Project description:BackgroundHealthline is one of the 39 free telehealth services that Whakarongorau Aotearoa/New Zealand Telehealth Services provides to New Zealanders. In early 2021, an image upload system for viewing service user-uploaded images was implemented into the Healthline service.AimsThe aim of this research was to understand the utilisation of Healthline's image upload system by clinicians and service users in New Zealand.MethodsThis is a retrospective observational study analysing Healthline image upload data over a two-year period: March 2021 through to December 2022. A total of 40,045 images were analysed, including demographics of the service users who uploaded an image: ethnicity, age group, and area of residence. The outcome or recommendation of the Healthline call was also assessed based on whether an image was included.ResultsImages uploaded accounted for 6.0% of total Healthline calls (n = 671,564). This research found that more service users were advised to go to an Emergency Department if they did not upload an image compared to service users who used the tool (13.5% vs. 7.7%), whereas a higher proportion of service users were given a lower acuity outcome if they included an image, including visiting an Urgent Care (24.0% vs. 16.9%) and GP (36.7% vs. 24.3%).ConclusionService users who did not upload an image had a higher proportion of Emergency Department outcomes than service users who did use the tool. This image upload tool has shown the potential to decrease stress on Emergency Departments around Aotearoa, New Zealand, through increased lower acuity outcomes.
Project description:BackgroundThe Distributed Annotation System (DAS) allows merging of DNA sequence annotations from multiple sources and provides a single annotation view. A straightforward way to establish a DAS annotation server is to use the "Lightweight DAS" server (LDAS). Onto this type of server, annotations can be uploaded as flat text files in a defined format. The popular Ensembl ContigView uses the same format for the transient upload and display of user data.ResultsIn order to easily generate LDAS upload files we developed a software tool that is accessible via a web-interface http://atgc.lirmm.fr/eldasionator.html. Users can submit their DNA sequences of interest. Our program (i) aligns these sequences to the reference sequences of Ensembl, (ii) determines start and end positions of each sequence on the reference sequence, and (iii) generates a formatted annotation file. This file can be used to load any LDAS annotation server or it can be uploaded to the Ensembl ContigView.ConclusionThe eL-DASionator is an on-line tool that is intended for life-science researchers with little bioinformatics background. It conveniently generates LDAS upload files, and makes it possible to generate annotations in a standard format that permits comfortable sharing of this data.
Project description:This dataset contains peptide array information from 120 patients from 5 different cancer types using classic blinded test/train method. This array is library 1 (GPL17600).
Project description:This dataset contains peptide array information from 1516 patients from 12 different cancer types, 2 infectious diseases, and healthy controls using leave one out cross validation. This array is library 2 (GPL14921).
Project description:This dataset contains peptide array information from 120 patients from 5 different cancer types using classic blinded test/train method. This array is library 1 (GPL17600). A 1:500 dilution of human serum is added to a peptide array (GPL17600). This array is a two-up design, with 10420 peptides printed on the top and bottom of a standard glass microscope slide. Samples were run in duplicate. The average of the duplicates are listed here. 20 train and 20 blinded test samples were run.
Project description:This dataset contains peptide array information from 1516 patients from 12 different cancer types, 2 infectious diseases, and healthy controls using leave one out cross validation. This array is library 2 (GPL14921). A 1:500 dilution of human serum is added to a peptide array (GPL14921). This array is a one-up design, with 10286 peptides printed in duplicate on a standard glass microscope slide. 1516 patients samples from 14 different diseases and 1 control cohort were analyzed
Project description:Mind upload, or the digital copying of an individual brain and mind, could theoretically allow one to "live forever." If such a technology became available, who would be most likely to approve of it or condemn it? Research has shown that fear of death positively predicts the moral approval of hypothetical mind upload technology, while religiosity may have the opposite effect. We build on these findings, drawing also from work on religiosity and existential mattering as predictors of perceived meaning in one's life. In a cross-sectional study (N = 1,007), we show that existential mattering and afterlife beliefs are negatively associated with moral approval of mind upload technology: people who believe there is a soul or some form of afterlife and who also report a high level of existential mattering, are least likely to morally approve of mind upload technology. Indeed, mind uploading-if it ever becomes feasible-is a form of technology that would fundamentally redraw the existential boundaries of what it means to be human.