Identification of key regulatory molecules in the early development stage of Alzheimer's disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases, the incidence of which increases with age, and the pathological changes in the brain are irreversible. Recent studies have highlighted the essential role of long noncoding RNAs (lncRNAs) in AD by acting as competing endogenous RNAs (ceRNAs). Our aim was to construct lncRNA-associated ceRNA regulatory networks composed of potential biomarkers for the early stage of AD. AD related datasets come from AlzData and GEO databases. The R package 'Limma' identifies differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases for functional enrichment analysis. Protein-protein interactions (PPIs) in DEGs were constructed in the STRING database, and Cytoscape software identified DEGs. Convergent functional genomics (CFG) analysis of differentially expressed hub genes (referred to as early-DEGs) in the brain before the development of AD pathology. The AlzData database analyses the expression levels of early-DEGs in different nerve cells. The lncRNA-miRNA-mRNA regulatory network was established according to the ceRNA hypothesis. We identified four lncRNAs (XIST, NEAT1, KCNQ1OT1 and HCG18) and four miRNAs (hsa-let-7c-5p, hsa-miR-107, hsa-miR-129-2-3p and hsa-miR-214-3p) were preliminarily identified as potential biomarkers for early AD, competitively regulating Atp6v0b, Atp6v1e1 Atp6v1f and Syt1. This study indicates that NEAT1, XIST, HCG18 and KCNQ1OT1 act as ceRNAs in competitive binding with miRNAs to regulate the expression of Atp6v0b, Atp6v1e1, Atp6v1f and Syt1 before the occurrence of pathological changes in AD.

Neuregulin 4 (Nrg4) cooperates with melatonin to regulate the PRL expression via ErbB4/Erk signaling pathway as a potential prolactin (PRL) regulator.

Neuregulin-4 (Nrg4) and melatonin play vital roles in endocrine diseases. However, there is little discussion about the function and potential mechanism of Nrg4 and melatonin in prolactin (PRL) regulation. The human normal pituitary data from Gene Expression Profiling Interactive Analysis (GEPIA) database was used to explore the correlation between NRG4 and PRL. The expression and correlation of NRG4 and PRL were determined by Immunofluorescence staining (IF) and human normal pituitary tissue microarray. Western Blot (WB) was used to detect the expression of PRL, p-ErbB2/3/4, ErbB2/3/4, p-Erk1/2, Erk1/2, p-Akt and Akt in PRL-secreting pituitary GH3 and RC-4B/C cells treated by Nrg4, Nrg4-small interfering RNA, Erk1/2 inhibitor FR180204 and melatonin. The expression of NRG4 was significantly positively correlated with that of PRL in the GEPIA database and normal human pituitary tissues. Nrg4 significantly increased the expression and secretion of PRL and p-Erk1/2 expression in GH3 cells and RC-4B/C cells. Inhibition of Nrg4 significantly inhibited PRL expression. The increased levels of p-Erk1/2 and PRL induced by Nrg4 were abolished significantly in response to FR180204 in GH3 and RC-4B/C cells. Additionally, Melatonin promotes the expression of Nrg4, p-ErbB4, p-Erk1/2, and PRL and can further promote the expression of p-Erk1/2 and PRL in combination with Nrg4. Further investigation into the function of Nrg4 and melatonin on PRL expression and secretion may provide new clues to advance the clinical control of prolactinomas and hyperprolactinemia.

The dynamic molecular characteristics of neutrophils are associated with disease progression in dengue patients.

Dengue, the most prevalent mosquito-borne disease worldwide, poses a significant health burden. This study integrates clinical data and transcriptomic datasets from different phases of dengue to investigate distinctive and shared cellular and molecular features. Clinical data from 29 dengue patients were collected and analyzed alongside a public transcriptomic data set (GSE28405) to perform differential gene expression analysis, functional enrichment, immune landscape assessment, and development of machine learning model. Neutropenia was observed in 54.79% of dengue patients, particularly during the defervescence phase (65.79%) in clinical cohorts. Bioinformatics analyses corroborated a significant reduction in neutrophil immune infiltration in dengue patients. Receiver operating characteristic curve analysis demonstrated that dynamic changes in neutrophil infiltration levels could predict disease progression, especially during the defervescence phase, with the area under the curve of 0.96. Three neutrophil-associated biomarkers-DHRS12, Transforming growth factor alpha, and ZDHHC19-were identified as promising for diagnosing and predicting dengue progression. In addition, the activation of neutrophil extracellular traps was significantly enhanced and linked to FcγR-mediated signaling pathways and Toll-like receptor signaling pathways. Neutrophil activation and depletion play a critical role in dengue's immune response. The identified biomarkers and their associated pathways offer potential for improved diagnosis and understanding of dengue pathogenesis and progression.

Genetic analyses unravel the causal association of cytokine levels on lichen simplex chronicus risk: insights from a mendelian randomization study.

Lichen simplex chronicus (LSC) presents a challenge in dermatology due to its elusive pathogenic mechanisms. While associations between circulating inflammatory cytokines and LSC were observed, the definitive causal dynamics remain to be elucidated. Our study used a two-sample Mendelian randomization (MR) approach to investigate causal relationships. We applied a suite of MR methodologies, including IVW, Weighted Median, MR-Egger, Weighted Mode, Simple Mode, MR-PRESSO, and the Steiger test, to ensure robust causal inference. Our analysis confirmed the causal impact of genetically determined cytokine levels on LSC risk, particularly MMP-10 (OR = 0.493, P = 0.004) and DNER (OR = 0.651, P = 0.043) in risk attenuation. We also found a positive causal correlation between GDNF levels (OR = 1.871, P = 0.007) and LSC prevalence. Notably, bidirectional causality was observed between DNER and LSC. Consistency across various MR analyses and sensitivity analyses confirmed the absence of horizontal pleiotropy, validating the causal estimates. This pioneering MR investigation unveils a novel genetically anchored causal relationship between the circulating levels of MMP-10, DNER, and GDNF and LSC risk. Although further validation is requisite, our findings augment the understanding of cytokine mediation in LSC and underscore prospective avenues for research.

Evolving immune evasion and transmissibility of SARS-CoV-2: The emergence of JN.1 variant and its global impact.

The continuous evolution of SARS-CoV-2 variants constitutes a significant impediment to the public health. The World Health Organization (WHO) has designated the SARS-CoV-2 variant JN.1, which has evolved from its progenitor BA.2.86, as a Variant of Interest (VOI) in light of its enhanced immune evasion and transmissibility. The proliferating dissemination of JN.1 globally accentuates its competitive superiority and the potential to instigate fresh surges of infection, notably among cohorts previously infected by antecedent variants. Notably, prevailing evidence does not corroborate an increase in pathogenicity associated with JN.1, and antiviral agents retain their antiviral activity against both BA.2.86 and JN.1. The sustained effectiveness of antiviral agents offers a beacon of hope. Nonetheless, the variant's adeptness at eluding the immunoprotective effects conferred by extant vaccines highlights the imperative for the development of more effective vaccines and therapeutic approaches. Overall, the distinct evolutionary trajectories of BA.2.86 and JN.1 underscore the necessity for ongoing surveillance and scholarly inquiry to elucidate their implications for the pandemic's evolution, which requires the international communities to foster collaboration through the sharing of data, exchange of insights, and collective scientific endeavors.

Cytokine IL-5 and HGF: combined prediction of non-/low immune response to hepatitis B vaccination at birth in infants born to HBsAg-positive mothers.

Background: The immune response to hepatitis B vaccine may be influenced by numerous factors, and patients with non/low response re-exposed to hepatitis B virus remain susceptible. Thus, a better understanding of the underlying mechanisms of non/low immune response in infants born to Hepatitis B surface antigen (HBsAg)-positive mothers is essential. Methods: 100 infants born to HBsAg-positive mothers from 2015 to 2020 were enrolled in the study, further divided into the non/low response group (n=13) and the moderate strong response group (n=87) based on the quantification of hepatitis B surface antibody at 12 months of age. The differential expression of 48 immune-related cytokines in the two groups was compared and analyzed in detail. The key cytokines were further identified and clinically predictive models were developed. Results: We found that 13 cytokines were lowly expressed and one cytokine was highly expressed in the non/low response group, compared with the moderate strong response group at birth. In addition, 9 cytokines were lowly expressed and one cytokine was highly expressed in the non/low response group at 12 months of age. Furthermore, we found that IL-5 and HGF were promising predictors for predicting the immunization response to hepatitis B vaccine in infants, and the combination of the two cytokines showed the best predictive efficiency, with an area under the curve (AUC) value of 0.844. Conclusion: The present study provides a theoretical basis on cytokines for developing and implementing effective immunotherapies against non/low immune response in infants born to HBsAg-positive mothers.