The Transportation Industry: Investigating Women as an Underutilized Workforce in a Traditionally Male Industry

This study investigated women\u27s interest in the transportation industry. Staffing shortages coupled with disproportionate gender distributions were cause for concern within transportation. Surveys were used to investigate occupational preferences, work values, sex-type identities, self-efficacy, and perception of barriers present among women. These findings were then analyzed for significant correlations and predictive value resulting in a job profile for women that may be interested in transportation. Several predictors of interest were found to exist including age, self-efficacy, work values, and specific occupational types

Anti-Inflammatory Effects of Vitamin D on Human Immune Cells in the Context of Bacterial Infection.

Vitamin D induces a diverse range of biological effects, including important functions in bone health, calcium homeostasis and, more recently, on immune function. The role of vitamin D during infection is of particular interest given data from epidemiological studies suggesting that vitamin D deficiency is associated with an increased risk of infection. Vitamin D has diverse immunomodulatory functions, although its role during bacterial infection remains unclear. In this study, we examined the effects of 1,25(OH)₂D₃, the active metabolite of vitamin D, on peripheral blood mononuclear cells (PBMCs) and purified immune cell subsets isolated from healthy adults following stimulation with the bacterial ligands heat-killed pneumococcal serotype 19F (HK19F) and lipopolysaccharide (LPS). We found that 1,25(OH)₂D₃ significantly reduced pro-inflammatory cytokines TNF-α, IFN-γ, and IL-1β as well as the chemokine IL-8 for both ligands (three- to 53-fold), while anti-inflammatory IL-10 was increased (two-fold, p = 0.016) in HK19F-stimulated monocytes. Levels of HK19F-specific IFN-γ were significantly higher (11.7-fold, p = 0.038) in vitamin D-insufficient adults (50 nmol/L). Vitamin D also shifted the pro-inflammatory/anti-inflammatory balance towards an anti-inflammatory phenotype and increased the CD14 expression on monocytes (p = 0.008) in response to LPS but not HK19F stimulation. These results suggest that 1,25(OH)₂D₃ may be an important regulator of the inflammatory response and supports further in vivo and clinical studies to confirm the potential benefits of vitamin D in this context

Quantum mechanics/molecular mechanics modeling of drug metabolism:Mexiletine N-hydroxylation by cytochrome P450 1A2

The mechanism of cytochrome P450­(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (<i>R</i>)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM­(B3LYP-D)/MM­(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site, but this is not a prerequisite for reaction via either mechanism. Several active site residues play a role in the binding of mexiletine in the active site, including Thr124 and Phe226. This work reveals key details of the N-hydroxylation of mexiletine and further demonstrates that mechanistic studies using QM/MM methods are useful for understanding drug metabolism

The international perinatal outcomes in the pandemic (iPOP) study: Protocol

Preterm birth is the leading cause of infant death worldwide, but the causes of preterm birth are largely unknown. During the early COVID-19 lockdowns, dramatic reductions in preterm birth were reported; however, these trends may be offset by increases in stillbirth rates. It is important to study these trends globally as the pandemic continues, and to understand the underlying cause(s). Lockdowns have dramatically impacted maternal workload, access to healthcare, hygiene practices, and air pollution - all of which could impact perinatal outcomes and might affect pregnant women differently in different regions of the world. In the international Perinatal Outcomes in the Pandemic (iPOP) Study, we will seize the unique opportunity offered by the COVID-19 pandemic to answer urgent questions about perinatal health. In the first two study phases, we will use population-based aggregate data and standardized outcome definitions to: 1) Determine rates of preterm birth, low birth weight, and stillbirth and describe changes during lockdowns; and assess if these changes are consistent globally, or differ by region and income setting, 2) Determine if the magnitude of changes in adverse perinatal outcomes during lockdown are modified by regional differences in COVID-19 infection rates, lockdown stringency, adherence to lockdown measures, air quality, or other social and economic markers, obtained from publicly available datasets. We will undertake an interrupted time series analysis covering births from January 2015 through July 2020. The iPOP Study will involve at least 121 researchers in 37 countries, including obstetricians, neonatologists, epidemiologists, public health researchers, environmental scientists, and policymakers. We will leverage the most disruptive and widespread natural experiment of our lifetime to make rapid discoveries about preterm birth. Whether the COVID-19 pandemic is worsening or unexpectedly improving perinatal outcomes, our research will provide critical new information to shape prenatal care strategies throughout (and well beyond) the pandemic

Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform: a statistical modelling study

This study is part of the EAVE II project. EAVE II is funded by the MRC (MR/R008345/1) with the support of BREATHE—The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through Public Health Scotland and Scottish Government Director General Health and Social Care. The original EAVE project was funded by the NIHR Health Technology Assessment programme (11/46/23).Background   As the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave.  Methods   We established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death.  Findings   Our cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, 2020, were associated with several patient characteristics, including male sex (hospitalisation hazard ratio [HR] 1·47, 95% CI 1·38–1·57; death HR 1·62, 1·49–1·76) and various comorbidities, with the highest hospitalisation HR found for transplantation (4·53, 1·87–10·98) and the highest death HR for myoneural disease (2·33, 1·46–3·71). For those testing positive, there were decreasing temporal trends in hospitalisation and death rates. The proportion of positive tests among older age groups (>40 years) and those with at-risk comorbidities increased during October, 2020. On Nov 10, 2020, the projected number of hospitalisations for Dec 8, 2020 (28 days later) was 90 per day (95% prediction interval 55–125) and the projected number of deaths was 21 per day (12–29). Interpretation The estimated incidence of SARS-CoV-2 infection based on positive tests recorded in this unique data resource has provided forecasts of hospitalisation and death rates for the whole of Scotland. These findings were used by the Scottish Government to inform their response to reduce COVID-19-related morbidity and mortality.Publisher PDFPeer reviewe

Reduced IL-17A Secretion Is Associated with High Levels of Pneumococcal Nasopharyngeal Carriage in Fijian Children.

Streptococcus pneumonia (the pneumococcus) is the leading vaccine preventable cause of serious infections in infants under 5 years of age. The major correlate of protection for pneumococcal infections is serotype-specific IgG antibody. More recently, antibody-independent mechanisms of protection have also been identified. Preclinical studies have found that IL-17 secreting CD4+ Th17 cells in reducing pneumococcal colonisation. This study assessed IL-17A levels in children from Fiji with high and low pneumococcal carriage density, as measured by quantitative real-time PCR (qPCR). We studied Th17 responses in 54 children who were designated as high density carriers (N=27, >8.21x10(5) CFU/ml) or low density carriers (N=27, <1.67x10(5) CFU/ml). Blood samples were collected, and isolated peripheral blood mononuclear cells (PBMCs) were stimulated for 6 days. Supernatants were harvested for cytokine analysis by multiplex bead array and/or ELISA. Th17 cytokines assayed included IL-17A, IL-21, IL-22 as well as TNF-α, IL-10, TGF-β, IL-6, IL-23 and IFNγ. Cytokine levels were significantly lower in children with high density pneumococcal carriage compared with children with low density carriage for IL-17A (p=0.002) and IL-23 (p=0.04). There was a trend towards significance for IL-22 (p=0.057) while no difference was observed for the other cytokines. These data provide further support for the role of Th17-mediated protection in humans and suggest that these cytokines may be important in the defence against pneumococcal carriage