Mitogenomics supports an unexpected taxonomic relationship for the extinct diving duck Chendytes lawi and definitively places the extinct Labrador Duck

Chendytes lawi, an extinct flightless diving anseriform from coastal California, was traditionally classified as a sea duck, tribe Mergini, based on similarities in osteological characters. We recover and analyze mitochondrial genomes of C. lawi and five additional Mergini species, including the extinct Labrador Duck, Camptorhyncus labradorius. Despite its diving morphology, C. lawi is reconstructed as an ancient relictual lineage basal to the dabbling ducks (tribe Anatini), revealing an additional example of convergent evolution of characters related to feeding behavior among ducks. The Labrador Duck is sister to Steller’s Eider which may provide insights into the evolution and ecology of this poorly known extinct species. Our results demonstrate that inclusion of full length mitogenomes, from taxonomically distributed ancient and modern sources can improve phylogeny reconstruction of groups previously assessed with shorter single-gene mitochondrial sequences

The Radio Sky at Meter Wavelengths: m-Mode Analysis Imaging with the Owens Valley Long Wavelength Array

A host of new low-frequency radio telescopes seek to measure the 21-cm transition of neutral hydrogen from the early universe. These telescopes have the potential to directly probe star and galaxy formation at redshifts $20 \gtrsim z \gtrsim 7$, but are limited by the dynamic range they can achieve against foreground sources of low-frequency radio emission. Consequently, there is a growing demand for modern, high-fidelity maps of the sky at frequencies below 200 MHz for use in foreground modeling and removal. We describe a new widefield imaging technique for drift-scanning interferometers, Tikhonov-regularized $m$-mode analysis imaging. This technique constructs images of the entire sky in a single synthesis imaging step with exact treatment of widefield effects. We describe how the CLEAN algorithm can be adapted to deconvolve maps generated by $m$-mode analysis imaging. We demonstrate Tikhonov-regularized $m$-mode analysis imaging using the Owens Valley Long Wavelength Array (OVRO-LWA) by generating 8 new maps of the sky north of $\delta=-30^\circ$ with 15 arcmin angular resolution, at frequencies evenly spaced between 36.528 MHz and 73.152 MHz, and $\sim$800 mJy/beam thermal noise. These maps are a 10-fold improvement in angular resolution over existing full-sky maps at comparable frequencies, which have angular resolutions $\ge 2^\circ$. Each map is constructed exclusively from interferometric observations and does not represent the globally averaged sky brightness. Future improvements will incorporate total power radiometry, improved thermal noise, and improved angular resolution -- due to the planned expansion of the OVRO-LWA to 2.6 km baselines. These maps serve as a first step on the path to the use of more sophisticated foreground filters in 21-cm cosmology incorporating the measured angular and frequency structure of all foreground contaminants.Comment: 27 pages, 18 figure

Identification guide to the heterobranch sea slugs (Mollusca: Gastropoda) from Bocas del Toro, Panama

The Bocas del Toro Archipelago is located off the Caribbean coast of Panama. Until now, only 19 species of heterobranch sea slugs have been formally reported from this area; this number constitutes a fraction of total diversity in the Caribbean region. The Bocas del Toro Archipelago is located off the Caribbean coast of Panama. Until now, only 19 species of heterobranch sea slugs have been formally reported from this area; this number constitutes a fraction of total diversity in the Caribbean region. This increase in known diversity strongly suggests that the distribution of species within the Caribbean is still poorly known and species ranges may need to be modified as more surveys are conducted.https://doi.org/10.1186/s41200-016-0048-

The Radio Sky at Meter Wavelengths: m-mode Analysis Imaging with the OVRO-LWA

A host of new low-frequency radio telescopes seek to measure the 21 cm transition of neutral hydrogen from the early universe. These telescopes have the potential to directly probe star and galaxy formation at redshifts 20 ≳ z ≳ 7 but are limited by the dynamic range they can achieve against foreground sources of low-frequency radio emission. Consequently, there is a growing demand for modern, high-fidelity maps of the sky at frequencies below 200 MHz for use in foreground modeling and removal. We describe a new wide-field imaging technique for drift-scanning interferometers: Tikhonov-regularized m-mode analysis imaging. This technique constructs images of the entire sky in a single synthesis imaging step with exact treatment of wide-field effects. We describe how the CLEAN algorithm can be adapted to deconvolve maps generated by m-mode analysis imaging. We demonstrate Tikhonov-regularized m-mode analysis imaging using the Owens Valley Radio Observatory Long Wavelength Array (OVRO-LWA) by generating eight new maps of the sky north of δ = −30° with 15' angular resolution at frequencies evenly spaced between 36.528 and 73.152 MHz and ~800 mJy beam^(−1) thermal noise. These maps are a 10-fold improvement in angular resolution over existing full-sky maps at comparable frequencies, which have angular resolutions ≥2°. Each map is constructed exclusively from interferometric observations and does not represent the globally averaged sky brightness. Future improvements will incorporate total power radiometry, improved thermal noise, and improved angular resolution due to the planned expansion of the OVRO-LWA to 2.6 km baselines. These maps serve as a first step on the path to the use of more sophisticated foreground filters in 21 cm cosmology incorporating the measured angular and frequency structure of all foreground contaminants

Glioma Through the Looking GLASS: Molecular Evolution of Diffuse Gliomas and the Glioma Longitudinal AnalySiS Consortium

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas (TCGA) and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal AnalySiS Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities, and ultimately, improved outcomes for a patient population in need

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Breaking barriers: using the behavior change wheel to develop a tailored intervention to overcome workplace inhibitors to breaking up sitting time

© The Author(s). 2019. Background: The workplace is a prominent domain for excessive sitting. The consequences of increased sitting time include adverse health outcomes such as cardiovascular disease and poor mental wellbeing. There is evidence that breaking up sitting could improve health, however, any such intervention in the workplace would need to be informed by a theoretical evidence-based framework. The aim of this study was to use the Behaviour Change Wheel (BCW) to develop a tailored intervention to break up and reduce workplace sitting in desk-based workers. Methods: The BCW guide was followed for this qualitative, pre-intervention development study. Semi-structured interviews were conducted with 25 office workers (26–59years, mean age 40.9 [SD=10.8] years; 68% female) who were purposively recruited from local council offices and a university in the East of England region. The interview questions were developed using the Theoretical Domains Framework (TDF). Transcripts were deductively analysed using the COM-B (Capability, Opportunity, Motivation – Behaviour) model of behaviour. The Behaviour Change Technique Taxonomy Version 1 (BCTv1) was thereafter used to identify possible strategies that could be used to facilitate change in sitting behaviour of office workers in a future intervention. Results: Qualitative analysis using COM-B identified that participants felt that they had the physical Capability to break up their sitting time, however, some lacked the psychological Capability in relation to the knowledge of both guidelines for sitting time and the consequences of excess sitting. Social and physical Opportunity was identified as important, such as a supportive organisational culture (social) and the need for environmental resources (physical). Motivation was highlighted as a core target for intervention, both reflective Motivation, such as beliefs about capability and intention and automatic in terms of overcoming habit through reinforcement. Seven intervention functions and three policy categories from the BCW were identified as relevant. Finally, 39 behaviour change techniques (BCTs) were identified as potential active components for an intervention to break up sitting time in the workplace. Conclusions: The TDF, COM-B model and BCW can be successfully applied through a systematic process to understand the drivers of behaviour of office workers to develop a co-created intervention that can be used to break up and decrease sitting in the workplace. Intervention designers should consider the identified BCW factors and BCTs when developing interventions to reduce and break up workplace sitting