Understanding predictors of mental health and substance use treatment utilization among US adults: A repeated cross-sectional study.

Background: Understanding discrepancies in mental health and substance use treatment utilization can help identify inequities in access to health services. We investigate mental health and substance use treatment utilization as function of demographic and social determinants, as well as pre-existing mental health and substance use disorders. Methods: In this repeated cross-sectional study, we used the 2017-2019 National Survey on Drug Use and Health data on US adults above age 18. Two logistic regression models were conducted, using predictors of age, gender, race/Hispanicity, sexual identity, education, insurance, family income, and past year mental health and substance use disorders, with outcomes of mental health or substance use treatment utilization. Weighted estimates of substance use disorders and insurance types and Pearson's correlation tests of vulnerability among age, gender, and treatment type were reported. Findings: Racial minorities, uninsured populations, sexual minorities, and females had lower odds of receiving mental health treatment, while older populations, lower income groups, and dual eligible enrollees had higher odds. Individuals with substance use disorders but no mental illness had higher odds of receiving mental health treatment. Those utilizing mental health treatment were mostly of high income, privately insured, and using cannabis, cocaine, and opioids. Older populations, men, and Medicaid only enrollees had higher odds of receiving substance use disorder treatment, whereas racial minorities had lower odds. Distribution of income, insurance type, and substance use were more widespread than mental health treatment. Interpretation: Mental health treatment can be used as an avenue for substance use treatment, particularly opioid use disorders. It is important to target vulnerable populations, like racial minorities and uninsured populations to improve access to mental health and substance use treatment.

Candida albicans Elicits Pro-Inflammatory Differential Gene Expression in Intestinal Peyer's Patches.

The details of how gut-associated lymphoid tissues such as Peyer's patches (PPs) in the small intestine play a role in immune surveillance, microbial differentiation and the mucosal barrier protection in response to fungal organisms such as Candida albicans are still unclear. We particularly focus on PPs as they are the immune sensors and inductive sites of the gut that influence inflammation and tolerance. We have previously demonstrated that CD11c+ phagocytes that include dendritic cells and macrophages are located in the sub-epithelial dome within PPs sample C. albicans. To gain insight on how specific cells within PPs sense and respond to the sampling of fungi, we gavaged naïve mice with C. albicans strains ATCC 18804 and SC5314 as well as Saccharomyces cerevisiae. We measured the differential gene expression of sorted CD45+ B220+ B-cells, CD3+ T-cells and CD11c+ DCs within the first 24 h post-gavage using nanostring nCounter® technology. The results reveal that at 24 h, PP phagocytes were the cell type that displayed differential gene expression. These phagocytes were able to sample C. albicans and discriminate between strains. In particular, strain ATCC 18804 upregulated fungal-specific pro-inflammatory genes pertaining to innate and adaptive immune responses. Interestingly, PP CD11c+ phagocytes also differentially expressed genes in response to C. albicans that were important in the protection of the mucosal barrier. These results highlight that the mucosal barrier not only responds to C. albicans, but also aids in the protection of the host.

RNA isolation from Peyer's patch lymphocytes and mononuclear phagocytes to determine gene expression profiles using NanoString technology.

Sampling and immune surveillance within gut-associated lymphoid tissues such as the intestinal Peyer's patch (PP) occurs by an elegantly orchestrated effort that involves the epithelial barrier, B and T lymphocytes, and an extensive network of mononuclear phagocytes. Although we now understand more about the dynamics of antigen and microbial sampling within PPs, the gene expression changes that occur in individual cell subsets during sampling are not well characterized. This protocol describes the isolation of high-quality RNA from sorted PP, B and T-lymphocytes, and CD11c+ phagocytes for use with nCounter-NanoString technology. This method allows investigators to study gene expression changes within PPs in response to antigens, microbes, and oral vaccine delivery vehicles of interest that are sampled.