Dissecting the causal relationship between neuroticism and osteoarthritis: a univariable and multivariable Mendelian randomization study.

Background: Mental health has been found to be associated with risk of osteoarthritis (OA), but the causal relationship was not fully clarified. Methods: Two-sample Mendelian randomization (MR) study was conducted to investigate the causal relationship between neuroticism (n = 329,821) and the two most frequently affected parts of osteoarthritis (OA) (knee OA: case/control =24,955/378,169; hip OA: case/control = 15,704/378,169) using large scale summary genome-wide association study (GWAS) data. Inverse variance weighted (IVW), weighted median, and MR-Egger were used to estimate the causal effects. Multiple sensitivity analyses were conducted to examine the robustness of the causal estimates. Multivariable MR analysis was used to estimate the direct effects of neuroticism on OA after accounting for the other OA risk factors. Two-step MR approach was employed to explore the potential mediators of the causal relationship. Results: Univariable MR analysis indicated that 1-SD increase in genetically predicted neuroticism score was associated with an increased risk of knee OA (IVW: OR, 1.17; 95% CI, 1.087-1.26; p = 2.72E-05) but not with hip OA. The causal effects remained significant after accounting for the effects of BMI, alcohol drinking, and vigorous physical activity but were attenuated with adjustment of smoking. Further mediation analysis revealed that smoking initiation mediated a significant proportion of the causal effects of neuroticism on knee OA (proportion of mediation effects in total effects: 22.3%; 95% CI, 5.9%-38.6%; p = 7.60E-03). Conclusions: Neuroticism has significant causal effects on knee OA risk. Smoking might partly mediate the causal relationship. Further studies were warranted to explore the underlying mechanisms and potential use of neuroticism management for OA treatment.

Model-based large-dynamic iterative piston correction using extended objects.

Cophasing is crucial for segmented or sparse aperture telescopes to achieve high resolution. In this Letter, we propose a novel, to the best of our knowledge, model-based piston correction method that can remove large-scale piston errors within a few iterations using extended objects. The relation between the piston error and a metric function is derived theoretically under broadband illumination. The metric function is based on the image's power spectral density at the spatial frequency where the sidelobe peak of the modulation transfer function (MTF) appears. The piston error is iteratively estimated and corrected by introducing positive and negative piston biases. The dynamic range of piston correction can be as large as the coherence length of light. The correction accuracy in experiments is affected by the image noises and the accuracy of the introduced piston biases.

Model-based fine phasing of segmented mirror using Chebyshev segmented piston-tip-tilt modes.

On-orbit cophasing is essential for high-resolution imaging of space telescopes with a segmented primary mirror. A model-based fine phasing method for a segmented mirror is proposed and demonstrated in this Letter. The tip-tilt error is related to the second moment of spot intensity, and the piston error is related to the Strehl ratio. Chebyshev segmented piston-tip-tilt (CSPTT) modes are used to express cophasing errors to suppress the effect of imaging noises. The CSPTT modal coefficients are estimated by the "2N + 1" algorithm that introduces bidirectional biases for each mode's estimation. The proposed method is proved robust to image noises and figure errors.

Fluid dynamics simulations show that facial masks can suppress the spread of COVID-19 in indoor environments.

The Coronavirus disease outbreak of 2019 has been causing significant loss of life and unprecedented economical loss throughout the world. Social distancing and face masks are widely recommended around the globe in order to protect others and prevent the spread of the virus through breathing, coughing, and sneezing. To expand the scientific underpinnings of such recommendations, we carry out high-fidelity computational fluid dynamics simulations of unprecedented resolution and realism to elucidate the underlying physics of saliva particulate transport during human cough with and without facial masks. Our simulations: (a) are carried out under both a stagnant ambient flow (indoor) and a mild unidirectional breeze (outdoor); (b) incorporate the effect of human anatomy on the flow; (c) account for both medical and non-medical grade masks; and (d) consider a wide spectrum of particulate sizes, ranging from 10 micro m to 300 micro m. We show that during indoor coughing some saliva particulates could travel up to 0.48 m, 0.73 m, and 2.62 m for the cases with medical-grade, non-medical grade, and without facial masks, respectively. Thus, in indoor environments either medical or non-medical grade facial masks can successfully limit the spreading of saliva particulates to others. Under outdoor conditions with a unidirectional mild breeze, however, leakage flow through the mask can cause saliva particulates to be entrained into the energetic shear layers around the body and transported very fast at large distances by the turbulent flow, thus, limiting the effectiveness of facial masks.

Carbon Nanotube-Silicon Nanowire Heterojunction Solar Cells with Gas-Dependent Photovoltaic Performances and Their Application in Self-Powered NO2 Detecting.

A multifunctional device combining photovoltaic conversion and toxic gas sensitivity is reported. In this device, carbon nanotube (CNT) membranes are used to cover onto silicon nanowire (SiNW) arrays to form heterojunction. The porous structure and large specific surface area in the heterojunction structure are both benefits for gas adsorption. In virtue of these merits, gas doping is a feasible method to improve cell's performance and the device can also work as a self-powered gas sensor beyond a solar cell. It shows a significant improvement in cell efficiency (more than 200 times) after NO2 molecules doping (device working as a solar cell) and a fast, reversible response property for NO2 detection (device working as a gas sensor). Such multifunctional CNT-SiNW structure can be expected to open a new avenue for developing self-powered, efficient toxic gas-sensing devices in the future.