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Traditional coal spontaneous combustion (CSC) inhibitors, while effective, have limitations such as frequent application or short-term efficacy. To this end, we developed a slow-release and water-soluble synergistic inhibitor (SWSI) to achieve long-term CSC inhibition. The SWSI was formulated by integrating synergistic antioxidants (SA) composed of ascorbic acid (AsA) and Fe-superoxide dismutase (Fe-SOD) dissolved in a super absorbent polymer (SAP) encapsulated within hydrogel microcapsules. The effectiveness of SWSI was evaluated through simultaneous thermal analysis and in-situ free radical tests. The formulation optimization demonstrated that AsA and Fe-SOD had the maximum synergistic inhibition effect at a 1:1 molar ratio. The optimal SA: SAP ratio of 3:1 achieved the lowest oxygen consumption rate and highest inhibition rate. The encapsulation formulation, consisting of 3% SA, 6% PAM, 1% CaCl2, and 0.5% citric acid, generated the highest swelling ratio. Simultaneous thermal analysis and in-situ free radical tests indicated that SWSI greatly increased feature temperatures and the apparent activation energy, lowered reaction heat, and substantially reduced free radical concentration in the full oxidation process. The newly developed SWSI offers a significant advancement in long-term CSC prevention by integrating physical and chemical inhibition, which provides sustained and effective inhibition throughout the entire oxidation process. [ABSTRACT FROM AUTHOR]

This study employs a combination of theoretical analysis, Similarity simulation, and computational fluid dynamics (CFD) to examine the airflow caused by the stack effect under different leakage conditions in high-rise buildings and the transport of fire smoke. Building on previous research, we quantify the leakage area using a formula and classify it into two categories, "tight" and "leaky." Based on the analysis results, we conduct a similarity simulation experiment in a small-scale high-rise building experimental platform with a height of 5.2 m to create a certain size of leakage area at the bottom and record carbon monoxide concentration at different locations and times. The obtained result is then compared with the numerical simulation result, and the similarity simulation results match well with the numerical simulation results. The findings demonstrate that increasing the leakage area accelerates the transport of smoke due to the stack effect, particularly at higher floors. This paper also discusses strategies to impede smoke diffusion, providing valuable references for the safety design of high-rise buildings. [ABSTRACT FROM AUTHOR]

Premature ovarian insufficiency (POI) is a reproductive endocrine disorder characterized by infertility and perimenopausal syndrome, with a highly heterogeneous genetic etiology and its mechanism is not fully understood. Therefore, we utilized Oxford Nanopore Technology (ONT) for the first time to characterize the full-length transcript profile, and revealed biomarkers, pathway and molecular mechanisms for POI by bioinformatics analysis and machine learning. Ultimately, we identified 272 differentially expressed genes, 858 core genes, and 25 hub genes by analysis of differential expression, gene set enrichment, and protein–protein interactions. Seven candidate genes were identified based on the intersection features of the random forest and Boruta algorithm. qRT-PCR results indicated that COX5A, UQCRFS1, LCK, RPS2 and EIF5A exhibited consistent expression trends with sequencing data and have potential as biomarkers. Additionally, GSEA analysis revealed that the pathophysiology of POI is closely associated with inhibition of the PI3K-AKT pathway, oxidative phosphorylation and DNA damage repair, as well as activation of inflammatory and apoptotic pathways. Furthermore, we emphasize that downregulation of respiratory chain enzyme complex subunits and inhibition of oxidative phosphorylation pathways play crucial roles in the pathophysiology of POI. In conclusion, our utilization of long-read sequencing has refined the annotation information within the POI transcriptional profile. This valuable data provides novel insights for further exploration into molecular regulatory networks and potential biomarkers associated with POI. [ABSTRACT FROM AUTHOR]

This correction notice addresses an error in the original article titled "Exploring biomarkers of premature ovarian insufficiency based on oxford nanopore transcriptional profile and machine learning." The error involved the order of the author names, which has been corrected to Zhaoyang Yu, Mujun Li, and Weilong Peng. Additionally, an incorrect email address for author Mujun Li was provided, and the correct email address is lmj0081@163.com. The original article has been updated to reflect these corrections. [Extracted from the article]

Bacteriophage Q protein engages σ-dependent paused RNA polymerase (RNAP) by binding to a DNA site embedded in late gene promoter and renders RNAP resistant to termination signals. Here, we report a single-particle cryo-electron microscopy (cryo-EM) structure of an intact Q-engaged arrested complex. The structure reveals key interactions responsible for σ-dependent pause, Q engagement, and Q-mediated transcription antitermination. The structure shows that two Q protomers (QI and QII) bind to a direct-repeat DNA site and contact distinct elements of the RNA exit channel. Notably, QI forms a narrow ring inside the RNA exit channel and renders RNAP resistant to termination signals by prohibiting RNA hairpin formation in the RNA exit channel. Because the RNA exit channel is conserved among all multisubunit RNAPs, it is likely to serve as an important contact site for regulators that modify the elongation properties of RNAP in other organisms, as well. Bacteriophage Q protein serves as a model regulator for the study of transcription elongation. Here the authors report a cryo-EM structure of an intact Q-engaged arrested complex, revealing the interactions responsible for σ-dependent pause, Q engagement, and Q-mediated transcription antitermination. [ABSTRACT FROM AUTHOR]