Lower levels of damaged protein biomarkers in the plasma of overweight type 2 diabetic men following supplementation with a standardised bilberry extract

Peer reviewedPublisher PD

Developing a Natural Language Understanding Model to Characterize Cable News Bias

Media bias has been extensively studied by both social and computational sciences. However, current work still has a large reliance on human input and subjective assessment to label biases. This is especially true for cable news research. To address these issues, we develop an unsupervised machine learning method to characterize the bias of cable news programs without any human input. This method relies on the analysis of what topics are mentioned through Named Entity Recognition and how those topics are discussed through Stance Analysis in order to cluster programs with similar biases together. Applying our method to 2020 cable news transcripts, we find that program clusters are consistent over time and roughly correspond to the cable news network of the program. This method reveals the potential for future tools to objectively assess media bias and characterize unfamiliar media environments

Prior History of Learning Disabilities in Reye's Syndrome Survivors

Twenty-six children, ages nine-18, who had recovered from Reye's syndrome were tested for possible memory deficits. In reviewing school histories, an unexpected finding was the disproportionately high number of students who were Learning Disabled before contracting Reye's syndrome. Seven of the children had been receiving special education services for being Learning Disabled and another two were viewed by their schools as being hyperactive. This is 10 times the expected incident rate. This group of Learning Disabled students did not score significantly worse on any measure than did the other children who had Reye's syndrome.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68975/2/10.1177_002221948501800607.pd

Perceived value of work-integrated learning on the teaching efficacy and classroom management of pre-service teachers.

The aim of this study was to examine associations of teaching competence, autonomous motivation, and self-efficacy between two groups of pre-service teachers enrolled in a four-year Bachelor of Education degree program. One group participated in a Work-Integrated Learning (WIL) pathway and one who did not participate in a Work-Integrated Learning pathway. Self-reports of basic psychological needs, motivational regulations, and self-efficacy were completed by 116 pre-service teachers. Findings indicated that pre-service teachers who participated in the WIL pathway had higher levels of efficacy in classroom management, and pre-service teachers who participated in the WIL pathway had higher perceptions of identified regulation, demonstrating that they perceived WIL teaching sessions as a useful way to develop other characteristics of themselves. These findings suggest that exposure to authentic and experiential learning encounters through practical WIL experiences has a favourable impact on pre-service teacher competence, autonomous motivation, and self-efficacy. Incorporating authentic and practical opportunities such as WIL into teacher education programs presents a valuable and feasible option to foster broad skill development and teacher readiness

Greenhouse gas considerations in rail infrastructure in the UK

Transportation-related greenhouse gas (GHG) emissions account for an increasing proportion of total emissions in the UK and globally. The provision of rail transit is popularly proposed to reduce transport GHG emissions, but the provision of new infrastructure is itself GHG intensive. Understanding of the GHG emissions impact of rail projects is limited and very few longitudinal studies have been carried out. Existing assessments are often limited both in their scope and the factors considered. A holistic understanding of GHG impacts must include an assessment of capital GHG emissions, operational energy and maintenance as well as an assessment of ridership mode shift and mode share impacts and the relationship between transit infrastructure and land use. This paper explores rail infrastructure projects and their associated GHG emissions. Guidance is given on the aspects of rail planning, design and construction that must be considered to more fully understand the associated GHG impacts.The authors would like to thank The Commonwealth Scholarship Commission in the UK for the scholarship funding that facilitated this work

AIM2 and NLRC4 inflammasomes contribute with ASC to acute brain injury independently of NLRP3

Inflammation that contributes to acute cerebrovascular disease is driven by the proinflammatory cytokine interleukin-1 and is known to exacerbate resulting injury. The activity of interleukin-1 is regulated by multimolecular protein complexes called inflammasomes. There are multiple potential inflammasomes activated in diverse diseases, yet the nature of the inflammasomes involved in brain injury is currently unknown. Here, using a rodent model of stroke, we show that the NLRC4 (NLR family, CARD domain containing 4) and AIM2 (absent in melanoma 2) inflammasomes contribute to brain injury. We also show that acute ischemic brain injury is regulated by mechanisms that require ASC (apoptosis-associated speck-like protein containing a CARD), a common adaptor protein for several inflammasomes, and that the NLRP3 (NLR family, pyrin domain containing 3) inflammasome is not involved in this process. These discoveries identify the NLRC4 and AIM2 inflammasomes as potential therapeutic targets for stroke and provide new insights into how the inflammatory response is regulated after an acute injury to the brain