Dual-responsive magnetic nanodroplets for controlled oxygen release via ultrasound and magnetic stimulation.

Magnetic oxygen-loaded nanodroplets (MOLNDs) are a promising class of nanomaterials dually sensitive to ultrasound and magnetic fields, which can be employed as nanovectors for drug delivery applications, particularly in the field of hypoxic tissue treatment. Previous investigations were primarily focused on the application of these hybrid systems for hyperthermia treatment, exploiting magnetic nanoparticles for heat generation and nanodroplets as carriers and ultrasound contrast agents for treatment progress monitoring. This work places its emphasis on the prospect of obtaining an oxygen delivery system that can be activated by both ultrasound and magnetic fields. To achieve this goal, Fe3O4 nanoparticles were employed to decorate and induce the magnetic vaporization of OLNDs, allowing oxygen release. We present an optimized method for preparing MOLNDs by decorating nanodroplets made of diverse fluorocarbon cores and polymeric coatings. Furthermore, we performed a series of characterizations for better understanding how magnetic decoration can influence the physicochemical properties of OLNDs. Our comprehensive analysis demonstrates the efficacy of magnetic stimulation in promoting oxygen release compared to conventional ultrasound-based methods. We emphasize the critical role of selecting the appropriate fluorocarbon core and polymeric coating to optimize the decoration process and enhance the oxygen release performance of MOLNDs.

Handling Privacy-Sensitive Medical Data With Federated Learning: Challenges and Future Directions.

Recent medical applications are largely dominated by the application of Machine Learning (ML) models to assist expert decisions, leading to disruptive innovations in radiology, pathology, genomics, and hence modern healthcare systems in general. Despite the profitable usage of AI-based algorithms, these data-driven methods are facing issues such as the scarcity and privacy of user data, as well as the difficulty of institutions exchanging medical information. With insufficient data, ML is prevented from reaching its full potential, which is only possible if the database consists of the full spectrum of possible anatomies, pathologies, and input data types. To solve these issues, Federated Learning (FL) appeared as a valuable approach in the medical field, allowing patient data to stay where it is generated. Since an FL setting allows many clients to collaboratively train a model while keeping training data decentralized, it can protect privacy-sensitive medical data. However, FL is still unable to deliver all its promises and meets the more stringent requirements (e.g., latency, security) of a healthcare system based on multiple Internet of Medical Things (IoMT). For example, although no data are shared among the participants by definition in FL systems, some security risks are still present and can be considered as vulnerabilities from multiple aspects. This paper sheds light upon the emerging deployment of FL, provides a broad overview of current approaches and existing challenges, and outlines several directions of future work that are relevant to solving existing problems in federated healthcare, with a particular focus on security and privacy issues.

Raman-dielectrophoresis goes viral: towards a rapid and label-free platform for plant virus characterization.

An innovative spectroscopic method that allows to chemically and structurally characterize viruses directly in suspension within few minutes was developed. A library of five different plant viruses was obtained combining dielectrophoresis (DEP), performed with a device specifically designed to capture and agglomerate virus particles, and Raman spectroscopy to provide a chemical fingerprint of virions. The tested viruses, purified from infected plants, were chosen for their economic impact on horticultural crops and for their different morphological and structural features. Using the Raman-DEP device, specific profiles for each virus were successfully obtained, relying on chemical differences occurring even with genetically similar viruses belonging to the same taxonomic species and morphologically indiscernible by transmission electron microscopy (TEM). Moreover, we investigated the potentiality of Raman-DEP to follow dynamic changes occurring upon heat treatment of tobacco mosaic virus (TMV) particles. Raman peak deviations linked to TMV coat protein conformation were observed upon treatment at temperatures equal or higher than 85°C, substantiating the rod-to-spherical shape transitions observed by TEM and the concomitant drastic loss of infectivity following plant inoculation. Overall, the Raman-DEP method can be useful for the characterization of virus (nano)particles, setting the basis to create a database suitable for the study of viruses or virus derived-nanoparticles relevant for the agricultural, medical, or biotechnological fields.

Molecular Aspects of the Interaction with Gram-Negative and Gram-Positive Bacteria of Hydrothermal Carbon Nanoparticles Associated with Bac8c2,5Leu Antimicrobial Peptide.

Antimicrobial peptides (AMPs) are widely studied as therapeutic agents due to their broad-spectrum efficacy against infections. However, their clinical use is hampered by the low in vivo bioavailability and systemic toxicity. Such limitations might be overcome by using appropriate drug delivery systems. Here, the preparation of a drug delivery system (DDS) by physical conjugation of an arginine-rich peptide and hydrothermal carbon nanoparticles (CNPs) has been explored, and its antimicrobial efficacy against Eschericia coli (E. coli) and Staphylococcus aureus investigated in comparison with the unloaded carrier and the free peptide. The mechanism of interaction between CNPs and the bacteria was investigated by scanning electron microscopy and a combined dielectrophoresis-Raman spectroscopy method for real-time analysis. In view of a possible systemic administration, the effect of proteins on the stability of the DDS was investigated by using albumin as a model protein. The peptide was bounded electrostatically to the CNPs surface, establishing an equilibrium modulated by pH and albumin. The DDS exhibited antimicrobial activity toward the two bacterial strains, albeit lower as compared to the free peptide. The decrease in effectiveness toward E. coli was likely due to the rapid formation of a particle-induced extracellular matrix. The present results are relevant for the future development of hydrothermal CNPs as drug delivery agents of AMPs.

On Edge Computing for Remote Pathology Consultations and Computations.

Telepathology aims to replace the pathology operations performed on-site, but current systems are limited by their prohibitive cost, or by the adopted underlying technologies. In this work, we contribute to overcoming these limitations by bringing the recent advances of edge computing to reduce latency and increase local computation abilities to the pathology ecosystem. In particular, this paper presents LiveMicro, a system whose benefit is twofold: on one hand, it enables edge computing driven digital pathology computations, such as data-driven image processing on a live capture of the microscope. On the other hand, our system allows remote pathologists to diagnosis in collaboration in a single virtual microscope session, facilitating continuous medical education and remote consultation, crucial for under-served and remote hospital or private practice. Our results show the benefits and the principles underpinning our solution, with particular emphasis on how the pathologists interact with our application. Additionally, we developed simple yet effective diagnosis-aided algorithms to demonstrate the practicality of our approach.

In situ seed-growth synthesis of silver nanoplates on glass for the detection of food contaminants by surface enhanced Raman scattering.

Seed-growth synthesis is a common strategy to prepare silver nanoplates, whose peculiar plasmonic features can be exploited for surface enhanced Raman scattering (SERS) applications. Here we describe the fabrication and characterization of SERS chips using a peculiar in situ seed growth method, yielding a dense layer of nano-objects directly on a glass slide. In this way, geometric features (i.e. shape and dimensions) of the nano-objects can be tuned by controlling the growth time, obtaining a high concentration of hot spots on the surface. In particular, the SERS response of four kinds of chips were investigated to define the best SERS configuration in terms of size of the silver nano-objects, excitation wavelength and homogeneity of the SERS response. Silver nano-plates with a seeded growth time of 60 min demonstrated remarkable results both in terms of plasmonic enhancement, with an enhancement factor (EF) of 2 × 105 using a 532 nm laser excitation, and good homogeneity of the SERS response with intra- and inter-maps RSD of 10% and 5%, respectively. In order to demonstrate application of these chips for real sample analysis, an analytical procedure for the detection of a model pesticide, i.e. thiram fungicide, was developed and applied to its detection on green apples peels. SERS measurements on 60 min seeded growth silver nano-plates chip coupled with a multivariate PLS approach demonstrated high accuracy and repeatability for thiram detection in food matrix within the European law limits.

Flexible and Transparent Substrates Based on Gold Nanoparticles and TiO2 for in Situ Bioanalysis by Surface-Enhanced Raman Spectroscopy.

Flexible and transparent substrates are emerging as low cost and easy-to-operate support for surface-enhanced Raman spectroscopy (SERS). In particular, in situ SERS detection approach for surface characterization in transmission modality can be efficiently employed for non-invasive analysis of non-planar surfaces. Here we propose a new methodology to fabricate a homogenous, transparent, and flexible SERS membrane by the assistance of a thin TiO2 porous layer deposited on the PDMS surface, which supports the uniform loading of gold nanoparticles over large area. The substrate was first characterized for homogeneity, sensitivity and repeatability using a model molecule for SERS, i.e., 7-mercapto-4-methylcoumarin. Satisfactory intra-substrate uniformity and inter-substrates repeatability was achieved, showing an RSD of 10%, and an analytical sensitivity down to 10 nM was determined with an EF of 3.4 × 105 ± 0.4 × 105. Furthermore, SERS detection of pyrimethanil (PMT), a commonly employed pesticide in crops for human consumption, was performed in situ, exploiting the optical transparency of the device, using both model surfaces and non-flat bio-samples. PMT contamination at the phytochemical concentration levels corresponding to commonly used infield doses was successfully detected on the surface of the yellow Ficus benjiamina leaves, supporting the use of this substrate for food safety in-field application.

Development of a candidate reference sample for the characterization of tip-enhanced Raman spectroscopy spatial resolution.

Tip-Enhanced Raman Spectroscopy (TERS) is a topographic and chemical analysis technique with nanoscale resolution, consisting of the combination of Scanning Probe Microscopy (SPM) and Localized Surface Plasmon Resonance (LSPR) for the enhancement of Raman scattering in the vicinity of the probe. The quantification of spatial resolution represents an important issue, and, as of now, standards for calibration are not available. In the present work a candidate reference sample for TERS measurements was fabricated. It consists of a flat, conductive gold surface with a nanometric grating of a self-assembled monolayer of Raman-active organic molecules fabricated by an optimized Electron Beam Lithography (EBL) method to replicate established SPM calibration standards. Its feasibility as a TERS standard was tested by STM-TERS imaging.