Acquired Immunodeficiency Syndrome (AIDS) is a human viral infectious disease caused by the positive-sense single-stranded (ss) RNA Human Immunodeficiency Virus (HIV) (Retroviridae family, Ortervirales order). HIV-1 can be distinguished into various worldwide spread groups and subtypes. HIV-2 also causes human immunodeficiency, which develops slowly and tends to be less aggressive. HIV-2 only partially homologates to HIV-1 despite the similar derivation. Antiretroviral therapy (ART) is the treatment approved to control HIV infection, based on multiple antiretroviral drugs that belong to different classes: (i) NNRTIs, (ii) NRTIs, (iii) PIs, (iv) INSTIs, and (v) entry inhibitors. These drugs, acting on different stages of the HIV life cycle, decrease the patient’s total burden of HIV, maintain the function of the immune system, and prevent opportunistic infections. The appearance of several strains resistant to these drugs, however, represents a problem today that needs to be addressed as best as we can. New outbreaks of strains show a widespread geographic distribution and a highly variable mortality rate, even affecting treated patients significantly. Therefore, novel treatment approaches should be explored. The present review discusses updated information on HIV-1– and HIV-2–resistant strains, including details on different mutations responsible for drug resistance.
Background: To date, in personalized medicine approaches, single-cell analyses such as circulating tumour cells (CTC) are able to reveal small structural cell modifications, and therefore can retrieve several biophysical cell properties, such as the cell dimension, the dimensional relationship between the nucleus and the cytoplasm and the optical density of cellular sub-compartments. On this basis, we present in this study a new morphological measurement approach for the detection of vital CTC from pleural washing in individual non-small cell lung cancer (NSCLC) patients. Materials and methods: After a diagnosis of pulmonary malignancy, pleural washing was collected from nine NSCLC patients. The collected samples were processed with a density gradient separation process. Light scattering analysis was performed on a single cell. The results of this analysis were used to obtain the cell’s biophysical pattern and, later on, as basis for Machine Learning (ML) on unknown samples. Results: Morphological single-cell analysis followed by ML show a predictive picture for an NSCLC patient, screening that it is possible to distinguish CTC from other cells. Moreover, we find that the proposed measurement approach was fast, reliable, label-free, identifying and count CTC in a biological fluid. Conclusions: Our findings demonstrate that CTC Biophysical Profile by Pure Light Scattering in NSCLC could be used as a promising diagnostic candidate in NSCLC patients.
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