Conjugation to gold nanoparticles of methionine gamma-lyase, a cancer-starving enzyme. Physicochemical characterization of the nanocomplex for prospective nanomedicine applications.

The pyridoxal 5'-dependent enzyme methionine γ-lyase (MGL) catalyzes the degradation of methionine. This activity has been profitable to develop an antitumor agent exploiting the strict dependence of most malignant cells on the availability of methionine. Indeed, methionine depletion blocks tumor proliferation and leads to an increased susceptibility to anticancer drugs. Here, we explore the conjugation of MGL to gold nanoparticles capped with citrate (AuNPs) as a novel strategy to deliver MGL to cancer cells. Measurements of Transmission Electron Microscopy, Dynamic Light Scattering, Asymmetrical Flow Field-Flow Fractionation, X-ray Photoelectron Spectroscopy, and Circular Dichroism allowed to achieve an extensive biophysical and biochemical characterization of the MGL-AuNP complex including particle size, size distribution, MGL loading yield, enzymatic activity, and impact of gold surface on protein structure. Noticeably, we found that activity retention was improved over time for the enzyme adsorbed to AuNPs with respect to the enzyme free in solution. The acquired body of knowledge on the nanocomplex properties and this encouraging stabilizing effect upon conjugation are the necessary basis for further studies aimed at the evaluation of the therapeutic potential of MGL-AuNP complex in a biological milieu.

Incorporation of Copper Nanoparticles on Electrospun Polyurethane Membrane Fibers by a Spray Method.

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.

Raman spectroscopy and topological machine learning for cancer grading.

In the last decade, Raman Spectroscopy is establishing itself as a highly promising technique for the classification of tumour tissues as it allows to obtain the biochemical maps of the tissues under investigation, making it possible to observe changes among different tissues in terms of biochemical constituents (proteins, lipid structures, DNA, vitamins, and so on). In this paper, we aim to show that techniques emerging from the cross-fertilization of persistent homology and machine learning can support the classification of Raman spectra extracted from cancerous tissues for tumour grading. In more detail, topological features of Raman spectra and machine learning classifiers are trained in combination as an automatic classification pipeline in order to select the best-performing pair. The case study is the grading of chondrosarcoma in four classes: cross and leave-one-patient-out validations have been used to assess the classification accuracy of the method. The binary classification achieves a validation accuracy of 81% and a test accuracy of 90%. Moreover, the test dataset has been collected at a different time and with different equipment. Such results are achieved by a support vector classifier trained with the Betti Curve representation of the topological features extracted from the Raman spectra, and are excellent compared with the existing literature. The added value of such results is that the model for the prediction of the chondrosarcoma grading could easily be implemented in clinical practice, possibly integrated into the acquisition system.

Surgical margin assessment of bone tumours: A systematic review of current and emerging technologies.

Osteosarcoma is the most common malignant tumour of the bone. Complete surgical excision is critical to achieve optimal outcomes and lower recurrence rates. However, accurate assessment of tumour margins remains a challenge and multiple technologies are employed for this purpose. The aim of this study is to highlight current and emerging technologies and their efficacy in detecting clear bone margins intraoperatively, through a systematic review of the literature. The following databases were searched using the OVID platform: Medline, Embase, Global Health and Google Scholar. Studies were screened using predetermined eligibility criteria. Data was extracted based on study and patient characteristics, modes of detection, and commercial availability, followed by quality assessment. A total of 17 studies were included. The primary diagnosis varied, with osteosarcoma being reported by 9 studies. Three studies reported relapse, ranging between 17.6%-48%. Twelve studies reported non-invasive imaging as the mode of detection used, while 4 studies reported the use of frozen section. MRI and CT were found to have an accuracy of up to 93 %. Raman spectroscopy was reported to have an accuracy, sensitivity, and specificity of 69%, 58.8% and 83.3% respectively. CT had a sensitivity and specificity up to 83% and 100%, respectively. In conclusion, there seems to be high potential for the use of multimodal technologies to increase the accuracy of intraoperative margin assessment. Although imaging modalities possess a fair level of accuracy, they carry the risk of radiation exposure, are expensive, and cannot be used in-situ. Future clinical trials are needed to test the effectiveness of these technologies to measure the diagnostic accuracy and overall patient survival.

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

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.

A Copper nanoparticles-based polymeric spray coating: Nanoshield against Sars-Cov-2.

Face masks are an effective protection tool to prevent bacterial and viral transmission. However, commercial face masks contain filters made of materials that are not capable of inactivating either SARS-CoV-2. In this regard, we report the development of an antiviral coating of polyurethane and Copper nanoparticles on a face mask filter fabricated with a spray technology that is capable of inactivating more than 99% of SARS-CoV-2 particles in 30 min of contact.

Quantum biology.π-πentanglement signatures in protein-DNA interactions.

The biological functions of DNA are carried out by individual proteins that interact with specific sequences along the DNA in order to prime the molecular processes required by the cellular metabolism. Protein-DNA interactions include DNA replication, gene expression and its regulation, DNA repair, DNA restriction and modification by endonucleases, generally classified as enzymatic functions, or transcription factors functions. To find specific binding target sequences and achieve their aims, in less than one second proteins operate in symbiosis with a crowded cellular environment, identifying extremely small cognate sequences along the DNA chain, which range from 15-20 bps for repressors to 4-6 bps for restriction enzymes. In a previous work, we proposed that the extraordinary ability of proteins to identify consensus sequences on DNA in a short time appears to be dependent on specific quantum signatures such as the entanglement ofπ-πelectrons between DNA nucleotides and protein amino acids, where the couple ofπelectrons function as a radical pair, oneπelectron is located on a specific site of sequence to be identified and the other one performs a quantum walk to identify possible sites of consensus sequence. In this paper, we use the restriction endonucleases enzymes, EcoRV and EcoRI as a case study. These enzymes are able to recognize 3'-GATACT-5' or 3'-GAATCT-5' sequences, respectively. We exploit the analogy of a coin operator with a Bloch sphere to demonstrate that the entanglement betweenπ-πelectrons generated at the contacts on specific GA dimers between proteins and DNA relies on the spin of the electrons that form an initial singlet state. The latter is a maximally entangled state so that the identification of specific nucleotides is associated with the formation of singlet states. On the other hand, during the identification of subsequent GA dimers, the spin-orbit interaction on walkingπelectron induces triplet transitions so that singlet-triplet transitions should manifest an experimentally measurable effect. We propose that the possible experimental evidence of entanglement betweenπ-πelectrons may be due to the phosphorescence signal correspondence to triplet decay processes.

Exploiting gold nanoparticles for diagnosis and cancer treatments.

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.

Protein-DNA target search relies on quantum walk.

Protein-DNA interactions play a fundamental role in all life systems. A critical issue of such interactions is given by the strategy of protein search for specific targets on DNA. The mechanisms by which the protein are able to find relatively small cognate sequences, typically 15-20 base pairs (bps) for repressors, and 4-6 bps for restriction enzymes among the millions of bp of non-specific chromosomal DNA have hardly engaged researchers for decades. Recent experimental studies have generated new insights on the basic processes of protein-DNA interactions evidencing the underlying complex dynamic phenomena involved, which combine three-dimensional and one-dimensional motion along the DNA chain. It has been demonstrated that protein molecules have an extraordinary ability to find the target very quickly on the DNA chain, in some cases, with two orders of magnitude faster than the diffusion limit. This unique property of protein-DNA search mechanism is known as facilitated diffusion. Several theoretical mechanisms have been suggested to describe the origin of facilitated diffusion. However, none of such models currently has the ability to fully describe the protein search strategy. In this paper, we suggest that the ability of proteins to identify consensus sequences on DNA is based on the entanglement of π-π electrons between DNA nucleotides and protein amino acids. The π-π entanglement is based on Quantum Walk (QW), through Coin-position entanglement (CPE). First, the protein identifies a dimer belonging to the consensus sequence, and localize a π on such dimer, hence, the other π electron scans the DNA chain until the sequence is identified. Focusing on the example of recognition of consensus sequences of EcoRV or EcoRI, we will describe the quantum features of QW on protein-DNA complexes during the search strategy, such as walker quadratic spreading on a coherent superposition of different vertices and environment-supported long-time survival probability of the walker. We will employ both discrete- or continuous-time versions of QW. Biased and unbiased classical Random Walk (CRW) have been used for a long time to describe the Protein-DNA search strategy. QW, the quantum version of CRW, has been widely studied for its applications in quantum information applications. In our biological application, the walker (the protein) resides at a vertex in a graph (the DNA structural topology). Differently to CRW, where the walker moves randomly, the quantum walker can hop along the edges in the graph to reach other vertices entering coherently a superposition across different vertices spreading quadratically faster than CRW analogous evidencing the typical speed up features of the QW. When applied to a protein-DNA target search problem, QW gives the possibility to achieve the experimental diffusional motion of proteins over diffusion classical limits experienced along DNA chains exploiting quantum features such as CPE and long-time survival probability supported by the environment. In turn, we come to the conclusion that, under quantum picture, the protein search strategy does not distinguish between one-dimensional (1D) and three-dimensional (3D) cases.

Advanced Infrared Technology and Applications 2020: introduction to the feature issue.

The 2020 edition of the Applied Optics (AO) special issue on advanced infrared technology and applications (AITA) collects significantly expanded refereed papers presented at the conference of the same name, held in Florence, Italy, 16-19 September 2019. All authors who participated at the conference were contacted and invited to contribute to this special issue. The issue also was expanded to include contributions from other practitioners of IR through direct contact and a call for papers published in AO.

Contribution of Raman Spectroscopy to Diagnosis and Grading of Chondrogenic Tumors.

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.

An E-Nose for the Monitoring of Severe Liver Impairment: A Preliminary Study.

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.

In Situ Surface-Enhanced Raman Spectroscopy of Cellular Components: Theory and Experimental Results.

In the last decade, surface-enhanced Raman spectroscopy (SERS) met increasing interest in the detection of chemical and biological agents due to its rapid performance and ultra-sensitive features. Being SERS a combination of Raman spectroscopy and nanotechnology, it includes the advantages of Raman spectroscopy, providing rapid spectra collection, small sample sizes, characteristic spectral fingerprints for specific analytes. In addition, SERS overcomes low sensitivity or fluorescence interference that represents two major drawbacks of traditional Raman spectroscopy. Nanoscale roughened metal surfaces tremendously enhance the weak Raman signal due to electromagnetic field enhancement generated by localized surface plasmon resonances. In this paper, we detected label-free SERS signals for arbitrarily configurations of dimers, trimers, etc., composed of gold nanoshells (AuNSs) and applied to the mapping of osteosarcoma intracellular components. The experimental results combined to a theoretical model computation of SERS signal of specific AuNSs configurations, based on open cavity plasmonics, give the possibility to quantify SERS enhancement for overcoming spectral fluctuations. The results show that the Raman signal is locally enhanced inside the cell by AuNSs uptake and correspondent geometrical configuration generating dimers are able to enhance locally electromagnetic fields. The SERS signals inside such regions permit the unequivocal identification of cancer-specific biochemical components such as hydroxyapatite, phenylalanine, and protein denaturation due to disulfide bonds breaking between cysteine links or proline.

Raman spectroscopy of osteosarcoma cells.

Osteosarcoma is the most common primary malignant bone tumor. In the last years, several studies have demonstrated that the increase of Hydroxyapatite (HA) and Interleukin-6 (IL-6) syntheses compared to those expressed by normal osteoblasts could be used to detect the degree of malignancy of osteosarcoma cells. Conventional biochemical methods widely employed to evaluate bone cell differentiation, including normal and cancerous phenotypes, are time consuming and may require a large amount of cells. HA is a mineral form of calcium phosphate whose presence increases with maturation of osteosarcoma cells. Analogously, IL-6 is a fundamental cytokine whose production is highly increased in osteosarcoma cells. In this study, we employ Raman spectroscopy to the identification and discrimination of osteosarcoma cells from osteo-differentiated mesenchymal stromal cells (MSCs) by detecting the presence of HA and IL-6. However, while the identification of HA is facilitated by the characteristic peak at 960 cm-1, corresponding to symmetric stretching (P-O) mode, the quantification of IL-6 it is much more elusive, being its Raman signal characterized by cysteine, but also by phenylalanine, amide I II and III whose signals are common to other proteins. Supported by an accurate multivariate analysis, the results show that Raman spectroscopy is a high sensitivity technique dealing out a direct and quantitative measurement of specific mineralization levels of osteosarcoma cells. In turn, by exploiting the Surface-Enhanced Raman Scattering stimulated by internalized Gold Nanoshells (AuNSs) and combined with scanning probe microscopies, we were able to employ Raman spectroscopy to study subcellular components locally.

Advanced Infrared Technology and Applications: introduction.

This special issue of Applied Optics on Advanced Infrared Technology and Applications collects significantly expanded refereed papers presented at the conference of the same name, held in Quebec City, Canada, Sept. 27 to Sept. 30, 2017. All the authors who participated at the conference were contacted and invited to contribute to this special issue. Furthermore, the AO dedicated issue on AITA was open to contributions from other practitioners of IR, through direct contact and a call for papers published in AO.

Detection of Intracellular Gold Nanoparticles: An Overview.

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.

Near-field surface plasmon field enhancement induced by rippled surfaces.

The occurrence of plasmon resonances on metallic nanometer-scale structures is an intrinsically nanoscale phenomenon, given that the two resonance conditions (i.e., negative dielectric permittivity and large free-space wavelength in comparison with system dimensions) are realized at the same time on the nanoscale. Resonances on surface metallic nanostructures are often experimentally found by probing the structures under investigation with radiation of various frequencies following a trial-and-error method. A general technique for the tuning of these resonances is highly desirable. In this paper we address the issue of the role of local surface patterns in the tuning of these resonances as a function of wavelength and electric field polarization. The effect of nanoscale roughness on the surface plasmon polaritons of randomly patterned gold films is numerically investigated. The field enhancement and relation to specific roughness patterns is analyzed, producing many different realizations of rippled surfaces. We demonstrate that irregular patterns act as metal-dielectric-metal local nanogaps (cavities) for the resonant plasmonic field. In turn, the numerical results are compared to experimental data obtained via aperture scanning near-field optical microscopy.

Detection and localization of gold nanoshells inside cells: near-field approximation.

The optical properties of metal nanoparticles play a fundamental role for their use in a wide range of applications. In hyperthermia treatment, for example, gold nanoshells (NSs, dielectric core+gold shell) pre-embedded in a cancer cell absorb energy when exposed to appropriate wavelengths of a laser beam and heat up, thereby destroying the cancer cell. In this process, nevertheless, healthy tissues (not targeted by the NSs) along the laser path are not affected; this is because most biological soft tissues have a relatively low light absorption coefficient in the near-infrared (NIR) regions-a characteristic known as the tissue optical window. Over such a window, NIR light transmits through the tissues with scattering-limited attenuation and minimal heating, thereby avoiding damage to healthy tissues. As a consequence, the identification of NSs assumed a fundamental role for the further development of such cancer treatment. Recently, we have demonstrated the possibility to identify 100-150 nm diameter gold NSs inside mouse cells using a scanning near-optical microscope (SNOM). In this paper, we provide a numerical demonstration that the SNOM is able to locate NSs inside the cell with a particle-aperture distance of about 100 nm. This result was obtained by developing an analytical approach based on the calculation of the dyadic Green function in the near-field approximation. The implications of our findings will remarkably affect further investigations on the interaction between NSs and biological systems.

Advances in Infrared Technology and Applications: introduction.

The special issue of Applied Optics on Advanced Infrared Technology and Applications(AITA) arose out of the biannual conference of the same name, most recently held in Pisa, Italy, 29 September to 2 October, 2015.

Nanoscale rippling on polymer surfaces induced by AFM manipulation.

Nanoscale rippling induced by an atomic force microscope (AFM) tip can be observed after performing one or many scans over the same area on a range of materials, namely ionic salts, metals, and semiconductors. However, it is for the case of polymer films that this phenomenon has been widely explored and studied. Due to the possibility of varying and controlling various parameters, this phenomenon has recently gained a great interest for some technological applications. The advent of AFM cantilevers with integrated heaters has promoted further advances in the field. An alternative method to heating up the tip is based on solvent-assisted viscoplastic deformations, where the ripples develop upon the application of a relatively low force to a solvent-rich film. An ensemble of AFM-based procedures can thus produce nanoripples on polymeric surfaces quickly, efficiently, and with an unprecedented order and control. However, even if nanorippling has been observed in various distinct modes and many theoretical models have been since proposed, a full understanding of this phenomenon is still far from being achieved. This review aims at summarizing the current state of the art in the perspective of achieving control over the rippling process on polymers at a nanoscale level.