Digital Biohacking Approach to Dietary Interventions: A Comprehensive Strategy for Healthy and Sustainable Weight Loss.

The rising obesity epidemic requires effective and sustainable weight loss intervention strategies that take into account both of individual preferences and environmental impact. This study aims to develop and evaluate the effectiveness of an innovative digital biohacking approach for dietary modifications in promoting sustainable weight loss and reducing carbon footprint impact. A pilot study was conducted involving four participants who monitored their weight, diet, and activities over the course of a year. Data on food consumption, carbon footprint impact, calorie intake, macronutrient composition, weight, and energy expenditure were collected. A digital replica of the metabolism based on nutritional information, the Personalized Metabolic Avatar (PMA), was used to simulate weight changes, plan, and execute the digital biohacking approach to dietary interventions. The dietary modifications suggested by the digital biohacking approach resulted in an average daily calorie reduction of 236.78 kcal (14.24%) and a 15.12% reduction in carbon footprint impact (-736.48 gCO2eq) per participant. Digital biohacking simulations using PMA showed significant differences in weight change compared to actual recorded data, indicating effective weight reduction with the digital biohacking diet. Additionally, linear regression analysis on real data revealed a significant correlation between adherence to the suggested diet and weight loss. In conclusion, the digital biohacking recommendations provide a personalized and sustainable approach to weight loss, simultaneously reducing calorie intake and minimizing the carbon footprint impact. This approach shows promise in combating obesity while considering both individual preferences and environmental sustainability.

Plant-derived extracellular nanovesicles: a promising biomedical approach for effective targeting of triple negative breast cancer cells.

Introduction: Triple negative breast cancer (TNBC), a highly aggressive subtype accounting for 15-20% of all breast cancer cases, faces limited treatment options often accompanied by severe side effects. In recent years, natural extracellular nanovesicles derived from plants have emerged as promising candidates for cancer therapy, given their safety profile marked by non-immunogenicity and absence of inflammatory responses. Nevertheless, the potential anti-cancer effects of Citrus limon L.-derived extracellular nanovesicles (CLENs) for breast cancer treatment is still unexplored. Methods: In this study, we investigated the anti-cancer effects of CLENs on two TNBC cell lines (4T1 and HCC-1806 cells) under growth conditions in 2D and 3D culture environments. The cellular uptake efficiency of CLENs and their internalization mechanism were evaluated in both cells using confocal microscopy. Thereafter, we assessed the effect of different concentrations of CLENs on cell viability over time using a dual approach of Calcein-AM PI live-dead assay and CellTiter-Glo bioluminescence assay. We also examined the influence of CLENs on the migratory and evasion abilities of TNBC cells through wound healing and 3D Matrigel drop evasion assays. Furthermore, Western blot analysis was employed to investigate the effects of CLENs on the phosphorylation levels of phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), and extracellular signal- regulated kinase (ERK) expression. Results: We found that CLENs were internalized by the cells via endocytosis, leading to decreased cell viability, in a dose- and time-dependent manner. Additionally, the migration and evasion abilities of TNBC cells were significantly inhibited under exposed to 40 and 80 µg/mL CLENs. Furthermore, down-regulated expression levels of phosphorylated phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), and extracellular signal-regulated kinase (ERK), suggesting that the inhibition of cancer cell proliferation, migration, and evasion is driven by the inhibition of the PI3K/AKT and MAPK/ERK signaling pathways. Discussion: Overall, our results demonstrate the anti-tumor efficiency of CLENs against TNBC cells, highlighting their potential as promising natural anti-cancer agents for clinical applications in cancer treatment.

Optical discrimination of pathological red blood cells.

Fast diagnostic methods are crucial to reduce the burden on healthcare systems. Currently, detection of diabetes complications such as neuropathy requires time-consuming approaches to observe the correlated red blood cells (RBCs) morphological changes. To tackle this issue, an optical analysis of RBCs in air was conducted in the 250-2500 nm range. The distinct oscillations present in the scattered and direct transmittance spectra have been analyzed with both Mie theory and anomalous diffraction approximation. The results provide information about the swelling at the ends of RBCs and directly relate the optical data to RBCs morphology and deformability. Both models agree on a reduction in the size and deformability of RBCs in diabetic patients, thus opening the way to diabetes diagnosis and disease progression assessment.

Assessment of the influence of chewing pattern on glucose homeostasis through linear regression model.

OBJECTIVE: Maintaining plasma glucose homeostasis is vital for mammalian survival, but the masticatory function, which influences glucose regulation, has, to our knowledge, been overlooked. RESEARCH METHODS AND PROCEDURES: In this study, we investigated the relationship between the glycemic response curve and chewing performance in a group of 8 individuals who consumed 80 g of apple. A device called "Chewing" utilizing electromyographic (EMG) technology quantitatively assesses chewing pattern, while glycemic response is analyzed using continuous glucose monitoring. We assessed chewing pattern characterizing chewing time (tchew), number of bites (nchew), work (w), power (wr), and chewing cycles (tcyc). Moreover, we measured the principal features of the glycemic response curve, including the area under the curve (α) and the mean time to reach the glycemic peak (tmean). We used linear regression models to examine the correlations between these variables. RESULTS: tchew, nchew, and wr were correlated with α (R2 =  0.44,   P  <  0.05 for tchew and nchew, P  <  0.001 for wr), and tmean was correlated with tchew (R2  =  0.25,  P  <  0.05). These findings suggest that increasing chewing time and power, while reducing the number of chews, resulted in a wider glycemic curve and an earlier attainment of the glycemic peak. CONCLUSIONS: These results emphasize the influence of proper chewing techniques on blood sugar levels. Implementing correct chewing habits could serve as an additional approach to managing the glycemic curve, particularly for individuals with diabetes.

Digital applications for diet monitoring, planning, and precision nutrition for citizens and professionals: a state of the art.

The objective of this review was to critically examine existing digital applications, tailored for use by citizens and professionals, to provide diet monitoring, diet planning, and precision nutrition. We sought to identify the strengths and weaknesses of such digital applications, while exploring their potential contributions to enhancing public health, and discussed potential developmental pathways. Nutrition is a critical aspect of maintaining good health, with an unhealthy diet being one of the primary risk factors for chronic diseases, such as obesity, diabetes, and cardiovascular disease. Tracking and monitoring one's diet has been shown to help improve health and weight management. However, this task can be complex and time-consuming, often leading to frustration and a lack of adherence to dietary recommendations. Digital applications for diet monitoring, diet generation, and precision nutrition offer the promise of better health outcomes. Data on current nutrition-based digital tools was collected from pertinent literature and software providers. These digital tools have been designed for particular user groups: citizens, nutritionists, and physicians and researchers employing genetics and epigenetics tools. The applications were evaluated in terms of their key functionalities, strengths, and limitations. The analysis primarily concentrated on artificial intelligence algorithms and devices intended to streamline the collection and organization of nutrition data. Furthermore, an exploration was conducted of potential future advancements in this field. Digital applications designed for the use of citizens allow diet self-monitoring, and they can be an effective tool for weight and diabetes management, while digital precision nutrition solutions for professionals can provide scalability, personalized recommendations for patients, and a means of providing ongoing diet support. The limitations in using these digital applications include data accuracy, accessibility, and affordability, and further research and development are required. The integration of artificial intelligence, machine learning, and blockchain technology holds promise for improving the performance, security, and privacy of digital precision nutrition interventions. Multidisciplinarity is crucial for evidence-based and accessible solutions. Digital applications for diet monitoring and precision nutrition have the potential to revolutionize nutrition and health. These tools can make it easier for individuals to control their diets, help nutritionists provide better care, and enable physicians to offer personalized treatment.

Unraveling the potential of graphene quantum dots against Mycobacterium tuberculosis infection.

Introduction: The emergence of drug-resistant Mycobacterium tuberculosis (Mtb) strains has underscored the urgent need for novel therapeutic approaches. Carbon-based nanomaterials, such as graphene oxide (GO), have shown potential in anti-TB activities but suffer from significant toxicity issues. Methods: This study explores the anti-TB potential of differently functionalized graphene quantum dots (GQDs) - non-functionalized, L-GQDs, aminated (NH2-GQDs), and carboxylated (COOH-GQDs) - alone and in combination with standard TB drugs (isoniazid, amikacin, and linezolid). Their effects were assessed in both axenic cultures and in vitro infection models. Results: GQDs alone did not demonstrate direct mycobactericidal effects nor trapping activity. However, the combination of NH2-GQDs with amikacin significantly reduced CFUs in in vitro models. NH2-GQDs and COOH-GQDs also enhanced the antimicrobial activity of amikacin in infected macrophages, although L-GQDs and COOH-GQDs alone showed no significant activity. Discussion: The results suggest that specific types of GQDs, particularly NH2-GQDs, can enhance the efficacy of existing anti-TB drugs. These nanoparticles might serve as effective adjuvants in anti-TB therapy by boosting drug performance and reducing bacterial counts in host cells, highlighting their potential as part of advanced drug delivery systems in tuberculosis treatment. Further investigations are needed to better understand their mechanisms and optimize their use in clinical settings.

Slow and steady wins the race: Fractionated near-infrared treatment empowered by graphene-enhanced 3D scaffolds for precision oncology.

Surgically addressing tumors poses a challenge, requiring a tailored, multidisciplinary approach for each patient based on the unique aspects of their case. Innovative therapeutic regimens combined to reliable reconstructive methods can contribute to an extended patient's life expectancy. This study presents a detailed comparative investigation of near-infrared therapy protocols, examining the impact of non-fractionated and fractionated irradiation regimens on cancer treatment. The therapy is based on the implantation of graphene oxide/poly(lactic-co-glycolic acid) three-dimensional printed scaffolds, exploring their versatile applications in oncology by the examination of pro-inflammatory cytokine secretion, immune response, and in vitro and in vivo tumor therapy. The investigation into cell death patterns (apoptosis vs necrosis) underlines the pivotal role of protocol selection underscores the critical influence of treatment duration on cell fate, establishing a crucial parameter in therapeutic decision-making. In vivo experiments corroborated the profound impact of protocol selection on tumor response. The fractionated regimen emerged as the standout performer, achieving a substantial reduction in tumor size over time, surpassing the efficacy of the non-fractionated approach. Additionally, the fractionated regimen exhibited efficacy also in targeting tumors in proximity but not in direct contact to the scaffolds. Our results address a critical gap in current research, highlighting the absence of a standardized protocol for optimizing the outcome of photodynamic therapy. The findings underscore the importance of personalized treatment strategies in achieving optimal therapeutic efficacy for precision cancer therapy.

Erythrocyte membrane fluidity: A novel biomarker of residual cardiovascular risk in type 2 diabetes.

AIMS: Improving the composition of circulating fatty acids (FA) leads to a reduction in cardiovascular diseases (CVD) in high-risk individuals. The membrane fluidity of red blood cells (RBC), which reflects circulating FA status, may be a valid biomarker of cardiovascular (CV) risk in type 2 diabetes (T2D). METHODS: Red blood cell membrane fluidity, quantified as general polarization (GP), was assessed in 234 subjects with T2D, 86 with prior major CVD. Based on GP distribution, a cut-off of .445 was used to divide the study cohort into two groups: the first with higher GP, called GEL, and the second, defined as lower GP (LGP). Lipidomic analysis was performed to evaluate FA composition of RBC membranes. RESULTS: Although with comparable CV risk factors, the LGP group had a greater percentage of patients with major CVD than the GEL group (40% vs 24%, respectively, p < .05). Moreover, in a logistic regression analysis, a lower GP value was independently associated with the presence of macrovascular complications. Lipidomic analysis showed a clear shift of LGP membranes towards a pro-inflammatory condition due to higher content of arachidonic acid and increased omega 6/omega 3 index. CONCLUSIONS: Increased membrane fluidity is associated with a higher CV risk in subjects with T2D. If confirmed in prospective studies, membrane fluidity could be a new biomarker for residual CV risk assessment in T2D.

SPTBN1 Mediates the Cytoplasmic Constraint of PTTG1, Impairing Its Oncogenic Activity in Human Seminoma.

Seminoma is the most common testicular cancer. Pituitary tumor-transforming gene 1 (PTTG1) is a securin showing oncogenic activity in several tumors. We previously demonstrated that nuclear PTTG1 promotes seminoma tumor invasion through its transcriptional activity on matrix metalloproteinase 2 (MMP-2) and E-cadherin (CDH1). We wondered if specific interactors could affect its subcellular distribution. To this aim, we investigated the PTTG1 interactome in seminoma cell lines showing different PTTG1 nuclear levels correlated with invasive properties. A proteomic approach upon PTTG1 immunoprecipitation uncovered new specific securin interactors. Western blot, confocal microscopy, cytoplasmic/nuclear fractionation, sphere-forming assay, and Atlas database interrogation were performed to validate the proteomic results and to investigate the interplay between PTTG1 and newly uncovered partners. We observed that spectrin beta-chain (SPTBN1) and PTTG1 were cofactors, with SPTBN1 anchoring the securin in the cytoplasm. SPTBN1 downregulation determined PTTG1 nuclear translocation, promoting its invasive capability. Moreover, a PTTG1 deletion mutant lacking SPTBN1 binding was strongly localized in the nucleus. The Atlas database revealed that seminomas that contained higher nuclear PTTG1 levels showed significantly lower SPTBN1 levels in comparison to non-seminomas. In human seminoma specimens, we found a strong PTTG1/SPTBN1 colocalization that decreases in areas with nuclear PTTG1 distribution. Overall, these results suggest that SPTBN1, along with PTTG1, is a potential prognostic factor useful in the clinical management of seminoma.

Self-assembly of glycoprotein nanostructured filaments for modulating extracellular networks at long range.

The intriguing capability of branched glycoprotein filaments to change their hierarchical organization, mediated by external biophysical stimuli, continues to expand understanding of self-assembling strategies that can dynamically rearrange networks at long range. Previous research has explored the corresponding biological, physiological and genetic mechanisms, focusing on protein assemblies within a limited range of nanometric units. Using direct microscopy bio-imaging, we have determined the morpho-structural changes of self-assembled filament networks of the zona pellucida, revealing controlled levels of structured organizations to join distinct evolved stages of the oocyte (Immature, Mature, and Fertilized). This natural soft network reorganizes its corresponding hierarchical network to generate symmetric, asymmetric, and ultimately a state with the lowest asymmetry of the outer surface roughness, and internal pores reversibly changed from elliptical to circular configurations at the corresponding stages. These elusive morpho-structural changes are regulated by the nanostructured polymorphisms of the branched filaments by self-extension/-contraction/-bending processes, modulated by determinate theoretical angles among repetitive filament units. Controlling the nanoscale self-assembling properties by delivering a minimum number of activation bio-signals may be triggered by these specific nanostructured polymorphic organizations. Finally, this research aims to guide this soft biomaterial into a desired state to protect oocytes, eggs, and embryos during development, to favour/prevent the fertilization/polyspermy processes and eventually to impact interactions with bacteria/virus at multiscale levels.

Interventional Radiotherapy (Brachytherapy) for Nasal Vestibule: Novel Strategies to Prevent Side Effects.

Interventional radiotherapy (brachytherapy) has become the new therapeutic standard in the management of early stages nasal vestibule tumors; in fact it allows for high local control rates and low toxicity profiles. However, since more and more patients will receive interventional radiotherapy (brachytherapy) as primary treatment, it is desirable to implement novel strategies to reduce the dose to organs at risk with the future aim to result in further lowering long-term side effects. MATERIALS AND METHODS: We were able to identify two different strategies to reduce dose to the treatment volume, including the implantation technique (the implant can be interstitial, endocavitary or mixed and the catheters may be placed either using the Paris system rules or the anatomical approach) and the dose distribution within the implant (the most commonly used parameter to consider is the dose non-uniformity ratio). We subsequently propose two novel strategies to reduce dose to organs at risk, including the use of metal shields for fixed organs as in the case of the eyes and the use of a mouth swab to push away mobile organs, such in the case of the mandible. We used two different algorithms to verify the values namely the TG-43 and the TG-186. RESULTS: We provided an accurate literature review regarding strategies to reduce toxicity to the treatment volume, underlining the pros and cons of all implantation techniques and about the use dose non-uniformity ratio. Regarding the innovative strategies to reduce the dose to organs at risk, we investigated the use of eye shielding and the use of swabs to push away the mandible by performing an innovative calculation using two different algorithms in a series of three consecutive patients. Our results show that the dose reduction, both in the case of the mandible and in the case of eye shielding, was statistically significant. CONCLUSION: Proper knowledge of the best implantation technique and dose non-uniformity ratio as highlighted by existing literature is mandatory in order to reduce toxicity within the treatment volume. With regard to the dose reduction to the organs at risk we have demonstrated that the use of eye shielding and mouth swab could play a pivotal role in clinical practice; in fact, they are effective at lowering the doses to the surrounding organs and do not require any change to the current clinical workflow.

Extreme transport of light in spheroids of tumor cells.

Extreme waves are intense and unexpected wavepackets ubiquitous in complex systems. In optics, these rogue waves are promising as robust and noise-resistant beams for probing and manipulating the underlying material. Localizing large optical power is crucial especially in biomedical systems, where, however, extremely intense beams have not yet been observed. We here discover that tumor-cell spheroids manifest optical rogue waves when illuminated by randomly modulated laser beams. The intensity of light transmitted through bio-printed three-dimensional tumor models follows a signature Weibull statistical distribution, where extreme events correspond to spatially-localized optical modes propagating within the cell network. Experiments varying the input beam power and size indicate that the rogue waves have a nonlinear origin. We show that these nonlinear optical filaments form high-transmission channels with enhanced transmission. They deliver large optical power through the tumor spheroid, and can be exploited to achieve a local temperature increase controlled by the input wave shape. Our findings shed light on optical propagation in biological aggregates and demonstrate how nonlinear extreme event formation allows light concentration in deep tissues, paving the way to using rogue waves in biomedical applications, such as light-activated therapies.

Evaluation of the Chewing Pattern through an Electromyographic Device.

Chewing is essential in regulating metabolism and initiating digestion. Various methods have been used to examine chewing, including analyzing chewing sounds and using piezoelectric sensors to detect muscle contractions. However, these methods struggle to distinguish chewing from other movements. Electromyography (EMG) has proven to be an accurate solution, although it requires sensors attached to the skin. Existing EMG devices focus on detecting the act of chewing or classifying foods and do not provide self-awareness of chewing habits. We developed a non-invasive device that evaluates a personalized chewing style by analyzing various aspects, like chewing time, cycle time, work rate, number of chews and work. It was tested in a case study comparing the chewing pattern of smokers and non-smokers, as smoking can alter chewing habits. Previous studies have shown that smokers exhibit reduced chewing speed, but other aspects of chewing were overlooked. The goal of this study is to present the device and provide additional insights into the effects of smoking on chewing patterns by considering multiple chewing features. Statistical analysis revealed significant differences, as non-smokers had more chews and higher work values, indicating more efficient chewing. The device provides valuable insights into personalized chewing profiles and could modify unhealthy chewing habits.

Cardiolipin drives the catalytic activity of GPX4 on membranes: Insights from the R152H mutant.

The aim of this study was to examine, in biochemical detail, the functional role of the Arg152 residue in the selenoprotein Glutathione Peroxidase 4 (GPX4), whose mutation to His is involved in Sedaghatian-type Spondylometaphyseal Dysplasia (SSMD). Wild-type and mutated recombinant enzymes with selenopcysteine (Sec) at the active site, were purified and structurally characterized to investigate the impact of the R152H mutation on enzymatic function. The mutation did not affect the peroxidase reaction's catalytic mechanism, and the kinetic parameters were qualitatively similar between the wild-type enzyme and the mutant when mixed micelles and monolamellar liposomes containing phosphatidylcholine and its hydroperoxide derivatives were used as substrate. However, in monolamellar liposomes also containing cardiolipin, which binds to a cationic area near the active site of GPX4, including residue R152, the wild-type enzyme showed a non-canonical dependency of the reaction rate on the concentration of both enzyme and membrane cardiolipin. To explain this oddity, a minimal model was developed encompassing the kinetics of both the enzyme interaction with the membrane and the catalytic peroxidase reaction. Computational fitting of experimental activity recordings showed that the wild-type enzyme was surface-sensing and prone to "positive feedback" in the presence of cardiolipin, indicating a positive cooperativity. This feature was minimal, if any, in the mutant. These findings suggest that GPX4 physiology in cardiolipin containing mitochondria is unique, and emerges as a likely target of the pathological dysfunction in SSMD.

Nanotechnology in the COVID-19 era: Carbon-based nanomaterials as a promising solution.

The Coronavirus Disease 2019 (COVID-19) pandemic has led to collaboration between nanotechnology scientists, industry stakeholders, and clinicians to develop solutions for diagnostics, prevention, and treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections. Nanomaterials, including carbon-based materials (CBM) such as graphene and carbon nanotubes, have been studied for their potential in viral research. CBM unique effects on microorganisms, immune interaction, and sensitivity in diagnostics have made them a promising subject of SARS-CoV-2 research. This review discusses the interaction of CBM with SARS-CoV-2 and their applicability, including CBM physical and chemical properties, the known interactions between CBM and viral components, and the proposed prevention, treatment, and diagnostics uses.

Evaluation of the Toxic Activity of the Graphene Oxide in the Ex Vivo Model of Human PBMC Infection with Mycobacterium tuberculosis.

Graphene Oxide has been proposed as a potential adjuvant to develop improved anti-TB treatment, thanks to its activity in entrapping mycobacteria in the extracellular compartment limiting their entry in macrophages. Indeed, when administered together with linezolid, Graphene Oxide significantly enhanced bacterial killing due to the increased production of Reactive Oxygen Species. In this work, we evaluated Graphene Oxide toxicity and its anti-mycobacterial activity on human peripheral blood mononuclear cells. Our data show that Graphene Oxide, different to what is observed in macrophages, does not support the clearance of Mycobacterium tuberculosis in human immune primary cells, probably due to the toxic effects of the nano-material on monocytes and CD4+ lymphocytes, which we measured by cytometry. These findings highlight the need to test GO and other carbon-based nanomaterials in relevant in vitro models to assess the cytotoxic activity while measuring antimicrobial potential.

Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction.

Nutrition is a cross-cutting sector in medicine, with a huge impact on health, from cardiovascular disease to cancer. Employment of digital medicine in nutrition relies on digital twins: digital replicas of human physiology representing an emergent solution for prevention and treatment of many diseases. In this context, we have already developed a data-driven model of metabolism, called a "Personalized Metabolic Avatar" (PMA), using gated recurrent unit (GRU) neural networks for weight forecasting. However, putting a digital twin into production to make it available for users is a difficult task that as important as model building. Among the principal issues, changes to data sources, models and hyperparameters introduce room for error and overfitting and can lead to abrupt variations in computational time. In this study, we selected the best strategy for deployment in terms of predictive performance and computational time. Several models, such as the Transformer model, recursive neural networks (GRUs and long short-term memory networks) and the statistical SARIMAX model were tested on ten users. PMAs based on GRUs and LSTM showed optimal and stable predictive performances, with the lowest root mean squared errors (0.38 ± 0.16-0.39 ± 0.18) and acceptable computational times of the retraining phase (12.7 ± 1.42 s-13.5 ± 3.60 s) for a production environment. While the Transformer model did not bring a substantial improvement over RNNs in term of predictive performance, it increased the computational time for both forecasting and retraining by 40%. The SARIMAX model showed the worst performance in term of predictive performance, though it had the best computational time. For all the models considered, the extent of the data source was a negligible factor, and a threshold was established for the number of time points needed for a successful prediction.

Metabolic Imaging and Molecular Biology Reveal the Interplay between Lipid Metabolism and DHA-Induced Modulation of Redox Homeostasis in RPE Cells.

Diabetes-induced oxidative stress induces the development of vascular complications, which are significant causes of morbidity and mortality in diabetic patients. Among these, diabetic retinopathy (DR) is often caused by functional changes in the blood-retinal barrier (BRB) due to harmful oxidative stress events in lipids, proteins, and DNA. Docosahexaenoic acid (DHA) has a potential therapeutic effect against hyperglycemia-induced oxidative damage and apoptotic pathways in the main constituents of BRB, retinal pigment epithelium cells (ARPE-19). Effective antioxidant response elicited by DHA is driven by the activation of the Nrf2/Nqo1 signaling cascade, which leads to the formation of NADH, a reductive agent found in the cytoplasm. Nrf2 also induces the expression of genes encoding enzymes involved in lipid metabolism. This study, therefore, aims at investigating the modulation of lipid metabolism induced by high-glucose (HG) on ARPE-19 cells through the integration of metabolic imaging and molecular biology to provide a comprehensive functional and molecular characterization of the mechanisms activated in the disease, as well the therapeutic role of DHA. This study shows that HG augments RPE metabolic processes by enhancing lipid metabolism, from fatty acid uptake and turnover to lipid biosynthesis and ß-oxidation. DHA exerts its beneficial effect by ameliorating lipid metabolism and reducing the increased ROS production under HG conditions. This investigation may provide novel insight for formulating novel treatments for DR by targeting lipid metabolism pathways.

Automatic Detection of Aerobic Threshold through Recurrence Quantification Analysis of Heart Rate Time Series.

During exercise with increasing intensity, the human body transforms energy with mechanisms dependent upon actual requirements. Three phases of the body's energy utilization are recognized, characterized by different metabolic processes, and separated by two threshold points, called aerobic (AerT) and anaerobic threshold (AnT). These thresholds occur at determined values of exercise intensity(workload) and can change among individuals. They are considered indicators of exercise capacities and are useful in the personalization of physical activity plans. They are usually detected by ventilatory or metabolic variables and require expensive equipment and invasive measurements. Recently, particular attention has focused on AerT, which is a parameter especially useful in the overweight and obese population to determine the best amount of exercise intensity for weight loss and increasing physical fitness. The aim of study is to propose a new procedure to automatically identify AerT using the analysis of recurrences (RQA) relying only on Heart rate time series, acquired from a cohort of young athletes during a sub-maximal incremental exercise test (Cardiopulmonary Exercise Test, CPET) on a cycle ergometer. We found that the minima of determinism, an RQA feature calculated from the Recurrence Quantification by Epochs (RQE) approach, identify the time points where generic metabolic transitions occur. Among these transitions, a criterion based on the maximum convexity of the determinism minima allows to detect the first metabolic threshold. The ordinary least products regression analysis shows that values of the oxygen consumption VO2, heart rate (HR), and Workload correspondent to the AerT estimated by RQA are strongly correlated with the one estimated by CPET (r > 0.64). Mean percentage differences are <2% for both HR and VO2 and <11% for Workload. The Technical Error for HR at AerT is <8%; intraclass correlation coefficients values are moderate (≥0.66) for all variables at AerT. This system thus represents a useful method to detect AerT relying only on heart rate time series, and once validated for different activities, in future, can be easily implemented in applications acquiring data from portable heart rate monitors.

Antenna-enhanced mid-infrared detection of extracellular vesicles derived from human cancer cell cultures.

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 µm. 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 µm) 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 µm, 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 derived from cancer cells with increasing invasiveness and metastatic potential, suggesting that the average secondary structure content in EVs can be correlated with cell malignancy. CONCLUSIONS: Thanks to the high protein sensitivity and the possibility to work with small sample volumes-two key features for ultrasensitive detection of extracellular vesicles- our lab-on-chip can positively impact the development of novel laboratory medicine methods for the molecular characterization of EVs.