The aim of this study was to assess the nutraceutical qualities of extra virgin olive oil (EVOO) samples obtained from three Sicilian olive cultivars: Nocellara, Biancolilla, and Cerasuola. We also evidenced the relationship among biophenols, base parameters and panel test scores, and evaluated the stability of the biophenols in EVOO. The assessment also took into consideration variations in olive harvesting periods and the influence of four different milling methods. A statistical analysis of the collected data revealed that the cultivar and harvesting period were the primary factors influencing the bio-phenol content, while the milling methods employed did not significantly affect the levels of biophenols in the oils. The panel test results were also illuminating as they were strongly related to the cultivar and polyphenol content. Following the criteria outlined in EC Regulation 432/2012, we selected three samples, each representing one of the cultivars, which exhibited the highest bio-phenol content to evaluate the biophenol stability during a time span of 16 months.

UNASSIGNED: Studies suggest that short chain fatty acids (SCFAs), which are primarily produced from fermentation of fiber, regulate insulin secretion through free fatty acid receptors 2 and 3 (FFA2 and FFA3). As these are G-protein coupled receptors (GPCRs), they have potential therapeutic value as targets for treating type 2 diabetes (T2D). The exact mechanism by which these receptors regulate insulin secretion and other aspects of pancreatic β cell function is unclear. It has been reported that glucose-dependent release of acetate from pancreatic β cells negatively regulates glucose stimulated insulin secretion. While these data raise the possibility of acetate\'s potential autocrine action on these receptors, these findings have not been independently confirmed, and multiple concerns exist with this observation, particularly the lack of specificity and precision of the acetate detection methodology used.
UNASSIGNED: Using Min6 cells and mouse islets, we assessed acetate and pyruvate production and secretion in response to different glucose concentrations, via liquid chromatography mass spectrometry.
UNASSIGNED: Using Min6 cells and mouse islets, we showed that both intracellular pyruvate and acetate increased with high glucose conditions; however, intracellular acetate level increased only slightly and exclusively in Min6 cells but not in the islets. Further, extracellular acetate levels were not affected by the concentration of glucose in the incubation medium of either Min6 cells or islets.
UNASSIGNED: Our findings do not substantiate the glucose-dependent release of acetate from pancreatic β cells, and therefore, invalidate the possibility of an autocrine inhibitory effect on glucose stimulated insulin secretion.

Introduction: Doping and steroid use represent a serious threat to animal health and can even lead to their untimely and painful death. However, doping is an acute problem in today\'s animal racing world, particularly in camel racing. Testosterone and its ten esters (benzoate, valerate, isocaproate, hexahydrobenzoate, decanoate, undecanoate, laurate, enanthate, cypionate, and caproate) are of utmost importance, because when they are administered to animals it is difficult to measure them efficiently. The levels of testosterone and its esters in camels and other animals are typically determined using urine and blood tests. The aim of this study was to develop and validate a liquid chromatographic-mass spectrometric (LC-MS/MS) method to determine testosterone esters in camel hair, and to apply the validated method to determine testosterone esters in collected samples. To our knowledge, this is the first report of such research. Results and Discussion: The levels of testosterone and its ten derivatives, along with the cortisol-D4 internal standard, were optimised for LC-MS/MS analysis; however, only testosterone along with its seven esters (namely benzoate, valerate, isocaproate, hexahydrobenzoate, decanoate, undecanoate and laurate) could be validated in camel hair. Only five testosterone esters could be determined in camel hair samples; the concentrations were obtained as 10.5-14.9 pg/mg for valerate (in three camels), 12.5-151.6 pg/mg for hexahydrobenzoate (in six camels), 4.8-32.1 pg/mg for laurate (in five camels), 5.1 pg/mg decanoate (in one camel), and 8.35-169 pg/mg for testosterone (in all 24 camels). Interestingly, the three racing camels displayed high concentrations of testosterone (59.2-169 pg/mg, all three camels), laurate (4.8-14.5 pg/mg, two camels), hexahydrobenzoate (116 pg/mg, one camel), decanoate (5.1 pg/mg, one camel), and valerate (11.7 pg/mg, one camel). Methods: Camel hair samples were collected from 21 non-racing dromedary camels along with three racing camels in Al Ain, UAE; these were decontaminated, pulverised, sonicated, and extracted prior to analysis. An LC-MS/MS method was employed to determine the levels of testosterone esters in the hair samples. Conclusions: This novel camel-hair test procedure is accurate, sensitive, rapid, and robust. The findings reported in this study could be significant to evaluate racing camels for suspected doping offenses. Further controlled testosterone supplementation studies are required to evaluate individual esters\' effects on camel health and diseases and on performance enhancement levels. This new hair test could promote further studies in doping control, toxicology, and pharmacology, as well as having other clinical applications relating to camel health, injury, and disease.

This study aimed to determine whether leaf extracts from seven Eruca vesicaria subsp. sativa cultivars and their biochemically active compounds (glucosinolates and downstream-derived products) inhibit mycelia growth of three well-known pathogenic oomycetes, Phytopythium chamaehyphon, Phytopythium vexans and Phytophthora citrophthora; being the most significant in the development of Kiwifruit Vine Decline Syndrome (KVDS). Leaf extract quantity of 10, 20 and 30 mg were inoculated in Petri dish (90 mm Ø, each 22 mL of liquid medium - Potato Dextrose Agar), for in vitro bioassays. A pathogen plug was placed in the centre of each plate and the Oomycota colony perimeter was marked 5 days after inoculation. Radial colony growth was measured from 4 marks per plate 5, 10, and 15 days after inoculation, further elaborated with Image J software image analysis. Growth rates for all strains were inhibited by around 67% after 15 days. This was most pronounced when applying the highest concentration of leaf extract. By using Liquid Chromatography Mass Spectrometry (LC-MS) and Gas Chromatography Mass Spectrometry (GC-MS), fifteen glucosinolate compounds, of which glucosativin was found in the highest quantity, were identified. Concentrations of hydrolysis products produced by leaves (erucin and sativin) were also investigated, and were significantly associated with colony radial growth, especially towards Pp. chamaehyphon and Pp. vexans. Three downstream products of glucosinolates (two pure isothiocyanates, AITC and PEITC; and one indole I3C; all commonly present in Brassicaceae) were also tested, and a statistically significant inhibition of growth was observed at the highest concentration (0.6 µL).

BACKGROUND: The inclusion of dexmedetomidine (DEX) within a balanced general anaesthesia protocol is effective in improving the clinical outcome and recovery quality of anaesthesia in horses. This study aimed to determine the pharmacokinetic profile of DEX following repeated subcutaneous (SC) administration at 2 µg/kg every 60 min till the end of the procedure in comparison to intravenous constant rate infusion (CRI) at 1 µg/kg/h in anaesthetized horses undergoing diagnostic procedures up to the end of the diagnostic procedure.
RESULTS: In the CRI and SC groups DEX maximum concentrations (Cmax) were 0.83 ± 0.27 ng/mL and 1.14 ± 0.71 ng/mL, respectively, reached at a time (Tmax) of 57.0 ± 13.4 min and 105.5 ± 29.9 min. Mean residence time to the last measurable concentration (MRTlast) was 11.7 ± 6.2 and 55.8 ± 19.7 min for the CRI group and SC groups, respectively. The apparent elimination half-life was 18.0 ± 10.0 min in the CRI group and 94.8 ± 69.8 min for the SC group, whereas the area under the curve (AUC0-last) resulted 67.7 ± 29.3 and 83.2 ± 60.5 min*ng/mL for CRI and SC group, respectively. Clearance was 16.26 ± 8.07 mL/min/kg for the CRI group. No signs of adverse effects were recorded in both groups.
CONCLUSIONS: The pharmacokinetic profile of DEX following repeated SC administration in anaesthetized horses was comparable to intravenous CRI administration during the intranaesthetic period and beneficial during the recovery phase from general anaesthesia. The SC route could be considered as an alternative to CRI for improving the recovery quality of equine patients undergoing general anaesthesia.

Consumption of low levels of egg already can evoke harmful physiological responses in humans in those allergic to eggs. By detection of egg in food products, using Egg ELISA kits to determine its unintended presence, food producers can respond to avoid potential safety or quality risks of their products. Selection of an ELISA kit fit for the issue at hand is challenging due to, amongst others, lack of information on assay performances with specified matrices. In this study, performances of seven commercial egg ELISA kits are compared for nine different relevant matrices: cookie, chocolate, pasta, dressing, stock cube, wine, vegetable drink and milk, ice cream and meat/meat replacers. The presence of egg was unified for all ELISA kits to mg total egg protein kg-1 food product. In every matrix, kit performances for recovery, intra- and interassay were compared, and also processing is accounted for by determination of egg in incurred samples. All seven kits were able to detect egg qualitatively at the VITAL3 ED01 level of 0.2 mg total egg protein and the corresponding relevant portion size for each matrix. For quantitative results, each ELISA kit showed an increase in detected egg concentration with increased egg levels and performed within the set criteria for recovery for the cookie, chocolate, stock cube and wine. For pasta, vegetable drink and milk, ice cream, and salad dressing, recovery of egg was within the set criteria for at least 4 ELISA kits. Most challenging matrices were meat/meat replacers, showing high matrix effects which could not be explained by the possible egg presence in the cognate blank. Only one ELISA kit was able to recover egg within the set criteria for the meat/meat replacer matrix. Results enable food industry to choose for ELISA kits suitable for egg detection in the matrix of interest.

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates such as fatty acids, carbohydrates, lipids, and amino acids to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic extractions) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection - direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF MS/MS). Using DI-FTICR MS, 9,521 metabolic features were detected where 7,699 were assigned a chemical formula and 1,756 were assigned an annotated by accurate mass assignment. Using LC-Q-TOF MS/MS, 21,428 metabolic features were detected where 626 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 2276 heart metabolites were identified in this study which span a wide range of polarities including polar (benzenoids, alkaloids and derivatives and nucleosides) as well as non-polar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results of this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.

Collection of finger sweat is explored here as a rapid and convenient way of monitoring patient adherence to antipsychotic drugs. Finger sweat samples (n = 426) collected from patients receiving treatment with clozapine, quetiapine and olanzapine were analysed by liquid chromatography mass spectrometry, including a subgroup of patients with paired plasma samples. Finger sweat samples were also analysed from a negative control group and patients who had handled antipsychotic medication only. The finger sweat test (based on the detection of parent drug in one donated sample) was 100% effective in monitoring adherence within commonly prescribed dosing ranges. In comparison to participants who handled the medication only, the test could distinguish between contact and administration through monitoring of the drug metabolite, or the level of parent drug. Additionally, in a subgroup of patients prescribed clozapine, a statistically significant correlation was observed between the mass of parent drug in finger sweat and plasma concentration. The finger sweat technology shows promise as a dignified, noninvasive method to monitor treatment adherence in patients taking antipsychotics.

Filipendula ulmaria, commonly known as meadowsweet, is a wild herbaceous flowering plant that is widely distributed in Europe. A range of salicylic acid derivatives and flavonol glycosides have been previously associated with the antirheumatic and diuretic properties of F. ulmaria. In the present work, a hydroalcoholic extract from F. ulmaria aerial parts was extensively profiled using an efficient NMR-based dereplication strategy. The approach involves the fractionation of the crude extract by centrifugal partition chromatography (CPC), 13C NMR analysis of the fractions, 2D-cluster mapping of the entire NMR dataset, and, finally, structure elucidation using a natural metabolite database, validated by 2D NMR data interpretation and liquid chromatography coupled with mass spectrometry. The chemodiversity of the aerial parts was extensive, with 28 compounds unambiguously identified, spanning various biosynthetic classes. The F. ulmaria extract and CPC fractions were screened for their potential to enhance skin epidermal barrier function and skin renewal properties using in vitro assays performed on Normal Human Epidermal Keratinocytes. Fractions containing quercetin, kaempferol glycosides, ursolic acid, pomolic acid, naringenin, β-sitosterol, and Tellimagrandins I and II were found to upregulate genes related to skin barrier function, epidermal renewal, and stress responses. This research is significant as it could provide a natural solution for improving hydration and skin renewal properties.

Accuracy of peptide identification in LC-MS analysis is crucial for information regarding the aspects of proteins that aid in biomarker discovery and the profiling of complex proteomes. The detection of peptide fragment ions in tandem mass spectrometry is still challenging given that current tools were not created or tested for the low-abundance, low-peak fragments of peptides found in MS2 data. Feature detection, a crucial pre-processing step in the LC-MS analysis pipeline that quantifies peptides by their mass-to-charge ratio, retention time, and intensity, is particularly challenging due to the overlapping nature of peptides and weak signals that are often indistinguishable from noises, thus creating a reliance on rigid mathematical structures and heuristics. In this study, we developed a deep-learning-based model with an innovative sliding window process that enables high-resolution processing of quantitative MS/MS data to conduct MS2 feature detection. Experimental results show that our model can produce more accurate values and identifications than existing feature detection tools, as well as a high rate of true positive features quantified. Therefore, we believe that our model illustrates the advantages of deep learning techniques applied towards computational proteomics.