Making waves: The NORMAN antibiotic resistant bacteria and resistance genes database (NORMAN ARB&ARG)-An invitation for collaboration to tackle antibiotic resistance.

With the global concerns on antibiotic resistance (AR) as a public health issue, it is pivotal to have data exchange platforms for studies on antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment. For this purpose, the NORMAN Association is hosting the NORMAN ARB&ARG database, which was developed within the European project ANSWER. The present article provides an overview on the database functionalities, the extraction and the contribution of data to the database. In this study, AR data from three studies from China and Nepal were extracted and imported into the NORMAN ARB&ARG in addition to the existing AR data from 11 studies (mainly European studies) on the database. This feasibility study demonstrates how the scientific community can share their data on AR to generate an international evidence base to inform AR mitigation strategies. The open and FAIR data are of high potential relevance for regulatory applications, including the development of emission limit values / environmental quality standards in relation to AR. The growth in sharing of data and analytical methods will foster collaboration on risk management of AR worldwide, and facilitate the harmonization in the effort for identification and surveillance of critical hotspots of AR. The NORMAN ARB&ARG database is publicly available at: https://www.norman-network.com/nds/bacteria/.

NMR-guided isolation of undescribed triterpenoid saponins from Lysimachia atropurpurea L.

Phytochemical investigation on aerial parts of Lysimachia atropurpurea L. (Myrsinaceae), guided by NMR methods, resulted in the isolation and characterization of three previously undescribed triterpenoid saponins named stralysaponins A-C along with five known compounds. Their structures were elucidated by 1D and 2D NMR spectroscopy and HR-ESI-MS. Stralysaponins A-C were categorized into 13ß-28-epoxyoleanane-type triterpenoid saponins, reaffirming their prevalent presence of this type in the Myrsinaceae family and the genus Lysimachia. The identified derivatives share a common four-unit branched sugar chain, with rhamnose as the terminal sugar linked at C-3 of the aglycone. The presence of triterpenoid saponins in L. atropurpurea is reported herein for the first time. This study enriched the chemical diversity of triterpenoid saponins of the genus Lysimachia. Additionally, it demonstrates the effectiveness of NMR-profiling in isolating previously undescribed triterpenoid saponins from Lysimachia spp.

A comprehensive HRMS methodology using LC-(ESI)-/GC-(APCI)-QTOF MS complementary platforms for wide-scope target screening of >750 pesticides in olive oil.

This study presents the development and validation of a comprehensive high-resolution mass spectrometry (HRMS) methodology for the detection of 771 pesticides in olive oil, using liquid chromatography with electrospray ionization, operating in positive and negative mode, and gas chromatography with atmospheric-pressure chemical ionization in positive mode, both coupled to quadrupole-time-of-flight mass spectrometry (LC-(ESI)-/GC-(APCI)-QTOF MS). Special reference is made to the post-acquisition evaluation step, in which all LC/GC-HRMS analytical evidence (i.e. mass accuracy, retention time, isotopic pattern, MS/MS fragmentation) is taken into account in order to successfully identify the compounds. The sample preparation of the method involves a QuEChERS-based protocol, common for both techniques, differentiated only on the reconstitution step, making the method highly applicable in routine analysis. A smart evaluation of method's performance was carried out, with 65 representative analytes comprising the validation set. The method was validated in terms of linearity, accuracy, matrix effect and precision, while the limits of detection and quantification of the method were estimated. Finally, twenty Greek olive oil samples were analysed in both analytical platforms and the findings included the pesticides lambda-cyhalothrin, chlorpyrifos, phosphamidon, pirimiphos-methyl and esprocarb at low ng g-1 level.

Significant Turning Point: Common Buzzard (Buteo buteo) Exposure to Second-Generation Anticoagulant Rodenticides in the United Kingdom.

Second-generation anticoagulant rodenticides (SGARs) are widely used to control rodent populations, resulting in the serious secondary exposure of predators to these contaminants. In the United Kingdom (UK), professional use and purchase of SGARs were revised in the 2010s. Certain highly toxic SGARs have been authorized since then to be used outdoors around buildings as resistance-breaking chemicals under risk mitigation procedures. However, it is still uncertain whether and how these regulatory changes have influenced the secondary exposure of birds of prey to SGARs. Based on biomonitoring of the UK Common Buzzard (Buteo buteo) collected from 2001 to 2019, we assessed the temporal trend of exposure to SGARs and statistically determined potential turning points. The magnitude of difenacoum decreased over time with a seasonal fluctuation, while the magnitude and prevalence of more toxic brodifacoum, authorized to be used outdoors around buildings after the regulatory changes, increased. The summer of 2016 was statistically identified as a turning point for exposure to brodifacoum and summed SGARs that increased after this point. This time point coincided with the aforementioned regulatory changes. Our findings suggest a possible shift in SGAR use to brodifacoum from difenacoum over the decades, which may pose higher risks of impacts on wildlife.

Evaluating an integrated nano zero-valent iron column system for emerging contaminants removal from different wastewater matrices - Identification of transformation products.

The presence of micropollutants in water bodies has become a growing concern due to their persistence, bioaccumulation and potential toxicological effects on aquatic life and humans. In this study, the performance of a column system consisting of zero-valent iron nanoparticles (nZVI) incorporated into a cationic resin and synthesized from green tea extract with the addition of persulfate for the elimination of selected pharmaceuticals and endocrine disruptors from wastewater is evaluated. Ibuprofen, naproxen, diclofenac and ketoprofen were the target pharmaceuticals from non-steroidal anti-inflammatory drugs group, while bisphenol A was the target endocrine disruptor. In this context, different real wastewater effluent matrices were investigated: anaerobic membrane bioreactor (AnMBR), upflow anaerobic sludge blanket reactor (UASB) after microfiltration, tertiary treated by conventional activated sludge system and saturated vertical constructed wetland followed by a sand filtration unit effluent (hybrid). The transformation products of diclofenac and bisphenol A were also identified. The experimental results indicated that the performance of the R-nFe/PS system towards the removal efficiency of the target compounds was enhanced in the order of effluents: tertiary > AnMBR ≈ hybrid > UASB. More than 70% removal was obtained for almost all target compounds when conventional tertiary effluent was used, while the maximum removal efficiency was about 50% in the case of filtered UASB. As far as we know, this is the first time that nZVI has been assessed in combination with persulfate for the removal of micropollutants in a continuous flow system receiving various types of real wastewater with different matrix characteristics.

Acesulfame degradation by thermally activated persulfate: Kinetics, transformation products and estimated toxicity.

The existence of the artificial sweetener acesulfame (ACE) in quantities of significance can negatively impact water quality, and its consumption has been associated with deleterious health effects. The present investigation explores the efficacy of heat-activated sodium persulfate (SPS) for eliminating ACE. The complete degradation of 0.50 mg L-1 of ACE was achieved within 45 min under a reaction temperature of 50 °C and 100 mg L-1 of SPS. The impact of thermal decomposition on ACE at a temperature of 60 °C was negligible. This study considers several factors, such as the SPS and ACE loading, the reaction temperature, the initial pH, and the water matrix of the reactor. The results indicate that the method's efficiency is positively correlated with higher initial concentrations of SPS, whereas it is inversely associated with the initial concentration of ACE. Furthermore, higher reaction temperatures and acidic initial pH levels promote the degradation of acesulfame. At the same time, certain constituents of the water matrix, such as humic acid, chlorides, and bicarbonates, can hinder the degradation process. Additionally, the data from LC-QToF-MS analysis of the samples were used to investigate transformation through suspect and non-target screening approaches. Overall, ACE's eight transformation products (TPs) were detected, and a potential ACE decomposition pathway was proposed. The concentration of TPs followed a volcano curve, decreasing in long treatment times. The ecotoxicity of ACE and its identified TPs was predicted using the ECOSAR software. The majority of TPs exhibited not harmful values.

Spike-Seq: An amplicon-based high-throughput sequencing approach for the sensitive detection and characterization of SARS-CoV-2 genetic variations in environmental samples.

Ever since the outbreak of COVID-19 disease in Wuhan, China, different variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been identified. Wastewater-based epidemiology (WBE), an approach that has been successfully applied in numerous case studies worldwide, offers a cost-effective and rapid way for monitoring trends of SARS-Cov-2 in the community level without selection bias. Despite being a gold-standard procedure, WBE is a challenging approach due to the sample instability and the moderate efficiency of SARS-CoV-2 concentration in wastewater. In the present study, we introduce Spike-Seq, a custom amplicon-based approach for the S gene sequencing of SARS-CoV-2 in wastewater samples, which enables not only the accurate identification of the existing Spike-related genetic markers, but also the estimation of their frequency in the investigated samples. The implementation of Spike-Seq involves the combination of nested PCR-based assays that efficiently amplify the entire nucleotide sequence of the S gene and next-generation sequencing, which enables the variant detection and the estimation of their frequency. In the framework of the current work, Spike-Seq was performed to investigate the mutational profile of SARS-CoV-2 in samples from the Wastewater Treatment Plant (WWTP) of Athens, Greece, which originated from multiple timepoints, ranging from March 2021 until July 2022. Our findings demonstrate that Spike-Seq efficiently detected major genetic markers of B.1.1.7 (Alpha), B.1.617.2 (Delta) as well as B.1.1.529 (Omicron) variants in wastewater samples and provided their frequency levels, showing similar variant distributions with the published clinical data from the National Public Health organization. The presented approach can prove to be a useful tool for the detection of SARS-CoV-2 in challenging wastewater samples and the identification of the existing genetic variants of S gene.

Comprehensive profiling and semi-quantification of exogenous chemicals in human urine using HRMS-based strategies.

Chemicals infiltrate our daily experiences through multiple exposure pathways. Human biomonitoring (HBM) is routinely used to comprehensively understand these chemical interactions. Historically, HBM depended on targeted screening methods limited to a relatively small set of chemicals with triple quadrupole instruments typically. However, recent advances in high-resolution mass spectrometry (HRMS) have facilitated the use of broad-scope target, suspect, and non-target strategies, enhancing chemical exposome characterization within acceptable detection limits. Despite these advancements, establishing robust and efficient sample treatment protocols is still essential for trustworthy broad-range chemical analysis. This study sought to validate a methodology leveraging HRMS-based strategies for accurate profiling of exogenous chemicals and related metabolites in urine samples. We evaluated five extraction protocols, each encompassing various chemical classes, such as pharmaceuticals, plastic additives, personal care products, and pesticides, in terms of their extraction recoveries, linearity, matrix effect, sensitivity, and reproducibility. The most effective protocol was extensively validated and subsequently applied to 10 real human urine samples using wide-scope target analysis encompassing over 2000 chemicals. We successfully identified and semi-quantified a total of 36 chemicals using an ionization efficiency-based model, affirming the methodology's robust performance. Notably, our results dismissed the need for a deconjugation step, a typically labor-intensive and time-consuming process.

Development and validation of a high-throughput headspace solid-phase microextraction gas chromatography-mass spectrometry methodology for target and suspect determination of honey volatiles.

The determination of volatile compounds is essential for the chemical characterisation of honey's aroma and its correlation to its sensory profile and botanical origin. The present study describes the development, optimization and validation of a new, simple and reliable method for the determination of volatile compounds in honey using headspace solid-phase microextraction combined with gas chromatography/mass spectrometry (HS-SPME-GC-MS). The optimization of the SPME conditions showed that the ratio of honey: water (2:1) and the incubation temperature (60 °C) are the most critical parameters. Gas chromatography was performed with medium polar Varian CP-Select 624 column and the experimental Retention Index for a number of compounds was determined as an additional identification feature for suspect analysis. The simultaneous use of four internal standards chlorobenzene, benzophenone, 2-pentanol and 4-methyl-2-pentanone and matrix matched calibration enhanced method accuracy achieving recoveries 73-114 % and repeatability ranging between 3.9 and 19 % relative standard deviations. Furthermore, the superiority of the HS-SPME to static head space technique was verified exhibiting four-to nine-fold higher sensitivity. Target and suspect screening were applied to 30 Greek honey samples and 53 volatile compounds belonging to different chemical classes, such as alkanes, aldehydes, ketones, alcohols, and esters were identified with quantified concentrations ranging between 3.1 µg kg-1 (Limonene) up to 20 mg kg-1 (Benzeneacetaldehyde). Among the new findings is the detection of Myrtenol in Greek pine honey and 2,3-butanediol in Greek oak honey. The developed analytical protocol can be a valuable tool in order to chemically characterize honey based on the volatile content.

Metabolomic Profiling of Second-Trimester Amniotic Fluid for Predicting Preterm Delivery: Insights from NMR Analysis.

Preterm delivery (PTD) is a notable pregnancy complication, affecting one out of every ten births. This study set out to investigate whether analyzing the metabolic composition of amniotic fluid (AF) collected from pregnant women during the second trimester of pregnancy could offer valuable insights into prematurity. The research employed 1H-NMR metabolomics to examine AF samples obtained from 17 women who gave birth prematurely (between 29+0 and 36+5 weeks of gestation) and 43 women who delivered at full term. The application of multivariate analysis revealed metabolites (dimethylglycine, glucose, myo-inositol, and succinate) that can serve as possible biomarkers for the prognosis and early diagnosis of preterm delivery. Additionally, pathway analysis unveiled the most critical metabolic pathways relevant to our research hypothesis. In summary, these findings suggest that the metabolic composition of AF in the second trimester can be a potential indicator for identifying biomarkers associated with the risk of PTD.

Longitudinal Plant Health Monitoring via High-Resolution Mass Spectrometry Screening Workflows: Application to a Fertilizer Mediated Tomato Growth Experiment.

Significant efforts have been spent in the modern era towards implementing environmentally friendly procedures like composting to mitigate the negative effects of intensive agricultural practices. In this context, a novel fertilizer was produced via the hydrolysis of an onion-derived compost, and has been previously comprehensively chemically characterized. In order to characterize its efficacy, the product was applied to tomato plants at five time points to monitor plant health and growth. Control samples were also used at each time point to eliminate confounding parameters due to the plant's normal growth process. After harvesting, the plant leaves were extracted using aq. MeOH (70:30, v/v) and analyzed via UPLC-QToF-MS, using a C18 column in both ionization modes (±ESI). The data-independent (DIA/bbCID) acquisition mode was employed, and the data were analyzed by MS-DIAL. Statistical analysis, including multivariate and trend analysis for longitudinal monitoring, were employed to highlight the differentiated features among the controls and treated plants as well as the time-point sequence. Metabolites related to plant growth belonging to several chemical classes were identified, proving the efficacy of the fertilizer product. Furthermore, the efficiency of the analytical and statistical workflows utilized was demonstrated.

First-Row Transition Metal Complexes Incorporating the 2-(2'-pyridyl)quinoxaline Ligand (pqx), as Potent Inflammatory Mediators: Cytotoxic Properties and Biological Activities against the Platelet-Activating Factor (PAF) and Thrombin.

Inflammatory mediators constitute a recently coined term in the field of metal-based complexes with antiplatelet activities. Our strategy targets Platelet-Activating Factor (PAF) and its receptor, which is the most potent lipid mediator of inflammation. Thus, the antiplatelet (anti-PAF) potency of any substance could be exerted by inhibiting the PAF-induced aggregation in washed rabbit platelets (WRPs), which internationally is a well-accepted methodology. Herein, a series of mononuclear (mer-[Cr(pqx)Cl3(H2O]) (1), [Co(pqx)Cl2(DMF)] (2) (DMF = N,N'-dimethyl formamide), [Cu(pqx)Cl2(DMSO)] (3) (DMSO = dimethyl sulfoxide), [Zn(pqx)Cl2] (4)) and dinuclear complexes ([Mn(pqx)(H2O)2Cl2]2 (5), [Fe(pqx)Cl2]2 (6) and [Ni(pqx)Cl2]2 (7)) incorporating the 2-(2'-pyridyl)quinoxaline ligand (pqx), were biologically evaluated as inhibitors of the PAF- and thrombin-induced aggregation in washed rabbit platelets (WRPs). The molecular structure of the five-co-ordinate analog (3) has been elucidated by single-crystal X-ray diffraction revealing a trigonal bipyramidal geometry. All complexes are potent inhibitors of the PAF-induced aggregation in WRPs in the micromolar range. Complex (6) displayed a remarkable in vitro dual inhibition against PAF and thrombin, with IC50 values of 1.79 µM and 0.46 µM, respectively. Within the series, complex (5) was less effective (IC50 = 39 µM) while complex (1) was almost 12-fold more potent against PAF, as opposed to thrombin-induced aggregation. The biological behavior of complexes 1, 6 and 7 on PAF's basic metabolic enzymatic pathways reveals that they affect key biosynthetic and catabolic enzymes of PAF underlying the anti-inflammatory properties of the relevant complexes. The in vitro cytotoxic activities of all complexes in HEK293T (human embryonic kidney cells) and HeLa cells (cervical cancer cells) are described via the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. The results reveal that complex 3 is the most potent within the series.

Co-assembled MoS2-TiO2 Inverse Opal Photocatalysts for Visible Light-Activated Pharmaceutical Photodegradation.

Heterostructured photocatalytic materials in the form of photonic crystals have been attracting attention for their unique light harvesting ability that can be ideally combined with judicious compositional modifications toward the development of visible light-activated (VLA) photonic catalysts, though practical environmental applications, such as the degradation of pharmaceutical emerging contaminants, have been rarely reported. Herein, heterostructured MoS2-TiO2 inverse opal films are introduced as highly active immobilized photocatalysts for the VLA degradation of tetracycline and ciprofloxacin broad-spectrum antibiotics as well as salicylic acid. A single-step co-assembly method was implemented for the challenging incorporation of MoS2 nanosheets into the nanocrystalline inverse opal walls. Compositional tuning and photonic band gap engineering of the MoS2-TiO2 photonic films showed that integration of low amounts of MoS2 nanosheets in the inverse opal framework maintains intact the periodic macropore structure and enhances the available surface area, resulting in efficient VLA antibiotic degradation far beyond the performance of benchmark TiO2 films. The combination of broadband MoS2 visible light absorption and photonic-assisted light trapping together with the enhanced charge separation that enables the generation of reactive oxygen species via firm interfacial coupling between MoS2 nanosheets and TiO2 nanoparticles is concluded as a competent approach for pharmaceutical abatement in water bodies.

Wastewater surveillance of the most common circulating respiratory viruses in Athens: The impact of COVID-19 on their seasonality.

Due to governments' actions to contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the activity of common circulating respiratory viruses was significantly disrupted after the COVID-19 pandemic and thorough surveillance of respiratory pathogens was considered essential worldwide. Wastewater-based epidemiology has proven to be a valuable tool, that provides complementary information on disease outbreaks and is increasingly used to study the infection dynamics of other viruses, apart from SARS-CoV-2. The aims of the present study were the detection of four commonly circulating respiratory viruses: SARS-CoV-2, influenza A, B and Human Respiratory Syncytial Virus (RSV), the evaluation of the COVID-19 pandemic impact on their seasonality and the determination of the possible common trends in the viral load of these viruses in the wastewater of the Attica region. A standardized and validated concentration and extraction protocol was used, generic for all four viruses, followed by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) assays. The study proved that there was a prolonged period when all four viruses circulated in the population and an early outbreak of seasonal influenza and RSV in 2022-2023, compared to data from the pre-COVID-19 period. SARS-CoV-2, influenza A and RSV concentrations showed peak levels during December, followed by a slight decline in influenza A concentrations, followed by steady increase of influenza B concentrations in January 2023. SARS-CoV-2 was the dominant virus throughout the whole study period. This is the first study in Greece that investigated the most common circulating viruses simultaneously and in one of the largest timelines, providing crucial information about their infection dynamics during a period when an outbreak of respiratory diseases was declared by the National Public Health Organization. Presented results highlight the establishment of environmental surveillance as a non-invasive and complementary virus outbreak monitoring tool and the importance of influenza A, B and RSV integration into a wastewater-based surveillance system to help in disease management.

Development of a novel apigenin prodrug programmed for alkaline-phosphatase instructed self-inhibition to combat cancer.

Elevated levels of alkaline phosphatase (ALP) in the tumor microenvironment (TME) are a hallmark of cancer progression and thus inhibition of ALP could serve as an effective approach against cancer. Herein, we developed a novel prodrug approach to tackle cancer that bears self-inhibiting alkaline phosphatase-responsiveness properties that can enhance at the same time the solubility of the parent compound. To probe this novel concept, we selected apigenin as the cytotoxic agent since we first unveiled, that it directly interacts and inhibits ALP activity. Consequently, we rationally designed and synthesized, using a self-immolative linker, an ALP responsive apigenin-based phosphate prodrug, phospho-apigenin. Phospho-apigenin markedly increased the stability of the parent compound apigenin. Furthermore, the prodrug exhibited enhanced antiproliferative effect in malignant cells with elevated ALP levels, compared to apigenin. This recorded potency of the developed prodrug was further confirmed in vivo where phospho-apigenin significantly suppressed by 52.8% the growth of PC-3 xenograft tumors.Communicated by Ramaswamy H. Sarma.

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Festivals following the easing of COVID-19 restrictions: Prevalence of new psychoactive substances and illicit drugs.

The market for illicit drugs and new psychoactive substances (NPS) has grown significantly and people attending festivals have been identified as being at high risk (high extent and frequency of substance use). Traditional public health surveillance data sources have limitations (high costs, long implementation times, and ethical issues) and wastewater-based epidemiology (WBE) can cost-effectively support surveillance efforts. Influent wastewater samples were analyzed for NPS and illicit drug consumption collected during New Year period (from 29-Dec-2021 to 4-Jan-2022) and a summer Festival (from 29-June-2022 to 12-July-2022) in a large city in Spain. Samples were analyzed for phenethylamines, cathinones, opioids, benzodiazepines, plant-based NPS, dissociatives, and the illicit drugs methamphetamine, MDA, MDMA, ketamine, heroin, cocaine, and pseudoephedrine by liquid chromatography mass spectrometry. High consumption rates of specific NPS and established illicit drugs were identified at the peak of each event. Furthermore, a dynamic change in NPS use (presence and absence of substances) was detected over a period of six months. Eleven NPS, including synthetic cathinones, benzodiazepines, plant-based NPS and dissociatives, and seven illicit drugs were found across both the New Year and summer Festival. Statistically significant differences (p < 0.05) were seen for 3-MMC (New Year vs summer Festival), eutylone (New Year vs summer Festival), cocaine (summer Festival vs normal week and summer Festival vs New Year), MDMA (New Year vs normal week and summer Festival vs normal week), heroin (summer Festival vs New Year) and pseudoephedrine (summer Festival vs New Year). This WBE study assessed the prevalence of NPS and illicit drugs at festivals following the reduction of the COVID-19 pandemic restrictions highlighting the high use of specific substances at the peak of each event. This approach identified in a cost-effective and timely manner without any ethical issues the most used drugs and changes in use patterns and, thus, can complement public health information.

Alzheimer's disease: using gene/protein network machine learning for molecule discovery in olive oil.

Alzheimer's disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies.

Comprehensive HRMS Chemical Characterization of Pomegranate-Based Antioxidant Drinks via a Newly Developed Suspect and Target Screening Workflow.

Antioxidants play a significant role in human health, protecting against a variety of diseases. Therefore, the development of products with antioxidant activity is becoming increasingly prominent in the human lifestyle. New antioxidant drinks containing different percentages of pomegranate, blackberries, red grapes, and aronia have been designed, developed, and manufactured by a local industry. The comprehensive characterization of the drinks' constituents has been deemed necessary to evaluate their bioactivity. Thus, LC-qTOFMS has been selected, due to its sensitivity and structure identification capability. Both data-dependent and -independent acquisition modes have been utilized. The data have been treated according to a novel, newly designed workflow based on MS-DIAL and MZmine for suspect, as well as target screening. The classical MS-DIAL workflow has been modified to perform suspect and target screening in an automatic way. Furthermore, a novel methodology based on a compiled bioactivity-driven suspect list was developed and expanded with combinatorial enumeration to include metabolism products of the highlighted metabolites. Compounds belonging to ontologies with possible antioxidant capacity have been identified, such as flavonoids, amino acids, and fatty acids, which could be beneficial to human health, revealing the importance of the produced drinks as well as the efficacy of the new in-house developed workflow.

Complete chemical characterization of Crocus sativus via LC-HRMS: Does trimming affect the chemical content of saffron?

Saffron, a spice derived from Crocus sativus, which in Iran is subjected to different trimming, is known for its beneficial health effects and high market value. Authentication studies related to geographical origin and adulterants presence mainly exist in literature, however fraud due to trimming has not been reported. In the current research, chemical characterization of six saffron trims, namely Sargol, Negin, Pushal, Bunch, Style, and Powder, was accomplished through suspect and non-target screening employing LC-QToF-MS in both electrospray ionization modes. The samples were extracted using methanol:water (50:50,v:v) and 62 compounds were identified, including amino acids, vitamins, flavonoids, phenolics, carotenoids, cyclohexenones. A clear discrimination among the red trims (Pushal, Sargol and Negin), as well as between Style and Bunch using Multivariate Chemometrics techniques was achieved. Proline and isophorone were highlighted as authenticity markers. Finally, the effect of three harvesting year on the most contributing compounds for trimming discrimination has been evaluated.