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  • 1
    In: Intensive Care Medicine, Springer Science and Business Media LLC, Vol. 47, No. 8 ( 2021-08), p. 867-886
    Type of Medium: Online Resource
    ISSN: 0342-4642 , 1432-1238
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 2
    In: JAMA, American Medical Association (AMA), Vol. 326, No. 17 ( 2021-11-02), p. 1690-
    Type of Medium: Online Resource
    ISSN: 0098-7484
    RVK:
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2021
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    SSG: 5,21
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  • 3
    In: JAMA Network Open, American Medical Association (AMA), Vol. 6, No. 5 ( 2023-05-25), p. e2314428-
    Abstract: Platelet activation is a potential therapeutic target in patients with COVID-19. Objective To evaluate the effect of P2Y12 inhibition among critically ill patients hospitalized for COVID-19. Design, Setting, and Participants This international, open-label, adaptive platform, 1:1 randomized clinical trial included critically ill (requiring intensive care–level support) patients hospitalized with COVID-19. Patients were enrolled between February 26, 2021, through June 22, 2022. Enrollment was discontinued on June 22, 2022, by the trial leadership in coordination with the study sponsor given a marked slowing of the enrollment rate of critically ill patients. Intervention Participants were randomly assigned to receive a P2Y12 inhibitor or no P2Y12 inhibitor (usual care) for 14 days or until hospital discharge, whichever was sooner. Ticagrelor was the preferred P2Y12 inhibitor. Main Outcomes and Measures The primary outcome was organ support–free days, evaluated on an ordinal scale that combined in-hospital death and, for participants who survived to hospital discharge, the number of days free of cardiovascular or respiratory organ support up to day 21 of the index hospitalization. The primary safety outcome was major bleeding, as defined by the International Society on Thrombosis and Hemostasis. Results At the time of trial termination, 949 participants (median [IQR] age, 56 [46-65] years; 603 male [63.5%]) had been randomly assigned, 479 to the P2Y12 inhibitor group and 470 to usual care. In the P2Y12 inhibitor group, ticagrelor was used in 372 participants (78.8%) and clopidogrel in 100 participants (21.2%). The estimated adjusted odds ratio (AOR) for the effect of P2Y12 inhibitor on organ support–free days was 1.07 (95% credible interval, 0.85-1.33). The posterior probability of superiority (defined as an OR  & amp;gt; 1.0) was 72.9%. Overall, 354 participants (74.5%) in the P2Y12 inhibitor group and 339 participants (72.4%) in the usual care group survived to hospital discharge (median AOR, 1.15; 95% credible interval, 0.84-1.55; posterior probability of superiority, 80.8%). Major bleeding occurred in 13 participants (2.7%) in the P2Y12 inhibitor group and 13 (2.8%) in the usual care group. The estimated mortality rate at 90 days for the P2Y12 inhibitor group was 25.5% and for the usual care group was 27.0% (adjusted hazard ratio, 0.96; 95% CI, 0.76-1.23; P  = .77). Conclusions and Relevance In this randomized clinical trial of critically ill participants hospitalized for COVID-19, treatment with a P2Y12 inhibitor did not improve the number of days alive and free of cardiovascular or respiratory organ support. The use of the P2Y12 inhibitor did not increase major bleeding compared with usual care. These data do not support routine use of a P2Y12 inhibitor in critically ill patients hospitalized for COVID-19. Trial Registration ClinicalTrials.gov Identifier: NCT04505774
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
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  • 4
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: A major challenge in genomics is discerning which bases among billions alter organismal phenotypes and affect health and disease risk. Evidence of past selective pressure on a base, whether highly conserved or fast evolving, is a marker of functional importance. Bases that are unchanged in all mammals may shape phenotypes that are essential for organismal health. Bases that are evolving quickly in some species, or changed only in species that share an adaptive trait, may shape phenotypes that support survival in specific niches. Identifying bases associated with exceptional capacity for cellular recovery, such as in species that hibernate, could inform therapeutic discovery. RATIONALE The power and resolution of evolutionary analyses scale with the number and diversity of species compared. By analyzing genomes for hundreds of placental mammals, we can detect which individual bases in the genome are exceptionally conserved (constrained) and likely to be functionally important in both coding and noncoding regions. By including species that represent all orders of placental mammals and aligning genomes using a method that does not require designating humans as the reference species, we explore unusual traits in other species. RESULTS Zoonomia’s mammalian comparative genomics resources are the most comprehensive and statistically well-powered produced to date, with a protein-coding alignment of 427 mammals and a whole-genome alignment of 240 placental mammals representing all orders. We estimate that at least 10.7% of the human genome is evolutionarily conserved relative to neutrally evolving repeats and identify about 101 million significantly constrained single bases (false discovery rate 〈 0.05). We cataloged 4552 ultraconserved elements at least 20 bases long that are identical in more than 98% of the 240 placental mammals. Many constrained bases have no known function, illustrating the potential for discovery using evolutionary measures. Eighty percent are outside protein-coding exons, and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Constrained bases tend to vary less within human populations, which is consistent with purifying selection. Species threatened with extinction have few substitutions at constrained sites, possibly because severely deleterious alleles have been purged from their small populations. By pairing Zoonomia’s genomic resources with phenotype annotations, we find genomic elements associated with phenotypes that differ between species, including olfaction, hibernation, brain size, and vocal learning. We associate genomic traits, such as the number of olfactory receptor genes, with physical phenotypes, such as the number of olfactory turbinals. By comparing hibernators and nonhibernators, we implicate genes involved in mitochondrial disorders, protection against heat stress, and longevity in this physiologically intriguing phenotype. Using a machine learning–based approach that predicts tissue-specific cis - regulatory activity in hundreds of species using data from just a few, we associate changes in noncoding sequence with traits for which humans are exceptional: brain size and vocal learning. CONCLUSION Large-scale comparative genomics opens new opportunities to explore how genomes evolved as mammals adapted to a wide range of ecological niches and to discover what is shared across species and what is distinctively human. High-quality data for consistently defined phenotypes are necessary to realize this potential. Through partnerships with researchers in other fields, comparative genomics can address questions in human health and basic biology while guiding efforts to protect the biodiversity that is essential to these discoveries. Comparing genomes from 240 species to explore the evolution of placental mammals. Our new phylogeny (black lines) has alternating gray and white shading, which distinguishes mammalian orders (labeled around the perimeter). Rings around the phylogeny annotate species phenotypes. Seven species with diverse traits are illustrated, with black lines marking their branch in the phylogeny. Sequence conservation across species is described at the top left. IMAGE CREDIT: K. MORRILL
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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  • 5
    In: The Lancet, Elsevier BV, Vol. 397, No. 10289 ( 2021-05), p. 2049-2059
    Type of Medium: Online Resource
    ISSN: 0140-6736
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 6
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of 〉 400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic]
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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  • 7
    In: JAMA, American Medical Association (AMA), Vol. 329, No. 13 ( 2023-04-04), p. 1066-
    Abstract: Randomized clinical trials (RCTs) of therapeutic-dose heparin in patients hospitalized with COVID-19 produced conflicting results, possibly due to heterogeneity of treatment effect (HTE) across individuals. Better understanding of HTE could facilitate individualized clinical decision-making. Objective To evaluate HTE of therapeutic-dose heparin for patients hospitalized for COVID-19 and to compare approaches to assessing HTE. Design, Setting, and Participants Exploratory analysis of a multiplatform adaptive RCT of therapeutic-dose heparin vs usual care pharmacologic thromboprophylaxis in 3320 patients hospitalized for COVID-19 enrolled in North America, South America, Europe, Asia, and Australia between April 2020 and January 2021. Heterogeneity of treatment effect was assessed 3 ways: using (1) conventional subgroup analyses of baseline characteristics, (2) a multivariable outcome prediction model (risk-based approach), and (3) a multivariable causal forest model (effect-based approach). Analyses primarily used bayesian statistics, consistent with the original trial. Exposures Participants were randomized to therapeutic-dose heparin or usual care pharmacologic thromboprophylaxis. Main Outcomes and Measures Organ support–free days, assigning a value of −1 to those who died in the hospital and the number of days free of cardiovascular or respiratory organ support up to day 21 for those who survived to hospital discharge; and hospital survival. Results Baseline demographic characteristics were similar between patients randomized to therapeutic-dose heparin or usual care (median age, 60 years; 38% female; 32% known non-White race; 45% Hispanic). In the overall multiplatform RCT population, therapeutic-dose heparin was not associated with an increase in organ support–free days (median value for the posterior distribution of the OR, 1.05; 95% credible interval, 0.91-1.22). In conventional subgroup analyses, the effect of therapeutic-dose heparin on organ support–free days differed between patients requiring organ support at baseline or not (median OR, 0.85 vs 1.30; posterior probability of difference in OR, 99.8%), between females and males (median OR, 0.87 vs 1.16; posterior probability of difference in OR, 96.4%), and between patients with lower body mass index (BMI & amp;lt;30) vs higher BMI groups (BMI ≥30; posterior probability of difference in ORs & amp;gt;90% for all comparisons). In risk-based analysis, patients at lowest risk of poor outcome had the highest propensity for benefit from heparin (lowest risk decile: posterior probability of OR & amp;gt;1, 92%) while those at highest risk were most likely to be harmed (highest risk decile: posterior probability of OR & amp;lt;1, 87%). In effect-based analysis, a subset of patients identified at high risk of harm ( P  = .05 for difference in treatment effect) tended to have high BMI and were more likely to require organ support at baseline. Conclusions and Relevance Among patients hospitalized for COVID-19, the effect of therapeutic-dose heparin was heterogeneous. In all 3 approaches to assessing HTE, heparin was more likely to be beneficial in those who were less severely ill at presentation or had lower BMI and more likely to be harmful in sicker patients and those with higher BMI. The findings illustrate the importance of considering HTE in the design and analysis of RCTs. Trial Registration ClinicalTrials.gov Identifiers: NCT02735707 , NCT04505774 , NCT04359277 , NCT04372589
    Type of Medium: Online Resource
    ISSN: 0098-7484
    RVK:
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
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    detail.hit.zdb_id: 2018410-4
    SSG: 5,21
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  • 8
    In: Biological Conservation, Elsevier BV, Vol. 283 ( 2023-07), p. 110021-
    Type of Medium: Online Resource
    ISSN: 0006-3207
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1496231-7
    SSG: 12
    SSG: 23
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  • 9
    In: Global Ecology and Biogeography, Wiley, Vol. 31, No. 10 ( 2022-10), p. 2085-2104
    Abstract: After environmental disasters, species with large population losses may need urgent protection to prevent extinction and support recovery. Following the 2019–2020 Australian megafires, we estimated population losses and recovery in fire‐affected fauna, to inform conservation status assessments and management. Location Temperate and subtropical Australia. Time period 2019–2030 and beyond. Major taxa Australian terrestrial and freshwater vertebrates; one invertebrate group. Methods From 〉  1,050 fire‐affected taxa, we selected 173 whose distributions substantially overlapped the fire extent. We estimated the proportion of each taxon’s distribution affected by fires, using fire severity and aquatic impact mapping, and new distribution mapping. Using expert elicitation informed by evidence of responses to previous wildfires, we estimated local population responses to fires of varying severity. We combined the spatial and elicitation data to estimate overall population loss and recovery trajectories, and thus indicate potential eligibility for listing as threatened, or uplisting, under Australian legislation. Results We estimate that the 2019–2020 Australian megafires caused, or contributed to, population declines that make 70–82 taxa eligible for listing as threatened; and another 21–27 taxa eligible for uplisting. If so‐listed, this represents a 22–26% increase in Australian statutory lists of threatened terrestrial and freshwater vertebrates and spiny crayfish, and uplisting for 8–10% of threatened taxa. Such changes would cause an abrupt worsening of underlying trajectories in vertebrates, as measured by Red List Indices. We predict that 54–88% of 173 assessed taxa will not recover to pre‐fire population size within 10 years/three generations. Main conclusions We suggest the 2019–2020 Australian megafires have worsened the conservation prospects for many species. Of the 91 taxa recommended for listing/uplisting consideration, 84 are now under formal review through national processes. Improving predictions about taxon vulnerability with empirical data on population responses, reducing the likelihood of future catastrophic events and mitigating their impacts on biodiversity, are critical.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
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    SSG: 12
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  • 10
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: Thousands of genetic variants have been associated with human diseases and traits through genome-wide association studies (GWASs). Translating these discoveries into improved therapeutics requires discerning which variants among hundreds of candidates are causally related to disease risk. To date, only a handful of causal variants have been confirmed. Here, we leverage 100 million years of mammalian evolution to address this major challenge. RATIONALE We compared genomes from hundreds of mammals and identified bases with unusually few variants (evolutionarily constrained). Constraint is a measure of functional importance that is agnostic to cell type or developmental stage. It can be applied to investigate any heritable disease or trait and is complementary to resources using cell type– and time point–specific functional assays like Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTEx). RESULTS Using constraint calculated across placental mammals, 3.3% of bases in the human genome are significantly constrained, including 57.6% of coding bases. Most constrained bases (80.7%) are noncoding. Common variants (allele frequency ≥ 5%) and low-frequency variants (0.5% ≤ allele frequency 〈 5%) are depleted for constrained bases (1.85 versus 3.26% expected by chance, P 〈 2.2 × 10 −308 ). Pathogenic ClinVar variants are more constrained than benign variants ( P 〈 2.2 × 10 −16 ). The most constrained common variants are more enriched for disease single-nucleotide polymorphism (SNP)–heritability in 63 independent GWASs. The enrichment of SNP-heritability in constrained regions is greater (7.8-fold) than previously reported in mammals and is even higher in primates (11.1-fold). It exceeds the enrichment of SNP-heritability in nonsynonymous coding variants (7.2-fold) and fine-mapped expression quantitative trait loci (eQTL)–SNPs (4.8-fold). The enrichment peaks near constrained bases, with a log-linear decrease of SNP-heritability enrichment as a function of the distance to a constrained base. Zoonomia constraint scores improve functionally informed fine-mapping. Variants at sites constrained in mammals and primates have greater posterior inclusion probabilities and higher per-SNP contributions. In addition, using both constraint and functional annotations improves polygenic risk score accuracy across a range of traits. Finally, incorporating constraint information into the analysis of noncoding somatic variants in medulloblastomas identifies new candidate driver genes. CONCLUSION Genome-wide measures of evolutionary constraint can help discern which variants are functionally important. This information may accelerate the translation of genomic discoveries into the biological, clinical, and therapeutic knowledge that is required to understand and treat human disease. Using evolutionary constraint in genomic studies of human diseases. ( A ) Constraint was calculated across 240 mammal species, including 43 primates (teal line). ( B ) Pathogenic ClinVar variants ( N = 73,885) are more constrained across mammals than benign variants ( N = 231,642; P 〈 2.2 × 10 −16 ). ( C ) More-constrained bases are more enriched for trait-associated variants (63 GWASs). ( D ) Enrichment of heritability is higher in constrained regions than in functional annotations (left), even in a joint model with 106 annotations (right). ( E ) Fine-mapping (PolyFun) using a model that includes constraint scores identifies an experimentally validated association at rs1421085. Error bars represent 95% confidence intervals. BMI, body mass index; LF, low frequency; PIP, posterior inclusion probability.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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    detail.hit.zdb_id: 2060783-0
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