Randomised controlled trial combining vitamin E-functionalised chocolate with physical exercise to reduce the risk of protein-energy malnutrition in predementia aged people: study protocol for Choko-Age.

OBJECTIVE: Protein-energy malnutrition and the subsequent muscle wasting (sarcopenia) are common ageing complications. It is knowing to be also associated with dementia. Our programme will test the cytoprotective functions of vitamin E combined with the cortisol-lowering effect of chocolate polyphenols (PP), in combination with muscle anabolic effect of adequate dietary protein intake and physical exercise to prevent the age-dependent decline of muscle mass and its key underpinning mechanisms including mitochondrial function, and nutrient metabolism in muscle in the elderly. METHODS AND ANALYSIS: In 2020, a 6-month double-blind randomised controlled trial in 75 predementia older people was launched to prevent muscle mass loss, in respond to the 'Joint Programming Initiative A healthy diet for a healthy life'. In the run-in phase, participants will be stabilised on a protein-rich diet (0.9-1.0 g protein/kg ideal body weight/day) and physical exercise programme (high-intensity interval training specifically developed for these subjects). Subsequently, they will be randomised into three groups (1:1:1). The study arms will have a similar isocaloric diet and follow a similar physical exercise programme. Control group (n=25) will maintain the baseline diet; intervention groups will consume either 30 g/day of dark chocolate containing 500 mg total PP (corresponding to 60 mg epicatechin) and 100 mg vitamin E (as RRR-alpha-tocopherol) (n=25); or the high polyphenol chocolate without additional vitamin E (n=25). Muscle mass will be the primary endpoint. Other outcomes are neurocognitive status and previously identified biomolecular indices of frailty in predementia patients. Muscle biopsies will be collected to assess myocyte contraction and mitochondrial metabolism. Blood and plasma samples will be analysed for laboratory endpoints including nutrition metabolism and omics. ETHICS AND DISSEMINATION: All the ethical and regulatory approvals have been obtained by the ethical committees of the Azienda Ospedaliera Universitaria Integrata of Verona with respect to scientific content and compliance with applicable research and human subjects' regulation. Given the broader interest of the society toward undernutrition in the elderly, we identify four main target audiences for our research activity: national and local health systems, both internal and external to the project; targeted population (the elderly); general public; and academia. These activities include scientific workshops, public health awareness campaigns, project dedicated website and publication is scientific peer-review journals. TRIAL REGISTRATION NUMBER: NCT05343611.

Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration.

Introduction: Age related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly confer risk for advanced disease. Due to the differential cholesterol composition of drusen and SDD, lipid transfer and cycling between photoreceptors and support cells are candidate dysregulated pathways leading to deposit formation. The current study explores this hypothesis through a comprehensive lipid compositional analysis of SDD. Methods: Histology and transmission electron microscopy were used to characterize the morphology of SDD. Highly sensitive tools of imaging mass spectrometry (IMS) and nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) in positive and negative ion modes were used to spatially map and identify SDD lipids, respectively. An interpretable supervised machine learning approach was utilized to compare the lipid composition of SDD to regions of uninvolved retina across 1873 IMS features and to automatically discern candidate markers for SDD. Immunohistochemistry (IHC) was used to localize secretory phospholipase A2 group 5 (PLA2G5). Results: Among the 1873 detected features in IMS data, three lipid classes, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lysophosphatidic acid (LysoPA) were observed nearly exclusively in SDD while presumed precursors, including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidic acid (PA) lipids were detected in SDD and adjacent photoreceptor outer segments. Molecular signals specific to SDD were found in central retina and elsewhere. IHC results indicated abundant PLA2G5 in photoreceptors and retinal pigment epithelium (RPE). Discussion: The abundance of lysolipids in SDD implicates lipid remodeling or degradation in deposit formation, consistent with ultrastructural evidence of electron dense lipid-containing structures distinct from photoreceptor outer segment disks and immunolocalization of secretory PLA2G5 in photoreceptors and RPE. Further studies are required to understand the role of lipid signals observed in and around SDD.

Mapping the Lipids of Skin Sebaceous Glands and Hair Follicles by High Spatial Resolution MALDI Imaging Mass Spectrometry.

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a technology that utilizes the high sensitivity and specificity of mass spectrometry, combined with a high spatial resolution to characterize the molecular species present in skin tissue. In this article, we use MALDI IMS to map specific lipids characteristic of two important skin appendages in minipig skin: the sebaceous glands and hair follicles. A set of specific lipid markers linked to the synthesis of sebum, stages of sebum production, and the secretion of sebum for two different sebaceous gland subzones, the peripheral and central necrotic, were identified. Furthermore, biochemical pathway analysis of the identified markers provides potential drug-targeting strategies to reduce sebum overproduction in pathological conditions. In addition, specific lipid markers characteristic of the different layers in the hair follicle bulge area, including the outer root sheath, the inner root sheath, and the medulla that are associated with the growth cycles of the hair, were determined. This research highlights the ability of MALDI IMS to link a molecular distribution not only to the morphological features in skin tissue but to the physiological state as well. Thus, this platform can provide a basis for the investigation of biochemical pathways as well as the mechanisms of disease and pharmacology in the skin, which will ultimately be critical for drug discovery and the development of dermatology-related illnesses.

Mass Spectrometry Imaging Disclosed Spatial Distribution of Defense-Related Metabolites in Triticum spp.

Fusarium Head Blight is the most common fungal disease that strongly affects Triticum spp., reducing crop yield and leading to the accumulation of toxic metabolites. Several studies have investigated the plant metabolic response to counteract mycotoxins accumulation. However, information on the precise location where the defense mechanism is taking place is scarce. Therefore, this study aimed to investigate the specific tissue distribution of defense metabolites in two Triticum species and use this information to postulate on the metabolites' functional role, unlocking the "location-to-function" paradigm. To address this challenge, transversal cross-sections were obtained from the middle of the grains. They were analyzed using an atmospheric-pressure (AP) SMALDI MSI source (AP-SMALDI5 AF, TransMIT GmbH, Giessen, Germany) coupled to a Q Exactive HF (Thermo Fisher Scientific GmbH, Bremen, Germany) orbital trapping mass spectrometer. Our result revealed the capability of (AP)-SMALDI MSI instrumentation to finely investigate the spatial distribution of wheat defense metabolites, such as hydroxycinnamic acid amides, oxylipins, linoleic and α-linoleic acids, galactolipids, and glycerolipids.

Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications. In this work, we revised a well-established molecular mechanics' force field and applied a hybrid quantum mechanics and machine learning approach to parametrize the hydrogen-bonding (HB) potentials of small molecules, improving this aspect of the molecular description. Approximately 66,000 molecules were chosen from available drug databases and subjected to density functional theory calculations (DFT). For each atom, the molecular electrostatic potential (EP) was extracted and used to derive new HB energy contributions; this was subsequently combined with a fingerprint-based description of the structural environment via partial least squares modeling, enabling the new potentials to be used for molecules outside of the training set. We demonstrate that parameter prediction for molecules outside of the training set correlates with their DFT-derived EP, and that there is correlation of the new potentials with hydrogen-bond acidity and basicity scales. We show the newly derived MIFs vary in strength for various ring substitution in accordance with chemical intuition. Finally, we report that this derived parameter, when extended to non-HB atoms, can also be used to estimate sites of reaction.

Mycotoxin Uptake in Wheat - Eavesdropping Fusarium Presence for Priming Plant Defenses or a Trojan Horse to Weaken Them?

Fusarium mycotoxins represent a major threat for cereal crops and food safety. While previous investigations have described plant biotransforming properties on mycotoxins or metabolic relapses of fungal infections in plants, so far, the potential consequences of radical exposure in healthy crops are mostly unknown. Therefore, we aimed at evaluating whether the exposure to mycotoxins, deoxynivalenol (DON) and zearalenone (ZEN), at the plant-soil interface may be considered a form of biotic stress capable of inducing priming or a potential initiation of fungal attack. To address this, we used atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging to investigate the activation or the inhibition of specific biosynthetic pathways and in situ localization of primary and secondary metabolites in wheat. According to our untargeted metabolomics investigation, the translocation of plant defense metabolites (i.e., hydroxycinnamic acid amide and flavones) follows the mycotoxin accumulation organs, which is the root for ZEN-treated plantlet and culm for DON-treated sample, suggesting a local "defense-on-demand response." Therefore, it can be hypothesized that DON and ZEN are involved in the eavesdropping of Fusarium presence in soil and that wheat response based on secondary metabolites may operate on multiple organs with a potential interplay that involves masked mycotoxins.

Infrared MALDI Mass Spectrometry with Laser-Induced Postionization for Imaging of Bacterial Colonies.

Ultraviolet matrix-assisted laser desorption ionization mass spectrometry imaging (UV-MALDI-MSI) is a powerful tool to visualize bacterial metabolites in microbial colonies and in biofilms. However, a challenge for the method is the efficient extraction of analytes from deeper within the bacterial colonies and from the cytoplasm of individual cells during the matrix coating step. Here, we used a pulsed infrared (IR) laser of 2.94 µm wavelength to disrupt and ablate bacterial cells without a prior coating with a MALDI matrix. Instead, tissue water or, in some experiments, in addition a small amount of glycerol was exploited for the deposition of the IR laser energy and for supporting the ionization of the analytes. Compared to water, glycerol exhibits a lower vapor pressure, which prolonged the available measurement time window within an MSI experiment. Mass spectra were acquired with a hybrid Synapt G2-S HDMS instrument at a pixel size of 120 µm. A frequency-quadrupled q-switched Nd:YAG laser with 266 nm wavelength served for laser-induced postionization (MALDI-2). In this way, the ion abundances of numerous small molecules such as nucleobases, 2-alkyl-quinolones, a prominent class of Pseudomonas aeruginosa signaling molecules involved in one of the three quorum-sensing pathways, and also the signals of various bacterial phospholipids were boosted, partially by orders of magnitude. We analyzed single and cocultured colonies of Gram-negative P. aeruginosa and of Gram-positive Bacillus subtilis and Staphylococcus aureus as exemplary bacterial systems. To enable a rapid (within 5 s) MSI-compatible steam inactivation in a custom-made autoclave filled with hot water steam, bacterial cultures were grown on porous polyamide membranes. Compared to a UV-MALDI-2-MS measurement of the same systems, mass spectra with a reduced low mass background were generally generated. This resulted in the unequivocal detection of numerous metabolites only with the IR laser. In a fundamental part of our study, and to optimize the IR-MALDI-2 approach for the highest analytical sensitivity, we characterized the expansion dynamics of the particle plume as generated by the IR laser. Here, we recorded the total ion count and the intensities of selected signals registered from P. aeruginosa samples as a function of the interlaser delay and buffer gas pressure in the ion source. The data revealed that the IR-MALDI-2 ion signals are primarily generated from slow particles having mean velocities of ∼10 m/s. Interestingly, two different pressure/delay time regimes of the optimized ionization efficiency for phospholipids and smaller metabolites, respectively, were revealed, a result pointing to yet-unknown convoluted reaction cascades. The described IR-MALDI-2 method could be a helpful new tool for a microbial mass spectrometry imaging of small molecules requiring little sample preparation.

How Can Chemometrics Support the Development of Point of Need Devices?

The necessity to establish novel solutions for decentralized monitoring is attracting attention in all fields of analytical chemistry, i.e., clinical, pharmaceutical, environmental, agri-food. The research around the terms "point-of-need", "point-of-care", "lab-on-chip", "biosensor", "microfluidics", etc. is/has been always aimed at the possibility to produce easy-to-use and fast-response devices to be used by nonspecialists. However, the routes to produce the optimal device might be time-consuming and costly. In this Feature, we would like to highlight the role of chemometric-based approaches that are useful in the conceptualization, production, and data analysis in developing reliable portable devices and also decrease the amount of experiments (thus, costs) at the same time. Readers will be provided a concise overview regarding the most employed chemometric tools used for target identification, design of experiments, data analysis, and digitalization of results applied to the development of diverse portable analytical platforms. This Feature provides a tutorial perspective regarding all the major methods and applications that have been currently developed. In particular, the presence of a concise and informative table assists analytical chemists in utilizing the right chemometrics-based tool depending on the architectures and transduction.

High-Spatial-Resolution Multimodal Imaging by Tapping-Mode Scanning Probe Electrospray Ionization with Feedback Control.

Direct extraction and ionization techniques using minute amounts of solvent can be employed for the rapid analysis of chemical components in a sample without any sample preparation steps. This type of approach is important for mass spectrometry imaging of samples with multiple chemical components that have different spatial distributions (i.e., biological tissues). To improve the spatial resolution of such imaging, it is necessary to reduce the solvent volume for extraction and deliver it to the sample surface. This report describes a feedback control system applied to tapping-mode scanning probe electrospray ionization. By combining the measurement technique of capillary probe vibration with the dynamic distance control system between the probe and the sample, the vibration amplitude of the probe is maintained while the probe scans over uneven samples. This method allows simultaneous high-resolution imaging of molecular distribution, surface topography, and amplitude/phase changes in the probe vibration. Such multimodal imaging is demonstrated on rhodamine B thin films in microwells and on a mouse brain tissue section. This technique can generally be applied to examine the multidimensional molecular distribution and the surface profiles of various objects.

Unveiling the spatial distribution of aflatoxin B1 and plant defense metabolites in maize using AP-SMALDI mass spectrometry imaging.

In order to cope with the presence of unfavorable compounds, plants can biotransform xenobiotics, translocate both parent compounds and metabolites, and perform compartmentation and segregation at the cellular or tissue level. Such a scenario also applies to mycotoxins, fungal secondary metabolites with a pre-eminent role in plant infection. In this work, we aimed to describe the effect of the interplay between Zea mays (maize) and aflatoxin B1 (AFB1) at the tissue and organ level. To address this challenge, we used atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI) to investigate the biotransformation, localization and subsequent effects of AFB1 on primary and secondary metabolism of healthy maize plants, both in situ and from a metabolomics standpoint. High spatial resolution (5 µm) provided fine localization of AFB1, which was located within the root intercellular spaces, and co-localized with its phase-I metabolite aflatoxin M2. We provided a parallel visualization of maize metabolic changes, induced in different organs and tissues by an accumulation of AFB1. According to our untargeted metabolomics investigation, anthocyanin biosynthesis and chlorophyll metabolism in roots are most affected. The biosynthesis of these metabolites appears to be inhibited by AFB1 accumulation. On the other hand, metabolites found in above-ground organs suggest that the presence of AFB1 may also activate the biochemical response in the absence of an actual fungal infection; indeed, several plant secondary metabolites known for their antimicrobial or antioxidant activities were localized in the outer tissues, such as phenylpropanoids, benzoxazinoids, phytohormones and lipids.

LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging.

Mass Spectrometry Imaging (MSI) is an established and powerful MS technique that enables molecular mapping of tissues and cells finding widespread applications in academic, medical, and pharmaceutical industries. As both the applications and MSI technology have undergone rapid growth and improvement, the challenges associated both with analyzing large datasets and identifying the many detected molecular species have become apparent. The lack of readily available and comprehensive software covering all necessary data analysis steps has further compounded this challenge. To address this issue we developed LipostarMSI, comprehensive and vendor-neutral software for targeted and untargeted MSI data analysis. Through user-friendly implementation of image visualization and co-registration, univariate and multivariate image and spectral analysis, and for the first time, advanced lipid, metabolite, and drug metabolite (MetID) automated identification, LipostarMSI effectively streamlines biochemical interpretation of the data. Here, we introduce LipostarMSI and case studies demonstrating the versatility and many capabilities of the software.

Dual Laser and Desorption Electrospray Ionization Mass Spectrometry Imaging Using the Same Interface.

For a more comprehensive characterization of molecular heterogeneities of matter, multimodal mass spectrometry imaging must be developed to take advantage of the complementarity of information available through different ionization mechanisms. We report the design, implementation, and performance validation of a laser desorption imaging interface composed of add-on components that adapt a commercial Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) imaging interface for dual imaging of Picosecond Infrared Laser Mass Spectrometry (PIRL-MS) with DESI-MS. The interface utilizes hardware elements and data analysis pipelines already established for DESI-MS imaging, and was further validated in cancer margin assessments using human medulloblastoma cancers. The PIRL-MS images were robust and reproducible across multiple experimental runs on independently prepared xenograft tumors, and could be segmented into cancer and healthy regions in concordance with pathology using a variety of supervised and unsupervised clustering methods. The spectral quality and complexity obtained with this interface were examined with infiltrating and noninfiltrating tumors, and were comparable to other mass spectrometry analysis interfaces. The average PIRL-MS spectra from spatially resolved images could be used for robust cancer m/z model building to classify medulloblastoma cancer from healthy tissue without any misclassifications, an observation that held true over close to 70 sampling data points. While the unsupervised spectral analysis methods suggested a slight suppression of signal in the phospholipid range compared to the hand-held configuration, these changes were insufficient to hamper utility in cancer margin assessment with spatially resolved data obtained with our interface. Dual PIRL-MS and DESI-MS imaging of consecutive sections, as suggested by multivariate loading plots, revealed highly complementary molecular information with m/z values identifiable with one desorption method sufficient to reveal cancer regions being absent in another, further emphasizing the need for effective hardware and software interfaces for dual mass spectrometry imaging.

From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions.

Aldehyde oxidase (AOX) is a molibdo-flavoenzyme that has raised great interest in recent years, since its contribution in xenobiotic metabolism has not always been identified before clinical trials, with consequent negative effects on the fate of new potential drugs. The fundamental role of AOX in metabolizing xenobiotics is also due to the attempt of medicinal chemists to stabilize candidates toward cytochrome P450 activity, which increases the risk for new compounds to be susceptible to AOX nucleophile attack. Therefore, novel strategies to predict the potential liability of new entities toward the AOX enzyme are urgently needed to increase effectiveness, reduce costs, and prioritize experimental studies. In the present work, we present the most up-to-date computational method to predict liability toward human AOX (hAOX), for applications in drug design and pharmacokinetic optimization. The method was developed using a large data set of homogeneous experimental data, which is also disclosed as Supporting Information .

Efficient and regioselective one-step synthesis of 7-aryl-5-methyl- and 5-aryl-7-methyl-2-amino-[1,2,4]triazolo[1,5-a]pyrimidine derivatives.

Two facile and efficient one-step procedures for the regioselective synthesis of 7-aryl-5-methyl- and 5-aryl-7-methyl-2-amino-[1,2,4]triazolo[1,5-a]pyrimidines have been developed, via reactions of 3,5-diamino-1,2,4-triazole with variously substituted 1-aryl-1,3-butanediones and 1-aryl-2-buten-1-ones, respectively. The excellent yield and/or regioselectivity shown by the reactions decreased when ethyl 5-amino-1,2,4-triazole-3-carboxylate was used. [1,2,4]Triazolo[1,5-a]pyrimidine being a privileged scaffold, the procedures herein reported may be useful for the preparation of biologically active compounds. In this study, the preparation of a set of compounds based on the [1,2,4]triazolo[1,5-a]pyrimidine scaffold led to the identification of compound 20 endowed with a very promising ability to inhibit influenza virus RNA polymerase PA-PB1 subunit heterodimerization.

Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics.

To date, the main limitations for LC-MS-based untargeted lipidomics reside in the lack of adequate computational and cheminformatics tools that are able to support the analysis of several thousands of species from biological samples, enabling data mining and automating lipid identification and external prediction processes. To address these issues, we developed Lipostar, novel vendor-neutral high-throughput software that effectively supports both targeted and untargeted LC-MS lipidomics, implementing data acquisition, user-friendly multivariate analysis (to be used for model generation and new sample predictions), and advanced lipid identification protocols that can work with or without the support of preformed lipid databases. Moreover, Lipostar integrates the lipidomic processes with a full metabolite identification (MetID) procedure, essential in drug safety applications and in translational studies. Case studies demonstrating a number of Lipostar features are also presented.

Structure-metabolism relationships in human-AOX: Chemical insights from a large database of aza-aromatic and amide compounds.

Aldehyde oxidase (AOX) is a metabolic enzyme catalyzing the oxidation of aldehyde and aza-aromatic compounds and the hydrolysis of amides, moieties frequently shared by the majority of drugs. Despite its key role in human metabolism, to date only fragmentary information about the chemical features responsible for AOX susceptibility are reported and only "very local" structure-metabolism relationships based on a small number of similar compounds have been developed. This study reports a more comprehensive coverage of the chemical space of structures with a high risk of AOX phase I metabolism in humans. More than 270 compounds were studied to identify the site of metabolism and the metabolite(s). Both electronic [supported by density functional theory (DFT) calculations] and exposure effects were considered when rationalizing the structure-metabolism relationship.

Use of lipidomics to investigate sebum dysfunction in juvenile acne.

Acne is a multifactorial skin disorder frequently observed during adolescence with different grades of severity. Multiple factors centering on sebum secretion are implicated in acne pathogenesis. Despite the recognized role of sebum, its compositional complexity and limited analytical approaches have hampered investigation of alterations specifically associated with acne. To examine the profiles of lipid distribution in acne sebum, 61 adolescents (29 males and 32 females) were enrolled in this study. Seventeen subjects presented no apparent clinical signs of acne. The 44 affected individuals were clinically classified as mild (13 individuals), moderate (19 individuals), and severe (12 individuals) acne. Sebum was sampled from the forehead with Sebutape(TM) adhesive patches. Profiles of neutral lipids were acquired with rapid-resolution reversed-phase/HPLC-TOF/MS in positive ion mode. Univariate and multivariate statistical analyses led to the identification of lipid species with significantly different levels between healthy and acne sebum. The majority of differentiating lipid species were diacylglycerols (DGs), followed by fatty acyls, sterols, and prenols. Overall, the data indicated an association between the clinical grading of acne and sebaceous lipid fingerprints and highlighted DGs as more abundant in sebum from adolescents affected with acne.

Benchmarking DFT and semi-empirical methods for a reliable and cost-efficient computational screening of benzofulvene derivatives as donor materials for small-molecule organic solar cells.

A systematic computational investigation on the optical properties of a group of novel benzofulvene derivatives (Martinelli 2014 Org. Lett. 16 3424-7), proposed as possible donor materials in small molecule organic photovoltaic (smOPV) devices, is presented. A benchmark evaluation against experimental results on the accuracy of different exchange and correlation functionals and semi-empirical methods in predicting both reliable ground state equilibrium geometries and electronic absorption spectra is carried out. The benchmark of the geometry optimization level indicated that the best agreement with x-ray data is achieved by using the B3LYP functional. Concerning the optical gap prediction, we found that, among the employed functionals, MPW1K provides the most accurate excitation energies over the entire set of benzofulvenes. Similarly reliable results were also obtained for range-separated hybrid functionals (CAM-B3LYP and wB97XD) and for global hybrid methods incorporating a large amount of non-local exchange (M06-2X and M06-HF). Density functional theory (DFT) hybrids with a moderate (about 20-30%) extent of Hartree-Fock exchange (HFexc) (PBE0, B3LYP and M06) were also found to deliver HOMO-LUMO energy gaps which compare well with the experimental absorption maxima, thus representing a valuable alternative for a prompt and predictive estimation of the optical gap. The possibility of using completely semi-empirical approaches (AM1/ZINDO) is also discussed.