Is Low Alveolar Type II Cell SOD3 in the Lungs of Elderly Linked to the Observed Severity of COVID-19?

Human lungs single cell RNA sequencing data from healthy donors (elderly and young; GEO accession number GSE122960) were analyzed to isolate and specifically study gene expression in alveolar type II cells. Co-localization of ACE2 and TMPRSS2 enables SARS-CoV 2 to enter the cells. Expression of these genes in the alveolar type II cells of elderly and young patients were comparable and therefore do not seem to be responsible for worse outcomes observed in COVID-19 affected elderly. In cells from the elderly, 263 genes were downregulated and 95 upregulated. SOD3 was identified as the top-ranked gene that was most down-regulated in the elderly. Other redox-active genes that were also downregulated in cells from the elderly included ATF4 and M2TA. ATF4, an ER stress sensor that defends lungs via induction of heme oxygenase 1. The study of downstream factors known to be induced by ATF4, according to Ingenuity Pathway AnalysisTM, identified 24 candidates. Twenty-one of these were significantly downregulated in the cells from the elderly. These downregulated candidates were subjected to enrichment using the Reactome Database identifying that in the elderly, the ability to respond to heme deficiency and the ATF4-dependent ability to respond to endoplasmic reticulum stress is significantly compromised. SOD3-based therapeutic strategies have provided beneficial results in treating lung disorders including fibrosis. The findings of this work propose the hypotheses that lung-specific delivery of SOD3/ATF4 related antioxidants may work in synergy with promising anti-viral drugs such as remdesivir to further improve COVID-19 outcomes in the elderly

Origin of biological information: Inherent occurrence of intron-rich split genes, coding for complex extant proteins, within pre-biotic random genetic sequences

The origin of biological information is an unexplained phenomenon. Prior research in resolving the origin of proteins, based on the assumption that the first genes were contiguous prokaryotic sequences has not succeeded. Rather, it has been established that contiguous protein-coding genes do not exist in practically any amount of random genetic sequences. We found that complex eukaryotic proteins could be inherently encoded in split genes that could exist by chance within mere micrograms to milligrams of random DNA. Using protein amino acid sequence variability, codon degeneracy, and stringent exon-length restriction, we demonstrate that split genes for proteins of extant eukaryotes occur extensively in random genetic sequences. The results provide evidence that an abundance of split genes encoding advanced proteins in a small amount of prebiotic genetic material could have ignited the evolution of the eukaryotic genome

Location-Specific Tweet Detection and Topic Summarization in Twitter

Abstract-Automatic detection of tweets that provide Location-specific information will be extremely useful in conveying geo-location based knowledge to the users. However, there is a significant challenge in retrieving such tweets due to the sparsity of geo-tag information, the short textual nature of tweets, and the lack of pre-defined set of topics. In this paper, we develop a novel framework to identify and summarize tweets that are specific to a location. First, we propose a weighting scheme called Location Centric Word Co-occurrence (LCWC) that uses the content of the tweets and the network information of the twitterers to identify tweets that are location-specific. We evaluate the proposed model using a set of annotated tweets and compare the performance with other weighting schemes studied in the literature. This paper reports three key findings: (a) top trending tweets from a location are poor descriptors of location-specific tweets, (b) ranking tweets purely based on users' geo-location cannot ascertain the location specificity of tweets, and (c) users' network information plays an important role in determining the location-specific characteristics of the tweets. Finally, we train a topic model based on Latent Dirichlet Allocation (LDA) using a large collection of local news database and tweet-based Urls to predict the topics from the location-specific tweets and present them using an interactive web-based interface

Identification of Genomic Regions and Sources for Wheat Blast Resistance through GWAS in Indian Wheat Genotypes

Wheat blast (WB) is a devastating fungal disease that has recently spread to Bangladesh and poses a threat to the wheat production in India, which is the second-largest wheat producing country in the world. In this study, 350 Indian wheat genotypes were evaluated for WB resistance in 12 field experiments in three different locations, namely Jashore in Bangladesh and Quirusillas and Okinawa in Bolivia. Single nucleotide polymorphisms (SNPs) across the genome were obtained using DArTseq (R) technology, and 7554 filtered SNP markers were selected for a genome-wide association study (GWAS). All the three GWAS approaches used identified the 2NS translocation as the only major source of resistance, explaining up to 32% of the phenotypic variation. Additional marker-trait associations were located on chromosomes 2B, 3B, 4D, 5A and 7A, and the combined effect of three SNPs (2B_180938790, 7A_752501634 and 5A_618682953) showed better resistance, indicating their additive effects on WB resistance. Among the 298 bread wheat genotypes, 89 (29.9%) carried the 2NS translocation, the majority of which (60 genotypes) were CIMMYT introductions, and 29 were from India. The 2NS carriers with a grand mean WB index of 6.6 showed higher blast resistance compared to the non-2NS genotypes with a mean index of 46.5. Of the 52 durum wheats, only one genotype, HI 8819, had the 2NS translocation and was the most resistant, with a grand mean WB index of 0.93. Our study suggests that the 2NS translocation is the only major resistance source in the Indian wheat panel analysed and emphasizes the urgent need to identify novel non-2NS resistance sources and genomic regions

Serre's "formule de masse" in prime degree

For a local field F with finite residue field of characteristic p, we describe completely the structure of the filtered F_p[G]-module K^*/K^*p in characteristic 0 and $K^+/\wp(K^+) in characteristic p, where K=F(\root{p-1}\of F^*) and G=\Gal(K|F). As an application, we give an elementary proof of Serre's mass formula in degree p. We also determine the compositum C of all degree p separable extensions with solvable galoisian closure over an arbitrary base field, and show that C is K(\root p\of K^*) or K(\wp^{-1}(K)) respectively, in the case of the local field F. Our method allows us to compute the contribution of each character G\to\F_p^* to the degree p mass formula, and, for any given group \Gamma, the contribution of those degree p separable extensions of F whose galoisian closure has group \Gamma.Comment: 36 pages; most of the new material has been moved to the new Section