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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.
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Doenças Cardiovasculares , Diabetes Mellitus Tipo 2 , Humanos , Membrana Eritrocítica/metabolismo , Fluidez de Membrana , Estudos Prospectivos , Fatores de Risco , Eritrócitos/metabolismo , Ácidos Graxos/metabolismo , Fatores de Risco de Doenças Cardíacas , Biomarcadores/metabolismoRESUMO
Transmembrane semaphorins are signaling molecules, controlling axonal wiring and embryo development, which are increasingly implicated in human diseases. Semaphorin 6C (Sema6C) is a poorly understood family member and its functional role is still unclear. Upon targeting Sema6C expression in a range of cancer cells, we observed dramatic growth suppression, decreased ERK phosphorylation, upregulation of cell cycle inhibitor proteins p21, p27 and p53, and the onset of cell senescence, associated with activation of autophagy. These data are consistent with a fundamental requirement for Sema6C to support viability and growth in cancer cells. Mechanistically, we unveiled a novel signaling pathway elicited by Sema6C, and dependent on its intracellular domain, mediated by tyrosine kinases c-Abl and Focal Adhesion Kinase (FAK). Sema6C was found in complex with c-Abl, and induced its phosphorylation, which in turn led to FAK activation, independent of cell-matrix adhesion. Sema6C-induced FAK activity was furthermore responsible for increased nuclear localization of YAP transcriptional regulator. Moreover, Sema6C conferred YAP signaling-dependent long-term cancer cell survival upon nutrient deprivation. In conclusion, our findings demonstrate that Sema6C elicits a cancer promoting-signaling pathway sustaining cell viability and self-renewal, independent of growth factors and nutrients availability.
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Neoplasias , Transdução de Sinais , Humanos , Proteína-Tirosina Quinases de Adesão Focal/metabolismo , Sobrevivência Celular , Quinase 1 de Adesão Focal/genética , Quinase 1 de Adesão Focal/metabolismo , Fosforilação , Proteínas de Ciclo Celular/metabolismo , Neoplasias/genéticaRESUMO
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.
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Seminoma , Neoplasias Testiculares , Humanos , Masculino , Linhagem Celular Tumoral , Citoplasma/metabolismo , Regulação Neoplásica da Expressão Gênica , Metaloproteinase 2 da Matriz/metabolismo , Proteômica , Securina/genética , Securina/metabolismo , Seminoma/genética , Espectrina/genética , Neoplasias Testiculares/genéticaRESUMO
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.
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Exercício Físico , Corrida , Análise por Conglomerados , Coração , Frequência Cardíaca , Consumo de Oxigênio , Aptidão Física/fisiologiaRESUMO
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 µm in DM to 0.183 ± 0.124 µm 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.
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Diabetes Mellitus Tipo 2 , Doença Arterial Periférica , Diabetes Mellitus Tipo 2/complicações , Eritrócitos/metabolismo , Hemoglobinas Glicadas/metabolismo , Humanos , Fluidez de Membrana , Doença Arterial Periférica/complicaçõesRESUMO
The non-orthotopic expression of olfactory receptors (ORs) includes the male reproductive system, and in particular spermatozoa; their active ligands could be essential to sperm chemotaxis and chemical sperm-oocyte communication. OR51E2 expression has been previously reported on sperm cells' surface. It has been demonstrated in different cellular models that olfactory receptor 51E2 (OR51E2) binds volatile short-chain fatty acids (SCFAs) as specific ligands. In the present research, we make use of Western blot, confocal microscopy colocalization analysis, and the calcium-release assay to demonstrate the activation of sperm cells through OR51E2 upon SCFAs stimulus. Moreover, we perform a novel modified swim-up assay to study the involvement of OR51E2/SCFAs in sperm migration. Taking advantage of computer-assisted sperm analysis (CASA system), we determine the kinematics parameters of sperm cells migrating towards SCFAs-enriched medium, revealing that these ligands are able to promote a more linear sperm-cell orientation. Finally, we obtain SCFAs by mass spectrometry in cervico-vaginal mucus and show for the first time that a direct incubation between cervical mucus and sperm cells could promote their activation. This study can shed light on the possible function of chemosensory receptors in successful reproduction activity, laying the foundation for the development of new strategies for the treatment of infertile individuals.
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Neurônios Receptores Olfatórios , Receptores Odorantes , Feminino , Masculino , Animais , Receptores Odorantes/metabolismo , Sêmen/metabolismo , Espermatozoides/metabolismo , Ácidos Graxos Voláteis , Neurônios Receptores Olfatórios/metabolismoRESUMO
BACKGROUND: A high level of glycosylated haemoglobin (HbA1c), which is a nonenzymatic glycosylation product, is correlated with an increased risk of developing microangiopathic complications in Diabetes Mellitus (DM). Erythrocyte membrane fluidity could provide a complementary index to monitor the development of complications since it is influenced by several hyperglycaemia-induced pathways and other independent risk factors. MATERIALS AND METHODS: 15 healthy controls and 33 patients with long-duration (≥20 years) type 1 Diabetes Mellitus (T1DM) were recruited. Diabetic subjects were classified into two groups: T1DM, constituted by 14 nonretinopathic patients, and T1DM + RD, constituted by 19 patients in any stage of diabetic retinopathy. Red blood cells (RBC) were incubated with the fluorescent Laurdan probe and median values of Generalized Polarization (GP), representative of membrane fluidity, were compared between the two groups. Baseline characteristics among groups have been compared with Student's t test or ANOVA. Values of P < .05 were considered statistically significant. RESULTS: All the participants were comparable for age, Body Mass Index (BMI), creatinine and lipid profile. The duration of diabetes was similar for T1DM (34.4 ± 7.8 years) and T1DM + RD (32.8 ± 7.5 years) subjects as well as values of HbA1c: (55.6 ± 8.1) mmol/mol for T1DM and (61.2 ± 11.0) mmol/mol for T1DM + RD, respectively. Erythrocyte plasmatic membranes of RD patients were found to be more fluid (GP: 0.40 ± 0.04) than non-RD patients (GP: 0.43 ± 0.03) with a statistically significant difference (P = .035). CONCLUSIONS: Altered erythrocyte membrane fluidity may therefore represent a marker of retinopathy in T1DM patients as a result of post-translational modifications of multifactorial aetiology (nonenzymatic glycosylation of proteins, generation of reactive oxygen species, lipid peroxidation).
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Diabetes Mellitus Tipo 1/sangue , Retinopatia Diabética/sangue , Membrana Eritrocítica/metabolismo , Eritrócitos/metabolismo , Fluidez de Membrana/fisiologia , Adulto , Biomarcadores , Estudos de Casos e Controles , Diabetes Mellitus Tipo 1/complicações , Retinopatia Diabética/etiologia , Membrana Eritrocítica/fisiologia , Feminino , Hemoglobinas Glicadas/metabolismo , Humanos , Masculino , Pessoa de Meia-IdadeRESUMO
Free fatty acids are essential structural components of the cell, and their intracellular distribution and effects on membrane organelles have crucial roles in regulating the metabolism, development, and cell cycle of most cell types. Here we engineered novel fluorescent, polarity-sensitive fatty acid derivatives, with the fatty acid aliphatic chain of increasing length (from 12 to 18 carbons). As in the laurdan probe, the lipophilic acyl tail is connected to the environmentally sensitive dimethylaminonaphthalene moiety. The fluorescence lifetime imaging analysis allowed us to monitor the intracellular distribution of the free fatty acids within the cell, and to simultaneously examine how the fluidity and the microviscosity of the membrane environment influence their localization. Each of these probes can thus be used to investigate the membrane fluidity regulation of the correspondent fatty acid intracellular distribution. We observed that, in PC-12 cells, fluorescent sensitive fatty acid derivatives with increased chain length compartmentalize more preferentially in the fluid regions, characterized by a low microviscosity. Moreover, fatty acid derivatives with the longest chain compartmentalize in lipid droplets and lysosomes with characteristic lifetimes, thus making these probes a promising tool for monitoring lipophagy and related events.
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Ácidos Graxos/metabolismo , Corantes Fluorescentes/metabolismo , Espaço Intracelular/metabolismo , Fluidez de Membrana , 2-Naftilamina/análogos & derivados , 2-Naftilamina/química , Animais , Fluorescência , Lauratos/química , Lisossomos/metabolismo , Células PC12 , Ratos , Solventes , ViscosidadeRESUMO
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.
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Pegada de Carbono , Ingestão de Energia , Obesidade , Redução de Peso , Humanos , Projetos Piloto , Masculino , Feminino , Obesidade/dietoterapia , Adulto , Metabolismo Energético , Pessoa de Meia-Idade , Dieta Redutora/métodos , Dieta/métodosRESUMO
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.
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Polyphenols are a class of natural compounds that act as antioxidants, neutralising harmful free radicals that would damage cells and increase the risk of diseases such as cancer, diabetes and heart disease. They also reduce inflammation, which is thought to be at the root of many chronic diseases. We are investigating the photoprotective effects of punicalagin, a type of polyphenolic compound mainly found in pomegranates, against UVA-induced damage in human skin fibroblasts. Punicalagin increases cell viability and reduces the high levels of ROS generated by photooxidative stress through its ability to modulate the Nrf2 transcriptional pathway. Interestingly, activation of the Nrf2 pathway results in an increase in reduced glutathione, NADH, and subsequently protects mitochondrial respiratory capacity. Integrating molecular and imaging approaches, our results demonstrate a potential cytoprotective effect of punicalagin against UVA-induced skin damage through an anti-apoptotic mechanism.
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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 = â 0.44, â â Pâ < â 0.05â for tchew and nchew, Pâ < â 0.001 for wr), and tmean was correlated withâ tchew (R2â = â 0.25, â Pâ < â 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.
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Glicemia , Homeostase , Mastigação , Humanos , Mastigação/fisiologia , Glicemia/metabolismo , Masculino , Adulto , Modelos Lineares , Feminino , Adulto Jovem , EletromiografiaRESUMO
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.
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Aprendizado Profundo , Humanos , Redes Neurais de Computação , Estado Nutricional , Previsões , Modelos EstatísticosRESUMO
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.
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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.
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Mastigação , Fumar , Mastigação/fisiologia , Alimentos , Fatores de Tempo , Eletromiografia/métodosRESUMO
Even though Everolimus has been investigated in a phase II randomized trial as a host-directed therapy (HDT) to treat tuberculosis (TB), an oncological patient treated with Everolimus for a neuroendocrine pancreatic neoplasia developed active TB twice and a non-tuberculous mycobacterial (NTM) infection in a year and a half time span. To investigate this interesting case, we isolated and genotypically characterized the Mycobacterium tuberculosis (Mtb) clinical strain from the patient and tested the effect of Everolimus on its viability in an axenic culture and in a peripheral blood mononuclear cell (PBMCs) infection model. To exclude strain-specific resistance, we tested the activity of Everolimus against Mtb strains of ancient and modern lineages. Furthermore, we investigated the Everolimus effect on ROS production and autophagy modulation during Mtb infection. Everolimus did not have a direct effect on mycobacteria viability and a negligible effect during Mtb infection in host cells, although it stimulated autophagy and ROS production. Despite being a biologically plausible HDT against TB, Everolimus does not exert a direct or indirect activity on Mtb. This case underlines the need for a careful approach to drug repurposing and implementation and the importance of pre-clinical experimental studies.
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The human gut microbiome, an intricate ecosystem housing trillions of microorganisms within the gastrointestinal tract, holds significant importance in human health and the development of diseases. Recent advances in technology have allowed for an in-depth exploration of the gut microbiome, shedding light on its composition and functions. Of particular interest is the role of diet in shaping the gut microbiome, influencing its diversity, population size, and metabolic functions. Precision nutrition, a personalized approach based on individual characteristics, has shown promise in directly impacting the composition of the gut microbiome. However, to fully understand the long-term effects of specific diets and food components on the gut microbiome and to identify the variations between individuals, longitudinal studies are crucial. Additionally, precise methods for collecting dietary data, alongside the application of machine learning techniques, hold immense potential in comprehending the gut microbiome's response to diet and providing tailored lifestyle recommendations. In this study, we investigated the complex mechanisms that govern the diverse impacts of nutrients and specific foods on the equilibrium and functioning of the individual gut microbiome of seven volunteers (four females and three males) with an average age of 40.9 ± 10.3 years, aiming at identifying potential therapeutic targets, thus making valuable contributions to the field of personalized nutrition. These findings have the potential to revolutionize the development of highly effective strategies that are tailored to individual requirements for the management and treatment of various diseases.
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Idebenone is a ubiquinone short-chain synthetic analog with antioxidant properties, which is believed to restore mitochondrial ATP synthesis. As such, idebenone is investigated in numerous clinical trials for diseases of mitochondrial aetiology and it is authorized as a drug for the treatment of Leber's hereditary optic neuropathy. Mitochondria of retinal pigment epithelium (RPE) are particularly vulnerable to oxidative damage associated with cellular senescence. Therefore, the aim of this study was to explore idebenone's cytoprotective effect and its underlying mechanism. We used a human-RPE cell line (ARPE-19) exposed to idebenone pre-treatment for 24 h followed by conditions inducing H2O2 oxidative damage for a further 24 h. We found that idebenone: (a) ameliorated H2O2-lowered cell viability in the RPE culture; (b) activated Nrf2 signaling pathway by promoting Nrf2 nuclear translocation; (c) increased Bcl-2 protein levels, leaving unmodified those of Bax, thereby reducing the Bax/Bcl-2 ratio; (d) maintained the mitochondrial membrane potential (ΔΨm) at physiological levels, preserving the functionality of mitochondrial respiratory complexes and counteracting the excessive production of ROS; and (e) reduced mitochondrial cytochrome C-mediated caspase-3 activity. Taken together, our findings show that idebenone protects RPE from oxidative damage by modulating the intrinsic mitochondrial pathway of apoptosis, suggesting its possible role in retinal epitheliopathies associated with mitochondrial dysfunction.
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Self-monitoring of weight, diet and physical activity is a valuable component of behavioral weight loss treatment. The validation and user-friendliness of this approach is not optimal since users are selected from homogeneous pools and rely on different applications, increasing the burden and achieving partial, generic and/or unrelated information about their metabolic state. Moreover, studies establishing type, time, duration, and adherence criteria for self-monitoring are lacking. In this study, we developed a digital web-based application (ArmOnIA), which integrates dietary, anthropometric, and physical activity data and provides a personalized estimation of energy balance. Moreover, we determined type, time, duration, and adherence criteria for self-monitoring to achieve significant weight loss in a highly heterogeneous group. A single-arm, uncontrolled prospective study on self-monitored voluntary adults for 7 months was performed. Hierarchical clustering of adherence parameters yielded three behavioral approaches: high (HA), low (LA), and medium (MA) adherence. Average BMI decrease is statistically significant between LA and HA. Moreover, we defined thresholds for the minimum frequencies and duration of dietary and weight self-monitoring. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim of achieving long-lasting results when pursuing a healthy lifestyle.
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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.