Detectable EBV DNA levels and an unsatisfactory tumor response (stable disease or disease progression) after NACT serve as predictors of poor prognosis for patients with advanced-stage NPC. These findings will facilitate further risk stratification, early treatment modification, or both before CCRT.

Porcine epidemic diarrhea virus (PEDV), a member of the group of alphacoronaviruses, is the pathogen of a highly contagious gastrointestinal swine disease. The elucidation of the events associated with the intestinal epithelial response to PEDV infection has been limited by the absence of good in vitro porcine intestinal models that recapitulate the multicellular complexity of the gastrointestinal tract. Here, we generated swine enteroids from the intestinal crypt stem cells of the duodenum, jejunum, or ileum and found that the generated enteroids are able to satisfactorily recapitulate the complicated intestinal epithelium in vivo and are susceptible to infection by PEDV. PEDV infected multiple types of cells, including enterocytes, stem cells, and goblet cells, and exhibited segmental infection discrepancies compared with ileal enteroids and colonoids, and this finding was verified in vivo. Moreover, the clinical isolate PEDV-JMS propagated better in ileal enteroids than the cell-adapted isolate PEDV-CV777, and PEDV infection suppressed interferon (IFN) production early during the infection course. IFN lambda elicited a potent antiviral response and inhibited PEDV in enteroids more efficiently than IFN alpha (IFN-␣). Therefore, swine enteroids provide a novel in vitro model for exploring the pathogenesis of PEDV and for the in vitro study of the interplay between a host and a variety of swine enteric viruses. IMPORTANCE PEDV is a highly contagious enteric coronavirus that causes significant economic losses, and the lack of a good in vitro model system is a major roadblock to an in-depth understanding of PEDV pathogenesis. Here, we generated a porcine intestinal enteroid model for PEDV infection. Utilizing porcine intestinal enteroids, we demonstrated that PEDV infects multiple lineages of the intestinal epithelium and preferably infects ileal enteroids over colonoids and that enteroids prefer to respond to IFN lambda 1 over IFN-␣. These events recapitulate the events that occur in vivo. This study constitutes the first use of a primary intestinal enteroid model to investigate the susceptibility of porcine enteroids to PEDV and to determine the antiviral response following infection. Our study provides important insights into the events associated with PEDV infection of the porcine intestine and provides a valuable in vitro model for studying not only PEDV but also other swine enteric viruses.

Three novel metabolites were identified in mice after oral administration of 5-demethylniobiletin. These metabolites exhibited strong inhibitory effects against human colon cancer cells. Our results provide a first report on these bioactive metabolites and warrant further investigation on their molecular mechanism of actions.

To investigate the chemical composition and insecticidal activity of the essential oils of certain Chinese medicinal herbs and spices, the essential oils were extracted from the stem barks, leaves, and fruits of Cinnamomum camphora (L.) Presl, which were found to possess strong fumigant toxicity against Tribolium castaneum and Lasioderma serricorne adults. The essential oils of the plants were extracted by the method of steam distillation using a Clavenger apparatus. Their composition was determined by gas chromatography/mass spectrometric (GC-MS) analyses (HP-5MS column), and their insecticidal activity was measured by seal-spaced fumigation. D-camphor (51.3%), 1,8-cineole (4.3%), and α-terpineol (3.8%), while D-camphor (28.1%), linalool (22.9%), and 1,8-cineole (5.3%) were the main constituents of its fruits. The essential oils of the C. camphora all showed fumigant and contact toxicity. Other compounds exhibited various levels of bioactivities. The results indicate that the essential oils of C. camphora and its individual compounds can be considered a natural resource for the two stored-product insect management.

A total of 20,305 patients with nonmetastatic nasopharyngeal carcinoma from 1990 to 2012 were involved in this study. The overall survival (OS), progression-Purpose: Previous studies demonstrated that the radiation therapy, image technology, and the application of chemotherapy have developed in the last 2 decades. This study explored the survival trends and treatment failure patterns of patients with nonmetastatic nasopharyngeal carcinoma (NPC) treated with radiation therapy. Furthermore, we evaluated the survival benefit brought by the development of radiation therapy, image technology, and chemotherapy based on a large cohort from 1990 to 2012. Methods and Materials: Data from 20,305 patients with nonmetastatic NPC treated between 1990 and 2012 were analyzed. Patients were divided into 4 calendar periods

Inflammation plays important roles in initiation and progress of many diseases including cancers in multiple organ sites. Herein, we investigated the anti-inflammatory effects of two dietary compounds, nobiletin (NBN) and sulforaphane (SFN) in combination. Non-cytotoxic concentrations of NBN, SFN, and their combinations were studied in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophage cells. The results showed that combined NBN and SFN treatments produced much stronger inhibitory effects on the production of nitric oxide (NO) than NBN or SFN alone at higher concentrations. These enhanced inhibitory effects were synergistic based on the isobologram analysis. Western blot analysis showed that combined NBN and SFN treatments synergistically decreased iNOS and COX-2 protein expression levels and induced heme oxygenase-1 (HO-1) protein expression. Real-time PCR analysis indicated that low doses of NBN and SFN in combination significantly suppressed LPS-induced upregulation of IL-1 mRNA levels, and synergistically increased HO-1 mRNA levels. Overall our results demonstrated that NBN and SFN in combination produced synergistic effects in inhibiting LPS-induced inflammation in RAW 264.7 cells.

BackgroundDue to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning.MethodsAn endoscopic images-based nasopharyngeal malignancy detection model (eNPM-DM) consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation. Briefly, a total of 28,966 qualified images were collected. Among these images, 27,536 biopsy-proven images from 7951 individuals obtained from January 1st, 2008, to December 31st, 2016, were split into the training, validation and test sets at a ratio of 7:1:2 using simple randomization. Additionally, 1430 images obtained from January 1st, 2017, to March 31st, 2017, were used as a prospective test set to compare the performance of the established model against oncologist evaluation. The dice similarity coefficient (DSC) was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images, by comparing automatic segmentation with manual segmentation performed by the experts.ResultsAll images were histopathologically confirmed, and included 5713 (19.7%) normal control, 19,107 (66.0%) nasopharyngeal carcinoma (NPC), 335 (1.2%) NPC and 3811 (13.2%) benign diseases. The eNPM-DM attained an overall accuracy of 88.7% (95% confidence interval (CI) 87.8%–89.5%) in detecting malignancies in the test set. In the prospective comparison phase, eNPM-DM outperformed the experts: the overall accuracy was 88.0% (95% CI 86.1%–89.6%) vs. 80.5% (95% CI 77.0%–84.0%). The eNPM-DM required less time (40 s vs. 110.0 ± 5.8 min) and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background, with an average DSC of 0.78 ± 0.24 and 0.75 ± 0.26 in the test and prospective test sets, respectively.ConclusionsThe eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant, and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.

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