Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity

Background/Aims Prematurely born infants undergo costly, stressful eye examinations to uncover the small fraction with retinopathy of prematurity (ROP) that needs treatment to prevent blindness. The aim was to develop a prediction tool (DIGIROP-Screen) with 100% sensitivity and high specificity to safely reduce screening of those infants not needing treatment. DIGIROP-Screen was compared with four other ROP models based on longitudinal weights. Methods Data, including infants born at 24–30 weeks of gestational age (GA), for DIGIROP-Screen development (DevGroup, N=6991) originate from the Swedish National Registry for ROP. Three international cohorts comprised the external validation groups (ValGroups, N=1241). Multivariable logistic regressions, over postnatal ages (PNAs) 6–14 weeks, were validated. Predictors were birth characteristics, status and age at first diagnosed ROP and essential interactions. Results ROP treatment was required in 287 (4.1%)/6991 infants in DevGroup and 49 (3.9%)/1241 in ValGroups. To allow 100% sensitivity in DevGroup, specificity at birth was 53.1% and cumulatively 60.5% at PNA 8 weeks. Applying the same cut-offs in ValGroups, specificities were similar (46.3% and 53.5%). One infant with severe malformations in ValGroups was incorrectly classified as not needing screening. For all other infants, at PNA 6–14 weeks, sensitivity was 100%. In other published models, sensitivity ranged from 88.5% to 100% and specificity ranged from 9.6% to 45.2%. Conclusions DIGIROP-Screen, a clinical decision support tool using readily available birth and ROP screening data for infants born GA 24–30 weeks, in the European and North American populations tested can safely identify infants not needing ROP screening. DIGIROP-Screen had equal or higher sensitivity and specificity compared with other models. DIGIROP-Screen should be tested in any new cohort for validation and if not validated it can be modified using the same statistical approaches applied to a specific clinical setting

Prediction of survival of HPV16-negative, p16-negative oral cavity cancer patients using a 13-gene signature: A multicenter study using FFPE samples

Objectives: To WA the performance of an oral cancer prognostic 13-gene signature for the prediction of survival of patients diagnosed with HPV-negative and p16-negative oral cavity cancer. Materials and Methods: Diagnostic formalin-fixed paraffin-embedded oral cavity cancer tumor samples were obtained from the Fred Hutchinson Cancer Research Center/University of Washington, University of Calgary, University of Michigan, University of Utah, and seven ARCAGE study centers coordinated by the International Agency of Research on Cancer. RNA from 638 Human Papillomavirus (HPV)-negative and p16-negative samples was analyzed for the 13 genes using a NanoString assay. Ridge-penalized Cox regressions were applied to samples randomly split into discovery and validation sets to build models and evaluate the performance of the 13-gene signature in predicting 2-year oral cavity cancer-specific survival overall and separately for patients with early and late stage disease. Results: Among AJCC stage I/II patients, including the 13-gene signature in the model resulted in substantial improvement in the prediction of 2-year oral cavity cancer-specific survival. For models containing age and sex with and without the 13-gene signature score, the areas under the Receiver Operating Characteristic Curve (AUC) and partial AUC were 0.700 vs. 0.537 (p < 0.001), and 0.046 vs. 0.018 (p < 0.001), respectively. Improvement in predicting prognosis for AJCC stage III/IV disease also was observed, but to a lesser extent. Conclusions: If confirmed using tumor samples from a larger number of early stage oral cavity cancer patients, the 13-gene signature may inform personalized treatment of early stage HPV-negative and p16-negative oral cavity cancer patients

allodb: An R package for biomass estimation at globally distributed extratropical forest plots

Allometric equations for calculation of tree above-ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built-in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types

Reduced TRPC Channel Expression in Psoriatic Keratinocytes Is Associated with Impaired Differentiation and Enhanced Proliferation

Psoriasis is a characteristic inflammatory and scaly skin condition with typical histopathological features including increased proliferation and hampered differentiation of keratinocytes. The activation of innate and adaptive inflammatory cellular immune responses is considered to be the main trigger factor of the epidermal changes in psoriatic skin. However, the molecular players that are involved in enhanced proliferation and impaired differentiation of psoriatic keratinocytes are only partly understood. One important factor that regulates differentiation on the cellular level is Ca2+. In normal epidermis, a Ca2+ gradient exists that is disturbed in psoriatic plaques, favoring impaired keratinocyte proliferation. Several TRPC channels such as TRPC1, TRPC4, or TRPC6 are key proteins in the regulation of high [Ca2+]ex induced differentiation. Here, we investigated if TRPC channel function is impaired in psoriasis using calcium imaging, RT-PCR, western blot analysis and immunohistochemical staining of skin biopsies. We demonstrated substantial defects in Ca2+ influx in psoriatic keratinocytes in response to high extracellular Ca2+ levels, associated with a downregulation of all TRPC channels investigated, including TRPC6 channels. As TRPC6 channel activation can partially overcome this Ca2+ entry defect, specific TRPC channel activators may be potential new drug candidates for the topical treatment of psoriasis

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

A Low Concentration of Ethanol Impairs Learning but Not Motor and Sensory Behavior in Drosophila Larvae

Drosophila melanogaster has proven to be a useful model system for the genetic analysis of ethanol-associated behaviors. However, past studies have focused on the response of the adult fly to large, and often sedating, doses of ethanol. The pharmacological effects of low and moderate quantities of ethanol have remained understudied. In this study, we tested the acute effects of low doses of ethanol (∼7 mM internal concentration) on Drosophila larvae. While ethanol did not affect locomotion or the response to an odorant, we observed that ethanol impaired associative olfactory learning when the heat shock unconditioned stimulus (US) intensity was low but not when the heat shock US intensity was high. We determined that the reduction in learning at low US intensity was not a result of ethanol anesthesia since ethanol-treated larvae responded to the heat shock in the same manner as untreated animals. Instead, low doses of ethanol likely impair the neuronal plasticity that underlies olfactory associative learning. This impairment in learning was reversible indicating that exposure to low doses of ethanol does not leave any long lasting behavioral or physiological effects

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2