Current Status of Human Papillomavirus-Related Head and Neck Cancer: From Viral Genome to Patient Care

Virologica Sinica - Human papillomavirus (HPV) infection identified as a definitive human carcinogen is increasingly being recognized for its role in carcinogenesis of human cancers. Up to...     

雪腐核盘菌菌核的萌发条件与致死温度

菌核是核盘菌Sclerotinia spp.在土壤中的主要存活形式和菌核病的主要初侵染源,在土壤中可存活8年以上,其数量和存活状况直接影响着菌核病的发生和危害程度。本研究以雪腐核盘菌Sclerotinia nivalis菌株SS-TB为材料,分析了菌核萌发的影响因素、致死温度以及土壤温度对菌核存活的影响。结果表明,未成熟菌核较成熟菌核更容易萌发;菌核萌发的最佳温度为20-25℃、pH为3.0-4.0、土壤含水量为20%-45%。菌核长时间浸泡水中对其存活不利,浸泡30d以后,存活率开始急剧下降,至47d时存活率为0。雪腐核盘菌菌核具有较强的耐高温特性,随着温度和处理时间的增加,菌核萌发率呈下降趋势。菌核在水浴中85℃ 5min、80℃ 10min、75℃ 10min、70℃ 30min、65℃ 120min、60℃ 180min时全部丧失活力。在土壤温度30℃和35℃处理5周、40℃和45℃处理4周时菌核全部失去活力。该研究结果为通过水旱轮作和土壤高温处理来防治西洋参菌核病提供了理论基础。     

三氟苯嘧啶不同种子处理方式对稻飞虱的控制效应

为探明三氟苯嘧啶不同种子处理方式对稻飞虱的田间防治效果、防治时长以及对稻田蜘蛛和水稻的安全性,为该药剂种子处理防治稻飞虱提供科学依据,本研究设置10％三氟苯嘧啶悬浮剂按不同浓度(0.375、0.75、1.125和1.5 g a.i./kg种子)对水稻种子分别以干种子拌种(干拌)、清水浸种后拌种(湿拌)和药剂浸种3种方式,清水处理作为空白对照.结果表明,3种处理方式下的水稻发芽率和出苗率均与空白对照间无显著差异,播种后100 d,各浓度对稻飞虱的防治效果均在90％以上;当药剂浓度相同时,干拌与湿拌防治时长要优于药剂浸种;不同浓度三氟苯嘧啶药剂处理在3种方式下稻田蜘蛛种群数量均略低于空白对照田蜘蛛数量.因此,水稻生产中使用三氟苯嘧啶0.375～1.5 g a.i./kg种子干拌或湿拌处理,可有效降低田间稻飞虱种群数量,对天敌蜘蛛影响较小,对水稻种子发芽、出苗安全,可在水稻生产中推广使用.     

The long-run heterogeneous effects of a cholera pandemic on stature: Evidence from industrializing Japan

The recent COVID-19 pandemic poses the general question on how infectious diseases can persistently affect human health. A growing body of literature has found a significant amount of evidence on the long-term adverse effects of infectious diseases, such as influenza, typhoid fever, and yellow fever. However, we must be careful about the fact that little is known about the long-term consequences of the acute diarrheal disease pandemic cholera – Vibrio cholerae bacillus – which still threatens the health of the population in many developing countries. To bridge this gap in the body of knowledge, we utilized unique census-based data on army height at age 20 in early 20th-century Japan, with a difference-in-differences estimation strategy using regional variation in the intensity of cholera pandemics. We found that early-life exposure to a cholera pandemic had heterogeneous stunting effects on the final height of men; the magnitude of the stunting effects increased as the intensity of exposure increased.     

Prediction of multi-criteria optimization (MCO) parameter efficiency in volumetric modulated arc therapy (VMAT) treatment planning using machine learning (ML)

PurposeTo predict the impact of optimization parameter changes on dosimetric plan quality criteria in multi-criteria optimized volumetric-modulated-arc therapy (VMAT) planning prior to optimization using machine learning (ML).MethodsA data base comprising a total of 21,266 VMAT treatment plans for 44 cranial and 18 spinal patient geometries was generated. The underlying optimization algorithm is governed by three highly composite parameters which model a combination of important aspects of the solution. Patient geometries were parametrized via volume- and shape properties of the voxel objects and overlap-volume histograms (OVH) of the planning-target-volume (PTV) and a relevant organ-at-risk (OAR). The impact of changes in one of the three optimization parameters on the maximally achievable value range of five dosimetric properties of the resulting dose distributions was studied. To predict the extent of this impact based on patient geometry, treatment site, and current parameter settings prior to optimization, three different ML-models were trained and tested. Precision-recall curves, as well as the area-under-curve (AUC) of the resulting receiver-operator-characteristic (ROC) curves were analyzed for model assessment.ResultsSuccessful identification of parameter regions resulting in a high variability of dosimetric plan properties depended on the choice of geometry features, the treatment indication and the plan property under investigation. AUC values between 0.82 and 0.99 could be achieved. The best average-precision (AP) values obtained from the corresponding precision/recall curves ranged from 0.71 to 0.99.ConclusionsMachine learning models trained on a database of pre-optimized treatment plans can help finding relevant optimization parameter ranges prior to optimization.     

The prognostic value of CD3+ tumor-infiltrating lymphocytes for stage II colon cancer according to use of adjuvant chemotherapy: A large single-institution cohort study

BackgroundHigh tumor infiltrating lymphocytes (TILs) density was previously shown to be associated with favorable prognosis for patients with colon cancer (CC). However, the impact of TILs on overall survival (OS) of stage II CC patients who received adjuvant chemotherapy (ADJ) or not (no-ADJ) is unknown. We assessed the prognostic value of CD3+ TILs in stage II CC patients according to whether they had ADJ or not.MethodsPatients treated with curative surgery for stage II CC (2002–2013) were selected from the Santa Maria alle Scotte Hospital registry. TILs at the invasive front, center of tumor, and stroma were determined by immunohistochemistry and manually quantified as the rate of TILs/total tissue areas. High TILs (H-TILs) was defined as >20%. Patients were categorized as high or low TILs (L-TILs) and ADJ or no-ADJ.ResultsOf the 678 patients included, 137 (20%) received ADJ and 541 (80%) did not. The distribution of the 4 groups were: 16% (L-TIL/ADJ), 64% (L-TIL/no-ADJ), 5% (H-TIL/ADJ), 15% (H-TIL/no-ADJ). Compared to H-TILs/no-ADJ, ADJ patients showed a significantly increased OS (P<.01) regardless of the TILs rate whereas L-TILs/no-ADJ had significantly decreased OS and higher risk of death (HR=1.41; 95% CI, 1.06–1.88; P<.0001). On multivariable analysis, the unfavorable prognostic value of L-TILs (vs. H-TILs) for no-ADJ patients was confirmed (HR=1.36; 95% CI 1.02, 1.82; P=.0373).ConclusionLow CD3+ TILs rate was associated with shorter OS in those with stage II colon cancer who did not receive adjuvant therapy. Low CD3+ TILs could be considered an additional risk factor for still ADJ-untreated stage II CC patients, which could facilitate clinical decision making.     

In silico molecular docking analysis for repurposing approved antiviral drugs against SARS-CoV-2 main protease

Developing a safe and effective antiviral treatment takes a decade, however, when it comes to the coronavirus disease (COVID-19), time is a sensitive matter to slow the spread of the pandemic. Screening approved antiviral drugs against COVID-19 would speed the process of finding therapeutic treatment. The current study examines commercially approved drugs to repurpose them against COVID-19 virus main protease using structure-based in-silico screening. The main protease of the coronavirus is essential in the viral replication and is involved in polyprotein cleavage and immune regulation, making it an effective target when developing the treatment. A Number of approved antiviral drugs were tested against COVID-19 virus using molecular docking analysis by calculating the free natural affinity of the binding ligand to the active site pocket and the catalytic residues without forcing the docking of the ligand to active site. COVID-19 virus protease solved structure (PDB ID: 6LU7) is targeted by repurposed drugs. The molecular docking analysis results have shown that the binding of Remdesivir and Mycophenolic acid acyl glucuronide with the protein drug target has optimal binding features supporting that Remdesivir and Mycophenolic acid acyl glucuronide can be used as potential anti-viral treatment against COVID-19 disease.