RESUMEN
Machine learning (ML) is an innovative method that is widely used in data prediction. Predicting the COVID-19 distribution using ML is essential for urban security risk assessment and governance. This study uses conditional generative adversarial network (CGAN) to construct a method to predict the COVID-19 hotspot distribution through urban texture and business formats and establishes a relationship between urban elements and COVID-19 so that machines can automatically predict the epidemic hotspots in cities. Taking Macau as an example, this method is used to determine the correlation between the urban texture and business hotspots of Macau and the new epidemic hotspot clusters. Different types of samples afforded different epidemic prediction accuracies. The results show the following: (1) CGAN can accurately predict the distribution area of COVID-19, and the accuracy can exceed 70%. (2) The results of predicting the COVID-19 distribution through urban texture and POI data of hospitals and stations are the best, with an accuracy of more than 60% in experiments in different regions of Macau. (3) The proposed method can also predict other areas in the city that may be at risk of COVID-19 and help urban epidemic prevention and control.
RESUMEN
Pancreatic cancer is an aggressive malignancy and is unresponsive to conventional chemotherapies. Parthenolide, a sesquiterpene lactone isolated from feverfew, has exhibited potent anticancer effects against various cancers. The purpose of this report was to investigate the effect and underlying mechanism of parthenolide in human pancreatic cancer Panc-1 and BxPC3 cells. The results demonstrated that parthenolide suppressed the growth and induced apoptosis of Panc-1 and BxPC3 pancreatic cancer cells with the half maximal inhibitory concentration (IC50) ranging between 7 and 9 µM after 24 h of treatment. Significant autophagy was induced by parthenolide treatment in pancreatic cancer cells. Parthenolide treatment concentration-dependently increased the percentage of autophagic cells and significantly increased the expression levels of p62/SQSTM1, Beclin 1, and LC3II in Panc-1 cells. Punctate LC3II staining confirmed autophagy. Furthermore, inhibiting autophagy by chloroquine, 3-methyladenine, or LC3II siRNA significantly blocked parthenolide-induced apoptosis, suggesting that parthenolide induced apoptosis through autophagy in this study. In conclusion, these studies established that parthenolide inhibits pancreatic cell growth by autophagy-mediated apoptosis. Data of the present study suggest that parthenolide can serve as a potential chemotherapeutic agent for pancreatic cancer.
RESUMEN
A 42-year-old male patient was admitted to the Department of General Surgery of The First Affiliated Hospital of Henan University of Science and Technology (Luoyang, China) presenting with abdominal discomfort. Enhanced computed tomography of the abdomen revealed a 15.1×7.0-cm, enhanced, double-spherical, exogenous, solid tumor originating from the left lateral hepatic lobe, in addition to a 4.3×4.2-cm mass in the mid portion of the left kidney. Pre-operative imaging analysis resulted in the diagnosis of double cancer, consisting of hepatocellular carcinoma (HCC) and renal cell carcinoma (RCC). The patient subsequently underwent left hemihepatectomy and left nephrectomy. Histological examination confirmed that the tumor originating from the left lateral hepatic lobe was HCC, and the tumor arising from the mid portion of the left kidney was clear cell RCC (ccRCC). The post-operative follow-up was uneventful. To the best of our knowledge, the present case is the first of its kind to describe the resection of synchronous double cancer, consisting of primary HCC and ccRCC.