Estimating deoxynivalenol contents of wheat samples containing different levels of Fusarium-damaged kernels by diffuse reflectance spectrometry and partial least square regression

Fusarium head blight is a fungal disease causing yield losses and mycotoxin contamination in wheat and other cereals. Wheat kernels (cultivar Ritmo) were sampled in 2001, 2002, 2003, and 2006 and Fusarium-damaged kernels were separated from sound grain based on visual assessment. Subsequently, grain lots containing 0, 20, 40, 60, 80, and 100% of damaged kernels were compiled. Each lot was split and the spectrometric reflectance (wavelengths 350-2500 nm) was measured using subgroup one, while the concentration of the mycotoxin deoxynivalenol (DON) was determined by high-performance liquid chromatography in subgroup two. DON concentrations in batches classified as sound were not significantly different from 0. Estimating DON contents from the percentage of Fusarium-damaged kernels was impeded by vast variability, resulting in a coefficient of determination of 0.49. Using spectrometric data subjected to partial least square regression allowed estimating DON contents with higher accuracy, in particular at elevated percentages of damaged kernels. The coefficient of determination was 0.84 for the relationship between DON contents estimated based on spectrometric data and the DON contents measured. The intercept of a regression line fitted through a plot of estimated versus measured DON contents was 0.89 ± 3.61 mg/kg. Since intercept + standard error was larger than the actual legal limit (1.25 mg DON per kg dry grain in the European Union), the spectrometric procedure was still not precise enough to allow a reliable separation of grain samples with DON contents below 1.25 mg/kg from samples with DON contents above the limit. However, spectrometric data also allowed estimating the DON content of the average damaged kernel within a given lot composed of sound and damaged kernels, which is probably the reason for the reduction of the fraction of unexplained variance by 35% compared to the visual approach and illustrates that spectrometric approaches can make a contribution to reducing DON contents of wheat grain.     

Comparing Source-Based and Gist-Based False Recognition in Aging and Alzheimer's Disease.

This study examined 2 factors contributing to false recognition of semantic associates: errors based on confusion of source and errors based on general similarity information or gist. The authors investigated these errors in patients with Alzheimer's disease (AD), age-matched control participants, and younger adults, focusing on each group's ability to use recollection of source information to suppress false recognition. The authors used a paradigm consisting of both deep and shallow incidental encoding tasks, followed by study of a series of categorized lists in which several typical exemplars were omitted. Results showed that healthy older adults were able to use recollection from the deep processing task to some extent but less than that used by younger adults. In contrast, false recognition in AD patients actually increased following the deep processing task, suggesting that they were unable to use recollection to oppose familiarity arising from incidental presentation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Viability of the etiologic agent of the Lethargic Crab Disease, Exophiala cancerae, during cooking of the mangrove-land crab: Does this traditional dish represent a risk to humans?

One of the most typical seafood dishes in the Brazilian coastal areas is the cooked mangrove-land crab, Ucides cordatus (L.). Mortality events of U. cordatus were reported from a large extension for over 15 years, especially in the Northeast region. These mortalities are known to be triggered by an epizooty known as Lethargic Crab Disease, for which the putative etiological agent is a new species of black yeast, Exophiala cancerae De Hoog, Vicente, Najafzadeh, Harrak, Seyedmousavi, & Boeger. Although there is no compelling evidence that this fungus may represent a zoonosis, there is great public concern regarding consumption of crabs from affected regions. Thus, this study evaluates the efficiency of cooking procedures on the inactivation of the etiologic agent. The variation of the internal temperature of crabs and tests of the activity of E. cancerae to temperature under simulated cooking condition were determined and the results were analyzed combined. The results indicate that crab’s core body attains the boiling water temperature about an average of 14 min after exposition. Furthermore, short intervals of exposure (30 s) to such boiling temperatures were sufficient to warrant inactivation of E. cancerae. Thus, the traditional mode of preparation of the mangrove-land crab is sufficient to inactivate the pathologic agent and the consumption of sick or carrier animals should not represent a potential public health risk.     

数据挖掘技术在健康管理系统中的应用

该文研究了基于决策树的ID3算法,针对ID3算法应用在健康管理系统中存在的问题,提出了一个改进的算法,并利用改进算法对居民健康档案数据进行慢性病诱因的数据挖掘,挖掘结果证明,改进算法的决策树在健康管理系统中的数据挖掘是有效的。     

Tn and sialyl-Tn antigens,aberrant O-glycomics as human disease markers

In many different human disorders, the cellular glycome is altered. An interesting but poorly understood alteration occurs in the mucin-type O-glycome, in which there is aberrant expression of the truncated O-glycans Tn (GalNAcα1-Ser/Thr) and its sialylated version sialyl-Tn (STn) (Neu5Acα2,6GalNAcα1-Ser/Thr). Both Tn and STn are tumor-associated carbohydrate antigens and tumor biomarkers, since they are not expressed normally and appear early in tumorigenesis. Moreover, their expression is strongly associated with poor prognosis and tumor metastasis. The Tn and STn antigens are also expressed in other human diseases and disorders, such as Tn syndrome and IgA nephropathy. The major pathological mechanism for expression of the Tn and STn antigens is compromised T-synthase activity, resulting from alteration of the X-linked gene that encodes for Cosmc, a molecular chaperone specifically required for the correct folding of T-synthase to form active enzyme. This review will summarize our current understanding of the Tn and STn antigens in terms of their biochemistry and role in pathology.     

常见疾病自我诊断系统的设计与实现

针对目前公众自行购买非处方药治疗常见轻微疾病的过程中存在的问题,提出了开发基于Web的常见疾病自我诊断系统.该系统采用带有可信度的产生式规则表示法来表示常见病诊断知识,采用正反向混合推理模式,通过可信度的传递以及结论阈值的设定,实现了疾病诊断的数字化.经测试,系统诊断准确度达83%.系统对完善常见病诊断方式、指导公众安全使用非处方药具有积极的作用.     

DB-TASNet for disease diagnosis and lesion segmentation in medical images

Deep learning algorithms have been successfully used in the field of medical image analysis and have greatly improved application of intelligent algorithms to medical diagnosis. However, existing deep-learning-based diagnostic methods still suffer from several drawbacks: (1) In most medical image multi-tasking methods, focus segmentation and disease classification are often performed linearly, resulting in excessive reliance on the final results of focus segmentation. (2) The computational cost of the traditional attention mechanism for performing the segmentation task is very high and the convolutional architecture cannot be used to model long-distance dependencies, which in turn affects the segmentation accuracy. To address these issues, we propose a disease diagnosis and lesion segmentation model, Dual-Branch with Transformer Axial-attention Segmentation Net (DB-TASNet). DB-TASNet is built by the DenseNet-121 classification network and U-Net segmentation network improved using an axial-attention transformer model. Moreover, DB-TASNet also includes a lesion integration module to integrate segmentation results with the classification network in order to increase its attention to lesions and improve the diagnosis results. Experimental results on the Pneumothorax dataset provided by the Society for Imaging Informatics in Medicine (SIIM) show that the average AUC of the DB-TASNet classification task reaches 0.939, and the DICE coefficient of the segmentation task reaches 0.886. Such performance suggests that the proposed model may provide an efficient and effective diagnosis tool for medical personnel.     

浅析疾控系统的网络安全

加强疾控系统计算机网络安全与管理是一项亟待解决的任务.本文针对疾控系统的网络安全进行了分析,列举出影响疾控网络安全的因素,并从网络安全技术和管理两个方面提出了自己的观点.     

一种基于图像的农作物病虫害诊断专家系统研究

相当多的植物病虫害具有类似的症状．使得非专业化人员很难准确地区分开这些植物病虫害。通过与病虫害图片或多个症状相似的案例进行比较．在很大程度上能帮助非专业化人员克服病虫害的识别难题。该方法通过图像显示效果让用户能够识别出任何疾病。并迅速做出正确的决策,选择正确的治理方法,同时也提高用户对植物病虫害诊断的理解水平。