Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the labeling difficulty of infection areas, and the slight discrepancy between COVID-19 and other viral pneumonia in chest CT. While a few pioneering works have made significant progress, they are either demanding manual annotations of infection areas or lack of interpretability. In this paper, we report our attempt towards achieving highly accurate and interpretable screening of COVID-19 from chest CT with weak labels. We propose an attention-based deep 3D multiple instance learning (AD3D-MIL) where a patient-level label is assigned to a 3D chest CT that is viewed as a bag of instances. AD3D-MIL can semantically generate deep 3D instances following the possible infection area. AD3D-MIL further applies an attention-based pooling approach to 3D instances to provide insight into each instance's contribution to the bag label. AD3D-MIL finally learns Bernoulli distributions of the bag-level labels for more accessible learning. We collected 460 chest CT examples: 230 CT examples from 79 patients with COVID-19, 100 CT examples from 100 patients with common pneumonia, and 130 CT examples from 130 people without pneumonia. A series of empirical studies show that our algorithm achieves an overall accuracy of 97.9%, AUC of 99.0%, and Cohen kappa score of 95.7%. These advantages endow our algorithm as an efficient assisted tool in the screening of COVID-19.
Glycolysis is a typical conduit for energy metabolism in pancreatic cancer (PC) due to the hypoxic microenviroment. Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate and is considered to be a key checkpoint of anaerobic glycolysis. The aim of the present study was to explore the mechanism of interactions between hypoxia, HIF-1/2α and LDHA, and the function of LDHA on PC cells by analyzing 244 PC and paratumor specimens. It was found that LDHA was over-expressed and related to tumor stages. The result of in vitro study demonstrated that hypoxia induced LDHA expression. To explore the relationship between HIF and LDHA, chromatin immunoprecipitation assay and luciferase assay were performed. The result showed that HIF-1/2α bound to LDHA at 89bp under the hypoxic condition. Furthermore, knockdown of endogenous HIF-1α and HIF-2α decreased the LDHA expression even in the hypoxic condition, which was accompanied with a significant decrease in lactate production and glucose utilization (p < 0.01). Immunofluorescence in the 244 specimens showed that HIF-1/2α was over-expressed and associated with LDHA over-expression (p < 0.0001). Forced expression of LDHA promoted the growth and migration of PC cells, while knocking down the expression of LDHA inhibited the cell growth and migration markedly. In summary, the present study proved that HIF1/2α could activate LDHA expression in human PC cells, and high expression of LDHA promoted the growth and migration of PC cells.
Metformin, an ancient drug commonly used for treating type II diabetes, has been associated to anti-cancer capacity in a variety of developing cancers, though the mechanism remains elusive. Here, we aimed to examine the inhibitory effect of metformin in osteosarcoma. Herein, we demonstrated that metformin treatment blocked proliferation progression by causing accumulation of G2/M phase in U2OS and 143B cells. Furthermore, metformin treatment triggered programmed cell death process in osteosarcoma cell lines. Further research indicated the induction of apoptosis and autophagy triggered by metformin could remarkably attenuate after the treatment of ROS scavenger NAC and JNK inhibitor SP600125. Additionally, our results showed that NAC-suppressed JNK/c-Jun signaling pathway could have been activated through metformin treatment. Lastly, metformin could inhibit osteosarcoma growth under safe dose in vivo. Thus, we propose that metformin could induce cell cycle arrest as well as programmed cell death, including apoptosis and autophagy, through ROS-dependent JNK/c-Jun cascade in human osteosarcoma. This metformin-induced pathway provides further insights into its antitumor potential molecular mechanism and illuminates potential cancer targets for osteosarcoma.
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