Purpose: The study is to describe the clinical characteristics, outcomes and follow-up of cancer patients with COVID-19. Methods: Clinical records, demographic data, signs and symptoms, laboratory results, cytokine pro les, chest CT scans, comorbidities, treatments, clinical outcomes, and RT-PCR of SARS-CoV-2 after discharge were retrospectively collected for fty-six cancer patients with laboratory-con rmed COVID-19 pneumonia who were admitted to

IMPORTANCE Health care workers (HCWs) have high infection risk owing to treating patients with coronavirus disease 2019 (COVID-19). However, research on their infection risk and clinical characteristics is limited. OBJECTIVES To explore infection risk and clinical characteristics of HCWs with COVID-19 and to discuss possible prevention measures.

Fumonisin B1 (FB1) is reportedly the causative agent of several animal mycotoxicoses and has etiologically been linked to human oesophageal and liver cancer in certain areas of South Africa and China. To study a possible relationship between exposure to FB1 and human cancer risk, the current status of FB1 contamination in food samples in Huaian and Fusui, where incidences of oesophageal and liver cancer are amongst the highest in China, was investigated. A total of 259 corn samples were collected from individual households in five villages of different townships in Huaian during December 2001 and December 2002, and in four villages of different townships in Fusui during May 2001 and May 2002. Corn samples were also collected from individual households in two villages in Huantai, an area with low incidences of both cancers. Enzyme-linked immunosorbent assays (ELISA) and immunoaffinity-HPLC methods were used for FB1 analysis. In corn samples from Huaian, FB1 was detectable in 95.7% (112/117) of the samples, with an average of 2.84 mg kg-1 (range 0.1-25.5 mg kg-1). FB1 was detected in 83.0% (78/94) of the Fusui samples, with an average of 1.27 mg kg-1 (range 0.1-14.9 mg kg-1), and in 83.3% (40/48) of Huantai samples, with an average of 0.65 mg kg-1 ranging from 0.1 to 5.7 mg kg-1. The level of FB1 in corn samples from Huaian was significantly higher than from Huantai (P < 0.001). In addition, 47 of 112 (42.0%) positive Huaian samples had FB1 level greater than 2.0 mg kg-1, which was significantly higher than 10.0% (4/40) of Huantai samples (P < 0.001). Furthermore, variations were found between samples collected in different years and different villages. The high contamination rates of FB1 found in food from these areas, along with previous reports, suggest a possible contributing role of FB1 in human esophageal- and hepato-carcinogenesis.

Background: Continuous exposure to various environmental carcinogens and genetic polymorphisms of xenobiotic-metabolizing enzymes (XME) are associated with many types of human cancers, including esophageal squamous cell carcinoma (ESCC). Huaian, China, is one of the endemic regions of ESCC, but fewer studies have been done in characterizing the risk factors of ESCC in this area. The aims of this study is to evaluate the etiological roles of demographic parameters, environmental and food-borne carcinogens exposure, and XME polymorphisms in formation of ESCC, and to investigate possible gene-gene and gene-environment interactions associated with ESCC in Huaian, China.

Background Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics. Methods We trained a U-Net-based model on unenhanced chest CT scans obtained from 2447 patients admitted to Tongji Hospital (Wuhan, China) between Feb 1, 2020, and March 3, 2020 (1647 patients with RT-PCR-confirmed COVID-19 and 800 patients without COVID-19) to segment lung opacities and alert cases with COVID-19 imaging manifestations. The ability of artificial intelligence (AI) to triage patients suspected to have COVID-19 was assessed in a large external validation set, which included 2120 retrospectively collected consecutive cases from three fever clinics inside and outside the epidemic centre of Wuhan (Tianyou Hospital [Wuhan, China; area of high COVID-19 prevalence], Xianning Central Hospital [Xianning, China; area of medium COVID-19 prevalence], and The Second Xiangya Hospital [Changsha, China; area of low COVID-19 prevalence]) between Jan 22, 2020, and Feb 14, 2020. To validate the sensitivity of the algorithm in a larger sample of patients with COVID-19, we also included 761 chest CT scans from 722 patients with RT-PCR-confirmed COVID-19 treated in a makeshift hospital (Guanggu Fangcang Hospital, Wuhan, China) between Feb 21, 2020, and March 6, 2020. Additionally, the accuracy of AI was compared with a radiologist panel for the identification of lesion burden increase on pairs of CT scans obtained from 100 patients with COVID-19. Findings In the external validation set, using radiological reports as the reference standard, AI-aided triage achieved an area under the curve of 0·953 (95% CI 0·949–0·959), with a sensitivity of 0·923 (95% CI 0·914–0·932), specificity of 0·851 (0·842–0·860), a positive predictive value of 0·790 (0·777–0·803), and a negative predictive value of 0·948 (0·941–0·954). AI took a median of 0·55 min (IQR: 0·43–0·63) to flag a positive case, whereas radiologists took a median of 16·21 min (11·67–25·71) to draft a report and 23·06 min (15·67–39·20) to release a report. With regard to the identification of increases in lesion burden, AI achieved a sensitivity of 0·962 (95% CI 0·947–1·000) and a specificity of 0·875 (95 %CI 0·833–0·923). The agreement between AI and the radiologist panel was high (Cohen's kappa coefficient 0·839, 95% CI 0·718–0·940). Interpretation A deep learning algorithm for triaging patients with suspected COVID-19 at fever clinics was developed and externally validated. Given its high accuracy across populations with varied COVID-19 prevalence, integration of this system into the standard clinical workflow could expedite identification of chest CT scans with imaging indications of COVID-19. Funding Special Project for Emergency of the Science and Technology Department of Hubei Province, China.

BackgroundUntil now, little research concerning the lipid-lowering and anti-obesity functions of garlic oil and onion oil has been performed. The objective of this study was to explore the effects of garlic oil and onion oil on serum lipid levels in hyperlipidemia model rats, to provide a scientific basis for the prevention of hyperlipidemia through a dietary approach, and to explore the potential health benefits of garlic and onion.MethodNinety-six male Sprague-Dawley rats were randomly allocated into eight groups based on their body weight and serum levels of triglycerides (TG) and total cholesterol (TC). The rats received repeated oral administration of volatile oils extracted from garlic and onion for 60 days. Serum lipids and parameters of obesity were examined.ResultsThe volatile oils suppressed the HFD-induced body weight gain and tended to decrease adipose tissue weight. The oils decreased the levels of TG, TC and LDL-C and increased the serum level of HDL-C compared with the rats in the hyperlipidemia model groups (P < 0.05). The oils were also effective at improving the lipid profile and alleviating hepatic steatosis.ConclusionOur results implied that garlic oil and onion oil have anti-obesity properties that can counteract the effects of an HFD on body weight, adipose tissue weight, and serum lipid profiles.Electronic supplementary materialThe online version of this article (10.1186/s12986-018-0275-x) contains supplementary material, which is available to authorized users.

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Better understanding of esophageal precancerous lesions (EPL) can inform prevention strategies for esophageal squamous cell carcinoma (ESCC). Here, a cross-sectional epidemiologic study based on the Early Diagnosis and Early Treatment Project of Esophageal Cancer database from 2011 to 2017 was performed to fully investigate and characterize the epidemiology of EPL in rural Huai'an District. Data of 11,518 participants ages 35-75 years were collected through face-to-face interviews by questionnaire. Participants underwent a routine endoscopy examination, tissues were biopsied, and diagnosed according to the histologic criteria of dysplasia. Unconditional univariate and multivariate logistic regression analyses were performed to obtain crude and adjusted odds ratios and corresponding 95% confidence intervals, respectively. A total of 667 subjects were diagnosed with EPL. Factors associated with an increased risk of EPL included: drinking shallow well water and surface water, irregular diet, excessive smoking, exposure to secondhand smoke, consumption of corn, corn flour, pickled food, fried food, and hot food, and having a history of digestive system diseases. In addition, liquor use, but not other alcohol types, contributed to risk of EPL. Consumption of deep well water and vegetables, fruits, and animal livers were associated with lower EPL risk. This study suggested a completely distinct pattern that alcohol use plays only a minor role in EPL and excessive tobacco use shows a significant association in rural Huai'an District, while eating habits and environmental exposure may be the dominant factors. This work may be promising to provide scientific evidence to support primary prevention of ESCC in this region.