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Nudibranch color diversity shares a common physical basis in guanine photonic structure ‘pixels’
No full text
Nudibranchs are well known for their bright and diverse color patterns. This coloration is typically a form of aposematism, warning predators against toxic compounds sequestered from their prey and weaponized as a form of defense. Although many of the hues in nudibranchs were thought to be of pigmentary origin, here we show, using a combination of white light and Raman microspectroscopy, that hierarchically organized micron-scale guanine multilayer structures are responsible for many of these colors. Such architectures are widespread across the dorid and aeolid groups and are responsible for a striking array of angular-independent structural colors. By using cryogenic focused ion beam (cryo-FIB) SEM tomography, we were able to access the complex 3D organization of the guanine nanoplatelets responsible for the strong blue coloration of
Chromodoris annae
. We propose that the multilayer organization of guanine platelets with varying orientations across the tissue and their micron-scale size offers a particularly effective strategy for producing diverse optical effects. The macroscopic angular independent color results from individual multilayers which we describe as “pixels”, these “pixels” reflect light at a wavelength governed by their interlayer spacing and guanine platelet thickness. The macroscopic hue can be spectrally tuned by altering the statistical distribution of pixels with each color, while the angular dependence of color can be changed through the relative orientation of the multilayer stacks and their size, allowing for a single structural motif to generate a broad palette of optical appearances.
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Research Data Supporting "Highly Disordered Nanoporous Carbons for Enhanced Energy Storage in Supercapacitors"
No full textGeographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020.
No full textWe show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2
Dynamic factor analysis for sparse and irregular longitudinal data: an application to metabolite measurements in a COVID-19 study
No full textFactor analysis (FA) can be used to identify key biomarkers in biological processes by assuming that latent biological pathways (statistically, `latent factors') drive the activity of measurable biomarkers (`observed variables'). However, biological pathways often interact, meaning that the classical FA assumption of independence between factors is questionable. Motivated by sparsely and irregularly collected longitudinal measurements of metabolites in a COVID-19 study, we propose a dynamic factor analysis model that accounts for cross-correlations between pathways via a multi-output Gaussian processes (MOGP) prior on the factor trajectories. To mitigate against overfitting caused by sparsity of longitudinal measurements, we introduce a roughness penalty upon MOGP hyperparameters and allow for non-zero mean functions. We also propose a scalable stochastic expectation maximization (StEM) algorithm that, in simulations, is both 20 times faster and provides more accurate and stable MOGP hyperparameter estimates than a previously-proposed Monte Carlo Expectation Maximisation algorithm. In the motivating COVID-19 study, our methodology identifies a kynurenine pathway that affects the clinical severity of patients with COVID-19 disease and uncovers the role of the biomarker taurine. Our R package DFA4SIL implements the proposed method
Critical minerals requirements for meeting net zero pathways in the United Kingdom
No full textCritical minerals are essential to the future decarbonisation plans of any country in a range of sectors including clean energy transition and defence. The ability for countries to secure this demand into the future is becoming a key concern of policymakers. Despite this concern, it is still unclear how much and when critical minerals will be required, as this is not routinely examined at the national level. This paper fills this gap, by estimating future national demand profiles for critical minerals, using the United Kingdom (UK) as a case study. We show that the demand for cobalt, graphite, and lithium is likely to grow the most, with annual demand growing between 7 and 15 times by 2050 from current levels. We found that, although the timing and demand growth rates for these minerals differ across net-zero pathways, the cumulative demand by 2050 is approximately the same, regardless of the pathway to net-zero. We also test the impact of changing battery chemistries in electric vehicles on the demand for critical minerals and find that a shift towards higher shares of lithium-ion- phosphate (LFP) batteries could eliminate the majority of demand for cobalt, while increasing demand for graphite by approximately 11% in 2050
BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies
No full textBackground
Microbial genome-wide association studies (GWAS) are crucial for linking genetic variation to phenotypic traits in bacteria. However, current tools often involve complex manual processing, limited scalability, and fragmented workflows, which constrain large-scale or routine bacterial GWAS.
Results
We developed BaGPipe, an automated and flexible bacterial GWAS pipeline built using Nextflow and incorporating Pyseer for association analysis. BaGPipe integrates pre-processing, statistical analysis, and downstream visualisation into a unified workflow that is reproducible and easy to deploy across diverse computational environments. BaGPipe was validated on a publicly available dataset of Streptococcus pneumoniae whole-genome sequences, and reproduced published findings with improved computational efficiency. BaGPipe was then applied to a dataset of Staphylococcus aureus whole-genome sequences, successfully identifying known and novel antibiotic resistance associations.
Conclusions
By offering an accessible, efficient, and reproducible platform, BaGPipe accelerates bacterial GWAS and facilitates deeper exploration into the genetic underpinnings of phenotypic traits. BaGPipe is freely available at https://github.com/sanger-pathogens/BaGPipe
A Survey on Unmanned Aerial Vehicles (UAVs) Communications: State-of-the-art, Existing Standards and Future Directions
No full textWith a diverse range of applications in both private and public sector, the market value of Unmanned Aerial Vehicles (UAVs) skyrocketed to 17.31 billion USD in 2024 and is expected to reach 32.95 billion USD by 2030. 3GPP considered UAVs in Release 15 and will include them in Release 18 as part of the 5G-Advanced technology. To provide smooth and safe inclusion in the current airspace, fast and reliable communications between UAVs and between ground base stations and UAVs are needed. Several research studies have been conducted, but there is no comprehensive picture of their advancements in terms of wireless communications and networking for UAVs. This survey paper provides detailed information on the current status of UAV communications and networking, including important aspects such as architectural solutions, protocols and design options related to spectrum management, resource optimization and security requirements. Efforts related to standardization and integration with different applications are also covered. The survey will help researchers and practitioners in the field of wireless communications, UAV service provision and telecommunications learn about the current state of the art and open the door to future research and development avenues in their fields
Early Radiation Therapy Response Assessment Using Multi‐Scale Photoacoustic Imaging
No full textABSTRACT
There is a critical unmet clinical need to identify biomarkers that predict and detect radiation therapy (RT) response in cancer. Using the unique capabilities of multi‐scale photoacoustic imaging (PAI) to depict tumor oxygenation and vasculature in vivo, we identified surrogate biomarkers of RT response in two human breast cancer xenograft models (MCF7 and MDA‐MB‐231), comparing hypofractionated delivery with an ablative single‐dose scheme. Mesoscopic and multispectral tomographic PAI were performed 24h pre‐RT, 24h post‐RT and at endpoint and were supported by ex vivo immunohistochemistry. MCF7 xenografts, which exhibited a denser and more mature vasculature, showed improved response to both RT schemes than MDA‐MB‐231, in terms of oxygenation, volume control and proliferation. Higher pre‐RT oxygenation and oxygen‐diffusion capacity were associated with improved outcome, consistent with the oxygen‐enhancement effect. PAI further revealed regimen‐specific vascular effects: ablative RT produced early pruning of looping vessels and superficial blood volume, while only hypofractionated RT led to a rise in intratumoral oxygenation at the endpoint in radiosensitive MCF7, indicative of reduced oxygen consumption in damaged tumor cells. We showed that PAI could capture early RT response and inform on radioresistance, thus demonstrating PAI as a promising tool to monitor the tumor vascular response to RT.</jats:p
Deconstructing the brain's moral network: dissociable functionality between the temporoparietal junction and ventro-medial prefrontal cortex.
No full textResearch has illustrated that the brain regions implicated in moral cognition comprise a robust and broadly distributed network. However, understanding how these brain regions interact and give rise to the complex interplay of cognitive processes underpinning human moral cognition is still in its infancy. We used functional magnetic resonance imaging to examine patterns of activation for 'difficult' and 'easy' moral decisions relative to matched non-moral comparators. This revealed an activation pattern consistent with a relative functional double dissociation between the temporoparietal junction (TPJ) and ventro-medial prefrontal cortex (vmPFC). Difficult moral decisions activated bilateral TPJ and deactivated the vmPFC and OFC. In contrast, easy moral decisions revealed patterns of activation in the vmPFC and deactivation in bilateral TPJ and dorsolateral PFC. Together these results suggest that moral cognition is a dynamic process implemented by a distributed network that involves interacting, yet functionally dissociable networks
Assessment of the performance of non-invasive risk models to predict incident type 2 diabetes in a Swedish population - Västerbotten Intervention Programme.
No full textAIM: We assessed the performance of non-invasive risk prediction models to predict 10-year incident type 2 diabetes in a large Swedish cohort. METHODS: Using the Västerbotten Intervention Programme (VIP) cohort, which includes serial oral glucose tolerance tests (OGTTs), we assessed discrimination (concordance (c)-statistic) and calibration (expected-to-observed probability ratio, integrated calibration index, calibration slope and plots) before and after recalibration in twelve non-invasive models. Incident diabetes cases were determined by an OGTT at a 10-year follow-up visit or through previously validated register-based cases. RESULTS: Among 91708 VIP participants, the 10-year diabetes incidence was 2.8 %. Most models had acceptable discrimination (c-statistic ≥0.70 and < 0.80). Discrimination was better in women and persons <50 years old. Eight models overestimated and four models underestimated mean absolute risk. Recalibration improved miscalibration in all models. Overall, the Framingham Personal and QDScore models' predictions were most accurate but the Framingham model included more easily obtainable variables. Most models overestimated risk in older people while no consistent pattern was observed across sexes. CONCLUSION: All models required recalibration to improve prediction accuracy. The Framingham personal model is recommended for risk predictions and will be the easiest to implement