Regulatory Assessment of Casgevy for the Treatment of Transfusion-Dependent ß-Thalassemia and Sickle Cell Disease with Recurrent Vaso-Occlusive Crises.

Sickle cell disease (SCD) and transfusion-dependent ß-thalassemia (TDT) are hereditary haemoglobinopathies characterized by a reduction in functional ß-globin chains. Both conditions cause tiredness and increase susceptibility to infection, which can lead organ failure, significantly reducing life expectancy and typically requiring those affected to undergo regular erythrocyte transfusion. Recently, a novel therapeutic treatment for SCD and TDT was approved by the UK regulatory body (Medicines and Healthcare products Regulatory Agency; MHRA). Exagamglogene autotemcel (Casgevy) is the first licensed therapy globally to utilize CRIPSR/Cas9 technology and induces an increase in expression of γ-globin chains to compensate for the reduction in functional ß-globin. Casgevy represents a first-in-class therapeutic, and numerous considerations were made by the MHRA throughout its assessment of the medicine. These include, but are not limited to, the risk of tumorigenicity and off-target editing, a limited cohort size, the validity of proposed dosing and the conduction of only single-arm studies. The MHRA's analyses of the data to support the proposed indications are presented and discussed throughout this manuscript. Overall, the sponsors claims were considered well supported by their data, and Casgevy was licensed for the treatment of TDT or SCD in patients 12 years of age and older for whom hematopoietic stem cell (HSC) transplantation is appropriate, but a human leukocyte antigen-matched related HSC donor is not available.

Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs.

This forecasting approach may be useful for water managers and associated public health managers to predict near-term future high-risk cyanobacterial harmful algal blooms (cyanoHAB) occurrence. Freshwater cyanoHABs may grow to excessive concentrations and cause human, animal, and environmental health concerns in lakes and reservoirs. Knowledge of the timing and location of cyanoHAB events is important for water quality management of recreational and drinking water systems. No quantitative tool exists to forecast cyanoHABs across broad geographic scales and at regular intervals. Publicly available satellite monitoring has proven effective in detecting cyanobacteria biomass near-real time within the United States. Weekly cyanobacteria abundance was quantified from the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite as the response variable. An Integrated Nested Laplace Approximation (INLA) hierarchical Bayesian spatiotemporal model was applied to forecast World Health Organization (WHO) recreation Alert Level 1 exceedance >12 µg L-1 chlorophyll-a with cyanobacteria dominance for 2192 satellite resolved lakes in the United States across nine climate zones. The INLA model was compared against support vector classifier and random forest machine learning models; and Dense Neural Network, Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Gneural Network (GNU) neural network models. Predictors were limited to data sources relevant to cyanobacterial growth, readily available on a weekly basis, and at the national scale for operational forecasting. Relevant predictors included water surface temperature, precipitation, and lake geomorphology. Overall, the INLA model outperformed the machine learning and neural network models with prediction accuracy of 90% with 88% sensitivity, 91% specificity, and 49% precision as demonstrated by training the model with data from 2017 through 2020 and independently assessing predictions with data from the 2021 calendar year. The probability of true positive responses was greater than false positive responses and the probability of true negative responses was less than false negative responses. This indicated the model correctly assigned lower probabilities of events when they didn't exceed the WHO Alert Level 1 threshold and assigned higher probabilities when events did exceed the threshold. The INLA model was robust to missing data and unbalanced sampling between waterbodies.

Calibration using R-programming and parallel processing at the HUC12 subbasin scale in the Mid-Atlantic region: Development of national SWAT hydrologic calibration.

The first phase of a national scale Soil and Water Assessment Tool (SWAT) model calibration effort at the HUC12 (Hydrologic Unit Code 12) watershed scale was demonstrated over the Mid-Atlantic Region (R02), consisting of 3036 HUC12 subbasins. An R-programming based tool was developed for streamflow calibration including parallel processing for SWAT-CUP (SWAT- Calibration and Uncertainty Programs) to streamline the computational burden of calibration. Successful calibration of streamflow for 415 gages (KGE ≥0.5, Kling-Gupta efficiency; PBIAS ≤15%, Percent Bias) out of 553 selected monitoring gages was achieved in this study, yielding calibration parameter values for 2106 HUC12 subbasins. Additionally, 67 more gages were calibrated with relaxed PBIAS criteria of 25%, yielding calibration parameter values for an additional 150 HUC12 subbasins. This first phase of calibration across R02 increases the reliability, uniformity, and replicability of SWAT-related hydrological studies. Moreover, the study presents a comprehensive approach for efficiently optimizing large-scale multi-site calibration.

Catchment scale runoff time-series generation and validation using statistical models for the Continental United States.

We developed statistical models to generate runoff time-series at National Hydrography Dataset Plus Version 2 (NHDPlusV2) catchment scale for the Continental United States (CONUS). The models use Normalized Difference Vegetation Index (NDVI) based Curve Number (CN) to generate initial runoff time-series which then is corrected using statistical models to improve accuracy. We used the North American Land Data Assimilation System 2 (NLDAS-2) catchment scale runoff time-series as the reference data for model training and validation. We used 17 years of 16-day, 250-m resolution NDVI data as a proxy for hydrologic conditions during a representative year to calculate 23 NDVI based-CN (NDVI-CN) values for each of 2.65 million NHDPlusV2 catchments for the Contiguous U.S. To maximize predictive accuracy while avoiding optimistically biased model validation results, we developed a spatio-temporal cross-validation framework for estimating, selecting, and validating the statistical correction models. We found that in many of the physiographic sections comprising CONUS, even simple linear regression models were highly effective at correcting NDVI-CN runoff to achieve Nash-Sutcliffe Efficiency values above 0.5. However, all models showed poor performance in physiographic sections that experience significant snow accumulation.

Phylogenomics Identifies an Ancestral Burst of Gene Duplications Predating the Diversification of Aphidomorpha.

Aphids (Aphidoidea) are a diverse group of hemipteran insects that feed on plant phloem sap. A common finding in studies of aphid genomes is the presence of a large number of duplicated genes. However, when these duplications occurred remains unclear, partly due to the high relatedness of sequenced species. To better understand the origin of aphid duplications we sequenced and assembled the genome of Cinara cedri, an early branching lineage (Lachninae) of the Aphididae family. We performed a phylogenomic comparison of this genome with 20 other sequenced genomes, including the available genomes of five other aphids, along with the transcriptomes of two species belonging to Adelgidae (a closely related clade to the aphids) and Coccoidea. We found that gene duplication has been pervasive throughout the evolution of aphids, including many parallel waves of recent, species-specific duplications. Most notably, we identified a consistent set of very ancestral duplications, originating from a large-scale gene duplication predating the diversification of Aphidomorpha (comprising aphids, phylloxerids, and adelgids). Genes duplicated in this ancestral wave are enriched in functions related to traits shared by Aphidomorpha, such as association with endosymbionts, and adaptation to plant defenses and phloem-sap-based diet. The ancestral nature of this duplication wave (106-227 Ma) and the lack of sufficiently conserved synteny make it difficult to conclude whether it originated from a whole-genome duplication event or, alternatively, from a burst of large-scale segmental duplications. Genome sequencing of other aphid species belonging to different Aphidomorpha and related lineages may clarify these findings.

The European Medicines Agency Review of Kymriah (Tisagenlecleucel) for the Treatment of Acute Lymphoblastic Leukemia and Diffuse Large B-Cell Lymphoma.

Chimeric antigen receptor (CAR)-engineered T-cell therapy is becoming one of the most promising approaches in the treatment of cancer. On June 28, 2018, the Committee for Advanced Therapies (CAT) and the Committee for Medicinal Products for Human Use (CHMP) of the European Medicines Agency adopted a positive opinion, recommending the granting of a marketing authorization for the medicinal product Kymriah for pediatric and young adult patients up to 25 years of age with B-cell acute lymphoblastic leukemia (ALL) that is refractory, in relapse after transplant, or in second or later relapse and for adult patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL) after two or more lines of systemic therapy. Kymriah became one of the first European Union-approved CAR T therapies. The active substance of Kymriah is tisagenlecleucel, an autologous, immunocellular cancer therapy that involves reprogramming the patient's own T cells to identify and eliminate CD19-expressing cells. This is achieved by addition of a transgene encoding a CAR. The benefit of Kymriah was its ability to achieve remission with a significant duration in patients with ALL and an objective response with a significant duration in patients with DLBCL. The most common hematological toxicity was cytopenia in both patients with ALL and those with DLBCL. Nonhematological side effects in patients with ALL were cytokine release syndrome (CRS), infections, secondary hypogammaglobulinemia due to B-cell aplasia, pyrexia, and decreased appetite. The most common nonhematological side effects in patients with DLBCL were CRS, infections, pyrexia, diarrhea, nausea, hypotension, and fatigue. Kymriah also received an orphan designation on April 29, 2014, following a positive recommendation by the Committee for Orphan Medicinal Products (COMP). Maintenance of the orphan designation was recommended at the time of marketing authorization as the COMP considered the product was of significant benefit for patients with both conditions. IMPLICATIONS FOR PRACTICE: Chimeric antigen receptor (CAR)-engineered T-cell therapy is becoming the most promising approach in cancer treatment, involving reprogramming the patient's own T cells with a CAR-encoding transgene to identify and eliminate cancer-specific surface antigen-expressing cells. On June 28, 2018, Kymriah became one of the first EMA approved CAR T therapies. CAR T technology seems highly promising for diseases with single genetic/protein alterations; however, for more complex diseases there will be challenges to target clonal variability within the tumor type or clonal evolution during disease progression. Products with a lesser toxicity profile or more risk-minimization tools are also anticipated.

PiSCES: Pi(scine) stream community estimation system.

The Piscine Stream Community Estimation System (PiSCES) provides users with a hypothesized fish community for any stream reach in the conterminous United States using information obtained from Nature Serve, the US Geological Survey (USGS), StreamCat, and the Peterson Field Guide to Freshwater Fishes of North America for over 1000 native and non-native freshwater fish species. PiSCES can filter HUC8-based fish assemblages based on species-specific occurrence models; create a community abundance/biomass distribution by relating relative abundance to mean body weight of each species; and allow users to query its database to see ancillary characteristics of each species (e.g., habitat preferences and maximum size). Future efforts will aim to improve the accuracy of the species distribution database and refine/augment increase the occurrence models. The PiSCES tool is accessible at the EPA's Quantitative Environmental Domain (QED) website at https://qed.epacdx.net/pisces/.

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT.

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network-Daily (GHCN-D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN-D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN-D based SWAT-simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge-based measurements can improve hydrologic model performance, especially for extreme events.

Phenology-adjusted dynamic curve number for improved hydrologic modeling.

The Soil Conservation Service Curve Number (SCS-CN, or CN) is a widely used method to estimate runoff from rainfall events. It has been adapted to many parts of the world with different land uses, land cover types, and climatic conditions and successfully applied to situations ranging from simple runoff calculations and land use change assessment to comprehensive hydrologic/water quality simulations. However, the CN method lacks the ability to incorporate seasonal variations in vegetated surface conditions, and unnoticed landuse/landcover (LULC) change that shape infiltration and storm runoff. Plant phenology is a main determinant of changes in hydrologic processes and water balances across seasons through its influence on surface roughness and evapotranspiration. This study used regression analysis to develop a dynamic CN (CNNDVI) based on seasonal variations in the remotely-sensed Normalized Difference Vegetation Index (NDVI) to monitor intra-annual plant phenological development. A time series of 16-day MODIS NDVI (MOD13Q1 Collection 5) images were used to monitor vegetation development and provide NDVI data necessary for CNNDVI model calibration and validation. Twelve years of rainfall and runoff data (2001-2012) from four small watersheds located in the Konza Prairie Biological Station, Kansas were used to develop, calibrate, and validate the method. Results showed CNNDVI performed significantly better in predicting runoff with calibrated CNNDVI runoff increasing by approximately 0.74 for every unit increase in observed runoff compared to 0.46 for SCS-CN runoff and was more highly correlated to observed runoff (r = 0.78 vs. r = 0.38). In addition, CNNDVI runoff had better NSE (0.53) and PBIAS (4.22) compared to the SCS-CN runoff (-0.87 and -94.86 respectively). In the validated model, CNNDVI runoff increased by approximately 0.96 for every unit of observed runoff, while SCS-CN runoff increased by 0.49. Validated runoff was also better correlated to observed runoff than SCS-CN runoff (r = 0.52 vs. r = 0.33). These findings suggest that the CNNDVI can yield improved estimates of surface runoff from precipitation events, leading to more informed water and land management decisions.

Life cycle assessment of a rainwater harvesting system compared with an AC condensate harvesting system.

This study presents a life cycle assessment (LCA) of a rainwater harvesting (RWH) system and an air-conditioning condensate harvesting (ACH) system for non-potable water reuse. U.S. commercial buildings were reviewed to design rooftop RWH and ACH systems for one to multi-story buildings' non-potable water demand. A life cycle inventory was compiled from the U.S. EPA's database. Nine scenarios were analyzed, including baseline RWH system, ACH system, and combinations of the two systems adapted to 4-story and 19-story commercial buildings in San Francisco and a 4-story building in Washington, DC. Normalization of 11 life cycle impact assessment categories showed that RWH systems in 4-story buildings at both locations outperformed ACH systems (45-80% of ACH impacts) except equivalent in Evaporative Water Consumption. However, San Francisco's ACH system in 19-story building outperformed the RWH system (51-83% of RWH impacts) due to the larger volume of ACH collection, except equivalent in Evaporative Water Consumption. For all three buildings, the combined system preformed equivalently to the better-performing option (≤4-8% impact difference compared to the maximum system). Sensitivity analysis of the volume of water supply and building occupancy showed impact-specific results. Local climatic conditions, rainfall, humidity, water collections and demands are important when designing building-scale RWH and ACH systems. LCA models are transferrable to other locations with variable climatic conditions for decision-making when developing and implementing on-site non-potable water systems.

Basin-wide Impacts of Climate Change on Ecosystem Services in the Lower Mekong Basin.

Water resources support more than 60 million people in the Lower Mekong Basin (LMB) and are important for food security-especially rice production-and economic security. This study aims to quantify water yield under near- and long-term climate scenarios and assess the potential impacts on rice cultivation. The InVEST model (Integrated Valuation of Ecosystem Services and Tradeoffs) forecasted water yield, and land evaluation was used to delineate suitability classes. Pattern-downscaled climate data were specially generated for the LMB. Predicted annual water yields for 2030 and 2060, derived from a drier overall scenario in combination with medium and high greenhouse gas emissions, indicated a reduction of 9-24% from baseline (average 1986-2005) runoff. In contrast, increased seasonality and wetter rainfall scenarios increased annual runoff by 6-26%. Extreme drought decreased suitability of transplanted rice cultivation by 3%, and rice production would be reduced by 4.2 and 4%, with and without irrigation projects, relative to baseline. Greatest rice reduction was predicted for Thailand, followed by Lao PDR and Cambodia, and was stable for Vietnam. Rice production in the LMB appears sufficient to feed the LMB population in 2030, while rice production in Lao PDR and Cambodia are not expected to be sufficient for domestic consumption, largely due to steep topography and sandy soils as well as drought. Four adaptation measures to minimize climate impacts (i.e., irrigation, changing the planting calendar, new rice varieties, and alternative crops) are discussed.

Mobile device application for monitoring cyanobacteria harmful algal blooms using Sentinel-3 satellite Ocean and Land Colour Instruments.

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near realtime to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Ecosystem quality in LCIA: status quo, harmonization, and suggestions for the way forward.

PURPOSE: Life cycle impact assessment (LCIA) results are used to assess potential environmental impacts of different products and services. As part of the UNEP-SETAC life cycle initiative flagship project that aims to harmonize indicators of potential environmental impacts, we provide a consensus viewpoint and recommendations for future developments in LCIA related to the ecosystem quality area of protection (AoP). Through our recommendations, we aim to encourage LCIA developments that improve the usefulness and global acceptability of LCIA results. METHODS: We analyze current ecosystem quality metrics and provide recommendations to the LCIA research community for achieving further developments towards comparable and more ecologically relevant metrics addressing ecosystem quality. RESULTS AND DISCUSSION: We recommend that LCIA development for ecosystem quality should tend towards species-richnessrelated metrics, with efforts made towards improved inclusion of ecosystem complexity. Impact indicators-which result from a range of modeling approaches that differ, for example, according to spatial and temporal scale, taxonomic coverage, and whether the indicator produces a relative or absolute measure of loss-should be framed to facilitate their final expression in a single, aggregated metric. This would also improve comparability with other LCIA damage-level indicators. Furthermore, to allow for a broader inclusion of ecosystem quality perspectives, the development of an additional indicator related to ecosystem function is recommended. Having two complementary metrics would give a broader coverage of ecosystem attributes while remaining simple enough to enable an intuitive interpretation of the results. CONCLUSIONS: We call for the LCIA research community to make progress towards enabling harmonization of damage-level indicators within the ecosystem quality AoP and, further, to improve the ecological relevance of impact indicators.

An Integrated Ecological Modeling System for Assessing Impacts of Multiple Stressors on Stream and Riverine Ecosystem Services within River Basins.

We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990 - 2010 for the population of streams in the CRB and serves as a foundation for future model development.

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking source waters.

Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking source waters because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection, In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentine1-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 hectare in area. Results from this study show that 5.6 % of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7 % of waterbodies were resolvable when a three by three pixel (3×3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3×3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization's (WHO) high threshold for risk of 100,000 cells mL-1. The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1 %) and Grand Lake St. Marys, OH (83 %) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.

Life cycle assessment of a commercial rainwater harvesting system compared with a municipal water supply system.

Building upon previously published life cycle assessment (LCA) methodologies, we conducted an LCA of a commercial rainwater harvesting (RWH) system and compared it to a municipal water supply (MWS) system adapted to Washington, D.C. Eleven life cycle impact assessment (LCIA) indicators were assessed, with a functional unit of 1 m3 of rainwater and municipal water delivery system for toilets and urinals in a four-story commercial building with 1000 employees. Our assessment shows that the benchmark commercial RWH system outperforms the MWS system in all categories except Ozone Depletion. Sensitivity and performance analyses revealed pump and pumping energy to be key components for most categories, which further guides LCIA tradeoff analysis with respect to energy intensities. Tradeoff analysis revealed that commercial RWH performed better than MWS in Ozone Depletion if RWH's energy intensity was less than that of MWS by at least 0.86 kWh/m3 (249% of the benchmark MWS energy usage at 0.35 kWh/m3). RWH also outperformed MWS in Metal Depletion and Freshwater Withdrawal, regardless of energy intensities, up to 5.51 kWh/m3. An auxiliary commercial RWH system with 50% MWS reduced Ozone Depletion by 19% but showed an increase in all other impacts, which were still lower than benchmark MWS system impacts. Current models are transferrable to commercial RWH installations at other locations.

Considerations of Environmentally Relevant Test Conditions for Improved Evaluation of Ecological Hazards of Engineered Nanomaterials.

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

CholMine: Determinants and Prediction of Cholesterol and Cholate Binding Across Nonhomologous Protein Structures.

Identifying physiological ligands is necessary for annotating new protein structures, yet this presents a significant challenge to biologists and pharmaceutical chemists. Here we develop a predictor of cholesterol and cholate binding that works across diverse protein families, extending beyond sequence motif-based prediction. This approach combines SimSite3D site comparison with the detection of conserved interactions in cholesterol/cholate bound crystal structures to define three-dimensional interaction motifs. The resulting predictor identifies cholesterol sites with an ∼82% unbiased true positive rate in both membrane and soluble proteins, with a very low false positive rate relative to other predictors. The CholMine Web server can analyze users' structures, detect those likely to bind cholesterol/cholate, and predict the binding mode and key interactions. By deciphering the determinants of binding for these important steroids, CholMine may also aid in the design of selective inhibitors and detergents for targets such as G protein coupled receptors and bile acid receptors.

Integrated analyses of genome-wide DNA occupancy and expression profiling identify key genes and pathways involved in cellular transformation by a Marek's disease virus oncoprotein, Meq.

Marek's disease (MD) is an economically significant disease in chickens that is caused by the highly oncogenic Marek's disease virus (MDV). A major unanswered question is the mechanism of MDV-induced tumor formation. Meq, a bZIP transcription factor discovered in the 1990s, is critically involved in viral oncogenicity, but only a few of its host target genes have been described, impeding our understanding of MDV-induced tumorigenesis. Using chromatin immunoprecipitation-sequencing (ChIP-seq) and microarray analysis, a high-confidence list of Meq binding sites in the chicken genome and a global transcriptome of Meq-responsive genes were generated. Meq binding sites were found to be enriched in the promoter regions of upregulated genes but not in those of downregulated genes. ChIP-seq was also performed for c-Jun, a known heterodimeric partner of Meq. The close location of binding sites of Meq and c-Jun was noted, suggesting cooperativity between these two factors in modulating transcription. Pathway analysis indicated that Meq transcriptionally regulates many genes that are part of several signaling pathways including the extracellular signal-regulated kinase /mitogen-activated protein kinase (ERK/MAPK), Jak-STAT, and ErbB pathways, which are critical for oncogenesis and/or include signaling mediators involved in apoptosis. Meq activates oncogenic signaling cascades by transcriptionally activating major kinases in the ERK/MAPK pathway and simultaneously repressing phosphatases, as verified using inhibitors of MEK and ERK1/2 in a cell proliferation assay. This study provides significant insights into the mechanistic basis of Meq-dependent cell transformation.

Proposal for new European pharmaceutical legislation to permit access to custom-made anti-sense oligonucleotide medicinal products.

Current European pharmaceutical legislation is not adequate to meet advances in science and technologies that will lead to rapid development of custom-made medicines. Using existing legislation for custom-made medical devices as a template and anti-sense oligonucleotides as model medicinal products, we propose new European pharmaceutical legislation to permit timely access to custom-made anti-sense oligonucleotide medicinal products. The proposals may be more widely applicable to other medicinal products.