Modeling the interactions between river morphodynamics and riparian vegetation

The study of river-riparian vegetation interactions is an important and intriguing research field in geophysics. Vegetation is an active element of the ecological dynamics of a floodplain which interacts with the fluvial processes and affects the flow field, sediment transport, and the morphology of the river. In turn, the river provides water, sediments, nutrients, and seeds to the nearby riparian vegetation, depending on the hydrological, hydraulic, and geomorphological characteristic of the stream. In the past, the study of this complex theme was approached in two different ways. On the one hand, the subject was faced from a mainly qualitative point of view by ecologists and biogeographers. Riparian vegetation dynamics and its spatial patterns have been described and demonstrated in detail, and the key role of several fluvial processes has been shown, but no mathematical models have been proposed. On the other hand, the quantitative approach to fluvial processes, which is typical of engineers, has led to the development of several morphodynamic models. However, the biological aspect has usually been neglected, and vegetation has only been considered as a static element. In recent years, different scientific communities (ranging from ecologists to biogeographers and from geomorphologists to hydrologists and fluvial engineers) have begun to collaborate and have proposed both semiquantitative and quantitative models of river-vegetation interconnections. These models demonstrate the importance of linking fluvial morphodynamics and riparian vegetation dynamics to understand the key processes that regulate a riparian environment in order to foresee the impact of anthropogenic actions and to carefully manage and rehabilitate riparian areas. In the first part of this work, we review the main interactions between rivers and riparian vegetation, and their possible modeling. In the second part, we discuss the semiquantitative and quantitative models which have been proposed to date, considering both multi- and single-thread river

A targeted sequencing panel identifies rare damaging variants in multiple genes in the cranial neural tube defect, anencephaly

Neural tube defects (NTDs) affecting the brain (anencephaly) are lethal before or at birth, whereas lower spinal defects (spina bifida) may lead to life-long neurological handicap. Collectively NTDs rank among the most common birth defects worldwide. This study focuses on anencephaly, which despite having a similar frequency to spina bifida and being the most common type of NTD observed in mouse models, has had more limited inclusion in genetic studies. A genetic influence is strongly implicated in determining risk of NTDs and a molecular diagnosis is of fundamental importance to families both in terms of understanding the origin of the condition and for managing future pregnancies. Here we used a custom panel of 191 NTD candidate genes to screen 90 patients with cranial NTDs (n=85 anencephaly and n=5 craniorachischisis) with a targeted exome sequencing platform. After filtering and comparing to our in-house control exome database (N=509), we identified 397 rare variants (MAF<1%), 21 of which were previously unreported and predicted damaging. This included 1 frameshift (PDGFRA), 2 stop-gained (MAT1A; NOS2) and 18 missense variations. Together with evidence for oligogenic inheritance, this study provides new information on the possible genetic causation of anencephaly

Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19

Background Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19.Methods For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes.Findings Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2middot97 [95% CI 1middot43-6middot27], p=0middot0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1middot89 [95% CI 1middot17-3middot20] per SD, p=0middot012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [&gt;= 6middot99] vs low [&lt;6middot99] C19-RS; hazard ratio [HR] 3middot31 [95% CI 1middot49-7middot33], p=0middot0033; and 2middot58 [1middot10-6middot05], p=0middot028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8middot24 (95% CI 2middot16-31middot36, p=0middot0019) in patients who received no dexamethasone treatment, but 2middot27 (0middot69-7middot55, p=0middot18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0middot61, p=0middot00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways.Interpretation Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. Funding Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.Copyright (c) 2022 The Author(s). Published by Elsevier Ltd.This is an Open Access article under the CC BY 4.0 license

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

Fringe effects: detecting bull trout (Salvelinus confluentus) at distributional boundaries in a montane watershed

Robust assessment and monitoring programs are critical for effective conservation, yet for many taxa we fail to understand how trade-offs in sampling design affect power to detect population trends and describe spatial patterns. We tested an occupancy-based sampling approach to evaluate design considerations for detecting watershed-scale population trends associated with juvenile bull trout (Salvelinus confluentus) distributions. Electrofishing surveys were conducted across 275 stream sites from the Prairie Creek watershed, Northwest Territories, Canada. Site-level detectability of juvenile bull trout was not uniform, and imperfect detection affected modelled occupancy probabilities most in fringe habitats near distributional boundaries in steep reaches and large streams. We show that detecting a 30% change in watershed-level occupancy ≥78% of the time as conservation guidelines suggest, may require three repeat surveys (i.e., temporal replicates) and increased spatial sampling intensity of fringe habitats. Additional sampling effort in fringe sites could be offset by sampling fewer sites in core habitats to optimize designs for detecting demographic shifts in bull trout, while still minimizing risk of non-detection for this cryptic species.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Fine-scale population structure in lake trout (<i>Salvelinus namaycush</i>) influenced by life history variation in the Husky Lakes drainage basin, Northwest Territories, Canada

Partial anadromy is common within salmonid populations, where resident and anadromous individuals interbreed and overlap in habitat use during portions of life. Deviation to this definition occurs within the Husky Lakes drainage basin (HLDB), Northwest Territories, where freshwater resident, semi-anadromous, and brackish-water resident lake trout (Salvelinus namaycush) life history types are documented. In this study, microsatellite DNA variation was assayed to evaluate genetic structuring among life history types from the HLDB and adjacent lower Mackenzie River system. Significant differentiation was resolved among most locations and life histories (global FST= 0.192). Brackish-water residents were differentiated from all locations and life histories, including sympatric semi-anadromous individuals, providing evidence for genetically fixed strategies. Also, this provides the first evidence of breeding partial migration in salmonids using brackish-water environments, where brackish-water residents and semi-anadromous migrants interact during the nonbreeding season, but the latter migrate elsewhere to spawn. Alternatively, the lack of genetic differentiation between semi-anadromous and Sitidgi Lake residents suggests conditional mating tactics may also influence partial anadromy. This work provides novel insights into partial anadromy in Arctic salmonids and expands our knowledge of biodiversity in this region.</jats:p