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1,146 results for “collaboration;”
PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: CCRCC Validation Cohort Grades 1 and 2
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Data from: Perioperative medication management: expanding the role of the preadmission clinic pharmacist in a single centre, randomised controlled trial of collaborative prescribing
Objectives: Current evidence to support non-medical prescribing is predominantly qualitative, with little evaluation of accuracy, safety and appropriateness. Our aim was to evaluate a new model of service for the Australia healthcare system, of inpatient medication prescribing by a pharmacist in an elective surgery pre admission clinic (PAC) against usual care, using an endorsed performance framework. Design: Single centre, randomised controlled, two arm trial Setting: Elective surgery pre admission clinic in Brisbane based tertiary hospital Participants: Four hundred adults scheduled for elective surgery were randomised to intervention or control. Intervention: A pharmacist generated the inpatient medication chart to reflect the patient's regular medication, made a plan for medication perioperatively and prescribed VTE prophylaxis. In the control arm, the medication chart was generated by the Resident Medical Officers (RMO). Outcome Measures: Primary outcome was frequency of omissions and prescribing errors when compared against the medication history. The clinical significance of omissions was also analysed. Secondary outcome was appropriateness of VTE prophylaxis prescribing. Results: There were significantly less unintended omissions of medications: 11 of 887 (1.2%) intervention orders compared with 383 of 1217 (31.5%) control (p<0.001). There were significantly less prescribing errors involving selection of drug, dose or frequency: 2 in 857 (0.2%) intervention orders compared with 51 in 807 (6.3%) control (p<0.001). Orders with at least one component of the prescription missing, incorrect or unclear occurred in 20826 of 904 (235%) intervention orders and 445667 of 1034 (4364.5%) control (p<0.001). VTE prophylaxis on admission to the ward was appropriate in 93% of intervention patients and 90% control (p=0.29). Conclusion: Medication charts in the intervention arm contained fewer clinically significant omissions, and prescribing errors, when compared to control. There was no difference in appropriateness of VTE prophylaxis on admission between the two groups. Trial Registration: Registered with ANZCTR – ACTR Number ACTRN12609000426280
Data from: Human-relevant mechanisms and risk factors for TAK-875-induced liver injury identified via a gene pathway-based approach in collaborative cross mice
<p>Development of TAK-875 was discontinued when a small number of serious drug-induced liver injury (DILI) cases were observed in Phase 3 clinical trials. Subsequent studies have identified hepatocellular oxidative stress, mitochondrial dysfunction, altered bile acid homeostasis, and immune response as mechanisms of TAK-875 DILI and the contribution of genetic risk factors in oxidative response and mitochondrial pathways to the toxicity susceptibility observed in patients. We tested the hypothesis that a novel preclinical approach based on gene pathway analysis in the livers of Collaborative Cross mice could be used to identify human-relevant mechanisms of toxicity and genetic risk factors at the level of the hepatocyte as reported in a human genome-wide association study. Eight (8) male mice (4 matched pairs) from each of 45 Collaborative Cross lines were treated with a single oral (gavage) dose of either vehicle or 600 mg/kg TAK-875. As expected, liver injury was not detected histologically and few changes in plasma biomarkers of hepatotoxicity were observed. However, gene expression profiling in the liver identified hundreds of transcripts responsive to TAK-875 treatment across all strains reflecting alterations in immune response and bile acid homeostasis and the interaction of treatment and strain reflecting oxidative stress and mitochondrial dysfunction. Fold-change expression values were then used to develop pathway-based phenotypes for genetic mapping which identified candidate risk factor genes for TAK-875 toxicity susceptibility at the level of the hepatocyte. Taken together, these findings support our hypothesis that a gene pathway-based approach using Collaborative Cross mice could inform sensitive strains, human-relevant mechanisms of toxicity, and genetic risk factors for TAK-875 DILI. This novel preclinical approach may be helpful in understanding, predicting, and ultimately preventing clinical DILI for other drugs.</p>
Dying to cooperate: the role of environmental harshness in human collaboration
<p class="MsoNoSpacing">It has been proposed that environmental stress acted as a selection pressure on the evolution of human cooperation. Through agent-based evolutionary modelling, mathematical analysis and human experimental data we illuminate the mechanisms by which the environment influences cooperative success and decision making in a Stag Hunt game. The modelling and mathematical results show that only cooperative foraging phenotypes survive the harshest of environments but pay a penalty for mis-coordination in favourable environments. When agents are allowed to coordinate their hunting intentions by communicating, cooperative phenotypes outcompete those who pursue individual strategies in almost all environmental and payoff scenarios examined. Data from human participants show flexible decision-making in face of cooperative uncertainty, favouring high-risk, high-reward strategy when environments are harsher and starvation is imminent. Converging lines of evidence from the three approaches indicate a significant role for environmental variability in human cooperative dynamics and the species-unique cognition designed to support it.</p>
Figure 1 from: Smith V, Rycroft S, Brake I, Scott B, Baker E, Livermore L, Blagoderov V, Roberts D (2011) Scratchpads 2.0: a Virtual Research Environment supporting scholarly collaboration, communication and data publication in biodiversity science. ZooKeys 150: 53-70. https://doi.org/10.3897/zookeys.150.2193
Figure 1 - Scratchpad usage statistics from February 2007 to September 2011. The black dashed line represents the number of Scratchpad community sites (in hundreds) and the blue solid line represents the number of registered users (in thousands). As of September 2011 we have switched to recording the number of active users (currently 4424) since this figure provides a more accurate guide to usage.
Figure 2 from: Smith V, Rycroft S, Brake I, Scott B, Baker E, Livermore L, Blagoderov V, Roberts D (2011) Scratchpads 2.0: a Virtual Research Environment supporting scholarly collaboration, communication and data publication in biodiversity science. ZooKeys 150: 53-70. https://doi.org/10.3897/zookeys.150.2193
Figure 2 - Screenshots of the Scratchpad 2 publication module showing an example workflow. Top, the section writing tool showing material and methods section; middle, the relationship selector that allows a taxon and additional materials to be associated with a section of the publication; and bottom, supplementary files such as illustrations, photos or graphs can be added to complete the publication.
Figure 3 from: Just A, Gourvil J, Millet J, Boullet V, Milon T, Mandon I, Dutrève B (2015) SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories. PhytoKeys 56: 47-60. https://doi.org/10.3897/phytokeys.56.5723
Figure 3 - Density of cells by richness of observed species: looking at the distribution within the dataset, it appears that cells with less than 250 distinct species recorded are over-represented.
Figure 4 from: Just A, Gourvil J, Millet J, Boullet V, Milon T, Mandon I, Dutrève B (2015) SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories. PhytoKeys 56: 47-60. https://doi.org/10.3897/phytokeys.56.5723
Figure 4 - Dataset completeness for Metropolitan France according to the Jackknife 1 estimator (data from 1990 to 2013). The number of records in each cell was used as an estimator of the sampling effort. The ratio between the observed and estimated richness of species measures the completeness of inventory in each surveyed cell (Vallet et al. 2012).
OpenAlex slices for "Collaboration and topic switches in Science"
<p>OpenAlex slices stored as zipped parquet files. Needs pandas >= 2, pyarrow >= 7.</p>
Files for Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation
<p>This are the files needed for running the experiments of "Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation".</p> <ul> <li> <p>listening_events.tsv.bz2 : Dataset excerpt from <a href="http://www.cp.jku.at/datasets/LFM-2b/">LFM-2b</a>, before filtering (see submission for details)</p> </li> <li> <p>BPR_item_embeddings.tsv.bz2 : Item embeddings obtained from the pre-trained BPR instance</p> </li> <li> <p>user_split.tar.bz2 : csv file of the listening history of each user</p> </li> <li> <p>2023_recsys_actr_poster.pdf ; poster presented at RecSys 2023</p> </li> </ul> <p>The code for running the experiments is available on <a href="https://github.com/hcai-mms/actr">GitHub</a><br> <br> If you use these files, please cite<br> </p> <blockquote> <p>@inproceedings{10.1145/3604915.3608838,<br> author = {Moscati, Marta and Wallmann, Christian and Reiter-Haas, Markus and Kowald, Dominik and Lex, Elisabeth and Schedl, Markus},<br> title = {Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation},<br> year = {2023},<br> isbn = {9798400702419},<br> publisher = {Association for Computing Machinery},<br> address = {New York, NY, USA},<br> url = {https://doi.org/10.1145/3604915.3608838},<br> doi = {10.1145/3604915.3608838},<br> abstract = {Music listening sessions often consist of sequences including repeating tracks. Modeling such relistening behavior with models of human memory has been proven effective in predicting the next track of a session. However, these models intrinsically lack the capability of recommending novel tracks that the target user has not listened to in the past. Collaborative filtering strategies, on the contrary, provide novel recommendations by leveraging past collective behaviors but are often limited in their ability to provide explanations. To narrow this gap, we propose four hybrid algorithms that integrate collaborative filtering with the cognitive architecture ACT-R. We compare their performance in terms of accuracy, novelty, diversity, and popularity bias, to baselines of different types, including pure ACT-R, kNN-based, and neural-networks-based approaches. We show that the proposed algorithms are able to achieve the best performances in terms of novelty and diversity, and simultaneously achieve a higher accuracy of recommendation with respect to pure ACT-R models. Furthermore, we illustrate how the proposed models can provide explainable recommendations.},<br> booktitle = {Proceedings of the 17th ACM Conference on Recommender Systems},<br> pages = {840–847},<br> numpages = {8},<br> keywords = {Music Recommender Systems, Psychology-Informed Recommender Systems, Collaborative Filtering, Adaptive Control Thought-Rational (ACT-R), Sequential Recommendation, Explainability},<br> location = {Singapore, Singapore},<br> series = {RecSys '23}<br> }</p> </blockquote> <p>This research was funded in whole, or in part, by the Austrian Science Funds (FWF): P33526 and DFH-23, and by the State of Upper Austria and the Federal Ministry of Education, Science, and Research, through grant LIT-2020-9-SEE-113.</p>
Scholarly Ecosystem Collaboration Potentialities: A SAGE White Paper Update
<p>The lifecycle of academic works from idea to investigation -- followed by publication, discovery, access, and usage -- is supported by extensive cross-sector collaboration throughout the scholarly communications ecosystem. However, transformational changes occurring worldwide within the knowledge creation and publication landscape have disturbed traditional divisions of labour and established codes of practice. These long-standing conventions and relationships among libraries, publishers, and their respective vendors are now being revisited and renegotiated.</p> <p>With the aim of furthering collaborative cross-sector conversations, SAGE commissioned a study among scholarly communications ‘value chain’ experts. Results were reported in January 2012 as a white paper titled Improving Discoverability of Scholarly Content in the Twentieth Century: Collaboration Opportunities for Librarians, Publishers, and Vendors. Since then, various commissioned studies, research reports, journal articles, international standards, conference papers, and white papers have advanced industry standards and demonstrated collaboration possibilities. Now advancements in ‘intelligent tools’ offer further promise for ‘pushing the boundaries’ of knowledge creation through synergistic relationships that enhance not only discoverability of the scholarly corpus, but also its creation, dissemination, navigation, visibility, and usage.</p>
Treat-to-target in RA: Collaboration To Improve adOption and adhereNce
ClinicalTrials.gov study NCT02260778. IPD Sharing: Not stated. Countries: 0. Publications: 23.
European Pregnancy and Paediatric Infections Cohort Collaboration (EPPICC) SARS-CoV-2 Antibody Study Protocol. Covid-19
ClinicalTrials.gov study NCT04726137. IPD Sharing: NO. Countries: 6. Publications: 0.
A Collaborative Public/Private Employment Training and Placement Model ASD Transition Age Youth With Autism Spectrum Disorder (ASD)
ClinicalTrials.gov study NCT02360332. IPD Sharing: Not stated. Countries: 0. Publications: 3.
Oral Health Status of Cystic Fibrosis Patients. An Online Survey in Collaboration With the Vaincre la Mucoviscidose Patient Association.
ClinicalTrials.gov study NCT06356246. IPD Sharing: YES. Countries: 1. Publications: 0.
Online Peer Networked Collaborative Learning for Managing Depressive Symptoms
ClinicalTrials.gov study NCT02841787. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Relative Patient Benefits of a Hospital-PCMH Collaboration Within an ACO to Improve Care Transitions
ClinicalTrials.gov study NCT02130570. IPD Sharing: YES. Countries: 1. Publications: 0.
Improving Outcomes Using Collaborative Group Clinics to Empower Older Patients
ClinicalTrials.gov study NCT00481286. IPD Sharing: Not stated. Countries: 0. Publications: 2.
Collaborative Studies on the Genetics of Asthma (CSGA)
ClinicalTrials.gov study NCT00005500. IPD Sharing: Not stated. Countries: 0. Publications: 37.
Validation Testing for Plasma Oxalate Levels in the Biochemical Laboratory at the Galilee Medical Center, in Collaboration With the Biochemistry Laboratory at CHARITE Hospital in Berlin, and Testing t
ClinicalTrials.gov study NCT06578754. IPD Sharing: NO. Countries: 0. Publications: 5.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.