Latest Improvement upon Molecular Photoacoustic Image resolution together with CarbonBased Nanocomposites

Strategies that restore the plasma concentration of arginine, inhibit arginase activity, and/or enhance the bioavailability and potency of NO represent promising therapeutic approaches that may preserve immune function and prevent the development of severe vascular disease in patients with COVID-19.Non-alcoholic fatty liver (NAFLD) over the past years has become a metabolic pandemic linked to a collection of metabolic diseases. The nuclear receptors ERRs, REV-ERBs, RORs, FXR, PPARs, and LXR are master regulators of metabolism and liver physiology. The characterization of these nuclear receptors and their biology has promoted the development of synthetic ligands. The possibility of targeting these receptors to treat NAFLD is promising, as several compounds including Cilofexor, thiazolidinediones, and Saroglitazar are currently undergoing clinical trials. This review focuses on the latest development of the pharmacology of these metabolic nuclear receptors and how they may be utilized to treat NAFLD and subsequent comorbidities.Tsukushi (TSK) is a member of the small leucine-rich proteoglycan family that controls developmental processes and organogenesis. TSK was also identified as a new hepatokine, which is mainly expressed in the liver, and is secreted by hepatocytes, to regulate energy and glycolipid metabolism in response to nonalcoholic fatty liver disease. However, the role of plasma TSK, especially its role in the general population, has not been fully addressed. We investigated the associations between plasma TSK concentration and several metabolic markers, including fibroblast growth factor 21 (FGF21), a hepatokine, and adiponectin, an adipokine, in 253 subjects (men/women 114/139) with no medication in the Tanno-Sobetsu Study, which employed a population-based cohort. There was no significant sex difference in plasma TSK concentration, and the level was positively correlated with the fatty liver index (FLI) (r = 0.131, p = 0.038), levels of insulin (r = 0.295, p < 0.001) and levels of FGF21 (r = 0.290, p < 0.001), and was negatively correlated with the total cholesterol level (r = -0.124, p = 0.049). There was no significant correlation between the TSK level and body mass index, waist circumference, adiponectin, high-density lipoprotein cholesterol or total bile acids. The multivariable regression analysis showed that high levels of insulin and FGF21 and a low level of total cholesterol were independent determinants of plasma TSK concentration, after adjustment for age, sex and FLI. In conclusion, plasma TSK concentration is independently associated with high levels of insulin and FGF21, a hepatokine, and a low level of total cholesterol, but not with adiposity and adiponectin, in a general population of subjects who have not taken any medications.Plant roots exude a wide variety of secondary metabolites able to attract and/or control a large diversity of microbial species. In return, among the root microbiota, some bacteria can promote plant development. Among these, Pseudomonas are known to produce a wide diversity of secondary metabolites that could have biological activity on the host plant and other soil microorganisms. We previously showed that wheat can interfere with Pseudomonas secondary metabolism production through its root metabolites. Interestingly, production of Pseudomonas bioactive metabolites, such as phloroglucinol, phenazines, pyrrolnitrin, or acyl homoserine lactones, are modified in the presence of wheat root extracts. A new cross metabolomic approach was then performed to evaluate if wheat metabolic interferences on Pseudomonas secondary metabolites production have consequences on wheat metabolome itself. Two different Pseudomonas strains were conditioned by wheat root extracts from two genotypes, leading to modification of bacterial secondary metabolites production. Bacterial cells were then inoculated on each wheat genotypes. Then, wheat root metabolomes were analyzed by untargeted metabolomic, and metabolites from the Adular genotype were characterized by molecular network. This allows us to evaluate if wheat differently recognizes the bacterial cells that have already been into contact with plants and highlights bioactive metabolites involved in wheat-Pseudomonas interaction.Kombucha is a fermented beverage obtained through the activity of a complex microbial community of yeasts and bacteria. Exo-metabolomes of kombucha microorganisms were analyzed using FT-ICR-MS to investigate their interactions. A simplified set of microorganisms including two yeasts (Brettanomyces bruxellensis and Hanseniaspora valbyensis) and one acetic acid bacterium (Acetobacter indonesiensis) was used to investigate yeast-yeast and yeast-acetic acid bacterium interactions. A yeast-yeast interaction was characterized by the release and consumption of fatty acids and peptides, possibly in relationship to commensalism. A yeast-acetic acid bacterium interaction was different depending on yeast species. With B. find more bruxellensis, fatty acids and peptides were mainly produced along with consumption of sucrose, fatty acids and polysaccharides. In opposition, the presence of H. valbyensis induced mainly the decrease of polyphenols, peptides, fatty acids, phenolic acids and putative isopropyl malate and phenylpyruvate and few formulae have been produced. With all three microorganisms, the formulae involved with the yeast-yeast interactions were consumed or not produced in the presence of A. indonesiensis. The impact of the yeasts' presence on A. indonesiensis was consistent regardless of the yeast species with a commensal consumption of compounds associated to the acetic acid bacterium by yeasts. In detail, hydroxystearate from yeasts and dehydroquinate from A. indonesiensis were potentially consumed in all cases of yeast(s)-acetic acid bacterium pairing, highlighting mutualistic behavior.Indoles are formed from dietary tryptophan by tryptophanase-positive bacterium. A few amounts of indole are excreted in the urine. On the other hand, cigarette smoke contains indoles, which could also change the urine indole levels. This study sought to elucidate the relationship between urine indole levels and smoking habits. A total of 273 healthy men (46 ± 6 years old) were enrolled in the study. Fasting urine and blood samples were obtained in the morning. The indole concentration was measured by a commercialized kit with a modified Kovac's reagent. The relationship with smoking status was evaluated. The median value of the urine indole test was 29.2 mg/L (interquartile range; 19.6-40.8). The urine indole level was significantly elevated in the smoking subjects (non-smoking group, 28.9 (20.9-39.1) mg/L, n = 94; past-smoking group, 24.5 (15.7-35.5) mg/L, n = 108; current-smoking group, 34.3 (26.9-45.0) mg/L, n = 71). In the current-smoking group, urine indole levels correlated with the number of cigarettes per day (ρ = 0.224, p = 0.060). A multivariate regression test with stepwise method revealed that the factors relating to urine indole level were current smoking (yes 1/no 0) (standardized coefficient β = 0.173, p = 0.004), blood urea nitrogen (β = 0.152, p = 0.011), and triglyceride (β = -0.116, p = 0.051). The result suggests that smoking is associated with increased urine indole levels. The practical test might be used as a screening tool to identify the harmful effect of smoking.Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive loss of the upper and lower motor neurons. Despite the increasing effort in understanding the etiopathology of ALS, it still remains an obscure disease, and no therapies are currently available to halt its progression. Following the discovery of the first gene associated with familial forms of ALS, Cu-Zn superoxide dismutase, it appeared evident that mitochondria were key elements in the onset of the pathology. However, as more and more ALS-related genes were discovered, the attention shifted from mitochondria impairment to other biological functions such as protein aggregation and RNA metabolism. In recent years, mitochondria have again earned central, mechanistic roles in the pathology, due to accumulating evidence of their derangement in ALS animal models and patients, often resulting in the dysregulation of the energetic metabolism. In this review, we first provide an update of the last lustrum on the molecular mechanisms by which the most well-known ALS-related proteins affect mitochondrial functions and cellular bioenergetics. Next, we focus on evidence gathered from human specimens and advance the concept of a cellular-specific mitochondrial "metabolic threshold", which may appear pivotal in ALS pathogenesis.Point-of-care screening tools are essential to expedite patient care and decrease reliance on slow diagnostic tools (e.g., microbial cultures) to identify pathogens and their associated antibiotic resistance. Analysis of volatile organic compounds (VOC) emitted from biological media has seen increased attention in recent years as a potential non-invasive diagnostic procedure. This work explores the use of solid phase micro-extraction (SPME) and ambient plasma ionization mass spectrometry (MS) to rapidly acquire VOC signatures of bacteria and fungi. The MS spectrum of each pathogen goes through a preprocessing and feature extraction pipeline. Various supervised and unsupervised machine learning (ML) classification algorithms are trained and evaluated on the extracted feature set. These are able to classify the type of pathogen as bacteria or fungi with high accuracy, while marked progress is also made in identifying specific strains of bacteria. This study presents a new approach for the identification of pathogens from VOC signatures collected using SPME and ambient ionization MS by training classifiers on just a few samples of data. This ambient plasma ionization and ML approach is robust, rapid, precise, and can potentially be used as a non-invasive clinical diagnostic tool for point-of-care applications.Alzheimer's disease (AD) is the most common progressive neurodegenerative disease. 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) is widely used to predict AD using a deep learning model. However, the effects of noise and blurring on 18F-FDG PET images were not considered. The performance of a classification model trained using raw, deblurred (by the fast total variation deblurring method), or denoised (by the median modified Wiener filter) 18F-FDG PET images without or with cropping around the limbic system area using a 3D deep convolutional neural network was investigated. The classification model trained using denoised whole-brain 18F-FDG PET images achieved classification performance (0.75/0.65/0.79/0.39 for sensitivity/specificity/F1-score/Matthews correlation coefficient (MCC), respectively) higher than that with raw and deblurred 18F-FDG PET images. The classification model trained using cropped raw 18F-FDG PET images achieved higher performance (0.78/0.63/0.81/0.40 for sensitivity/specificity/F1-score/MCC) than the whole-brain 18F-FDG PET images (0.72/0.32/0.71/0.10 for sensitivity/specificity/F1-score/MCC, respectively). The 18F-FDG PET image deblurring and cropping (0.89/0.67/0.88/0.57 for sensitivity/specificity/F1-score/MCC) procedures were the most helpful for improving performance. For this model, the right middle frontal, middle temporal, insula, and hippocampus areas were the most predictive of AD using the class activation map. Our findings demonstrate that 18F-FDG PET image preprocessing and cropping improves the explainability and potential clinical applicability of deep learning models.