Intravascular tissue factor initiates coagulation via circulating microvesicles and platelets

Although tissue factor (TF), the principial initiator of physiological coagulation and pathological thrombosis, has recently been proposed to be present in human blood, the functional significance and location of the intravascular TF is unknown. In the plasma portion of blood, we found TF to be mainly associated with circulating microvesicles. By cell sorting with the specific marker CD42b, platelet-derived microvesicles were identified as a major location of the plasma TF. This was confirmed by the presence of full-length TF in microvesicles acutely shedded from the activated platelets. TF was observed to be stored in the α-granules and the open canalicular system of resting platelets and to be exposed on the cell surface after platelet activation. Functional competence of the blood-based TF was enabled when the microvesicles and platelets adhered to neutrophils, as mediated by P-selectin and neutrophil counterreceptor (PSGL-1, CD18 integrins) interactions. Moreover, neutrophil-secreted oxygen radical species supported the intravascular TF activity. The pools of platelet and microvesicle TF contributed additively and to a comparable extent to the overall blood TF activity, indicating a substantial participation of the microvesicle TF. Our results introduce a new concept of TF-mediated coagulation crucially dependent on TF associated with microvesicles and activated platelets, which principally enables the entire coagulation system to proceed on a restricted cell surface

Salience and valence of appearance in a population with a visible difference of appearance: Direct and moderated relationships with self-consciousness, anxiety and depression

Psychometric measures of appearance salience and valence, CARSAL and CARVAL, have been previously demonstrated to be key factors underpinning appearance related self-consciousness and negative affect in the general population. However, the extent to which the scales are appropriate for people with a visibly different appearance has not previously been reported. Neither has the moderating effect of appearance salience (CARSAL) on the relationship between appearance valence (CARVAL) and appearance self-consciousness, previously shown in a general population sample, been replicated with people who are visibly different. Twelve hundred and sixty five participants with a visible difference in either secondary care (n = 651) or the community (n = 614) provided data. Analysis confirmed the psychometric qualities of both CARSAL and CARVAL, and the conceptual independence of each scale. The scales also demonstrated independent and interdependent relationships with social anxiety and avoidance in relation to appearance, depression and anxiety. Appearance salience moderated the relationship with valence on these psychosocial measures. In summary, this paper corroborates the use of CARSAL and CARVAL with both visibly different and general adult populations for the measurement of appearance salience and valence. © 2014 Moss et al

WormQTL-public archive and analysis web portal for natural variation data in Caenorhabditis spp

Here, we present WormQTL (http://www.wormqtl.org), an easily accessible database enabling search, comparative analysis and meta-analysis of all data on variation in Caenorhabditis spp. Over the past decade, Caenorhabditis elegans has become instrumental for molecular quantitative genetics and the systems biology of natural variation. These efforts have resulted in a valuable amount of phenotypic, high-throughput molecular and genotypic data across different developmental worm stages and environments in hundreds of C. elegans strains. WormQTL provides a workbench of analysis tools for genotype-phenotype linkage and association mapping based on but not limited to R/qtl (http://www.rqtl.org). All data can be uploaded and downloaded using simple delimited text or Excel formats and are accessible via a public web user interface for biologists and R statistic and web service interfaces for bioinformaticians, based on open source MOLGENIS and xQTL workbench software. WormQTL welcomes data submissions from other worm researcher

XThe psychosocial impact of living with an ocular prosthesis

Objective: Many patients are satisfied with their ocular prosthesis, but some describe problems with social interactions, body image and self-esteem. Although both clinical practice and research suggest that the severity of a disfiguring condition does not predict distress, there has been little research with patients living with an ocular prosthesis. The objective was to explore the psychological impact of living with an artificial eye or cosmetic shell and determine the relationship between psychological well-being and clinical and psychosocial factors. Methods: A cross-sectional study between March and September 2008 at the ocular prosthesis clinic of Moorfields Eye Hospital, UK. The primary outcome measures were mood as measured by the Hospital Anxiety and Depression Scale (HADS) and appearance-related social anxiety and social avoidance, as measured by the Derriford Appearance Scale (DAS24). Results: Mean scores on the HADS and DAS24 were within normal range, but a considerable proportion of participants were experiencing significant levels of distress. Psychosocial adjustment was unrelated to most clinical and demographic variables, but was associated with a series of cognitive processes. Conclusions: Psychological variables, rather than clinical or demographic factors, are associated with how a patient adjusts to wearing an ocular prosthesis. Such factors might be amenable to change through psychosocial intervention

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE Xplore submission as part of WACV 202

Power estimation for non-standardized multisite studies

AbstractA concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions

Bridging Formal and Conceptual Semantics Selected papers of BRIDGE-14

The articles in this volume are the outcome of the successful BRIDGE Workshop held in Düsseldorf in 2014. The workshop gathered a number of distinguished researchers from formal semantics and conceptual semantics and aimed to initiate a deeper conversation and collaboration instead of separating the two sides as competing views. The workshop provided a platform to further discuss parallelisms on specific semantic issues on the one hand and on the other hand to confront opposed claims from the two different perspectives. This volume represents a selected number of high-quality papers presented at the workshop featuring various approaches to meaning from linguistics, logic and philosophy of language. The series 'Studies in Language and Cognition' explores issues of mental representation, linguistic structure and representation, and their interplay. The research presented in this series is grounded in the idea explored in the Collaborative Research Center 'The structure of representations in language, cognition and science' (SFB 991) that there is a universal format for the representation of linguistic and cognitive concepts

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences