Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

A new panel of SNPs to assess thyroid carcinoma risk: a pilot study in a Brazilian admixture population

Abstract Background Thyroid cancer is a common malignant disease of the endocrine system with increasing incidence rates over the last few decades. In this study, we sought to analyze the possible association of 45 single nucleotide polymorphisms (SNPs) with thyroid cancer in a population from Rio Grande do Norte, Brazil. Methods Based on histological analysis by a pathologist, 80 normal thyroid specimens of tissue adjacent to thyroid tumors were obtained from the biobank at the Laboratory of Pathology of Liga Norte Riograndense Contra o Câncer, Natal, RN. Patient samples were then genotyped using the MassARRAY platform (Sequenon, Inc) followed by statistical analysis employing the SNPassoc package in R program. The genotypic frequencies of all 45 SNPs obtained from the International HapMap Project database and based on data from the ancestral populations of European and African origin were used to compose the control study group. Results In our study, the following 9 SNPs showed significant differences in their frequency when comparing the study and control groups: rs3744962, rs258107, rs1461855, rs4075022, rs9943744, rs4075570, rs2356508, rs17485896, and rs2651339. Furthermore, the SNPs rs374492 C/T and rs258107 C/T were associated with a relative risk for thyroid carcinoma of 3.78 (p = 6.27 × 10e−5) and 2.91 (p = 8.27 × 10e−5), respectively, after Bonferroni’s correction for multiple comparisons. Conclusions These nine polymorphisms could be potential biomarkers of predisposition to thyroid carcinoma in the population from Rio Grande do Norte. However, complementary studies including a control group with samples obtained from healthy subjects in Rio Grande do Norte state, should be conducted to confirm these results

Transmission-blocking activity of antimalarials for Plasmodium vivax malaria in Anopheles darlingi.

Malaria is caused by parasite of the genus Plasmodium and is still one of the most important infectious diseases in the world. Several biological characteristics of Plasmodium vivax contribute to the resilience of this species, including early gametocyte production, both of which lead to efficient malaria transmission to mosquitoes. This study evaluated the impact of currently used drugs on the transmission of P. vivax. Participants received one of the following treatments for malaria: i) chloroquine [10 mg/kg on day 1 and 7.5 mg/kg on day 2 and 3] co-administered with Primaquine [0.5 mg/kg/day for 7 days]; ii) Chloroquine [10 mg/kg on day 1 and 7.5 mg/kg on day 2 and 3] co-administered with one-dose of Tafenoquine [300 mg on day 1]; and iii) Artesunate and Mefloquine [100 mg and 200 mg on day 1, 2 and 3] co-administered with Primaquine [0.5 mg/kg/day for 14 days]. Patient blood was collected before treatment and 4 h, 24 h, 48 h and 72 h after treatment. The blood was used to perform a direct membrane feeding assay (DMFA) using Anopheles darlingi mosquitoes. The results showed 100% inhibition of the mosquito infection after 4 h using ASMQ+PQ, after 24 h for the combination of CQ+PQ and 48 h using CQ+TQ. The density of gametocytes declined over time in all treatment groups, although the decline was more rapid in the ASMQ+PQ group. In conclusion, it was possible to demonstrate the transmission-blocking efficacy of the malaria vivax treatment and that ASMQ+PQ acts faster than the two other treatments

Genomic Analysis of Limosilactobacillus fermentum ATCC 23271, a Potential Probiotic Strain with Anti-Candida Activity

Limosilactobacillus fermentum (ATCC 23271) was originally isolated from the human intestine and has displayed antimicrobial activity, primarily against Candida species. Complete genome sequencing and comparative analyses were performed to elucidate the genetic basis underlying its probiotic potential. The ATCC 23271 genome was found to contain 2,193,335 bp, with 2123 protein-coding sequences. Phylogenetic analysis revealed that the ATCC 23271 strain shares 941 gene clusters with six other probiotic strains of L. fermentum. Putative genes known to confer probiotic properties have been identified in the genome, including genes related to adhesion, tolerance to acidic pH and bile salts, tolerance to oxidative stress, and metabolism and transport of sugars and other compounds. A search for bacteriocin genes revealed a sequence 48% similar to that of enterolysin A, a protein from Enterococcus faecalis. However, in vitro assays confirmed that the strain has inhibitory activity on the growth of Candida species and also interferes with their adhesion to HeLa cells. In silico analyses demonstrated a high probability of the protein with antimicrobial activity. Our data reveal the genome features of L. fermentum ATCC 23271, which may provide insight into its future use given the functional benefits, especially against Candida infections