Species and population specific gene expression in blood transcriptomes of marine turtles.

BACKGROUND: Transcriptomic data has demonstrated utility to advance the study of physiological diversity and organisms' responses to environmental stressors. However, a lack of genomic resources and challenges associated with collecting high-quality RNA can limit its application for many wild populations. Minimally invasive blood sampling combined with de novo transcriptomic approaches has great potential to alleviate these barriers. Here, we advance these goals for marine turtles by generating high quality de novo blood transcriptome assemblies to characterize functional diversity and compare global transcriptional profiles between tissues, species, and foraging aggregations. RESULTS: We generated high quality blood transcriptome assemblies for hawksbill (Eretmochelys imbricata), loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) turtles. The functional diversity in assembled blood transcriptomes was comparable to those from more traditionally sampled tissues. A total of 31.3% of orthogroups identified were present in all four species, representing a core set of conserved genes expressed in blood and shared across marine turtle species. We observed strong species-specific expression of these genes, as well as distinct transcriptomic profiles between green turtle foraging aggregations that inhabit areas of greater or lesser anthropogenic disturbance. CONCLUSIONS: Obtaining global gene expression data through non-lethal, minimally invasive sampling can greatly expand the applications of RNA-sequencing in protected long-lived species such as marine turtles. The distinct differences in gene expression signatures between species and foraging aggregations provide insight into the functional genomics underlying the diversity in this ancient vertebrate lineage. The transcriptomic resources generated here can be used in further studies examining the evolutionary ecology and anthropogenic impacts on marine turtles.

Use of electronic health record structured text and its payoffs. The approach and barriers to using structured text in EHR to document care encounters.

The Military Health System (MHS) deployed its electronic health record (EHR), AHLTA to Military Treatment Facilities (MTFs) around the world. This paper focuses on the approach and barriers to using structured text in AHLTA to document care encounters and illustrates the direct correlation between the use of structured text and achievement of expected benefits. AHLTA uses commercially available products, a health data dictionary and standardized medical terminology, enabling the capture of structured computable data. With structured text stored in the AHLTA Clinical Data Repository (CDR), the MHS has seen a return on its EHR investment with improvements in the accuracy and completeness of coding and the documentation of care provided. Determining the aspects of documentation where structured text is most beneficial, as well as the degree of structured text needed has been a significant challenge. This paper describes how the economic value framework aligns the enterprise strategic objectives with the EHR investment features, performance metrics and expected benefits. The framework analyses focus on return on investment calculations, baseline assessment and post-implementation benefits validation. Cost avoidance, revenue enhancements and operational improvements, such as evidence-based medicine and medical surveillance can be directly attributed to use structured text.