Development and psychometric properties of ECPICID-AVC to measure informal caregivers’ skills when caring for older stroke survivors at home

Introduction: Informal caregivers provide a significant part of the total care needed by dependent older people poststroke. Although informal care is often the preferred option of those who provide and those who receive informal care, informal caregivers often report lack of preparation to take care of older dependent people. This article outlines the development and psychometric testing of informal caregivers’ skills when providing care to older people after a stroke – ECPICID-AVC. Design: Prospective psychometric instrument validation study. Methods: Eleven experts participated in a focus group in order to delineate, develop and validate the instrument. Data were gathered among adult informal caregivers (n = 186) living in the community in Northern Portugal from August 2013 to January 2014. Results: The 32-item scale describes several aspects of informal caregiver’s skills. The scale has eight factors: skill to feed/hydrate by nasogastric feeding, skill to assist the person in personal hygiene, skill to assist the person for transferring, skill to assist the person for positioning, skill to provide technical aids, skill to assist the person to use the toilet, skill to feed/hydrate and skill to provide technical aids for dressing/undressing. Analysis demonstrated adequate internal consistency (Cronbach’s alpha = 0.83) and good temporal stability 0.988 (0.984–0.991). Conclusion: The psychometric properties of the measurement tool showed acceptable results allowing its implementation in clinical practice by the nursing community staff for evaluating practical skills in informal caregivers when providing care to older stroke survivors living at home.

Marine Collagen/Apatite scaffolds envisaging tissue engineering applications

Despite the vast investigation and the large amount of products already available in the market to treat the different bone defects there is still a growing need to develop more advanced and complex therapeutic strategies. In this context, a mixture of Marine Hydroxyapatite-Fluorapatite:Collagen (HA-FP:ASC) seems to be a promising solution to overcome these bone defects, specifically, dental defects. HA-FP particles (20–63 μm) were obtained through pyrolysis (950°C, 12 h) of shark teeth (Isurus oxyrinchus, P. glauca), and Type I collagen was isolated from Prionace glauca skin as previously described (1). After the steps of purification, collagen was solubilized in 0.5 M acetic acid and HA-FP added producing three different formulations: were produced, 30:70, 50:50 and 70:30 of HA-FP:ASC, respectively. EDC/NHS and HMDI binding agents were used to stabilize the produced scaffolds. Mechanical properties were evaluated by compression tests. SEM analysis allowed observing the mineral deposition, after immersion in simulated body fluid and also permitted to evaluate how homogenous was the distribution of HA-FP in the different scaffold formulations, also confirmed by μ-CT assay. It was readily visible by Cytotoxicity and life/dead CLSM assays that cells were able to adhere and proliferate in the produced scaffolds. Scaffolds crosslinked with EDC/NHS showed lower cytotoxicity, being the ones chosen for further cellular evaluation.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.