A qualitative study on the facilitators and barriers to adopting the N-of-1 trial methodology as part of clinical practice: potential versus implementation challenges.

Purpose: To investigate opinions among healthcare stakeholders whether implementation of the N-of-1 trial approach in clinical practice is a feasible way to optimize evidence-based treatment results for unique patients.

Methods: We interviewed clinicians, researchers, and a patient advocate ( = 13) with an interest in or experience with N-of-1 trials on the following topics: experience with N-of-1, measurement, validity and reliability, informally gathered data usability, and influence on physician-patient relationship. Interviews were analysed using qualitative, thematic analysis.

Fusion of three spectroscopic techniques for prediction of fatty acid in processed lamb.

The application of individual spectroscopic techniques for meat analysis has been widely explored. Attempts to fuse data from multiple spectroscopic instruments for meat analysis are still lacking. Comparative assessment of the performance of mid infrared (MIR), near infrared (NIR) and Raman spectroscopy to estimate fatty acid (FA) composition in processed lamb was investigated.

Evaluating low- mid- and high-level fusion strategies for combining Raman and infrared spectroscopy for quality assessment of red meat.

The implementation of Raman and infrared spectroscopy with three data fusion strategies to predict pH and % IMF content of red meat was investigated. Raman and FTIR systems were utilized to assess quality parameters of intact red meat. Quantitative models were built using PLS, with model performances assessed with respect to the determination coefficient (R), root mean square error and normalized root mean square error (NRMSEP).

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy.

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies.