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Autofluorescence microscopy is a promising label-free approach to characterize NADH and FAD metabolites in live cells, with potential applications in clinical practice. Although spectrally resolved lifetime imaging techniques can acquire multiparametric information about the biophysical and biochemical state of the metabolites, these data are evaluated at the whole-cell level, thus providing only limited insights in the activation of metabolic networks at the microscale. To overcome this issue, here we introduce an artificial intelligence-based analysis that, leveraging the multiparametric content of spectrally resolved lifetime images, allows to detect and classify, through an unsupervised learning approach, metabolic clusters, which are regions having almost uniform metabolic properties. This method contextually detects the cellular mitochondrial turnover and the metabolic activation state of intracellular compartments at the pixel level, described by two functions: the cytosolic activation state (CAF) and the mitochondrial activation state (MAF). This method was applied to investigate metabolic changes elicited in the breast cancer cell line MCF-7 by specific inhibitors of glycolysis and electron transport chain, and by the deregulation of a specific mitochondrial enzyme (ACO2) leading to defective aerobic metabolism associated with tumor growth. In this model, mitochondrial fraction undergoes to a 13% increase upon ACO2 overexpression and the MAF function changes abruptly by altering the metabolic state of about the 25% of the mitochondrial pixels.

This article presents an efficient digital polar transmitter (DPTX) at mm-wave frequencies that exploit a novel N -way series Doherty combiner (SDC) to enhance its drain and system efficiency at deep power back-off (PBO). The proposed N -way SDC is scalable and can be implemented elegantly using N transformers and N-1 shunt capacitors. As a proof of concept, a four-way Doherty DPTX is realized with the proposed SDC in which four identical but independent digital phase modulators deliver a phase-modulated constant envelope signal to their corresponding digital power amplifiers to perform the required amplitude modulation. Fabricated in a 40nm CMOS process, the proposed DPTX occupies a core area of 1.1 mathrm {mm^{2}} and exhibits 18.7dBm saturated output power and <-40dBc LO feedthrough. It demonstrates a drain efficiency of 33%/36%/22% at 0/4.5/11.5dB PBO at a 29.5GHz carrier frequency. While transmitting a 300MHz 64-QAM OFDM signal with a peak-to-average power ratio of 10.7dB, the DPTX achieves 18%/8% average drain/system efficiency, -27.6dB error vector magnitude, and -27.5dBc adjacent channel leakage ratio. To the best of our knowledge, this work is the first reported mm-wave Doherty transmitter that includes the entire chain all the way from the binary data stream up to the modulated mm-wave output signal., Accepted author manuscript, Electronics

We report on the first demonstration of dynamic beam steering using a scanning lens phased array. A scanning lens phased array relies on a combination of mechanical and electrical phase shifting to dynamically steer a high-gain beam beyond the grating-lobe free region using a sparse array. These two concepts have been demonstrated separately in the past, here we present, for the first time, a prototype demonstration where active mechanical and electrical phase shifting are combined. For this purpose, we have developed a sparse 4x1 scanning lens phased array at W-band (75-110 GHz) capable of beam steering a directive beam (>30 dBi) towards ± 20° with low grating lobe levels (around -10 dB). The lens array is fed by a waveguide-based leaky-wave feeding architecture that illuminates the lenses with high aperture efficiency over a wide bandwidth, which is required in the proposed scanning lens phased array architecture. The electrical phase shifting has been implemented using IQ-mixers around 15 GHz in combination with x6 multipliers to reach the W-band. The mechanical phase shifting relies on a piezo-electric motor, which is able to achieve displacements of the lens array of 6 mm with an accuracy of a few nanometers. The entire active array is calibrated over the air with an ad-hoc quasi-optical measurement setup. Resulting measurements show excellent agreement with the anticipated performance., Tera-Hertz Sensing, Electronics

Globally, breast cancer is the most diagnosed invasive cancer among women. Current therapies (e.g., chemotherapy) show numerous limitations due to the lack of selectivity and involved side effects, which urgently asks for novel approaches with enhanced tumor-killing efficacy. We previously demonstrated that MXenes, new bioactive nanomaterials with promising photophysical properties, are capable to increase the efficiency of the targeted breast cancer photothermal therapy (PTT). In this work, we investigated the effect of few- and multi-layer Ti3C2Tx MXenes mediated-PTT on two different 3D reliable breast cancer models such as conventional and bio-printed spheroids. We performed PTT on both cancer models using a non-toxic MXene concentration of 50 µg/mL. After PTT, a significant reduction in the cell viability along with a notable increase in reactive oxygen species (ROS) was observed. Moreover, we studied the effect of PTT on the migration of macrophages and endothelial cells toward cancer regions in both 3D models. Our results indicate that PTT mediated by both few- and multi-layer MXenes significantly modulates the tumor progression through cells’ death by increasing the temperature, which holds particularly true for the bio-printed model.

In this contribution we will present the diffraction-limited imaging capabilities of a focal plane array (FPA) of antenna-coupled direct-detectors at submillimeter wavelengths. The FPA prototype is a tightly sampled, 12-pixel array that was developed in a 22 nm CMOS technology and it covers a band from 200 GHz to 600 GHz. A quasi-optical (QO) setup was developed to actively illuminate this FPA in order to perform imaging with > 40 dB SNR. The resulting images will be the first that have diffraction-limited angular resolution at these wavelengths, which demonstrates that this FPA design can be very attractive for future passive THz imaging applications., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Tera-Hertz Sensing, Electronics

In this contribution, we employ direct calibration/de-embedding approaches to validate the large signal device model of state-of-the-art HBTs and CMOS technologies operating in the mm-wave frequency band WR6. The capability of placing the first tier calibration reference plane in close proximity to the DUT allows the large signal metric to be directly compared with foundry models., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronics

This work presents a novel lens antenna architecture based on a core-shell lens design with a leaky-wave in-packaged antenna at 150GHz. An electrically small core lens made of dense dielectric material is used to enhance the radiation of the in-packaged antenna. A low-loss dielectric shell lens with electrically large dimensions is then added to provide high directivity. A microstrip feeding network for connection to a 150GHz chipset is then also discussed. The proposed lens antenna provides good quality patterns with aperture efficiencies above 80% over a bandwidth of 20%., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Tera-Hertz Sensing, Electronics

In this contribution, We analyze the bandwidth versus accuracy trade-offs of conventional two-step de-embedding approaches, often employed to extract the device model parameters. The accuracy limitation of incorporating the pad/line section of classical DUT test-fixtures into shunt-series complex and frequency-dependent elements is analyzed by means of linear circuit simulations and EM parametric analysis. The de-embedding accuracy is then evaluated by employing 3D surfaces to include both the frequency and the geometrical dependency. To validate the presented analysis, classical device monitoring parameters are extracted versus frequency for the same nMOS device embedded in two different fixtures. One topology only supports pad level calibration, thus including the fixture pad/line section in the de-embedding process. The second topology allows a direct on-Wafer calibration (reference plane set on metal-1 in close proximity to the DUT) thus minimizing the residual parasitics to be removed by the de-embedding step. Experimental data are then presented and compared to simulation test benches to highlight the improved consistency of the extracted model parameters of the metal-1 calibration approach up to 220GHz., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronics

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronics

VO2max index has a significant impact on overall health. Its estimation through wearables notifies the user of his level of fitness but cannot provide a detailed analysis of the time intervals in which heartbeat dynamics are changed and/or fatigue is emerging. Here, we developed a multiple modality biosignal processing method to investigate running sessions to characterize in real time heartbeat dynamics in response to external energy demand. We isolated dynamic regimes whose fraction increases with the VO2max and with the emergence of neuromuscular fatigue. This analysis can be extremely valuable by providing personalized feedback about the user's fitness level improvement that can be realized by developing personalized exercise plans aimed to target a contextual increase in the dynamic regime fraction related to VO2max increase, at the expense of the dynamic regime fraction related to the emergence of fatigue. These strategies can ultimately result in the reduction in cardiovascular risk.

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.

In this work, we will investigate if red blood cell (RBC) membrane fluidity, influenced by several hyperglycemia-induced pathways, could provide a complementary index of HbA1c to monitor the development of type 2 diabetes mellitus (T2DM)-related macroangiopathic complications such as Peripheral Artery Disease (PAD). The contextual liquid crystalline (LC) domain spatial organization in the membrane was analysed to investigate the phase dynamics of the transition. Twenty-seven patients with long-duration T2DM were recruited and classified in DM, including 12 non-PAD patients, and DM + PAD, including 15 patients in any stage of PAD. Mean values of RBC generalized polarization (GP), representative of membrane fluidity, together with spatial organization of LC domains were compared between the two groups; p-values < 0.05 were considered statistically significant. Although comparable for anthropometric characteristics, duration of diabetes, and HbA1c, RBC membranes of PAD patients were found to be significantly more fluid (GP: 0.501 +/- 0.026) than non-PAD patients (GP: 0.519 +/- 0.007). These alterations were shown to be triggered by changes in both LC microdomain composition and distribution. We found a decrease in Feret diameter from 0.245 +/- 0.281 mu m in DM to 0.183 +/- 0.124 mu m in DM + PAD, and an increase in circularity. Altered RBC membrane fluidity is correlated to a spatial reconfiguration of LC domains, which, by possibly altering metabolic function, are associated with the development of T2DM-related macroangiopathic complications.

Simple Summary Seminoma represents one of the most common neoplasms in Caucasian males between 15 and 40 years old. The molecular pathways underlying its clinical behavior are far from being understood yet. We previously demonstrated that nuclear Pituitary-tumor transforming-gene 1 (PTTG1), overexpressed in several neoplasms, promotes invasiveness through its transcriptional target matrix-metalloproteinase-2 (MMP2). PTTG1 sustains the migratory and invasive properties of cancer cells through the induction of the epithelial-to-mesenchymal transition (EMT). E-Cadherin (E-CAD) repression is the first step of EMT. Therefore, we investigated the role of PTTG1 in EMT in human seminoma using an in vitro and in vivo model and through Atlas database interrogation. Our data showed a PTTG1-mediated E-CAD transcriptional repression through Zinc finger E-box binding homeobox 1 (ZEB1), a master regulator of the EMT process. Our data provide insights into the molecular characterization of seminoma, promoting PTTG1 as a prognostic marker useful in human seminoma clinical management. (1) Background: PTTG1 sustains the EMT process and the invasiveness of several neoplasms. We previously showed the role of nuclear PTTG1 in promoting invasiveness, through its transcriptional target MMP2, in seminoma in vitro models. Here, we investigated the key players involved in PTTG1-mediated EMT in human seminoma. (2) Methods: Two seminoma cell lines and four human seminoma tumor specimens were used. E-Cadherin gene regulation was investigated using Western blot, real-time PCR, and luciferase assay. Immunoprecipitation, ChIP, RE-ChIP, and confocal microscopy analysis were performed to evaluate the interplay between PTTG1 and ZEB1. Matrigel invasion and spheroid formation assays were applied to functionally investigate PTTG1 involvement in the EMT of seminoma cell lines. RNA depletion and overexpression experiments were performed to verify the role of PTTG1/ZEB1 in E-Cadherin repression and seminom

Development of predictive computational models of metabolism through mechanistic models is complex and resource demanding, and their personalization remains challenging. Data-driven models of human metabolism would constitute a reliable, fast, and continuously updating model for predictive analytics. Wearable devices, such as smart bands and impedance balances, allow the real time and remote monitoring of physiological parameters, providing for a flux of data carrying information on user metabolism. Here, we developed a data-driven model of end-user metabolism, the Personalized Metabolic Avatar (PMA), to estimate its personalized reactions to diets. PMA consists of a gated recurrent unit (GRU) deep learning model trained to forecast personalized weight variations according to macronutrient composition and daily energy balance. The model can perform simulations and evaluation of diet plans, allowing the definition of tailored goals for achieving ideal weight. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim to achieve long-lasting results in pursuing a healthy lifestyle.

Background: Extracellular Vesicles (EVs) are sub-micrometer lipid-bound particles released by most cell types. They are considered a promising source of cancer biomarkers for liquid biopsy and personalized medicine due to their specific molecular cargo, which provides biochemical information on the state of parent cells. Despite this potential, EVs translation process in the diagnostic practice is still at its birth, and the development of novel medical devices for their detection and characterization is highly required. Results: In this study, we demonstrate mid-infrared plasmonic nanoantenna arrays designed to detect, in the liquid and dry phase, the specific vibrational absorption signal of EVs simultaneously with the unspecific refractive index sensing signal. For this purpose, EVs are immobilized on the gold nanoantenna surface by immunocapture, allowing us to select specific EV sub-populations and get rid of contaminants. A wet sample-handling technique relying on hydrophobicity contrast enables effortless reflectance measurements with a Fourier-transform infrared (FTIR) spectro-microscope in the wavelength range between 10 and 3 mu m. In a proof-of-principle experiment carried out on EVs released from human colorectal adenocarcinoma (CRC) cells, the protein absorption bands (amide-I and amide-II between 5.9 and 6.4 mu m) increase sharply within minutes when the EV solution is introduced in the fluidic chamber, indicating sensitivity to the EV proteins. A refractive index sensing curve is simultaneously provided by our sensor in the form of the redshift of a sharp spectral edge at wavelengths around 5 mu m, where no vibrational absorption of organic molecules takes place: this permits to extract of the dynamics of EV capture by antibodies from the overall molecular layer deposition dynamics, which is typically measured by commercial surface plasmon resonance sensors. Additionally, the described metasurface is exploited to compare the spectral response of EVs d

Red blood cells (RBCs) are characterized by a remarkable elasticity, which allows them to undergo very large deformation when passing through small vessels and capillaries. This extreme deformability is altered in various clinical conditions, suggesting that the analysis of red blood cell (RBC) mechanics has potential applications in the search for non-invasive and cost-effective blood biomarkers. Here, we provide a comparative study of the mechanical response of RBCs in patients with Alzheimer's disease (AD) and healthy subjects. For this purpose, RBC viscoelastic response was investigated using atomic force microscopy (AFM) in the force spectroscopy mode. Two types of analyses were performed: (i) a conventional analysis of AFM force-distance (FD) curves, which allowed us to retrieve the apparent Young's modulus, E; and (ii) a more in-depth analysis of time-dependent relaxation curves in the framework of the standard linear solid (SLS) model, which allowed us to estimate cell viscosity and elasticity, independently. Our data demonstrate that, while conventional analysis of AFM FD curves fails in distinguishing the two groups, the mechanical parameters obtained with the SLS model show a very good classification ability. The diagnostic performance of mechanical parameters was assessed using receiving operator characteristic (ROC) curves, showing very large areas under the curves (AUC) for selected biomarkers (AUC > 0.9). Taken all together, the data presented here demonstrate that RBC mechanics are significantly altered in AD, also highlighting the key role played by viscous forces. These RBC abnormalities in AD, which include both a modified elasticity and viscosity, could be considered a potential source of plasmatic biomarkers in the field of liquid biopsy to be used in combination with more established indicators of the pathology.

We report the measured results of a sparse, 4x1 scanning lens phased array prototype at W-band that is capable of beam steering a directive (>30 dBi) beam towards ±20° with sidelobe levels around -10 dB. The array elements are high-aperture-efficiency resonant leaky-wave lens antennas with a feed that suppresses the spurious TM0 mode over a wide bandwidth by using a circular waveguide in a ground plane surrounded by annular corrugations. The scanning lens phased array relies on simultaneous electrical and mechanical phase shifting to steer the beams. We use 15 GHz IQ-mixers followed by x6 multipliers to achieve electronic amplitude and phase control at W-band and a piezo-electric motor for mechanical phase shifting, which allows us to scan this array up to 20°. Measurements at 90 GHz of the lens array are in excellent agreement with simulations. More measurement results will be presented at the conference., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Tera-Hertz Sensing, Electronics

Exosomes (EXOs) are considered an exceptionally promising source of cancer biomarkers for personalized medicine and liquid biopsy. Despite this potential, the EXOs translation process in diagnostics is still at its birth, and the development of reliable and reproducible methods for their characterization is highly demanded. Fourier Transform Infrared (FTIR) Spectroscopy is perfectly suited for this purpose, as it can provide a label-free biochemical profile of EXOs in terms of lipid, protein, and nucleic acid content. Here we evaluated the applicability of FTIR spectroscopy to the study of cancer-derived EXOs as a function of cell differentiation. For this purpose, we used N-acetyl-L-Cysteine (NAC) to induce a controlled differentiation in human colon carcinoma cells from a proliferative mesenchymal morphology to a less invasive epithelial phenotype, as measured with fluorescence and electron microscopy. EXOs derived from cells with different phenotypes showed significant variation in the relative intensity of the amide I-II and CH-stretching bands in the mid-IR range, indicating the spectroscopic lipid/protein ratio as an effective classification parameter. Additionally, we showed that different cell phenotypes are associated with a shape modification in these spectral bands that can be automatically detected by combining Principal Component Analysis (PCA) with Linear Discriminant Analysis (LDA). On the one hand, our study confirms that an FTIR analysis of EXOs allows scientists to precisely detect modifications occurring at the parental cell level; on the other hand, it unveils a set of effective spectral biomarkers able to monitoring cell changes from a mesenchymal to an epithelial phenotype, a clinically valuable piece of information considering that the epithelial-to-mesenchymal transition is a key step in the metastatic process.

Cancer spheroids are in vitro 3D models that became crucial in nanomaterials science thanks to the possibility of performing high throughput screening of nanoparticles and combined nanoparticle-drug therapies on in vitro models. However, most of the current spheroid analysis methods involve manual steps. This is a time-consuming process and is extremely liable to the variability of individual operators. For this reason, rapid, user-friendly, ready-to-use, high-throughput image analysis software is necessary. In this work, we report the INSIDIA 2.0 macro, which of-fers researchers high-throughput and high content quantitative analysis of in vitro 3D cancer cell spheroids and allows advanced parametrization of the expanding and invading cancer cellular mass. INSIDIA has been implemented to provide in-depth morphologic analysis and has been used for the analysis of the effect of graphene quantum dots photothermal therapy on glioblastoma (U87) and pancreatic cancer (PANC-1) spheroids. Thanks to INSIDIA 2.0 analysis, two types of effects have been observed: In U87 spheroids, death is accompanied by a decrease in area of the entire spheroid, with a decrease in entropy due to the generation of a high uniform density spheroid core. On the other hand, PANC-1 spheroids’ death caused by nanoparticle photothermal disruption is accompanied with an overall increase in area and entropy due to the progressive loss of integrity and increase in variability of spheroid texture. We have summarized these effects in a quantitative parameter of spheroid disruption demonstrating that INSIDIA 2.0 multiparametric analysis can be used to quantify cell death in a non-invasive, fast, and high-throughput fashion.

Amyotrophic lateral sclerosis (ALS) is characterized by the degeneration and death of motor neurons. This neurodegenerative disease leads to muscle atrophy, paralysis, and death due to respiratory failure. MicroRNAs (miRNAs) are small non-coding ribonucleic acids (RNAs) with a length of 19 to 25 nucleotides, participating in the regulation of gene expression. Different studies have demonstrated that miRNAs deregulation is critical for the onset of a considerable number of neurodegenerative diseases, including ALS. Some studies have underlined how miRNAs are deregulated in ALS patients and for this reason, design therapies are used to correct the aberrant expression of miRNAs. With this rationale, delivery systems can be designed to target specific miRNAs. Specifically, these systems can be derived from viral vectors (viral systems) or synthetic or natural materials, including exosomes, lipids, and polymers. Between many materials used for nonviral vectors production, the two-dimensional graphene and its derivatives represent a good alternative for efficiently delivering nucleic acids. The large surface-to-volume ratio and ability to penetrate cell membranes are among the advantages of graphene. This review focuses on the specific pathogenesis of miRNAs in ALS and on graphene delivery systems designed for gene delivery to create a primer for future studies in the field.

Estimating the post-mortem interval is a fundamental, albeit challenging task in forensic sciences. To this aim, forensic practitioners need to assess post-mortem changes through a plethora of different methods, most of which are inherently qualitative, thus providing broad time intervals rather than precise determinations. This challenging problem is further complicated by the influence of environmental factors, which modify the temporal dynamics of post-mortem changes, sometimes in a rather unpredictable fashion. In this context, the search for quantitative and objective descriptors of post-mortem changes is highly demanded. In this study, we used computed tomography (CT) to assess the post-mortem anatomical modifications occurring in the time interval 0–4 days after death in the brain of four corpses. Our results show that fractal analysis of CT brain slices provides a set of quantitative descriptors able to map post-mortem changes over time throughout the whole brain. Although incapable of producing a direct estimation of the PMI, these descriptors could be used in combination with other more established methods to improve the accuracy and reliability of PMI determination.

Additive manufacturing has played a crucial role in the COVID-19 global emergency allowing for rapid production of medical devices, indispensable tools for hospitals, or personal protection equipment. However, medical devices, especially in nosocomial environments, represent high touch surfaces prone to viral infection and currently used filaments for 3D printing can't inhibit transmission of virus [1]. Graphene-family materials are capable of reinforcing mechanical, optical and thermal properties of 3D printed constructs. In particular, graphene can adsorb near-infrared light with high efficiency. Here we demonstrate that the addition of graphene nanoplatelets to PLA filaments (PLA-G) allows the creation of 3D-printed devices that can be sterilized by near-infrared light exposure at power density analog to sunlight. This method has been used to kill SARS-CoV-2 viral particles on the surface of 3D printed PLA-G by 3 min of exposure. 3D-printed PLA-G is highly biocompatible and can represent the ideal material for the production of sterilizable personal protective equipment and daily life objects intended for multiple users.

2-deoxy-2-fluorine-(18F)fluoro-D-glucose Positron Emission Tomography/Computed Tomography (18F-FDG-PET/CT) is widely used in oncology mainly for diagnosis and staging of various cancer types, including lung cancer, which is the most common cancer worldwide. Since histopathologic subtypes of lung cancer show different degree of 18F-FDG uptake, to date there are some diagnostic limits and uncertainties, hindering an 18F-FDG-PET-driven classification of histologic subtypes of lung cancers. On the other hand, since activated macrophages, neutrophils, fibroblasts and granulation tissues also show an increased 18F-FDG activity, infectious and/or inflammatory processes and post-surgical and post-radiation changes may cause false-positive results, especially for lymph-nodes assessment. Here we propose a model-free, machine-learning based algorithm for the automated classification of adenocarcinoma, the most common type of lung cancer, and other types of tumors. Input for the algorithm are dynamic acquisitions of PET data (dPET), providing for a spatially and temporally resolved characterization of the uptake kinetic. The algorithm consists in a trained Random Forest classifier which, relying contextually on several spatial and temporal features of 18F-FDG uptake, generates as an outcome probability maps allowing to distinguish adenocarcinoma from other lung histotype and to identify metastatic lymph-nodes, ultimately increasing the specificity of the technique. Its performance, evaluated on a dPET dataset of 19 patients affected by primary lung cancer, provides a probability 0.943 ± 0.090 for the detection of adenocarcinoma. The use of this algorithm will guarantee an automatic and more accurate localization and discrimination of tumors, also providing a powerful tool for detecting at which extent tumor has spread beyond a primary tumor into lymphatic system.

Glioblastoma is the most aggressive and lethal brain cancer. Current treatments involve surgical resection, radiotherapy and chemotherapy. However, the life expectancy of patients with this disease remains short and chemotherapy leads to severe adverse effects. Furthermore, the presence of the blood-brain barrier (BBB) makes it difficult for drugs to effectively reach the brain. A promising strategy lies in the use of graphene quantum dots (GQDs), which are light-responsive graphene nanoparticles that have shown the capability of crossing the BBB. Here we investigate the effect of GQDs on U87 human glioblastoma cells and primary cortical neurons. Non-functionalized GQDs (NF-GQDs) demonstrated high biocompatibility, while dimethylformamide-functionalized GQDs (DMF-GQDs) showed a toxic effect on both cell lines. The combination of GQDs and the chemotherapeutic agent doxorubicin (Dox) was tested. GQDs exerted a synergistic increase in the efficacy of chemotherapy treatment, specifically on U87 cells. The mechanism underlying this synergy was investigated, and it was found that GQDs can alter membrane permeability in a manner dependent on the surface chemistry, facilitating the uptake of Dox inside U87 cells, but not on cortical neurons. Therefore, experimental evidence indicates that GQDs could be used in a combined therapy against brain cancer, strongly increasing the efficacy of chemotherapy and, at the same time, reducing its dose requirement along with its side effects, thereby improving the life quality of patients.

We report the case of a 38 year-old Caucasian man enrolled in a study aimed at investigating the physical properties of red blood cells (RBCs) using advanced microscopy techniques, including Atomic Force Microscopy (AFM). At the time of his first enrolment in the study, he had normal Fasting Plasma Glucose (FPG) values, a BMI of 24.1, and no other symptoms of diabetes, including fatigue, high triglycerides, low HDL cholesterol, and altered inflammatory and corpuscular RBC indices. The subject reported no family history of diabetes, obesity, and cardiovascular diseases. Despite his apparently healthy conditions, the biomechanics of his RBCs was altered, showing increased values of stiffness and viscosity. More than 1 year after the mechanical measurements, the subject was admitted to the Operational Unit of Diabetology of the Policlinico Gemelli Hospital with high blood glucose and glycosylated hemoglobin (HbA1c) levels and diagnosed with type 1 diabetes (T1DM). Here, we show these data, and we discuss the hypothesis that RBC mechanical properties could be sensitive to changes occurring during the pre-diabetic phase of T1DM.

Exosomes possess great potential as cancer biomarkers in personalized medicine due to their easy accessibility and capability of representing their parental cells. To boost the translational process of exosomes in diagnostics, the development of novel and effective strategies for their label-free and automated characterization is highly desirable. In this context, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides direct access to specific biomolecular bands that give compositional information on exosomes in terms of their protein, lipid and genetic content. Here, we used FTIR spectroscopy in the mid-Infrared (mid-IR) range to study exosomes released from human colorectal adenocarcinoma HT-29 cancer cells cultured in different media. To this purpose, cells were studied in well-fed condition of growth, with 10% of exosome-depleted FBS (EVd-FBS), and under serum starvation with 0.5% EVd-FBS. Our data show the presence of statistically significant differences in the shape of the Amide I and II bands in the two conditions. Based on these differences, we showed the possibility to automatically classify cancer cell-derived exosomes using Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA); we tested the effectiveness of the classifier with a cross-validation approach, obtaining very high accuracy, precision, and recall. Aside from classification purposes, our FTIR data provide hints on the underlying cellular mechanisms responsible for the compositional differences in exosomes, suggesting a possible role of starvation-induced autophagy.

The present paper concerns a new description of changing in metabolism during incremental exercises test that permit an individually tailored program of exercises for obese subjects. We analyzed heart rate variability from RR interval time series (tachogram) with an alternative approach, the recurrence quantification analysis, that allows a description of a time series in terms of its dynamic structure and is able to identify the phase transitions. A transition in cardiac signal dynamics was detected and it perfectly reflects the aerobic threshold, as identified by gas exchange during an incremental exercise test, revealing the coupling from the respiratory system toward the heart. Moreover, our analysis shows that, in the recurrence plot of RR interval, it is possible to identify a specific pattern that allows to identify phase transitions between different dynamic regimes. The perfect match of the occurrence of the phase transitions with changes observed in the VO2 consumption, the gold standard approach to estimate thresholds, strongly supports the possibility of using our analysis of RR interval to detect metabolic threshold. In conclusion, we propose a novel nonlinear data analysis method that allows for an easy and personalized detection of thresholds both from professional and even from low-cost wearable devices, without the need of expensive gas analyzers.

Fragile X-related disorders are due to a dynamic mutation of the CGG repeat at the 5′ UTR of the FMR1 gene, coding for the RNA-binding protein FMRP. As the CGG sequence expands from premutation (PM, 56-200 CGGs) to full mutation (> 200 CGGs), FMRP synthesis decreases until it is practically abolished in fragile X syndrome (FXS) patients, mainly due to FMR1 methylation. Cells from rare individuals with no intellectual disability and carriers of an unmethylated full mutation (UFM) produce slightly elevated levels of FMR1-mRNA and relatively low levels of FMRP, like in PM carriers. With the aim of clarifying how UFM cells differ from CTRL and FXS cells, a comparative proteomic approach was undertaken, from which emerged an overexpression of SOD2 in UFM cells, also confirmed in PM but not in FXS. The SOD2-mRNA bound to FMRP in UFM more than in the other cell types. The high SOD2 levels in UFM and PM cells correlated with lower levels of superoxide and reactive oxygen species (ROS), and with morphological anomalies and depolarization of the mitochondrial membrane detected through confocal microscopy. The same effect was observed in CTRL and FXS after treatment with MC2791, causing SOD2 overexpression. These mitochondrial phenotypes reverted after knock-down with siRNA against SOD2-mRNA and FMR1-mRNA in UFM and PM. Overall, these data suggest that in PM and UFM carriers, which have high levels of FMR1 transcription and may develop FXTAS, SOD2 overexpression helps to maintain low levels of both superoxide and ROS with signs of mitochondrial degradation.