Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods

Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as social cohesion among neighbors combined with their willingness to intervene on behalf of the common good. Sociologists measure collective efficacy by conducting survey studies designed to measure individuals' perception of their community. In this work, we employ the curated data from a survey study (ground truth) and examine the effectiveness of substituting costly survey questionnaires with proxies derived from social media. We enrich a corpus of tweets mentioning a local venue with several linguistic and topological features. We then propose a pairwise learning to rank model with the goal of identifying a ranking of neighborhoods that is similar to the ranking obtained from the ground truth collective efficacy values. In our experiments, we find that our generated ranking of neighborhoods achieves 0.77 Kendall tau-x ranking agreement with the ground truth ranking. Overall, our results are up to 37% better than traditional baselines.Comment: 10 pages, 7 figure

Assessing mechanical integrity of spinal fusion by in situ endochondral osteoinduction in the murine model

<p>Abstract</p> <p>Background</p> <p>Historically, radiographs, micro-computed tomography (micro-CT) exams, palpation and histology have been used to assess fusions in a mouse spine. The objective of this study was to develop a faster, cheaper, reproducible test to directly quantify the mechanical integrity of spinal fusions in mice.</p> <p>Methods</p> <p>Fusions were induced in ten mice spine using a previously described technique of in situ endochondral ossification, harvested with soft tissue, and cast in radiolucent alginate material for handling. Using a validated software package and a customized mechanical apparatus that flexed and extended the spinal column, the amount of intervertebral motion between adjacent vertebral discs was determined with static flexed and extended lateral spine radiographs. Micro-CT images of the same were also blindly reviewed for fusion.</p> <p>Results</p> <p>Mean intervertebral motion between control, non-fused, spinal vertebral discs was 6.1 ± 0.2° during spine flexion/extension. In fusion samples, adjacent vertebrae with less than 3.5° intervertebral motion had fusions documented by micro-CT inspection.</p> <p>Conclusions</p> <p>Measuring the amount of intervertebral rotation between vertebrae during spine flexion/extension is a relatively simple, cheap (<$100), clinically relevant, and fast test for assessing the mechanical success of spinal fusion in mice that compared favorably to the standard, micro-CT.</p

Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations

Accurate methods to assess the pathogenicity of mutations are needed to fully leverage the possibilities of genome sequencing in diagnosis. Current data-driven and bioinformatics approaches are, however, limited by the large number of new variations found in each newly sequenced genome, and often do not provide direct mechanistic insight. Here we demonstrate, for the first time, that saturation mutagenesis, biophysical modeling and co-variation analysis, performed in silico, can predict the abundance, metabolic stability, and function of proteins inside living cells. As a model system, we selected the human mismatch repair protein, MSH2, where missense variants are known to cause the hereditary cancer predisposition disease, known as Lynch syndrome. We show that the majority of disease-causing MSH2 mutations give rise to folding defects and proteasome-dependent degradation rather than inherent loss of function, and accordingly our in silico modeling data accurately identifies disease-causing mutations and outperforms the traditionally used genetic disease predictors. Thus, in conclusion, in silico biophysical modeling should be considered for making genotype-phenotype predictions and for diagnosis of Lynch syndrome, and perhaps other hereditary diseases

PICS-Ord: unlimited coding of ambiguous regions by pairwise identity and cost scores ordination

<p>Abstract</p> <p>Background</p> <p>We present a novel method to encode ambiguously aligned regions in fixed multiple sequence alignments by 'Pairwise Identity and Cost Scores Ordination' (PICS-Ord). The method works via ordination of sequence identity or cost scores matrices by means of Principal Coordinates Analysis (PCoA). After identification of ambiguous regions, the method computes pairwise distances as sequence identities or cost scores, ordinates the resulting distance matrix by means of PCoA, and encodes the principal coordinates as ordered integers. Three biological and 100 simulated datasets were used to assess the performance of the new method.</p> <p>Results</p> <p>Including ambiguous regions coded by means of PICS-Ord increased topological accuracy, resolution, and bootstrap support in real biological and simulated datasets compared to the alternative of excluding such regions from the analysis a priori. In terms of accuracy, PICS-Ord performs equal to or better than previously available methods of ambiguous region coding (e.g., INAASE), with the advantage of a practically unlimited alignment size and increased analytical speed and the possibility of PICS-Ord scores to be analyzed together with DNA data in a partitioned maximum likelihood model.</p> <p>Conclusions</p> <p>Advantages of PICS-Ord over step matrix-based ambiguous region coding with INAASE include a practically unlimited number of OTUs and seamless integration of PICS-Ord codes into phylogenetic datasets, as well as the increased speed of phylogenetic analysis. Contrary to word- and frequency-based methods, PICS-Ord maintains the advantage of pairwise sequence alignment to derive distances, and the method is flexible with respect to the calculation of distance scores. In addition to distance and maximum parsimony, PICS-Ord codes can be analyzed in a Bayesian or maximum likelihood framework. RAxML (version 7.2.6 or higher that was developed for this study) allows up to 32-state ordered or unordered characters. A GTR, MK, or ORDERED model can be applied to analyse the PICS-Ord codes partition, with GTR performing slightly better than MK and ORDERED.</p> <p>Availability</p> <p>An implementation of the PICS-Ord algorithm is available from <url>http://scit.us/projects/ngila/wiki/PICS-Ord</url>. It requires both the statistical software, R <url>http://www.r-project.org</url> and the alignment software Ngila <url>http://scit.us/projects/ngila</url>.</p

Tyrosine kinase inhibitors reprogramming immunity in renal cell carcinoma: rethinking cancer immunotherapy

Review article[Abstract] The immune system regulates angiogenesis in cancer by way of both pro- and antiangiogenic activities. A bidirectional link between angiogenesis and the immune system has been clearly demonstrated. Most antiangiogenic molecules do not inhibit only VEGF signaling pathways but also other pathways which may affect immune system. Understanding of the role of these pathways in the regulation of immunosuppressive mechanisms by way of specific inhibitors is growing. Renal cell carcinoma (RCC) is an immunogenic tumor in which angiogenesis and immunosuppression work hand in hand, and its growth is associated with impaired antitumor immunity. Given the antitumor activity of selected TKIs in metastatic RCC (mRCC), it seems relevant to assess their effect on the immune system. The confirmation that TKIs improve cell cytokine response in mRCC provides a basis for the rational combination and sequential treatment of TKIs and immunotherapy

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP

Outer membrane protein folding from an energy landscape perspective

The cell envelope is essential for the survival of Gram-negative bacteria. This specialised membrane is densely packed with outer membrane proteins (OMPs), which perform a variety of functions. How OMPs fold into this crowded environment remains an open question. Here, we review current knowledge about OFMP folding mechanisms in vitro and discuss how the need to fold to a stable native state has shaped their folding energy landscapes. We also highlight the role of chaperones and the β-barrel assembly machinery (BAM) in assisting OMP folding in vivo and discuss proposed mechanisms by which this fascinating machinery may catalyse OMP folding

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio