Project description:Endovascular thrombectomy for large vessel ischaemic stroke substantially reduces disability, with recent positive randomised trials leading to guideline changes worldwide. This review discusses in detail the evidence provided by recent randomised trials and meta-analyses, the remaining areas of uncertainty and the future directions for research. The data from existing trials have demonstrated the robust benefit of endovascular thrombectomy for internal carotid and proximal middle cerebral artery occlusions. Uncertainty remains for more distal occlusions where the efficacy of alteplase is greater, less tissue is at risk and the safety of endovascular procedures is less established. Basilar artery occlusion was excluded from the trials, but with a dire natural history and proof of principle that rapid reperfusion is effective, it seems reasonable to continue treating these patients pending ongoing trial results. There has been no evidence of heterogeneity in treatment effect in clinically defined subgroups by age, indeed, those aged >80 years have at least as great an overall reduction in disability and reduced mortality. Similarly there was no heterogeneity across the range of baseline stroke severities included in the trials. Evidence that routine use of general anaesthesia reduces the benefit of endovascular thrombectomy is increasing and conscious sedation is generally preferred unless severe agitation or airway compromise is present. The impact of time delays has become clearer with description of onset to imaging and imaging to reperfusion epochs. Delays in the onset to imaging reduce the proportion of patients with salvageable brain tissue. However, in the presence of favourable imaging, rapid treatment appears beneficial regardless of the onset to imaging time elapsed. Imaging to reperfusion delays lead to decay in the clinical benefit achieved, particularly in those with less robust collateral flow. The brain imaging options to assess prognosis have various advantages and disadvantages, but whatever strategy is employed must be fast. Ongoing trials are investigating extended time windows, using advanced brain imaging selection. There is also a need for further technical advances to maximise rates of complete reperfusion in the minimum time.
Project description:OBJECTIVE:To present a measure of effective workplace organizational policies, programs, and practices that focuses on working conditions and organizational facilitators of worker safety, health and well-being: the workplace integrated safety and health (WISH) assessment. METHODS:Development of this assessment used an iterative process involving a modified Delphi method, extensive literature reviews, and systematic cognitive testing. RESULTS:The assessment measures six core constructs identified as central to best practices for protecting and promoting worker safety, health and well-being: leadership commitment; participation; policies, programs, and practices that foster supportive working conditions; comprehensive and collaborative strategies; adherence to federal and state regulations and ethical norms; and data-driven change. CONCLUSIONS:The WISH Assessment holds promise as a tool that may inform organizational priority setting and guide research around causal pathways influencing implementation and outcomes related to these approaches.
Project description:Enhanced cross-linking immunoprecipitation (eCLIP) featuring a size-matched input control has been recently applied to profile the binding sites of more than one hundred RNA binding proteins (RBPs). However computational pipelines and quality control metrics needed to process CLIP data at scale have yet to be well defined. Here, we describe our ENCODE eCLIP processing pipeline (https://github.com/YeoLab/eclip), enabling users to go from raw reads to processed peaks that are enriched above paired input, reproducible across biological replicates, and can be directly compared against the public ENCODE eCLIP resource. In particular, we discuss processing steps designed to address common artifacts, including properly quantifying unique RNA fragments bound by both unique genomic- and repetitive element-mapped reads. Using manual quality annotation of 350 ENCODE eCLIP experiments, we develop metrics for quality assessment of eCLIP experiments prior to and after sequencing, including library yield, number of unique fragments in the library, total binding relative information, and biological reproducibility. In particular, we quantify the commonly believed linkage between depth of sequencing and peak discovery, and derive methods for estimating required sequencing depth based on pre-sequencing metrics. Finally we provide recommendations for the common question of integrating RBP binding information with RNA-seq to generate splicing maps representing the positional effect of binding on alternative splicing. These pipelines and QC metrics enable large-scale processing and analysis of eCLIP data, and will help to standardize rigorous analysis of RBP binding data.
Project description:Enhanced cross-linking immunoprecipitation (eCLIP) featuring a size-matched input control has been recently applied to profile the binding sites of more than one hundred RNA binding proteins (RBPs). However computational pipelines and quality control metrics needed to process CLIP data at scale have yet to be well defined. Here, we describe our ENCODE eCLIP processing pipeline (https://github.com/YeoLab/eclip), enabling users to go from raw reads to processed peaks that are enriched above paired input, reproducible across biological replicates, and can be directly compared against the public ENCODE eCLIP resource. In particular, we discuss processing steps designed to address common artifacts, including properly quantifying unique RNA fragments bound by both unique genomic- and repetitive element-mapped reads. Using manual quality annotation of 350 ENCODE eCLIP experiments, we develop metrics for quality assessment of eCLIP experiments prior to and after sequencing, including library yield, number of unique fragments in the library, total binding relative information, and biological reproducibility. In particular, we quantify the commonly believed linkage between depth of sequencing and peak discovery, and derive methods for estimating required sequencing depth based on pre-sequencing metrics. Finally we provide recommendations for the common question of integrating RBP binding information with RNA-seq to generate splicing maps representing the positional effect of binding on alternative splicing. These pipelines and QC metrics enable large-scale processing and analysis of eCLIP data, and will help to standardize rigorous analysis of RBP binding data.
Project description:This submission is a dataset of single-nucleus multi-omics of uninjured and injured spinal cords of mice harvested and profiled using 10x Multiome ATAC + Gene Expression kit.
Project description:R-loops represent an abundant class of large non-B DNA structures in genomes. Even though they form transiently and at modest frequencies, interfering with R-loop formation or dissolution significantly impacts genome stability. Addressing the mechanism(s) of R-loop-mediated genome destabilization requires a precise characterization of their distribution in genomes. A number of independent methods have been developed to visualize and map R-loops, but their results are at times discordant, leading to confusion. Here we review the main existing methodologies underlying R-loop mapping and assess their limitations and the robustness of existing datasets. We offer a set of best practices to improve the reproducibility of maps, hoping that such guidelines could be useful for authors and referees alike. Finally, we offer a possible resolution to the apparent contradictions in R-loop mapping outcomes between antibody-based and RNase H1-based mapping approaches.
Project description:Thirty-five years ago, precision-cut liver slices (PCLS) were described as a promising tool and were expected to become the standard in vitro model to study liver disease as they tick off all characteristics of a good in vitro model. In contrast to most in vitro models, PCLS retain the complex 3D liver structures found in vivo, including cell-cell and cell-matrix interactions, and therefore should constitute the most reliable tool to model and to investigate pathways underlying chronic liver disease in vitro. Nevertheless, the biggest disadvantage of the model is the initiation of a procedure-induced fibrotic response. In this review, we describe the parameters and potential of PCLS cultures and discuss whether the initially described limitations and pitfalls have been overcome. We summarize the latest advances in PCLS research and critically evaluate PCLS use and progress since its invention in 1985.
Project description:BackgroundEcological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants' behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no "gold standard" for EMA study design to promote compliance.ObjectiveThe purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs.MethodsParticipants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1-number of questions per EMA survey (15 vs 25); factor 2-number of EMAs per day (2 vs 4); factor 3-EMA prompting schedule (random vs fixed times); factor 4-payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5-EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined.ResultsParticipants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance.ConclusionsStudy results have broad implications for developing best practices guidelines for future studies that use EMA methodologies.Trial registrationClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228.
Project description:ObjectiveTo describe PCORnet, a clinical research network developed for patient-centered outcomes research on a national scale.Study design and settingDescriptive study of the current state and future directions for PCORnet. We conducted cross-sectional analyses of the health systems and patient populations of the 9 Clinical Research Networks and 2 Health Plan Research Networks that are part of PCORnet.ResultsWithin the Clinical Research Networks, electronic health data are currently collected from 337 hospitals, 169,695 physicians, 3,564 primary care practices, 338 emergency departments, and 1,024 community clinics. Patients can be recruited for prospective studies from any of these clinical sites. The Clinical Research Networks have accumulated data from 80 million patients with at least one visit from 2009 to 2018. The PCORnet Health Plan Research Network population of individuals with a valid enrollment segment from 2009 to 2019 exceeds 60 million individuals, who on average have 2.63 years of follow-up.ConclusionPCORnet's infrastructure comprises clinical data from a diverse cohort of patients and has the capacity to rapidly access these patient populations for pragmatic clinical trials, epidemiological research, and patient-centered research on rare diseases.