Deep learning to detect optical coherence tomography-derived diabetic macular edema from retinal photographs: a multicenter validation study

PURPOSE: To validate the generalizability of a deep learning system (DLS) that detects diabetic macular edema (DME) from two-dimensional color fundus photography (CFP), where the reference standard for retinal thickness and fluid presence is derived from three-dimensional optical coherence tomography (OCT). DESIGN: Retrospective validation of a DLS across international datasets. PARTICIPANTS: Paired CFP and OCT of patients from diabetic retinopathy (DR) screening programs or retina clinics. The DLS was developed using datasets from Thailand, the United Kingdom (UK) and the United States and validated using 3,060 unique eyes from 1,582 patients across screening populations in Australia, India and Thailand. The DLS was separately validated in 698 eyes from 537 screened patients in the UK with mild DR and suspicion of DME based on CFP. METHODS: The DLS was trained using DME labels from OCT. Presence of DME was based on retinal thickening or intraretinal fluid. The DLS's performance was compared to expert grades of maculopathy and to a previous proof-of-concept version of the DLS. We further simulated integration of the current DLS into an algorithm trained to detect DR from CFPs. MAIN OUTCOME MEASURES: Superiority of specificity and non-inferiority of sensitivity of the DLS for the detection of center-involving DME, using device specific thresholds, compared to experts. RESULTS: Primary analysis in a combined dataset spanning Australia, India, and Thailand showed the DLS had 80% specificity and 81% sensitivity compared to expert graders who had 59% specificity and 70% sensitivity. Relative to human experts, the DLS had significantly higher specificity (p=0.008) and non-inferior sensitivity (p 50%) and a sensitivity of 100% (p=0.02 for sensitivity > 90%). CONCLUSIONS: The DLS can generalize to multiple international populations with an accuracy exceeding experts. The clinical value of this DLS to reduce false positive referrals, thus decreasing the burden on specialist eye care, warrants prospective evaluation

On the use of parataxonomy in biodiversity monitoring: a case study on wild flora

International audienceMonitoring programs that assess species-richness and turnover are now regarded as essential to document biodiversity loss worldwide. Implementation of such programs is impeded by a general decrease in the number of skilled naturalists. Here we studied how morphotypes, instead of species, might be used by unskilled participants (referred to as “volunteers”) to survey common plant communities. Our main questions were: (1) Can morphotypes be used as a robust estimator of species-richness (alpha-diversity) and assemblage turnover (Beta-diversity)? and (2) What is the robustness (reproducibility and repeatability) of such methods? Double inventories were performed on 150 plots in arable Weld margins, one by a non-expert using morphotypes, the other by a taxonomist using species. To test the robustness of morphotype identiWcation among participants, 20 additional plots were surveyed by eight volunteers using the same protocol. We showed that (1) the number of morphotypes identiWed by unskilled volunteers in a plot was always strongly correlated with species-richness. (2) Morphotypes were sensitive to diVerences among habitats but were less accurate than species to detect these diVerences. (3) Morphotype identiWcation varied signiWcantly within and between volunteers. Due to this lack of repeatability and reproducibility, parataxonomy cannot be considered a good surrogate for taxonomy. Nevertheless, assuming that morphotypes are identiWed with standardized methods, and that results are used only to evaluate gross species-richness but not species turnover, parataxonomy might be a valuable tool for rapid biodiversity assessment of common wild flora

The interrelated effect of sleep and learning in dogs (Canis familiaris); an EEG and behavioural study

The active role of sleep in memory consolidation is still debated, and due to a large between-species variation, the investigation of a wide range of different animal species (besides humans and laboratory rodents) is necessary. The present study applied a fully non-invasive methodology to study sleep and memory in domestic dogs, a species proven to be a good model of human awake behaviours. Polysomnography recordings performed following a command learning task provide evidence that learning has an effect on dogs’ sleep EEG spectrum. Furthermore, spectral features of the EEG were related to post-sleep performance improvement. Testing an additional group of dogs in the command learning task revealed that sleep or awake activity during the retention interval has both short- and long-term effects. This is the first evidence to show that dogs’ human-analogue social learning skills might be related to sleep-dependent memory consolidation

Human-computer collaboration for skin cancer recognition

The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-

The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants’ Ethical Decision Making

This study investigates the association of a broad set of variables with the ethical decision making of management accountants in Libya. Adopting a cross-sectional methodology, a questionnaire including four different ethical scenarios was used to gather data from 229 participants. For each scenario, ethical decision making was examined in terms of the recognition, judgment and intention stages of Rest’s model. A significant relationship was found between ethical recognition and ethical judgment and also between ethical judgment and ethical intention, but ethical recognition did not significantly predict ethical intention—thus providing support for Rest’s model. Organizational variables, age and educational level yielded few significant results. The lack of significance for codes of ethics might reflect their relative lack of development in Libya, in which case Libyan companies should pay attention to their content and how they are supported, especially in the light of the under-development of the accounting profession in Libya. Few significant results were also found for gender, but where they were found, males showed more ethical characteristics than females. This unusual result reinforces the dangers of gender stereotyping in business. Personal moral philosophy and moral intensity dimensions were generally found to be significant predictors of the three stages of ethical decision making studied. One implication of this is to give more attention to ethics in accounting education, making the connections between accounting practice and (in Libya) Islam. Overall, this study not only adds to the available empirical evidence on factors affecting ethical decision making, notably examining three stages of Rest’s model, but also offers rare insights into the ethical views of practising management accountants and provides a benchmark for future studies of ethical decision making in Muslim majority countries and other parts of the developing world

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Activated CD4+ T cells enhance radiation effect through the cooperation of interferon-γ and TNF-α

<p>Abstract</p> <p>Background</p> <p>Approaches that enhance radiation effect may lead to improved clinical outcome and decrease toxicity. Here we investigated whether activated CD4+ T cells (aCD4) can serve as an effective radiosensitizer.</p> <p>Methods</p> <p>CD4+ T cells were activated with anti-CD3 and anti-CD28 mAbs. Hela cells were presensitized with aCD4 or conditioned supernatant (aCD4S) or recombinant cytokines for 2 days, followed γ-irradiation. The treated cells were cultured for an additional 2 to 5 days for cell proliferation, cell cycle, and western blot assays. For confirmation, other cancer cell lines were also used.</p> <p>Results</p> <p>Presensitization of tumor cells with aCD4 greatly increased tumor cell growth inhibition. Soluble factors secreted from activated CD4⁺T cells were primarily responsible for the observed effect. IFN-γ seemed to play a major role. TNF-α, though inactive by itself, significantly augmented the radiosensitizing activity of IFN-γ. aCD4S, but not IFN-γ or IFN-γ/TNF-α combination, was found to enhance the γ-irradiation-induced G2/M phase arrest. Bax expression was highly upregulated in Hela cells presensitized with aCD4S followed by γ-irradiation. The radio-sensitizing activity of aCD4 is not uniquely observed with Hela cell line, but also seen with other cancer cell lines of various histology.</p> <p>Conclusions</p> <p>Our findings suggest possible molecular and cellular mechanisms that may help explain the radio-sensitization effect of activated lymphocytes, and may provide an improved strategy in the treatment of cancer with radiotherapy.</p

Identification and Characterization of a Novel Multipotent Sub-Population of Sca-1+ Cardiac Progenitor Cells for Myocardial Regeneration

The cardiac stem/progenitor cells from adult mice were seeded at low density in serum-free medium. The colonies thus obtained were expanded separately and assessed for expression of stem cell antigen-1 (Sca-1). Two colonies each with high Sca-1 (CSH1; 95.9%; CSH2; 90.6%) and low Sca-1 (CSL1; 37.1%; CSL2; 17.4%) expressing cells were selected for further studies. Sca-1⁺ cells (98.4%) isolated using Magnetic Cell Sorting System (MACS) from the hearts were used as a control. Although the selected populations were similar in surface marker expression (low in c-kit, CD45, CD34, CD31 and high in CD29), these cells exhibited diverse differentiation potential. Unlike CSH1, CSH2 expressed Nanog, TERT, Bcrp1, Nestin, Musashi1 and Isl-1, and also showed differentiation into osteogenic, chondrogenic, smooth muscle, endothelial and cardiac lineages. MACS sorted cells exhibited similar tendency albeit with relatively weaker differentiation potential. Transplantation of CSH2 cells into infarcted heart showed attenuated infarction size, significantly preserved left ventricular function and anterior wall thickness, and increased capillary density. We also observed direct differentiation of transplanted cells into endothelium and cardiomyocytes.The cardiac stem/progenitor cells isolated by a combined clonal selection and surface marker approach possessed multiple stem cell features important for cardiac regeneration