Background: Non-obstructive azoospermia (NOA) is the most severe form of male infertility. Currently, the molecular mechanisms underlying NOA pathology have not yet been elucidated. Hence, elucidation of the mechanisms of NOA and exploration of potential biomarkers are essential for accurate diagnosis and treatment of this disease. In the present study, we aimed to screen for biomarkers and pathways involved in NOA and reveal their potential molecular mechanisms using integrated bioinformatics.Methods: We downloaded two gene expression datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in NOA and matched the control group tissues were identified using the limma package in R software. Subsequently, Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein-protein interaction (PPI) network, gene-microRNAs network, and transcription factor (TF)-hub genes regulatory network analyses were performed to identify hub genes and associated pathways. Finally, we conducted immune infiltration analysis using CIBERSORT to evaluate the relationship between the hub genes and the NOA immune infiltration levels.Results: We identified 698 common DEGs, including 87 commonly upregulated and 611 commonly downregulated genes in the two datasets. GO analysis indicated that the most significantly enriched gene was protein polyglycylation, and KEGG pathway analysis revealed that the DEGs were most significantly enriched in taste transduction and pancreatic secretion signaling pathways. GSEA showed that DEGs affected the biological functions of the ribosome, focaladhesion, and protein_expor. We further identified the top 31 hub genes from the PPI network, and friends analysis of hub genes in the PPI network showed that NR4A2 had the highest score. In addition, immune infiltration analysis found that CD8+ T cells and plasma cells were significantly correlated with ODF3 expression, whereas naive B cells, plasma cells, monocytes, M2 macrophages, and resting mast cells showed significant variation in the NR4A2 gene expression group, and there were differences in T cell regulatory immune cell infiltration in the FOS gene expression groups.Conclusion: The present study successfully constructed a regulatory network of DEGs between NOA and normal controls and screened three hub genes using integrative bioinformatics analysis. In addition, our results suggest that functional changes in several immune cells in the immune microenvironment may play an important role in spermatogenesis. Our results provide a novel understanding of the molecular mechanisms of NOA and offer potential biomarkers for its diagnosis and treatment.
The higher moral sensitivity to bullying a student has, the more likely they are to help the victim or inhibit bullying rather than ignore it. Research has mainly focused on particular sensitivity to bullying, and it remains unknown whether sensitivity to everyday moral issues functions similarly. The present study aimed to examine the effect of everyday moral sensitivity (EMS) on bullying bystander behaviors. We included a range of school children ( n = 1,655, Grades 3–12, 27.6% girls) in Southwest China. The results show 6.10% have been a victim-only, 0.48% have been a bully-only, 0.85% have been the bullying victim, 92.57% have been neither a bully nor a bullying victim, and 45.86% have observed bullying. Students in lower grades are more likely to be bullied. After controlling for covariates (i.e., gender, grade, and social desirability), EMS is positively associated with positive bystander behaviors. Moreover, empathy and moral disengagement (MD) play a mediating role in the relationship between EMS and positive bystander behaviors. The results reveal two parallel processes of EMS influenced bystander behaviors (i.e., empathy and MD). The findings indicate the possibility of cultivating EMS and highlight the role of morality development in preventing school bullying.
In previous research frameworks, researchers used an everyday dilemma to test people’s altruistic versus egoistic inclination. However, there are at least three different psychological processes that could induce altruistic over egoistic decisions, i.e., stronger altruistic sensitivity, weaker egoistic sensitivity, and stronger overall action versus inaction preference. To dissociate these different psychological processes, we developed new materials and applied the CAN algorithm from traditional moral dilemma research in two studies. In Study 1, we designed scenarios varying with a 2 (egoistic/non-egoistic) × 2 (non-altruistic/altruistic) structure. Then, we recruited 209 participants to validate the scenarios and filtered six scene frameworks with 24 scenarios in total. In Study 2, we recruited 747 participants to judge whether they would conduct behavior that is simultaneously altruistic (or non-altruistic) and egoistic (or non-egoistic) in the filtered scenarios obtained from Study 1. They also filled in the Social Isolation Scale, Distress Disclosure Scale, and some other demographic information. As we dissociated the psychological processes using the CAN algorithm, significant correlations between social isolation and distress disclosure and three parameters (i.e., altruistic tendency, egoistic tendency, and overall action/inaction preference) underlying the altruistic choice were revealed to varying degrees. Other individual differences in the psychological processes in everyday moral decision-making were further demonstrated. Our study provided materials and methodological protocols to dissociate the multiple psychological processes in everyday moral decision-making. It promotes our insights on everyday moral decisions from a differential psychological processes perspective.
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