Dataset Information

Study of infectious diseases in archaeological bone material - A dataset.

ABSTRACT: Bones of human and ground sloth remains were analyzed for presence of Trypanosoma cruzi by conventional PCR using primers TC, TC1 and TC2. Sequence results amplified a fragment with the same product size as the primers (300 and 350pb). Amplified PCR product was sequenced and analyzed on GenBank, using Blast. Although these sequences did not match with these parasites they showed high amplification with species of bacteria. This article presents the methodology used and the alignment of the sequences. The display of this dataset will allow further analysis of our results and discussion presented in the manuscript "Finding the unexpected: a critical view on molecular diagnosis of infectious diseases in archaeological samples" (Pucu et al. 2017) [1].

SUBMITTER: Pucu E

PROVIDER: S-EPMC5506867 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Study of infectious diseases in archaeological bone material - A dataset.

Pucu Elisa E Cascardo Paula P Chame Marcia M Felice Gisele G Guidon Niéde N Cleonice Vergne Maria M Campos Guadalupe G Roberto Machado-Silva José J Leles Daniela D

Data in brief 20170704

Bones of human and ground sloth remains were analyzed for presence of <i>Trypanosoma cruzi</i> by conventional PCR using primers TC, TC1 and TC2. Sequence results amplified a fragment with the same product size as the primers (300 and 350pb). Amplified PCR product was sequenced and analyzed on GenBank, using Blast. Although these sequences did not match with these parasites they showed high amplification with species of bacteria. This article presents the methodology used and the alignment of th ...[more]

PMID: 28725674

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Project description:Understanding complexity in healthcare has the potential to reduce decision and treatment uncertainty. Therefore, identifying both patient and task complexity may offer better task allocation and design recommendation for next-generation health information technology system design.To identify specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians.We observed and audio recorded clinical rounds of three infectious disease teams. Thirty cases were observed for a period of four consecutive days. Transcripts were coded based on clinical complexity-contributing factors from the clinical complexity model. Ratings of complexity on day 1 for each case were collected. We then used statistical methods to identify complexity-contributing factors in relationship to perceived complexity of clinicians.A factor analysis (principal component extraction with varimax rotation) of specific items revealed three factors (eigenvalues>2.0) explaining 47% of total variance, namely task interaction and goals (10 items, 26%, Cronbach's Alpha=0.87), urgency and acuity (6 items, 11%, Cronbach's Alpha=0.67), and psychosocial behavior (4 items, 10%, Cronbach's alpha=0.55). A linear regression analysis showed no statistically significant association between complexity perceived by the physicians and objective complexity, which was measured from coded transcripts by three clinicians (Multiple R-squared=0.13, p=0.61). There were no physician effects on the rating of perceived complexity.Task complexity contributes significantly to overall complexity in the infectious diseases domain. The different complexity-contributing factors found in this study can guide health information technology system designers and researchers for intuitive design. Thus, decision support tools can help reduce the specific complexity-contributing factors. Future studies aimed at understanding clinical domain-specific complexity-contributing factors can ultimately improve task allocation and design for intuitive clinical reasoning.

Dataset Information

Study of infectious diseases in archaeological bone material - A dataset.

Publications

Study of infectious diseases in archaeological bone material - A dataset.

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