Wearable acceleration sensors are increasingly used for the assessment of free-living physical activity. Acceleration sensor calibration is a potential source of error. This study aims to describe and evaluate an autocalibration method to minimize calibration error using segments within the free-living records (no extra experiments needed). The autocalibration method entailed the extraction of nonmovement periods in the data, for which the measured vector magnitude should ideally be the gravitational acceleration (1 g); this property was used to derive calibration correction factors using an iterative closest-point fitting process. The reduction in calibration error was evaluated in data from four cohorts: UK (n = 921), Kuwait (n = 120), Cameroon (n = 311), and Brazil (n = 200). Our method significantly reduced calibration error in all cohorts (P < 0.01), ranging from 16.6 to 3.0 mg in the Kuwaiti cohort to 76.7 to 8.0 mg error in the Brazil cohort. Utilizing temperature sensor data resulted in a small nonsignificant additional improvement (P > 0.05). Temperature correction coefficients were highest for the z-axis, e.g., 19.6-mg offset per 5°C. Further, application of the autocalibration method had a significant impact on typical metrics used for describing human physical activity, e.g., in Brazil average wrist acceleration was 0.2 to 51% lower than uncalibrated values depending on metric selection (P < 0.01). The autocalibration method as presented helps reduce the calibration error in wearable acceleration sensor data and improves comparability of physical activity measures across study locations. Temperature ultization seems essential when temperature deviates substantially from the average temperature in the record but not for multiday summary measures.

Objectives: The prevalence of obesity and diabetes in the Middle East is among the highest in the world. Valid measures of abdominal adiposity are essential to understanding the metabolic consequences of obesity. Dual-energy X-ray absorptiometry (DXA) is increasingly being utilised to assess body composition in population studies, and has recently been used to estimate visceral adipose tissue (VAT). The aim of this study was to determine the accuracy of DXA-derived VAT in a Middle Eastern population using magnetic resonance imaging (MRI) as the criterion measure. Method: VAT was estimated from abdominal DXA measures in 237 adult men (n=130) and women (n=107), aged 18–65 years, participating in the Kuwait Wellbeing Study. These estimates were compared with MRI measures of the corresponding anatomical region. The agreement between methods was assessed using Bland–Altman as well as correlation analysis. Results: Median MRI VAT was 1148.5 cm³ (95% confidence interval: 594.2–1734.6) in men and 711.3 cm³ (95% confidence interval: 395.5–1042.8) in women. DXA estimates of VAT showed high correlations with corresponding MRI measures (r=0.94 (P<0.0001) in men; r=0.93 (P<0.0001) in women). DXA overestimated VAT with a mean bias (95% limits of agreement) of 79.7 cm³ (−767 to 963) in men and 46.8 cm³ (−482 to 866) in women. The imprecision of DXA increased with increasing VAT level in both men and women. Conclusion: DXA estimates of VAT are valid for use in Middle Eastern populations, although accuracy decreases with increasing level of visceral adiposity.

The coronavirus disease 2019 (COVID-19) pandemic has caused an exponential rise in death rates and hospitalizations. The aim of this study was to characterize the D614G substitution in the severe acute respiratory syndome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S protein), which may affect viral infectivity. The effect of D614G substitution on the structure and thermodynamic stability of the S protein was analyzed with use of DynaMut and SCooP. HDOCK and PRODIGY were used to model furin protease binding to the S protein RRAR cleavage site and calculate binding affinities. Molecular dynamics simulations were used to predict the S protein apo structure, the S protein–furin complex structure, and the free binding energy of the complex. The D614G substitution in the G clade of SARS-CoV-2 strains introduced structural mobility and decreased the thermal stability of the S protein (ΔΔG = −0.086 kcal mol−1). The substitution resulted in stronger binding affinity (Kd = 1.6 × 10−8) for furin, which may enhance S protein cleavage. The results were corroborated by molecular dynamics simulations demonstrating higher binding energy of furin and the S protein D614G mutant (−61.9 kcal mol−1 compared with −56.78 kcal mol−1 for wild-type S protein). The D614G substitution in the G clade induced flexibility of the S protein, resulting in increased furin binding, which may enhance S protein cleavage and infiltration of host cells. Therefore, the SARS-CoV-2 D614G substitution may result in a more virulent strain.

The B.1.1.7 SARS-CoV-2 strain that has emerged in the UK in early December presents seven mutations and three deletions on S-protein structure that could lead to a more infective strain. The P681H mutation in the “PRRAR” furin cleavage site might affect the binding affinity to furin enzyme and hence its infectivity.

Objective. Gestational diabetes mellitus (GDM) is a growing global public health problem that can have short- and long-term health consequences for the mother and the child. Despite its criticalness, many countries still do not have the epidemiological data which could guide them in responding to the problem. Due to the lack of knowledge on GDM and the fact that diabetes and obesity are high in Kuwait, this study sought to estimate the prevalence of GDM and determine its risk factors and outcomes. Methods. This cross-sectional study enrolled 947 mothers living in Kuwait, who had given birth within the previous four years. Participants were recruited from primary health care clinics and public hospitals. GDM status was self-reported by the mother. Associations between exposures and outcomes were evaluated using logistic regression, and adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated. Results. Of the 868 mothers with no prior history of diabetes mellitus, 109 (12.6%, 95% CI: 10.4, 14.8) reported having been given a GDM diagnosis during their last pregnancy. The prevalence of GDM increased with maternal age and prepregnancy body mass index. GDM was positively associated with caesarean section delivery (aOR=1.76, 95% CI: 1.17, 2.66) and fetal macrosomia (aOR=2.36, 95% CI: 1.14, 4.89). Conclusion. GDM is prevalent in Kuwait and is associated with poor maternal, fetal, and neonatal outcomes. To date, GDM has received little attention, and there is a need for more research to identify and respond to individual and public health implications of GDM in Kuwait.

SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) protein is the target for the antiviral drug Remdesivir (RDV). With RDV clinical trials on COVID-19 patients showing a reduced hospitalisation time. During the spread of the virus, the RdRp has developed several mutations, with the most frequent being A97V and P323L. The current study sought to investigate whether A97V and P323L mutations influence the binding of RDV to the RdRp of SARS-CoV-2 compared to wild-type (WT). The interaction of RDV with WT-, A97V-, and P323L-RdRp were measured using molecular dynamic (MD) simulations, and the free binding energies were extracted. Results showed that RDV that bound to WT- and A97V-RdRp had a similar dynamic motion and internal residue fluctuations, whereas RDV interaction with P323L-RdRp exhibited a tighter molecular conformation, with a high internal motion near the active site. This was further corroborated with RDV showing a higher binding affinity to P323L-RdRp (−24.1 kcal/mol) in comparison to WT-RdRp (−17.3 kcal/mol). This study provides insight into the potential significance of administering RDV to patients carrying the SARS-CoV-2 P323L-RdRp mutation, which may have a more favourable chance of alleviating the SARS-CoV-2 illness in comparison to WT-RdRp carriers, thereby suggesting further scientific consensus for the usage of Remdesivir as clinical candidate against COVID-19.