Hurricanes: A Primer for the Aviation Professional

This article has been written in response to the recent increase in hurricane activity within the Atlantic basin and the expectation that this heightened activity will continue for another 20 to 30 years. Its purpose is to educate aviation professionals on the hurricane phenomenon. The topics presented are focused, keying on information that will help these individuals better protect their aircraft and other resources. The issue of aircraft evacuation in response to a threatening hurricane is addressed throughout this paper

The Certainty of Uncertainty: Understanding and Exploiting Probability-Based Aviation Weather Products

Probability-based weather forecasts (i.e., forecasts that quantify uncertainty) have been available for certain weather elements for over 40 years; for example, the probability of precipitation forecast. More recently, probability forecasts designed specifically for aviation have become widely available on the internet through two National Weather Service (NWS) forecast centers, the Aviation Weather Center (AWC) and the Environmental Modeling Center (EMC). Although these probability-based products are generally not recognized by the Federal Aviation Administration (FAA) for operational use, their potential is beginning to be recognized by the aviation community. For example, the Joint Program Development Office (JPDO) Next Generation Air Transportation System (NEXTGEN) Air Traffic Management (ATM)-Weather Integration Plan cites probabilistic forecasts as playing a key role in future air traffic management decision support tools by the year 2023 (JPDO, 2010). Specifically, the JPDO identified the integration of weather uncertainty information (i.e., probabilities and confidence information) into decision-support tools as the highest of four levels of weather integration into the air traffic management system

Quantifying the Effects of Humidity on Density Altitude Calculations for Professional Aviation Education

The effects of humidity on density altitude are quantified in detail and graphically represented as a function of temperature and dew-point temperature for ease of use in professional aviation education. A ten-year climatology of dew-point temperatures for various representative locations throughout the United States is created to provide a basis for comparison and use with the graphical displays. Density altitude is demonstrated to be a function only of dew-point temperature for a given pressure altitude. The absolute errors between density altitude calculations that incorporate humidity to those that do not are combined with linear regression techniques to create a simple rule of thumb for diagnosing the impact of humidity on density altitude. The rule of thumb for the correction (in feet) is simply twenty times the dew-point temperature in Celsius, or colloquially, “double the dew point and add a zero.” This rule of thumb is shown to limit the percent error in density-altitude calculations to within five percent for the range of dew-point temperatures between 5°C to 30°C and elevations below 6,000 compared to over 20 percent for the same conditions using the dry case alone. The effect of humidity is also shown to create larger absolute errors in density-altitude calculations for the same dew-point temperature at higher pressure altitudes; however, the percent error decreases quickly with pressure altitude

Optimal Meteorological Conditions at Selected NASCAR Facilities

The purpose of this research is to determine the time of year with the highest probability of optimum conditions to hold an event at selected NASCAR tracks. This project is important to the NASCAR industry because it aims to minimize the number of events postponed or cancelled due to poor weather conditions and focus on keeping fans comfortable. This analysis is based on a set of optimum meteorological conditions intended to maximize fan comfort. These conditions include limits on: (1) a calculated apparent temperature that includes both moisture and wind chill effects, (2) wind speed, and (3) the presence of precipitation. Hourly weather data taken from a representative observation site located near each chosen track is examined and the frequency of optimum conditions is identified for specified periods to determine the probability of when the conditions will be optimum for an event

Type 2 alveolar cells are stem cells in adult lung

Gas exchange in the lung occurs within alveoli, air-filled sacs composed of type 2 and type 1 epithelial cells (AEC2s and AEC1s), capillaries, and various resident mesenchymal cells. Here, we use a combination of in vivo clonal lineage analysis, different injury/repair systems, and in vitro culture of purified cell populations to obtain new information about the contribution of AEC2s to alveolar maintenance and repair. Genetic lineage-tracing experiments showed that surfactant protein C–positive (SFTPC-positive) AEC2s self renew and differentiate over about a year, consistent with the population containing long-term alveolar stem cells. Moreover, if many AEC2s were specifically ablated, high-resolution imaging of intact lungs showed that individual survivors undergo rapid clonal expansion and daughter cell dispersal. Individual lineage-labeled AEC2s placed into 3D culture gave rise to self-renewing “alveolospheres,” which contained both AEC2s and cells expressing multiple AEC1 markers, including HOPX, a new marker for AEC1s. Growth and differentiation of the alveolospheres occurred most readily when cocultured with primary PDGFRα+ lung stromal cells. This population included lipofibroblasts that normally reside close to AEC2s and may therefore contribute to a stem cell niche in the murine lung. Results suggest that a similar dynamic exists between AEC2s and mesenchymal cells in the human lung

Identification of ORC1/CDC6-Interacting Factors in Trypanosoma brucei Reveals Critical Features of Origin Recognition Complex Architecture

DNA Replication initiates by formation of a pre-replication complex on sequences termed origins. In eukaryotes, the pre-replication complex is composed of the Origin Recognition Complex (ORC), Cdc6 and the MCM replicative helicase in conjunction with Cdt1. Eukaryotic ORC is considered to be composed of six subunits, named Orc1–6, and monomeric Cdc6 is closely related in sequence to Orc1. However, ORC has been little explored in protists, and only a single ORC protein, related to both Orc1 and Cdc6, has been shown to act in DNA replication in Trypanosoma brucei. Here we identify three highly diverged putative T. brucei ORC components that interact with ORC1/CDC6 and contribute to cell division. Two of these factors are so diverged that we cannot determine if they are eukaryotic ORC subunit orthologues, or are parasite-specific replication factors. The other we show to be a highly diverged Orc4 orthologue, demonstrating that this is one of the most widely conserved ORC subunits in protists and revealing it to be a key element of eukaryotic ORC architecture. Additionally, we have examined interactions amongst the T. brucei MCM subunits and show that this has the conventional eukaryotic heterohexameric structure, suggesting that divergence in the T. brucei replication machinery is limited to the earliest steps in origin licensing

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine