The impact of self-employment on mental health of the younger elderly in China.

BACKGROUND: With the prolongation of the life expectancy of the Chinese population and the intensification of the aging process of the population, the mental health problems of the elderly have become increasingly prominent. This study aims to explore whether self-employment can promote and how to promote the mental health of the elderly. METHOD: Based on the 2018 China Longitudinal Aging Social Survey (CLASS) data, this paper uses OLS model and KHB method to verify the impact of self-employment on the mental health of the younger elderly and its mechanism. RESULTS: The results indicate that self-employment can significantly reduce the depression tendency of the younger elderly and promote their mental health. Heterogeneity analysis shows that self-employment has a more significant positive impact on the mental health of the younger elderly who are self-rated healthy, free of chronic diseases and low-level medical service utilization. The mechanism shows that self-employment can indirectly improve the mental health of the younger elderly through income growth effect and self-worth realization effect, in which the self-worth realization effect is greater than the economic effect. It illustrates that with the development of China's economy, the elderly are pursuing more intrinsic values brought by self-employment than economic benefits. CONCLUSION: In view of the above research results, it is suggested to encourage the elderly to actively participate in social activities, provide policy support for the younger elderly to engage in self-employment, increase government support as well as health guarantee level, and improve the subjective initiative of the elderly to participate in self-employment, so that the society can truly realize the healthy aging of "being useful and productive for the elderly".

Covariation between spontaneous neural activity in the insula and affective temperaments is related to sleep disturbance in individuals with major depressive disorder.

BACKGROUND: Affective temperaments have been considered antecedents of major depressive disorder (MDD). However, little is known about how the covariation between alterations in brain activity and distinct affective temperaments work collaboratively to contribute to MDD. Here, we focus on the insular cortex, a critical hub for the integration of subjective feelings, emotions, and motivations, to examine the neural correlates of affective temperaments and their relationship to depressive symptom dimensions. METHODS: Twenty-nine medication-free patients with MDD and 58 healthy controls underwent magnetic resonance imaging scanning and completed the Temperament Evaluation of Memphis, Pisa, Paris and San Diego (TEMPS). Patients also received assessments of the Hamilton Depression Rating Scale (HDRS). We used multivariate analyses of partial least squares regression and partial correlation analyses to explore the associations among the insular activity, affective temperaments, and depressive symptom dimensions. RESULTS: A profile (linear combination) of increased fractional amplitude of low-frequency fluctuations (fALFF) of the anterior insular subregions (left dorsal agranular-dysgranular insula and right ventral agranuar insula) was positively associated with an affective-temperament (depressive, irritable, anxious, and less hyperthymic) profile. The covariation between the insula-fALFF profile and the affective-temperament profile was significantly correlated with the sleep disturbance dimension (especially the middle and late insomnia scores) in the medication-free MDD patients. CONCLUSIONS: The resting-state spontaneous activity of the anterior insula and affective temperaments collaboratively contribute to sleep disturbances in medication-free MDD patients. The approach used in this study provides a practical way to explore the relationship of multivariate measures in investigating the etiology of mental disorders.

How does digital life influence the health service use among rural residents? Evidence from China.

BACKGROUND: The Healthy China strategy is an important development objective of the 14th Five-Year Plan and Vision 2035 in China, while health service use in rural China has been a weak link in this strategy. OBJECTIVE: Nowadays, people's health service use will be influenced by digital technology due to the arrival of the Digital Age, and that is the reason why our interest is to discuss the effect of digital life on health service use among rural residents. METHODS: We use the data from the China Family Panel Studies (CFPS) 2020 to examine the effect of digital life on health service use among rural residents, and we use Instrumental Variables method to control the endogenous problem and use KHB model to discuss the mechanism of this effect. RESULTS: It was found that digital life has increased the health service use among rural residents significantly, and this result has been verified by robust test and Instrumental Variables method. Besides, digital life can increase health service use through the information channel effect and the health literacy effect indirectly. Moreover, digital life has a more significant impact on the residents with low social capital, low physical capital and low social trust, which represents the inclusivity of digital life. CONCLUSION: The results of our paper will be helpful to examine the effect of the digital policy on promoting the health service use in rural China, and our findings will provide evidence of how to use digital life to enhance health service use among rural residents. Based on this, the government should take measures to eliminate the digital divide between urban and rural areas by promoting the level of digital life among rural residents, paying more attention to the digital literacy development among them, and forging ahead toward the great goal of the Healthy China under the Digital Age.

A novel heterogeneous transfer learning method based on data stitching for the sequential coding brain computer interface.

OBJECTIVE: For the brain computer interface (BCI), it is necessary to collect enough electroencephalography (EEG) signals to train the classification model. When the operation dimension of BCI is large, it will bring great burden to data acquisition. Fortunately, this problem can be solved by our proposed transfer learning method. METHOD: For the sequential coding experimental paradigm, the multi-band data stitching with label alignment and tangent space mapping (MDSLATSM) algorithm is proposed as a novel heterogeneous transfer learning method. After filtering by multi-band filtering, the artificial signals can be obtained by data stitching from the source domain, which build a bridge between the source domain and target domain. To make the distribution of two domains closer, their covariance matrices are aligned by label alignment. After mapping to the tangent space, the features are extracted from the Riemannian manifold. Finally, the classification results are obtained with feature selection and classification. RESULTS: Our data set includes the EEG signals from 16 subjects. For the heterogeneous transfer learning of cross-label, the average classification accuracy is 78.28%. MDSLATSM is also tested for cross-subject, and the average classification accuracy is 64.01%, which is better than existing methods. SIGNIFICANCE: Combining multi-band filtering, data stitching, label alignment and tangent space mapping, a novel heterogeneous transfer learning method can be achieved with superior performance, which promotes the practical application of the BCI systems.

Covariation between Childhood-Trauma Related Resting-State Functional Connectivity and Affective Temperaments is Impaired in Individuals with Major Depressive Disorder.

Affective temperaments and childhood-trauma experiences are associated with major depressive disorder (MDD). So far, how the covariation between distinct affective temperaments and childhood-trauma insulted brain functional connectivities (FCs) contribute to MDD remains unclear. Here, we aimed to investigate whether certain brain FC patterns are related to certain affective temperaments and whether the FCs contribute to depressive symptom dimensions of MDD patients. Twenty-nine medication-free MDD patients and 58 healthy controls underwent magnetic resonance imaging scanning and completed the Hamilton Depression Rating Scale (HDRS), the Hamilton Anxiety Rating Scale (HARS), the Childhood Trauma Questionnaire-Short Form (CTQ-SF), and the Temperament Evaluation of Memphis, Pisa, Paris and San Diego (TEMPS). Two multivariate analyses of partial least squares (PLS) regression were used to explore the associations among childhood-trauma related resting-state FCs, affective temperaments and depressive symptom dimensions. In all participants, a linear combination of 81 FCs (involving parahippocampus, amygdala, cingulate cortex, insula, frontal-temporal-parietal-occipital cortex, pallidum, and cerebellum) were associated with a linear combination of increased depressive, irritable, anxious, and cyclothymic temperaments. Moreover, the covariation between the PLS FC profile and the PLS affective-temperament profile were enhanced in the MDD patients compared to healthy controls. In MDD participants alone, the affective-temperament modulated FC profile (mainly of the lingual and temporal cortex) was associated with the somatization symptom dimension when age, sex, ill-duration, age-of-onset, and HARS scores were adjusted. The findings imply possible neural correlates of affective temperaments and may find applications in intervention of the somatization-depression symptoms by stimulation of the related neural correlates.

Genome-wide analysis of circular RNAs in prenatal and postnatal muscle of sheep.

Circular RNAs (circRNAs), a type of non-coding RNA with circular structure, were generated by back splicing and widely expressed in animals and plants. Recent studies have shown that circRNAs extensively participate in cell proliferation, cell differentiation, cell autophagy and other biological processes. However, the role and expression of circRNAs in the development and growth of muscle have not been studied in sheep. In our study, we first used RNA-seq to study the circRNAs in prenatal and postnatal longissimus dorsi muscle of sheep. A total of 6113 circRNAs were detected from the RNA-seq data. Several circRNAs were identified using reverse transcription PCR, DNA sequencing and RNase R digestion experiments. The expression levels of several circRNAs in prenatal and postnatal muscle were confirmed by Real-Time RT-PCR. The gene ontology (GO) and KEGG enrichment analysis of the host gene of the circRNAs showed that these circRNAs were mainly involved in the growth and development of muscle related signaling pathways. These circRNAs might sponge microRNAs (miRNAs) in predicted circRNA-miRNA-mRNA networks. The circRNAs expression profiles in muscle provided an important reference for the study of circRNAs in sheep.

Genome-wide analysis of circular RNAs in prenatal and postnatal pituitary glands of sheep.

Circular RNAs (circRNAs) are a class of animal non-coding RNAs and play an impor-tant role in animal growth and development. However, the expression and function of circRNAs in the pituitary gland of sheep are unclear. Transcriptome profiling of circRNAs in the pituitary gland of sheep may enable us to understand their biological functions. In the present study, we identified 10,226 circRNAs from RNA-seq data in the pituitary gland of prenatal and postnatal sheep. Reverse transcription PCR and DNA sequencing analysis confirmed the presence of several circRNAs. Real-time RT-PCR analysis showed that sheep circRNAs are resistant to RNase R digestion and are expressed in prenatal and postnatal pituitary glands. GO and KEGG enrichment analysis showed that host genes of differentially expressed circRNAs are involved in the regulation of hormone secretion as well as in several pathways related to these processes. We determined that numerous circRNAs interact with pituitary-specific miRNAs that are involved in the biologic functions of the pituitary gland. Moreover, several circRNAs contain at least one IRES element and open reading frame, indicating their potential to encode proteins. Our study provides comprehensive expression profiles of circRNAs in the pituitary gland, thereby offering a valuable resource for circRNA biology in sheep.