Medical waste management and environmental assessment in the Rio University Hospital,Western Greece

At this study a multi-criteria model was developed to examine the available procedures, techniques and methods of handling infectious waste in the large healthcare unit of University Regional General Hospital of Patras, Western Greece. Particularly, this study examined the: a) current legislation and Directives issued for medical waste management at Greece and among the other EU-members, b) contribution of healthcare wastes (HCW) generation rate on social and economic parameters in selected European countries, c) available procedures, techniques, and methods upon the disposal of infectious wastes at the healthcare studied, and, d) propositions for integrated management of such hazardous wastes. Specifically, the Analytic Hierarchy Process (AHP) methodology was applied under pair wise comparison matrices in two stages: 1) the scale factors and the indicators, and 2) the criteria and their sub–criteria. The assessment of these pair wise matrices included the indicators and the sub–criteria. Subsequently, two pair wise comparison matrices, upon a) the “Fulfillment of environmental objectives” indicator and b) the “Energy consumption” sub criterion, were denoted. The AHP methodology yielded good results; however there is still space of improving the environmental performance. The normalized relative weights obtained for the criteria and sub criteria motivated specific actions that have to be handled. Particularly, the results indicated a very good value in environmental management criteria due the values obtained for the commitment towards the environmental policy standards and the waste management procedures. However, further improvements on staff awareness (such as development programs to enhance sensitivity) and more green purchasing suppliers, should be further addressed.     

多种放射性肺损伤动物模型的建立和效应评价研究

放射性肺损伤是胸部肿瘤放疗后常见并发症,随着对放射性肺炎研究不断深入,如何为基础研究和药物干预寻求最佳的动物模型和效应评价已成为当前亟待解决的难题之一。通过检索近10年文献,对不同放射性肺损伤模型动物及放射部位的选择、照射剂量的确定、照射方法的比较和动物模型效应评价进行了对比研究,以期寻找建立放射性肺损伤动物模型的稳定方法和较为明确的效应机制,为防护和减缓放射性肺损伤的发生发展而进行的基础研究和药物研制提供可靠的方法。     

Effects of the loss and reconstruction of molar occlusal support on memory retrieval and hippocampal neuron density in rats

PurposeAnimal experiments have shown that the loss of occlusal support causes impairments in spatial cognition. Many reports have focused on the memory encoding process, and only few studies have investigated the effect on memory retrieval. This study aimed to examine the effects of both the loss and reconstruction of occlusal support on the memory retrieval process and on the number of hippocampal pyramidal cells.MethodsThe experimental animals were divided into a molarless group, in which molars were extracted, a denture-wearing molarless group with experimental dentures inserted after molar extraction, and a control group. Radial maze trials were performed for 20 consecutive days (acquisition phase). The rats were tested on long-term memory retention following the acquisition phase in eight trials every five days, and in an additional trial 20 days later (probe phase).ResultsThe denture-wearing molarless group showed higher levels of spatial learning and memory than the molarless group. There were no significant differences in memory retrieval during the probe phase between the denture-wearing molarless and the control group. The molarless group showed significantly worse spatial learning and memory and had fewer neurons in the hippocampus than the control group.ConclusionsOur results suggest that the loss of occlusal support decreases the number of pyramidal cells in the hippocampus and impairs memory decoding and retrieval. However, this effect is suppressed by the reconstruction of occlusal support.     

A low cost smart system to analyze different types of edible Bird's nest adulteration based on colorimetric sensor array

This study was performed to develop a low-cost smart system for identification and quantification of adulterated edible bird's nest (EBN). The smart system was constructed with a colorimetric sensor array (CSA), a smartphone and a multi-layered network model. The CSA were used to collect the odor character of EBN and the response signals of CSA were captured by the smartphone systems. The principal component analysis (PCA) and hierarchical cluster analysis (HAC) were used to inquiry the similarity among authentic and adulterated EBNs. The multi-layered network model was constructed to analyze EBN adulteration. In this model, discrimination of authentic EBN and adulterated EBN was realized using back-propagation neural networks (BPNN) algorithm. Then, another BPNN-based model was developed to identify the type of adulterant in the mixed EBN. Finally, adulterated percentage prediction model for each kind of adulterate EBN was built using partial least square (PLS) method. Results showed that recognition rates of the authentic EBN and adulterated EBN was as high as 90%. The correlation coefficient of percentage prediction model for calibration set was 0.886, and 0.869 for prediction set. The low-cost smart system provides a real-time, nondestructive tool to authenticate EBN for customers and retailers.     

Reducing unnecessary biopsies while detecting clinically significant prostate cancer including cribriform growth with the ERSPC Rotterdam risk calculator and 4Kscore

Introduction

The use of risk calculators predicting clinically significant prostate cancer (csCaP) on biopsy reduces unnecessary biopsies and overdiagnosis of indolent disease compared to a Prostate Specific Antigen (PSA) strategy. Updating these tools using more specific outcome measures and contemporary predictors could potentially lead to further reductions. Our objective was to assess clinical impact of the 4 kallikrein (4K) score, the Rotterdam Prostate Cancer Risk Calculator (RPCRC), and the combination of both for predicting csCaP based on the latest International Society of Urological Pathology grading system and cribriform growth pattern.

Aligning Developmental and Processing Accounts of Implicit and Statistical Learning

A long‐standing question in child language research concerns how children achieve mature syntactic knowledge in the face of a complex linguistic environment. A widely accepted view is that this process involves extracting distributional regularities from the environment in a manner that is incidental and happens, for the most part, without the learner's awareness. In this way, the debate speaks to two associated but separate literatures in language acquisition: statistical learning and implicit learning. Both fields have explored this issue in some depth but, at present, neither the results from the infant studies used by the statistical learning literature nor the artificial grammar learning tasks studies from the implicit learning literature can be used to fully explain how children's syntax becomes adult‐like. In this work, we consider an alternative explanation—that children use error‐based learning to become mature syntax users. We discuss this proposal in the light of the behavioral findings from structural priming studies and the computational findings from Chang, Dell, and Bock's (2006) dual‐path model, which incorporates properties from both statistical and implicit learning, and offers an explanation for syntax learning and structural priming using a common error‐based learning mechanism. We then turn our attention to future directions for the field, here suggesting how structural priming might inform the statistical learning and implicit learning literature on the nature of the learning mechanism.     

Bayesian adaptive lasso for additive hazard regression with current status data

Variable selection is a crucial issue in model building and it has received considerable attention in the literature of survival analysis. However, available approaches in this direction have mainly focused on time-to-event data with right censoring. Moreover, a majority of existing variable selection procedures for survival models are developed in a frequentist framework. In this article, we consider additive hazards model in the presence of current status data. We propose a Bayesian adaptive least absolute shrinkage and selection operator procedure to conduct a simultaneous variable selection and parameter estimation. Efficient Markov chain Monte Carlo methods are developed to implement posterior sampling and inference. The empirical performance of the proposed method is demonstrated by simulation studies. An application to a study on the risk factors of heart failure disease for type 2 diabetes patients is presented.     

Can muscle weakness and disability influence the relationship between pain catastrophizing and pain worsening in patients with knee osteoarthritis? A cross-sectional study

ObjectiveTo verify if the relationship between pain catastrophizing and pain worsening would be mediated by muscle weakness and disability in patients with symptomatic knee osteoarthritis.MethodsThis was a cross-sectional study in a hospital out-patient setting. Convenience sampling was used with a total of 50 participants with symptomatic knee osteoarthritis. Pain and the activities of daily livings (ADL) were assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS) subscale. Pain catastrophizing was assessed using the Coping Strategy Questionnaire (CSQ) subscale. Muscle strength of knee extension and 30-s chair stand test (30CST) were also assessed. Path analysis was performed to test the hypothetical model. Goodness of fit of models were assessed by using statistical parameters such as the chi-square value, goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA).ResultsThe chi-square values were not significant (chi-square = 0.283, p = 0.594), and the indices of goodness of fit were high, implying a valid model (GFI = 1.000; AGFI = 0.997; CFI = 1.000; RMSEA = 0.000). Pain was influenced significantly by muscle strength and ADL; muscle strength was influenced significantly by ADL via 30CST; ADL was influenced by pain catastrophizing.ConclusionThe relationship between pain catastrophizing with pain worsening are mediated by muscle weakness and disability.     

新型冠状病毒肺炎疫情下社区医院人员防控知识强化测评模式效果评价

目的 对社区医院人员防控知识强化测评模式的实施效果进行评价。方法 通过第三方数据收集平台,在规定时间内、实名制进行疫情防控知识问卷考核,以各岗位合格分数为标准,确认能否上岗,防控知识反复强化,题库动态更新,使各岗位人员保持高度认知的实战状态。结果 首次测试,医院全体人员新型冠状病毒肺炎防控知识平均分为78.37,100%的人知晓用过的一次性帽子和口罩的处理;只有23.27%的知晓医疗机构预检点或分诊台物品的消毒频次。强化测评模式实施1周后,医院全体人员新型冠状病毒肺炎防控知识平均分上升至93.84。上岗情况中,培训3 d上岗人数由48人上升至78人,培训第10天为149人,上岗率也由30.19%上升至第3天的49.05%,以及培训第10天的93.71%。结论 强制社区医院人员学习新型冠状病毒肺炎防控知识效果明显,整体水平短期内迅速提升,并保持高度认知,该强化测评模式对一线社区医院人员防控能力的提升有实际应用价值。