Presentation1_Causal effects of homocysteine levels on the components of sarcopenia: A two-sample mendelian randomization study.pdf

Background: Currently, it is unclear whether there is a causal association between genetically predicted plasma homocysteine (Hcy) levels and the risk of sarcopenia. We performed a Mendelian randomization (MR) study to assess the association between circulating Hcy levels and the components [grip strength, walking pace, and appendicular lean mass (ALM)] of sarcopenia.Methods: Independent single nucleotide polymorphisms (SNPs) significantly associated with plasma Hcy levels served as instrumental variables. Summary-level data regarding the components of sarcopenia. Were obtained from the UK Biobank. Inverse variance weighted (IVW) as the primary method was used for Mendelian randomization (MR) analysis. We also use four models, weighted median, MR-Egger regression, Maximum likelihood, and Penalised weighted median, as supplementary methods to IVW. The MR-Egger intercept test, Cochran’s Q test, and “leave-one-out” sensitivity analysis were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of the causal association between Hcy levels and the components of sarcopenia.Results: The IVW-MR analysis suggested significant negative associations of increased plasma Hcy levels with grip strength (right: effect = −0.036, SE = 0.032, p = 5.53E-4; left: effect = −0.045, SE = 0.010, p = 1.45E-5), walking pace (effect = −0.038, SE = 0.011, p = 3.18E-4), and ALM (effect = −0.058, 0.013, p = 1.03E-5). However, there were no significant associations of decreased plasma Hcy levels with grip strength (right: effect = 0.005, SE = 0.021, p = 0.82; left: effect = −0.006, SE = 0.014, p = 0.64), walking pace (effect = 0.01, 0.020, p = 0.61), or ALM (effect = -0.034, SE = 0.018, p = 0.06).The accuracy and robustness of these findings were confirmed by sensitivity tests.Conclusion: Increased circulating Hcy levels were associated with lower grip strength, slower walking pace, and decreased ALM.</p

On Nucleation Pathways and Particle Size Distribution Evolutions in Stratospheric Aircraft Exhaust Plumes with H₂SO₄ Enhancement

Stratospheric aerosol injection (SAI) is proposed as a means of reducing global warming and climate change impacts. Similar to aerosol enhancements produced by volcanic eruptions, introducing particles into the stratosphere would reflect sunlight and reduce the level of warming. However, uncertainties remain about the roles of nucleation mechanisms, ionized molecules, impurities (unevaporated residuals of injected precursors), and ambient conditions in the generation of SAI particles optimally sized to reflect sunlight. Here, we use a kinetic ion-mediated and homogeneous nucleation model to study the formation of H2SO4 particles in aircraft exhaust plumes with direct injection of H2SO4 vapor. We find that under the conditions that produce particles of desired sizes (diameter ∼200–300 nm), nucleation occurs in the nascent (t T = 360–445 K), and dry (RH = 0.01–0.1%) plume and is predominantly unary. Nucleation on chemiions occurs first, followed by neutral new particle formation, which converts most of the injected H2SO4 vapor to particles. Coagulation in the aging and diluting plumes governs the subsequent evolution to a narrow (σg = 1.3) particle size distribution. Scavenging by exhaust soot is negligible, but scavenging by acid impurities or incomplete H2SO4 evaporation in the hot exhaust plume and enhanced background aerosols can matter. This research highlights the need to obtain laboratory and/or real-world experiment data to verify the model prediction

LiTFSI-Free Hole Transport Materials for Robust Perovskite Solar Cells and Modules with High Efficiencies

Lithium bis(trifluoromethane) sulfonamide (LiTFSI) and oxygen-doped organic semiconductors have been frequently used to achieve record power conversion efficiencies of perovskite solar cells (PSCs). However, this conventional doping process is time-consuming and leads to poor device stability due to the incorporation of Li ions. Herein, aiming to accelerate the doping process and remove the Li ions, we report an alternative p-doping process by mixing a new small-molecule organic semiconductor, N2,N2,N7,N7-tetrakis (4-methoxyphenyl)-9-(4-(octyloxy) phenyl)-9H carbazole-2,7-diamine (labeled OH44) and its preoxidized form OH44+(TFSI–). With this method, a champion efficiency of 21.8% has been achieved for small-area PSCs, which is superior to the state-of-the-art EH44 and comparable with LiTFSI and oxygen-doped spiro-OMeTAD. Moreover, the stability of OH44-based PSCs is improved compared with those of EH44, maintaining more than 85% of its initial efficiency after aging in an ambient condition without encapsulation for 1000 h. In addition, we achieved efficiencies of 14.7 and 12.6% for the solar modules measured with a metal mask of 12.0 and 48.0 cm2, respectively, which demonstrated the scalability of this method

Compositional Constraints are Vital for Atmospheric PM_2.5 Source Attribution over India

India experiences some of the highest levels of ambient PM2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMBModified: 0.19; NMBBase: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMBModified: 0.08; NMBBase: 1.64) and ammonium simulation (NMBModified: 0.49; NMBBase: 0.90). We use this validated simulation to estimate a population-weighted annual PM2.5 exposure of 61.4 μg m–3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM2.5 aerosol source attribution for health assessments and air quality management in India