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Abstract In the United States (US), neonatal intensive care units (NICUs) monitor and treat newborns for a variety of adverse health concerns including preterm status, respiratory distress and restricted growth. As such, NICU admission is an integrated measure of neonatal risk. We linked 2018 US national birth registry NICU admission data among singleton births with satellite and modelled air pollution levels for the month prior to birth to examine whether late-pregnancy exposure to ambient air pollutants is associated with adverse neonatal health outcomes. Regardless of season, higher ambient levels of nitrogen dioxide (NO2) and fine particulate matter

Abstract Over the past four decades, research has underscored the significance of approaching and preventing trauma from a systemic standpoint. Trauma-informed care (TIC) methodologies offer a structure for healthcare practices, striving to convert organizations into trauma-informed systems that employ trauma-specific interventions. This review employs epidemiological and household data from Turkey to underscore the importance of integrating trauma-informed care as a means of prevention and intervention. Through a desk review, the study examines the role of adverse childhood experiences (ACEs), delving into their origin from family dynamics, migration, violence, exposure to violence, juvenile delinquency, and child maltreatment. The research highlights innovative healthcare approaches that leverage data to address complex patient health issues while considering mental health needs. In contemporary times, healthcare organizations acknowledge the value of a data-driven approach to make informed clinical decisions, enhance treatment procedures, and improve overall healthcare outcomes. The reviewed research and empirical data furnish proof of the importance of effective and efficient treatment methods that prioritize trauma prevention and treatment, integrating the role of ACEs. This paper seeks to contribute to discussions on transforming the healthcare system to meet the healthcare needs of Turkish households, all the while taking into account the evolving sociopolitical factors that shape Turkey's population characteristics.

Objectives The study investigated the association between indoor air pollution (IAP) and risk factors for acute respiratory infection (ARI) symptoms in children under 5 years of age. Methods A cross-sectional study was conducted using data derived from Indonesia Demographic and Health Survey in 2017. Binary logistic regression modeling was employed to examine each predictor variable associated with ARI among children under 5 years of age in Indonesia. Results The study included a total of 4936 households with children. Among children under 5 years old, 7.2% reported ARI symptoms. The presence of ARI symptoms was significantly associated with the type of residence, wealth index, and father’s smoking frequency, which were considered the sample’s socio-demographic characteristics. In the final model, living in rural areas, having a high wealth index, the father’s smoking frequency, and a low education level were all linked to ARI symptoms. Conclusions The results revealed that households in rural areas had a substantially higher level of reported ARI symptoms among children under 5 years old. Furthermore, the father’s smoking frequency and low education level were associated with ARI symptoms.

Antiretroviral treatment (ART) appropriately and regularly used decreases the human immunodeficiency virus (HIV) viral load in the bloodstream, preventing HIV-infected people from spreading the infection to others. Disparities in ART adoption persists in East and Southern Africa, with low HIV-positive status knowledge being the primary factor. We investigated individual and household characteristics of HIV-positive status awareness among adults with long-term HIV infection in four East and Southern African countries: Eswatini, Malawi, Tanzania, and Zimbabwe. The study analyzed data from surveys conducted in Eswatini, Malawi, Tanzania, and Zimbabwe in 2015-2016. Only individuals who tested positive for HIV through rapid tests were included in the analysis. Those who already knew they were HIV-positive were categorized as aware, while those who reported being negative, never tested, or didn't know their status were categorized as unaware. Statistical models were used to examine various factors related to HIV awareness. Pooled and country-specific odds ratios were computed. The percentage of people who knew they had HIV ranged from 58% (Tanzania and Malawi) to 87% (Eswatini). After adjusting for other variables, young persons in all countries were less likely to be aware of their HIV-positive status. Gender, marital status, education, working status, household wealth, and urbanization level of households were also associated with HIV-positive status awareness but inconsistent across countries. HIV-positive status awareness in these four East and Southern African nations remained unsatisfactory as compared to the United Nations' 95% guideline, indicating that testing and knowledge of HIV testing in this region still has a lot of potential for improvement. The observed variations among nations may be attributable to differences in HIV pandemic culture and policies. The findings of this study will assist governments determining which subpopulations to target to boost adoption of HIV testing services, as well as in designing and development of policies.

Background: One of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB. Method: The genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)). Results: A total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores. Conclusion: Through the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.

Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein–protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.