RESUMEN

Papillary thyroid carcinoma (PTC), accounting for approximately 85% cases of thyroid cancer, is a common endocrine tumour with a relatively low mortality but an alarmingly high rate of recurrence or persistence. Long non-coding RNAs (lncRNAs) is emerging as a critical player modulating diverse cellular mechanisms correlated with the progression of various cancers, including PTC. Herein, we aimed to investigate the role of lncRNA SLC26A4-AS1 in regulating autophagy and tumour growth during PTC progression. Initially, ITPR1 was identified by bioinformatics analysis as a differentially expressed gene. Then, Western blot and RT-qPCR were conducted to determine the expression of ITPR1 and SLC26A4-AS1 in PTC tissues and cells, both of which were found to be poorly expressed in PTC tissues and cells. Then, we constructed ITPR1-overexpressing cells and revealed that ITPR1 overexpression could trigger the autophagy of PTC cells. Further, we performed a series of gain- and loss-of function experiments. The results suggested that silencing of SLC26A4-AS1 led to declined ITPR1 level, up-regulation of ETS1 promoted ITPR1 expression, and either ETS1 knockdown or autophagy inhibitor Bafilomycin A1 could mitigate the promoting effects of SLC26A4-AS1 overexpression on PTC cell autophagy. In vivo experiments also revealed that SLC26A4-AS1 overexpression suppressed PTC tumour growth. In conclusion, our study elucidated that SLC26A4-AS1 overexpression promoted ITPR1 expression through recruiting ETS1 and thereby promotes autophagy, alleviating PTC progression. These finding provides insight into novel target therapy for the clinical treatment of PTC.

Asunto(s)

RESUMEN

Head pose classification is an important part of the preprocessing process of face recognition, which can independently solve application problems related to multi-angle. But, due to the impact of the COVID-19 coronavirus pandemic, more and more people wear masks to protect themselves, which covering most areas of the face. This greatly affects the performance of head pose classification. Therefore, this article proposes a method to classify the head pose with wearing a mask. This method focuses on the information that is helpful for head pose classification. First, the H-channel image of the HSV color space is extracted through the conversion of the color space. Then use the line portrait to extract the contour lines of the face, and train the convolutional neural networks to extract features in combination with the grayscale image. Finally, stacked generalization technology is used to fuse the output of the three classifiers to obtain the final classification result. The results on the MAFA dataset show that compared with the current advanced algorithm, the accuracy of our method is 94.14% on the front, 86.58% on the more side, and 90.93% on the side, which has better performance.

RESUMEN

AIM: Myocardial injury is inevitable during cardiac surgical procedures and reducing myocardial injury in patients with CPB surgery is the focus of current research. Papaverine is accepted as an ideal coronary vasodilator. This study was to estimate the effect of papaverine perfusion via the aortic root before heart re-beating on patients undergoing heart valve replacement. METHODS: All the patients enrolled in this study were admitted during 2013-2015. The basic clinical characteristics of the patients preoperative, intraoperative, and postoperative were compared. The immunochemistry assays and enzyme-linked immunosorbent assay (ELISA) were performed to assess the serum biomarkers. Western blot and immunohistochemistry (IHC) were undertaken to detect the expression of associated proteins. RESULTS: Patients receiving papaverine perfusion via the aortic root before heart re-beating during heart valve replacement surgery under CPB showed less extracorporeal circulation time and CPB time, higher automatic heartbeat recovery rate, less mechanical ventilation time, shorter ICU and in-hospital stay, less leak of cTnI and CK-MB, and weaker inflammatory response than the patients in control group. In addition, the protein expression of IL-6/8/10 and TNF-α was reduced by the perfusion of papaverine. The IHC staining for NFκB was depressed in papaverine group. CONCLUSION: Papaverine perfusion presented positive effect during valve replacement; this cardioprotective effect may be associated with inhibition of inflammatory response and NF-κB. These findings provided new clues for reduction of myocardial injury during cardiac surgery.

Asunto(s)

RESUMEN

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

Asunto(s)