Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Helios expressing regulatory T cells are correlated with decreased IL-2 producing CD8 T cells and antibody diversity in Mozambican individuals living chronically with HIV-1

BACKGROUND: Human immunodeficiency virus type 1 (HIV-1) causes impairment of T and B cell responses, which begins during the acute phase of infection and is not completely restored by antiretroviral treatment. Regulatory T cell (Tregs) can improve overall disease outcome by controlling chronic inflammation but may also suppress beneficial HIV-1 specific immune responses. We aimed to analyze the profile of Tregs and their correlation with the status of T cells activation, the expression of IL-2 and IFNγ and the profile of HIV-1 specific antibodies response in Mozambican people living chronically with HIV-1 (PLWH-C). RESULTS: In PLWH-C, the proportion of total Tregs was positively correlated with the proportion of IL-2(+)CD4 T cells (r = 0.647; p = 0.032) and IL-2(+)IFNγ(+)CD8 T cells (r = 0.551; p = 0.014), while the proportions of Helios(+)Tregs correlated inversely with levels of IL-2(+)CD8 T cells (r = − 0.541; p = 0.017). Overall, PLWH-C, with (82%) or without virologic suppression (64%), were seronegative for at least HIV-1 p31, gp160 or p24, and the breadth of antibody responses was positively correlated with proportions of CD38(+)HLA-DR(+)CD8 T cells (r = 0.620; p = 0.012), viral load (r = 0.452; p = 0.040) and inversely with absolute CD4 T cells count (r = − 0.481; p = 0.027). Analysis of all individuals living HIV-1 showed that the breadth of HIV-1 antibody responses was inversely correlated with the proportion of Helios(+)Tregs (r = − 0.45; p = 0.02). CONCLUSION: Among Mozambican people living with HIV-1, seronegativity to some HIV-1 proteins is common, particularly in virologically suppressed individuals. Furthermore, lower diversity of HIV-specific antibodies is correlated to lower immune activation, lower viral replication and higher CD4 counts, in PLWH-C. Elevation in the proportion of Helios(+)Tregs is related to a reduction of CD8 T expressing intracellular IL-2, in PLWH-C, but may contribute to impairment of B cell function. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12865-022-00487-3

False reactive HIV-1 diagnostic test results in an individual from Kenya on multiple testing platforms-A case report

Background: Rapid diagnostic tests (RDT) are routinely used in screening for HIV infection. More complex diagnostic algorithms incorporating fourth-generation screening and confirmatory HIV-1/HIV-2 differentiation immunoassays (IA) may be used to confirm HIV infection. Co-infections and autoimmune diseases may lead to falsely reactive HIV diagnostic test results. Case presentation: A Kenyan man with asymptomatic schistosomiasis and low risk factors for HIV infection demonstrated an inconsistent and discordant pattern of reactivity on HIV RDT, repeated reactivity on fourth-generation IA and positive at a single time-point for HIV-1 on the Geenius HIV1/HIV2 confirmatory assay during the course of a prospective cohort study with HIV repeat testing. The individual initiated antiretroviral therapy following HIV diagnosis. However, his bi-annual behavioral questionnaire suggested low-risk factors for infection. Supplementary confirmatory serologic and nucleic acid tests were performed and gave discordant results. The participant was determined to be HIV uninfected using cell-associated HIV-1 DNA/RNA testing and antiretroviral therapy was discontinued. Discussion and conclusions: Sole reliance on diagnostic test results may result in misdiagnosis of HIV infection, social harm and potential antiretroviral induced drug toxicity. Interpretation of HIV test results should incorporate multiple parameters

Determining hematological, biochemical and immunological reference values in healthy adults with high-risk for HIV acquisition in Mozambique.

INTRODUCTION:In many African countries, laboratory reference values are not established for the local healthy adult population. In Mozambique, reference values are known for young adults (18-24yo) but not yet established for a wider age range. Our study aimed to establish hematological, biochemical and immunological reference values for vaccine trials in Mozambican healthy adults with high-risk for HIV acquisition. METHODS:A longitudinal cohort and site development study in Mozambique between November 2013 and 2014 enrolled 505 participants between 18 to 35 years old. Samples from these healthy participants, were analyzed to determine reference values. All volunteers included in the analysis were clinically healthy and human immunodeficiency virus (HIV), hepatitis B and C virus, and syphilis negative. Median and reference ranges were calculated for the hematological, biochemical and immunological parameters. Ranges were compared with other African countries, the USA and the US National Institute of Health (NIH) Division of AIDS (DAIDS) toxicity tables. RESULTS:A total of 505 participant samples were analyzed. Of these, 419 participants were HIV, hepatitis B and C virus and syphilis negative including 203 (48.5%) females and 216 (51.5%) males, with a mean age of 21 years. In the hematological parameters, we found significant differences between sex for erythrocytes, hemoglobin, hematocrit, MCV, MCH and MCHC as well as white blood cells, neutrophils and platelets: males had higher values than females. There were also significant differences in CD4+T cell values, 803 cells/μL in men versus 926 cells/μL in women. In biochemical parameters, men presented higher values than women for the metabolic, enzymatic and renal parameters: total and direct bilirubin, ALT and creatinine. CONCLUSION:This study has established reference values for healthy adults with high-risk for HIV acquisition in Mozambique. These data are helpful in the context of future clinical research and patient care and treatment for the general adult population in the Mozambique and underline the importance of region-specific clinical reference ranges

Clinical laboratory reference values in adults in Kisumu County, Western Kenya; hematology, chemistry and CD4.

BackgroundClinical laboratory reference intervals (RIs) are essential for diagnosing and managing patients in routine clinical care as well as establishing eligibility criteria and defining adverse events in clinical trials, but may vary by age, gender, genetics, nutrition and geographic location. It is, therefore, critical to establish region-specific reference values in order to inform clinical decision-making.MethodsWe analyzed data from a prospective observational HIV incidence cohort study in Kombewa, Kenya. Study participants were healthy males and females, aged 18-35 years, without HIV. Median and 95% reference values (2.5th percentile to 97.5th percentile) were calculated for laboratory parameters including hematology, chemistry studies, and CD4 T cell count. Standard Deviation Ratios (SDR) and Bias Ratios (BR) are presented as measures of effect magnitude. Findings were compared with those from the United States and other Kenyan studies.ResultsA total of 299 participants were analyzed with a median age of 24 years (interquartile range: 21-28). Ratio of males to females was 0.9:1. Hemoglobin range (2.5th-97.5th percentiles) was 12.0-17.9 g/dL and 9.5-15.3 g/dL in men and women respectively. In the cohort, MCV range was 59-95fL, WBC 3.7-9.2×103/μL, and platelet 154-401×103/μL. Chemistry values were higher in males; the creatinine RI was 59-103 μmol/L in males vs. 46-76 μmol/L in females (BRUL>.3); and the alanine transferase range was 8.8-45.3 U/L in males vs. 7.5-36.8 U/L in females (SDR>.3). The overall CD4 T cell count RI was 491-1381 cells/μL. Some parameters including hemoglobin, neutrophil, creatinine and ALT varied with that from prior studies in Kenya and the US.ConclusionThis study not only provides clinical reference intervals for a population in Kisumu County but also highlights the variations in comparable settings, accentuating the requirement for region-specific reference values to improve patient care, scientific validity, and quality of clinical trials in Africa

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to- biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g., RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Aboveground Biomass Density Models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) Lidar Mission

NASAs Global Ecosystem Dynamics Investigation (GEDI) is collecting space-borne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDIs footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDIs waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we select the best input predictor variables, data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favors combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) does not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and that the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Oxygen targets and 6-month outcome after out of hospital cardiac arrest: a pre-planned sub-analysis of the targeted hypothermia versus targeted normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial

International audienceAbstract Background Optimal oxygen targets in patients resuscitated after cardiac arrest are uncertain. The primary aim of this study was to describe the values of partial pressure of oxygen values (PaO 2 ) and the episodes of hypoxemia and hyperoxemia occurring within the first 72 h of mechanical ventilation in out of hospital cardiac arrest (OHCA) patients. The secondary aim was to evaluate the association of PaO 2 with patients’ outcome. Methods Preplanned secondary analysis of the targeted hypothermia versus targeted normothermia after OHCA (TTM2) trial. Arterial blood gases values were collected from randomization every 4 h for the first 32 h, and then, every 8 h until day 3. Hypoxemia was defined as PaO 2  300 mmHg. Mortality and poor neurological outcome (defined according to modified Rankin scale) were collected at 6 months. Results 1418 patients were included in the analysis. The mean age was 64 ± 14 years, and 292 patients (20.6%) were female. 24.9% of patients had at least one episode of hypoxemia, and 7.6% of patients had at least one episode of severe hyperoxemia. Both hypoxemia and hyperoxemia were independently associated with 6-month mortality, but not with poor neurological outcome. The best cutoff point associated with 6-month mortality for hypoxemia was 69 mmHg (Risk Ratio, RR = 1.009, 95% CI 0.93–1.09), and for hyperoxemia was 195 mmHg (RR = 1.006, 95% CI 0.95–1.06). The time exposure, i.e., the area under the curve (PaO 2 -AUC), for hyperoxemia was significantly associated with mortality ( p = 0.003). Conclusions In OHCA patients, both hypoxemia and hyperoxemia are associated with 6-months mortality, with an effect mediated by the timing exposure to high values of oxygen. Precise titration of oxygen levels should be considered in this group of patients. Trial registration : clinicaltrials.gov NCT02908308 , Registered September 20, 2016