Objective: To explore the characteristic of obesity in adolescents with major depressive disorder and its relationship with inflammatory cytokines. Methods : One hundred and forty adolescents with major depressive disorder were enrolled. According to the classification standard of body mass index(BMI) for adolescents in China, the patients were classified into underweight group, normal group, overweight group and obese group. The center for epidemiologic studies depression scale(CES-D) was used to evaluate symptoms of depression in patients, and ultrasensitive multiplex electrochemiluminescence detection technology was used to measure the levels of plasma inflammatory cytokines including interleukin(IL)-6,IL-17A,IL-1β,IL-6,IL-8 and tumour necrosis factor(TNF)-α. One-way ANOVA or Kruskal-WallisHtest and chi-square test were used for comparison between groups. Binary Logistic regression was used to analyze the influencing factors of obesity in adolescent patients with major depressive disorder. Results : Among the 140 adolescent patients with major depressive disorder, wasting were 9.3%(13/140), overweight were 17.9%(25/140) and obesity were 6.4%(9/140) respectively. There were statistically significant differences in gender(χ2=8.301,P<0.05) and inflammatory cytokines IL-6(H=16.217,P<0.01), IL-8(H=10.926,P<0.05) and TNF-α(H=7.879,P<0.05) among the four groups. Analysis of covariance showed that the difference in levels of the inflammatory cytokine IL-6(F=4.486,P<0.01) remained statistically significant after controlling for age, gender and antidepressant use. The results of multiple comparisons showed that compared with the wasting group, the plasma IL-6(Z=-3.843,PBonferroni calibrate<0.01) were higher in the obese group; compared with the normal group, the obesity rate of males was higher than that of females(χ2=8.812,PBonferroni calibrate<0.01), and the level of IL-6 in the obese group(Z=-3.023,PBonferroni calibrate<0.05) was higher. Binary Logistic regression analysis showed that plasma IL-6(OR=2.500,P<0.01) and gender(OR=11.292,P<0.01) were independent influencing factors for obesity in patients with adolescent depressive disorders. Conclusion There are gender differences in obesity rates in adolescents with depressive disorders, and obesity is associated with elevated levels of inflammatory cytokines.

ObjectiveThe biosynthetic pathways of benzylisoquinoline alkaloids（BIAs） in Nelumbo nucifera are of great theoretical and economic value. In this paper， N. nucifera O-methyltransferase（NnOMT） and N. nucifera N-methyltransferase（NnNMT） gene families were identified and analyzed by bioinformatics in order to facilitate the biosynthetic pathway of BIAs in N. nucifera. MethodBased on the whole genome of N. nucifera， UniPort and National Center for Biotechnology Information（NCBI） databases were used to identify the NnOMT and NnNMT gene families of N. nucifera， and analyze their physicochemical properties and subcellular localization， then TBtools， MEME， MEGA 11.0， FigTree 1.4.4 and other tools were used to analyze the phylogeny， sequence characteristics， gene structure， functional annotation and cis-acting elements of NnOMT and NnNMT genes identified in the previous stage. ResultA total of 61 NnOMT and NnNMT genes were identified in this paper， the number of amino acids encoded by these genes ranged from 168 aa to 580 aa， the isoelectric point ranged from 4.76 to 9.16， and the relative molecular weight ranged from 18 699.52 Da to 64 934.53 Da， most of which showed acidic and mostly hydrophilic proteins. There were 10 conserved motifs， Kyoto Encyclopedia of Genes and Genomes（KEGG） analysis enriched a total of 12 pathways， including metabolism， biosynthesis of phenylpropane and isoquinoline alkaloids， etc. And Visualization of Gene Ontology（GO） enrichment results showed that 61 NnOMT and NnNMT genes were annotated to 32 items， which included 16 molecular functions［such as reduced nicotinamide adenine dinucleotide（NADH） activity and exopeptidase activity］ and 16 biological processes（such as metabolic process of carbon tetrachloride， anaerobic carbon tetrachloride metabolic process and responses to exogenous biological stimuli）. There were a variety of cis-acting elements in the promoter regions of NnOMT and NnNMT genes， mainly promoter and enhancer regions element， light responsive element and methyl jasmonate responsive element. ConclusionIn this study， a comprehensive bioinformatics analysis of 61 NnOMT and NnNMT genes is carried out based on the genome data of N. nucifera， which lays a foundation for research on the gene structure and function of NnOMT and NnNMT gene families， and provides a reference for biosynthetic pathway elucidation of BIAs in N. nucifera.

BackgroundPatients demonstrating depressive disorder with psychotic symptoms often have increased risk of death and poor prognosis. A large amount of research has explored the factors influencing psychotic symptoms in adult patients with depressive disorder， but few has focused on adolescent patients. ObjectiveTo explore the influencing factors of psychotic symptoms in adolescent patients with depressive disorder， so as to provide references for early screening and intervention in clinic. MethodsA total of 96 adolescent patients who met the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） for depressive disorder and were seen in the psychiatry departments of Chaohu Hospital of Anhui Medical University and The Fourth People's Hospital of Hefei from September 2022 to January 2023 were included. Another 56 healthy individuals from the health examination center of Chaohu Hospital of Anhui Medical University were concurrently recruited as control group. Patients were assigned into psychotic group （n=32） and non-psychotic group （n=64） according to the presence or absence of psychotic symptoms. Hamilton Depression Scale-24 item （HAMD-24）， Positive and Negative Syndrome Scale （PANSS）， Positive and Negative Suicide Ideation （PANSI） and Childhood Trauma Questionnaire-Short Form （CTQ-SF） were used for evaluation. Plasma brain-derived neurotrophic factor （BDNF） concentration was obtained using Meso Scale Discovery electrochemiluminescence assay. Pearson and Spearman correlation analysis were adopted to determine the correlation of PANSS positive symptom subscale score with plasma BDNF concentration and clinical characteristics of adolescent depression patients with psychotic symptoms. Binary Logistic regression analysis was used to identify the factors influencing the presence of psychotic symptoms in adolescent patients with depressive disorder， and multiple linear regression analysis was utilized to screen the factors affecting the severity of psychotic symptoms. ResultsThe plasma BDNF concentration of adolescent patients with depressive disorder was lower than that of control group （t=-3.080， P<0.01）.The plasma BDNF concentration of psychotic group was lower than that of non-psychotic group （t=2.418， P<0.05）， while the body mass index （BMI） PANSI scores， CTQ-SF scores and HAMD-24 total scores were all higher than those of non-psychotic group （t=-2.024， -2.530， -2.187， -4.977， P<0.05 or 0.01）. Correlation analysis showed that PANSS positive symptom subscale scores were negatively correlated with anxiety/somatization factor score and weight factor score in HAMD-24 of psychotic group （r=-0.438， -0.498， P<0.05 or 0.01）. Binary Logistic regression showed that BMI， plasma BDNF concentration， HAMD-24 total scores and cognitive dysfunction factor score were the influencing factors of psychotic symptoms in adolescent patients with depressive disorder. Multiple linear regression analysis demonstrated that weight factor scores （β=-0.349， P<0.05） and anxiety/somatization factor score （β=-0.433， P<0.05） in HAMD-24 were the factors influencing the severity of psychotic symptoms. ConclusionHigh BMI， low plasma BDNF concentration， severe depressive symptoms and cognitive dysfunction may be the risk factors of psychotic symptoms in adolescent patients with depressive disorder， furthermore， BMI and anxiety symptoms are found to be associated with the severity of psychotic symptoms. ［Funded by Scientific Research Fund Project of Anhui Institute of Translational Medicine （number， 2022zhyx-B01）； Central Finance Supported Provincial Key Clinical Specialty Construction Project of Anhui Province in 2019］