Effects of Lightning on Trees: A Predictive Model Based on in situ Electrical Resistivity

The effects of lightning on trees range from catastrophic death to the absence of observable damage. Such differences may be predictable among tree species, and more generally among plant life history strategies and growth forms. We used field‐collected electrical resistivity data in temperate and tropical forests to model how the distribution of power from a lightning discharge varies with tree size and identity, and with the presence of lianas. Estimated heating density (heat generated per volume of tree tissue) and maximum power (maximum rate of heating) from a standardized lightning discharge differed 300% among tree species. Tree size and morphology also were important; the heating density of a hypothetical 10 m tall Alseis blackiana was 49 times greater than for a 30 m tall conspecific, and 127 times greater than for a 30 m tall Dipteryx panamensis. Lianas may protect trees from lightning by conducting electric current; estimated heating and maximum power were reduced by 60% (±7.1%) for trees with one liana and by 87% (±4.0%) for trees with three lianas. This study provides the first quantitative mechanism describing how differences among trees can influence lightning–tree interactions, and how lianas can serve as natural lightning rods for trees

The RELAMPAGO Lightning Mapping Array: Preliminary Scientific Results and Application to GLM Calibration and Validation

During November 2018 through April 2019, an 11-station NASA lightning mapping array (LMA) was installed in the Cordoba region of Argentina, in support of GOES-16 Geostationary Lightning Mapper (GLM) calibration and validation, as well as the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. This region of Argentina is well known for frequent, intense thunderstorms and severe weather. The LMA was monitored remotely via the Internet throughout its deployment, but due to bandwidth limitations no real-time data were available. Custom GOES-16 imagery provided by NASA SPoRT assisted with monitoring of thunderstorm cases. Occasional site visits were done to obtain data disks, perform routine maintenance, and troubleshoot problems. During the deployment the network captured lightning in a variety of storm modes, including ordinary and severe multicells, supercells, and mesoscale convective systems. Many examples of normal-polarity thunderstorms, as well as a few examples of anomalously charged thunderstorms, were observed. Long (100+ km) horizontally stratified lightning flashes, as well as lightning in overshooting tops, also were frequently observed. Supporting research radar observations were available through January 2019, with operational radar coverage available after that time. Some cases featured supporting ABI meso scanning. This presentation will report on the LMA deployment in context with the RELAMPAGO field campaign, show results from some representative case studies, and will provide initial comparisons to GLM observations

Development of a Kemp\u27s Ridley Sea Turtle Stock Assessment Model

We developed a Kemp’s ridley (Lepidochelys kempii) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for the next stock assessment to evaluate the 2010 event using more recent nesting and in-water data

Safety and Effectiveness of Meropenem in Infants With Suspected or Complicated Intra-abdominal Infections

Background. Intra-abdominal infections are common in young infants and lead to significant morbidity and mortality. Meropenem is a broad-spectrum antimicrobial with excellent activity against pathogens associated with intra-abdominal infections. The purpose of this study was to determine the safety and effectiveness of meropenem in young infants with suspected or complicated intra-abdominal infections

Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

BACKGROUND: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. METHODS: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. RESULTS: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. CONCLUSIONS: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. FUNDING: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. CLINICAL TRIAL NUMBER: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701

The RELAMPAGO Lightning Mapping Array: Preliminary Scientific Results and Application to GLM Calibration and Validation

No abstract availabl

Association of convalescent plasma therapy with survival in patients with hematologic cancers and COVID-19

Importance: COVID-19 is a life-threatening illness for many patients. Prior studies have established hematologic cancers as a risk factor associated with particularly poor outcomes from COVID-19. To our knowledge, no studies have established a beneficial role for anti-COVID-19 interventions in this at-risk population. Convalescent plasma therapy may benefit immunocompromised individuals with COVID-19, including those with hematologic cancers. Objective: To evaluate the association of convalescent plasma treatment with 30-day mortality in hospitalized adults with hematologic cancers and COVID-19 from a multi-institutional cohort. Design, Setting, and Participants: This retrospective cohort study using data from the COVID-19 and Cancer Consortium registry with propensity score matching evaluated patients with hematologic cancers who were hospitalized for COVID-19. Data were collected between March 17, 2020, and January 21, 2021. Exposures: Convalescent plasma treatment at any time during hospitalization. Main Outcomes and Measures: The main outcome was 30-day all-cause mortality. Cox proportional hazards regression analysis with adjustment for potential confounders was performed. Hazard ratios (HRs) are reported with 95% CIs. Secondary subgroup analyses were conducted on patients with severe COVID-19 who required mechanical ventilatory support and/or intensive care unit admission. Results: A total of 966 individuals (mean [SD] age, 65 [15] years; 539 [55.8%] male) were evaluated in this study; 143 convalescent plasma recipients were compared with 823 untreated control patients. After adjustment for potential confounding factors, convalescent plasma treatment was associated with improved 30-day mortality (HR, 0.60; 95% CI, 0.37-0.97). This association remained significant after propensity score matching (HR, 0.52; 95% CI, 0.29-0.92). Among the 338 patients admitted to the intensive care unit, mortality was significantly lower in convalescent plasma recipients compared with nonrecipients (HR for propensity score-matched comparison, 0.40; 95% CI, 0.20-0.80). Among the 227 patients who required mechanical ventilatory support, mortality was significantly lower in convalescent plasma recipients compared with nonrecipients (HR for propensity score-matched comparison, 0.32; 95% CI, 0.14-0.72). Conclusions and Relevance: The findings of this cohort study suggest a potential survival benefit in the administration of convalescent plasma to patients with hematologic cancers and COVID-19

Population Pharmacokinetics of Meropenem in Plasma and Cerebrospinal Fluid of Infants With Suspected or Complicated Intra-abdominal Infections

Background: Suspected or complicated intra-abdominal infections are common in young infants and lead to significant morbidity and mortality. Meropenem is a broad-spectrum antimicrobial agent with excellent activity against pathogens associated with intra-abdominal infections in this population. The purpose of this study was to determine the pharmacokinetics (PK) of meropenem in young infants as a basis for optimizing dosing and minimizing adverse events. Methods: Premature and term infants <91 days old hospitalized in 24 neonatal intensive care units were studied. Limited PK sampling was performed following single and multiple doses of meropenem 20 to 30 mg/kg of body weight every 8 to 12 hours based on postnatal and gestational age at birth. Population and individual patient (Bayesian) PK parameters were estimated using NONMEM. Results: In this study, 200 infants were enrolled and received the study drug. Of them, 188 infants with 780 plasma meropenem concentrations were analyzed. Their median (range) gestational age at birth and postnatal age at PK evaluation were 28 (23-40) weeks and 21 (1-92) days, respectively. In the final PK model, meropenem clearance was strongly associated with serum creatinine and postmenstrual age (clearance [L/h/kg] = 0.12*[(0.5/serum creatinine)**0.27]*[(postmenstrual age/32.7)**1.46]). Meropenem concentrations remained > 4 mu g/mL for 50% of the dose interval and > 2 mu g/mL for 75% of the dose interval in 96% and 92% of patients, respectively. The estimated penetration of meropenem into the cerebrospinal fluid was 70% (5-148). Conclusions: Meropenem dosing strategies based on postnatal and gestational age achieved therapeutic drug exposure in almost all infants