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BackgroundMajor depressive disorder and insomnia often coexist， and the two may share a mechanism of pathogenesis and be affected by common underlying genes with strong pleiotropic effects. Previous genome-wide association studies （GWAS） mainly focused on single-gene morphological characters analysis， which impose limitations on showing possible pleiotropic effects.ObjectiveTo identify genetic loci related to insomnia and major depressive disorder， and to examine whether there are common genetic factors underlying both insomnia and depression.MethodsThe GWAS data for major depressive disorder originates from the Psychiatric Genomics Consortium （PGC）， which comprises a total of 246 363 depressive cases and 561 190 controls. The insomnia GWAS data was downloaded from Sleep Disorder Knowledge Portal， involving 1 331 010 participants. Then the conditional false discovery rate （cFDR） and conjunction cFDR （ccFDR） were utilized to identify the genetic loci associated with major depressive disorder and insomnia， and pathway enrichment analysis was performed to examine the biological functions of these loci.ResultsA significant pleiotropic effect was detected between major depressive disorder and insomnia. By leveraging pleiotropic enrichment， 21 susceptibility loci （17 novel loci） for major depressive disorder and 38 susceptibility loci （28 novel loci） for insomnia were identified with the threshold of cFDR

Coalbed methane development primarily relies on hydraulic fracturing and drainage gas extraction processes. The intrusion of external fluids and long-term drainage and extraction contribute to the water blocking effect, which becomes one of the crucial factors affecting production capacity. In this study, the coal reservoir of a certain coalbed methane in Hancheng, Shaanxi Province, was selected as the research object. The experimental method was employed to comprehensively evaluate the correlation between factors such as coal sample moisture content, permeability, porosity, properties of external liquids, and water blocking damage. The results indicated that there was a positive correlation between coal sample moisture content, liquid surface tension, and water blocking damage. On the other hand, coal sample pore permeability characteristics, liquid contact angle with rock samples, and water blocking damage showed a negative correlation. Building upon the aforementioned research, an investigation into remedial measures for water blocking damage was conducted. Additionally, a chemical treatment study using the compound surfactant system JSS-1 as a water-blocking agent was performed to manage the water blocking effect. The results demonstrated that JSS-1 as a water-blocking agent significantly reduced the surface tension of the wellbore fluid and improved its wetting behavior on the coal-rock surface. The laboratory experiments confirmed the capability of JSS-1 in managing the water blocking effect.

This paper presents a design to realize extremely low cross‐polarization level in multibeam antenna. The antenna consists of two reflectors placed on top of each other. The front reflector is a panel made of metal grid, which is used to separate two orthogonal polarizations. The rear reflector serves as the actual multibeam antenna surface. The multibeam antenna and feed array operated at Ku band are designed and fabricated. The test results show that the gains of the 28 beams can be better than 40.42 dBi, and the cross‐polarization level can be lower than −40 dB. The proposed method provides a novel idea for the design of ultralow cross‐polarization multibeam antenna. [ABSTRACT FROM AUTHOR]

Assessing the terrestrial vegetation carbon density (TVCD) is crucial for evaluating the national carbon balance. However, current national‐scale TVCD assessments show strong disparities, despite the good estimation method of their underlying models. Here, we attribute this contradiction to a flaw in the methods of using multimodel simulation results, which ignore the connections between results, leading to an overoptimistic evaluation of the multimodel ensemble mean (MMEM) method.Thus, using the state‐of‐the‐art multimodel random forest ensemble (MMRFE) method to integrate the results of 10 models, we reproduced Chinese TVCD data during 1982–2010.Compared with the nationally averaged TVCD field investigation data (27 ± 26 Mg C/ha), we found that the results of five models were overestimated by 7.4%–85.2%, and the remaining models were underestimated by 3.7%–77.8%. The MMEM TVCD method produced an overestimation of 2%, but the MMRFE method produced an underestimation of only 0.2%. Additionally, the summary Taylor diagrams of the TVCD at the national and ecosystem (forest, shrub, grass and crop ecosystems) scales all showed that the MMRFE TVCD produced the smallest standard deviations and root mean square deviations and the highest correlation coefficients. Furthermore, the MMRFE TVCDs were all significantly positively correlated with the normalized difference vegetation index (NDVI), and they had the same increasing trend, but an opposite variation trend from the MMEM TVCD and NDVI. This result implied that the spatiotemporal variation modes of the MMRFE TVCD were consistent with those of the NDVI. The results suggested that compared with the traditional MMEM method, the MMRFE TVCD and its spatiotemporal variation modes were more similar to the real TVCD.In conclusion, the MMRFE method can effectively improve the accuracy of national‐scale TVCD estimation, and effectively reduce the uncertainty of large‐scale terrestrial vegetation carbon estimation processes. Notably, we provide a new method that uses a machine learning approach to mine multimodel terrestrial carbon information to reduce the uncertainty in the estimation of terrestrial ecosystem carbon components. [ABSTRACT FROM AUTHOR]

We intended to discuss the influence of histone deacetylase 3 (HDAC3) on spinal cord injury (SCI) by regulating microRNA-19b-1-5p (miR-19b-1-5p) and janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) pathway. In a rat model, the role of HDAC3 and miR-19b-1-5p in SCI was identified through detecting motor function, serum inflammation, pathological damage, cell apoptosis and GFAP expression. Also, by measuring GFAP expression and migration of spinal cord astrocytes, the effects of HDAC3 and miR-19b-1-5p in SCI were identified in vitro. Restoration of miR-19b-1-5p or depletion of HDAC3 alleviated motor function, inflammation, relieved pathological damage and reduced apoptosis, and reduced GFAP expression in the spinal cord tissue of SCI rats. Up-regulating miR-19b-1-5p or down-regulating HDAC3 decreased migration and GFAP expression of injured astrocytes. Our study presents that down-regulated HDAC3 can facilitate the recovery of SCI via inhibiting the activation of JAK2/STAT3 pathway by up-regulating miR-19b-1-5p. • Decreased miR-19b-1-5p and increased HDAC3 are found in SCI. • HDAC3 specially binds to miR-19b-1-5p. • Raised miR-19b-1-5p/reduced HDAC3 promote SCI recovery of SCI rats. • Raised miR-19b-1-5p/reduced HDAC3 inhibit apoptosis of astrocytes. • HDAC3 may be a potential candidate for treatment of SCI. [ABSTRACT FROM AUTHOR]

When a material enters the body, it is immediately attacked by hundreds of proteins, organized into complex networks of binding interactions and reactions. How do such complex systems interact with a material, "deciding" whether to attack? We focus on the "complement" system of ∼40 blood proteins that bind microbes, nanoparticles, and medical devices, initiating inflammation. We show a sharp threshold for complement activation upon varying a fundamental material parameter, the surface density of potential complement attachment points. This sharp threshold manifests at scales spanning single nanoparticles to macroscale pathologies, shown here for diverse engineered and living materials. Computational models show these behaviors arise from a minimal subnetwork of complement, manifesting percolation-type critical transitions in the complement response. This criticality switch explains the "decision" of a complex signaling network to interact with a material, and elucidates the evolution and engineering of materials interacting with the body.