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Objective:To analyze the influencing factors for depression in primary school children aged 9-10 years in Jiangsu Province, and to construct a risk prediction model.Methods:A retrospective study.A total of 1 162 primary school children aged 9-10 years from 3 primary schools in 3 regions of Jiangsu Province were recruited.Their demographic data were collected, and they were surveyed by the Depression Anxiety Stress Scales-21 (DASS-21), the Strengths and Difficulties Questionnaire (SDQ), and the Family Environment Scale (FES). Children were divided into control group (1 059 cases) and depression group (103 cases) based on the depression scores obtained from the DASS-21 scale.Multivariate Logistic regression analysis was used to analyze the influencing factors for depression in primary school students aged 9-10 and construct a risk prediction model. Results:There were significant differences in the economic development region, physical activities, academic performance, student cadres, parents′ education level, frequency of parental quarrels, SDQ and FES dimension scores between control group and depression group (all P<0.05). Among them, economic development areas (Northern Jiangsu and Southern Jiangsu), student cadres, father′s education level (elementary school and below) and intimacy of the FES scale were protective factors for depression in elementary school children; while emotional symptoms, peer problems and the total difficulty score in the SDQ scale, and the conflict in the FES scale were the risk factors for depression in elementary school children.The prediction model was created based on the influencing factors: Logit ( P)=-1.390×economic development area (Northern Jiangsu) -1.508×economic development area (Southern Jiangsu) -1.248×student cadres -2.206×father′s education level (primary school and below) -1.145×father′s education level (junior high school)+ 3.316×emotional symptoms in the SDQ+ 0.979×peer problems in the SDQ+ 2.520×total difficulty score in the SDQ -1.697×cohesion in the FES + 0.760×conflict in the FES -0.678.The area under the curve of receiver operating characteristic was 0.931, with the sensitivity and specificity of 85.42% and 91.83%, respectively. Conclusions:The regional level of economic development, class or school cadres, father′s education level, peer problems, total difficulty score, cohesion and conflict in the family are influencing factors for depression among primary school children aged 9-10 years in Jiangsu Province.The created prediction model can effectively assess the depressive risk factors in this population, which is conductive to achieve the early recognition and intervention of depression in them.
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Objective:To explore the speech features of female patients with anhedonic depression and their recognition of pleasure deficient symptoms.Methods:A total of 102 female depression patients who were hospitalized at Nanjing Brain Hospital from September 2020 to October 2021 were selected, including 62 anhedonic depression patients (anhedonic group) and 40 non-anhedonic depression patients (non-anhedonic group). A total of 50 female healthy controls were recruited during the same period.All participants were evaluated by the 17-item Hamilton depression scale (HAMD-17), Snaith-Hamilton pleasure scale (SHAPS), and the temporal experience of pleasure scale (TEPS), as well as voice acquisition.SPSS 23.0 software was used for data processing.Statistical analysis was conducted using one-way ANOVA, non-parametric tests, Logistic regression, and receiver operating characteristic curve.Results:Compared with the non-anhedonic group, the anhedonic group showed significant changes in 15 voice features(all P<0.05), including Mel-frequency cepstral coefficients, formant frequencies, intensity, and energy features.Among these features, Mel-frequency cepstral coefficients exhibited the highest accuracy in identifying anhedonic depression, with sensitivity of 47.5%, specificity of 91.9%, area under curve (AUC) of 0.751, 95% CI=0.686-0.866.Formant frequencies could identify female anhedonic depression, with a sensitivity of 90.0%, a specificity of 40.3%, an AUC of 0.647, and 95% CI=0.605-0.824.Energy features could identify anhedonic deficient depression, with a sensitivity of 60.0%, a specificity of 74.2%, an AUC of 0.679, and 95% CI=0.587-0.804.Intensity features could identify female anhedonic depression, with a sensitivity of 70.0%, a specificity of 58.1%, an AUC of 0.640, and 95% CI=0.554-0.769. Conclusion:Mel-frequency cepstral coefficients, formant frequencies, intensity features, and energy features may have specific changes in female patients with anhedonic depression.The Mel-frequency cepstral coefficients has the highest recognition accuracy for anhedonic symptoms in female depression patients, and is expected to become an objective evaluation index for female anhedonic depression.
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ZNF804A rs1344706 has been identified as one of the risk genes for schizophrenia. However, the neural mechanisms underlying this association are unknown. Given that ZNF804A upregulates the expression of COMT, we hypothesized that ZNF804A may influence brain activity by interacting with COMT. Here, we genotyped ZNF804A rs1344706 and COMT rs4680 in 218 healthy Chinese participants. Amplitudes of low-frequency fluctuations (ALFFs) were applied to analyze the main and interaction effects of ZNF804A rs1344706 and COMT rs4680. The ALFFs of the bilateral dorsolateral prefrontal cortex showed a significant ZNF804A rs1344706 × COMT rs4680 interaction, manifesting as a U-shaped modulation, presumably by dopamine signaling. Significant main effects were also found. These findings suggest that ZNF804A affects the resting-state functional activation by interacting with COMT, and may improve our understanding of the neurobiological effects of ZNF804A and its association with schizophrenia.
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Objective To investigate gender differences of plasma glial cell line-derived neurotro-phic factor (GDNF) levels in patients with major depressive disorder (MDD). Methods MDD subjects (male 20,female 36) and healthy controls (HCs) (male 35,female 45) were divided into four groups by gender. Plasma levels of GDNF were measured and compared in different gender groups. The clinical symp-tom severity of MDD patients was evaluated by 17-item Hamilton Depression Scale (HAMD-17) and Hamil-ton Anxiety Scale (HAMA-17). Results (1)The plasma GDNF level in male patients with major depres-sive disorder (( 1. 55 ± 0. 43 ) pg/ml ) was significantly lower than that in healthy controls (( 1. 86 ± 0. 50)pg/ml,F=4. 64,P=0. 036). There was no significant difference in GDNF level between female de-pression patients((1.62±0.46)pg/ml)) and female healthy control((1. 64±0. 48)pg/ml,F=0. 18,P=0. 672). In HCs,the GDNF level of male was significantly higher than that of female((1. 86±0. 50)pg/ml, (1. 64±0. 48)pg/ml,F=2. 04,P=0. 045). There was no significant difference in GDNF level between male and female patients(P>0. 05). (2) GDNF level in male patients with major depressive disorder was nega-tively correlated with HAMA score(r=-0. 388,P=0. 034). Conclusion The expression of GDNF is affect-ed by sex factors,which may be related to the different pathogenesis of MDD.
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Objective To discuss the difference of handwriting characteristics of schizophrenia,neurosis and healthy people according to the gender,the age and the level of educated.Methods The handwriting data were obtained under the standard condition of handwriting,then the 24 Chinese characters handwriting image information were transformed into digital data using the quantitative characteristics of Chinese characters handwriting recognition system (CCQAS4.0),finally the data of 99 patients with schizophrenia and 131 patients with neurosis were analyzed.Results Many significant differences had been found in schizophrenia,neurosis and norm group (P ＜0.05,P＜0.01),such as footer space((198.33±26.50) mm,(180.31±39.31)mm,(192.39±35.08) mm),average line spacing ((4.02 ± 1.68) mm,(5.34 ± 2.20) mm,(4.76 ± 2.00) mm) etc ; and there were also some important differences between the schizophrenia patient and the neurosis patient from different gender,age and education level in the 24 handwriting characteristics (P＜0.05,P＜0.01).Conclusions (1) Significant handwriting characteristic differences have surely been found among the schizophrenia/neurosis patient and normal people.(2) Gender,age and education level have impact on the characteristic in the schizophrenia patient and the neurosis patient.