The effect of the treatment of denture related stomatitis on peripheral T cells and monocytes

Purpose: Systemic immune activation has been recently linked to chronic inflammatory disorders of the oral cavity, particularly to periodontitis. The purpose of this study was to determine whether treatment of a fungus-induced oral inflammation, namely denture-related stomatitis (DRS), can affect the activation of the systemic immune response. Materials and Methods: Peripheral blood from patients with denture-related stomatitis caused by Candida albicans infection (n = 15) was collected at three time points: before treatment with nystatin, at the end of therapy and 2 months after finishing therapy. Activation of T cells and monocytes was assessed by flow cytometry. Results: The percentages of peripheral lymphocytes, T cells and their subpopulations, as well as monocytes were similar before, immediately following and two months after nystatin treatment. Cells expressing early activation marker CD69 and RANTES C-C chemokine receptor type 5 significantly increased immediately after treatment and returned to baseline levels after two months. Th17 cells, which have been implicated in the pathogenesis of DRS, remained unchanged. Central memory CD4+ subset and intermediate subset of monocytes were lower after therapy and this effect was sustained for two months. Conclusion: Treatment of denture-related stomatitis does not seem to affect the general state of the cellular components of the immune system. The results suggest a potential proinflammatory effect of the antifungal agent, nystatin. Although transient and not intense, this effect might be of particular clinical importance, because of relationships between inflammation and certain diseases. Further studies are required to clarify this aspect

Th17 responses are not altered by natural exposure to seasonal allergens in pollen-sensitive patients

Background: Allergic rhinitis affects 10–30 % of the global population and this number is likely to increase in the forthcoming years. Moreover, it commonly co-exists with allergic asthma as a chronic allergic respiratory syndrome. While the involvement of Th2 cells in allergy is well understood, alterations of pro-inflammatory Th17 responses remain poorly characterized. The aim of our study was to determine whether natural seasonal allergen exposure causes changes in T cell subset characteristics in patients with allergic rhinitis and asthma. Methods: Sixteen patients with allergic rhinitis/atopic asthma (9M, 7F; age 31.8 ± 12.1) and 16 healthy controls were recruited into the study (9M, 7F; age 31.2 ± 5.3). Blood samples were collected from the patients 1–3 months before pollen season (visit 1), within 7 days of the appearance of pollen/initiation of allergic symptoms (visit 2) and 2 weeks after visit 2 following the introduction of symptomatic treatment with antihistamines (visit 3). Flow cytometry was used to assess major T cell subsets (naïve, central memory, effector memory and CD45RA+ effector) and key T cell cytokine production (IFNγ, IL-17A, TNF and IL-4) using intracellular staining. Data were analyzed using repeated measures ANOVA and paired t test. Results: As expected, an increase in the percentage of IL‐4+ CD4+ cells was observed during natural pollen exposure in patients with allergic respiratory syndrome. No significant changes were observed in the production of other cytokines, including Th17 cells, which tended to be lower than in the control population but unchanged during pollen exposure. Introduction of antihistamine treatment led to only moderate changes in cytokine production from CD4 and CD8 T cells. Selective changes in CD8+ T cells were observed during natural pollen exposure including a decrease in transient cells (with features of CD45RA+ and CD45RO+ cells) and a decrease in the percentage of central memory cells in the peripheral circulation. Within the CD4 cell group the total percentage of CD45RA positive CD4 cells was increased during pollen exposure. Conclusions: Th1 and Th17 responses are not altered during pollen season but allergen exposure affects T cell activation and memory cell status in patients with allergic respiratory syndrome

Hyperandrogenism and Metabolic Syndrome Are Associated With Changes in Serum-Derived microRNAs in Women With Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) remains one of the most common endocrine disorder in premenopausal women with an unfavorable metabolic risk profile. Here, we investigate whether biochemical hyperandrogenism, represented by elevated serum free testosterone, resulted in an aberrant circulating microRNA (miRNAs) expression profile and whether miRNAs can identify those PCOS women with metabolic syndrome (MetS). Accordingly, we measured serum levels of miRNAs as well as biochemical markers related to MetS in a case-control study of 42 PCOS patients and 20 Controls. Patients were diagnosed based on the Rotterdam consensus criteria and stratified based on serum free testosterone levels (≥0.034 nmol/l) into either a normoandrogenic (n = 23) or hyperandrogenic (n = 19) PCOS group. Overall, hyperandrogenic PCOS women were more insulin resistant compared to normoandrogenic PCOS women and had a higher prevalence of MetS. A total of 750 different miRNAs were analyzed using TaqMan Low-Density Arrays. Altered levels of seven miRNAs (miR-485-3p, -1290, -21-3p, -139-3p, -361-5p, -572, and -143-3p) were observed in PCOS patients when compared with healthy Controls. Stratification of PCOS women revealed that 20 miRNAs were differentially expressed between the three groups. Elevated serum free testosterone levels, adjusted for age and BMI, were significantly associated with five miRNAs (miR-1290, -20a-5p, -139-3p, -433-3p, and -361-5p). Using binary logistic regression and receiver operating characteristic curves (ROC), a combination panel of three miRNAs (miR-361-5p, -1225-3p, and -34-3p) could correctly identify all of the MetS cases within the PCOS group. This study is the first to report comprehensive miRNA profiling in different subgroups of PCOS women with respect to MetS and suggests that circulating miRNAs might be useful as diagnostic biomarkers of MetS for a different subset of PCOS

Transcriptional and epigenomic profiling identifies YAP signaling as a key regulator of intestinal epithelium maturation

During intestinal organogenesis, equipotent epithelial progenitors mature into phenotypically distinct stem cells that are responsible for lifelong maintenance of the tissue. While the morphological changes associated with the transition are well characterized, the molecular mechanisms underpinning the maturation process are not fully understood. Here, we leverage intestinal organoid cultures to profile transcriptional, chromatin accessibility, DNA methylation, and three-dimensional (3D) chromatin conformation landscapes in fetal and adult epithelial cells. We observed prominent differences in gene expression and enhancer activity, which are accompanied by local changes in 3D organization, DNA accessibility, and methylation between the two cellular states. Using integrative analyses, we identified sustained Yes-Associated Protein (YAP) transcriptional activity as a major gatekeeper of the immature fetal state. We found the YAP-associated transcriptional network to be regulated at various levels of chromatin organization and likely to be coordinated by changes in extracellular matrix composition. Together, our work highlights the value of unbiased profiling of regulatory landscapes for the identification of key mechanisms underlying tissue maturation

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery