Accounting for variability when resurrecting dormant propagules substantiates their use in eco-evolutionary studies

There has been a steady rise in the use of dormant propagules to study biotic responses to environmental change over time. This is particularly important for organisms that strongly mediate ecosystem processes, as changes in their traits over time can provide a unique snapshot into the structure and function of ecosystems from decades to millennia in the past. Understanding sources of bias and variation is a challenge in the field of resurrection ecology, including those that arise because often-used measurements like seed germination success are imperfect indicators of propagule viability. Using a Bayesian statistical framework, we evaluated sources of variability and tested for zero-inflation and overdispersion in data from 13 germination trials of soil-stored seeds of Schoenoplectus americanus, an ecosystem engineer in coastal salt marshes in the Chesapeake Bay. We hypothesized that these two model structures align with an ecological understanding of dormancy and revival: zero-inflation could arise due to failed germinations resulting from inviability or failed attempts to break dormancy, and overdispersion could arise by failing to measure important seed traits. A model that accounted for overdispersion, but not zero-inflation, was the best fit to our data. Tetrazolium viability tests corroborated this result: most seeds that failed to germinate did so because they were inviable, not because experimental methods failed to break their dormancy. Seed viability declined exponentially with seed age and was mediated by seed provenance and experimental conditions. Our results provide a framework for accounting for and explaining variability when estimating propagule viability from soil-stored natural archives which is a key aspect of using dormant propagules in eco-evolutionary studies

Population pharmacokinetics of fluconazole in critically ill patients receiving continuous venovenous hemodiafiltration - using Monte Carlo Simulations to predict doses for specified pharmacodynamic targets

Fluconazole is a widely used antifungal agent that is extensively reabsorbed in patients with normal renal function. However, its reabsorption can be compromised in patients with acute kidney injury, thereby leading to altered fluconazole clearance and total systemic exposure. Here, we explore the pharmacokinetics of fluconazole in 10 critically ill anuric patients receiving continuous venovenous hemodiafiltration (CVVHDF). We performed Monte Carlo simulations to optimize dosing to appropriate pharmacodynamic endpoints for this population. Pharmacokinetic profiles of initial and steady-state doses of 200 mg intravenous fluconazole twice daily were obtained from plasma and CVVHDF effluent. Nonlinear mixed-effects modeling (NONMEM) was used for data analysis and to perform Monte Carlo simulations. For each dosing regimen, the free drug area under the concentration-time curve (fAUC)/MIC ratio was calculated. The percentage of patients achieving an AUC/MIC ratio greater than 25 was then compared for a range of MIC values. A two-compartment model adequately described the disposition of fluconazole in plasma. The estimate for total fluconazole clearance was 2.67 liters/h and was notably 2.3 times faster than previously reported in healthy volunteers. Of this, fluconazole clearance by the CVVHDF route (CL(CVVHDF)) represented 62% of its total systemic clearance. Furthermore, the predicted efficiency of CL(CVVHDF) decreased to 36.8% when filters were in use >48 h. Monte Carlo simulations demonstrated that a dose of 400 mg twice daily maximizes empirical treatment against fungal organisms with MIC up to 16 mg/liter. This is the first study we are aware of that uses Monte Carlo simulations to inform dosing requirements in patients where tubular reabsorption of fluconazole is probably nonexistent

Ancient DNA from lake sediments: Bridging the gap between paleoecology and genetics

<p>Abstract</p> <p>Background</p> <p>Quaternary plant ecology in much of the world has historically relied on morphological identification of macro- and microfossils from sediments of small freshwater lakes. Here, we report new protocols that reliably yield DNA sequence data from Holocene plant macrofossils and bulk lake sediment used to infer ecological change. This will allow changes in census populations, estimated from fossils and associated sediment, to be directly associated with population genetic changes.</p> <p>Results</p> <p>We successfully sequenced DNA from 64 samples (out of 126) comprised of bulk sediment and seeds, leaf fragments, budscales, and samaras extracted from Holocene lake sediments in the western Great Lakes region of North America. Overall, DNA yields were low. However, we were able to reliably amplify samples with as few as 10 copies of a short cpDNA fragment with little detectable PCR inhibition. Our success rate was highest for sediments < 2000 years old, but we were able to successfully amplify DNA from samples up to 4600 years old. DNA sequences matched the taxonomic identity of the macrofossil from which they were extracted 79% of the time. Exceptions suggest that DNA molecules from surrounding nearby sediments may permeate or adhere to macrofossils in sediments.</p> <p>Conclusions</p> <p>An ability to extract ancient DNA from Holocene sediments potentially allows exciting new insights into the genetic consequences of long-term environmental change. The low DNA copy numbers we found in fossil material and the discovery of multiple sequence variants from single macrofossil extractions highlight the need for careful experimental and laboratory protocols. Further application of these protocols should lead to better understanding of the ecological and evolutionary consequences of environmental change.</p

Forest responses to last‐millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity

Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under‐constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial‐scale hydroclimate variability, by comparing dendroclimatic and pollen‐inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model‐data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world

Integrated mutation, copy number and expression profiling in resectable non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to identify critical genes involved in non-small cell lung cancer (NSCLC) pathogenesis that may lead to a more complete understanding of this disease and identify novel molecular targets for use in the development of more effective therapies.</p> <p>Methods</p> <p>Both transcriptional and genomic profiling were performed on 69 resected NSCLC specimens and results correlated with mutational analyses and clinical data to identify genetic alterations associated with groups of interest.</p> <p>Results</p> <p>Combined analyses identified specific patterns of genetic alteration associated with adenocarcinoma vs. squamous differentiation; <it>KRAS </it>mutation; <it>TP53 </it>mutation, metastatic potential and disease recurrence and survival. Amplification of 3q was associated with mutations in <it>TP53 </it>in adenocarcinoma. A prognostic signature for disease recurrence, reflecting <it>KRAS </it>pathway activation, was validated in an independent test set.</p> <p>Conclusions</p> <p>These results may provide the first steps in identifying new predictive biomarkers and targets for novel therapies, thus improving outcomes for patients with this deadly disease.</p

Blockade of ROS production inhibits oncogenic signaling in acute myeloid leukemia and amplifies response to precision therapies

Mutations in the type III receptor tyrosine kinase FLT3 are frequent in patients with acute myeloid leukemia (AML) and are associated with a poor prognosis. AML is characterized by the overproduction of reactive oxygen species (ROS), which can induce cysteine oxidation in redox-sensitive signaling proteins. Here, we sought to characterize the specific pathways affected by ROS in AML by assessing oncogenic signaling in primary AML samples. The oxidation or phosphorylation of signaling proteins that mediate growth and proliferation was increased in samples from patient subtypes with FLT3 mutations. These samples also showed increases in the oxidation of proteins in the ROS-producing Rac/NADPH oxidase-2 (NOX2) complex. Inhibition of NOX2 increased the apoptosis of FLT3-mutant AML cells in response to FLT3 inhibitors. NOX2 inhibition also reduced the phosphorylation and cysteine oxidation of FLT3 in patient-derived xenograft mouse models, suggesting that decreased oxidative stress reduces the oncogenic signaling of FLT3. In mice grafted with FLT3 mutant AML cells, treatment with a NOX2 inhibitor reduced the number of circulating cancer cells, and combining FLT3 and NOX2 inhibitors increased survival to a greater extent than either treatment alone. Together, these data raise the possibility that combining NOX2 and FLT3 inhibitors could improve the treatment of FLT3 mutant AML

Perils of paradigm: Complexity, policy design, and the Endocrine Disruptor Screening Program

The Endocrine Disruptor Screening Program (EDSP), mandated by the United States Congress in the Food Quality Protection Act of 1996, attempts to protect public health from adverse endocrine effects of synthetic chemical compounds by establishing a new testing regime. But the complexities and uncertainties of endocrine disruption and its broader regulatory and social context all but ensure the failure of this policy. This article addresses the issues facing EDSP comprehensively and in detail, in order to move beyond the current regulatory paradigm and foster discourse on a positive role for scientists in support of EDSP's end goal: to protect public health

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Hoban_J_cinerea_Mol_Ecol_2010_Microsat_Data_Dryad

This file contains the microsatellite genotypes for 11 loci and 904 individuals, in 29 natural populations (forest) of butternut (J cinerea L) across eastern North America. These are the data referred to in the first sentence of the Results. They are data AFTER removal of hybrid individuals, identical genotypes, or individuals with too much missing data. These data are therefore the data used to calculate all statistics in the paper. The data are in GENEPOP format. The names of individuals are unique identification numbers used in our lab. The names of the loci correspond to those from Robichaud et al, and Hoban et al, as described in the Materials and Methods of the paper