Search

Treating Multiple sclerosis (MS), a well-known immune-mediated disease characterized by axonal demyelination, is challenging due to its complex causes. Naphthalenedione, present in numerous plants, is being explored as a potential medicine for MS due to its immunomodulatory properties. However, its effects on lymphocytes can vary depending on factors such as the specific compound, concentration, and experimental conditions. In this study, we aim to explore the therapeutic potential of 2-bromo-1,4-naphthalenedione (BrQ), a derivative of naphthalenedione, in experimental autoimmune encephalomyelitis (EAE), an animal model of MS, and to elucidate its underlying mechanisms. We observed that mice treated with BrQ exhibited reduced severity of EAE symptoms, including lower clinical scores, decreased leukocyte infiltration, and less extensive demyelination in central nervous system. Furthermore, it was noted that BrQ does not directly affect the remyelination process. Through cell-chat analysis based on bulk RNA-seq data, coupled with validation of flow analysis, we discovered that BrQ significantly promotes the expansion of CD8+ T cells and their interactions with other immune cells in peripheral immune system in EAE mice. Subsequent CD8+ T cell depletion experiments confirmed that BrQ alleviates EAE in a CD8+ T cell-dependent manner. Mechanistically, expanded CD8+ cells were found to selectively reduce antigen-specific CD4+ cells and subsequently inhibit Th1 and Th17 cell development in vivo, ultimately leading to relief from EAE. In summary, our findings highlight the crucial role of BrQ in modulating the pathogenesis of MS, suggesting its potential as a novel drug candidate for treating MS and other autoimmune diseases. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) based on sparse recovery achieves excellent clutter suppression and target detection performance, even with a limited number of available training samples. However, most of these methods face performance degradation due to grid mismatch, which impedes their application in bistatic clutter suppression. Some gridless methods, such as atomic norm minimization (ANM), can effectively address grid mismatch issues, yet they are sensitive to parameter settings and array errors. In this article, the authors propose a data and model-driven algorithm that unfolds the iterative process of atomic norm minimization into a deep network. This approach establishes a concrete and systematic link between iterative algorithms, extensively utilized in signal processing, and deep neural networks. This methodology not only addresses the challenges associated with parameter settings in traditional optimization algorithms, but also mitigates the lack of interpretability issues commonly found in deep neural networks. Moreover, due to more rational parameter settings, the proposed algorithm achieves effective clutter suppression with fewer iterations, thereby reducing computational time. Finally, extensive simulation experiments demonstrate the effectiveness of the proposed algorithm in clutter suppression for airborne bistatic radar. [ABSTRACT FROM AUTHOR]

The traditional sparse recovery (SR) space-time adaptive processing (STAP) algorithms are greatly affected by grid mismatch, leading to poor performance in airborne bistatic radar clutter suppression. In order to address this issue, this paper proposes an SR STAP algorithm for airborne bistatic radars based on atomic selection under the Bayesian framework. This method adopts the idea of atomic selection for the process of Bayesian inference, continuously evaluating the contribution of atoms to the likelihood function to add or remove atoms, and then using the selected atoms to estimate the clutter support subspace and perform sparse recovery in the clutter support subspace. Due to the inherent sparsity of clutter signals, performing sparse recovery in the clutter support subspace avoids using a massive number of atoms from an overcomplete space-time dictionary, thereby greatly improving computational efficiency. In airborne bistatic radar scenarios where significant grid mismatch exists, this method can mitigate the performance degradation caused by grid mismatch by encrypting grid points. Since the sparse recovery is performed in the clutter support subspace, encrypting grid points does not lead to excessive computational burden. Additionally, this method integrates out the noise term under a new hierarchical Bayesian model, preventing the adverse effects caused by inaccurate noise power estimation during iterations in the traditional SR STAP algorithms, further enhancing its performance. Our simulation results demonstrate the high efficiency and superior clutter suppression performance and target detection performance of this method. [ABSTRACT FROM AUTHOR]

mRNA 3' end processing is an essential step in gene expression. It is well established that canonical eukaryotic pre-mRNA 3' processing is carried out within a macromolecular machinery consisting of dozens of trans-acting proteins. However, it is unknown whether RNAs play any role in this process. Unexpectedly, we found that a subset of small nucleolar RNAs (snoRNAs) are associated with the mammalian mRNA 3' processing complex. These snoRNAs primarily interact with Fip1, a component of cleavage and polyadenylation specificity factor (CPSF). We have functionally characterized one of these snoRNAs and our results demonstrated that the U/A-rich SNORD50A inhibits mRNA 3' processing by blocking the Fip1-poly(A) site (PAS) interaction. Consistently, SNORD50A depletion altered the Fip1-RNA interaction landscape and changed the alternative polyadenylation (APA) profiles and/or transcript levels of a subset of genes. Taken together, our data revealed a novel function for snoRNAs and provided the first evidence that non-coding RNAs may play an important role in regulating mRNA 3' processing.

According to Zhao Juan’s research, there are three main paths of Western I Ching which are: 1) the path of religiosity with missionary Sinology as its mother; 2) the path of analytical psychology-comparative culture with Jung as its starting point; and 3) the historical-philosophical path characterized by examination and contemplation. This paper mainly explores the westward movement of ekphrasis through the second path. In addition, according to the four basic features of analytical psychology, i.e., the principle of Purpose Theory, the principle of Mind Power Theory, the doctrine of Collective Unconscious, and the doctrine of Psychological Types, this paper explores the influence of I Ching on analytical psychology from these four aspects.

ZnO nanostructures show great potential in hydrogen sensing at atmospheric conditions for good gas adsorption abilities. However, there is less research on low-pressure hydrogen sensing performance due to its low concentration and in-homogeneous distributions under low-pressure environments. Here, we report the low-pressure hydrogen sensing by the construction of Al–N-co-doped ZnO nanorods based on the adsorption-induced field emission enhancement effect in the pressure range of 10−7 to 10−3 Pa. The investigation indicates that the Al–N-co-doped ZnO sample is the most sensitive to low-pressure hydrogen sensing among all ZnO samples, with the highest sensing current increase of 140% for 5 min emission. In addition, the increased amplitude of sensing current for the Al–N-co-doped ZnO sample could reach 75% at the pressure 7 × 10−3 Pa for 1 min emission. This work not only expands the hydrogen sensing applications to the co-doped ZnO nanomaterials, but also provides a promising approach to develop field emission cathodes with strong low-pressure hydrogen sensing effect. [ABSTRACT FROM AUTHOR]

This article describes the principle, structure, main technical characteristics and Uncertainty evaluation of the 100MN force calibration machine (FCM). The machine adopts a nested structure, that is, a small oil cylinder and a set of reference standard sensors are installed in a large oil cylinder, so that two sets of oil cylinders and reference standard sensors are used together on one machine to realize automatic range conversion. The height of the main frame is 18 m, and the total weight of the machine is 650 t. The maximum force in the compression/the tension direction is 100 MN/60 MN for large range and 1 MN/1 MN for small range. The “direct method” is used to evaluate the Uncertainty of the force value generated by the FCM. The Uncertainty of the relative force value is equal to the average of the relative uncertainty of the output of 9 sensors in parallel. The relative expanded uncertainty of the process and return force values is 0.1%, k = 2.