A novel device for investigating structure-function relationships and mechanoadaptation of biological tissues.

Exploring the structure-function relationships of cartilage on a microstructural level is crucial for tissue engineering approaches aiming to restore function. Therefore, a combination of mechanical testing with cell and tissue-level imaging would allow for longitudinal studying loading mechanisms, biological responses and mechanoadaptation of tissues at a microstructural level. This paper describes the design and validation of FELIX, a custom-built device for non-destructive image-guided micromechanical evaluation of biological tissues and tissue-engineered constructs. It combines multiphoton microscopy with non-destructive mechanical testing of native soft tissues. Ten silicone samples of the same size were mechanically tested with FELIX by different users to assess the repeatability and reproducibility. The results indicate that FELIX can successfully substitute mechanical testing protocols with a commercial device without compromising precision. Furthermore, FELIX demonstrated consistent results across repeated measurements, with very small deviations. Therefore, FELIX can be used to accurately measure biomechanical properties by different users for separate studies. Additionally, cell nuclei and collagen of porcine articular cartilage were successfully imaged under compression. Cell viability remained high in chondrocytes cultured in agarose over 21 days. Furthermore, there were no signs of contamination indicating a cell friendly, sterile environment for longitudinal studies. In conclusion, this work demonstrates that FELIX can consistently quantify mechanical measures without compromising precision. Furthermore, it is biocompatible allowing for longitudinal measurements.

Unsupervised domain adaptation for the segmentation of breast tissue in mammography images.

BACKGROUND AND OBJECTIVE: Breast density refers to the proportion of glandular and fatty tissue in the breast and is recognized as a useful factor assessing breast cancer risk. Moreover, the segmentation of the high-density glandular tissue from mammograms can assist medical professionals visualizing and localizing areas that may require additional attention. Developing robust methods to segment breast tissues is challenging due to the variations in mammographic acquisition systems and protocols. Deep learning methods are effective in medical image segmentation but they often require large quantities of labelled data. Unsupervised domain adaptation is an area of research that employs unlabelled data to improve model performance on variations of samples derived from different sources. METHODS: First, a U-Net architecture was used to perform segmentation of the fatty and glandular tissues with labelled data from a single acquisition device. Then, adversarial-based unsupervised domain adaptation methods were used to incorporate single unlabelled target domains, consisting of images from a different machine, into the training. Finally, the domain adaptation model was extended to include multiple unlabelled target domains by combining a reconstruction task with adversarial training. RESULTS: The adversarial training was found to improve the generalization of the initial model on new domain data, demonstrating clearly improved segmentation of the breast tissues. For training with multiple unlabelled domains, combining a reconstruction task with adversarial training improved the stability of the training and yielded adequate segmentation results across all domains with a single model. CONCLUSIONS: Results demonstrated the potential for adversarial-based domain adaptation with U-Net architectures for segmentation of breast tissue in mammograms coming from several devices and demonstrated that domain-adapted models could achieve a similar agreement with manual segmentations. It has also been found that combining adversarial and reconstruction-based methods can provide a simple and effective solution for training with multiple unlabelled target domains.

Reducing pressure injuries in critically ill patients by using a patient skin integrity care bundle (InSPiRE).

PURPOSE: To test an interventional patient skin integrity bundle, the InSPiRE protocol, for reducing pressure injuries in critically ill patients in an Australian adult intensive care unit. METHODS: Before and after design: patients receiving the intervention (InSPiRE protocol) were compared with a similar control group who received standard care. Data collected included demographic and clinical variables, skin assessment, presence and stage of pressure injuries, and score on the Sequential Organ Failure Assessment (SOFA). RESULTS: Overall, 207 patients were enrolled, 105 in the intervention group and 102 in the control group. Most patients were men (mean age, 55 years). The groups were similar on major demographic variables (age, SOFA scores, intensive care unit stay). Cumulative incidence of pressure injuries was significantly lower in the intervention group (18.1%) than in the control group (30.4%) for skin injuries ( [Formula: see text], P = .04) and mucous injuries (t = 3.27, P ≤ .001). Significantly fewer pressure injuries developed over time in the intervention group (log rank = 11.842, df = 1, P ≤ .001) and intervention patients had fewer skin injuries (> 3 pressure injuries/patient = 1/105) than did control patients (> 3 pressure injuries/patient = 10/102; P = .02). CONCLUSION: The intervention group, receiving the InSPiRE protocol, had a lower cumulative incidence of pressure injuries, and fewer and less severe pressure injuries that developed over time. Systematic and ongoing assessment of the patient's skin and risk for pressure injuries as well as implementation of tailored prevention measures are central to preventing pressure injuries.

Undertaking a literature review: a step-by-step approach.

Nowadays, most nurses, pre- and post-qualification, will be required to undertake a literature review at some point, either as part of a course of study, as a key step in the research process, or as part of clinical practice development or policy. For student nurses and novice researchers it is often seen as a difficult undertaking. It demands a complex range of skills, such as learning how to define topics for exploration, acquiring skills of literature searching and retrieval, developing the ability to analyse and synthesize data as well as becoming adept at writing and reporting, often within a limited time scale. The purpose of this article is to present a step-by-step guide to facilitate understanding by presenting the critical elements of the literature review process. While reference is made to different types of literature reviews, the focus is on the traditional or narrative review that is undertaken, usually either as an academic assignment or part of the research process.

Step-by-step guide to critiquing research. Part 2: Qualitative research.

As with a quantitative study, critical analysis of a qualitative study involves an in-depth review of how each step of the research was undertaken. Qualitative and quantitative studies are, however, fundamentally different approaches to research and therefore need to be considered differently with regard to critiquing. The different philosophical underpinnings of the various qualitative research methods generate discrete ways of reasoning and distinct terminology; however, there are also many similarities within these methods. Because of this and its subjective nature, qualitative research it is often regarded as more difficult to critique. Nevertheless, an evidenced-based profession such as nursing cannot accept research at face value, and nurses need to be able to determine the strengths and limitations of qualitative as well as quantitative research studies when reviewing the available literature on a topic.

Step-by-step guide to critiquing research. Part 1: quantitative research.

When caring for patients, it is essential that nurses are using the current best practice. To determine what this is, nurses must be able to read research critically. But for many qualified and student nurses, the terminology used in research can be difficult to understand, thus making critical reading even more daunting. It is imperative in nursing that care has its foundations in sound research, and it is essential that all nurses have the ability to critically appraise research to identify what is best practice. This article is a step-by-step approach to critiquing quantitative research to help nurses demystify the process and decode the terminology.

Psychological and physical well-being during unemployment: a meta-analytic study.

The authors used theoretical models to organize the diverse unemployment literature, and meta-analytic techniques were used to examine the impact of unemployment on worker well-being across 104 empirical studies with 437 effect sizes. Unemployed individuals had lower psychological and physical well-being than did their employed counterparts. Unemployment duration and sample type (school leaver vs. mature unemployed) moderated the relationship between mental health and unemployment, but the current unemployment rate and the amount of unemployment benefits did not. Within unemployed samples, work-role centrality, coping resources (personal, social, financial, and time structure), cognitive appraisals, and coping strategies displayed stronger relationships with mental health than did human capital or demographic variables. The authors identify gaps in the literature and propose directions for future unemployment research.

A covariance structure analysis of employees' response to performance feedback.

This longitudinal study used D. R. Ilgen, C. D. Fisher, and M. S. Taylor's (1979) feedback process model as a theoretical framework to determine whether a sequential chain of cognitive variables mediates an individual's response to performance feedback. One hundred two employees were surveyed 2 weeks after their performance appraisal, and performance was assessed 11 months later at the end of the review cycle. Covariance structure analysis supported the convergent and discriminant validity of the constructs underlying the model and the constellation of structural relationships. A set of cognitive variables was found to completely mediate the relationship between an individual's receipt and response to feedback. Implications for the feedback process and future research are discussed.

Assessing the construct validity of the job descriptive index: a review and meta-analysis.

The construct validity of the Job Descriptive Index (JDI) was investigated by using a meta-analysis to summarize previous empirical studies that examined antecedents, correlates, and consequences of job satisfaction. In total, 79 unique correlates with a combined total of 1,863 correlations were associated with the JDI subdimensions. The construct validity of the JDI was supported by (a) acceptable estimates of internal consistency and test-retest reliability, (b) results that conform to a nomological network of job satisfaction relationships, and (c) demonstrated convergent and discriminant validity. Contrasting results with previous meta-analytic findings offered further support for the JDI's construct validity. Limitations of the JDI and suggestions for future research are discussed.