Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained using the mpMRI, clinical, pathologic, and radiomic descriptors for prediction of the OncotypeDX risk score. The trained mpRad IRIS model had a 95% and specificity was 83% with an Area Under the Curve (AUC) of 0.89 for classifying low risk patients from the intermediate and high-risk groups. The lesion size was larger for the high-risk group (2.9 ± 1.7 mm) and lower for both low risk (1.9 ± 1.3 mm) and intermediate risk (1.7 ± 1.4 mm) groups. The lesion apparent diffusion coefficient (ADC) map values for high- and intermediate-risk groups were significantly (p \u3c 0.05) lower than the low-risk group (1.14 vs. 1.49 × 10−3 mm2/s). These initial studies provide deeper insight into the clinical, pathological, quantitative imaging, and radiomic features, and provide the foundation to relate these features to the assessment of treatment response for improved personalized medicine

What are the impacts of within-field farmland management practices on the flux of greenhouse gases from arable cropland in temperate regions? A systematic map protocol

Background: Reducing greenhouse gas emissions is a vital step in limiting climate change and meeting the goals outlined in the COP 21 Paris Agreement of 2015. Studies have suggested that agriculture accounts for around 11% of total greenhouse gas emissions and the industry has a significant role in meeting international and national climate change reduction objectives. However, there is currently little consensus on the mechanisms that regulate the production and assimilation of greenhouse gases in arable land and the practical factors that affect the process. Practical advice for farmers is often overly general, and models based on the amount of nitrogen fertiliser applied, for example, are used despite a lack of knowledge of how local conditions affect the process, such as the importance of humus content and soil types. Here, we propose a systematic map of the evidence relating to the impact on greenhouse gas flux from the agricultural management of arable land in temperate regions. Methods: Using established methods for systematic mapping in environmental sciences we will search for, collate and catalogue research studies relating to the impacts of farming in temperate systems on greenhouse gas emissions. We will search 6 bibliographic databases using a tested search string, and will hand search a web-based search engine and a list of organisational web sites. Furthermore, evidence will be sought from key stakeholders. Search results will then be screened for relevance at title, abstract and full text levels according to a predefined set of eligibility criteria. Consistency checking will be employed to ensure the criteria are being applied accurately and consistently. Relevant studies will then be subjected to coding and meta-data extraction, which will be used to populate a systematic map database describing each relevant study's settings, methods and measured outcomes. The mapping process will help to identify knowledge gaps (subjects lacking in evidence warranting further primary research) and knowledge clusters (subjects with sufficient studies to allow a useful full systematic review), and will highlight best and suboptimal research methods

RETRATO SIN IDENTIFICAR [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 201

What evidence exists on ecotechnologies for recycling carbon and nutrients from domestic wastewater? a systematic map

Abstract: Background: Eutrophication of the Baltic Sea, and many other water bodies, is partly the result of point-source emissions of nutrients and carbon from wastewater. At the same time, nitrogen and phosphorus planetary boundaries have been breached. There is a need for more efficient resource management, including the recovery and reuse of nutrients and carbon in waste. The aim of this paper is to collate evidence on ecotechnologies intended for use in the wastewater sector globally to facilitate the recovery or reuse of carbon and/or nutrients. Methods: Searches were performed on literature published between 2013 and 2017 and in 5 bibliographic databases, 1 search engine, and 38 specialist websites. Database searches were performed in English. Searches in specialist websites were also performed in Finnish, Polish and Swedish. There was no geographical limitation. Screening was conducted at title and abstract level, and on full texts. Apart from bibliographical information, we extracted information on ecotechnology type, intervention, details of the recovery or reuse, the type of wastewater stream to which the ecotechnology is applied, the study location, type and design. Prior to screening and coding, we conducted consistency checks amongst reviewers. We generated a searchable database of coded studies. Findings were synthesised narratively and visualised in a geographical information system (i.e. an evidence atlas). We identified a series of knowledge gaps and clusters that warrant further research. Results: The search resulted in 4024 records, out of which 413 articles were retained after the screening process. In addition, 35 pre-screened studies from the specialist website searches were added. Together, these 448 articles contained 474 individual studies of 28 types of ecotechnologies. A combination of ecotechnologies (16.7%), followed by microalgae cultivation (14.1%) were the most frequent ecotechnologies in the evidence base. Ecotechnologies for recovery composed 72.6% of the evidence base. The most common wastewater streams for recovery were mixed wastewater and sludge (73.8%). There was a relative lack of studies on recovery from source-separated wastewater. The most common type of recovery was energy (27.3%), followed by simultaneous recovery of nitrogen and phosphorus (22.1%). Reuse of recovered substances was described in 22.8% of the studies. The most common type of reuse was of nitrogen and phosphorus (57.4%), followed by joint reuse of organic carbon, nitrogen and phosphorus (35.2%). Reuse ecotechnologies were mostly focused on the use of wastewater for irrigation or reuse of biosolids, and not on the nutrients that had been extracted through e.g. precipitation of struvite. In 22 studies both recovery and reuse were described. In total, 60 different study countries were reported in the evidence base, and the most common study location was China

Childbearing intentions in a low fertility context: the case of Romania

This paper applies the Theory of Planned Behaviour (TPB) to find out the predictors of fertility intentions in Romania, a low-fertility country. We analyse how attitudes, subjective norms and perceived behavioural control relate to the intention to have a child among childless individuals and one-child parents. Principal axis factor analysis confirms which items proposed by the Generation and Gender Survey (GGS 2005) act as valid and reliable measures of the suggested theoretical socio-psychological factors. Four parity-specific logistic regression models are applied to evaluate the relationship between the socio-psychological factors and childbearing intentions. Social pressure emerges as the most important aspect in fertility decision-making among childless individuals and one-child parents, and positive attitudes towards childbearing are a strong component in planning for a child. This paper also underlines the importance of the region-specific factors when studying childbearing intentions: planning for the second child significantly differs among the development regions, representing the cultural and socio-economic divisions of the Romanian territory

Factors affecting adherence to guidelines for antithrombotic therapy in elderly patients with atrial fibrillation admitted to internal medicine wards

Current guidelines for ischemic stroke prevention in atrial fibrillation or flutter (AFF) recommend Vitamin K antagonists (VKAs) for patients at high-intermediate risk and aspirin for those at intermediate-low risk. The cost-effectiveness of these treatments was demonstrated also in elderly patients. However, there are several reports that emphasize the underuse of pharmacological prophylaxis of cardio-embolism in patients with AFF in different health care settings. AIMS: To evaluate the adherence to current guidelines on cardio-embolic prophylaxis in elderly (> 65 years old) patients admitted with an established diagnosis of AFF to the Italian internal medicine wards participating in REPOSI registry, a project on polypathologies/polytherapies stemming from the collaboration between the Italian Society of Internal Medicine and the Mario Negri Institute of Pharmacological Research; to investigate whether or not hospitalization had an impact on guidelines adherence; to test the role of possible modifiers of VKAs prescription. METHODS: We retrospectively analyzed registry data collected from January to December 2008 and assessed the prevalence of patients with AFF at admission and the prevalence of risk factors for cardio-embolism. After stratifying the patients according to their CHADS(2) score the percentage of appropriateness of antithrombotic therapy prescription was evaluated both at admission and at discharge. Univariable and multivariable logistic regression models were employed to verify whether or not socio-demographic (age >80years, living alone) and clinical features (previous or recent bleeding, cranio-facial trauma, cancer, dementia) modified the frequency and modalities of antithrombotic drugs prescription at admission and discharge. RESULTS: Among the 1332 REPOSI patients, 247 were admitted with AFF. At admission, CHADS(2) score was ≥ 2 in 68.4% of patients, at discharge in 75.9%. Among patients with AFF 26.5% at admission and 32.8% at discharge were not on any antithrombotic therapy, and 43.7% at admission and 40.9% at discharge were not taking an appropriate therapy according to the CHADS(2) score. The higher the level of cardio-embolic risk the higher was the percentage of antiplatelet- but not of VKAs-treated patients. At admission or at discharge, both at univariable and at multivariable logistic regression, only an age >80 years and a diagnosis of cancer, previous or active, had a statistically significant negative effect on VKAs prescription. Moreover, only a positive history of bleeding events (past or present) was independently associated to no VKA prescription at discharge in patients who were on VKA therapy at admission. If heparin was considered as an appropriate therapy for patients with indication for VKAs, the percentage of patients admitted or discharged on appropriate therapy became respectively 43.7% and 53.4%. CONCLUSION: Among elderly patients admitted with a diagnosis of AFF to internal medicine wards, an appropriate antithrombotic prophylaxis was taken by less than 50%, with an underuse of VKAs prescription independently of the level of cardio-embolic risk. Hospitalization did not improve the adherence to guideline

Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays