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In this study, surface dust samples were collected within the second ring road of Shenyang City under different land-use types, and the concentration and chemical speciation of metals in different particle sizes under different land-use types were analyzed. Dust samples were separated into four particle size fractions (＜50, 50–100, 100–500, 500–2000 μm), and particles in the range of 100–500 µm were the highest representing one-third of the dust mass. The results revealed that metals were detected in order Zn > Cr > Pb > Cu > Ni > As > Cd in different particle sizes of dust under different land-use types. The relative contribution of individual particle-size fractions for seven metals was different, but the results showed preferential partitioning to small particle-size fractions. The relative contribution of metals in individual particle-size fractions and chemical speciation were significantly affected by the type of land use. Metals concentrated on the smaller particles in the traffic area, and the particles (<50 µm) contained the highest percentage of metals but Cr. The residual fractions (F5) of Ni, Cr, As and Cu overall represented the predominant portion in different particle size of fractions under different land-use types, Zn and Pb were mostly bound to the Fe–Mn oxides-bound fraction (F3), and the exchangeable fraction (F1) accounted for a relatively large proportion of Cd. The results of the risk assessment code (RAC) of Cd indicated that the risk of Zn was medium, and it was high for Cd in the dust of Shenyang City. [ABSTRACT FROM AUTHOR]

High-radix Montgomery Modular Multiplication (MMM) is flexible and consumes fewer cycles, but turns inefficient especially when it comes to low-bit calculation. In this brief, we propose a high-radix MMM algorithm, called Separated Iterative Digit-Digit Modular Multiplication (S-IDDMM), which accelerates the MMM by taking full advantage of multipliers and adders. The relationship among clock cycles, pipeline of multiplications and number of multipliers for the proposed algorithm is derived and utilized to optimize the overall efficiency jointly. Xilinx Virtex-7 FPGA implementations of S-IDDMM in 256 bits and 512 bits are constructed with radix-32 and radix-64, respectively. Compared with IDDMM design reported elsewhere (Amiet et al., 2016), our calculation time is reduced by more than 2 times with a similar area cost, due to deep use of multipliers and higher frequency. [ABSTRACT FROM AUTHOR]

Retaining events containing action-related information in working memory (WM) is vital to daily activities such as action planning and social interaction. During processing of such events, action-related information is bound with other visual elements (e.g., colours) as event files. In this study, we explored whether retaining event files in WM consumes more attention than retaining the constituent elements. Considering that object-based attention underlies the rehearsal of static feature bindings in WM, we hypothesised that object-based attention played a key role in retaining event files in WM. As biological motion (BM) is one of the most frequently observed events in daily life, we employed BM-related event files as the tested stimuli. In separate blocks, we required participants to memorise BM, colours (or locations), or the binding between these elements (i.e., event files). Critically, we added an object-feature report task, which consumed object-based attention, during the WM maintenance phase. We predicted that the added secondary task would lead to larger impairment for BM event files than for the constituent elements. In line with this prediction, Experiments 1 and 2 consistently revealed a selective impairment to BM event files, which could not be attributed to an unbalanced number of elements between memory conditions (Experiment 3), or to the visual processing of a secondary task (Experiment 4). Taken together, these results suggest that object-based attention plays a pivotal role in maintaining event files in WM. [ABSTRACT FROM AUTHOR]

Objectives: Idiopathic inflammatory myopathy (IIM) is a group of systemic autoimmune diseases characterised by muscle involvement. This study aims to reveal the characteristics of IIM subtypes and explore the molecular mechanisms underlying IIM., Methods: The STRING database was utilised to construct a protein-protein interaction network of differentially expressed genes obtained from the GSE128470, GSE3112, and GSE39454 datasets. The immune cell infiltration level was assessed by CIBERSORT in polymyositis (PM). Experimental autoimmune myositis (EAM) model mice were constructed for experimental verification. Serum levels of soluble CD44 (sCD44) were measured using enzyme-linked immunosorbent assay., Results: The upregulated hub gene CD44 was highly expressed in inflammatory cells infiltrating the skeletal muscle of patients with PM and in EAM mice. CD44 was correlated with both M1 macrophages (r=0.57, p<0.0001) and M2 macrophages (r=0.57, p<0.0001) in PM. Additionally, CD44+F4/80+ macrophages in skeletal muscle were increased (p<0.0001) and CD44 showed a stronger association with markers of M1 macrophage in EAM mice. Moreover, serum sCD44 levels were elevated in patients with IIM (p=0.0024), PM (p=0.0332) and dermatomyositis (p=0.0001) notably in the anti-melanoma differentiation-associated gene 5 antibody positive subtype (p=0.0007). sCD44 levels also positively correlated with visual analogue score (r=0.4424, p=0.0013), myositis intention to treat activity index (r=0.3938, p=0.0047), skin damage score (r=0.3796, p=0.0101) and skin activity score (r=0.4625, p=0.0014) in patients with IIM., Conclusions: This study suggests that macrophages expressing CD44 may be involved in the pathogenesis of PM, and sCD44 could serve as a potential marker for skin damage and activity in IIM.

Parkinson's disease (PD) affects millions of individuals worldwide, and it is the second most common late-onset neurodegenerative disorder. There is no cure and current treatments only alleviate symptoms. Modifiable risk factors have been explored as possible options for decreasing risk or developing drug targets to treat PD, including low-density lipoprotein cholesterol (LDL-C). There is evidence of sex differences for cholesterol levels as well as for PD risk. Genetic datasets of increasing size are permitting association analyses with increased power, including sex-stratified analyses. These association results empower Mendelian randomization (MR) studies, which, given certain assumptions, test whether there is a causal relationship between the risk factor and the outcome using genetic instruments. Sex-specific causal inference approaches could highlight sex-specific effects that may otherwise be masked by sex-agnostic approaches. We conducted a sex-specific two-sample cis-MR analysis based on genetic variants in LDL-C target encoding genes to assess the impact of lipid-lowering drug targets on PD risk. To complement the cis-MR analysis, we also conducted a sex-specific standard MR analysis (using genome-wide independent variants). We did not find evidence of a causal relationship between LDL-C levels and PD risk in females [OR (95% CI) = 1.01 (0.60, 1.69), IVW random-effects] or males [OR (95% CI) = 0.93 (0.55, 1.56)]. The sex-specific standard MR analysis also supported this conclusion. We encourage future work assessing sex-specific effects using causal inference techniques to better understand factors that may contribute to complex disease risk differently between the sexes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao and Gagliano Taliun.)