Explore the vast range of titles available.

In Bayesian phylogenetic analyses of genetic data, prior probability distributions need to be specified for the model parameters, including the tree. When Bayesian methods are used for molecular dating, available tree priors include those designed for species-level data, such as the pure-birth and birth–death priors, and coalescent-based priors designed for population-level data. However, molecular dating methods are frequently applied to data sets that include multiple individuals across multiple species. Such data sets violate the assumptions of both the speciation and coalescent-based tree priors, making it unclear which should be chosen and whether this choice can affect the estimation of node times. To investigate this problem, we used a simulation approach to produce data sets with different proportions of within-and between-species sampling under the multispecies coalescent model. These data sets were then analyzed under pure-birth, birth–death, constant-size coalescent, and skyline coalescent tree priors. We also explored the ability of Bayesian model testing to select the best-performing priors. We confirmed the applicability of our results to empirical data sets from cetaceans, phocids, and coregonid whitefish. Estimates of node times were generally robust to the choice of tree prior, but some combinations of tree priors and sampling schemes led to large differences in the age estimates. In particular, the pure-birth tree prior frequently led to inaccurate estimates for data sets containing a mixture of inter- and intraspecific sampling, whereas the birth–death and skyline coalescent priors produced stable results across all scenarios. Model testing provided an adequate means of rejecting inappropriate tree priors. Our results suggest that tree priors do not strongly affect Bayesian molecular dating results in most cases, even when severely misspecified. However, the choice of tree prior can be significant for the accuracy of dating results in the case of data sets with mixed inter- and intraspecies sampling.

The application of deep learning, specifically deep convolutional neural networks (DCNNs), to the classification of remotely-sensed imagery of natural landscapes has the potential to greatly assist in the analysis and interpretation of geomorphic processes. However, the general usefulness of deep learning applied to conventional photographic imagery at a landscape scale is, at yet, largely unproven. If DCNN-based image classification is to gain wider application and acceptance within the geoscience community, demonstrable successes need to be coupled with accessible tools to retrain deep neural networks to discriminate landforms and land uses in landscape imagery. Here, we present an efficient approach to train/apply DCNNs with/on sets of photographic images, using a powerful graphical method called a conditional random field (CRF), to generate DCNN training and testing data using minimal manual supervision. We apply the method to several sets of images of natural landscapes, acquired from satellites, aircraft, unmanned aerial vehicles, and fixed camera installations. We synthesize our findings to examine the general effectiveness of transfer learning to landscape-scale image classification. Finally, we show how DCNN predictions on small regions of images might be used in conjunction with a CRF for highly accurate pixel-level classification of images.

A number of studies have highlighted physiological data from the first surge in critically unwell Covid-19 patients but there is a paucity of data describing emerging variants of SARS-CoV-2, such as B.1.1.7. We compared ventilatory parameters, biochemical and physiological data and mortality between the first and second COVID-19 surges in the United Kingdom, where distinct variants of SARS-CoV-2 were the dominant stain. We performed a retrospective cohort study investigating critically unwell patients admitted with COVID-19 across three tertiary regional ICUs in London, UK. Of 1782 adult ICU patients screened, 330 intubated and ventilated patients diagnosed with COVID-19 were included. In the second wave where B.1.1.7 variant was the dominant strain, patients were had increased severity of ARDS whilst compliance was greater (p<0.05) and d-dimer lower. The 28-day mortality was not statistically significant (1st wave: 42.2% vs 2nd wave: 39.8%). However, when adjusted for key covariates, the hazard ratio for 28-day mortality in those patients with B.1.1.7 was 3.79 (CI 1.04–13.8; p = 0.043) compared to the original strain. During the second surge in the UK, where the COVID-19 variant B.1.1.7 was most prevalent, significantly more patients presented to critical care with severe ARDS. Furthermore, mortality risk was significantly greater in our ICU population during the second wave of the pandemic in those patients with B.1.1.7. As ICUs are experiencing further waves (particularly by the delta (B.1.617.2) variant), we highlight the urgent need for prospective studies describing immunological and pathophysiological differences across novel emerging variants.

Malignant pleural mesothelioma incidence continues to rise, with few available evidence-based therapeutic options. Results of previous non-randomised studies suggested that video-assisted thoracoscopic partial pleurectomy (VAT-PP) might improve symptom control and survival. We aimed to compare efficacy in terms of overall survival, and cost, of VAT-PP and talc pleurodesis in patients with malignant pleural mesothelioma. We undertook an open-label, parallel-group, randomised, controlled trial in patients aged 18 years or older with any subtype of confirmed or suspected mesothelioma with pleural effusion, recruited from 12 hospitals in the UK. Eligible patients were randomly assigned (1:1) to either VAT-PP or talc pleurodesis by computer-generated random numbers, stratified by European Organisation for Research and Treatment of Cancer risk category (high vs low). The primary outcome was overall survival at 1 year, analysed by intention to treat (all patients randomly assigned to a treatment group with a final diagnosis of mesothelioma). This trial is registered with ClinicalTrials.gov, number NCT00821860. Between Oct 24, 2003, and Jan 24, 2012, we randomly assigned 196 patients, of whom 175 (88 assigned to talc pleurodesis, 87 assigned to VAT-PP) had confirmed mesothelioma. Overall survival at 1 year was 52% (95% CI 41–62) in the VAT-PP group and 57% (46–66) in the talc pleurodesis group (hazard ratio 1·04 [95% CI 0·76–1·42]; p=0·81). Surgical complications were significantly more common after VAT-PP than after talc pleurodesis, occurring in 24 (31%) of 78 patients who completed VAT-PP versus ten (14%) of 73 patients who completed talc pleurodesis (p=0·019), as were respiratory complications (19 [24%] vs 11 [15%]; p=0·22) and air-leak beyond 10 days (five [6%] vs one [1%]; p=0·21), although not significantly so. Median hospital stay was longer at 7 days (IQR 5–11) in patients who received VAT-PP compared with 3 days (2–5) for those who received talc pleurodesis (p<0·0001). VAT-PP is not recommended to improve overall survival in patients with pleural effusion due to malignant pleural mesothelioma, and talc pleurodesis might be preferable considering the fewer complications and shorter hospital stay associated with this treatment. BUPA Foundation.

Coastal erosion outpaces land generation along many of the world’s deltas and a significant percentage of shorelines, and human-caused alterations to coastal sediment budgets can be important drivers of this erosion. For sediment-starved and erosion-prone coasts, large-scale enhancement of sediment supply may be an important, but poorly understood, management option. Here we provide new topographic measurements that show patterns and trends of beach accretion following the restoration of sediment supply from a massive dam removal project. River sediment was initially deposited in intertidal-to-subtidal deltaic lobes, and this sediment was reworked by ocean waves into subaerial river mouth bars over time scales of several months. These river mouth bars welded to the shoreline and then initiated waves of sediment accretion along adjacent upcoast and downcoast beaches. Although the downcoast shoreline has a high wave-angle setting, the sedimentation waves straightened the downcoast shoreline rather than forming self-organized quasi-periodic instabilities, which suggests that simple coastal evolution theory did not hold under these conditions. Combined with other mega-nourishment projects, these findings provide new understanding of littoral responses to the restoration of sediment supplies.

Human impacts from dams reduce river sediment fluxes and are primary causes of coastal erosion worldwide. Here we provide new satellite-derived shoreline observation techniques to examine beach area trends across the diverse coastal settings of California. Contrary to global trends, these data reveal that the most heavily urbanized and dammed region of southern California experienced net beach growth of over 2 million m 2 during 1984-2024. While several beaches experienced severe erosion, overall widening is explained by sufficient sediment supply and concentrated widening from longshore transport captured at coastal structures and in littoral convergence zones. These results indicate that adequate sediment sources exist in this human-modified landscape to mitigate coastal erosion, but that this sediment is not effectively distributed to vulnerable beaches. This highlights the critical role that longshore sediment transport plays in long-term beach trends and illuminates management opportunities for coastal sustainability at the regional scale. This work highlights how changes to beaches are related to sand movement and human impacts to the coast and illuminates opportunities for sand management to resolve shoreline erosion and enhance beach sustainability.

Sediment pulses can cause widespread, complex changes to rivers and coastal regions. Quantifying landscape response to sediment-supply changes is a long-standing problem in geomorphology, but the unanticipated nature of most sediment pulses rarely allows for detailed measurement of associated landscape processes and evolution. The intentional removal of two large dams on the Elwha River (Washington, USA) exposed ~30 Mt of impounded sediment to fluvial erosion, presenting a unique opportunity to quantify source-to-sink river and coastal responses to a massive sediment-source perturbation. Here we evaluate geomorphic evolution during and after the sediment pulse, presenting a 5-year sediment budget and morphodynamic analysis of the Elwha River and its delta. Approximately 65% of the sediment was eroded, of which only ~10% was deposited in the fluvial system. This restored fluvial supply of sand, gravel, and wood substantially changed the channel morphology. The remaining ~90% of the released sediment was transported to the coast, causing ~60 ha of delta growth. Although metrics of geomorphic change did not follow simple time-coherent paths, many signals peaked 1–2 years after the start of dam removal, indicating combined impulse and step-change disturbance responses.

Background An accurate timescale of evolutionary history is essential to testing hypotheses about the influence of historical events and processes, and the timescale for evolution is increasingly derived from analysis of DNA sequences. But variation in the rate of molecular evolution complicates the inference of time from DNA. Evidence is growing for numerous factors, such as life history and habitat, that are linked both to the molecular processes of mutation and fixation and to rates of macroevolutionary diversification. However, the most widely used methods rely on idealised models of rate variation, such as the uncorrelated and autocorrelated clocks, and molecular dating methods are rarely tested against complex models of rate change. One relationship that is not accounted for in molecular dating is the potential for interaction between molecular substitution rates and speciation, a relationship that has been supported by empirical studies in a growing number of taxa. If these relationships are as widespread as current evidence suggests, they may have a significant influence on molecular dates. Results We simulate phylogenies and molecular sequences under three different realistic rate variation models—one in which speciation rates and substitution rates both vary but are unlinked, one in which they covary continuously and one punctuated model in which molecular change is concentrated in speciation events, using empirical case studies to parameterise realistic simulations. We test three commonly used “relaxed clock” molecular dating methods against these realistic simulations to explore the degree of error in molecular dates under each model. We find average divergence time inference errors ranging from 12% of node age for the unlinked model when reconstructed under an uncorrelated rate prior using BEAST 2, to up to 91% when sequences evolved under the punctuated model are reconstructed under an autocorrelated prior using PAML. Conclusions We demonstrate the potential for substantial errors in molecular dates when both speciation rates and substitution rates vary between lineages. This study highlights the need for tests of molecular dating methods against realistic models of rate variation generated from empirical parameters and known relationships.