Carbon dioxide, hydrographic, and chemical data obtained in the South Pacific Ocean (WOCE Sections P16A/P17A, P17E/P19S, and P19C, R/V Knorr, October 1992--April 1993)

This data documentation discusses the procedures and methods used to measure total carbon dioxide concentration (TCO{sub 2}) and partial pressure of CO{sub 2} (pCO{sub 2}) in discrete water samples collected during three expeditions of the Research Vessel (R/V) Knorr in the South Pacific Ocean. Conducted as part of the World Ocean Circulation Experiment (WOCE), the first cruise (WOCE Section P16A/P17A) began in Papeete, Tahiti, French Polynesia, on October 6, 1992, and returned to Papeete on November 25, 1992. The second cruise (WOCE Section P17E/P19S) began in Papeete on December 4, 1992, and finished in Punta Arenas, Chile, on January 22, 1993. The third expedition (WOCE Section P19C) started in Punta Arenas, on February 22 and finished in Panama City, Panama, on April 13, 1993. During the three expeditions, 422 hydrographic stations were occupied. Hydrographic and chemical measurements made along WOCE Sections P16A/P17A, P17E/P19S, and P19C included pressure, temperature, salinity, and oxygen [measured by conductivity, temperature, and depth (CTD) sensor], as well as discrete measurements of salinity, oxygen, phosphate, nitrate, nitrite, silicate, chlorofluorocarbons (CFC-11, CFC-12), TCO{sub 2}, and pCO{sub 2} measured at 4 and 20 C. In addition, potential temperatures were calculated from the measured variables

Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles

Purpose Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Methods This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. Results The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30- fold (HR:7.30, 95% CI:(3.11-17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10-6.00), p = 0.03) increases in hazard of death relative to phenotype III. Conclusion We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design

Shining a light on the evidence for hydroxychloroquine in SARS-CoV-2

Background The 2020 COVID-19 pandemic has stunned the world, financial markets, and healthcare systems. Researchers are rushing to identify effective treatments while maintaining rigorous adherence to the scientific method. Clinicians are doing their best to provide evidence-based care in a setting of very little good evidence. To date, no effective treatments exist for COVID-19 management. Unfortunately, traditional and social media coupled with world leader commentary have led some to believe hydroxychloroquine offers a bona fide cure and even prevention. The purpose of this commentary is to review the medical literature related to hydroxychloroquine building on knowledge over the past 17 years since the 2003 SARS-CoV epidemic

Fire as a fundamental ecological process: Research advances and frontiers

Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire‐dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above‐ground ecology, (d) fire effects on below‐ground ecology, (e) fire behaviour and (f) fire ecology modelling. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. Synthesis : As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives