7 research outputs found
Understanding the Use of Crisis Informatics Technology among Older Adults
Mass emergencies increasingly pose significant threats to human life, with a
disproportionate burden being incurred by older adults. Research has explored
how mobile technology can mitigate the effects of mass emergencies. However,
less work has examined how mobile technologies support older adults during
emergencies, considering their unique needs. To address this research gap, we
interviewed 16 older adults who had recent experience with an emergency
evacuation to understand the perceived value of using mobile technology during
emergencies. We found that there was a lack of awareness and engagement with
existing crisis apps. Our findings characterize the ways in which our
participants did and did not feel crisis informatics tools address human
values, including basic needs and esteem needs. We contribute an understanding
of how older adults used mobile technology during emergencies and their
perspectives on how well such tools address human values.Comment: 10 page
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Abstract C005: Inferring global ancestry using scRNA sequencing reads of the fallopian tube and ovarian cancer
Abstract Introduction Single cell RNA sequencing (scRNA-seq) is a powerful technique to profile the transcriptome of each single cell in the sample to characterize its gene expression profile. Final 10x scRNA-seq libraries are comprised of standard Illumina paired end constructs. Read 2 encodes the sequence of the actual cDNA fragment used in library preparation to amplify the RNA sequences, so read 2 is a result of transcription from the DNA encoded in a particular gene. We hypothesize that single nucleotide polymorphisms (SNPs) and global ancestry can be inferred from read 2. Methods Using the read 2, FASTQ files were mapped to the reference genome using the STAR algorithm (2-pass), subsequent steps were performed according to GATK best practices. For reference populations, we selected 2142 unrelated individuals from the 1000 genomes project with admixture >80% in a single ancestral population using k=5 ancestral populations. SNPs quality control for the FT samples and reference included call rates of < 95% or minor allele frequency (MAF) < 1% which were filtered out. Genotypes of fallopian tube (FT) cases were merged with pruned reference genotypes (markers) and intersecting SNPs were used for further analysis. Data was visualized using PCA and ADMIXTURE (k=5). Clinical and demographic variables available in our dataset included age at time of surgery, race, ethnicity, country of birth and specific germline mutation. Whole genome sequencing on the matched germline DNA of the same samples was performed as a validation step. Results A total of 34 cases underwent scRNA-seq. FT with germline mutations included seven BRCA1, seven BRCA2, five PALB2, two RAD51, two MLH1 and one ATM. Additionally, we sequenced six FT with no germline mutations and four ovarian cancer tumors. Self-identified race included 2 Asian, 9 Black, 16 White Hispanic and 6 White non-hispanic. A total of 730 382 SNPs intersected between all samples and pruned references. PCA visualization showed correlation between self-identified race and inferred global ancestry using five ancestral populations. Furthermore, there was high correlation between country of birth, position of cases in the PCA and ADMIXTURE with K=5. Conclusion Inferring global ancestry from scRNA seq reads will help estimate the genetic ancestry from data in which this variable is missing or was not captured. Genetic ancestry is a powerful tool that should be considered when generalizing gene expression results to populations. Citation Format: Alex P. Sanchez-Covarrubias, Ashlee Sealy, Dylan Thompson, David Samuel, Ayodele Omotoso, Destiny Burnett, Matthew Schlumbrecht, Sophia George. Inferring global ancestry using scRNA sequencing reads of the fallopian tube and ovarian cancer [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C005
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Variations in germline gene mutations in women diagnosed with epithelial ovarian cancer (2159)
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Insights from the tubal transcriptome on carcinogenesis in hereditary ovarian cancer: A single-cell RNA sequencing analysis (2281)
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Abstract 1968: A multiomic spatial atlas of breast cancer in women of African ancestry
Abstract The US Black population consists of both US-born Black and immigrant Black populations from the Caribbean and Africa. Normal tissues in Black individuals, independent of their country of birth or residence, are woefully understudied. Yet, Black individuals disproportionately develop aggressive pathologic diseases and are treatment refractory or resistant, thus leaing to premature deaths. In women, breast cancer is more common among US Black women, and the most common non-viral driven cancer in African and Caribbean countries. Furthermore, Black women develop this disease younger than other ancestral groups and have a higher incidence aggressive pathologies, such as metaplastic and triple-negative breast cancer. With the African-Caribbean Cancer Consortium (AC3) and Transatlantic Gynecologic Cancer Research Consortium, we have created a multiomic spatial atlas of triple-negative and other breast cancers across Africa, the Caribbean, and among US-Black individuals. We performed ultrahigh-plex RNA and protein spatial phenotyping on the PhenoCycler-Fusion (PCF). The PCF is a fast end-to-end spatial biology platform that enables whole-slide spatial readouts of RNA and protein moieties at single-cell resolution. Multiomic spatial phenotyping of tissues allowed for the detection of novel cell populations associated with a given African ancestry linking unique immune/stromal cell types to the outcome and severity of breast cancer. Here, we aim to develop a benchmark that confidently measures and interprets ancestral genomic differences at the cellular level. Deciphering the relationship between African ancestry, aggressive disease biology, and early onset will enable the characterization of the tissue composition and the proportion of cell sub-populations implicated in tumorigenesis and the interplay with germline genetics. Citation Format: Jasmine T. Plummer, Nadezhda Nikulina, Ayodele Omotoso, Destiny Burnett, Priscilla Coelho, Simone Badal, Judith Hurley, Carmen Gomez, Ha Yeun Ji, Maycon Marcao, Felipe Dezem Segato, Oliver Braubach, Sophia George. A multiomic spatial atlas of breast cancer in women of African ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1968
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Abstract A085: A comparison of the recruitment and enrollment of racially and ethnically minoritized patients in two non-interventional genetic testing studies in Florida
Abstract Objectives: To compare participation rates of minority individuals in two non-interventional genetic studies. Background: Enrollment of participants into non-interventional studies is important in understanding cancer development in minority patients. Black, Hispanic, and Latin men and women are diagnosed with aggressive forms of cancer at more advanced stages however, the underlying mechanisms leading to poor outcomes of disease is still not well understood. To understand disease development, two studies were launched. Study 1 focused on the recruitment of mutation carriers not yet diagnosed with cancer. Participants of this study were of any race and consented to the collection of fresh tissue. Participants were physician-referred and approached by the study team on the day of surgery. The patients received an explanation of the objectives and conditions of participation. Study 2 was focused on recruiting minority participants in clinic with a confirmed diagnosis of breast or prostate cancer. Participants consented to the collection of archival tissue and participants were called prior to their clinic visit and explained the objectives and conditions of participation. We compared the rates of enrollment of minority patients into these non-interventional genetic studies. Methods: Participants were Black, Hispanic/Latino(a), or White, Non-Hispanic who were mutation carriers without cancer or had an active diagnosis of ovarian, breast, or prostate cancer. The study team was composed of Latin, South, and Central American Spanish-speakers and African American Caribbeans Haitian-Creole speakers. All study materials were available in English, Haitian Creole, and Spanish. Matched recruitment was completed between the patient population and study team members who spoke English, Haitian Creole, and Spanish. The studies were assessed and compared for their methods of recruitment, participation rates, and demographics of their enrolled patient populations between December 2022 and May 2023. Results: A total of 121 men and women are included in this data analysis. 81.8% of patients approached for both studies consented to participate. 92.9% of those who consented were minorities. In Study 1, 68.6% eligible patients agreed to participate (24/35). Of the 24 patients enrolled, 41.7% (10/24) were White Hispanic/Latina, 20.8% (5/24) were Black Hispanic and non-Hispanic, 29.2% (7/24) were White non-Hispanic, and 2.7% (2/36) declined race. Of those who rejected participation, 63.6% were Black non-Hispanic. In Study 2, 87.2% (75/86) of the 86 eligible patients consented to the study. 72% (54/75) were female and 28% (21/75) were male. Of the female participants, 31.5% (17/54) were Black non-Hispanic and 68.5% (37/54) were White Hispanic/Latino. Of the male participants, 47.6% (10/21) were Black and 52.3% (11/21) were Hispanic/Latino. 63.6% of those who rejected participation were White Hispanic. Conclusions: Our results indicate that study acceptance by racially and ethnically minoritized individuals is dependent on recruitment approach and current health status. Citation Format: Destiny B. Burnett, Sandy St-Hilaire, Melissa N. Castillo, Daniela M. Zuniga Carlier, Osmaray Morales Casanova, Ashlee J. Sealy, Alex P. Sanchez, Matthew P. Schulmbrecht, Camille Ragin, Sophia George, Judith Hurley, Janaki Sharma, Alejandra Perez. A comparison of the recruitment and enrollment of racially and ethnically minoritized patients in two non-interventional genetic testing studies in Florida [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A085
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A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics
Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches were developed for single cell analysis but are often biased, manually curated and yet unproven in spatial omics. Here we apply a stemness model for assessing oncogenic states to single cell and spatial omic cancer datasets. This one-class logistic regression machine learning algorithm is used to extract transcriptomic features from non-transformed stem cells to identify dedifferentiated cell states in tumors. We found this method identifies single cell states in metastatic tumor cell populations without the requirement of cell annotation. This machine learning model identified stem-like cell populations not identified in single cell or spatial transcriptomic analysis using existing methods. For the first time, we demonstrate the application of a ML tool across five emerging spatial transcriptomic and proteomic technologies to identify oncogenic stem-like cell types in the tumor microenvironment