Microarray analysis of mouse ling examining the augmented pseudomonas aeruginosa clearance following mild traumatic brain injury

Our murine model of mild traumatic brain injury (mTBI) has shown improved survival after Pseudomonas aeruginosa (Psd) challenge as compared to controls (tail trauma or sham injury). Previous work suggests an mTBI-specific involvement of the neuro-immune axis which augments the innate immune response, increasing survival. Additional factors for the enhanced mTBI survival were explored via microarray analysis of lungs harvested 48 hours post-trauma, the point prior to Psd challenge in our model. At 48 hours post-trauma, mTBI lungs have a number of upregulated ATP synthesis and mitochondrial gene sets. Increased available energy could prime the mTBI lungs, allowing an earlier and more robust response to Psd infection, possibly contributing to the increased mTBI survival. This is supported by increased neutrophil recruitment in the bronchoalveolar lavage of mTBI mice four hours after Psd instillation. Downregulated gene sets related to cellular connections suggest that neutrophils recruited to the lung have an easier extravasation pathway into the air space of mTBI lungs compared to control. Based on genetic and neutrophil recruitment data, it is possible that mTBI creates an energetically prepared and easily accessible lung better tailored for recruiting and allowing entry of neutrophils in response to an infection compared to control

Towards a classification framework for social machines

The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as ‘social machines’ exploit the large-scale interaction of humans with machines. Interactions that are motivated by numerous goals and purposes including financial gain, charitable aid, and simply for fun. In this paper we explore the landscape of social machines, both past and present, with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation. We present an initial characterization of some of the most popular social machines, as demonstration of the use of the identified constructs. We believe that it is important to undertake an analysis of the behaviour and phenomenology of social machines, and of their growth and evolution over time. Our future work will seek to elicit additional opinions, classifications and validation from a wider audience, to produce a comprehensive framework for the description, analysis and comparison of social machines

Bucksport and the Sustainable Development Goals

The purpose of the project was to gather information that relates to the sustainability of Bucksport and the issues facing the town and use that information to find sustainable courses of action that the community may take. The group worked to gather information on several topics and issues including the culture, economy, politics, and natural attributes of the area. Through research, interviews, and collaboration the students gathered information that was examined through the lens of sustainable development in order to find potential solutions and provide data to the community for their dealings with the Horry County and Federal governments. A focus was placed on the United Nations Sustainable Development Goals, a set of global and local interlinked goals and indicators adopted by all member countries of the UN, the idea being a blueprint to achieve a better and more sustainable future for all. The group began finding which issues and factors related to which of the 17 sustainable development goals. These goals were then used as a guide and template for determining the best actions for the community to take moving forward. Rather than only looking for quick and temporary solutions, the group worked to figure out more sustainable routes that will do more to support the community in the long term and help it to endure through both current and future issues

High Streets for All

This study takes one of the most commonplace and everyday experiences of the city – the high street – and explores its social value from the perspective of Londoners. Social value is most commonly understood to be made up of economic, social and environmental aspects. Together with existing knowledge and new primary research, the study uses this evidence to set out the strategic case for advocacy, intervention and investment in London’s high streets

Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets

Vision-language models are growing in popularity and public visibility to generate, edit, and caption images at scale; but their outputs can perpetuate and amplify societal biases learned during pre-training on uncurated image-text pairs from the internet. Although debiasing methods have been proposed, we argue that these measurements of model bias lack validity due to dataset bias. We demonstrate there are spurious correlations in COCO Captions, the most commonly used dataset for evaluating bias, between background context and the gender of people in-situ. This is problematic because commonly-used bias metrics (such as Bias@K) rely on per-gender base rates. To address this issue, we propose a novel dataset debiasing pipeline to augment the COCO dataset with synthetic, gender-balanced contrast sets, where only the gender of the subject is edited and the background is fixed. However, existing image editing methods have limitations and sometimes produce low-quality images; so, we introduce a method to automatically filter the generated images based on their similarity to real images. Using our balanced synthetic contrast sets, we benchmark bias in multiple CLIP-based models, demonstrating how metrics are skewed by imbalance in the original COCO images. Our results indicate that the proposed approach improves the validity of the evaluation, ultimately contributing to more realistic understanding of bias in vision-language models.Comment: Github: https://github.com/oxai/debias-gensynt

Reinnervation of rat extensor digitorum longus muscles after free grafting

Free grafts of the extensor digitorum longus (EDL) muscle of the rat are invaded by regenerating nerve fibers during the second postoperative week. Neuromuscular junctions are established during the third week. Levels of choline acetyltransferase (CAT) activity parallel the invasion of the graft by nerve fibers, but this activity never returns to control levels. We conclude that incomplete reinnervation of free muscle grafts may be a factor in the failure of such grafts to reattain the mass of control muscles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50129/1/880020411_ftp.pd

Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation

Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation

Did the Market Signal Impending Problems at Northern Rock? An Analysis of Four Financial Instruments

The academic literature has regularly argued that market discipline can support regulatory authority mechanisms in ensuring banking sector stability. This includes, amongst other things, using forward-looking market prices to identify those credit institutions that are most at risk of failure. The paper's key aim is to analyse whether market investors signalled potential problems at Northern Rock in advance of the bank announcing that it had negotiated emergency lending facilities at the Bank of England in September 2007. A further aim of the paper is to examine the signalling qualities of four financial market instruments (credit default swap spreads, subordinated debt spreads, implied volatility from options prices and equity measures of bank risk) so as to explore both the relative and individual qualities of each. Therefore, the paper's findings contribute to the market discipline literature on using market data to identify bank risk-taking and enhancing supervisory monitoring. Our analysis suggests that private market participants did signal impending financial problems at Northern Rock. These findings lend some empirical support to proposals for the supervisory authorities to use market information more extensively to improve the identification of troubled banks. The paper identifies equities as providing the timeliest and clearest signals of bank condition, whilst structural factors appear to hamper the signalling qualities of subordinated debt spreads and credit default swap spreads. The paper also introduces idiosyncratic implied volatility as a potentially useful early warning metric for supervisory authorities to observe.Bank regulation ; bank failures ; market discipline ; early-warning signals