Keratinocyte TLR2 and TLR7 contribute to chronic itch through pruritic cytokines and chemokines in mice.

Although neuronal Toll-like receptors (TLRs) (e.g., TLR2, TLR3, and TLR7) have been implicated in itch sensation, the roles of keratinocyte TLRs in chronic itch are elusive. Herein, we evaluated the roles of keratinocyte TLR2 and TLR7 in chronic itch under dry skin and psoriasis conditions, which was induced by either acetone-ether-water treatment or 5% imiquimod cream in mice, respectively. We found that TLR2 and TLR7 signaling were significantly upregulated in dry skin and psoriatic skin in mice. Chronic itch and epidermal hyperplasia induced by dry skin or psoriasis were comparably reduced in TLR2 and TLR7 knockout mice. In the dry skin model, the enhanced messenger RNA (mRNA) expression levels of pruritic CXCL1/2, IL-31, IL-33, ST2, IL-6, IL-17A, TNF-α, and IFN-γ were inhibited in TLR2-/- mice, while CXCL2, IL-31, and IL-6 were inhibited in TLR7-/- mice. In psoriasis model, the enhanced mRNA expression levels of pruritic CXCL1/2, IL-31, IL-33, ST2, IL-6, and TNF-α were inhibited in TLR2-/- mice, while CXCL1/2, IL-31, IL-33, ST2, IL-6, IL-17A, and TNF-α were inhibited in TLR7-/- mice. Incubation with Staphylococcus aureus (S. aureus) peptidoglycan (PGN-SA) (a TLR2 agonist), imiquimod (a TLR7 agonist), and miR142-3p (a putative TLR7 agonist) were sufficient to upregulate the expression of pruritic cytokines or chemokines in cultured keratinocyte HaCaT cells. Finally, pharmacological blockade of C-X-C Motif Chemokine Receptor 1/2 and high mobility group box protein 1 dose-dependently attenuated acute and chronic itch in mice. Together, these results indicate that keratinocyte TLR2 and TLR7 signaling pathways are distinctly involved in the pathogenesis of chronic itch.

Improving the robustness of beach water quality modeling using an ensemble machine learning approach.

Microbial pollution of beach water can expose swimmers to harmful pathogens. Predictive modeling provides an alternative method for beach management that addresses several limitations associated with traditional culture-based methods of assessing water quality. Widely-used machine learning methods often suffer from high variability in performance from one year or beach to another. Therefore, the best machine learning method varies between beaches and years, making method selection difficult. This study proposes an ensemble machine learning approach referred to as model stacking that has a two-layered learning structure, where the outputs of five widely-used individual machine learning models (multiple linear regression, partial least square, sparse partial least square, random forest, and Bayesian network) are taken as input features for another model that produces the final prediction. Applying this approach to three beaches along eastern Lake Erie, New York, USA, we show that generally the model stacking approach was able to generate reliably good predictions compared to all of the five base models. The accuracy rankings of the stacking model consistently stayed 1st or 2nd every year, with yearly-average accuracy of 78%, 81%, and 82.3% at the three studied beaches, respectively. This study highlights the value of the model stacking approach in predicting beach water quality and solving other pressing environmental problems.

Identification of novel HLA-A0201-restricted T-cell epitopes against thyroid antigens in autoimmune thyroid diseases.

PURPOSE: The different mechanisms that trigger the autoimmune attack to the thyroid between Hashimoto's thyroiditis (HT) and Graves' disease (GD) are still unclear. The aim of this study was to recognize thyroid antigens specific CD8+ T-cell epitopes and explore the relationship between these epitopes and thyroid autoantibodies, duration and classification in these two diseases. METHODS: Free thiiodothyronine, free tetraiodothyronine, thyroid-stimulating hormone, TgAb, and TPOAb were all measured by immunochemiluminometric assays, while TRAb was tested by radioimmunoassay. HLA class I peptide affinity algorithms were applied to predict candidate thyroid autoantigen peptides that blind to HLA-A*0201. The ELISpot assay was used to detect Tg-, TPO-, and TSHR-specific CD8+ T cells. RESULTS: We demonstrated that TG-6 was a novel HLA-A*0201-restricted CTL epitope in GD. TG-6, TG-7, TG-10, TG-11, and TPO-6 were immunodominant in GD patients compared with HT patients (TG-6: 38.5 vs. 8%, P = 0.034; TG-7, TG-10, TG-11, and TPO-6: 23.1 vs. 0%, P = 0.034). The immunodominance of TG-6 in GD patients was more evident than healthy controls (HC) (TG-6: 35.8 vs. 0%, P = 0.011), but there was no statistically significant difference between HT patients and HC. Subgroup analyses revealed the T-cell responsiveness to TG-6 was stronger in TgAb-negative HT patients (0 vs. 40%, P = 0.033). However, there was no correlation showed for TPOAb, TRAb, medication and duration in both HT and GD patients. CONCLUSIONS: We report for the first time that both diseases, HT and GD, recognize different antigen-specific CD8-positive T cells. Tg maybe the dominant thyroid autoantigen contributing to breaking tolerance in GD. It could improve our knowledge of autoimmune thyroid diseases pathogenesis as well as offer new therapeutical tools in terms of peptide vaccine therapy.

The Association between Genomic DNA Methylation and Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus.

AIM: DNA methylation is thought to be involved in regulating the expression of key genes and inducing diabetic peripheral neuropathy (DPN). However, clinically, the level of whole-genome DNA methylation and its relationship with DPN remains unclear. METHODS: 186 patients with type 2 diabetes mellitus (T2DM) admitted to the Second Affiliated Hospital of Soochow University since Jul. 2016 to Oct. 2017 were enrolled in the study, including 100 patients in the DPN group and 86 patients in the non-DPN group, diagnosed with Toronto Clinical Scoring System (TCSS). Clinical and biochemical characteristics between the two groups were compared, and the correlations with TCSS scores were analyzed. Furthermore, the levels of genomic DNA methylation of leukocytes, measured with high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS), were also analyzed between the two groups. RESULTS: Age, duration, triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL-C), creatinine, uric acid (UA), blood urea nitrogen (BUN), and C-reactive protein (CRP) were significantly higher in the DPN group. Estimated glomerular filtration rate (eGFR) and the level of genomic DNA methylation were much lower in the DPN group. Spearman correlation analysis showed that TCSS was positively correlated with age, duration, UA, and CRP and was negatively correlated with body mass index (BMI), eGFR, and the level of genomic DNA methylation. Interestingly, multiple stepwise regression analysis showed that only duration, genomic DNA methylation, and eGFR had impacts on TCSS. The results also showed that the levels of genomic DNA methylation did not change significantly whether or not there was renal injury. Another multiple stepwise regression analysis showed that TCSS and BMI were the influencing factors of genomic DNA methylation. Finally, we found that genomic DNA methylation levels were decreased significantly in the DPN group compared with the non-DPN group when the duration is ≥5 years or BMI ≥ 25 kg/m2. CONCLUSION: Low level of genomic DNA methylation is a relative specific risk factor of diabetic peripheral neuropathy in patients with type 2 diabetes.

Evaluation of groundwater discharge into surface water by using Radon-222 in the Source Area of the Yellow River, Qinghai-Tibet Plateau.

Understanding hydrological processes in the Source Area of the Yellow River (SAYR), Qinghai-Tibet Plateau, is vital for protection and management of groundwater and surface water resources in the region. In situ water measurements of exchange rates between surface water and groundwater are, however, hard to conduct because of the harsh natural conditions of the SAYR. We here present an indirect method using in situ 222Rn measurements to estimate groundwater discharge into rivers and lakes in the SAYR. 222Rn was measured in rivers, lakes, groundwater and springs during three sampling periods (2014-2016), and the results indicate large variability in the concentration of the isotope. The data also indicate decreasing 222Rn trends in groundwater in the cold season (the Feb-2015 sampling period) which may be linked to frequency of capturing 222Rn in the frozen ground caused by geocryogenic processes. In addition, permafrost spatial extent and freeze-thaw processes have strongly affected the hydrological conditions in the region.