reactive system were conducted using the 480nm wavelength and the results were reported as absorbance unit(ABSU)and coloration rate of free cobalt.Results There were significant differences in serum free cobalt between the control and groups of acute coronary syndrome(ACS)and type 2 diabetes and between ACS and type 2 diabetes(P