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Deep learning models, characterized by their complex network layers, have demonstrated significant utility in the recognition and classification of ethnic artworks, particularly excelling in emotion recognition within such works. This study delves into the convolutional neural network (CNN) model underpinned by deep learning algorithms. The architecture of the model—encompassing the convolutional layer, pooling layer, fully connected layer, and activation layer—is meticulously constructed to extract emotional features from ethnic artworks. Subsequently, an activation function is employed to visualize these features, followed by the integration of emotional knowledge to optimize the network structure. The training of the model utilizes both the loss function and optimization function to enhance performance. The efficacy of the sentiment analysis is assessed through simulation experiments and practical applications, highlighting the model’s superior capability in identifying negative emotions such as Fear and Anger, achieving accuracies that are 0.101 and 0.137 higher, respectively, than those of the benchmark model. Additionally, a detailed analysis of the emotion scores of ethnic artworks reveals intriguing findings. Notably, Jiye Li’s “Four Seasons of Essays” registers the highest positive mean emotional score of 4.1026, with an overall mean of 3.5392, indicating a predominantly positive emotional response. Across the works of nine subjects analyzed, the aggregate mean emotional score stands at 1.0123, suggesting a generally positive emotional tone. This research underscores the nuanced capability of CNNs in the domain of emotional recognition in ethnic art, offering insights into both methodological advancements and interpretive analyses.

Background Considerable evidence suggests that people with depressive disorder are at higher risk for somatic symptoms than normal people, but the mechanisms of susceptibility are unclear. Some studies suggest that the levels of precursor of brain-derived neurotrophic factor (ProBDNF) and inflammatory cytokines in depressive disorder patients are higher, but it is still unclear whether this is related to the accompanying somatic symptoms. Objective To explore the characteristics of somatic symptoms, and their correlations with BDNF and inflammatory cytokines in patients with major depressive disorder (MDD) . Methods A total of 59 MDD outpatients and inpatients from Mental Health Department, First Hospital of Shanxi Medical University and 32 healthy volunteers from the community were recruited from February 2019 to December 2020. Somatic symptoms were diagnosed using the Somatic Self-rating Scale (SSS, SSS score >36 and SSS score ≤36 were defined as with somatic symptoms or without, respectively) . Depression was assessed using the Hamilton Depression Rating Scale (HAMD-17) . Clinical data were collected, including gender, age, years of education, HAMD-17 score, SSS score, absorbance of ProBDNF and BDNF, and inflammatory cytokines (CRP, IL-4, IL-10, IL-18, IL-23a, HMGB1, IL-6, TNF-α, IFN-α) . Spearman's rank correlation analysis was used to investigate the correlation of somatic symptoms (including dizziness and headache, frequent and urgency of urination, cardiovascular symptoms, muscle soreness, gastrointestinal symptoms, tingling and twitching of hands and feet, choking and sighing, blurred vision, and discomfort of the throat) , SSS-S factor score and HAMD-17 score with ProBDNF and BDNF, and inflammatory cytokines. Results MDD patients with somatic symptoms had higher total HAMD-17 score than those without (P

Coniochaeta species are versatile ascomycetes that have great capacity to deconstruct lignocellulose. Here, we explore the transcriptome of Coniochaeta sp. strain 2T2.1 from wheat straw-driven cultures with the fungus growing alone or as a member of a synthetic microbial consortium with Sphingobacterium multivorum w15 and Citrobacter freundii so4. The differential expression profiles of carbohydrate-active enzymes indicated an onset of (hemi)cellulose degradation by 2T2.1 during the initial 24 hours of incubation. Within the tripartite consortium, 63 transcripts of strain 2T2.1 were differentially expressed at this time point. The presence of the two bacteria significantly upregulated the expression of one galactose oxidase, one GH79-like enzyme, one multidrug transporter, one laccase-like protein (AA1 family) and two bilirubin oxidases, suggesting that inter-kingdom interactions (e.g. amensalism) take place within this microbial consortium. Overexpression of multicopper oxidases indicated that strain 2T2.1 may be involved in lignin depolymerization (a trait of enzymatic synergism), while S. multivorum and C. freundii have the metabolic potential to deconstruct arabinoxylan. Under the conditions applied, 2T2.1 appears to be a better degrader of wheat straw when the two bacteria are absent. This conclusion is supported by the observed suppression of its (hemi)cellulolytic arsenal and lower degradation percentages within the microbial consortium.

Background There are many subtypes of major depressive disorder (MDD) . Evidence about the differentiation of them is mostly based on symptomatological characteristics, but rarely by objective biological indicators. Objective To explore the differences in event-related potential (ERP) N400 between patients with different subtypes of depression, providing an objective electrophysiological basis for subtyping depression. Methods Two hundred and nine outpatients and inpatients who met the diagnostic criteria of MDD in Diagnostic and Statistical Manual of Mental Disorders, 5th Edition were selected from First Hospital of Shanxi Medical University from February 2019 to December 2021, including 78 with anxious depression (ASD+MD-) , 46 with melancholic depression (ASD-MD+) , 61 with anxious and melancholic depression (ASD+MD+) , and 24 with non-anxious and melancholic depression (ASD-MD-) subtyped using the 30-item Inventory of Depressive Symptomatology (IDS-30) and 17-item Hamilton Depression Rating Scale (HAMD-17) . Thirty-five community-living health volunteers were recruited as controls at the same time.The factor and total scores of the HAMD-17 and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) of all subjects were collected. And the latency and amplitude of N400 component of all subjects were collected by inducing N400 components through understanding ambiguous words at the end of sentences. Results (1) The total score and factor scores of HAMD-17 differed significantly across MDD subgroups and control group (P< 0.05) . The total score of HAMD-17 in each of the four MDD subgroups was much higher than that in control group (P0.05) .There were no significant differences in latency and amplitude of N400 component across different electrode sites (P>0.05) , and there were no interaction between no-depression or each of the four subtypes of MDD and electrode sites (P>0.05) . (4) The N400 amplitude value at Fz electrode was negatively correlated with the cognitive impairment factor score (r=-0.170, P=0.016) .The N400 amplitude value at Cz electrode was positively correlated with the block factor score (r=0.151, P=0.033) .The N400 amplitude valueat Pz electrode was positively correlated with the block factor score (r=0.174, P=0.014) .The N400 amplitude value of the Fz electrode was positively correlated with the immediate memory score (r=0.138, P=0.050) .The N400 latency value at Cz electrode was negatively correlated with the delayed memory score (r=-0.155, P=0.028) . Conclusion Extensive cognitive impairment was found in MDD patients, including impaired immediate memory, speech function, attention and delayed memory. ASD+MD+ and ASD+ MD-patients had more severe symptoms, and ASD+MD+ patients had the most severe cognitive impairment. N400 amplitude value was negatively correlated with cognitive impairment and positively correlated with block factor in MDD patients. But these patients demonstrated no impaired function of speech integration induced by ambiguous words at the end of sentences.

Objective: To obtain information on the current clinical research training status and evaluate the training needs comprehensively for medical staff in hospitals. Methods: This survey was initiated and conducted by the Health and Family Planning Commission of Shenzhen in conjunction with the Peking University Clinical Research Institute (Shenzhen) from Sep 2016 through Nov 2016. It was planned that no less than 10% of the total staff from each participating hospital were invited to complete the survey. All participants filled out the questionnaire anonymously and voluntarily. Results: A total of 644 subjects from 12 hospitals completed the survey with the response rate of 28.7%. The majority of respondents (80%) have attended training related to clinical research knowledge and skills, however, medical research ethical aspects and statistics knowledge have been provided only for 40% and 27% of respondents, respectively. With regard to preference on training subjects and contents, Protocol design and development (74%) is ranked first, followed by the data analysis and summary (59%) among those researchers from medical professions. Project management and quality control course are mostly demanded for technicians and nurses (53%). Unpredictably, no more than 40% of the respondents consider that it is necessary to receive "Regulation and Research ethics" course even for those Principal investigators. Conclusions: Our survey results indicated that training subjects on protocol design and research ethics are urgently needed and relatively inadequate in China. An appropriate clinical research competency training model should be developed and provided for hospital staffs in China.