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Implication of Mitochondrial Coenzyme Q10 (Ubiquinone) in Alzheimer’s Disease *
Published in Abhai Kumar, Debasis Bagchi, Antioxidants and Functional Foods for Neurodegenerative Disorders, 2021
Sayantan Maitra, Dibyendu Dutta
Coenzyme Q (CoQ) is a naturally occurring endogenous compound resembling the properties as of vitamins. This compound is ubiquitous in nature; i.e., it almost exists in every tissue and thus, it is also named as ubiquinone. Frederick Crane and colleagues first isolated CoQ from the mitochondria of beef heart in 1957. CoQ belongs to a homologous series of compounds that possess a common benzoquinone ring in their core structures but differ in the number of isoprene units. In humans and few other mammalian species, CoQ is found to contain 10 isoprene units, and thus, it is named as coenzyme Q10 (CoQ10). The chemical nomenclature of CoQ10 is 2,3-dimethoxy-5-methyl-6-decaprenyl-1,4-benzoquinone [1]. CoQ10 has a fundamental action in cellular bioenergetics as a cofactor in the mitochondrial electron transport chain (ETC) and is therefore crucial for the production of adenosine triphosphate (ATP). CoQ10 also possesses the property of lipid antioxidant and thus averts the generation of free radicals and modifications of proteins, lipids, and deoxyribonucleic acid (DNA) [2]. CoQ10 is ubiquitous but its concentration differs in tissues. The highest concentration of CoQ10 is found in organs where the rate of metabolism is higher, such as heart, kidney, and liver (114, 66.5, and 54.9 g of CoQ10 in each g of tissue, respectively). It is also over-the-counter available as dietary supplement, and this supplementation is found to possess potential health benefits in conditions such as cardiovascular and neurodegenerative disorders [3,4].
Use of Linear Retention Indices in GC-MS Libraries for Essential Oil Analysis
Published in K. Hüsnü Can Başer, Gerhard Buchbauer, Handbook of Essential Oils, 2020
Emanuela Trovato, Giuseppe Micalizzi, Paola Dugo, Margita Utczás, Luigi Mondello
The prediction of retention index has attracted a great deal of interest, as also the extrapolation of values of an analyte's specific physical properties that could be correlated through its retention index. The development of predictive relationships would represent a key for the reliability of retention data. More general approaches to retention index prediction are based on the generation of topological, geometric, and electronic molecular descriptors, which are subsequently fitted to the retention index using multiple linear regression or artificial neural networks. Bruchmann et al. (1993) investigated neural networks that were explored to predict GC retention index data based on electrotopographic indexes of monofunctional compounds, such as acyclic and cyclic monoterpenes and a mixed set of monosubstituted compounds and terpenes. According to the authors, predictions by neural networks are generally in good agreement with predictions done by multiple linear regression techniques. In addition, the prediction of retention indices of homologous series was proved to be effective, as demonstrated by Junkes et al. (2002).
Detection And Identification of Drugs of Dependence
Published in S.J. Mulé, Henry Brill, Chemical and Biological Aspects of Drug Dependence, 2019
A relatively excellent approach to the GLC of narcotic drugs was the peak shift technique reported by Anders and Mannering84 whereby derivatives of narcotic analgesics were prepared on the column by injecting anhydrides of acetate and propionate. The derivatives were formed with alcoholic or phenolic hydroxyl groups and with primary and secondary amines. Identification of the compound was achieved through comparison of the retention time of the unesterified free compound with that of the esterified derivative(s). The peak shift technique was used quite effectively by Mule’1 with extracts of tissues, urine, and blood. Figure 1 shows how effective the peak shift method was in forming esterified derivatives of morphine on the column by subjecting this drug to a homologous series of anhydrides. Retention data was obtained for the free drug, as well as the acetylated and propianated column derivative on a 2% SE-30 column at 215°C using an argon ionization detector. Unique differences were observed between 31 narcotic drugs representing 5 different chemical families.
The combined effect of essential oils on wood physico-chemical properties and their antiadhesive activity against mold fungi: application of mixture design methodology
Published in Biofouling, 2023
Moulay Sadiki, Mounyr Balouiri, Soumya Elabed, Fadoua Bennouna, Mohammed Lachkar, Saad Ibnsouda koraichi
The essential oils’ composition was determined by Gas chromatography coupled with mass spectrometry (GC/MS). The analysis was performed on GC Hewlett-Packard type (HP/Agilent 6890) with flame ionization detector (FID). It is coupled with a mass spectrometer (HP 5973 series) equipped with an HP-5MS capillary column (30 m x 0.25 mm, film thickness is 0.25 µm). The chromatography carrier gas was helium (1.2 mL min−1). The column temperature was programmed from 45 to 240 °C at 2 °C min−1. The fragmentation was done by impact electronics in a field of 70 eV. Essential oils were diluted in methanol (1/20 v/v). A sample volume of 2 µL was injected in a split mode (leakage ratio: 1/20) at a temperature of 250 °C. Identification of the components was made by the comparison of their mass spectra with those of the NIST MS search database (NIST 98), and by comparison of their retention indices (IR) with those of the Adams terpene library (Adams 2007). The retention indices were determined in relation to the homologous series of n-alkanes (C9-C23) under the same operating conditions.
A multidisciplinary approach to the comparison of three contrasting treatments on both lampenflora community and underlying rock surface
Published in Biofouling, 2023
Rosangela Addesso, Daniela Baldantoni, Beatriz Cubero, José Maria De La Rosa, José Antonio González Pérez, Igor Tiago, Ana Teresa Caldeira, Jo De Waele, Ana Z. Miller
Changes in the molecular chemical structure of rock surfaces were studied by pyrolysis-gas chromatography/mass spectrometry (Py-GC–MS). A double-shot microfurnace pyrolyser (model 2020i, Frontier Laboratories, Fukushima, Japan) attached to a GC-MS Agilent 6890 N (Agilent Technologies, Santa Clara, CA, USA) coupled to an Agilent 5973 mass selective detector system, was used for the direct analysis of samples. Finely ground samples (c. 10 mg) were placed in small crucible capsules and introduced into a preheated micro-furnace at 400 °C for 1 min. The pyrolysis products were directly injected into the gas chromatograph inlet line heated at 250 °C to prevent condensation. The GC was equipped with a HP-5ms-UI, low polar-fused silica (5%-Phenyl-methylpolysiloxane) (J&W Scientific, Folsom, CA, USA) capillary column of 30 m × 250 μm × 0.25 μm film thickness (Ref. DB-5). Chromatographic conditions were similar to those described in Miller et al. (2022). Compound assignment was achieved by considering diagnostic ions for the main homologous series, via low-resolution MS and via comparison with published and stored data in NIST and Wiley libraries. A semi-quantification of the products released by analytical pyrolysis was done for each sample by converting the peak areas to a percentage of the total chromatographic area. Minor compounds with 0.2% of the total chromatographic area were excluded.
Click chemistry approaches for developing carbonic anhydrase inhibitors and their applications
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2023
Andrea Angeli, Claudiu T. Supuran
Subsequently, the same research group employed the click-tailing approach for the synthesis of two homologous series of 4-(R-1H-1,2,3-triazol-1- yl)-benzenesulfonamides and 2,3,5,6-tetrafluoro-4–(5-R-1H-1,2,3-triazol-1-il)benzenesulfonamide incorporating a large variety of different moieties (3,4, Figure 2) and investigated the inhibition of the same four human isoforms, hCA I, II, IX and XII21. The tails chosen incorporated various chemical functionalities, such as aromatic, aliphatic, cycloalkyl, halogeno, hydroxyl or aminoalkyl moieties, in order to achieve a major chemical diversity, which influenced the inhibition profile in terms of selectivity against various isoforms. Indeed, the novel compounds were observed to be selective against the tumour-associated hCA IX and XII isoforms, with inhibition constants in the low nanomolar/subnanomolar range. They showed a medium inhibition potency against the cytosolic hCA I and II- Furthermore, two derivatives (3, 4) were crystallised in complex with hCA II (Figure 2)21.