Search

UBC Dataverse Logo
Derivation and internal validation of a data-driven prediction model to guide frontline health workers in triaging children under-five in Nairobi, Kenya
Borealis
Mawji, Alishah; Akech, Samuel; Mwaniki, Paul; Dunsmuir, Dustin; Bone, Jeffrey; Wiens, Matthew O; Gorges, Matthias; Kimutai, David; Kissoon, Niranjan; English, Mike; Ansermino, J Mark — 2024-11-19 <br/><strong>Background:</strong> Many hospitalized children in developing countries die from infectious diseases. Early recognition of those who are critically ill coupled with timely treatment can prevent many deaths. A data-driven, electronic triage system to assist frontline health workers in categorizing illness severity is lacking. This study aimed to develop a data-driven parsimonious triage algorithm for children under five years of age. <br> <br /><strong>Methods:</strong> This was a prospective observational study of children under-five years of age presenting to the outpatient department of Mbagathi Hospital in Nairobi, Kenya between January and June 2018. A study nurse examined participants and recorded history and clinical signs and symptoms using a mobile device with an attached low-cost pulse oximeter sensor. The need for hospital admission was determined independently by the facility clinician and used as the primary outcome in a logistic predictive model. We focused on the selection of variables that could be quickly and easily assessed by low skilled health workers. <br> <br /><strong>Results:</strong> The admission rate (for more than 24 hours) was 12% (N=138/1,132). We identified an eight-predictor logistic regression model including continuous variables of weight, mid-upper arm circumference, temperature, pulse rate, and transformed oxygen saturation, combined with dichotomous signs of difficulty breathing, lethargy, and inability to drink or breastfeed. This model predicts overnight hospital admission with an area under the receiver operating characteristic curve of 0.88 (95% CI 0.82 to 0.94). Low- and high-risk thresholds of 5% and 25%, respectively were selected to categorize participants into three triage groups for implementation. <br> <br /><strong>Conclusion:</strong> A logistic regression model comprised of eight easily understood variables may be useful for triage of children under the age of five based on the probability of need for admission. This model could be used by frontline workers with limited skills in assessing children. External validation is needed before adoption in clinical practice. <br> <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.
UBC Dataverse Logo
Standard Operating Procedures for Sepsis CoLab Administrators: Dataverse Operations
Borealis
Pediatric Sepsis Data CoLaboratory — 2024-10-31 Simple step by step instructions for CoLab administrators on operating and maintaining the CoLab Dataverse. <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on <a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab">this page</a> under "collaborate with the pediatric sepsis colab."
UBC Dataverse Logo
Shade Mapping for UBC Vancouver Neighbourhood Climate Adaptation and Community Wellbeing
Borealis
Wang, Chenyao — 2024-09-24 Shade is important to urban environments as they provide comfort, reduce heat-related stress, and enhance overall wellbeing. This report presents a comprehensive study on shade mapping for Neighbourhood climate adaptation and community wellbeing within the University of British Columbia Vancouver (UBCV) campus. The primary objectives are to develop methodologies for shade mapping, identify areas with insufficient shade coverage, and provide actionable recommendations for improving shade distribution. Using high-resolution LiDAR data and sun position data, a Digital Surface Model (DSM) was created to represent campus elevation, and hillshade analysis was employed to simulate shade coverage at 15-minute intervals. Findings reveal that pedestrian areas have the highest mean shade coverage (0.69507), while concrete areas such as buildings and structures have the lowest (0.434512). Significant variations exist across Neighbourhoods, with East Campus and Hampton Place showing high, consistent shade, while Stadium and UBlvd require improvement. Bus stations also exhibit variability in shade, with UBC Exchange Bay 8 having the lowest coverage (0.160035). Recommendations include enhancing shade consistency in pedestrian areas, providing shelters in open concrete spaces, and increasing shade in Neighbourhoods like Wesbrook Place and UBlvd. Limitations of the study include the hillshade method's inability to account for shaded areas underneath trees or structures and the need for ground-truth validation. Future work should explore 3D multipatch analysis, incorporate detailed tree inventory data, and integrate shade analysis into broader urban planning efforts. This methodology-driven research aims to inspire further enhancements to the campus environment, ensuring optimized shade coverage and contributing to a more comfortable and sustainable urban landscape.
UBC Dataverse Logo
Cardiac Arrest Detection Machine Learning Dataset
Borealis
Khalili, Mahsa; Lingawi, Saud; Hutton, Jacob; Fordyce, Christopher; Christenson, Jim; Shadgan, Babak; Grunau, Brian; Kuo, Calvin — 2024-10-02 This dataset contains data, code, and the final trained machine learning models in support of the manuscript: "Detecting Cardiac States with Wearable Photoplethysmograms: Implications for Out-of-Hospital Cardiac Arrest Detection"
UBC Dataverse Logo
Smart Discharges Uganda Under 5: Phase I clinical data of children 0-6 months
Borealis
Wiens, Matthew; Businge, Stephen; Tagoola, Abner; Larson, Charles P; Moschovis, Peter P; Singer, Joel; Kumbakumba, Elias; Novakowski, Stefanie; Lavoie, Pascal; Dumont, Guy AM; Ansermino, J Mark; Kabakyenga, Jerome; Kissoon, Niranjan — 2024-10-22 This data is a subset of the Smart Discharges Uganda Under 5 years parent study and is specific to the Phase I observational cohort of children aged 0-6 months. <br> <br/><strong>Objective(s):</strong> Used as part of the Smart Discharge prediction modelling for adverse outcomes such as post-discharge death and readmission. <br> <br /><strong>Data Description:</strong> All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge. . <br> <br /><strong>Data Processing:</strong> Created z-scores for anthropometry variables using height and weight according to WHO cutoff. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components.<br> <br /><strong>Limitations:</strong> There are missing dates and the admission, discharge, and readmission dates are not in order. <br> <br /><strong>Ethics Declaration:</strong> This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on <a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab">this page</a> under "collaborate with the pediatric sepsis colab."
UBC Dataverse Logo
Statistics Canada, 2024, "HART - 2021 Census of Canada - Selected Characteristics of Households led by Older Adults for Housing Need - Canada, all provinces and territories, at the Census Division (CD), and Census Metropolitan Area (CMA) level [custom tabulation]
Borealis
Statistics Canada — 2024-10-18 <h3>Housing Assessment Resource Tools (HART)</h3> </p> <p> This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. </p> <p> Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. </p> <p> Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). </p> <p> The dataset is in Beyond 20/20 (<i>.ivt</i>) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide </p> <p> <u><b>Custom order from Statistics Canada includes the following dimensions and data fields:</b></u> </p> <p> <b>Geography: </b><br /> - Country of Canada as a whole<br /> - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole<br /> - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories<br /> - All 43 census metropolitan areas (CMAs) in Canada<br /> <p> <b>Data Quality and Suppression: </b><br /> - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released.<br /><br /> - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. <a href="https://www12.statcan.gc.ca/nhs-enm/2011/ref/DQ-QD/guide_3-eng.cfm#A_3_1">Source: Statistics Canada</a> <br/><br /> - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. </p> <p> <b>Universe:</b><br /> Full Universe: <br /> Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings.<br /><br /> Definition of Households examined for Core Housing Need: <br /> Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. </p> <p> <u><b>Data Fields:</b></u><br /> <b>Table 1:</b><br /> <br /> <b>Age / Gender (12)</b><br /> 1. Total – Population 55 years and over <br /> 2. Men+ <br /> 3. Women+ <br /> 4. 55 to 64 years<br /> 5. Men+ <br /> 6. Women+<br /> 7. 65+ years<br /> 8. Men+<br /> 9. Women+<br /> 10. 85+<br /> 11. Men+<br /> 12. Women+<br /> </p> <p> <b>Housing indicators (13)</b><br /> 1. Total – Private Households by core housing need status <br /> 2. Households below one standard only<br /> 3. Households below affordability standard only<br /> 4. Households below adequacy standard only<br /> 5. Households below suitability standard only <br /> 6. Households below two or more standards<br /> 7. Households examined for core housing need status<br /> 8. Households in core housing need status<br /> 9. Below one standard only <br /> 10. Households below affordability standard only<br /> 11. Households below adequacy standard only<br /> 12. Households below suitability standard only<br /> 13. Below 2 or more standards<br /> </p> <p> <b>Tenure Including Presence of Mortgage and Subsidized Housing (7)</b><br /> 1. Total – Tenure <br /> 2. Owner <br /> 3. With mortgage<br /> 4. Without mortgage <br /> 5. Renter <br /> 6. Subsidized housing<br /> 7. Not subsidized housing<br /> </p> <p><b>Ethnicity / Indigeneity status (24)</b><br /> 1. Total – Visible minority status of the population<br /> 2. Total visible minority status <br /> 3. South Asian <br /> 4. Chinese<br /> 5. Black<br /> 6. Filipino<br /> 7. Latin American<br /> 8. Arab<br /> 9. Southeast Asian<br /> 10. West Asian<br /> 11. Korean<br /> 12. Japanese<br /> 13. Visible minority, n.i.e.<br /> 14. Multiple visible minorities<br /> 15. Not a visible minority<br /> 16. Total – Indigenous identity status of the population <br /> 17. Indigenous identity <br /> 18. Single Indigenous responses <br /> 19. First Nations <br /> 20. Metis <br /> 21. Inuk <br /> 22. Multiple Indigenous responses <br /> 23. Indigenous responses not included elsewhere <br /> 24. Non-Indigenous identity<br /> </p> <p><b>Daily Activity Limitations / Immigration Status / Number of Bedrooms (23)</b><br /> 1. Total – Daily Activity Limitations<br /> 2. No difficulties or long-term conditions reported <br /> 3. Yes, difficulties or long-term conditions <br /> 4. Question a seeing only<br /> 5. Question b hearing only<br /> 6. Question C physical only<br /> 7. Question D cognitive only<br /> 8. Question E mental health only<br /> 9. Question F other health problem or long-term condition only<br /> 10. Yes to 2 difficulties or long term condition <br /> 11. Yes to 3 or more difficulties or long term condition<br /> 12. Not stated<br /> 13. Total – Immigrant status<br /> 14. Non-immigrant<br /> 15. Immigrant<br /> 16. Recent immigrant (Period of migration 2016 to 2021)<br /> 17. Non-permanent resident<br /> 18. Total – number of bedrooms<br /> 19. No bedrooms<br /> 20. 1 bedroom<br /> 21. 2 bedrooms<br /> 22. 3 bedrooms<br /> 23. 4 or more bedrooms<br /> </p> ---------------------------------------------------------<br /> <b>Table 2:</b><br /> <br /> <b>Age / Gender (12)</b><br /> 1. Total – Population 55 years and over <br /> 2. Men+ <br /> 3. Women+ <br /> 4. 55 to 64 years<br /> 5. Men+ <br /> 6. Women+<br /> 7. 65+ years<br /> 8. Men+<br /> 9. Women+<br /> 10. 85+<br /> 11. Men+<br /> 12. Women+<br /> </p> <p> <b>Housing indicators (13)</b><br /> 1. Total – Private Households by core housing need status <br /> 2. Households below one standard only<br /> 3. Households below affordability standard only<br /> 4. Households below adequacy standard only<br /> 5. Households below suitability standard only <br /> 6. Households below two or more standards<br /> 7. Households examined for core housing need status<br /> 8. Households in core housing need status<br /> 9. Below one standard only <br /> 10. Households below affordability standard only<br /> 11. Households below adequacy standard only<br /> 12. Households below suitability standard only<br /> 13. Below 2 or more standards<br /> </p> <p> <b>Tenure Including Presence of Mortgage and Subsidized Housing (7)</b><br /> 1. Total – Tenure <br /> 2. Owner <br /> 3. With mortgage<br /> 4. Without mortgage <br /> 5. Renter <br /> 6. Subsidized housing<br /> 7. Not subsidized housing<br /> </p> <p><b>Structural type of dwelling and Period of Construction (50)</b><br /> 1. Total – Structural type of dwelling and Period of Construction<br /> 2. 1960 or before<br /> 3. 1961 to 1980<br /> 4. 1981 to 2000<br /> 5. 2001 to 2021<br /> 6. Single-detached house<br /> 7. 1960 or before<br /> 8. 1961 to 1980<br /> 9. 1981 to 2000<br /> 10. 2001 to 2021<br /> 11. Apartment in a building that has five or more storeys<br /> 12. 1960 or before<br /> 13. 1961 to 1980<br /> 14. 1981 to 2000<br /> 15. 2001 to 2021<br /> 16. Other attached dwelling<br /> 17. 1960 or before<br /> 18. 1961 to 1980<br /> 19. 1981 to 2000<br /> 20. 2001 to 2021<br /> 21. Apartment in a flat or duplex<br /> 22. 1960 or before<br /> 23. 1961 to 1980<br /> 24. 1981 to 2000<br /> 25. 2001 to 2021<br /> 26. Apartment in a building that has fewer than five storeys<br /> 27. 1960 or before<br /> 28. 1961 to 1980<br /> 29. 1981 to 2000<br /> </p> <p><b>Daily Activity Limitations / Immigration Status / Number of Bedrooms (23)</b><br /> 1. Total – Daily Activity Limitations<br /> 2. No difficulties or long-term conditions reported <br /> 3. Yes, difficulties or long-term conditions <br /> 4. Question a seeing only<br /> 5. Question b hearing only<br /> 6. Question C physical only<br /> 7. Question D cognitive only<br /> 8. Question E mental health only<br /> 9. Question F other health problem or long-term condition only<br /> 10. Yes to 2 difficulties or long term condition <br /> 11. Yes to 3 or more difficulties or long term condition<br /> 12. Not stated<br /> 13. Total – Immigrant status<br /> 14. Non-immigrant<br /> 15. Immigrant<br /> 16. Recent immigrant (Period of migration 2016 to 2021)<br /> 17. Non-permanent resident<br /> 18. Total – number of bedrooms<br /> 19. No bedrooms<br /> 20. 1 bedroom<br /> 21. 2 bedrooms<br /> 22. 3 bedrooms<br /> 23. 4 or more bedrooms<br /> </p> <br /> <p> <u><b>File list (5 total):</b></u> </p> <p> Original data files (5):<br /> 1. ORD-08869-N8B7T2.CT.1.1 CanProvCDsYukonNunavut.ivt <br/> 2. ORD-08869-N8B7T2.CT.1.2 Can_CMAs.ivt <br/> 3. ORD-08869-N8B7T2.CT.2.1 CanProvCDsYukonNunavut.ivt <br/> 4. ORD-08869-N8B7T2.CT.2.2A Can_CMAs (excludes ON and Que).ivt <br/> 5. ORD-08869-N8B7T2.CT.2.2B Can_CMAs (only ON and Que).ivt <br/> </p> (2024)
UBC Dataverse Logo
A theoretical study on the detection of dynamic gene regulation in bulk tissue transcriptomes
Borealis
Chu, Eric Ching-Pan; Morin, Alexander; Pavlidis, Paul — 2024-10-30 Thousands of studies have used co-expression analysis of bulk tissue samples to probe gene regulation. However, the extent that intracellular regulatory signals are present in these data is unclear. Specifically, we lack clarity of the factors that promote or impede the propagation of regulatory signals from the single cell level to the bulk tissue level. To bring these issues into focus, we developed a novel computational simulator, grounded in real data, to explore the theoretical relationship between events in single cells and bulk tissue expression profiles, and clarify the conditions required for the propagation of intracellular regulatory signals in complex tissues such as the brain. Our simulator first generates single cell expression profiles and subsequently samples and aggregates these single cells to produce bulk tissue expression profiles. Using this framework, we found that there are very specific and unlikely conditions under which intracellular dynamic regulatory signals can be propagated to the bulk tissue level. For the most part, such regulatory relationships, however strong at the single cell level, are unlikely to be detectable. Our results provide a quantitative explanation for why regulatory network inference from co-expression has proved challenging - even with the assistance of other data modalities - and gives the scientific community a set of tools to further explore these issues in both single-cell and bulk tissue data. List of Tables in TSV format: <ul> <li>Supplementary Table S1. Cell type profiles</li> <li>Supplementary Table S2. Gamma model parameters</li> <li>Supplementary Table S3. Mean-variance trends</li> <li>Supplementary Table S4. Explanatory power of CSIV versus ISV</li> <li>Supplementary Table S5. Effects of dilution</li> <li>Supplementary Table S6. Cell type proportions</li> <li>Supplementary Table S7. Effects of cellular composition variability</li> <li>Supplementary Table S8. Genes modeled in CCV experiments</li> <li>Supplementary Table S9. Co-expression values in CCV experiments</li> <li>Supplementary Table S10. Co-expression values of different scenarios</li> </ul>
UBC Dataverse Logo
Scaling of the extended phenotype: convergent energetics from diverse spider web geometries.
Borealis
Greenberg-Pines, Gabriel — 2024-10-16 <b>Abstract</b> <br> Capturing enough energy to support growth, survival, and reproduction is the main challenge organisms face. Metabolic theory predicts that larger multicellular organisms require less energy per unit time and mass than smaller ones. Structures used to capture energy thus need not scale isometrically with body size. Web-building spiders rely on extended phenotypes in the form of silk webs to capture energy. Webs tend to be phylogenetically constrained composite traits, being two-dimensional, typically in the shape of orbs in some spider families, or three-dimensional, in the shape of a tangle or a sheet-and-tangle, in others. We show that the mass-specific prey-capture surface area of webs with different geometries scales in taxon-specific ways with spider body size, including hollowing of sheet-and-tangle webs to maintain isometry. The mass-specific energy consumption rate, however, scaled hypometrically with identical slopes and intercepts across all three web geometries. Although an allometric relationship between energy acquisition and body size has been shown repeatedly across metazoans, no previous studies have shown such a relationship mediated by a diverse set of extended phenotypes. Our findings support the most general trend predicted by metabolic theory while illustrating how the extended phenotypes spiders build meet their bodies’ energetic demands in diverse ways. <br> <br> <b>Usage notes</b> <br> This dataset contains the data (i.e., Trait_data.csv, Bodylength_data.csv, and Wheeler.tre) and code (i.e., Whole_analysis_models_1-2.R, Whole_analysis_models_4-9.R, Ratio_analysis_models_1-2.R, Ratio_analysis_models_4-9.R, PGLS_analysis_model_3.R, and BodyLength_analysis.R) used to generate the results and figures for the paper titled ‘Scaling of the extended phenotype: convergent energetics from diverse spider web geometries’. The files Ratio_analysis_models_1-2.R, Ratio_analysis_models_4-9.R, PGLS_analysis_model_3.R, and BodyLength_analysis.R contain the code used to generate the graphs featured in the paper. The definitions for all columns (including units) for Trait_data.csv and Bodylength_data.csv are included in the ReadMe file. The Wheeler.tre file is used to create the phylogenetic tree used in the PGLS analysis. All analyses and graphs were done in R version 4.0.2.
UBC Dataverse Logo
Population Survey Data for Coastal Giant Salamanders in the Chilliwack River Valley
Borealis
Richardson, John — 2024-09-24 The Coastal Giant Salamander (Dicamptodon tenebrosus, formerly known as Pacific giant salamander) is considered a species at risk (Assessed as Threatened by COSEWIC and red-listed by BC-CDC), and the primary putative threat in BC is forestry. Forestry operations impact both the aquatic and terrestrial habitats of the salamanders. Lack of forest cover exposes the adults to wider temperature extremes and the possibility of desiccation. Development of land for farming and settlement along Vedder Mountain and the Cultus Lake area has encroached on the B.C. distribution range of Dicamptodon tenebrosus. Adults depend on riparian forests, which are often removed by logging. In the streams, larvae (and neotenic adults) must cope with more variable stream flows, erosion and sedimentation of stream habitats, and increased water temperatures. This long-term (1994-2001) mark-recapture study of Coastal Giant Salamanders led by Dr. John Richardson (UBC) and Dr. William Neill (UBC) took place in 12 small streams in the Chilliwack River Valley, BC. This study includes survey data to assess whether forest harvest history near the streams or other geomorphic characteristics impacted density, survival, and growth rates. These data, the only long-term data using mark-recapture designs (CJS, using Lebreton design) for this species anywhere, will play a crucial role in future recovery efforts for this threatened species in Canada. The scientific value is high in understanding population dynamics and in the face of continued land use impacts and climate change, offering hope for the future of these salamanders.
UBC Dataverse Logo
Lipopolysaccharide differentially alters systemic and brain glucocorticoid levels in neonatal and adult mice
Borealis
Hamden, Jordan; Salehzadeh, Melody; Bajaj, Hitasha; Li, Michael; Soma, Kiran — 2024-11-18 We treated male and female C57BL/6J mice at postnatal day 5 (PND5) or PND90 with lipopolysaccharide (LPS; 50 µg/kg bw i.p.) or vehicle and collected blood and brain after 4 hr. We microdissected the prefrontal cortex, hippocampus, hypothalamus, and amygdala. We measured 7 steroids, including corticosterone, via liquid chromatography-tandem mass spectrometry and measured transcripts for key steroidogenic enzymes and hypothalamic-pituitary-adrenal axis components (Cyp11b1, Hsd11b1, Hsd11b2, Crh, Crhr1, Pomc) via qPCR.
UBC Dataverse Logo
“The advice? Think bigger”: Community perspectives on dairy farming, including surplus calves – an Australian focus group study
Borealis
Bolton, Sarah; Vandresen, Bianca; von Keyserlingk, M.A.G — 2024-10-02 Citizens are becoming increasingly disconnected from food production. Despite this, many people still hold strong values about how food is produced. The aim of this study was to attain an in-depth understanding of Australian public attitudes towards sustainability and animal welfare in dairy production, as well as early life killing of surplus dairy calves and cow-calf separation; issues commonly identified as being out of step with public values. We conducted three focus group sessions, each with 8 Australians that varied in age, gender identity, income, and frequency of consumption of dairy products. Thematic analysis of the semi-structured discussions resulted in two key themes, each with underlying sub-themes: 1) Animal agriculture as an industry, including sustainability, farmers as people, and farming practices; and 2) Personal impacts and reflections as citizens, including ethical considerations, and consumer behaviors.
UBC Dataverse Logo
Data for: Zircon Morphology and Geochemical Diversity During Closed-System Crystallization of the Skaergaard Intrusion
Borealis
Moerhuis, Nichole; Scoates, James S.; Weis, Dominique; Scoates, R. F. Jon; Tegner, Christian — 2024-10-22 Data from Journal of Petrology paper "Zircon Morphology and Geochemical Diversity During Closed-System Crystallization of the Skaergaard Intrusion". These are supporting information data tables that contain all data generated from this study as well as literature data compiled and used in the publication. Supplementary Appendix A contains major and minor element oxide contents in zircon from the Skaergaard intrusion measured by EPMA. Supplementary Appendix B contains the procedures utilized for LA-ICP-MS trace element analysis of zircon in this study. Supplementary Appendix C contains trace element concentrations by LA-ICP-MS of mineral separate zircon from the Skaergaard intrusion. Supplementary Appendix D contains in situ trace element concentrations in zircon from the Skaergaard intrusion measured by LA-ICP-MS. Supplementary Appendix E contains whole rock compositions of Skaergaard parental melt proxies used in rhyolite-MELTS forward geochemical models.
UBC Dataverse Logo
Gaze and Eye Movement Data in Orthostatic Hypotension Study for Parkinson’s Patients
Borealis
Keung, Sheung Man — 2024-11-01 This dataset contains detailed eye-tracking measurements from patients with Parkinson’s disease (PD) who participated in a study on orthostatic hypotension (OH). Data were recorded as patients performed a series of gaze tasks, focusing on an object positioned first on the ceiling and then on the wall, repeating this process through three sequences of lying down and sitting up. The objective was to assess eye movement characteristics, gaze stability, and pupil dynamics under repeated orthostatic challenges. This study aims to investigate the relationship between PD, OH, and potential oculomotor and autonomic nervous system impairments.
UBC Dataverse Logo
Replication Data for: Not all animal surrender is the same: Comparisons of sought support and ultimate outcomes in surrendering owners
Borealis
Ly, Lexis H; McDonald, Shelby E; Zapata, Isain; Protopopova, Alexandra — 2024-11-06 Animal shelters aim to divert intake by encouraging pet retention in homes (e.g., support services) or through alternative methods of surrender (e.g., self-rehoming); however, it remains unclear what factors contribute to decisions to seek pet support services, as well as select different methods to surrender a pet. Using a sample of 452 U.S. and Canadian public members who rehomed a dog or cat within the past five years, the present study identified groups of pet owners who share similar patterns of responses to surrender circumstances using latent class analysis. The model revealed three heterogeneous classes of surrendering pet owners distinguished largely by the reason for surrender and the length of ownership. Comparisons revealed differences across classes regarding the proportion of respondents, the pathways used to surrender, and the concerns reported by respondents during surrender. Qualitative analysis revealed that respondents wanted or sought a variety of different support services, including behavioural support, part-time care, and veterinary care. Future research should consider the heterogeneity in surrender decision-making when addressing issues of intake diversion from animal shelters.
UBC Dataverse Logo
Navigating challenges in applied animal behaviour and welfare research: A focus group study
Borealis
Vandresen, Bianca; Nogues, Emeline; von Keyserlingk, M.A.G — 2024-11-14 Academics in applied animal behaviour and welfare science may face challenges while working within the constraints imposed by institutional and regulatory frameworks. However, to our knowledge, no studies have attempted to describe the nature of these difficulties and whether there are regional differences. This database contains the supplementary materials of a focus group study with 47 delegates attending the 56th Congress of the International Society of Applied Ethology (ISAE) held in Tallinn, Estonia, in August 2023. Participants represented 33 countries covering five continents. Using a semi-structured discussion guide, participants were encouraged to discuss their challenges, proposed solutions to the identified challenges, and the role international societies could play in overcoming some of these challenges. All focus group discussions were audio-recorded, transcribed and subjected to thematic analyses. Three main themes were identified: (1) the discipline of animal behaviour and welfare, (2) conducting and sharing research, and (3) researcher welfare and networking. Participants described numerous barriers hindering their research process, originating from within their academic institutions, local governments, and journal guidelines but also arising from prejudice and other personal challenges. Many of the challenges identified were shared among all participants, regardless of region, but specific socio-demographic groups more strongly voiced some issues. While solutions were difficult to identify, many participants communicated their willingness to collaborate as a first step to striving for solutions to the identified challenges.
UBC Dataverse Logo
Smart Triage: Clinical Data - QI
Borealis
Kissoon, Niranjan; Kasyaba, Ronald; Kenya-Mugisha, Nathan; Ansermino, J Mark; Opar, Bernard; Dumont, Guy; Komugisha, Clare; Agaba, Collins; Mwaka, Savio; Pillay, Yashodani; Wiens, Matthew O — 2024-11-20 This data is from the Smart Triage + QI: A digital triaging platform to improve quality of care for critically ill children study. Data collected for this study occurred from December 2021 to July 2023. <br> <br/><strong>Objective(s):</strong> This is a pre-post intervention study involving pediatric patients presenting to the study hospitals in seek of medical care for an acute illness. The purpose of this project was to implement Smart Triage + QI to improve the quality of care at four health care facilities in Uganda. The primary objective of the program is to enable healthcare workers to recognize the most urgent children more rapidly and allocate existing resources more efficiently. The second objective is to use the proactive processes of QI to identify and examine opportunities for ongoing improvement to strengthen the health system. The study involved two phases: (I) Baseline Period, and (II) Intervention Period. Phase II also involved a community sub-study at 1 site to identify key messaging for an appropriate methods for disseminating educational materials for VHTs and caregivers on Smart Triage. <br> <br /><strong>Data Description:</strong> Data was collected at the time of triage by trained study nurses using a custom-built mobile application. All data entered into the mobile application was stored an encrypted database. Data was uploaded directly from the mobile device to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). Outcomes were obtained from facility records or telephone follow-up at 7-10 days and the data was collected electronically. Starting in June 2022, outcomes were also collected via automated follow-up (SMS/WhatsApp) messages at one site. Time-specific outcomes were tracked using an RFID tagging system with study personnel as backup. <br> <br /><strong>Limitations:</strong> There is missing data and some variables were not collected at all sites. <br> <br /><strong>Ethics Declaration:</strong> This study was approved by the Makerere University Higher Degrees research and Ethics Committee (SPH-2021-41), the Uganda National Institute of Science and Technology (HS 1745ES). <br /><strong>NOTE for restricted files:</strong> If you are not yet a CoLab member, please complete our <a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79">membership application survey</a> to gain access to restricted files within 2 business days. <br />Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at <a href = mailto:sepsiscolab@bccchr.ca>sepsiscolab@bcchr.ca</a> or visit our <a href = "https://wfpiccs.org/pediatric-sepsis-colab/">website</a>.

Map search instructions

1.Turn on the map filter by clicking the “Limit by map area” toggle.
2.Move the map to display your area of interest. Holding the shift key and clicking to draw a box allows for zooming in on a specific area. Search results change as the map moves.
3.Access a record by clicking on an item in the search results or by clicking on a location pin and the linked record title.
Note: Clusters are intended to provide a visual preview of data location. Because there is a maximum of 50 records displayed on the map, they may not be a completely accurate reflection of the total number of search results.

(Source Repository: UBC Dataverse)

Limit by:

Clear all

to