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The inference of ploidy levels from genomic data is important to understand molecular mechanisms underpinning genome evolution. However, current methods based on allele frequency and sequencing depth variation do not have power to infer ploidy levels at low- and mid-depth sequencing data, as they do not account for data uncertainty. Here we introduce HMMploidy, a novel tool that leverages the information from multiple samples and combines the information from sequencing depth and genotype likelihoods. We demonstrate that HMMploidy outperforms existing methods in most tested scenarios, especially at low-depth with large sample size. We apply HMMploidy to sequencing data from the pathogenic fungus Cryptococcus neoformans and retrieve pervasive patterns of aneuploidy, even when artificially downsampling the sequencing data. We envisage that HMMploidy will have wide applicability to low-depth sequencing data from polyploid and aneuploid species.

We explored the impacts of a mathematics prerequisite on student success in Introductory Biology, focusing on students historically underserved in science, technology, engineering, and mathematics (STEM). Specifically, we studied Introductory Biology student outcomes 5 years before and 6 years after adding the prerequisite. Students who had not previously passed Intermediate Algebra had a 54.91% chance of passing Introductory Biology, compared with a ??69.25% chance for students who had passed this math course. Furthermore, we found a disproportionate benefit of passing the math course for Pell Grant recipients. When considering pre- versus post-prerequisite terms of Introductory Biology, we found pass rates were significantly higher after the mathematics prerequisite was required, but grades were not. After the mathematics prerequisite, enrollments in Introductory Biology temporarily decreased in comparison to a similar chemistry course and the college's overall enrollments, a potential cost to students. Pell Grant recipients and women took Introductory Biology at the same rate as before, and contrary to our hypothesis, we saw the proportion of persons excluded due to ethnicity or race (PEER) students enrolled in Introductory Biology was higher after the implementation. This study provides a model for assessing prerequisites in a local context and contributes evidence that mathematical prerequisites can benefit students.

Makerspace tools and technologies are becoming increasingly popular in K-12 educational settings. While makerspace education has the potential to democratize educational spaces, the integration of these new technologies into the classroom is not trivial. In this paper, we analyze a university-based makerspace apprenticeship program for pre-service teachers to learn makerspace tools and technologies for use in their future classrooms. We demonstrate how apprenticeship in this community of practice led to increased confidence in maker tools and technologies and a mindset toward learning in makerspaces as playful, collaborative, and iterative. We found that pre-service teachers require greater opportunities to see students engaged in making in elementary classrooms. We end with recommendations for supporting pre-service teachers to adopt making for their future classrooms.

Storytelling can stimulate learning by delivering scientific content within a narrative that increases comprehension and engagement. In this article I describe the coevolutionary arms race between toxic newts and predatory garter snakes. This engaging story centers on the use of a deadly neurotoxin called tetrodotoxin (TTX) as an antipredator defense. Some species of newts contain TTX in their tissues, but resistance to TTX has developed through convergent evolution in garter snakes and other species. TTX resistance results from mutated voltage-gated sodium channels. These channels, whether TTX resistant or not, are found in all animals and are vital to the function of nervous and muscle tissues. Through reciprocal selection, coevolution has created phenotypic matching between toxic newts and TTX-resistant garter snakes across their range in the western United States. In other words, as newts became more poisonous, garter snakes became more resistant. These results and the scientific process behind them are discussed in detail. This story can be used by educators to provide a unifying and engaging backdrop as students learn multiple aspects of biology, such as protein structure, genetics, phylogenetics, electrical signaling, evolution, and the process of science.

Outbreaks of emerging infectious diseases are influenced by local biotic and abiotic factors, with host declines occurring when conditions favour the pathogen. Deterioration in the population of the micro-endemic Tanzanian Kihansi spray toad (Nectophrynoides asperginis) occurred after the construction of a hydropower dam, implicating habitat modification in this species decline. Population recovery followed habitat augmentation; however, a subsequent outbreak of chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd) led to the spray toad's extinction in the wild. We show using spatiotemporal surveillance and mitogenome assembly of Bd from archived toad mortalities that the outbreak was caused by invasion of the BdCAPE lineage and not the panzootic lineage BdGPL. Molecular dating reveals an emergence of BdCAPE across southern Africa overlapping with the timing of the spray toad's extinction. That our post-outbreak surveillance of co-occurring amphibian species in the Udzungwa Mountains shows widespread infection by BdCAPE yet no signs of ill-health or decline suggests these other species can tolerate Bd when environments are stable. We conclude that, despite transient success in mitigating the impact caused by dams' construction, invasion by BdCAPE caused the ultimate die-off that led to the extinction of the Kihansi spray toad. [ABSTRACT FROM AUTHOR]

Metacognition and self-regulated learning are skills that contribute to student success, but few studies have examined these topics within a community college context. We addressed this lack of understanding by asking community college biology students to metacognitively reflect on their learning strategies. We took a novel approach in our analysis by investigating how learning strategies potentially differed based on race, age, gender, and final course grade. With some exceptions, we found little evidence to suggest that such differences existed. Notably, we found that learning strategies did not differ between high-achieving and low-achieving students, which contradicts previous studies. We offer several possible explanations for these preliminary results, which include misrepresentation by students in their reflections, external and internal barriers to studying, potential flaws in our survey instrument, and students not effectively using learning strategies. We suggest replication of this study with methodological changes to further investigate any potential differences that may exist among these groups of students. Our research is an example of how classroom action research can provide insight into how students learn, which empowers us to make evidence-based changes in our teaching.

Percentage changes greater than 100% are frequently used in consumer contexts; for example, a cordless vacuum cleaner may boast "125% longer runtime" compared to competitors. Via six studies (n  = 2,395) and 11 supplementary studies (n  = 3,249), the current research shows that consumers systematically underestimate the magnitude of percentage changes greater than 100%. Specifically, many consumers apply the relative size usage (e.g. "125% of," equivalent to 25% more) instead of the appropriate relative change (e.g. "125% more," equivalent to 100% more + 25% more), which leads them to be off by exactly 100% in their magnitude estimates. The rate of bias decreases when the difference between these two usages is emphasized. The Off by 100% bias occurs across a variety of consumer contexts, influencing behavioral intentions and incentive-compatible choice. The findings make theoretical contributions to research on processing of percentages, probability versus frequency formats, and magnitude judgments. Finally, understanding how different presentation formats of the same information can lead to different magnitude judgments enables marketers and policymakers to ensure more effective communication. [ABSTRACT FROM AUTHOR]

Shape‐conveying line drawings generated from 3D models normally create closed regions in image space. These lines and regions can be stylized to mimic various artistic styles, but for complex objects, the extracted topology is unnecessarily dense, leading to unappealing and unnatural results under stylization. Prior works typically simplify line drawings without considering the regions between them, and lines and regions are stylized separately, then composited together, resulting in unintended inconsistencies. We present a method for joint simplification of lines and regions simultaneously that penalizes large changes to region structure, while keeping regions closed. This feature enables region stylization that remains consistent with the outline curves and underlying 3D geometry. [ABSTRACT FROM AUTHOR]

Health services research is underpinned by partnerships between researchers and health services. Partnership-based research is increasingly needed to deal with the uncertainty of global pandemics, climate change induced severe weather events, and other disruptions. To date there is very little data on what has happened to health services research during the COVID-19 pandemic. This paper describes the establishment of an Australian multistate Decolonising Practice research project and charts its adaptation in the face of disruptions. The project used cooperative inquiry method, where partner health services contribute as coresearchers. When the COVID-19 pandemic hit, data collection needed to be immediately paused, and when restrictions started to lift, all research plans had to be renegotiated with services. Adapting the research surfaced health service, university, and staffing considerations. Our experience suggests that cooperative inquiry was invaluable in successfully navigating this uncertainty and negotiating the continuance of the research. Flexible, participatory methods such as cooperative inquiry will continue to be vital for successful health services research predicated on partnerships between researchers and health services into the future. They are also crucial for understanding local context and health services priorities and ways of working, and for decolonising Indigenous health research. [ABSTRACT FROM AUTHOR]

Background Carbapenem-resistant Enterobacterales (CRE) are an urgent public health threat in the United States. Objective Describe the clinical and molecular epidemiology of CRE in a multicenter pediatric cohort. Methods CRACKLE-1 and CRACKLE-2 are prospective cohort studies with consecutive enrollment of hospitalized patients with CRE infection or colonization between 24 December 2011 and 31 August 2017. Patients younger than age 18 years and enrolled in the CRACKLE studies were included in this analysis. Clinical data were obtained from the electronic health record. Carbapenemase genes were detected using polymerase chain reaction and whole-genome sequencing. Results Fifty-one children were identified at 18 healthcare system study sites representing all U.S. census regions. The median age was 8 months, with 67% younger than age 2 years. Median number of days from admission to culture collection was 11. Seventy-three percent of patients had required intensive care and 41% had a history of mechanical ventilation. More than half of children had no documented comorbidities (Q1, Q3 0, 2). Sixty-seven percent previously received antibiotics during their hospitalization. The most common species isolated were Enterobacter species (41%), Klebsiella pneumoniae (27%), and Escherichia coli (20%). Carbapenemase genes were detected in 29% of isolates tested, which was lower than previously described in adults from this cohort (61%). Thirty-four patients were empirically treated on the date of culture collection, but only 6 received an antibiotic to which the CRE isolate was confirmed susceptible in vitro. Thirty-day mortality was 13.7%. Conclusions CRE infection or colonization in U.S. children was geographically widespread, predominantly affected children younger than age 2 years, associated with significant mortality, and less commonly caused by carbapenemase-producing strains than in adults. [ABSTRACT FROM AUTHOR]

The amphibian‐infecting chytrid fungus, Batrachochytrium dendrobatidis (Bd), is widespread throughout Africa and is linked to declines of populations and species across the continent. While it is well established that the lineage of Bd encodes traits which determine disease severity, knowledge around how lineages are distributed according to environmental envelope is unclear. We here studied the distribution of Bd in South Africa based on the two lineages found, BdGPL and BdCAPE, in terms of their genome and environmental envelope statistically associated with their distribution. We used Bd surveillance data from published studies, as well as data collected during fieldwork from across South Africa, Lesotho, and eSwatini with samples collected along a transect spanning most of South Africa from Lesotho to the west coast. We utilized lineage‐typing qPCR to resolve the spatial distribution of BdGPL and BdCAPE across South Africa and used the resulting surveillance data to create a predictive ecological niche model for Bd lineages in South Africa. Phylogenomic analyses were performed on isolates sourced from across the transect. We show that BdGPL demonstrates a strong isolation by distance suggestive of stepping‐stone dispersal, while BdCAPE showed two distinct clusters within their genomic structure that appear geographically and temporally clustered, indicating two separate invasions. Our predictive niche model revealed that the two lineages tended to occur in different ecotypes; BdGPL was associated with lower altitude, arid regions while BdCAPE occurred across cooler, higher altitude environs. Niche predictions identified a zone of lineage contact, where genomics identified inter‐lineage recombinants. We argue that this zone of recombination should be prioritized for disease surveillance as it is a potential hotspot for the evolution of variants of amphibian chytrid with novel traits that may be epidemiologically relevant. [ABSTRACT FROM AUTHOR]

Context Thyroid nodule ultrasound-based risk stratification schemas rely on the presence of high-risk sonographic features. However, some malignant thyroid nodules have benign appearance on thyroid ultrasound. New methods for thyroid nodule risk assessment are needed. Objective We investigated polygenic risk score (PRS) accounting for inherited thyroid cancer risk combined with ultrasound-based analysis for improved thyroid nodule risk assessment. Methods The convolutional neural network classifier was trained on thyroid ultrasound still images and cine clips from 621 thyroid nodules. Phenome-wide association study (PheWAS) and PRS PheWAS were used to optimize PRS for distinguishing benign and malignant nodules. PRS was evaluated in 73 346 participants in the Colorado Center for Personalized Medicine Biobank. Results When the deep learning model output was combined with thyroid cancer PRS and genetic ancestry estimates, the area under the receiver operating characteristic curve (AUROC) of the benign vs malignant thyroid nodule classifier increased from 0.83 to 0.89 (DeLong, P value =.007). The combined deep learning and genetic classifier achieved a clinically relevant sensitivity of 0.95, 95% CI [0.88-0.99], specificity of 0.63 [0.55-0.70], and positive and negative predictive values of 0.47 [0.41-0.58] and 0.97 [0.92-0.99], respectively. AUROC improvement was consistent in European ancestry-stratified analysis (0.83 and 0.87 for deep learning and deep learning combined with PRS classifiers, respectively). Elevated PRS was associated with a greater risk of thyroid cancer structural disease recurrence (ordinal logistic regression, P value =.002). Conclusion Augmenting ultrasound-based risk assessment with PRS improves diagnostic accuracy. [ABSTRACT FROM AUTHOR]

This report surveys advances in deep learning‐based modelling techniques that address four different 3D indoor scene analysis tasks, as well as synthesis of 3D indoor scenes. We describe different kinds of representations for indoor scenes, various indoor scene datasets available for research in the aforementioned areas, and discuss notable works employing machine learning models for such scene modelling tasks based on these representations. Specifically, we focus on the analysis and synthesis of 3D indoor scenes. With respect to analysis, we focus on four basic scene understanding tasks – 3D object detection, 3D scene segmentation, 3D scene reconstruction and 3D scene similarity. And for synthesis, we mainly discuss neural scene synthesis works, though also highlighting model‐driven methods that allow for human‐centric, progressive scene synthesis. We identify the challenges involved in modelling scenes for these tasks and the kind of machinery that needs to be developed to adapt to the data representation, and the task setting in general. For each of these tasks, we provide a comprehensive summary of the state‐of‐the‐art works across different axes such as the choice of data representation, backbone, evaluation metric, input, output and so on, providing an organized review of the literature. Towards the end, we discuss some interesting research directions that have the potential to make a direct impact on the way users interact and engage with these virtual scene models, making them an integral part of the metaverse. [ABSTRACT FROM AUTHOR]