Information-Theoretic Inference of Large Transcriptional Regulatory Networks

The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy (MRMR), an effective information-theoretic technique for feature selection in supervised learning. The MRMR principle consists in selecting among the least redundant variables the ones that have the highest mutual information with the target. MRNET extends this feature selection principle to networks in order to infer gene-dependence relationships from microarray data. The paper assesses MRNET by benchmarking it against RELNET, CLR, and ARACNE, three state-of-the-art information-theoretic methods for large (up to several thousands of genes) network inference. Experimental results on thirty synthetically generated microarray datasets show that MRNET is competitive with these methods.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Machine learning techniques to identify putative genes involved in nitrogen catabolite repression in the yeast Saccharomyces cerevisiae

Nitrogen is an essential nutrient for all life forms. Like most unicellular organisms, the yeast Saccharomyces cerevisiae transports and catabolizes good nitrogen sources in preference to poor ones. Nitrogen catabolite repression (NCR) refers to this selection mechanism. All known nitrogen catabolite pathways are regulated by four regulators. The ultimate goal is to infer the complete nitrogen catabolite pathways. Bioinformatics approaches offer the possibility to identify putative NCR genes and to discard uninteresting genes.Journal Articleinfo:eu-repo/semantics/publishe

A Review on the Visible Light Active Titanium Dioxide Photocatalysts for Environmental Applications

Development of visible light active (VLA) titania photocatalysts Fujishima and Honda (1972) demonstrated the potential of titanium dioxide (TiO 2) semiconductor mate-rials to split water into hydrogen and oxygen in a photo-electrochemical cell. Their work triggered the development of semiconductor photocatalysis for a wide range of environmental and energy applica-tions. One of the most significant scientific and commercial advances to date has been the development of visible light active (VLA) TiO2 photocatalytic materials. In this review, a background on TiO2 struc-ture, properties and electronic properties in photocatalysis is presented. The development of different strategies to modify TiO2 for the utilization of visible light, including non metal and/or metal doping, dye sensitization and coupling semiconductors are discussed. Emphasis is given to the origin of visible light absorption and the reactive oxygen species generated, deduced by physicochemical and photo-electrochemical methods. Various applications of VLA TiO2, in terms of environmental remediation and in particular water treatment, disinfection and air purification, are illustrated. Comprehensive studies on the photocatalytic degradation of contaminants of emerging concern, including endocrine disrupting compounds, pharmaceuticals, pesticides, cyanotoxins and volatile organic compounds, with VLA TiO2 are discussed and compared to conventional UV-activated TiO2 nanomaterials. Recent advances in bac-terial disinfection using VLA TiO2 are also reviewed. Issues concerning test protocols for real visible light activity and photocatalytic efficiencies with different light sources have been highlighted

Age-Related Differences and Reliability on Computerized and Paper-and-Pencil Neurocognitive Assessment Batteries

Neurocognitive testing is a recommended component in a concussion assessment. Clinicians should be aware of age and practice effects on these measures to ensure appropriate understanding of results

Barriers and facilitators to person-centred infection prevention and control: results of a survey about the Dementia Isolation Toolkit

Objectives: People working in long-term care homes (LTCH) face difficult decisions balancing the risk of spread of infection with the hardship that infection control and prevention (ICP) measures put on residents. The Dementia Isolation Toolkit (DIT) was developed to address the gap in ethical guidance on how to safely and effectively isolate people living with dementia while supporting their personhood. In this study, we report the results of a survey of LTCH staff on barriers and facilitators regarding isolating residents, and on the use and impact of the DIT. Design: Online survey. Setting and Participants: Participants (n=208) were staff working on-site in LTCH in Ontario, Canada since March 1, 2020, with direct or indirect experience with the isolation of LTCH resi-dents. Methods: LTCH staff were recruited through provincial LTCH organizations, social media, and the DIT website. Survey results were summarized, and three groups compared, those: 1) unfamiliar with, 2) familiar with, and 3) users of the DIT. Results: 61% of respondents identified distress of LTCH staff about the harmful effects of isola-tion on residents as a major barrier to effective isolation. Facilitators for isolation included delivery of 1:1 activity in the resident’s room (81%) and designating essential caregivers to provide support (67%). Almost all respondents (84%) reported an increase in moral distress. DIT users were less likely to report an impact of moral distress on job satisfaction (OR 0.41, 95% CI 0.19-0.87) with 48% of users reporting it was helpful in reducing their level of distress. Conclusions and Implications: Isolation as an ICP measure in LTCH environments creates mor-al distress in staff which is a barrier to its effectiveness. ICP guidance to LTCH would be strength-ened with the inclusion of a dementia-specific ethical framework that addresses how to minimize the harms of isolation on both residents and staff

Prevalence, causes, and consequences of moral distress in healthcare providers caring for people living with dementia in long-term care during a pandemic

Healthcare providers caring for people living with dementia may experience moral distress when faced with ethically challenging situations, such as the inability to provide care that is consistent with their values. The COVID-19 pandemic produced conditions in long-term care homes (LTCHs) that could potentially contribute to moral distress. We conducted an online survey to examine changes in moral distress during the pandemic, its contributing factors and correlates, and its impact on the well-being of LTCH staff. Survey participants (n=227) working in LTCHs across Ontario, Canada were recruited through provincial LTCH organizations. Using a Bayesian approach, we examined the association between moral distress and staff demographics and roles, and characteristics of the LTCH. We performed a qualitative analysis of the survey's free-text responses. More than 80% of LTCH healthcare providers working with people with dementia reported an increase in moral distress since the start of the pandemic. There was no difference in the severity of distress by age, sex, role, or years of experience. The most common factors associated with moral distress were lack of activities and family visits, insufficient staffing and high turnover, and having to follow policies and procedures that were perceived to harm residents with dementia. At least two-thirds of respondents reported feelings of physical exhaustion, sadness/anxiety, frustration, powerlessness, and guilt due to the moral distress experienced during the pandemic. Respondents working in not-for-profit or municipal homes reported less sadness/anxiety and feelings of not wanting to go to work than those in for-profit homes. Front-line staff were more likely to report not wanting to work than those in management or administrative positions. Overall, we found that increases in moral distress during the pandemic negatively affected the well-being of healthcare providers in LTCHs, with preliminary evidence suggesting that individual and systemic factors may intensify the negative effect

Statements of Agreement From the Targeted Evaluation and Active Management (TEAM) Approaches to Treating Concussion Meeting Held in Pittsburgh, October 15-16, 2015

Conventional management for concussion involves prescribed rest and progressive return to activity. Recent evidence challenges this notion and suggests that active approaches may be effective for some patients. Previous concussion consensus statements provide limited guidance regarding active treatment

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype

New Insights into the Mechanism of Visible Light Photocatalysis

ABSTRACT: In recent years, the area of developing visible-lightactive photocatalysts based on titanium dioxide has been enormously investigated due to its wide range of applications in energy and environment related fields. Various strategies have been designed to efficiently utilize the solar radiation and to enhance the efficiency of photocatalytic processes. Building on the fundamental strategies to improve the visible light activity of TiO2-based photocatalysts, this Perspective aims to give an insight into many contemporary developments in the field of visible-light-active photocatalysis. Various examples of advanced TiO2 composites have been discussed in relation to their visible light induced photoconversion efficiency, dynamics of electron− hole separation, and decomposition of organic and inorganic pollutants, which suggest the critical need for further development of these types of materials for energy conversion and environmental remediation purposes