Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$

A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$

Cross-domain retinopathy classification with optical coherence tomography images via a novel deep domain adaptation method

Deep learning based retinopathy classification with optical coherence tomography (OCT) images has recently attracted great attention. However, existing deep learning methods fail to work well when training and testing datasets are different due to the general issue of domain shift between datasets caused by different collection devices, subjects, imaging parameters, etc. To address this practical and challenging issue, we propose a novel deep domain adaptation (DDA) method to train a model on a labeled dataset and adapt it to an unlabelled dataset (collected under different conditions). It consists of two modules for domain alignment, that is, adversarial learning and entropy minimization. We conduct extensive experiments on three public datasets to evaluate the performance of the proposed method. The results indicate that there are large domain shifts between datasets, resulting a poor performance for conventional deep learning methods. The proposed DDA method can significantly outperform existing methods for retinopathy classification with OCT images. It achieves retinopathy classification accuracies of 0.915, 0.959 and 0.990 under three cross-domain (cross-dataset) scenarios. Moreover, it obtains a comparable performance with human experts on a dataset where no labeled data in this dataset have been used to train the proposed DDA method. We have also visualized the learnt features by using the t-distributed stochastic neighbor embedding (t-SNE) technique. The results demonstrate that the proposed method can learn discriminative features for retinopathy classification.Ministry of Education (MOE)Ministry of Health (MOH)National Medical Research Council (NMRC)Submitted/Accepted versionWe sincerely appreciate funding support from Singapore Ministry of Health's National Medical Research Council under its Open Fund Individual Research Grant (MOH-OFIRG19may-0009), and Ministry of Education Singapore under its Academic Research Fund Tier1 (2018-T1-001-144) and its Academic Research Funding Tier 2 (MOE-T2EP30120-0001)

Hazelnut shell carbon filled polylactic acid composite filaments for 3D printing photothermal structures

Low-cost, compostable, high-efficiency photothermal conversion materials with shaping freedom into complex geometrical structures have received considerable attention by the photothermal conversion technologies. In this study, a kind of bio-based filament with photothermal conversion function for fused filament fabrication (FFF) technology was prepared by adding hazelnut shell carbon (HSCs) in polylactic acid (PLA) matrix. The HSCs were obtained at 300, 500, 700, and 900 °C. The results revealed that the morphology, particle size, pore structure, surface functional groups, and degree of graphitization of HSCs varied with the pyrolysis temperature. Additionally, the three-dimensional (3D) printability of PLA-HSC composite filaments as well as the photothermal performance of the printed structures were affected by the pyrolysis temperature of HSCs. All PLA-HSC filaments were suitable for 3D printing besides HSC pyrolyzed at 300 °C. Furthermore, the fluidity of the composites increased with the pyrolysis temperature of HSCs. The rheology results demonstrated that the complex viscosity, storage modulus, and loss modulus decreased with the increase of pyrolysis temperature. However, the mechanical properties and the thermal stability of the PLA-HSC filaments showed opposite trend. At the wavelength range of 250–2500 nm, with HSCs pyrolyzed at 700 and 900 °C, the 3D printed PLA-HSC parts demonstrated excellent photothermal performance with a light absorption intensity of around 93 %. Overall, HSCs pyrolyzed at 700 °C is the most cost-effective candidates for the preparation of PLA-based filament for photothermal conversion components. In this work, a brine evaporation crystallizer was 3D printed to demonstrate the application of this filament

Common trace metals in rheumatoid arthritis : A systematic review and meta-analysis

Introduction: Environmental risk factors regrading rheumatoid arthritis (RA) have not been explored extensively. Selenium (Se), zinc (Zn) and copper (Cu) nutrients were reported to associate with RA, but the results were inconsistent. Therefore, we conduct present study to meta-analyze the relationship between serum Se, Zn and Cu and RA and review the potential mechanisms. Methods: PubMed, Web of Science and Cochrane Library were comprehensively searched till October 1, 2018 for pertinent studies. Standard mean differences (SMDs) and 95% confident intervals (CIs) were calculated according to random effects model. Results: Finally 41 literatures were included. Meta-analysis of 16 studies involving 806 RA patients and 959 health controls showed that serum Se (SMD = −1.04, 95% CI = −1.58 to −0.50) was decreased in RA patients, and 23 literatures with 1398 patients and 1299 controls reported serum Zn (SMD = −1.20, 95% CI = −1.74 to −0.67) was decreased. But serum Cu (SMD = 1.26, 95% CI = 0.63 to −1.89) was increased with 26 studies including 1723 patients and 1451 controls. Meta-regression reported that steroid use was positively related to serum level of Se in RA (β = 0.041, 95% CI = 0.002 to 0.079). Differences in serum Se, Zn and Cu between rheumatoid arthritis patients and controls were all related with the geographical distribution. Conclusions: Patients with RA have significant decreased serum Se and Zn and increased serum Cu than health controls, suggesting potential roles of Se, Zn and Cu in the pathogenesis of RA. Patients and rheumatologist should give enough attention to the monitor of these elements during follow up.</p

Efficacy and safety of tocilizumab with inhibition of interleukin-6 in adult-onset Still’s disease : A meta-analysis

Objectives: Tocilizumab (TCZ) is the only available biologics inhibiting interleukin-6 presently, and emerging evidences have figured that elevated serum level of interleukin-6 is a crucial link of the pathogenesis of adult-onset Still’s disease (AOSD). However, evidence about the efficacy and safety of TCZ in AOSD with strong power is still scarce. Thus, this meta-analysis was conducted to synthetically assess the efficacy and safety of TCZ on AOSD. Methods: PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, and Chinese Biological Medical Literature database were comprehensively searched up to 31 July 2017 for the pertinent studies. The pooled remission rates were synthesized by fixed effect model or randomized effects model, depended on heterogeneity. Results: Ten original studies contained 147 individuals were included in our analysis. The overall partial and complete remission rates were 85.38 (95% CI: 69.32–96.88%) and 77.91% (95% CI: 57.91–90.04%), respectively, and the remission rate of refractory patients was 87.92% (95% CI: 56.53–100.00%). Conclusion: The use of TCZ could significantly reduce the need of corticosteroids for AOSD patients. Impressive improvements were attained in both clinical and laboratory parameters. Compared with conventional therapy, TCZ treatment was safety. In conclusion, TCZ was effective and well tolerated for the treatment of AOSD.</p

3D Printing of Solar Crystallizer with Polylactic Acid/Carbon Composites for Zero Liquid Discharge of High-Salinity Brine

Zero liquid discharge (ZLD) is a technique for treating high-salinity brine to obtain freshwater and/or salt using a solar interface evaporator. However, salt accumulation on the surface of the evaporator is a big challenge to maintaining stable water evaporation. In this study, a simple and easy-to-manufacture evaporator, also called a crystallizer, was designed and fabricated by 3D printing. The photothermal layer printed with polylactic acid/carbon composites had acceptable light absorption (93%) within the wavelength zone of 250 nm–2500 nm. The micron-sized voids formed during 3D printing provided abundant water transportation channels inside the crystallizer. After surface hydrophilic modification, the crystallizer had an ultra-hydrophilic channel structure and gravity-assisted salt recovery function. The results revealed that the angles between the photothermal layers affected the efficacy of solar evaporation and the yield of solid salt. The crystallizer with the angle of 90° between two photothermal layers could collect more solid salt than the three other designs with angles of 30°, 60°, and 120°, respectively. The crystallizer has high evaporation and salt crystallization efficiency in a high-salinity brine environment, which is expected to have application potentials in the zero liquid discharge of wastewater and valuable salt recovery

Associations of exposure to ambient fine particulate matter constituents from different pollution sources with semen quality: Evidence from a prospective cohort

The association between ambient fine particulate matter (PM2.5) exposure and semen quality remains inconclusive, possibly due to variations in pollution sources and PM2.5 compositions. Studies investigating the constituents of PM2.5 have been hindered by small sample sizes, and research exploring the relationships between PM2.5 pollution sources and semen quality is lacking. To address this gap, we conducted a comprehensive study based on the Anhui prospective assisted reproduction cohort to evaluate the associations between semen quality and the constituents and pollution sources of PM2.5. This study included 9013 semen samples from 4417 males in the urban districts of Hefei. The median concentrations of PM2.5 constituents, including eight metals and four water-soluble ions (WSIs), were measured for seven days per month at two monitoring stations during the 0–90-day exposure window. A linear mixed-effects model, weighted quantile sum regression, and positive matrix factorisation were used to evaluate the associations of the constituents and pollution sources of PM2.5 with semen quality. The results showed that exposure to PM2.5-bound metals (antimony, arsenic, cadmium, lead, and thallium) and WSIs (sulphate and chloride) were negatively associated with semen quality parameters. Moreover, mixtures of PM2.5-bound metals and WSIs were negatively associated with semen quality. Additionally, PM2.5 derived from traffic emissions was negatively associated with semen quality. In summary, our study revealed that ambient PM2.5 and its constituents, especially metals, were negatively associated with semen quality. Antimony, lead, and thallium emerged as the primary contributors to toxicity, and PM2.5 from traffic emissions was associated with decreased semen quality. These findings have important public health implications for the management of PM2.5 pollution in the context of male reproductive health.</p