Key Visual Features for Rapid Categorization of Animals in Natural Scenes

In speeded categorization tasks, decisions could be based on diagnostic target features or they may need the activation of complete representations of the object. Depending on task requirements, the priming of feature detectors through top–down expectation might lower the threshold of selective units or speed up the rate of information accumulation. In the present paper, 40 subjects performed a rapid go/no-go animal/non-animal categorization task with 400 briefly flashed natural scenes to study how performance depends on physical scene characteristics, target configuration, and the presence or absence of diagnostic animal features. Performance was evaluated both in terms of accuracy and speed and d′ curves were plotted as a function of reaction time (RT). Such d′ curves give an estimation of the processing dynamics for studied features and characteristics over the entire subject population. Global image characteristics such as color and brightness do not critically influence categorization speed, although they slightly influence accuracy. Global critical factors include the presence of a canonical animal posture and animal/background size ratio suggesting the role of coarse global form. Performance was best for both accuracy and speed, when the animal was in a typical posture and when it occupied about 20–30% of the image. The presence of diagnostic animal features was another critical factor. Performance was significantly impaired both in accuracy (drop 3.3–7.5%) and speed (median RT increase 7–16 ms) when diagnostic animal parts (eyes, mouth, and limbs) were missing. Such animal features were shown to influence performance very early when only 15–25% of the response had been produced. In agreement with other experimental and modeling studies, our results support fast diagnostic recognition of animals based on key intermediate features and priming based on the subject's expertise

Unusual use of objects after unilateral brain damage. The technical reasoning model.

International audienceIt has been suggested that gesture engrams, conceptual knowledge and/or the ability to infer function from structure can support object use. The present paper proposes an alternative view which is based upon the idea that object use requires solely the ability to reason about technical means provided by objects. Technical means are abstract principles which are not linked with any object representation (e.g., cutting involves the opposition between dense and permeable material). The technical reasoning model predicts that the inability to perform technical reasoning should impair performance in any situation requiring the use of objects (in a conventional way or not). Twenty left brain-damaged (LBD) patients, 11 right brain-damaged (RBD) patients and 41 healthy controls were examined on experimental tests assessing the conventional use of objects (e.g., screwing a screw with a screwdriver), conceptual knowledge about object function, pantomime of object use and recognition of object utilization gestures. We also designed the Unusual Use of Objects test, which demands unusual applications of objects to achieve a purpose for which the usually applied object is not provided (e.g., screwing a screw with a knife). The key findings are that only LBD patients have more difficulties on the Unusual Use of Objects Test than controls or RBD patients, and that the severity of their impairment is correlated with that on conventional use of objects. Correlations with tests assessing conceptual knowledge as well as with tests of pantomime of object use and recognition of object utilization gestures were weaker. These results support the technical reasoning model and question the role of conceptual knowledge and gesture engrams in object use. Since the technical reasoning model also predicts two distinct technical disorders, the discussion focuses on the existence of these disorders in regard to individual performance profiles obtained in the Unusual Use of Objects test

Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.

AIMS: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. METHODS AND RESULTS: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health. CONCLUSION: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare

Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: r(g) = 0.098, p = 2.3 x 10(-8)) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: r(g) = 0.137, p = 2.0 x 10(-12)). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis

Obesity, Metabolic Factors and Risk of Different Histological Types of Lung Cancer: A Mendelian Randomization Study

Background: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior

Open Data for Global Science

The global science system stands at a critical juncture. On the one hand, it is overwhelmed by a hidden avalanche of ephemeral bits that are central components of modern research and of the emerging ‘cyberinfrastructure’4 for e-Science.5 The rational management and exploitation of this cascade of digital assets offers boundless opportunities for research and applications. On the other hand, the ability to access and use this rising flood of data seems to lag behind, despite the rapidly growing capabilities of information and communication technologies (ICTs) to make much more effective use of those data. As long as the attention for data policies and data management by researchers, their organisations and their funders does not catch up with the rapidly changing research environment, the research policy and funding entities in many cases will perpetuate the systemic inefficiencies, and the resulting loss or underutilisation of valuable data resources derived from public investments. There is thus an urgent need for rationalised national strategies and more coherent international arrangements for sustainable access to public research data, both to data produced directly by government entities and to data generated in academic and not-for-profit institutions with public funding. In this chapter, we examine some of the implications of the ‘data driven’ research and possible ways to overcome existing barriers to accessibility of public research data. Our perspective is framed in the context of the predominantly publicly funded global science system. We begin by reviewing the growing role of digital data in research and outlining the roles of stakeholders in the research community in developing data access regimes. We then discuss the hidden costs of closed data systems, the benefits and limitations of openness as the default principle for data access, and the emerging open access models that are beginning to form digitally networked commons. We conclude by examining the rationale and requirements for developing overarching international principles from the top down, as well as flexible, common-use contractual templates from the bottom up, to establish data access regimes founded on a presumption of openness, with the goal of better capturing the benefits from the existing and future scientific data assets. The ‘Principles and Guidelines for Access to Research Data from Public Funding’ from the Organisation for Economic Cooperation and Development (OECD), reported on in another article by Pilat and Fukasaku,6 are the most important recent example of the high-level (inter)governmental approach. The common-use licenses promoted by the Science Commons are a leading example of flexible arrangements originating within the community. Finally, we should emphasise that we focus almost exclusively on the policy—the institutional, socioeconomic, and legal aspects of data access—rather than on the technical and management practicalities that are also important, but beyond the scope of this article

Updated Guidance Regarding The Risk ofAllergic Reactions to COVID-19 Vaccines and Recommended Evaluation and Management: A GRADE Assessment, and International Consensus Approach

This guidance updates 2021 GRADE (Grading of Recommendations Assessment, Development and Evaluation) recommendations regarding immediate allergic reactions following coronavirus disease 2019 (COVID-19) vaccines and addresses revaccinating individuals with first-dose allergic reactions and allergy testing to determine revaccination outcomes. Recent meta-analyses assessed the incidence of severe allergic reactions to initial COVID-19 vaccination, risk of mRNA-COVID-19 revaccination after an initial reaction, and diagnostic accuracy of COVID-19 vaccine and vaccine excipient testing in predicting reactions. GRADE methods informed rating the certainty of evidence and strength of recommendations. A modified Delphi panel consisting of experts in allergy, anaphylaxis, vaccinology, infectious diseases, emergency medicine, and primary care from Australia, Canada, Europe, Japan, South Africa, the United Kingdom, and the United States formed the recommendations. We recommend vaccination for persons without COVID-19 vaccine excipient allergy and revaccination after a prior immediate allergic reaction. We suggest against \u3e 15-minute postvaccination observation. We recommend against mRNA vaccine or excipient skin testing to predict outcomes. We suggest revaccination of persons with an immediate allergic reaction to the mRNA vaccine or excipients be performed by a person with vaccine allergy expertise in a properly equipped setting. We suggest against premedication, split-dosing, or special precautions because of a comorbid allergic history

A High Throughput Genetic Screen Identifies New Early Meiotic Recombination Functions in Arabidopsis thaliana

Meiotic recombination is initiated by the formation of numerous DNA double-strand breaks (DSBs) catalysed by the widely conserved Spo11 protein. In Saccharomyces cerevisiae, Spo11 requires nine other proteins for meiotic DSB formation; however, unlike Spo11, few of these are conserved across kingdoms. In order to investigate this recombination step in higher eukaryotes, we took advantage of a high-throughput meiotic mutant screen carried out in the model plant Arabidopsis thaliana. A collection of 55,000 mutant lines was screened, and spo11-like mutations, characterised by a drastic decrease in chiasma formation at metaphase I associated with an absence of synapsis at prophase, were selected. This screen led to the identification of two populations of mutants classified according to their recombination defects: mutants that repair meiotic DSBs using the sister chromatid such as Atdmc1 or mutants that are unable to make DSBs like Atspo11-1. We found that in Arabidopsis thaliana at least four proteins are necessary for driving meiotic DSB repair via the homologous chromosomes. These include the previously characterised DMC1 and the Hop1-related ASY1 proteins, but also the meiotic specific cyclin SDS as well as the Hop2 Arabidopsis homologue AHP2. Analysing the mutants defective in DSB formation, we identified the previously characterised AtSPO11-1, AtSPO11-2, and AtPRD1 as well as two new genes, AtPRD2 and AtPRD3. Our data thus increase the number of proteins necessary for DSB formation in Arabidopsis thaliana to five. Unlike SPO11 and (to a minor extent) PRD1, these two new proteins are poorly conserved among species, suggesting that the DSB formation mechanism, but not its regulation, is conserved among eukaryotes

Association between T2-related co-morbidities and effectiveness of biologics in severe asthma

Acknowledgments The authors thank Mr. Joash Tan (BSc, Hons), of the Observational and Pragmatic Research Institute (OPRI), and Ms Andrea Lim (BSc, Hons) of the Observational Pragmatic Research Institute (OPRI) for their editorial and formatting assistance that supported the development of this publication. Funding statement: This study was conducted by the Observational and Pragmatic Research Institute (OPRI) Pte Ltd and was partially funded by Optimum Patient Care Global and AstraZeneca Ltd. AstraZeneca UK LimitedPeer reviewe