The current state-of-the-art of spinal cord imaging: methods.

A first-ever spinal cord imaging meeting was sponsored by the International Spinal Research Trust and the Wings for Life Foundation with the aim of identifying the current state-of-the-art of spinal cord imaging, the current greatest challenges, and greatest needs for future development. This meeting was attended by a small group of invited experts spanning all aspects of spinal cord imaging from basic research to clinical practice. The greatest current challenges for spinal cord imaging were identified as arising from the imaging environment itself; difficult imaging environment created by the bone surrounding the spinal canal, physiological motion of the cord and adjacent tissues, and small cross-sectional dimensions of the spinal cord, exacerbated by metallic implants often present in injured patients. Challenges were also identified as a result of a lack of "critical mass" of researchers taking on the development of spinal cord imaging, affecting both the rate of progress in the field, and the demand for equipment and software to manufacturers to produce the necessary tools. Here we define the current state-of-the-art of spinal cord imaging, discuss the underlying theory and challenges, and present the evidence for the current and potential power of these methods. In two review papers (part I and part II), we propose that the challenges can be overcome with advances in methods, improving availability and effectiveness of methods, and linking existing researchers to create the necessary scientific and clinical network to advance the rate of progress and impact of the research

Many Labs 5: Testing Pre-Data-Collection Peer Review as an Intervention to Increase Replicability

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect (p <.05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3–9; median total sample = 1,279.5, range = 276–3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (Δr =.002 or.014, depending on analytic approach). The median effect size for the revised protocols (r =.05) was similar to that of the RP:P protocols (r =.04) and the original RP:P replications (r =.11), and smaller than that of the original studies (r =.37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r =.07, range =.00–.15) were 78% smaller, on average, than the original effect sizes (median r =.37, range =.19–.50)

Many Labs 5:Testing pre-data collection peer review as an intervention to increase replicability

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect (p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3?9; median total sample = 1,279.5, range = 276?3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (?r = .002 or .014, depending on analytic approach). The median effect size for the revised protocols (r = .05) was similar to that of the RP:P protocols (r = .04) and the original RP:P replications (r = .11), and smaller than that of the original studies (r = .37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r = .07, range = .00?.15) were 78% smaller, on average, than the original effect sizes (median r = .37, range = .19?.50)

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Conserving alpha and beta diversity in wood-production landscapes

International demand for wood and other forest products continues to grow rapidly, and uncertainties remain about how animal communities will respond to intensifying resource extraction associated with woody bioenergy production. We examined changes in alpha and beta diversity of bats, bees, birds, and reptiles across wood production landscapes in the southeastern United States, a biodiversity hotspot that is one of the principal sources of woody biomass globally. We sampled across a spatial gradient of paired forest land-uses (representing pre and postharvest) that allowed us to evaluate biological community changes resulting from several types of biomass harvest. Short-rotation practices and residue removal following clearcuts were associated with reduced alpha diversity (-14.1 and -13.9 species, respectively) and lower beta diversity (i.e., Jaccard dissimilarity) between land-use pairs (0.46 and 0.50, respectively), whereas midrotation thinning increased alpha (+3.5 species) and beta diversity (0.59). Over the course of a stand rotation in a single location, biomass harvesting generally led to less biodiversity. Cross-taxa responses to resource extraction were poorly predicted by alpha diversity: correlations in responses between taxonomic groups were highly variable (-0.2 to 0.4) with large uncertainties. In contrast, beta diversity patterns were highly consistent and predictable across taxa, where correlations in responses between taxonomic groups were all positive (0.05-0.4) with more narrow uncertainties. Beta diversity may, therefore, be a more reliable and information-rich indicator than alpha diversity in understanding animal community response to landscape change. Patterns in beta diversity were primarily driven by turnover instead of species loss or gain, indicating that wood extraction generates habitats that support different biological communities.SUPPORTING INFORMATION : APPENDIX S1. Distribution of the six land-use types across three ownerships (nonindustrial private, industrial timber, and local/state/federal). APPENDIX S2. Occupancy and detection covariate structures for multispecies occupancy models. APPENDIX S3. Alpha-diversity across the six sampled land uses. APPENDIX S4. Beta-diversity components (total Jaccard dissimilarity, Jaccard turnover, and Jaccard nestedness) for pairwise bioenergy contrasts. APPENDIX S5. Average beta-diversity and beta-diversity components for pairwise land-use comparisons across bats, bees, birds, and reptiles APPENDIX S6. Beta-diversity components (total Jaccard dissimilarity, Jaccard turnover, and Jaccard nestedness) within each of the six land use typesUS Department of Agriculture - NIFA.https://wileyonlinelibrary.com/journal/cobi2022-12-02hj2022Mammal Research Institut

Conserving alpha and beta diversity in wood-production landscapes

International demand for wood and other forest products continues to grow rapidly, and uncertainties remain about how animal communities will respond to intensifying resource extraction associated with woody bioenergy production. We examined changes in alpha and beta diversity of bats, bees, birds, and reptiles across wood production landscapes in the southeastern United States, a biodiversity hotspot that is one of the principal sources of woody biomass globally. We sampled across a spatial gradient of paired forest land-uses (representing pre and postharvest) that allowed us to evaluate biological community changes resulting from several types of biomass harvest. Short-rotation practices and residue removal following clearcuts were associated with reduced alpha diversity (−14.1 and −13.9 species, respectively) and lower beta diversity (i.e., Jaccard dissimilarity) between land-use pairs (0.46 and 0.50, respectively), whereas midrotation thinning increased alpha (+3.5 species) and beta diversity (0.59). Over the course of a stand rotation in a single location, biomass harvesting generally led to less biodiversity. Cross-taxa responses to resource extraction were poorly predicted by alpha diversity: correlations in responses between taxonomic groups were highly variable (−0.2 to 0.4) with large uncertainties. In contrast, beta diversity patterns were highly consistent and predictable across taxa, where correlations in responses between taxonomic groups were all positive (0.05–0.4) with more narrow uncertainties. Beta diversity may, therefore, be a more reliable and information-rich indicator than alpha diversity in understanding animal community response to landscape change. Patterns in beta diversity were primarily driven by turnover instead of species loss or gain, indicating that wood extraction generates habitats that support different biological communities.Fil: Gavin, Jones M.. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unidos. USDA Forest Service. Rocky Mountain Research Station; Estados UnidosFil: Brosi, Berry. University of Washington; Estados Unidos. University of Emory; Estados UnidosFil: Evans, Jason. Stetson University. Department of Environmental Science and Studies; Estados UnidosFil: Gottlieb, Isabel G. W.. University of Florida; Estados UnidosFil: Loy, Xingwen. University of Emory; Estados Unidos. Atlanta Botanical Garden. Conservation & Research Department; Estados UnidosFil: Núñez Regueiro, Mauricio Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Bio y Geociencias del NOA. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Museo de Ciencias Naturales. Instituto de Bio y Geociencias del NOA; Argentina. University of Florida; Estados UnidosFil: Ober, Holly K.. University of Florida. Department of Wildlife Ecology and Conservation; Estados UnidosFil: Pienaar, Elizabeth. University of Georgia; Estados Unidos. University of Pretoria. Mammal Research Institute; Estados UnidosFil: Pillay, Rajeev. University of Florida. Department of Wildlife Ecology and Conservation; Estados UnidosFil: Pisarello, Kathryn. University of Florida. Department of Wildlife Ecology and Conservation; Estados UnidosFil: Smith, Lora L.. Jones Center at Ichauway; Estados UnidosFil: Fletcher, Robert J.. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unido

QTLs associated with dry matter intake, metabolic mid-test weight, growth and feed efficiency have little overlap across 4 beef cattle studies

Background: The identification of genetic markers associated with complex traits that are expensive to record such as feed intake or feed efficiency would allow these traits to be included in selection programs. To identify large-effect QTL, we performed a series of genome-wide association studies and functional analyses using 50 K and 770 K SNP genotypes scored in 5,133 animals from 4 independent beef cattle populations (Cycle VII, Angus, Hereford and Simmental × Angus) with phenotypes for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake. Results: A total of 5, 6, 11 and 10 significant QTL (defined as 1-Mb genome windows with Bonferroni-corrected P-value Conclusions: This GWAS study, which is the largest performed for feed efficiency and its component traits in beef cattle to date, identified several large-effect QTL that cumulatively explained a significant percentage of additive genetic variance within each population. Differences in the QTL identified among the different populations may be due to differences in power to detect QTL, environmental variation, or differences in the genetic architecture of trait variation among breeds. These results enhance our understanding of the biology of growth, feed intake and utilisation in beef cattle

Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle

Background: Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations. Results: Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but \u3c 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained). Conclusions: Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species

Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle

Abstract Background Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations. Results Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but < 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained). Conclusions Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species