Adaptation and Mal-Adaptation to Ambient Hypoxia; Andean, Ethiopian and Himalayan Patterns

The study of the biology of evolution has been confined to laboratories and model organisms. However, controlled laboratory conditions are unlikely to model variations in environments that influence selection in wild populations. Thus, the study of “fitness” for survival and the genetics that influence this are best carried out in the field and in matching environments

Proteinase 3 contributes to endothelial dysfunction in an experimental model of sepsis

In sepsis-induced inflammation, polymorphonuclear neutrophils (PMNs) contribute to vascular dysfunction. The serine proteases proteinase 3 (PR3) and human leukocyte elastase (HLE) are abundant in PMNs and are released upon degranulation. While HLE’s role in inflammation-induced endothelial dysfunction is well studied, PR3’s role is largely uninvestigated. We hypothesized that PR3, similarly to HLE, contributes to vascular barrier dysfunction in sepsis. Plasma PR3 and HLE concentrations and their leukocyte mRNA levels were measured by ELISA and qPCR, respectively, in sepsis patients and controls. Exogenous PR3 or HLE was applied to human umbilical vein endothelial cells (HUVECs) and HUVEC dysfunction was assessed by FITC-dextran permeability and electrical resistance. Both PR3 and HLE protein and mRNA levels were significantly increased in sepsis patients (P \u3c 0.0001 and P \u3c 0.05, respectively). Additionally, each enzyme independently increased HUVEC monolayer FITC-dextran permeability (P \u3c 0.01), and decreased electrical resistance in a time- and dose-dependent manner (P \u3c 0.001), an effect that could be ameliorated by novel treatment with carbon monoxide-releasing molecule 3 (CORM-3). The serine protease PR3, in addition to HLE, lead to vascular dysfunction and increased endothelial permeability, a hallmark pathological consequence of sepsis-induced inflammation. CORMs may offer a new strategy to reduce serine protease-induced vascular dysfunction

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO2 could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest

Protocol for the Prognostication of Consciousness Recovery Following a Brain Injury

Individuals who have suffered a severe brain injury typically require extensive hospitalization in intensive care units (ICUs), where critical treatment decisions are made to maximize their likelihood of recovering consciousness and cognitive function. These treatment decisions can be difficult when the neurological assessment of the patient is limited by unreliable behavioral responses. Reliable objective and quantifiable markers are lacking and there is both (1) a poor understanding of the mechanisms underlying the brain’s ability to reconstitute consciousness and cognition after an injury and (2) the absence of a reliable and clinically feasible method of tracking cognitive recovery in ICU survivors. Our goal is to develop and validate a clinically relevant EEG paradigm that can inform the prognosis of unresponsive, brain-injured patients in the ICU. This protocol describes a study to develop a point-of-care system intended to accurately predict outcomes of unresponsive, brain-injured patients in the ICU. We will recruit 200 continuously-sedated brain-injured patients across five ICUs. Between 24 h and 7 days post-ICU admission, high-density EEG will be recorded from behaviorally unresponsive patients before, during and after a brief cessation of pharmacological sedation. Once patients have reached the waking stage, they will be asked to complete an abridged Cambridge Brain Sciences battery, a web-based series of neurocognitive tests. The test series will be repeated every day during acute admission (ICU, ward), or as often as possible given the constraints of ICU and ward care. Following discharge, patients will continue to complete the same test series on weekly, and then monthly basis, for up to 12 months following injury. Functional outcomes will also be assessed up to 12 months post-injury. We anticipate our findings will lead to an increased ability to identify patients, as soon as possible after their brain injury, who are most likely to survive, and to make accurate predictions about their long-term cognitive and functional outcome. In addition to providing critically needed support for clinical decision-making, this study has the potential to transform our understanding of key functional EEG networks associated with consciousness and cognition

Clinical characteristics, multiorgan dysfunction and outcomes of patients with COVID-19: a prospective case series

BACKGROUND: Characterizing the multiorgan manifestations and outcomes of patients hospitalized with COVID-19 will inform resource requirements to address the long-term burden of this disease. We conducted a descriptive analysis using prospectively collected data to describe the clinical characteristics and spectrum of organ dysfunction, and in-hospital and longer-term clinical outcomes of patients hospitalized with COVID-19 during the first wave of the pandemic at a Canadian centre. METHODS: We conducted a prospective case series involving adult patients (aged ≥ 18 yr) with COVID-19 admitted to 1 of 2 hospitals in London, Ontario, from Mar. 17 to June 18, 2020, during the first wave of the pandemic. We recorded patients\u27 baseline characteristics, physiologic parameters, measures of organ function and therapies administered during hospitalization among patients in the intensive care unit (ICU) and in non-ICU settings, and compared the characteristics of hospital survivors and nonsurvivors. Finally, we recorded follow-up thoracic computed tomography (CT) and echocardiographic findings after hospital discharge. RESULTS: We enrolled 100 consecutive patients (47 women) hospitalized with COVID-19, including 32 patients who received ICU care and 68 who received treatment in non-ICU settings. Respiratory sequelae were common: 23.0% received high-flow oxygen by nasal cannula, 9.0% received noninvasive ventilation, 24.0% received invasive mechanical ventilation and 2.0% received venovenous extracorporeal membrane oxygenation. Overall, 9.0% of patients had cerebrovascular events (3.0% ischemic stroke, 6.0% intracranial hemorrhage), and 6.0% had pulmonary embolism. After discharge, 11 of 19 patients had persistent abnormalities on CT thorax, and 6 of 15 had persistent cardiac dysfunction on echocardiography. INTERPRETATION: This study provides further evidence that COVID-19 is a multisystem disease involving neurologic, cardiac and thrombotic dysfunction, without evidence of hepatic dysfunction. Patients have persistent organ dysfunction after hospital discharge, underscoring the need for research on long-term outcomes of COVID-19 survivors

The path from root input to mineral-associated soil carbon is dictated by habitat-specific microbial traits and soil moisture

Soil microorganisms help transform plant inputs into mineral-associated soil organic carbon (SOC) – the largest and slowest-cycling pool of organic carbon on land. However, the microbial traits that influence this process are widely debated. While current theory and biogeochemical models have settled on carbon-use efficiency (CUE) and growth rate as positive predictors of mineral-associated SOC, empirical tests are sparse, with contradictory observations. Using 13C-labeling of an annual grass (Avena barbata) under two moisture regimes, we found that microbial traits associated with formation of 13C-mineral-associated SOC varied by soil habitat, as did active microbial taxa and SOC chemical composition. In the rhizosphere, bacterial-dominated communities with fast growth, high biomass, and high extracellular polymeric substance (EPS) production were positively associated with 13C-mineral-associated SOC. In contrast, the detritusphere held communities dominated by fungi and more filamentous bacteria, and with greater exoenzyme activity; there, 13C-mineral-associated SOC was associated with slower microbial growth and lower microbial biomass. CUE was a negative predictor of 13C-mineral-associated SOC in both habitats. Using 13C-quantitative stable isotope probing, we found that the majority of 13C assimilation in the rhizosphere and detritusphere at week 12 of the experiment was performed by very few bacterial and fungal taxa (3–5% of the total taxa that assimilated 13C). Several complementary chemical analyses (13C-NMR, FTICR-MS, and STXM-NEXAFS) suggested that SOC in the rhizosphere had a more oxidized chemical signature, while SOC in the detritusphere had a less oxidized, more lignin-like chemical signature. Our findings challenge current theory by demonstrating that microbial traits linked with mineral-associated SOC are not universal, but vary with soil habitat and moisture conditions, and are shaped by a small number of active taxa. Emerging SOC models that explicitly reflect these interactions may better predict SOC storage, since climate change causes shifts in soil moisture regimes and the ratio of living versus decaying roots

Critically Ill COVID-19 Patients Exhibit Anti-SARS-CoV-2 Serological Responses

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is a global health care emergency. Anti-SARS-CoV-2 serological profiling of critically ill COVID-19 patients was performed to determine their humoral response. Blood was collected from critically ill ICU patients, either COVID-19 positive (+) or COVID-19 negative (−), to measure anti-SARS-CoV-2 immunoglobulins: IgM; IgA; IgG; and Total Ig (combined IgM/IgA/IgG). Cohorts were similar, with the exception that COVID-19+ patients had a greater body mass indexes, developed bilateral pneumonias more frequently and suffered increased hypoxia when compared to COVID-19-patients (p \u3c 0.05). The mortality rate for COVID-19+ patients was 50%. COVID-19 status could be determined by anti-SARS-CoV-2 serological responses with excellent classification accuracies on ICU day 1 (89%); ICU day 3 (96%); and ICU days 7 and 10 (100%). The importance of each Ig isotype for determining COVID-19 status on combined ICU days 1 and 3 was: Total Ig, 43%; IgM, 27%; IgA, 24% and IgG, 6%. Peak serological responses for each Ig isotype occurred on different ICU days (IgM day 13 \u3e IgA day 17 \u3e IgG persistently increased), with the Total Ig peaking at approximately ICU day 18. Those COVID-19+ patients who died had earlier or similar peaks in IgA and Total Ig in their ICU stay when compared to patients who survived (p \u3c 0.005). Critically ill COVID-19 patients exhibit anti-SARS-CoV-2 serological responses, including those COVID-19 patients who ultimately died, suggesting that blunted serological responses did not contribute to mortality. Serological profiling of critically ill COVID-19 patients may aid disease surveillance, patient cohorting and help guide antibody therapies such as convalescent plasma

Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern

BACKGROUND. The role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome. METHODS. Using SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients’ plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution. RESULTS. We identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811–825, S-881–895, and N-156–170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes. CONCLUSION. Epitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats. FUNDING. Ontario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund