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Background and Objectives: Neurological disorders like stroke, spinal cord injury (SCI), and Parkinson’s disease (PD) significantly affect global health, requiring accurate diagnosis and long-term neurorehabilitation. Artificial intelligence (AI), such as machine learning (ML), may enhance early diagnosis, personalize treatment, and optimize rehabilitation through predictive analytics, robotic systems, and brain-computer interfaces, improving outcomes for patients. This systematic review examines how AI and ML systems influence diagnosis and treatment in neurorehabilitation among neurological disorders. Materials and Methods: Studies were identified from an online search of PubMed, Web of Science, and Scopus databases with a search time range from 2014 to 2024. This review has been registered on Open OSF (n) EH9PT. Results: Recent advancements in AI and ML are revolutionizing motor rehabilitation and diagnosis for conditions like stroke, SCI, and PD, offering new opportunities for personalized care and improved outcomes. These technologies enhance clinical assessments, therapy personalization, and remote monitoring, providing more precise interventions and better long-term management. Conclusions: AI is revolutionizing neurorehabilitation, offering personalized, data-driven treatments that enhance recovery in neurological disorders. Future efforts should focus on large-scale validation, ethical considerations, and expanding access to advanced, home-based care.

Screen-printed electrodes (SPEs) are reliable, portable, affordable, and versatile electrochemical platforms for the real-time analytical monitoring of emerging analytes in the environmental, clinical, and agricultural fields. The aim of this study was to evaluate the electrochemical behavior of gold screen-printed electrodes (SPGEs) modified with molecules containing amino (Tr-N) or α-aminophosphonate (Tr-P) groups for the selective and sensitive detection of the toxic metal ions Pb2+ and Hg2+ in aqueous samples. After optimizing the analytical parameters (conditioning potential and time, deposition potential and time, pH and concentration of the supporting electrolyte), anodic square wave stripping voltammetry (SWASV) was used to evaluate and compare the electrochemical performance of bare or modified electrodes for the detection of Hg2+ and Pb2+, either alone or in their mixtures in the concentration range between 1 nM and 10 nM. A significative improvement in the detection ability of Pb2+ ions was recorded for the amino-functionalized gold sensor SPGE-N, while the presence of a phosphonate moiety in SPGE-P led to greater sensitivity towards Hg2+ ions. The developed sensors allow the detection of Pb2+ and Hg2+ with a limit of detection (LOD) of 0.41 nM and 35 pM, respectively, below the legal limits for these heavy metal ions in drinking water or food, while the sensitivity was 5.84 µA nM−1cm−2 and 10 µA nM−1cm−2, respectively, for Pb2+ and Hg2+. The reported results are promising for the development of advanced devices for the in situ and cost-effective monitoring of heavy metals, even in trace amounts, in water resources.

Background: Prostate-specific membrane antigen (PSMA) is a type II transmembrane glycoprotein overexpressed on the surface of tumor cells in most of the patients affected by prostate adenocarcinoma (PCa). However, PSMA expression has also been demonstrated in the endothelial cells of newly formed vessels of various solid tumors, suggesting a role for PSMA in neoangiogenesis. In this scenario, gallium-68 (68Ga) or fluoro-18 (18F)-labeled PSMA positron emission tomography (PET) may play a role in tumors other than PCa, generally evaluated employing other radiopharmaceuticals targeting different pathways. This review aims to investigate the detection rate of PSMA-PET compared to other radiopharmaceuticals (especially [18F]FDG) in non-prostate tumors to identify patients who may benefit from the use of such a theragnostic agent. Methods: We performed a bibliographic search on three different databases until February 2024 using the following terms: “positron emission tomography”, “PET”, “PET/CT”, “Prostate-specific membrane antigen”, “PSMA”, “non-prostate”, “not prostate cancer”, “solid tumor”, “FDG”, “Fluorodeoxyglucose”, “FAPi”, “FET”, “MET”, “DOPA”, “choline”, “FCH”, “FES”, “DOTATOC”, “DOTANOC”, and “DOTATATE”. Only original articles edited in English with at least 10 patients were included. Results: Out of a total of 120 articles, only 25 original articles comparing PSMA with other radiotracers were included in this study. The main evidence was demonstrated in renal cell carcinoma, where PSMA showed a higher detection rate compared to [18F]FDG PET/CT, with implications for patient management. PSMA PET may also improve the assessment of other entities, such as gliomas, in defining regions of early neoangiogenesis. Further data are needed to evaluate the potential role of PSMA-PET in triple-negative breast cancer as a novel therapeutic vascular target. Finally, unclear applications of PSMA-PET include thyroid and gastrointestinal tumors. Conclusions: The present review shows the potential use of PSMA-labeled PET/CT in solid tumors beyond PCa, underlining its value over other radiopharmaceuticals (mainly [18F]FDG). Prospective clinical trials with larger sample sizes are crucial to further investigate these possible clinical applications.

Current and upcoming Sun-Induced chlorophyll Fluorescence (SIF) satellite products (e.g., GOME, TROPOMI, OCO, FLEX) have medium-to-coarse spatial resolutions (i.e., 0.3–80 km) and integrate radiances from different sources into a single ground surface unit (i.e., pixel). However, intrapixel heterogeneity, i.e., different soil and vegetation fractional cover and/or different chlorophyll content or vegetation structure in a fluorescence pixel, increases the challenge in retrieving and quantifying SIF. High spatial resolution Sentinel-2 (S2) data (20 m) can be used to better characterize the intrapixel heterogeneity of SIF and potentially extend the application of satellite-derived SIF to heterogeneous areas. In the context of the COST Action Optical synergies for spatiotemporal SENsing of Scalable ECOphysiological traits (SENSECO), in which this study was conducted, we proposed direct (i.e., spatial heterogeneity coefficient, standard deviation, normalized entropy, ensemble decision trees) and patch mosaic (i.e., local Moran’s I) approaches to characterize the spatial heterogeneity of SIF collected at 760 and 687 nm (SIF760 and SIF687, respectively) and to correlate it with the spatial heterogeneity of selected S2 derivatives. We used HyPlant airborne imagery acquired over an agricultural area in Braccagni (Italy) to emulate S2-like top-of-the-canopy reflectance and SIF imagery at different spatial resolutions (i.e., 300, 20, and 5 m). The ensemble decision trees method characterized FLEX intrapixel heterogeneity best (R2 > 0.9 for all predictors with respect to SIF760 and SIF687). Nevertheless, the standard deviation and spatial heterogeneity coefficient using k-means clustering scene classification also provided acceptable results. In particular, the near-infrared reflectance of terrestrial vegetation (NIRv) index accounted for most of the spatial heterogeneity of SIF760 in all applied methods (R2 = 0.76 with the standard deviation method; R2 = 0.63 with the spatial heterogeneity coefficient method using a scene classification map with 15 classes). The models developed for SIF687 did not perform as well as those for SIF760, possibly due to the uncertainties in fluorescence retrieval at 687 nm and the low signal-to-noise ratio in the red spectral region. Our study shows the potential of the proposed methods to be implemented as part of the FLEX ground segment processing chain to quantify the intrapixel heterogeneity of a FLEX pixel and/or as a quality flag to determine the reliability of the retrieved fluorescence.

The year 2020 was definitely like no other [...]

FAPI-based radiopharmaceuticals are a novel class of tracers, mainly used for PET imaging, which have demonstrated several advantages over [18F]FDG, especially in the case of low-grade or well-differentiated tumors. We conducted this systematic review to evaluate all the studies where a head-to-head comparison had been performed to explore the potential utility of FAPI tracers in clinical practice. FAPI-based radiopharmaceuticals have shown promising results globally, in particular in detecting peritoneal carcinomatosis, but studies with wider populations are needed to better understand all the advantages of these new radiopharmaceuticals.

New technologies and materials could help in this fight against healthcare-associated infections. As the majority of these infections are caused by antibiotic-resistant bacteria, the development of materials with intrinsic antibacterial properties is a promising field of research. We combined chitosan (CS), with antibacterial properties, with polyhedral oligomeric silsesquioxanes (POSS), a biocompatible polymer with physico-chemical, mechanical, and rheological properties, creating a hydrogel using cross-linking agent genipin. The antibacterial properties of CS and CS-POSS hydrogels were investigated against nosocomial Gram-positive and Gram-negative bacteria both in terms of membrane damage and surface charge variations, and finally, the anti-biofilm property was studied through confocal microscopy. Both materials showed a good antibacterial capacity against all analyzed strains, both in suspension, with % decreases between 36.36 and 73.58 for CS and 29.86 and 66.04 for CS-POSS, and in plates with % decreases between 55.29 and 78.32 and 17.00 and 53.99 for CS and CS-POSS, respectively. The treated strains compared to the baseline condition showed an important membrane damage, which also determined a variation of surface charges, and finally, for both hydrogels, a remarkable anti-biofilm property was highlighted. Our findings showed a possible future use of these biocompatible materials in the manufacture of medical and surgical devices with intrinsic antibacterial and anti-biofilm properties.

Solid tumors are a leading cause of cancer-related deaths globally, being characterized by rapid tumor growth and local and distant metastases. The failures encountered in cancer treatment are mainly related to the complicated biology of the tumor microenvironment. Nanoparticles-based (NPs) approaches have shown the potential to overcome the limitations caused by the pathophysiological features of solid cancers, enabling the development of multifunctional systems for cancer diagnosis and therapy and allowing effective inhibition of tumor growth. Among the different classes of NPs, 2D graphene-based nanomaterials (GBNs), due to their outstanding chemical and physical properties, easy surface multi-functionalization, near-infrared (NIR) light absorption and tunable biocompatibility, represent ideal nanoplatforms for the development of theranostic tools for the treatment of solid tumors. Here, we reviewed the most recent advances related to the synthesis of nano-systems based on graphene, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs), for the development of theranostic NPs to be used for photoacoustic imaging-guided photothermal–chemotherapy, photothermal (PTT) and photodynamic therapy (PDT), applied to solid tumors destruction. The advantages in using these nano-systems are here discussed for each class of GBNs, taking into consideration the different chemical properties and possibility of multi-functionalization, as well as biodistribution and toxicity aspects that represent a key challenge for their translation into clinical use.

Airborne micro- and nanoplastics are widely spread and pose a risk to human health. The third polymer plastic most commonly produced and present in atmospheric fallout is polystyrene (PS). For these reasons and for a more realistic assessment of biological effects, we examined in-home oxidised (ox-, simulating photoaging) nPS/mPS (0.1 and 1 μm), comparing the effects with virgin ones (v-). On human alveolar cells (A549), we quantified the cellular uptake, using FITC-functionalised nPS/mPS, while cytotoxicity, changes in the acidic compartment, ROS production, mitochondrial function, and DNA damage were assessed to study the effects of internalised v- and ox-nPS/mPS. The results showed that the uptake was dose-dependent and very fast (1 h), since, at the lowest dose (1.25 µg/well), it was 20.8% and 21.8% of nPS and mPS, respectively. Compared to v-, significant ROS increases, DNA damage, and mitochondrial impairment were observed after exposure to ox-nPS/mPS. The enhancement of effects due to environmental aging processes highlighted the true potential impact on human health of these airborne pollutants.

Machine and deep learning techniques are fuelling a revolution in the health domain and are attracting the interest of many cross-disciplinary research groups all over the world [...]

In recent years, bioactive compounds have been the focus of much interest in scientific research, due to their low toxicity and extraordinary properties. However, they possess poor solubility, low chemical stability, and unsustainable bioavailability. New drug delivery systems, and among them solid lipid nanoparticles (SLNs), could minimize these drawbacks. In this work, morin (MRN)-loaded SLNs (MRN-SLNs) were prepared using a solvent emulsification/diffusion method, using two different lipids, Compritol® 888 ATO (COM) or Phospholipon® 80H (PHO). SLNs were investigated for their physical–chemical, morphological, and technological (encapsulation parameters and in vitro release) properties. We obtained spherical and non-aggregated nanoparticles with hydrodynamic radii ranging from 60 to 70 nm and negative zeta potentials (about −30 mV and −22 mV for MRN-SLNs-COM and MRN-SLNs-PHO, respectively). The interaction of MRN with the lipids was demonstrated via μ-Raman spectroscopy, X-ray diffraction, and DSC analysis. High encapsulation efficiency was obtained for all formulations (about 99%, w/w), particularly for the SLNs prepared starting from a 10% (w/w) theoretical MRN amount. In vitro release studies showed that about 60% of MRN was released within 24 h and there was a subsequent sustained release within 10 days. Finally, ex vivo permeation studies with excised bovine nasal mucosa demonstrated the ability of SLNs to act as a penetration enhancer for MRN due to the intimate contact and interaction of the carrier with the mucosa.

Idebenone (IDE), a synthetic short-chain analogue of coenzyme Q10, is a potent antioxidant able to prevent lipid peroxidation and stimulate nerve growth factor. Due to these properties, IDE could potentially be active towards cerebral disorders, but its poor water solubility limits its clinical application. Octanoyl-β-cyclodextrin is an amphiphilic cyclodextrin (ACyD8) bearing, on average, ten octanoyl substituents able to self-assemble in aqueous solutions, forming various typologies of supramolecular nanoassemblies. Here, we developed nanoparticles based on ACyD8 (ACyD8-NPs) for the potential intranasal administration of IDE to treat neurological disorders, such as Alzheimer’s Disease. Nanoparticles were prepared using the nanoprecipitation method and were characterized for their size, zeta potential and morphology. STEM images showed spherical particles, with smooth surfaces and sizes of about 100 nm, suitable for the proposed therapeutical aim. The ACyD8-NPs effectively loaded IDE, showing a high encapsulation efficiency and drug loading percentage. To evaluate the host/guest interaction, UV-vis titration, mono- and two-dimensional NMR analyses, and molecular modeling studies were performed. IDE showed a high affinity for the ACyD8 cavity, forming a 1:1 inclusion complex with a high association constant. A biphasic and sustained release of IDE was observed from the ACyD8-NPs, and, after a burst effect of about 40%, the release was prolonged over 10 days. In vitro studies confirmed the lack of toxicity of the IDE/ACyD8-NPs on neuronal SH-SY5Y cells, and they demonstrated their antioxidant effect upon H2O2 exposure, as a general source of ROS.

Prostate cancer (PCa) is the most frequently diagnosed cancer worldwide and the second most common cause of cancer-related deaths among men. Progress in molecular imaging has magnified its clinical management; however, an unmet clinical need involves the identification of new imaging biomarkers that complement the gold standard of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) in cases of clinically significant PCa that do not express PSMA. Fibroblast activation protein (FAP) is a type II transmembrane serine overexpressed in many solid cancers that can be imaged through quinoline-based PET tracers derived from an FAP inhibitor (FAPi). Preliminary results of FAPi application in PCa (in PSMA-negative lesions, and in comparison with fluorodeoxyglucose—FDG) are now available in the literature. FAP-targeting ligands for PCa are not limited to detection, but could also include therapeutic applications. In this preliminary review, we provide an overview of the clinical applications of FAPi ligands in PCa, summarising the main results and highlighting contemporary strengths and limitations.

Bicalutamide (BCL) is a nonsteroidal antiandrogen drug that represents an alternative to castration in the treatment of prostate cancer, due to its relatively long half-life and tolerable side effects. However, it possesses a very low water solubility that can affect its oral bioavailability. In this work, we developed inclusion complexes of BCL with the highly soluble hydroxypropyl-β-cyclodextrin (HP-β-CyD) and sulfobutylether-β-cyclodextrin (SBE-β-CyD) to increase the water solubility and anticancer activity of BCL. The inclusion complexes were prepared using the freeze-drying method and were then characterized in a solid state via differential scanning calorimetry and X-ray analysis and in solution via phase-solubility studies and UV-vis and NMR spectroscopy. The BCL/HP-β-CyD and BCL/SBE-β-CyD inclusion complexes were amorphous and rapidly dissolved in water. Both the 1H-NMR spectra and molecular modeling studies confirmed the penetration of the 2-(trifluoromethyl)benzonitrile ring of BCL within the cavity of both cyclodextrins (CyDs). Due to the consistent improvement of the water solubility of BCL, the inclusion complexes showed higher antiproliferative activity toward the human prostate androgen-independent cell lines, DU-145 and PC-3, with respect to free BCL. These results demonstrate the ability of HP-β-CyD and SBE-β-CyD to complex BCL, permitting the realization of liquid formulations with potentially high oral bioavailability and/or possible parenteral administration.

Cancer-targeted drug delivery systems (DDS) based on carbon nanostructures have shown great promise in cancer therapy due to their ability to selectively recognize specific receptors overexpressed in cancer cells. In this paper, we have explored a green route to synthesize nanobiochar (NBC) endowed with graphene structure from the hydrothermal carbonization (HTC) of orange peels and evaluated the suitability of this nanomaterial as a nanoplatform for cancer therapy. In order to compare the cancer-targeting ability of different widely used targeting ligands (TL), we have conjugated NBC with biotin, riboflavin, folic acid and hyaluronic acid and have tested, in vitro, their biocompatibility and uptake ability towards a human alveolar cancer cell line (A549 cells). The nanosystems which showed the best biological performances—namely, the biotin- and riboflavin- conjugated systems—have been loaded with the poorly water-soluble drug DHF (5,5-dimethyl-6a-phenyl-3-(trimethylsilyl)-6,6a-dihydrofuro[3,2-b]furan-2(5H)-one) and tested for their anticancer activity. The in vitro biological tests demonstrated the ability of both systems to internalize the drug in A549 cells. In particular, the biotin-functionalized NBC caused cell death percentages to more than double with respect to the drug alone. The reported results also highlight the positive effect of the presence of oxygen-containing functional groups, present on the NBC surface, to improve the water dispersion stability of the DDS and thus make the approach of using this nanomaterial as nanocarrier for poorly water-soluble drugs effective.

The upcoming Fluorescence Explorer (FLEX) mission will provide sun-induced fluorescence (SIF) products at unprecedented spatial resolution. Thus, accurate calibration and validation (cal/val) of these products are key to guarantee robust SIF estimates for the assessment and quantification of photosynthetic processes. In this study, we address one specific component of the uncertainty budget related to SIF retrieval: the spatial representativeness of in situ SIF observations compared to medium-resolution SIF products (e.g., 300 m pixel size). Here, we propose an approach to evaluate an optimal sampling strategy to characterise the spatial representativeness of in situ SIF observations based on high-spatial-resolution SIF data. This approach was applied for demonstration purposes to two agricultural areas that have been extensively characterized with a HyPlant airborne imaging spectrometer in recent years. First, we determined the spatial representativeness of an increasing number of sampling points with respect to a reference area (either monocultural crop fields or hypothetical FLEX pixels characterised by different land cover types). Then, we compared different sampling approaches to determine which strategy provided the most representative reference data for a given area. Results show that between 3 and 13.5 sampling points are needed to characterise the average SIF value of both monocultural fields and hypothetical FLEX pixels of the agricultural areas considered in this study. The number of sampling points tends to increase with the standard deviation of SIF of the reference area, as well as with the number of land cover classes in a FLEX pixel, even if the increase is not always statistically significant. This study contributes to guiding cal/val activities for the upcoming FLEX mission, providing useful insights for the selection of the validation site network and particularly for the definition of the best sampling scheme for each site.

The direct oxidation reaction of isoxazolidines plays an important role in organic chemistry, leading to the synthesis of biologically active compounds. In this paper, we report a computational mechanistic study of RuO4-catalyzed oxidation of differently N-substituted isoxazolidines 1a–c. Attention was focused on the endo/exo oxidation selectivity. For all the investigated compounds, the exo attack is preferred to the endo one, showing exo percentages growing in parallel with the stability order of transient carbocations found along the reaction pathway. The study has been supported by experimental data that nicely confirm the modeling results.

An increasing amount of wind turbines, especially in Europe, are reaching the end of their expected lifetimes; therefore, long data sets describing their operation are available for scholars to analyze the performance trends. On these grounds, the present work is devoted to test case studies for the evaluation and the interpretation of wind turbine performance decline with age. Two wind farms were studied, featuring widely employed wind turbine models: the former is composed of 6 Senvion MM92 and the latter of 11 Vestas V52 wind turbines, owned by the ENGIE Italia company. SCADA data spanning, respectively, 10 and 7 years were analyzed for the two test cases. The effect of aging on the performance of the test case wind turbines was studied by constructing a data-driven model of appropriate operation curves, selected depending on the working region. For the Senvion MM92, we found that it is questionable to talk about performance aging because there is no evident trend in time: the performance variation year by year is in the order of a few kW and is therefore irrelevant for practical applications. For the Vestas V52 wind turbines, a much wider variability is observed: two wind turbines are affected by a remarkable performance drop, after which the behavior is stable and under-performing with respect to the rest of the wind farm. Particular attention is devoted to the interpretation of the results: the comparative discussion of the two test cases indicates that the observed operation curves are compatible with the hypothesis that the worsening with age of the two under-performing Vestas V52 can be ascribed to the behavior of the hydraulic blade pitch. Furthermore, for both test cases, it is estimated that the gearbox-aging contributes negligibly to the performance decline in time.

Multiple Sclerosis (MS) is a well-known, chronic demyelinating disease of the Central Nervous System (CNS) and one of the most common causes of disability in young adults. In this context, one of the major challenges in patients’ rehabilitation is to maintain the gained motor abilities in terms of functional independence. This could be partially obtained by applying new emerging and cutting-edge virtual/augmented reality and serious game technologies for a playful, noninvasive treatment that was demonstrated to be quite efficient and effective in enhancing the clinical status of patients and their (re)integration into society. Recently, Cloud computing and Internet of Things (IoT) emerged as technologies that can potentially revolutionize patients’ care. To achieve such a goal, a system that on one hand gathers patients’ clinical parameters through a network of medical IoT devices equipped with sensors and that, on the other hand, sends the collected data to a hospital Cloud for processing and analytics is required. In this paper, we assess the effectiveness of a Nintendo Wii Fit® Plus Balance Board (WFBB) used as an IoT medical device adopted in a rehabilitation training program aimed at improving the physical abilities of MS patients (pwMS). In particular, the main scientific contribution of this paper is twofold: (i) to present a preliminary new pilot study investigating whether exercises based on the Nintendo Wii Fit® balance board included in a rehabilitation training program could improve physical abilities and Quality of Life (QoL) of patients compared to that of a conventional four-week rehabilitation training program; (ii) to discuss how such a rehabilitation training program could be adopted in the perspective of near future networks of medical IoT-based rehabilitation devices, interconnected with a hospital Cloud system for big data processing to improve patients’ therapies and support the scientific research about motor rehabilitation. Results demonstrate the advantages of our approach from both health and technological points of view.

The concentration of sodium and potassium ions in biological fluids, such as blood, urine and sweat, is indicative of several basic body function conditions. Therefore, the development of simple methods able to detect these alkaline ions is of outmost importance. In this study, we explored the electrochemical and optical properties of graphene quantum dots (GQDs) combined with the selective chelating ability of the crown ethers 15-crown-5 and 18-crown-6, with the final aim to propose novel composites for the effective detection of these ions. The results obtained comparing the performances of the single GQDs and crown ethers with those of the GQDs-15-crown-5 and GQDs-18-crown-6 composites, have demonstrated the superior properties of these latter. Electrochemical investigation showed that the GQDs based composites can be exploited for the potentiometric detection of Na+ and K+ ions, but selectivity still remains a concern. The nanocomposites showed the characteristic fluorescence emissions of GQDs and crown ethers. The GQDs-18-crown-6 composite exhibited ratiometric fluorescence emission behavior with the variation of K+ concentration, demonstrating its promising properties for the development of a selective fluorescent method for potassium determination.

Health is one of the major research topics that has been attracting cross-disciplinary research groups [...]

A series of azastilbene derivatives, characterized by the presence of the 1,2,4-oxadiazole-5-one system as a linker of the two aromatic rings of stilbenes, have been prepared as novel potential inhibitors of p38 MAPK. Biological assays indicated that some of the synthesized compounds are endowed with good inhibitory activity towards the kinase. Molecular modeling data support the biological results showing that the designed compounds possess a reasonable binding mode in the ATP binding pocket of p38α kinase with a good binding affinity.

Nowadays, the penetration of sensors and actuators in different application fields is revolutionizing all aspects of our daily life. One of the major sectors that is taking advantage of such cutting-edge cheap smart devices is healthcare. In this context, Remote Patient Monitoring (RPM) at home represents a tempting opportunity for hospitals to reduce clinical costs and to improve the quality of life of both patients and their families. It allows patients to be monitored remotely by means networks of Internet of Things (IoT) medical devices equipped with sensors and actuators that collect healthcare data from patients and send them to a Cloud-based Hospital Information System (HIS) for processing. Up to now, many different proprietary software systems have been developed as stand-along expensive solutions, presenting interoperability, extensibility, and scalability issues. In recent years, the European Commission (EC) has promoted the wide adoption of FIWARE technology, launching 16 Industrial Accelerators focusing on different application fields. One of these, i.e., FICHe, is specialized in healthcare, providing the guidelines on how to develop eHealth systems. This paper focuses on how to compose new cutting-edge IoT and Cloud-based Cyber Physical Health Sytem (CPHS) services and applications interconnected with remote medical sensors and actuators using FIWARE technology in the context envisioned by FICHe. In particular, we discuss the design and development of an RPM system implemented through the collaboration between the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) “Bonino Pulejo” (i.e., a clinical and research healthcare centre specialized in the treatment of neuro lesions), University of Messina, IBM Research, Telefónica, and the University of the Western Cape in South Africa. The description of our best practice provides a model and guidelines for the development of lightweight and low cost RPM services for rural and isolated areas, with the expectation of expanding healthcare to the developing world and in general allows us to outline how to deal with the real adoption of the FIWARE technology in an e-health project.

Due to their outstanding physicochemical properties, the next generation of the graphene family—graphene quantum dots (GQDs)—are at the cutting edge of nanotechnology development. GQDs generally possess many hydrophilic functionalities which allow their dispersibility in water but, on the other hand, could interfere with reactions that are mainly performed in organic solvents, as for cycloaddition reactions. We investigated the 1,3-dipolar cycloaddition (1,3-DCA) reactions of the C-ethoxycarbonyl N-methyl nitrone 1a and the newly synthesized C-diethoxyphosphorylpropilidene N-benzyl nitrone 1b with the surface of GQDs, affording the isoxazolidine cycloadducts isox-GQDs 2a and isox-GQDs 2b. Reactions were performed in mild and eco-friendly conditions, through the use of a natural deep eutectic solvent (NADES), free of chloride or any metal ions in its composition, and formed by the zwitterionic trimethylglycine as the -bond acceptor, and glycolic acid as the hydrogen-bond donor. The results reported in this study have for the first time proved the possibility of performing cycloaddition reactions directly to the p-cloud of the GQDs surface. The use of DES for the cycloaddition reactions on GQDs, other than to improve the solubility of reactants, has been shown to bring additional advantages because of the great affinity of these green solvents with aromatic systems.

Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest scientific contributions, some of which are being developed within the frame of the Training on Remote Sensing for Ecosystem Modelling (TRuStEE) program. Investigations from the Universities of Edinburgh (School of Geosciences) and Tasmania (School of Technology, Environments and Design) are first presented, both sharing the principle of the spectroradiometer optical path bifurcation throughout, the so called ‘Piccolo-Doppio’ and ‘AirSIF’ systems, respectively. Furthermore, JB Hyperspectral Devices’ ongoing investigations towards the closest possible characterization of the atmospheric interference suffered by orbital platforms are outlined. The latest approach focuses on the observation of one single ground point across a multiple-kilometer atmosphere vertical column using the high altitude UAS named as AirFloX, mounted on a specifically designed and manufactured fixed wing platform: ‘FloXPlane’. We present technical details and preliminary results obtained from each instrument, a summary of their main characteristics, and finally the remaining challenges and open research questions are addressed. On the basis of the presented findings, the consensus is that SIF can be retrieved from low altitude spectroscopy. However, the UAS-based methods for SIF retrieval still present uncertainties associated with the current sensor characteristics and the spatio-temporal mismatching between aerial and ground measurements, which complicate robust validations. Complementary studies regarding the standardization of calibration methods and the characterization of spectroradiometers and data processing workflows are also required. Moreover, other open research questions such as those related to the implementation of atmospheric correction, bidirectional reflectance distribution function (BRDF) correction, and accurate surface elevation models remain to be addressed.

In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform.

Compact multi-spectral sensors that can be mounted on lightweight drones are now widely available and applied within the geo- and environmental sciences. However; the spatial consistency and radiometric quality of data from such sensors is relatively poorly explored beyond the lab; in operational settings and against other sensors. This study explores the extent to which accurate hemispherical-conical reflectance factors (HCRF) and vegetation indices (specifically: normalised difference vegetation index (NDVI) and chlorophyll red-edge index (CHL)) can be derived from a low-cost multispectral drone-mounted sensor (Parrot Sequoia). The drone datasets were assessed using reference panels and a high quality 1 m resolution reference dataset collected near-simultaneously by an airborne imaging spectrometer (HyPlant). Relative errors relating to the radiometric calibration to HCRF values were in the 4 to 15% range whereas deviations assessed for a maize field case study were larger (5 to 28%). Drone-derived vegetation indices showed relatively good agreement for NDVI with both HyPlant and Sentinel 2 products (R2 = 0.91). The HCRF; NDVI and CHL products from the Sequoia showed bias for high and low reflective surfaces. The spatial consistency of the products was high with minimal view angle effects in visible bands. In summary; compact multi-spectral sensors such as the Parrot Sequoia show good potential for use in index-based vegetation monitoring studies across scales but care must be taken when assuming derived HCRF to represent the true optical properties of the imaged surface.

Nowadays, we are observing a growing interest about Big Data applications in different healthcare sectors. One of this is definitely cardiology. In fact, electrocardiogram produces a huge amount of data about the heart health status that need to be stored and analysed in order to detect a possible issues. In this paper, we focus on the arrhythmia detection problem. Specifically, our objective is to address the problem of distributed processing considering big data generated by electrocardiogram (ECG) signals in order to carry out pre-processing analysis. Specifically, an algorithm for the identification of heartbeats and arrhythmias is proposed. Such an algorithm is designed in order to carry out distributed processing over the Cloud since big data could represent the bottleneck for cardiology applications. In particular, we implemented the Menard algorithm in Apache Spark in order to process big data coming form ECG signals in order to identify arrhythmias. Experiments conducted using a dataset provided by the Physionet.org European ST-T Database show an improvement in terms of response times. As highlighted by our outcomes, our solution provides a scalable and reliable system, which may address the challenges raised by big data in healthcare.

Retrieval of Sun-Induced Chlorophyll Fluorescence (F) spectrum is one of the challenging perspectives for further advancing F studies towards a better characterization of vegetation structure and functioning. In this study, a simplified Spectral Fitting retrieval algorithm suitable for retrieving the F spectrum with a limited number of parameters is proposed (two parameters for F). The novel algorithm is developed and tested on a set of radiative transfer simulations obtained by coupling SCOPE and MODTRAN5 codes, considering different chlorophyll content, leaf area index and noise levels to produce a large variability in fluorescence and reflectance spectra. The retrieval accuracy is quantified based on several metrics derived from the F spectrum (i.e., red and far-red peaks, O2 bands and spectrally-integrated values). Further, the algorithm is employed to process experimental field spectroscopy measurements collected over different crops during a long-lasting field campaign. The reliability of the retrieval algorithm on experimental measurements is evaluated by cross-comparison with F values computed by an independent retrieval method (i.e., SFM at O2 bands). For the first time, the evolution of the F spectrum along the entire growing season for a forage crop is analyzed and three diverse F spectra are identified at different growing stages. The results show that red F is larger for young canopy; while red and far-red F have similar intensity in an intermediate stage; finally, far-red F is significantly larger for the rest of the season.

Hyperspectral remote sensing (RS) provides unique possibilities to monitor peatland vegetation traits and their temporal dynamics at a fine spatial scale. Peatlands provide a vital contribution to ecosystem services by their massive carbon storage and wide heterogeneity. However, monitoring, understanding, and disentangling the diverse vegetation traits from a heterogeneous landscape using complex RS signal is challenging, due to its wide biodiversity and distinctive plant species composition. In this work, we aim to demonstrate, for the first time, the large heterogeneity of peatland vegetation traits using well-established vegetation indices (VIs) and Sun-Induced Fluorescence (SIF) for describing the spatial heterogeneity of the signals which may correspond to spatial diversity of biochemical and structural traits. SIF originates from the initial reactions in photosystems and is emitted at wavelengths between 650−780 nm, with the first peak at around 687 nm and the second peak around 760 nm. We used the first HyPlant airborne data set recorded over a heterogeneous peatland area and its surrounding ecosystems (i.e., forest, grassland) in Poland. We deployed a comparative analysis of SIF and VIs obtained from differently managed and natural vegetation ecosystems, as well as from diverse small-scale peatland plant communities. Furthermore, spatial relationships between SIF and VIs from large-scale vegetation ecosystems to small-scale peatland plant communities were examined. Apart from signal variations, we observed a positive correlation between SIF and greenness-sensitive VIs, whereas a negative correlation between SIF and a VI sensitive to photosynthesis was observed for large-scale vegetation ecosystems. In general, higher values of SIF were associated with higher biomass of vascular plants (associated with higher Leaf Area Index (LAI)). SIF signals, especially SIF760, were strongly associated with the functional diversity of the peatland vegetation. At the peatland area, higher values of SIF760 were associated with plant communities of high perennials, whereas, lower values of SIF760 indicated peatland patches dominated by Sphagnum. In general, SIF760 reflected the productivity gradient on the fen peatland, from Sphagnum-dominated patches with the lowest SIF and fAPAR values indicating lowest productivity to the Carex-dominated patches with the highest SIF and fAPAR values indicating highest productivity.

The interest of the scientific community on the remote observation of sun-induced chlorophyll fluorescence (SIF) has increased in the recent years. In this context, hyperspectral ground measurements play a crucial role in the calibration and validation of future satellite missions. For this reason, the European cooperation in science and technology (COST) Action ES1309 OPTIMISE has compiled three papers on instrument characterization, measurement setups and protocols, and retrieval methods (current paper). This study is divided in two sections; first, we evaluated the uncertainties in SIF retrieval methods (e.g., Fraunhofer line depth (FLD) approaches and spectral fitting method (SFM)) for a combination of off-the-shelf commercial spectrometers. Secondly, we evaluated how an erroneous implementation of the retrieval methods increases the uncertainty in the estimated SIF values. Results show that the SFM approach applied to high-resolution spectra provided the most reliable SIF retrieval with a relative error (RE) ≤6% and F687 and F760, respectively. Furthermore, although the SFM was the least affected by an inaccurate definition of the absorption spectral window (RE = 5%) and/or interpolation strategy (RE = 15–30%), we observed a sensitivity of the SIF retrieval for the simulated training data underlying the SFM model implementation.

Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has to be changed or a set of operations have to be performed to address particular queries on data. Thus, open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported? What is the quality of NoSQL solutions in such cases? In this paper, we deal with such issues specifically considering one of the major NoSQL document oriented DB available on the market: MongoDB. In particular, we discuss an approach to perform join operations at application layer in MongoDB that allows us to preserve data models. We analyse performance of the proposes approach discussing the introduced overhead in comparison with SQL-like DBs.

Graphene quantum dots (GQD), the new generation members of graphene-family, have shown promising applications in anticancer therapy. In this study, we report the synthesis of a fluorescent and biocompatible nanovector, based on GQD, for the targeted delivery of an anticancer drug with benzofuran structure (BFG) and bearing the targeting ligand riboflavin (RF, vitamin B2). The highly water-dispersible nanoparticles, synthesized from multi-walled carbon nanotubes (MWCNT) by prolonged acidic treatment, were linked covalently to the drug by means of a cleavable PEG linker while the targeting ligand RF was conjugated to the GQD by π⁻π interaction using a pyrene linker. The cytotoxic effect of the synthesized drug delivery system (DDS) GQD-PEG-BFG@Pyr-RF was tested on three cancer cell lines and this effect was compared with that exerted by the same nanovector lacking the RF ligand (GQD-PEG-BFG) or the anticancer drug (GQD@Pyr-RF). The results of biological tests underlined the low cytotoxicity of the GQD sample and the cytotoxic activity of the DDS against the investigated cancer cell lines with a higher or similar potency to that exerted by the BFG alone, thus opening new possibilities for the use of this drug or other anticancer agents endowed of cytotoxicity and serious side effects.