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Background Various combinations of ultrasonographic (US) characteristics are increasingly utilized to classify thyroid nodules. But they lack theories, and heavily depend on radiologists’ experience, and cannot correctly classify thyroid nodules. Hence, our main purpose of this manuscript is to select the US characteristics significantly associated with malignancy and to develop an efficient scoring system for facilitating ultrasonic clinicians to correctly identify thyroid malignancy. Methods A logistic regression (LR) model is utilized to identify the potential thyroid malignancy, and the least absolute shrinkage and selection operator (LASSO) method is adopted to simultaneously select US characteristics significantly associated with malignancy and estimate parameters in LR model. Based on the selected US characteristics, we calculate the probability for each of thyroid nodules via random forest (RF) and extreme learning machine (ELM), and develop a scoring system to classify thyroid nodules. For comparison, we also consider eight state-of-the-art methods such as support vector machine (SVM), neural network (NET), etc. The area under the receiver operating characteristic curve (AUC) is employed to measure the accuracy of various classifiers. Results The US characteristics: nodule size, AP/T≥1, solid component, micro-calcifications, hackly border, hypoechogenicity, presence of halo, unclear border, irregular margin, and central vascularity are selected as the significant predictors associated with thyroid malignancy via the LASSO LR (LLR). Using the developed scoring system, thyroid nodules are classified into the following four categories: benign, low suspicion, intermediate suspicion, and high suspicion, whose rates of malignancy correctly identified for RF (ELM) method on the testing dataset are 0.0% (4.3%), 14.3% (50.0%), 58.1% (59.1%) and 96.1% (97.7%), respectively. Conclusion LLR together with RF performs better than other methods in identifying malignancy, especially for abnormal nodules, in terms of risk scores. The developed scoring system can well predict the risk of malignancy and guide medical doctors to make management decisions for reducing the number of unnecessary biopsies for benign nodules.

The overactivation of NLRP3 inflammasome in intestinal epithelial cells (IECs) is among the important reasons for severe inflammation in ulcerative colitis (UC). We found that heat shock transcription factor 2 (HSF2), which is highly expressed in UC, could inhibit the activation of NLRP3 inflammasome and reduce IL-1β in IECs, but the mechanisms were still not clear. It has been reported that HSP72 regulated by HSF2 can enhance the mitophagy mediated by Parkin. The number of damaged mitochondria and the mitochondrial derived ROS (mtROS) can be reduced by mitophagy, which means the activity of NLRP3 inflammasome is inhibited. Therefore, we speculate that HSF2 might regulate the activation of NLRP3 inflammasome of IECs in UC through the mitophagy mediated by Parkin. This study proves that the number of damaged mitochondria in IECs, the level of mitophagy, and the level of ROS in intestinal mucosa are positively correlated with the severity of UC. In mice and cells, mitophagy was promoted by HSF2 through the PARL/PINK1/Parkin pathway. This study reveals the potential mechanisms of HSF2 decreasing mtROS of IECs in UC.

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Objective and backgroundThe overactivation of NLRP3 inflammasome is a critical factor for ulcerative colitis (UC). We found that heat shock transcription factor 2 (HSF2), which is highly expressed in UC, could inhibit the activation of NLRP3 inflammasome and reduce IL-1β in intestinal epithelial cells(IECs), but the mechanisms were still unclear. We aimed to elucidate the mechanisms of HSF2 inhibiting the activation of NLRP3 inflammasome of IECs.Methods: TEM was used to detect the number of damaged mitochondria and the level of mitophagy in intestinal mucosa of UC patients, healthy controls, mice and Caco-2 cells. ROS levels were detected by immunofluorescence or flow cytometry. RT-PCR, WB and immunohistochemistry were used to detect the level of PARL, PINK1 and Parkin.Results: The levels of mitophagy and ROS in intestinal mucosa of UC patients were positively correlated with disease activity. In IECs, after downregulation of HSF2, mitophagy reduced and number of damaged mitochondria and ROS increased, while overexpression of HSF2 showed opposite results. In addition, HSF2 might regulate mitophagy through PARL/PINK1/Parkin signaling pathway.Conclusions:HSF2 may promote mitophagy and decrease the level of mtROS through the PARL/PINK1/Parkin signaling pathway, which might be a potential mechanism of HSF2 inhibiting inflammation in UC.