Malignant melanoma is the most aggressive form of skin cancer and has been traditionally considered difficult to treat. The worldwide incidence of melanoma has been increasing faster than any other type of cancer. Early detection, surgery, and adjuvant therapy enable improved outcomes; nonetheless, the prognosis of metastatic melanoma remains poor. Several therapies have been investigated for the treatment of melanoma; however, current treatment options for patients with metastatic disease are limited and non-curative in the majority of cases. Photodynamic therapy (PDT) has been proposed as a promising minimally invasive therapeutic procedure that employs three essential elements to induce cell death: a photosensitizer, light of a specific wavelength, and molecular oxygen. However, classical PDT has shown some drawbacks that limit its clinical application. In view of this, the use of nanotechnology has been considered since it provides many tools that can be applied to PDT to circumvent these limitations and bring new perspectives for the application of this therapy for different types of diseases. On that ground, this review focuses on the potential use of developing nanotechnologies able to bring significant benefits for anticancer PDT, aiming to reach higher efficacy and safety for patients with malignant melanoma.

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Low-cost, instrument-free colorimetric tests were developed to detect SARS-CoV-2 using plasmonic biosensors with Au nanoparticles functionalized with polyclonal antibodies (f-AuNPs). Intense color changes were noted with the naked eye owing to plasmon coupling when f-AuNPs form clusters on the virus, with high sensitivity and a detection limit of 0.28 PFU mL −1 (PFU stands for plaque-forming units) in human saliva. Plasmon coupling was corroborated with computer simulations using the finite-difference time-domain (FDTD) method. The strategies based on preparing plasmonic biosensors with f-AuNPs are robust to permit SARS-CoV-2 detection via dynamic light scattering and UV−vis spectroscopy without interference from other viruses, such as influenza and dengue viruses. The diagnosis was made with a smartphone app after processing the images collected from the smartphone camera, measuring the concentration of SARS-CoV-2. Both image processing and machine learning algorithms were found to provide COVID-19 diagnosis with 100% accuracy for saliva samples. In subsidiary experiments, we observed that the biosensor could be used to detect the virus in river waters without pretreatment. With fast responses and requiring small sample amounts (only 20 μL), these colorimetric tests can be deployed in any location within the point-of-care diagnosis paradigm for epidemiological control.

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The present work aimed to develop and evaluate a colloidal system composed of poly (DL-lactideco-glycolide) (PLGA) nanoparticles (NPs) associated with chlorambucil (CHB) and its effects on cancer cells. The nanoparticles showed %EE (>92%), a mean particle size in the range of 240 to 334 nm and zeta potential of −16.7 to −26.0 mV. In vitro release profile showed a biphasic pattern, with an initial burst for all formulations. The scanning electron microscopy of CHB-nanoparticles showed regular spherical shapes, smooth surface without aggregations. Differential scanning calorimetry thermograms, UV-vis absorption, fluorescence emission and Fourier transform infrared spectroscopy were performed showing the entrapment of the antitumoral in drug delivery system. CHB encapsulated in PLGA nanoparticles decrease the survival rates of the breast cancer cells: 68.9% reduction of cell viability on MCF-7 cell line and 59.7% on NIH3T3. Our results indicated that polymeric nanoparticles produced by classical methods are efficient drug delivery systems for CHB.