Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental

Evaluation of inadequate anti-retroviral treatment in patients with HIV/AIDS

INTRODUCTION: Since the emergence of antiretroviral therapy, the survival of patients infected with human immunodeficiency virus has increased. Non-adherence to this therapy is directly related to treatment failure, which allows the emergence of resistant viral strains. METHODS: A retrospective descriptive study of the antiretroviral dispensing records of 229 patients from the Center for Health Care, University Hospital, Federal University of Juiz de Fora, Brazil, was conducted between January and December 2009. RESULTS: The study aimed to evaluate patient compliance and determine if there was an association between non-adherence and the therapy. Among these patients, 63.8% were men with an average age of 44.0 ± 9.9 years. The most used treatment was a combination of 2 nucleoside reverse transcriptase inhibitors with 1 non-nucleoside reverse transcriptase inhibitor (55.5%) or with 2 protease inhibitors (28.8%). It was found that patients taking lopinavir/ritonavir with zidovudine and lamivudine had a greater frequency of inadequate treatment than those taking atazanavir with zidovudine and lamivudine (85% and 83.3%, respectively). Moreover, when the combination of zidovudine/ lamivudine was used, the patients were less compliant (χ2 = 4.468, 1 degree of freedom, p = 0.035). CONCLUSIONS: The majority of patients failed to correctly adhere to their treatment; therefore, it is necessary to implement strategies that lead to improved compliance, thus ensuring therapeutic efficacy and increased patient survival