NOX Inhibitors - A Promising Avenue for Ischemic Stroke.

NADPH-oxidase (NOX) mediated superoxide originally found on leukocytes, but now recognized in several types of cells in the brain. It has been shown to play an important role in the progression of stroke and related cerebrovascular disease. NOX is a multisubunit complex consisting of 2 membrane-associated and 4 cytosolic subunits. NOX activation occurs when cytosolic subunits translocate to the membrane, leading to transport electrons to oxygen, thus producing superoxide. Superoxide produced by NOX is thought to function in long-term potentiation and intercellular signaling, but excessive production is damaging and has been implicated to play an important role in the progression of ischemic brain. Thus, inhibition of NOX activity may prove to be a promising treatment for ischemic brain as well as an adjunctive agent to prevent its secondary complications. There is mounting evidence that NOX inhibition in the ischemic brain is neuroprotective, and targeting NOX in circulating immune cells will also improve outcome. This review will focus on therapeutic effects of NOX assembly inhibitors in brain ischemia and stroke. However, the lack of specificity and toxicities of existing inhibitors are clear hurdles that will need to be overcome before this class of compounds could be translated clinically

Designing Urban Media Storytelling through Greimas ’ Narrative Model

This article attempts to establish an urban media storytelling model based on Greimas’ narrative model. Greimas ’ narrative model is distinguished into Narrative Schema model and Actantial model. Of course, other contents that reproduced through urban media can also establish storytelling strategies using these. Moreover, it can also be utilized in establishing a storytelling that applies to the entire space called “city. ” To be more specific, it is a process that receives information and entertainment based on the city, explores the city and ultimately recognizes the city image. This writing suggest such storytelling design linked with a narrative schema and actantial model

Boosting Learning for LDPC Codes to Improve the Error-Floor Performance

Low-density parity-check (LDPC) codes have been successfully commercialized in communication systems due to their strong error correction capabilities and simple decoding process. However, the error-floor phenomenon of LDPC codes, in which the error rate stops decreasing rapidly at a certain level, presents challenges for achieving extremely low error rates and deploying LDPC codes in scenarios demanding ultra-high reliability. In this work, we propose training methods for neural min-sum (NMS) decoders to eliminate the error-floor effect. First, by leveraging the boosting learning technique of ensemble networks, we divide the decoding network into two neural decoders and train the post decoder to be specialized for uncorrected words that the first decoder fails to correct. Secondly, to address the vanishing gradient issue in training, we introduce a block-wise training schedule that locally trains a block of weights while retraining the preceding block. Lastly, we show that assigning different weights to unsatisfied check nodes effectively lowers the error-floor with a minimal number of weights. By applying these training methods to standard LDPC codes, we achieve the best error-floor performance compared to other decoding methods. The proposed NMS decoder, optimized solely through novel training methods without additional modules, can be integrated into existing LDPC decoders without incurring extra hardware costs. The source code is available at https://github.com/ghy1228/LDPC_Error_Floor .Comment: 17 pages, 10 figure

How to Mask in Error Correction Code Transformer: Systematic and Double Masking

In communication and storage systems, error correction codes (ECCs) are pivotal in ensuring data reliability. As deep learning's applicability has broadened across diverse domains, there is a growing research focus on neural network-based decoders that outperform traditional decoding algorithms. Among these neural decoders, Error Correction Code Transformer (ECCT) has achieved the state-of-the-art performance, outperforming other methods by large margins. To further enhance the performance of ECCT, we propose two novel methods. First, leveraging the systematic encoding technique of ECCs, we introduce a new masking matrix for ECCT, aiming to improve the performance and reduce the computational complexity. Second, we propose a novel transformer architecture of ECCT called a double-masked ECCT. This architecture employs two different mask matrices in a parallel manner to learn more diverse features of the relationship between codeword bits in the masked self-attention blocks. Extensive simulation results show that the proposed double-masked ECCT outperforms the conventional ECCT, achieving the state-of-the-art decoding performance with significant margins.Comment: 8 pages, 5 figure

Functional magnetic resonance imaging multivoxel pattern analysis reveals neuronal substrates for collaboration and competition with myopic and predictive strategic reasoning

Competition and collaboration are strategies that can be used to optimize the outcomes of social interactions. Research into the neuronal substrates underlying these aspects of social behavior has been limited due to the difficulty in distinguishing complex activation via univariate analysis. Therefore, we employed multivoxel pattern analysis of functional magnetic resonance imaging to reveal the neuronal activations underlying competitive and collaborative processes when the collaborator/opponent used myopic/predictive reasoning. Twenty- four healthy subjects participated in 2- Ã - 2 matrix- based sequential- move games. Searchlight- based multivoxel patterns were used as input for a support vector machine using nested cross- validation to distinguish game conditions, and identified voxels were validated via the regression of the behavioral data with bootstrapping. The left anterior insula (accuracy = 78.5%) was associated with competition, and middle frontal gyrus (75.1%) was associated with predictive reasoning. The inferior/superior parietal lobules (84.8%) and middle frontal gyrus (84.7%) were associated with competition, particularly in trials with a predictive opponent. The visual/motor areas were related to response time as a proxy for visual attention and task difficulty. Our results suggest that multivoxel patterns better represent the neuronal substrates underlying the social cognition of collaboration and competition intermixed with myopic and predictive reasoning than do univariate features.We employed multivoxel pattern analysis of functional magnetic resonance imaging to reveal the neuronal activations underlying competitive and collaborative processes when the collaborator/opponent used myopic/predictive reasoning in 2- Ã - 2 matrix- based sequential- move games. Searchlight- based multivoxel patterns and support vector machine were used in a nested cross- validation to distinguish game conditions, and identified voxels in the left anterior insula, middle frontal gyrus, and inferior/superior parietal lobules were validated via the regression of the behavioral data with bootstrapping by excluding potential visual attention component. Our results suggest that multivoxel patterns better represent the neuronal substrates underlying the social cognition of collaboration and competition intermixed with myopic and predictive reasoning than do univariate features.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162700/3/hbm25127-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162700/2/hbm25127_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162700/1/hbm25127.pd

Iterative Soft Decoding Algorithm for DNA Storage Using Quality Score and Redecoding

Ever since deoxyribonucleic acid (DNA) was considered as a next-generation data-storage medium, lots of research efforts have been made to correct errors occurred during the synthesis, storage, and sequencing processes using error correcting codes (ECCs). Previous works on recovering the data from the sequenced DNA pool with errors have utilized hard decoding algorithms based on a majority decision rule. To improve the correction capability of ECCs and robustness of the DNA storage system, we propose a new iterative soft decoding algorithm, where soft information is obtained from FASTQ files and channel statistics. In particular, we propose a new formula for log-likelihood ratio (LLR) calculation using quality scores (Q-scores) and a redecoding method which may be suitable for the error correction and detection in the DNA sequencing area. Based on the widely adopted encoding scheme of the fountain code structure proposed by Erlich et al., we use three different sets of sequenced data to show consistency for the performance evaluation. The proposed soft decoding algorithm gives 2.3% ~ 7.0% improvement of the reading number reduction compared to the state-of-the-art decoding method and it is shown that it can deal with erroneous sequenced oligo reads with insertion and deletion errors

Anticancer Efficacy of Cordyceps militaris

Cordyceps militaris is used widely as a traditional medicine in East Asia. Although a few studies have attempted to elucidate the anticancer activities of C. militaris, the precise mechanism of C. militaris therapeutic effects is not fully understood. We examined the anticancer activities of C. militaris ethanolic extract (Cm-EE) and its cellular and molecular mechanisms. For this purpose, a xenograft mouse model bearing murine T cell lymphoma (RMA) cell-derived cancers was established to investigate in vivo anticancer mechanisms. MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay, immunoblotting analysis, and flow cytometric assay were employed to check in vitro cytotoxicity, molecular targets, and proapoptotic action of Cm-EE. Interestingly, cancer sizes and mass were reduced in a C. militaris-administered group. Levels of the phosphorylated forms of p85 and AKT were clearly decreased in the group administered with Cm-EE. This result indicated that levels of phosphoglycogen synthase kinase 3β (p-GSK3β) and cleaved caspase-3 were increased with orally administered Cm-EE. In addition, Cm-EE directly inhibited the viability of cultured RMA cells and C6 glioma cells. The number of proapoptotic cells was significantly increased in a Cm-EE treated group compared with a control group. Our results suggested that C. militaris might be able to inhibit cancer growth through regulation of p85/AKT-dependent or GSK3β-related caspase-3-dependent apoptosis