COVID-19 Convalescent Plasma Therapy Decreases Inflammatory Cytokines: A Randomized Controlled Trial

This study examined the role that cytokines may have played in the beneficial outcomes found when outpatient individuals infected with SARS-CoV-2 were transfused with COVID-19 convalescent plasma (CCP) early in their infection. We found that the pro-inflammatory cytokine IL-6 decreased significantly faster in patients treated early with CCP. Participants with COVID-19 treated with CCP later in the infection did not have the same effect. This decrease in IL-6 levels after early CCP treatment suggests a possible role of inflammation in COVID-19 progression. The evidence of IL-6 involvement brings insight into the possible mechanisms involved in CCP treatment mitigating SARS-CoV-2 severity

Dynamics of Inflammatory Responses After SARS-CoV-2 Infection by Vaccination Status in the USA: A Prospective Cohort Study

BACKGROUND: Cytokines and chemokines play a critical role in the response to infection and vaccination. We aimed to assess the longitudinal association of COVID-19 vaccination with cytokine and chemokine concentrations and trajectories among people with SARS-CoV-2 infection. METHODS: In this longitudinal, prospective cohort study, blood samples were used from participants enrolled in a multi-centre randomised trial assessing the efficacy of convalescent plasma therapy for ambulatory COVID-19. The trial was conducted in 23 outpatient sites in the USA. In this study, participants (aged ≥18 years) were restricted to those with COVID-19 before vaccination or with breakthrough infections who had blood samples and symptom data collected at screening (pre-transfusion), day 14, and day 90 visits. Associations between COVID-19 vaccination status and concentrations of 21 cytokines and chemokines (measured using multiplexed sandwich immunoassays) were examined using multivariate linear mixed-effects regression models, adjusted for age, sex, BMI, hypertension, diabetes, trial group, and COVID-19 waves (pre-alpha or alpha and delta). FINDINGS: Between June 29, 2020, and Sept 30, 2021, 882 participants recently infected with SARS-CoV-2 were enrolled, of whom 506 (57%) were female and 376 (43%) were male. 688 (78%) of 882 participants were unvaccinated, 55 (6%) were partly vaccinated, and 139 (16%) were fully vaccinated at baseline. After adjusting for confounders, geometric mean concentrations of interleukin (IL)-2RA, IL-7, IL-8, IL-15, IL-29 (interferon-λ), inducible protein-10, monocyte chemoattractant protein-1, and tumour necrosis factor-α were significantly lower among the fully vaccinated group than in the unvaccinated group at screening. On day 90, fully vaccinated participants had approximately 20% lower geometric mean concentrations of IL-7, IL-8, and vascular endothelial growth factor-A than unvaccinated participants. Cytokine and chemokine concentrations decreased over time in the fully and partly vaccinated groups and unvaccinated group. Log INTERPRETATION: Initially and during recovery from symptomatic COVID-19, fully vaccinated participants had lower concentrations of inflammatory markers than unvaccinated participants suggesting vaccination is associated with short-term and long-term reduction in inflammation, which could in part explain the reduced disease severity and mortality in vaccinated individuals. FUNDING: US Department of Defense, National Institutes of Health, Bloomberg Philanthropies, State of Maryland, Mental Wellness Foundation, Moriah Fund, Octapharma, HealthNetwork Foundation, and the Shear Family Foundation

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

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

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

Clinical Isolates of Shiga Toxin 1a–Producing Shigella flexneri with an Epidemiological Link to Recent Travel to Hispañiola

Shiga toxins (Stx) are cytotoxins involved in severe human intestinal disease. These toxins are commonly found in Shigella dysenteriae serotype 1 and Shiga-toxin–producing Escherichia coli; however, the toxin genes have been found in other Shigella species. We identified 26 Shigella flexneri serotype 2 strains isolated by public health laboratories in the United States during 2001–2013, which encode the Shiga toxin 1a gene (stx1a). These strains produced and released Stx1a as measured by cytotoxicity and neutralization assays using anti-Stx/Stx1a antiserum. The release of Stx1a into culture supernatants increased ≈100-fold after treatment with mitomycin C, suggesting that stx1a is carried by a bacteriophage. Infectious phage were found in culture supernatants and increased ≈1,000-fold with mitomycin C. Whole-genome sequencing of several isolates and PCR analyses of all strains confirmed that stx1a was carried by a lambdoid bacteriophage. Furthermore, all patients who reported foreign travel had recently been to Hispañiola, suggesting that emergence of these novel strains is associated with that region

Prevalence and correlates of SARS-CoV-2 seropositivity among people who inject drugs in Baltimore, Maryland

Background: SARS-CoV-2 serosurveys can help characterize disparities in SARS-CoV-2 infection and identify gaps in population immunity. Data on SARS-CoV-2 seroprevalence among people who inject drugs (PWID) are limited. Methods: We conducted a cross-sectional study between December 2020 and July 2022 among 561 participants in the AIDS Linked to the IntraVenous Experience (ALIVE) study—a community-based cohort of current and former PWID in Baltimore, Maryland. Serum samples were assayed for infection-induced anti-nucleocapsid (anti-N) and infection and/or vaccination-induced anti-spike-1 (anti-S) SARS-CoV-2 IgG. We estimated adjusted prevalence ratios (aPR) via modified Poisson regression models. Results: The median age was 59 years, 35% were female, 84% were non-Hispanic Black, and 16% reported recent injection drug use. Anti-N antibody prevalence was 26% and anti-S antibody prevalence was 63%. Anti-N and anti-S antibody prevalence increased over time. Being employed (aPR=1.53 [95%CI=1.11–2.11]) was associated with higher anti-N prevalence, while a cancer history (aPR=0.40 [95%CI=0.17–0.90]) was associated with lower anti-N prevalence. HIV infection was associated with higher anti-S prevalence (aPR=1.13 [95%CI=1.02–1.27]), while younger age and experiencing homelessness (aPR=0.78 [95%CI=0.60–0.99]) were factors associated with lower anti-S prevalence. Substance use-related behaviors were not significantly associated with anti-N or anti-S prevalence. Conclusions: SARS-CoV-2 seroprevalence increased over time among current and former PWID, suggesting cumulative increases in the incidence of SARS-CoV-2 infection and vaccination; however, there were disparities in infection-induced seroprevalence and infection and/or vaccine-induced seroprevalence within this study sample. Dedicated prevention and vaccination programs are needed to prevent disparities in infection and gaps in population immunity among PWID during emerging epidemics