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Sub-Saharan Africa is under-represented in global biodiversity datasets, particularly regarding the impact of land use on species population abundances. Drawing on recent advances in expert elicitation to ensure data consistency, 200 experts were convened using a modified-Delphi process to estimate intactness scores: the remaining proportion of an intact reference population of a species group in a particular land use, on a scale from 0 (no remaining individuals) to 1 (same abundance as the reference) and, in rare cases, to 2 (populations that thrive in human-modified landscapes). The resulting bii4africa dataset contains intactness scores representing terrestrial vertebrates (tetrapods: ±5,400 amphibians, reptiles, birds, mammals) and vascular plants (±45,000 forbs, graminoids, trees, shrubs) in sub-Saharan Africa across the regions major land uses (urban, cropland, rangeland, plantation, protected, etc.) and intensities (e.g., large-scale vs smallholder cropland). This dataset was co-produced as part of the Biodiversity Intactness Index for Africa Project. Additional uses include assessing ecosystem condition; rectifying geographic/taxonomic biases in global biodiversity indicators and maps; and informing the Red List of Ecosystems.

Broad-spectrum antivirals are powerful weapons against dangerous viruses where no specific therapy exists, as in the case of the ongoing SARS-CoV-2 pandemic. We discovered that a lysine- and arginine-specific supramolecular ligand (CLR01) destroys enveloped viruses, including HIV, Ebola, and Zika virus, and remodels amyloid fibrils in semen that promote viral infection. Yet, it is unknown how CLR01 exerts these two distinct therapeutic activities. Here, we delineate a novel mechanism of antiviral activity by studying the activity of tweezer variants: the "phosphate tweezer" CLR01, a "carboxylate tweezer" CLR05, and a "phosphate clip" PC. Lysine complexation inside the tweezer cavity is needed to antagonize amyloidogenesis and is only achieved by CLR01. Importantly, CLR01 and CLR05 but not PC form closed inclusion complexes with lipid head groups of viral membranes, thereby altering lipid orientation and increasing surface tension. This process disrupts viral envelopes and diminishes infectivity but leaves cellular membranes intact. Consequently, CLR01 and CLR05 display broad antiviral activity against all enveloped viruses tested, including herpesviruses, Measles virus, influenza, and SARS-CoV-2. Based on our mechanistic insights, we potentiated the antiviral, membrane-disrupting activity of CLR01 by introducing aliphatic ester arms into each phosphate group to act as lipid anchors that promote membrane targeting. The most potent ester modifications harbored unbranched C4 units, which engendered tweezers that were approximately one order of magnitude more effective than CLR01 and nontoxic. Thus, we establish the mechanistic basis of viral envelope disruption by specific tweezers and establish a new class of potential broad-spectrum antivirals with enhanced activity.

Peer observation plays a key developmental role in initial teacher education courses. However, potential benefits can be limited due to time constraints and the rigidity of individual observation tasks. This article examines the use of synchronous computer-mediated communication (SCMC) as a peer observation tool on a CELTA course. We analyse SCMC feeds and participant interviews to discover how CELTA trainees and tutors use SCMC during observations and how participants perceive SCMC as an observation tool. SCMC enabled trainees to identify and solve problems, share ideas and opinions, give constructive feedback, and reflect on their own and their peers' teaching. Tutor questions were an important resource in prompting these actions. SCMC seemed to help build rapport and democratize feedback as trainees initiated discussions, chose topics, and interacted with each other and the tutor. Participants found SCMC engaging and useful. Results suggest that SCMC enhanced collaboration, dialogue, and reflection during peer observation.

Improvements in modelling power and input data have vastly improved the precision of physical flood models, but translation into economic outputs requires depth-damage functions that are inadequately verified. In particular, flood damage is widely assumed to increase monotonically with water depth. Here, we assess flood vulnerability in the US using >2 million claims from the National Flood Insurance Program (NFIP). NFIP claims data are messy, but the size of the dataset provides powerful empirical tests of damage patterns and modelling approaches. We show that current depth-damage functions consist of disparate relationships that match poorly with observations. Observed flood losses are not monotonic functions of depth, but instead better follow a beta function, with bimodal distributions for different water depths. Uncertainty in flood losses has been called the main bottleneck in flood risk studies, an obstacle that may be remedied using large-scale empirical flood damage data.

Global flood mapping has developed rapidly over the past decade, but previous approaches have limited scope, function, and accuracy. These limitations restrict the applicability and fundamental science questions that can be answered with existing model frameworks. Harnessing recently available data and modeling methods, this paper presents a new global ∼30 m resolution Global Flood Map (GFM) with complete coverage of fluvial, pluvial, and coastal perils, for any return period or climate scenario, including accounting for uncertainty. With an extensive compilation of global benchmark case studies—ranging from locally collected event water levels, to national inventories of engineering flood maps—we execute a comprehensive validation of the new GFM. For flood extent comparisons, we demonstrate that the GFM achieves a critical success index of ∼0.75. In the more discriminatory tests of flood water levels, the GFM deviates from observations by ∼0.6 m on average. Results indicating this level of global model fidelity are unprecedented in the literature. With an optimistic scenario of future warming (SSP1‐2.6), we show end‐of‐century global flood hazard (average annual inundation volume) increases are limited to 9% (likely range ‐6%–29%); this is within the likely climatological uncertainty of −8%–12% in the current hazard estimate. In contrast, pessimistic scenario (SSP5‐8.5) hazard changes emerge from the background noise in the 2040s, rising to a 49% (likely range of 7%–109%) increase by 2100. This work verifies the fitness‐for‐purpose of this new‐generation GFM for impact analyses with a variety of beneficial applications across policymaking, planning, and commercial risk assessment. Plain Language Summary: Computer models use a variety of data and physical equations to estimate the extent and depth of possible flood events. Global applications of these tools have been developed over the past decade, but they are not very good at simulating the behavior of real floods. In this paper, we address some key problems to make a global model that does a lot better than past ones. We apply new techniques to better understand how much water we need to put into the model for a given flood probability. This movement of water is simulated by the model over a more accurate map of the Earth's terrain than has been available previously, with river channels represented in a smarter way. We look at the projected changes in rainfall, river discharge, and sea levels for given levels of warming simulated by available climate models and adjust the probabilities of a given magnitude flood accordingly. The model results suggest that the effect of future climate change might be small relative to our ability to understand flood hazards today, but this depends heavily on how much carbon we emit in the coming decades. Key Points: New climate‐conditioned model framework represents fluvial, pluvial, and coastal flood hazards at high‐resolution globallyComprehensive validation studies suggest that the model is approaching local model skill in many casesEmissions reduction can hold flood hazards largely constant this century, though coastal flooding will increase drastically regardless [ABSTRACT FROM AUTHOR]

Coastal regions face increasing threats from rising sea levels and extreme weather events, highlighting the urgent need for accurate assessments of coastal flood risk. This study presents a novel approach to estimating global extreme sea level (ESL) exceedance probabilities using a regional frequency analysis (RFA) approach. The research combines observed and modelled hindcast data to produce a high-resolution (∼1 km) dataset of ESL exceedance probabilities, including wave setup, along the entire global coastline (excluding Antarctica). The methodology presented in this paper is an extension of the regional framework of Sweet et al. (2022), with innovations introduced to incorporate wave setup and apply the method globally. Water level records from tide gauges and a global reanalysis of tide and surge levels are integrated with a global ocean wave reanalysis. Subsequently, these data are regionalised, normalised, and aggregated and then fit with a generalised Pareto distribution. The regional distributions are downscaled to the local scale using the tidal range at every location along the global coastline obtained from a global tide model. The results show 8 cm of positive bias at the 1-in-10-year return level when compared to individual tide gauges. The RFA approach offers several advantages over traditional methods, particularly in regions with limited observational data. It overcomes the challenge of short and incomplete observational records by substituting long historical records with a collection of shorter but spatially distributed records. These spatially distributed data not only retain the volume of information but also address the issue of sparse tide gauge coverage in less populated areas and developing nations. The RFA process is illustrated using Cyclone Yasi (2011) as a case study, demonstrating how the approach can improve the characterisation of ESLs in regions prone to tropical cyclone activity. In conclusion, this study provides a valuable resource for quantifying the global coastal flood risk, offering an innovative global methodology that can contribute to preparing for – and mitigating against – coastal flooding. [ABSTRACT FROM AUTHOR]

Integration of new DNA into cellular genomes mediates replication of retroviruses and transposons; integration reactions have also been adapted for use in human gene therapy. Tracking the distributions of integration sites is important to characterize populations of transduced cells and to monitor potential outgrow of pathogenic cell clones. Here, we describe a pipeline for quantitative analysis of integration site distributions named INSPIIRED (integration site pipeline for paired-end reads). We describe optimized biochemical steps for site isolation using Illumina paired-end sequencing, including new technology for suppressing recovery of unwanted contaminants, then software for alignment, quality control, and management of integration site sequences. During library preparation, DNAs are broken by sonication, so that after ligation-mediated PCR the number of ligation junction sites can be used to infer abundance of gene-modified cells. We generated integration sites of known positions in silico, and we describe optimization of sample processing parameters refined by comparison to truth. We also present a novel graph-theory-based method for quantifying integration sites in repeated sequences, and we characterize the consequences using synthetic and experimental data. In an accompanying paper, we describe an additional set of statistical tools for data analysis and visualization. Software is available at https://github.com/BushmanLab/INSPIIRED.

Analysis of sites of newly integrated DNA in cellular genomes is important to several fields, but methods for analyzing and visualizing these datasets are still under development. Here, we describe tools for data analysis and visualization that take as input integration site data from our INSPIIRED pipeline. Paired-end sequencing allows inference of the numbers of transduced cells as well as the distributions of integration sites in target genomes. We present interactive heatmaps that allow comparison of distributions of integration sites to genomic features and that support numerous user-defined statistical tests. To summarize integration site data from human gene therapy samples, we developed a reproducible report format that catalogs sample population structure, longitudinal dynamics, and integration frequency near cancer-associated genes. We also introduce a novel summary statistic, the UC50 (unique cell progenitors contributing the most expanded 50% of progeny cell clones), which provides a single number summarizing possible clonal expansion. Using these tools, we characterize ongoing longitudinal characterization of a patient from the first trial to treat severe combined immunodeficiency-X1 (SCID-X1), showing successful reconstitution for 15 years accompanied by persistence of a cell clone with an integration site near the cancer-associated gene CCND2. Software is available at https://github.com/BushmanLab/INSPIIRED.

New remote sensing technologies, and the meter‐scale geospatial data they create, now allow for detailed urban landscape characterization, thereby advancing grid‐based hydrodynamic models. However, using a uniform fine grid over urban catchments generally result in dense grids and can lead to prohibitive computational costs. Moreover, an inability to see below the water surface and measure river bathymetry in most terrain remote sensing can severely impact local‐scale river hydraulics calculations given the significant volume of water conveyed by the channel. This paper introduces a super grid channel model which allow river channels with any width above that of the grid resolution to be simulated in 1D manner. As an extension of a previous subgrid model, this integration facilitates a seamless transition between subgrid and super grid channels, accommodating situations where channel width may surpass or fall below the grid resolution. The key contribution is the integration of the novel 1D channel representation with a nonuniform structured 2D floodplain hydrodynamic model and then coding this for application on GPU. Compared with the previous pure 2D nonuniform structured approaches, the new model presents an efficient compromise for riverine urban flooding where we are less concerned about fine‐scale details of in‐channel flow. Three tests reveal that the proposed model maintains accuracy but with significantly reduced computational cost. By leveraging GPU architectures, a ∼10× speedup compared to CPU computations is achieved, and a typical 6‐day urban flooding problem (domain size 1.42 km2) at 1 m resolution can be achieved within 10 hr on a single 8 GB GPU. Key Points: A nonuniform structured grid with a super grid river channel model is implemented on GPU for efficient meter‐scale urban flood modelingAs an extension of the subgrid model approach, this integration allows a seamless transition between subgrid and super grid channelsA ∼10× speedup compared to CPU computations is achieved by leveraging GPU architectures [ABSTRACT FROM AUTHOR]

Flood event set generation, as employed in catastrophe risk models, relies on gauge information that is not available in data‐scarce regions. To overcome this limitation, we develop a stochastic fluvial and pluvial flood model of Southeast Asia, using freely and globally available discharge data from the global hydrological model GloFAS and rainfall from the ERA5 reanalysis. We use a conditional multivariate statistical model to produce a synthetic catalog of 10,000 years of flood events. We calculate the flood population exposure associated with each flood event using freely available population data from WorldPop and generate exposure probability exceedance curves. We validate the population exposure curves against observed flood disaster data from EM‐DAT, showing that our methodology provides exposure estimates that are in line with historical observations. We find that there is a 1% probability that more than 30 million people will be exposed to flooding in a given year according to our event set. This number is roughly half the population living in the 100‐year return period flood zone of Fathom's hazard maps, suggesting most studies based on static flood maps overestimate exposure. This analysis provides significant progress over previous non‐stochastic studies which are only able to compute total or average exposure within a given floodplain area and demonstrates that a reanalysis‐based stochastic flood model can be designed to generate reliable estimates of population exposure probability exceedance. This study is a step toward a fully global catastrophe model for floods capable of providing exposure and loss estimates worldwide. Key Points: Global hydrological models can be used to drive a large‐scale stochastic flood inundation model in Southeast AsiaA reanalysis‐based stochastic flood model generates realistic flood eventsThe computed flood exposure exceedance curve for Southeast Asia compares well to the EM‐DAT database [ABSTRACT FROM AUTHOR]

Aggregatibacter actinomycetemcomitans cytolethal distending toxin (Cdt) is capable of intoxicating lymphocytes macrophages, mast cells and epithelial cells. Following Cdt binding to cholesterol, in the region of membrane lipid rafts, the CdtB and CdtC subunits are internalized and traffic to intracellular compartments. These events are dependent upon, cellugyrin, a critical component of synaptic like microvesicles (SLMVCg+). Target cells, such as Jurkat cells, rendered unable to express cellugyrin are resistant to Cdt-induced toxicity. Similar to Cdt, SARS-CoV-2 entry into host cells is initiated by binding to cell surface receptors, ACE-2, also associated with cholesterol-rich lipid rafts; this association leads to fusion and/or endocytosis of viral and host cell membranes and intracellular trafficking. The similarity in internalization pathways for both Cdt and SARS-CoV-2 led us to consider the possibility that cellugyrin was a critical component in both processes. Cellugyrin deficient Calu-3 cells (Calu-3Cg-) were prepared using Lentiviral particles containing shRNA; these cells were resistant to infection by VSV/SARS-CoV-2-spike pseudotype virus and partially resistant to VSV/VSV-G pseudotype virus. Synthetic peptides representing various regions of the cellugyrin protein were prepared and assessed for their ability to bind to Cdt subunits using surface plasmon resonance. Cdt was capable of binding to a region designated the middle outer loop (MOL) which corresponds to a region extending into the cytoplasmic surface of the SLMVCg+. SARS-CoV-2 spike proteins were assessed for their ability to bind to cellugyrin peptides; SARS-CoV-2 full length spike protein preferentially binds to a region within the SLMVCg+ lumen, designated intraluminal loop 1A. SARS-CoV-2-spike protein domain S1, which contains the receptor binding domains, binds to cellugyrin N-terminus which extends out from the cytoplasmic surface of SLMV. Binding specificity was further analyzed using cellugyrin scrambled peptide mutants. We propose that SLMVCg+ represent a component of a common pathway that facilitates pathogen and/or pathogen-derived toxins to gain host cell entry. [ABSTRACT FROM AUTHOR]