Irisin delays the onset of type 1 diabetes in NOD mice by enhancing intestinal barrier.

Type 1 diabetes (T1D), a complex autoimmune disease, is intricately linked to the gut's epithelial barrier function. Emerging evidence emphasizes the role of irisin, an exercise-related hormone, in preserving intestinal integrity. This study investigates whether irisin could delay T1D onset by enhancing the colon intestinal barrier. Impaired colon intestinal barriers were observed in newly diagnosed T1D patients and non-obese diabetic (NOD) mice, worsening with age and accompanied by islet inflammation. Using an LPS-induced colonic inflammation model, a dose-dependent impact of LPS on colon cells irisin expression, secretion, and barrier function was revealed. Exogenous irisin demonstrated remarkable effects, mitigating islet insulitis, enhancing energy expenditure, and alleviating autoimmune symptoms by reducing colon intestinal permeability. Single-cell RNA sequencing (scRNA-seq) highlighted irisin's positive impact on colon epithelial cell clusters, effectively restoring the intestinal barrier. Irisin also selectively modulated bacterial composition, averting potential bacterial translocation. Mechanistically, irisin enhanced colon intestinal barrier tight junction proteins through the AMPK/PI3K/AKT pathway, with FAM120A playing a crucial role. Irisin upregulated MUC3 expression, a protector against damage and inflammation. Harnessing irisin's exercise-mimicking properties suggests therapeutic potential in clinical settings for preventing T1D progression, offering valuable insights into fortifying the colon's intestinal barrier and managing autoimmune conditions associated with T1DM.

Constructed wetlands for the treatment of household organic micropollutants with contrasting degradation behaviour: Partially-saturated systems as a performance all-rounder.

The degradability of specific organic micropollutants in constructed wetlands (CWs) may differ depending on the prevalence of oxic or anoxic conditions. These conditions are governed, among other factors, by the water saturation level in the system. This study investigated the removal of three environmentally-relevant organic micropollutants: bisphenol-group plasticizer bisphenol S (BPS), household-use insecticide fipronil (FPN) and non-steroidal anti-inflammatory drug ketoprofen (KTP) in the model CWs set up in an outdoor column system. BPS and KTP, in contrast to FPN, exhibit higher biodegradability potential under oxic conditions. The experimental CWs were operated under various saturation conditions: unsaturated, partially saturated and saturated, and mimicked the conditions occurring in unsaturated, partially-saturated intermittent vertical-flow CWs and in horizontal-flow CWs, respectively. The CWs were fed with synthetic household wastewater with the concentration of the micropollutants at the level of 30-45 µg/L. BPS and KTP exhibited contrasting behaviour against FPN in the CWs in the present experiment. Namely, BPS and KTP were almost completely removed in the unsaturated CWs without a considerable effect of plants, but their removal in saturated CWs was only moderate (approx. 50%). The plants had only a pronounced effect on the removal of BPS in saturated systems, in which they enhanced the removal by 46%. The removal of FPN (approx. 90%) was the highest in the saturated and partially-saturated CWs, with moderate removal (66.7%) in unsaturated systems. Noteworthy, partially-saturated CWs provided high or very high removal of all three studied substances despite their contrasting degradability under saturated and unsaturated conditions. Namely, their removal efficiencies in planted CWs were 95.9%, 94.5% and 81.6%, for BPS, KTP and FPN, respectively. The removal of the micropollutants in partially-saturated CWs was comparable or only slightly lower than in the best treatment option making it the performance all-rounder for the compounds with contrasting biodegradability properties.

Salivary biomarkers-assisted ultrasound-based differentiation of malignant and benign thyroid nodules.

BACKGROUND: The incidence of papillary thyroid cancer (PTC) is increasing annually. ultrasonography (US) is the current primary method for evaluating thyroid nodules; however, there have been persisting challenges in diagnosing borderline malignancies. This paper aimed to establish the differential diagnostic value of salivary biomarkers for thyroid nodules geared towards improving the efficacy of US. METHODS: We recruited a total of 44 PTC patients and 42 benign thyroid tumor (BTT) patients to this study. The distribution of tumor markers and thyroid hormones in saliva and serum were compared between groups; then, uni-/multi-variate logistic analyses were used to determine the risk factors of PTC. Further, we estimated the differential diagnostic value of biomarkers in thyroid nodules, especially in borderline scenarios. Finally, a multi-index diagnostic model was constructed constituting biomarkers and US. RESULTS: The distributions of serum thyroglobulin (TG), salivary triiodothyronine (T3), free-triiodothyronine (FT3), and free-thyroxine (FT4) were significantly different in BTT and PTC (P<0.05); salivary FT3 was identified as an independent risk factor for PTC. By analyzing the diagnostic accuracy of various Thyroid Imaging Reporting and Data System (TI-RADS) categories, category 4A was shown to have the lowest diagnostic accuracy (48.39%) with the largest proportion (31 people, 36.05%). In 4A patients, the K-nearest neighbor (KNN) algorithm attained the highest sensitivity of 87.50% and specificity of 100.00% among the machine learning-based multi-biomarkers models. Eventually, by combing the US with the KNN-based biomarkers model, the sensitivity and specificity reached 90.91% and 83.33%, respectively. CONCLUSIONS: Salivary biomarkers exhibit good potential in the differential diagnosis of borderline thyroid nodules and they significantly improve the prediction accuracy of the US. Additionally, we found that salivary FT3 is an independent risk factor for PTC and may be used as a key marker for PTC diagnosis.

Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China.

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People's Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan-Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts.