Eye movements and reading in glaucoma: observations on patients with advanced visual field loss

Purpose To investigate the relationship between reading speed and eye movements in patients with advanced glaucomatous visual field (VF) defects and age-similar visually healthy people. Methods Eighteen patients with advanced bilateral VF defects (mean age: 71, standard deviation [SD]: 7 years) and 39 controls (mean age: 67, SD: 8 years) had reading speed measured using short passages of text on a computer set-up incorporating eye tracking. Scanpaths were plotted and analysed from these experiments to derive measures of ‘perceptual span’ (total number of letters read per number of saccades) and ‘text saturation’ (the distance between the first and last fixation on lines of text). Another eye movement measure, termed ‘saccadic frequency’ (total number of saccades made to read a single word), was derived from a separate lexical decision task, where words were presented in isolation. Results Significant linear association was demonstrated between perceptual span and reading speed in patients (R2=0.42) and controls (R2=0.56). Linear association between saccadic frequency during the LDT and reading speed was also found in patients (R2=0.42), but not in controls (R2=0.02). Patients also exhibited greater average text saturation than controls (P=0.004). Conclusion Some, but not all, patients with advanced VF defects read slower than controls using short text passages. Differences in eye movement behaviour may partly account for this variability in patients. These patients were shown to saturate lines of text more during reading, which may explain previously-reported difficulties with sustained reading

Structural basis for the RING catalyzed synthesis of K63 linked ubiquitin chains

This work was supported by grants from Cancer Research UK (C434/A13067), the Wellcome Trust (098391/Z/12/Z) and Biotechnology and Biological Sciences Research Council (BB/J016004/1).The RING E3 ligase catalysed formation of lysine 63 linked ubiquitin chains by the Ube2V2–Ubc13 E2 complex is required for many important biological processes. Here we report the structure of the RING domain dimer of rat RNF4 in complex with a human Ubc13~Ub conjugate and Ube2V2. The structure has captured Ube2V2 bound to the acceptor (priming) ubiquitin with Lys63 in a position that could lead to attack on the linkage between the donor (second) ubiquitin and Ubc13 that is held in the active “folded back” conformation by the RING domain of RNF4. The interfaces identified in the structure were verified by in vitro ubiquitination assays of site directed mutants. This represents the first view of the synthesis of Lys63 linked ubiquitin chains in which both substrate ubiquitin and ubiquitin-loaded E2 are juxtaposed to allow E3 ligase mediated catalysis.PostprintPeer reviewe

Preferential Paths of Air-water Two-phase Flow in Porous Structures with Special Consideration of Channel Thickness Effects.

Accurate understanding and predicting the flow paths of immiscible two-phase flow in rocky porous structures are of critical importance for the evaluation of oil or gas recovery and prediction of rock slides caused by gas-liquid flow. A 2D phase field model was established for compressible air-water two-phase flow in heterogenous porous structures. The dynamic characteristics of air-water two-phase interface and preferential paths in porous structures were simulated. The factors affecting the path selection of two-phase flow in porous structures were analyzed. Transparent physical models of complex porous structures were prepared using 3D printing technology. Tracer dye was used to visually observe the flow characteristics and path selection in air-water two-phase displacement experiments. The experimental observations agree with the numerical results used to validate the accuracy of phase field model. The effects of channel thickness on the air-water two-phase flow behavior and paths in porous structures were also analyzed. The results indicate that thick channels can induce secondary air flow paths due to the increase in flow resistance; consequently, the flow distribution is different from that in narrow channels. This study provides a new reference for quantitatively analyzing multi-phase flow and predicting the preferential paths of immiscible fluids in porous structures

Factors considered by medical students when formulating their specialty preferences in Japan: findings from a qualitative study

<p>Abstract</p> <p>Background</p> <p>Little research addresses how medical students develop their choice of specialty training in Japan. The purpose of this research was to elucidate factors considered by Japanese medical students when formulating their specialty choice.</p> <p>Methods</p> <p>We conducted qualitative interviews with 25 Japanese medical students regarding factors influencing specialty preference and their views on roles of primary versus specialty care. We qualitatively analyzed the data to identify factors students consider when developing specialty preferences, to understand their views about primary and subspecialty care, and to construct models depicting the pathways to specialization.</p> <p>Results</p> <p>Students mention factors such as illness in self or close others, respect for family member in the profession, preclinical experiences in the curriculum such as labs and dissection, and aspects of patient care such as the clinical atmosphere, charismatic role models, and doctor-patient communication as influential on their specialty preferences. Participating students could generally distinguish between subspecialty care and primary care, but not primary care and family medicine. Our analysis yields a "Two Career" model depicting how medical graduates can first train for hospital-based specialty practice, and then switch to mixed primary/specialty care outpatient practice years later without any requirement for systematic training in principles of primary care practice.</p> <p>Conclusion</p> <p>Preclinical and clinical experiences as well as role models are reported by Japanese students as influential factors when formulating their specialty preferences. Student understanding of family medicine as a discipline is low in Japan. Students with ultimate aspirations to practice outpatient primary care medicine do not need to commit to systematic primary care training after graduation. The Two Career model of specialization leaves the door open for medical graduates to enter primary care practice at anytime regardless of post-graduate residency training choice.</p

Standardised data on initiatives—STARDIT: Beta version

Background and objective: There is currently no standardised way to share information across disciplines about initiatives, including fields such as health, environment, basic science, manufacturing, media and international development. All problems, including complex global problems such as air pollution and pandemics require reliable data sharing between disciplines in order to respond effectively. Current reporting methods also lack information about the ways in which different people and organisations are involved in initiatives, making it difficult to collate and appraise data about the most effective ways to involve different people. The objective of STARDIT (Standardised Data on Initiatives) is to address current limitations and inconsistencies in sharing data about initiatives. The STARDIT system features standardised data reporting about initiatives, including who has been involved, what tasks they did, and any impacts observed. STARDIT was created to help everyone in the world find and understand information about collective human actions, which are referred to as ‘initiatives’. STARDIT enables multiple categories of data to be reported in a standardised way across disciplines, facilitating appraisal of initiatives and aiding synthesis of evidence for the most effective ways for people to be involved in initiatives. This article outlines progress to date on STARDIT; current usage; information about submitting reports; planned next steps and how anyone can become involved. Method: STARDIT development is guided by participatory action research paradigms, and has been co-created with people from multiple disciplines and countries. Co-authors include cancer patients, people affected by rare diseases, health researchers, environmental researchers, economists, librarians and academic publishers. The co-authors also worked with Indigenous peoples from multiple countries and in partnership with an organisation working with Indigenous Australians. Results and discussion: Over 100 people from multiple disciplines and countries have been involved in co-designing STARDIT since 2019. STARDIT is the first open access web-based data-sharing system which standardises the way that information about initiatives is reported across diverse fields and disciplines, including information about which tasks were done by which stakeholders. STARDIT is designed to work with existing data standards. STARDIT data will be released into the public domain (CC0) and integrated into Wikidata; it works across multiple languages and is both human and machine readable. Reports can be updated throughout the lifetime of an initiative, from planning to evaluation, allowing anyone to be involved in reporting impacts and outcomes. STARDIT is the first system that enables sharing of standardised data about initiatives across disciplines. A working Beta version was publicly released in February 2021 (ScienceforAll.World/STARDIT). Subsequently, STARDIT reports have been created for peer-reviewed research in multiple journals and multiple research projects, demonstrating the usability. In addition, organisations including Cochrane and Australian Genomics have created prospective reports outlining planned initiatives. Conclusions: STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems

Parity-Violating Electron Scattering from 4He and the Strange Electric Form Factor of the Nucleon

We have measured the parity-violating electroweak asymmetry in the elastic scattering of polarized electrons from ^4He at an average scattering angle = 5.7 degrees and a four-momentum transfer Q^2 = 0.091 GeV^2. From these data, for the first time, the strange electric form factor of the nucleon G^s_E can be isolated. The measured asymmetry of A_PV = (6.72 +/- 0.84 (stat) +/- 0.21 (syst) parts per million yields a value of G^s_E = -0.038 +/- 0.042 (stat) +/- 0.010 (syst), consistent with zero

Dengue Virus Targets the Adaptor Protein MITA to Subvert Host Innate Immunity

Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN). We found that activation of interferon regulatory factor 3 (IRF3) triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA) but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓96G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT) stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity

GENN: A GEneral Neural Network for Learning Tabulated Data with Examples from Protein Structure Prediction

We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its main strength is its efficient handling of the input data, enabling learning from large datasets. GENN is built on a two-layered neural network and has the option to use separate inputs–output pairs or window-based data using data structures to efficiently represent input–output pairs. The program was tested on predicting the accessible surface area of globular proteins, scoring proteins according to similarity to native, predicting protein disorder, and has performed remarkably well. In this paper we describe the program and its use. Specifically, we give as an example the construction of a similarity to native protein scoring function that was constructed using GENN. The source code and Linux executables for GENN are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org. Bugs and problems with the GENN program should be reported to EF

miR-34a Repression in Proneural Malignant Gliomas Upregulates Expression of Its Target PDGFRA and Promotes Tumorigenesis

Glioblastoma (GBM) and other malignant gliomas are aggressive primary neoplasms of the brain that exhibit notable refractivity to standard treatment regimens. Recent large-scale molecular profiling has revealed distinct disease subclasses within malignant gliomas whose defining genomic features highlight dysregulated molecular networks as potential targets for therapeutic development. The “proneural” designation represents the largest and most heterogeneous of these subclasses, and includes both a large fraction of GBMs along with most of their lower-grade astrocytic and oligodendroglial counterparts. The pathogenesis of proneural gliomas has been repeatedly associated with dysregulated PDGF signaling. Nevertheless, genomic amplification or activating mutations involving the PDGF receptor (PDGFRA) characterize only a subset of proneural GBMs, while the mechanisms driving dysregulated PDGF signaling and downstream oncogenic networks in remaining tumors are unclear. MicroRNAs (miRNAs) are a class of small, noncoding RNAs that regulate gene expression by binding loosely complimentary sequences in target mRNAs. The role of miRNA biology in numerous cancer variants is well established. In an analysis of miRNA involvement in the phenotypic expression and regulation of oncogenic PDGF signaling, we found that miR-34a is downregulated by PDGF pathway activation in vitro. Similarly, analysis of data from the Cancer Genome Atlas (TCGA) revealed that miR-34a expression is significantly lower in proneural gliomas compared to other tumor subtypes. Using primary GBM cells maintained under neurosphere conditions, we then demonstrated that miR-34a specifically affects growth of proneural glioma cells in vitro and in vivo. Further bioinformatic analysis identified PDGFRA as a direct target of miR-34a and this interaction was experimentally validated. Finally, we found that PDGF-driven miR-34a repression is unlikely to operate solely through a p53-dependent mechanism. Taken together, our data support the existence of reciprocal negative feedback regulation involving miR-34 and PDGFRA expression in proneural gliomas and, as such, identify a subtype specific therapeutic potential for miR-34a

Display of probability densities for data from a continuous distribution

Based on cumulative distribution functions, Fourier series expansion and Kolmogorov tests, we present a simple method to display probability densities for data drawn from a continuous distribution. It is often more efficient than using histograms.Comment: 5 pages, 4 figures, presented at Computer Simulation Studies XXIV, Athens, GA, 201