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1.
Aust J Prim Health ; 302024 Jul.
Article in English | MEDLINE | ID: mdl-38981000

ABSTRACT

Background Large datasets exist in Australia that make de-identified primary healthcare data extracted from clinical information systems available for research use. This study reviews these datasets for their capacity to provide insight into chronic disease care for Aboriginal and Torres Strait Islander peoples, and the extent to which the principles of Indigenous Data Sovereignty are reflected in data collection and governance arrangements. Methods Datasets were included if they collect primary healthcare clinical information system data, collect data nationally, and capture Aboriginal and Torres Strait Islander peoples. We searched PubMed and the public Internet for data providers meeting the inclusion criteria. We developed a framework to assess data providers across domains, including representativeness, usability, data quality, adherence with Indigenous Data Sovereignty and their capacity to provide insights into chronic disease. Datasets were assessed against the framework based on email interviews and publicly available information. Results We identified seven datasets. Only two datasets reported on chronic disease, collected data nationally and captured a substantial number of Aboriginal and Torres Strait Islander patients. No dataset was identified that captured a significant number of both mainstream general practice clinics and Aboriginal Community Controlled Health Organisations. Conclusions It is critical that more accurate, comprehensive and culturally meaningful Aboriginal and Torres Strait Islander healthcare data are collected. These improvements must be guided by the principles of Indigenous Data Sovereignty and Governance. Validated and appropriate chronic disease indicators for Aboriginal and Torres Strait Islander peoples must be developed, including indicators of social and cultural determinants of health.


Subject(s)
General Practice , Health Services, Indigenous , Native Hawaiian or Other Pacific Islander , Humans , Native Hawaiian or Other Pacific Islander/statistics & numerical data , Chronic Disease , Australia , Health Services, Indigenous/statistics & numerical data , General Practice/statistics & numerical data , General Practice/methods , Datasets as Topic , Primary Health Care/statistics & numerical data , Australian Aboriginal and Torres Strait Islander Peoples
2.
Vet Med Sci ; 6(4): 695-710, 2020 11.
Article in English | MEDLINE | ID: mdl-32432381

ABSTRACT

Puberty is a whole-body event, driven by the hypothalamic integration of peripheral signals such as leptin or IGF-1. In the process of puberty, reproductive development is simultaneous to growth, including muscle growth. To enhance our understanding of muscle function related to puberty, we performed transcriptome analyses of muscle samples from six pre- and six post-pubertal Brahman heifers (Bos indicus). Our aims were to perform differential expression analyses and co-expression analyses to derive a regulatory gene network associate with puberty. As a result, we identified 431 differentially expressed (DEx) transcripts (genes and non-coding RNAs) when comparing pre- to post-pubertal average gene expression. The DEx transcripts were compared with all expressed transcripts in our samples (over 14,000 transcripts) for functional enrichment analyses. The DEx transcripts were associated with "extracellular region," "inflammatory response" and "hormone activity" (adjusted p < .05). Inflammatory response for muscle regeneration is a necessary aspect of muscle growth, which is accelerated during puberty. The term "hormone activity" may signal genes that respond to progesterone signalling in the muscle, as the presence of this hormone is an important difference between pre- and post-pubertal heifers in our experimental design. The DEx transcript with the highest average expression difference was a mitochondrial gene, ENSBTAG00000043574 that might be another important link between energy metabolism and puberty. In the derived co-expression gene network, we identified six hub genes: CDC5L, MYC, TCF3, RUNX2, ATF2 and CREB1. In the same network, 48 key regulators of DEx transcripts were identified, using a regulatory impact factor metric. The hub gene TCF3 was also a key regulator. The majority of the key regulators (22 genes) are members of the zinc finger family, which has been implicated in bovine puberty in other tissues. In conclusion, we described how puberty may affect muscle gene expression in cattle.


Subject(s)
Cattle/genetics , Gene Expression Regulation , Muscles/metabolism , Transcription Factor 3/genetics , Animals , Cattle/metabolism , Female , Transcription Factor 3/metabolism
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