Towards End-to-end Video-based Eye-Tracking

Estimating eye-gaze from images alone is a challenging task, in large parts due to un-observable person-specific factors. Achieving high accuracy typically requires labeled data from test users which may not be attainable in real applications. We observe that there exists a strong relationship between what users are looking at and the appearance of the user's eyes. In response to this understanding, we propose a novel dataset and accompanying method which aims to explicitly learn these semantic and temporal relationships. Our video dataset consists of time-synchronized screen recordings, user-facing camera views, and eye gaze data, which allows for new benchmarks in temporal gaze tracking as well as label-free refinement of gaze. Importantly, we demonstrate that the fusion of information from visual stimuli as well as eye images can lead towards achieving performance similar to literature-reported figures acquired through supervised personalization. Our final method yields significant performance improvements on our proposed EVE dataset, with up to a 28 percent improvement in Point-of-Gaze estimates (resulting in 2.49 degrees in angular error), paving the path towards high-accuracy screen-based eye tracking purely from webcam sensors. The dataset and reference source code are available at https://ait.ethz.ch/projects/2020/EVEComment: Accepted at ECCV 202

Guidelines for reporting the quality of clinical case reports in Endodontics: a development protocol.

Case reports are used to communicate interesting, new or rare condition/s, innovative treatment approaches or novel techniques. Apart from informing readers, such information has the potential to contribute towards further scientific studies and the development of newer management modalities. Reporting guidelines are used to inform authors of the quality standards required to ensure their case report is accurate, complete and transparent. The aim of this project is to develop and disseminate new guidelines - Preferred Reporting Items for Case reports in Endodontics (PRICE). The primary aim is to aid authors when constructing case reports in the field of Endodontics to ensure the highest possible reporting standards are adopted. The project leaders (PD and VN) formed a steering committee comprising of six additional members. Subsequently, a four-phase consensus process will be used: 1. Pre-online consensus activities (literature search, creating PRICE guidelines), 2. Online Consensus (Delphi Process), 3. Face-to-face consensus meeting, and 4. Post-meeting activities. The steering committee will develop the PRICE guidelines by identifying relevant items (quality standards) derived from the CAse REport guidelines and Clinical and Laboratory Images in Publications principles, focussing on the content of case reports. Following this, the steering committee will identify a PRICE Delphi Group (PDG) consisting of 30 members including academicians, practitioners, and members of the public. The individual items (components) of the PRICE checklist will be evaluated by the PDG based on a 9-point Likert scale. Only items scored between 7 and 9 by 70% or more members will be included in the draft checklist. The Delphi process will be continued until a consensus is reached and a final set of items agreed by the PDG members. Following this, a PRICE Face-to-Face meeting group (PFMG) will be formed with 20 members to achieve a final consensus. The final consensus-based checklist and flow diagram will be evaluated and approved by selected members of the PDG and PFMG. The approved PRICE checklist will be published in relevant journals, and disseminated via contacts in academic institutions and national endodontic societies, as well as being presented at scientific/clinical meetings. This article is protected by copyright. All rights reserved

Narratives for drug design

We explore the role of narratives of complex systems in anti-cancer drug design. We set out the value of narratives relating to cancer in promoting awareness of risky behaviour and in supporting decision-making regarding treatment options. We present cancer as a dysregulated, complex system that has emergent behaviours at multiple scales, and is governed by dynamical spatio-temporal processes. We show that this system changes structure and function in response to anti-cancer drugs, and explain that these changes are sufficiently complex to impede effective drug design. We pose what narrative might offer to support the process of drug design, providing an example of work done to date that might serve as a foundation for narrating complexity. We suggest ways of using this work combined with that of others to begin to consider narrating drug design

Subarachnoidal Neurocysticercosis non-responsive to cysticidal drugs: a case series

<p>Abstract</p> <p>Background</p> <p>Neurocysticercosis (NC) is one of the most frequent parasitic diseases of the central nervous system. Cysticidal drugs, albendazole and praziquantel, are generally effective when parasites localize in the parenchyma. In contrast, parasites lodged in the subarachnoid basal cisterns are less responsive to treatment.</p> <p>Case Presentation</p> <p>The clinical and radiological pictures of six Mexican patients non-respondent to cysticidal treatment are presented.</p> <p>Conclusions</p> <p>The possible factors involved in the cysticidal non-response are discussed and hints are provided of potentially useful changes to therapeutic protocols.</p

Yeast Based Small Molecule Screen for Inhibitors of SARS-CoV

Severe acute respiratory coronavirus (SARS-CoV) emerged in 2002, resulting in roughly 8000 cases worldwide and 10% mortality. The animal reservoirs for SARS-CoV precursors still exist and the likelihood of future outbreaks in the human population is high. The SARS-CoV papain-like protease (PLP) is an attractive target for pharmaceutical development because it is essential for virus replication and is conserved among human coronaviruses. A yeast-based assay was established for PLP activity that relies on the ability of PLP to induce a pronounced slow-growth phenotype when expressed in S. cerevisiae. Induction of the slow-growth phenotype was shown to take place over a 60-hour time course, providing the basis for conducting a screen for small molecules that restore growth by inhibiting the function of PLP. Five chemical suppressors of the slow-growth phenotype were identified from the 2000 member NIH Diversity Set library. One of these, NSC158362, potently inhibited SARS-CoV replication in cell culture without toxic effects on cells, and it specifically inhibited SARS-CoV replication but not influenza virus replication. The effect of NSC158362 on PLP protease, deubiquitinase and anti-interferon activities was investigated but the compound did not alter these activities. Another suppressor, NSC158011, demonstrated the ability to inhibit PLP protease activity in a cell-based assay. The identification of these inhibitors demonstrated a strong functional connection between the PLP-based yeast assay, the inhibitory compounds, and SARS-CoV biology. Furthermore the data with NSC158362 suggest a novel mechanism for inhibition of SARS-CoV replication that may involve an unknown activity of PLP, or alternatively a direct effect on a cellular target that modifies or bypasses PLP function in yeast and mammalian cells

Computing the Viscosity of Supercooled Liquids: Markov Network Model

The microscopic origin of glass transition, when liquid viscosity changes continuously by more than ten orders of magnitude, is challenging to explain from first principles. Here we describe the detailed derivation and implementation of a Markovian Network model to calculate the shear viscosity of deeply supercooled liquids based on numerical sampling of an atomistic energy landscape, which sheds some light on this transition. Shear stress relaxation is calculated from a master-equation description in which the system follows a transition-state pathway trajectory of hopping among local energy minima separated by activation barriers, which is in turn sampled by a metadynamics-based algorithm. Quantitative connection is established between the temperature variation of the calculated viscosity and the underlying potential energy and inherent stress landscape, showing a different landscape topography or “terrain” is needed for low-temperature viscosity (of order 10[superscript 7] Pa·s) from that associated with high-temperature viscosity (10[superscript −5] Pa·s). Within this range our results clearly indicate the crossover from an essentially Arrhenius scaling behavior at high temperatures to a low-temperature behavior that is clearly super-Arrhenius (fragile) for a Kob-Andersen model of binary liquid. Experimentally the manifestation of this crossover in atomic dynamics continues to raise questions concerning its fundamental origin. In this context this work explicitly demonstrates that a temperature-dependent “terrain” characterizing different parts of the same potential energy surface is sufficient to explain the signature behavior of vitrification, at the same time the notion of a temperature-dependent effective activation barrier is quantified.Corning IncorporatedBoston University. Center for Scientific Computing and VisualizationNational Science Foundation (U.S.) (grant DMR-1008104)National Science Foundation (U.S.) (grant DMR-0520020)United States. Air Force Office of Scientific Research (FA9550-08-1-0325

Cherenkov radiation control via self-accelerating wave-packets

Cherenkov radiation is a ubiquitous phenomenon in nature. It describes electromagnetic radiation from a charged particle moving in a medium with a uniform velocity larger than the phase velocity of light in the same medium. Such a picture is typically adopted in the investigation of traditional Cherenkov radiation as well as its counterparts in different branches of physics, including nonlinear optics, spintronics and plasmonics. In these cases, the radiation emitted spreads along a “cone”, making it impractical for most applications. Here, we employ a self-accelerating optical pump wave-packet to demonstrate controlled shaping of one type of generalized Cherenkov radiation - dispersive waves in optical fibers. We show that, by tuning the parameters of the wave-packet, the emitted waves can be judiciously compressed and focused at desired locations, paving the way to such control in any physical system

Development of a video-based education and process change intervention to improve advance cardiopulmonary resuscitation decision-making

Background: Advance cardiopulmonary resuscitation (CPR) decision-making and escalation of care discussions are variable in routine clinical practice. We aimed to explore physician barriers to advance CPR decision-making in an inpatient hospital setting and develop a pragmatic intervention to support clinicians to undertake and document routine advance care planning discussions. Methods: Two focus groups, which involved eight consultants and ten junior doctors, were conducted following a review of the current literature. A subsequent iterative consensus process developed two intervention elements: (i) an updated ‘Goals of Patient Care’ (GOPC) form and process; (ii) an education video and resources for teaching advance CPR decision-making and communication. A multidisciplinary group of health professionals and policymakers with experience in systems development, education and research provided critical feedback. Results: Three key themes emerged from the focus groups and the literature, which identified a structure for the intervention: (i) knowing what to say; (ii) knowing how to say it; (iii) wanting to say it. The themes informed the development of a video to provide education about advance CPR decision-making framework, improving communication and contextualising relevant clinical issues. Critical feedback assisted in refining the video and further guided development and evolution of a medical GOPC approach to discussing and recording medical treatment and advance care plans. Conclusion: Through an iterative process of consultation and review, video-based education and an expanded GOPC form and approach were developed to address physician and systemic barriers to advance CPR decisionmaking and documentation. Implementation and evaluation across hospital settings is required to examine utility and determine effect on quality of care

Uncovering Genes with Divergent mRNA-Protein Dynamics in Streptomyces coelicolor

Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in many studies, examples of divergent trends are frequently observed. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in microbiology as they pertain to the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides (iTRAQ™) enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes exhibit mRNA-protein discordance in a similar fashion. Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level

Discovery of potent, novel, non-toxic anti-malarial compounds via quantum modelling, virtual screening and in vitro experimental validation

<p>Abstract</p> <p>Background</p> <p>Developing resistance towards existing anti-malarial therapies emphasize the urgent need for new therapeutic options. Additionally, many malaria drugs in use today have high toxicity and low therapeutic indices. Gradient Biomodeling, LLC has developed a quantum-model search technology that uses quantum similarity and does not depend explicitly on chemical structure, as molecules are rigorously described in fundamental quantum attributes related to individual pharmacological properties. Therapeutic activity, as well as toxicity and other essential properties can be analysed and optimized simultaneously, independently of one another. Such methodology is suitable for a search of novel, non-toxic, active anti-malarial compounds.</p> <p>Methods</p> <p>A set of innovative algorithms is used for the fast calculation and interpretation of electron-density attributes of molecular structures at the quantum level for rapid discovery of prospective pharmaceuticals. Potency and efficacy, as well as additional physicochemical, metabolic, pharmacokinetic, safety, permeability and other properties were characterized by the procedure. Once quantum models are developed and experimentally validated, the methodology provides a straightforward implementation for lead discovery, compound optimizzation and <it>de novo </it>molecular design.</p> <p>Results</p> <p>Starting with a diverse training set of 26 well-known anti-malarial agents combined with 1730 moderately active and inactive molecules, novel compounds that have strong anti-malarial activity, low cytotoxicity and structural dissimilarity from the training set were discovered and experimentally validated. Twelve compounds were identified <it>in silico </it>and tested <it>in vitro</it>; eight of them showed anti-malarial activity (IC50 ≤ 10 μM), with six being very effective (IC50 ≤ 1 μM), and four exhibiting low nanomolar potency. The most active compounds were also tested for mammalian cytotoxicity and found to be non-toxic, with a therapeutic index of more than 6,900 for the most active compound.</p> <p>Conclusions</p> <p>Gradient's metric modelling approach and electron-density molecular representations can be powerful tools in the discovery and design of novel anti-malarial compounds. Since the quantum models are agnostic of the particular biological target, the technology can account for different mechanisms of action and be used for <it>de novo </it>design of small molecules with activity against not only the asexual phase of the malaria parasite, but also against the liver stage of the parasite development, which may lead to true causal prophylaxis.</p