Gilteritinib as Post-Transplant Maintenance for AML With Internal Tandem Duplication Mutation of FLT3.

PURPOSE: Allogeneic hematopoietic cell transplantation (HCT) improves outcomes for patients with AML harboring an internal tandem duplication mutation of FLT3 (FLT3-ITD) AML. These patients are routinely treated with a FLT3 inhibitor after HCT, but there is limited evidence to support this. Accordingly, we conducted a randomized trial of post-HCT maintenance with the FLT3 inhibitor gilteritinib (ClinicalTrials.gov identifier: NCT02997202) to determine if all such patients benefit or if detection of measurable residual disease (MRD) could identify those who might benefit. METHODS: Adults with FLT3-ITD AML in first remission underwent HCT and were randomly assigned to placebo or 120 mg once daily gilteritinib for 24 months after HCT. The primary end point was relapse-free survival (RFS). Secondary end points included overall survival (OS) and the effect of MRD pre- and post-HCT on RFS and OS. RESULTS: Three hundred fifty-six participants were randomly assigned post-HCT to receive gilteritinib or placebo. Although RFS was higher in the gilteritinib arm, the difference was not statistically significant (hazard ratio [HR], 0.679 [95% CI, 0.459 to 1.005]; two-sided P = .0518). However, 50.5% of participants had MRD detectable pre- or post-HCT, and, in a prespecified subgroup analysis, gilteritinib was beneficial in this population (HR, 0.515 [95% CI, 0.316 to 0.838]; P = .0065). Those without detectable MRD showed no benefit (HR, 1.213 [95% CI, 0.616 to 2.387]; P = .575). CONCLUSION: Although the overall improvement in RFS was not statistically significant, RFS was higher for participants with detectable FLT3-ITD MRD pre- or post-HCT who received gilteritinib treatment. To our knowledge, these data are among the first to support the effectiveness of MRD-based post-HCT therapy.

Equity and modeling in sustainability science: Examples and opportunities throughout the process.

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Managing nitrogen in maize production for societal gain.

Highly productive agriculture is essential to feed humanity, but agricultural practices often harm human health and the environment. Using a nitrogen (N) mass-balance model to account for N inputs and losses to the environment, along with empirical based models of yield response, we estimate the potential gains to society from improvements in nitrogen management that could reduce health and environmental costs from maize grown in the US Midwest. We find that the monetized health and environmental costs to society of current maize nitrogen management practices are six times larger than the profits earned by farmers. Air emissions of ammonia from application of synthetic fertilizer and manure are the largest source of pollution costs. We show that it is possible to reduce these costs by 85% ($21.6 billion per year, 2020$) while simultaneously increasing farmer profits. These gains come from (i) managing fertilizer ammonia emissions by changing the mix of fertilizer and manure applied, (ii) improving production efficiency by reducing fertilization rates, and (iii) halting maize production on land where health and environmental costs exceed farmer profits, namely on low-productivity land and locations in which emissions are especially harmful. Reducing ammonia emissions from changing fertilizer types-in (i)-reduces health and environmental costs by 46% ($11.7 billion). Reducing fertilization rates-in (ii)-limits nitrous oxide emissions, further reducing health and environmental costs by $9.5 billion, and halting production on 16% of maize-growing land in the Midwest-in (iii)-reduces costs by an additional $0.4 billion.

Low Mutation Load in a Supergene Underpinning Alternative Male Mating Strategies in Ruff (Calidris pugnax).

A paradox in evolutionary biology is how supergenes can maintain high fitness despite reduced effective population size, the suppression of recombination, and the expected accumulation of mutational load. The ruff supergene involves 2 rare inversion haplotypes (satellite and faeder). These are recessive lethals but with dominant effects on male mating strategies, plumage, and body size. Sequence divergence to the wild-type (independent) haplotype indicates that the inversion could be as old as 4 million years. Here, we have constructed a highly contiguous genome assembly of the inversion region for both the independent and satellite haplotypes. Based on the new data, we estimate that the recombination event(s) creating the satellite haplotype occurred only about 70,000 yr ago. Contrary to expectations for supergenes, we find no substantial expansion of repeats and only a modest mutation load on the satellite and faeder haplotypes despite high sequence divergence to the non-inverted haplotype (1.46%). The essential centromere protein N (CENPN) gene is disrupted by the inversion and is as well conserved on the inversion haplotypes as on the noninversion haplotype. These results suggest that the inversion may be much younger than previously thought. The low mutation load, despite recessive lethality, may be explained by the introgression of the inversion from a now extinct lineage.

Alert to Action: Implementing Artificial Intelligence-Driven Clinical Decision Support Tools for Sepsis.

Background: Sepsis is the leading cause of mortality among hospitalized patients in our health care system and has been the target of major international initiatives such as the Surviving Sepsis Campaign championed by the Society of Critical Care Medicine and Get Ahead of Sepsis led by the Centers for Disease Control and Prevention. Methods: Our institution has strived to improve outcomes for patients by implementing a novel suite of integrated clinical decision support tools driven by a predictive learning algorithm in the electronic health record. The tools focus on sepsis multidisciplinary care using industry-standard heuristics of interface design to enhance usability and interaction. Results: Our novel clinical decision support tools demonstrated a higher level of interaction with a higher alert-to-action ratio compared to the average of all best practice alerts used at Ochsner Health (16.46% vs 8.4% to 12.1%). Conclusion: By using intuitive design strategies that encouraged users to complete best practice alerts and team-wide visualization of clinical decisions via a checklist, our clinical decision support tools for the detection and management of sepsis represent an improvement over legacy tools, and the results of this pilot may have implications beyond sepsis alerting.

Air quality policy should quantify effects on disparities.

New tools can guide US policies to better target and reduce racial and socioeconomic disparities in air pollution exposure.

Gilteritinib in Combination With Induction and Consolidation Chemotherapy and as Maintenance Therapy: A Phase IB Study in Patients With Newly Diagnosed AML.

PURPOSE: Gilteritinib is a type 1 FLT3 inhibitor active as monotherapy for relapsed or refractory FLT3-mutated AML. We investigated the safety, tolerability, and efficacy of gilteritinib incorporated into intensive induction and consolidation chemotherapy, and as maintenance therapy for adult patients with newly diagnosed, non-favorable-risk AML. METHODS: In this phase IB study (2215-CL-0103; ClinicalTrials.gov identifier: NCT02236013), 103 participants were screened and 80 were allocated to treatment. The study was divided into four parts: dose escalation, dose expansion, investigation of alternate anthracycline and gilteritinib schedule, and continuous gilteritinib during consolidation. RESULTS: After dose escalation, 120 mg gilteritinib once daily was chosen for further study. There were 58 participants evaluable for response at this dose, 36 of whom harbored FLT3 mutations. For participants with FLT3-mutated AML, the composite complete response (CRc) rate was 89% (83% were conventional complete responses), all achieved after a single induction cycle. The median overall survival time was 46.1 months. Gilteritinib was well-tolerated in this context although the median time to count recovery during induction was approximately 40 days. Longer time-to-count recovery was associated with higher trough levels of gilteritinib, which, in turn, were associated with azole use. The recommended regimen is gilteritinib at a dose of 120 mg once daily from days 4 to 17 or 8 to 21 of a 7 + 3 induction with either idarubicin or daunorubicin and from day 1 continuously with high-dose cytarabine consolidation. Maintenance therapy with gilteritinib was well-tolerated. CONCLUSION: These results demonstrated the safety and tolerability of gilteritinib incorporated into an induction and consolidation chemotherapy regimen, and as single-agent maintenance therapy for patients with newly diagnosed FLT3-mutant AML. The data herein provide an important framework for the design of randomized trials comparing gilteritinib with other FLT3 inhibitors.

Disaster Triage Skills Training: An Introductory Virtual Simulation for Medical Students.

Background Disaster triage training equips learners with the critical skills to rapidly evaluate patients, yet few medical schools include formal triage training in their curriculum. Simulation exercises can successfully teach triage skills, but few studies have specifically evaluated online simulation to teach these skills to medical students. Aims We sought to develop and evaluate a largely asynchronous activity for senior medical students to practice their triage skills in an online format. Methods We developed an online, interactive triage exercise for fourth-year medical students. For the exercise, the student participants acted as triage officers for an emergency department (ED) at a large tertiary care center during an outbreak of a severe respiratory illness. Following the exercise, a faculty member led a debriefing session using a structured debriefing guide. Pre- and post-test educational assessments used a five-point Likert scale to capture the helpfulness of the exercise and their self-reported pre- and post-competency in triage. Change in self-reported competency was analyzed for statistical significance and effect size. Results Since May 2021, 33 senior medical students have completed this simulation and pre- and post-test educational assessments. Most students found the exercise "very" or "extremely" helpful for learning, with a mean of 4.61 (SD: ±0.67). Most students rated their pre-exercise competency as "beginner" or "developing" and their post-exercise competency as "developing" or "proficient" on a four-point rubric. The average increase in self-reported competency was 1.17 points (SD: ±0.62), yielding a statistically significant difference (p < 0.001) and large effect size (Hedges' g: 1.94). Conclusions We conclude that a virtual simulation can increase students' sense of competence in triage skills, using fewer resources than in-person simulation of disaster triage. As a next step, the simulation and the source code are publicly available for anyone to engage with the simulation or adapt it for their respective learners.

Spatiotemporal variations in retrovirus-host interactions among Darwin's finches.

Endogenous retroviruses (ERVs) are inherited remnants of retroviruses that colonized host germline over millions of years, providing a sampling of retroviral diversity across time. Here, we utilize the strength of Darwin's finches, a system synonymous with evolutionary studies, for investigating ERV history, revealing recent retrovirus-host interactions in natural populations. By mapping ERV variation across all species of Darwin's finches and comparing with outgroup species, we highlight geographical and historical patterns of retrovirus-host occurrence, utilizing the system for evaluating the extent and timing of retroviral activity in hosts undergoing adaptive radiation and colonization of new environments. We find shared ERVs among all samples indicating retrovirus-host associations pre-dating host speciation, as well as considerable ERV variation across populations of the entire Darwin's finches' radiation. Unexpected ERV variation in finch species on different islands suggests historical changes in gene flow and selection. Non-random distribution of ERVs along and between chromosomes, and across finch species, suggests association between ERV accumulation and the rapid speciation of Darwin's finches.

Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality.

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.

Phase 3 trial of gilteritinib plus azacitidine vs azacitidine for newly diagnosed FLT3mut+ AML ineligible for intensive chemotherapy.

Treatment results for patients with newly diagnosed FMS-like tyrosine kinase 3 (FLT3)-mutated (FLT3mut+) acute myeloid leukemia (AML) ineligible for intensive chemotherapy are disappointing. This multicenter, open-label, phase 3 trial randomized (2:1) untreated adults with FLT3mut+ AML ineligible for intensive induction chemotherapy to receive gilteritinib (120 mg/d orally) and azacitidine (GIL + AZA) or azacitidine (AZA) alone. The primary end point was overall survival (OS). At the interim analysis (August 26, 2020), a total of 123 patients were randomized to treatment (GIL + AZA, n = 74; AZA, n = 49). Subsequent AML therapy, including FLT3 inhibitors, was received by 20.3% (GIL + AZA) and 44.9% (AZA) of patients. Median OS was 9.82 (GIL + AZA) and 8.87 (AZA) months (hazard ratio, 0.916; 95% CI, 0.529-1.585; P = .753). The study was closed based on the protocol-specified boundary for futility. Median event-free survival was 0.03 month in both arms. Event-free survival defined by using composite complete remission (CRc) was 4.53 months for GIL + AZA and 0.03 month for AZA (hazard ratio, 0.686; 95% CI, 0.433-1.087; P = .156). CRc rates were 58.1% (GIL + AZA) and 26.5% (AZA) (difference, 31.4%; 95% CI, 13.1-49.7; P < .001). Adverse event (AE) rates were similar for GIL + AZA (100%) and AZA (95.7%); grade ≥3 AEs were 95.9% and 89.4%, respectively. Common AEs with GIL + AZA included pyrexia (47.9%) and diarrhea (38.4%). Gilteritinib steady-state trough concentrations did not differ between GIL + AZA and gilteritinib. GIL + AZA resulted in significantly higher CRc rates, although similar OS compared with AZA. Results support the safety/tolerability and clinical activity of upfront therapy with GIL + AZA in older/unfit patients with FLT3mut+ AML. This trial was registered at www.clinicaltrials.gov as #NCT02752035.

Estimating the environmental impacts of 57,000 food products.

Understanding and communicating the environmental impacts of food products is key to enabling transitions to environmentally sustainable food systems [El Bilali and Allahyari, Inf. Process. Agric. 5, 456-464 (2018)]. While previous analyses compared the impacts of food commodities such as fruits, wheat, and beef [Poore and Nemecek, Science 360, 987-992 (2018)], most food products contain numerous ingredients. However, because the amount of each ingredient in a product is often known only by the manufacturer, it has been difficult to assess their environmental impacts. Here, we develop an approach to overcome this limitation. It uses prior knowledge from ingredient lists to infer the composition of each ingredient, and then pairs this with environmental databases [Poore and Nemecek Science 360, 987-992 (2018); Gephart et al., Nature 597, 360-365 (2021)] to derive estimates of a food product's environmental impact across four indicators: greenhouse gas emissions, land use, water stress, and eutrophication potential. Using the approach on 57,000 products in the United Kingdom and Ireland shows food types have low (e.g., sugary beverages, fruits, breads), to intermediate (e.g., many desserts, pastries), to high environmental impacts (e.g., meat, fish, cheese). Incorporating NutriScore reveals more nutritious products are often more environmentally sustainable but there are exceptions to this trend, and foods consumers may view as substitutable can have markedly different impacts. Sensitivity analyses indicate the approach is robust to uncertainty in ingredient composition and in most cases sourcing. This approach provides a step toward enabling consumers, retailers, and policy makers to make informed decisions on the environmental impacts of food products.

Expansion of a retrovirus lineage in the koala genome.

Retroviruses have left their legacy in host genomes over millions of years as endogenous retroviruses (ERVs), and their structure, diversity, and prevalence provide insights into the historical dynamics of retrovirus-host interactions. In bioinformatic analyses of koala (Phascolarctos cinereus) whole-genome sequences, we identify a recently expanded ERV lineage (phaCin-ß) that is related to the New World squirrel monkey retrovirus. This ERV expansion shares many parallels with the ongoing koala retrovirus (KoRV) invasion of the koala genome, including highly similar and mostly intact sequences, and polymorphic ERV loci in the sampled koala population. The recent phaCin-ß ERV colonization of the koala genome appears to predate the current KoRV invasion, but polymorphic ERVs and divergence comparisons between these two lineages predict a currently uncharacterized, possibly still extant, phaCin-ß retrovirus. The genomics approach to ERV-guided discovery of novel retroviruses in host species provides a strong incentive to search for phaCin-ß retroviruses in the Australasian fauna.

Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution).

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: "Global InMAP". Global InMAP uses a variable resolution grid, with horizontal grid cell widths ranging from 500 km in remote locations to 4km in urban locations. We evaluate Global InMAP performance against both measurements and a state-of-the-science chemical transport model, GEOS-Chem. Against measurements, InMAP predicts total PM2.5 concentrations with a normalized mean error of 62%, compared to 41% for GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%-121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6-8.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate policy assessment worldwide, providing a screening tool for reducing air pollution-related deaths where they occur most.

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Molecular profile of FLT3-mutated relapsed/refractory patients with AML in the phase 3 ADMIRAL study of gilteritinib.

The phase 3 Study of ASP2215 Versus Salvage Chemotherapy in Patients With Relapsed or Refractory Acute Myeloid Leukemia (AML) With FMS-like Tyrosine Kinase (FLT3) Mutation (ADMIRAL) trial demonstrated the superiority of the FLT3 inhibitor, gilteritinib, to salvage chemotherapy (SC) in patients with FLT3-mutated relapsed or refractory (R/R) AML. Baseline comutations, FLT3-internal tandem duplication (ITD) allelic ratio and length, and treatment-emergent mutations were analyzed in patients in the ADMIRAL trial. Baseline comutations were grouped according to gene subgroups (DNA methylation/hydroxymethylation, transcription, chromatin-spliceosome, receptor tyrosine kinase-Ras signaling, TP53-aneuploidy, NPM1, DNMT3A, DNMT3A/NPM1, WT-1, and IDH1/IDH2). Across all but 1 gene subgroup (TP53-aneuploidy), higher pretransplant response rates and a trend toward longer overall survival were observed with gilteritinib vs SC. Patients with DNMT3A/NPM1 comutations who received gilteritinib had the most favorable outcomes of any molecular subgroup analyzed. Survival outcomes with gilteritinib were not adversely affected by FLT3-ITD allelic ratio, FLT3-ITD length, or multiple FLT3-ITD mutations. Among patients who relapsed on gilteritinib, Ras/mitogen-activated protein kinase (MAPK) pathway and FLT3 F691L gene mutations were the most common mutational events associated with treatment resistance. However, the occurrence of Ras/MAPK pathway gene mutations at baseline did not preclude a clinical benefit from gilteritinib. Acquisition of multiple Ras/MAPK pathway gene mutations at relapse suggests a high level of pathway reactivation is needed to overcome the gilteritinib treatment effect. These findings provide insight into the R/R AML molecular profile and the impact of FLT3 inhibitors on mutational evolution associated with treatment resistance and benefit of gilteritinib across a wide spectrum of molecular and genetic subgroups in FLT3-mutated R/R AML. This trial was registered at www.clinicaltrials.gov as #NCT02421939.

High Throughput UHPLC-MS-Based Lipidomics Using Vacuum Jacketed Columns.

Reversed-phase UHPLC-MS is extensively employed for both the profiling of biological fluids and tissues to characterize lipid dysregulation in disease and toxicological studies. With conventional LC-MS systems the chromatographic performance and throughput are limited due to dispersion from the fluidic connections as well as radial and longitudinal thermal gradients in the LC column. In this study vacuum jacketed columns (VJC), positioned at the source of the mass spectrometer, were applied to the lipidomic analysis of plasma extracts. Compared to conventional UHPLC, the VJC-based methods offered greater resolution, faster analysis, and improved peak intensity. For a 5 min VJC analysis, the peak capacity increased by 66%, peak tailing reduced by up to 34%, and the number of lipids detected increased by 30% compared to conventional UHPLC. The narrower peaks, and thus increased resolution, compared to the conventional system resulted in a 2-fold increase in peak intensity as well a significant improvement in MS and MS/MS spectral quality resulting in a 22% increase in the number of lipids identified. When applied to mouse plasma samples, reproducibility of the lipid intensities in the pooled QC ranged from 1.8-12%, with no related drift in tR observed.