Pattern and Prognostic Impact of Regional Wall Motion Abnormalities in 255 697 Men and 236 641 Women Investigated with Echocardiography

Background Regional wall motion abnormalities (WMAs) after myocardial infarction are associated with adverse remodeling and increased mortality in the short to medium term. Their long-term prognostic impact is less well understood. Methods and Results Via the National Echo Database of Australia (2000-2019), we identified normal wall motion versus WMA for each left ventricular wall among 492 338 individuals aged 61.9±17.9 years. The wall motion score index was also calculated. We then examined actual 1- and 5-year mortality, plus adjusted risk of long-term mortality according to WMA status. Overall, 39 346/255 697 men (15.4%) and 17 834/236 641 women (7.5%) had a WMA. The likelihood of a WMA was associated with increasing age and greater systolic/diastolic dysfunction. A defect in the inferior versus anterior wall was the most and least common WMA in men (8.0% and 2.5%) and women (3.3% and 1.1%), respectively. Any WMA increased 5-year mortality from 17.5% to 29.7% in men and from 14.9% to 30.8% in women. Known myocardial infarction (hazard ratio [HR], 0.86 [95% CI, 0.80-0.93]) or revascularization (HR, 0.87 [95% CI, 0.82-0.92]) was independently associated with a better prognosis, whereas men (1.22-fold increase) and those with greater systolic/diastolic dysfunction had a worse prognosis. Among those with any WMA, apical (HR, 1.08 [95% CI, 1.02-1.13]) or inferior (HR, 1.09 [95% CI, 1.04-1.15]) akinesis, dyskinesis or aneurysm, or a wall motion score index >3.0 conveyed the worst prognosis. Conclusions In a large real-world clinical cohort, twice as many men as women have a WMA, with inferior WMA the most common. Any WMA confers a poor prognosis, especially inferoapical akinesis/dyskinesis/aneurysm.

Assessing opportunities and inequities in undergraduate ecological forecasting education

Conducting ecological research in a way that addresses complex, real-world problems requires a diverse, interdisciplinary and quantitatively trained ecology and environmental science workforce. This begins with equitably training students in ecology, interdisciplinary science, and quantitative skills at the undergraduate level. Understanding the current undergraduate curriculum landscape in ecology and environmental sciences allows for targeted interventions to improve equitable educational opportunities. Ecological forecasting is a sub-discipline of ecology with roots in interdisciplinary and quantitative science. We use ecological forecasting to show how ecology and environmental science undergraduate curriculum could be evaluated and ultimately restructured to address the needs of the 21^st century workforce. To characterize the current state of ecological forecasting education, we compiled existing resources for teaching and learning ecological forecasting at three curriculum levels: online resources; US university courses on ecological forecasting; and US university courses on topics related to ecological forecasting. We found persistent patterns (1) in what topics are taught to US undergraduate students at each of the curriculum levels; and (2) in the accessibility of resources, in terms of course availability at higher education institutions in the United States. We developed and implemented programs to increase the accessibility and comprehensiveness of ecological forecasting undergraduate education, including initiatives to engage specifically with Native American undergraduates and online resources for learning quantitative concepts at the undergraduate level. Such steps enhance the capacity of ecological forecasting to be more inclusive to undergraduate students from diverse backgrounds and expose more students to quantitative training.

Real-time visualization of phagosomal pH manipulation by Cryptococcus neoformans in an immune signal-dependent way

Understanding of how intracellular pathogens survive in their host cells is important to improve management of their diseases. This has been fruitful for intracellular bacteria, but it is an understudied area in fungal pathogens. Here we start elucidating and characterizing the strategies used by one of the commonest fungal pathogens, Cryptococcus neoformans, to survive intracellularly. The ability of the fungus to survive inside host cells is one of the main drivers of disease progression, yet it is unclear whether C. neoformans resides in a fully acidified, partially acidic, or neutral phagosome. Using a dye that only fluoresce under acidic conditions to stain C. neoformans, a hypha-defective Candida albicans mutant, and the nonpathogenic Saccharomyces cerevisiae, we characterized the fungal behaviors in infected macrophages by live microscopy. The main behavior in the C. albicans mutant strain and S. cerevisiae-phagosomes was rapid acidification after internalization, which remained for the duration of the imaging. In contrast, a significant number of C. neoformans-phagosomes exhibited alternative behaviors distinct from the normal phagosomal maturation: some phagosomes acidified with subsequent loss of acidification, and other phagosomes never acidified. Moreover, the frequency of these behaviors was affected by the immune status of the host cell. We applied the same technique to a flow cytometry analysis and found that a substantial percentage of C. neoformans-phagosomes showed impaired acidification, whereas almost 100% of the S. cerevisiae-phagosomes acidify. Lastly, using a membrane-damage reporter, we show phagosome permeabilization correlates with acidification alterations, but it is not the only strategy that C. neoformans uses to manipulate phagosomal acidification. The different behaviors described here provide an explanation to the confounding literature regarding cryptococcal-phagosome acidification and the methods can be applied to study other intracellular fungal pathogens.

MAPPER: An Open-Source, High-Dimensional Image Analysis Pipeline Unmasks Differential Regulation of Drosophila Wing Features

Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful genetic model for studying the underlying genetics for a broad range of cellular and developmental processes, are limited in speed, precision, and functional versatility. To expand on the utility of the wing as a phenotypic screening system, we developed MAPPER, an automated machine learning-based pipeline that quantifies high-dimensional phenotypic signatures, with each dimension quantifying a unique morphological feature of the Drosophila wing. MAPPER magnifies the power of Drosophila phenomics by rapidly quantifying subtle phenotypic differences in sample populations. We benchmarked MAPPER’s accuracy and precision in replicating manual measurements to demonstrate its widespread utility. The morphological features extracted using MAPPER reveal variable sexual dimorphism across Drosophila species and unique underlying sex-specific differences in morphogen signaling in male and female wings. Moreover, the length of the proximal-distal axis across the species and sexes shows a conserved scaling relationship with respect to the wing size. In sum, MAPPER is an open-source tool for rapid, high-dimensional analysis of large imaging datasets. These high-content phenomic capabilities enable rigorous and systematic identification of genotype-to-phenotype relationships in a broad range of screening and drug testing applications and amplify the potential power of multimodal genomic approaches.