Gold nanoparticles (AuNPs) represent a relatively simple nanosystem to be synthesised and functionalized. AuNPs offer numerous advantages over different nanomaterials, primarily due to highly optimized protocols for their production with sizes in the range 1–150 nm and shapes, spherical, nanorods (AuNRs), nanocages, nanostars or nanoshells (AuNSs), just to name a few. AuNPs possess unique properties both from the optical and chemical point of view. AuNPs can absorb and scatter light with remarkable efficiency. Their outstanding interaction with light is due to the conduction electrons on the metal surface undergoing a collective oscillation when they are excited by light at specific wavelengths. This oscillation, known as a localized surface plasmon resonance, causes the absorption and scattering intensities of AuNPs to be significantly higher than identically sized non-plasmonic nanoparticles. In addition, AuNP absorption and scattering properties can be tuned by controlling the particle size, shape, and the local refractive index near the particle surface. By the chemical side, AuNPs offer the advantage of functionalization with therapeutic agents through covalent and ionic binding, which can be useful for biomedical applications, with particular emphasis on cancer treatments. Functionalized AuNPs exhibit good biocompatibility and controllable distribution patterns when delivered in cells and tissues, which make them particularly fine candidates for the basis of innovative therapies. Currently, major available AuNP-based cancer therapeutic approaches are the photothermal therapy (PTT) or photodynamic therapy (PDT). PTT and PDT rely upon irradiation of surface plasmon resonant AuNPs (previously delivered in cancer cells) by light, in particular, in the near-infrared range. Under irradiation, AuNPs surface electrons are excited and resonate intensely, and fast conversion of light into heat takes place in about 1 ps. The cancer cells are destroyed by the induced hyperthermia, i.e. the condition under which cells are subject to temperature in the range of 41 °C–47 °C for tens of minutes. The review is focused on the description of the optical and thermal properties of AuNPs that underlie their continuous and progressive exploitation for diagnosis and cancer therapy.

In the last decade, Raman Spectroscopy has demonstrated to be a label-free and non-destructive optical spectroscopy able to improve diagnostic accuracy in cancer diagnosis. This is because Raman spectroscopic measurements can reveal a deep molecular understanding of the biochemical changes in cancer tissues in comparison with non-cancer tissues. In this pilot study, we apply Raman spectroscopy imaging to the diagnosis and grading of chondrogenic tumors, including enchondroma and chondrosarcomas of increasing histologic grades. The investigation included the analysis of areas of 50×50 μm² to approximately 200×200 μm², respectively. Multivariate statistical analysis, based on unsupervised (Principal Analysis Components) and supervised (Linear Discriminant Analysis) methods, differentiated between the various tumor samples, between cells and extracellular matrix, and between collagen and non-collagenous components. The results dealt out basic biochemical information on tumor progression giving the possibility to grade with certainty the malignant cartilaginous tumors under investigation. The basic processes revealed by Raman Spectroscopy are the progressive degrading of collagen type-II components, the formation of calcifications and the cell proliferation in tissues ranging from enchondroma to chondrosarcomas. This study highlights that Raman spectroscopy is particularly effective when cartilaginous tumors need to be subjected to histopathological analysis.

Photothermal therapy (PTT) takes advantage of unique properties of gold nanoparticles (AuNPs) (nanospheres, nanoshells (AuNSs), nanorods (AuNRs)) to destroy cancer cells or tumor tissues. This is made possible thanks principally to both to the so-called near-infrared biological transparency window, characterized by wavelengths falling in the range 700–1100 nm, where light has its maximum depth of penetration in tissue, and to the efficiency of cellular uptake mechanisms of AuNPs. Consequently, the possible identification of intracellular AuNPs plays a key role for estimating the effectiveness of PTT treatments. Here, we review the recognized detection techniques of such intracellular probes with a special emphasis to the exploitation of near-infrared biological transparency window.

The grading of cancer tissues is still one of the main challenges for pathologists. The development of enhanced analysis strategies hence becomes crucial to accurately identify and further deal with each individual case. Raman spectroscopy (RS) is a promising tool for the classification of tumor tissues as it allows us to obtain the biochemical maps of the tissues under analysis and to observe their evolution in terms of biomolecules, proteins, lipid structures, DNA, vitamins, and so on. However, its potential could be further improved by providing a classification system which would be able to recognize the sample tumor category by taking as input the raw Raman spectroscopy signal; this could provide more reliable responses in shorter time scales and could reduce or eliminate false-positive or -negative diagnoses. Deep Learning techniques have become ubiquitous in recent years, with models able to perform classification with high accuracy in most diverse fields of research, e.g., natural language processing, computer vision, medical imaging. However, deep models often rely on huge labeled datasets to produce reasonable accuracy, otherwise occurring in overfitting issues when the training data is insufficient. In this paper, we propose a chondrogenic tumor CLAssification through wavelet transform of RAman spectra (CLARA), which is able to classify with high accuracy Raman spectra obtained from bone tissues. CLARA recognizes and grades the tumors in the evaluated dataset with $97\%$ accuracy by exploiting a classification pipeline consisting of the division of the original task in two binary classification steps, where the first is performed on the original RS signals while the latter is accomplished through the use of a hybrid temporal-frequency 2D transform.

Biologically inspired to mammalian olfactory system, electronic noses became popular during the last three decades. In literature, as well as in daily practice, a wide range of applications are reported. Nevertheless, the most pioneering one has been (and still is) the assessment of the human breath composition. In this study, we used a prototype of electronic nose, called Wize Sniffer (WS) and based it on an array of semiconductor gas sensor, to detect ammonia in the breath of patients suffering from severe liver impairment. In the setting of severely impaired liver, toxic substances, such as ammonia, accumulate in the systemic circulation and in the brain. This may result in Hepatic Encephalopathy (HE), a spectrum of neuro–psychiatric abnormalities which include changes in cognitive functions, consciousness, and behaviour. HE can be detected only by specific but time-consuming and burdensome examinations, such as blood ammonia levels assessment and neuro-psychological tests. In the presented proof-of-concept study, we aimed at investigating the possibility of discriminating the severity degree of liver impairment on the basis of the detected breath ammonia, in view of the detection of HE at its early stage.

Electrospinning is an easy and versatile technique to obtain nanofibrous membranes with nanosized fibers, high porosity, and pore interconnectivity. Metal nanoparticles (e.g., Ag, Cu, ZnO) exhibit excellent biocide properties due to their size, shape, release of metal ions, or reactive oxygen species production, and thus are often used as antimicrobial agents. In this study, a combined electrospinning/spray technique was employed to fabricate electrospun polyurethane membranes loaded with copper nanoparticles at different surface densities (10, 20, 25, or 30 μg/cm²). This method allows particle deposition onto the surface of the membranes without the use of chemical agents. SEM images showed that polyurethane fibers own homogeneous thickness (around 650 nm), and that spray-deposited copper nanoparticles are evenly distributed. STEM-EDX demonstrated that copper nanoparticles are deposited onto the surface of the fibers and are not covered by polyurethane. Moreover, a uniaxial rupture test showed that particles are firmly anchored to the electrospun fibers. Antibacterial tests against model microorganisms Escherichia coli indicated that the prepared electrospun membranes possess good bactericidal effect. Finally, the antiviral activity against SARS-CoV-2 was about 90% after 1 h of direct contact. The obtained results suggested that the electrospun membranes possess antimicrobial activities and can be used in medical and industrial applications.