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Enregistrement W2760720395

Solid Phase Microextraction as a Sample Preparation Tool for Targeted and Untargeted Analysis of Biological Matrices

2017· dissertation· en· W2760720395 sur OpenAlexfundno aff
Nathaly Reyes‐Garcés

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2017
Typedissertation
Langueen
DomaineImmunology and Microbiology
ThématiqueBiosimilars and Bioanalytical Methods
Établissements canadiensnon disponible
Organismes subventionnairesConcordia University
Mots-clésSolid-phase microextractionSample preparationChromatographySample (material)ChemistryGas chromatography–mass spectrometryMass spectrometry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Successful determination of small molecules in complex biological systems requires implementation of robust analytical methodologies able to provide reliable information in a cost-effective and efficient manner. Solid phase microextraction (SPME) is a versatile, non-exhaustive sample preparation tool that has been demonstrated to be well-suited for facile analysis of biological matrices such as plasma, blood, and tissue. In SPME, a small amount of extraction phase immobilized on a solid support is utilized for the extraction of analytes of interest, either from the sample headspace or by direct immersion of the fiber in the matrix of choice. For the analysis of non-volatile compounds in complex biological matrices, SPME coatings made of sorbents embedded in a biocompatible binder (e.g. polyacrylonitrile (PAN)) are directly immersed into the sample under study for a defined period of time so as to allow for sufficient and reproducible extraction of analytes. The main advantages of such coating materials rely on their ability to provide high selectivity for extraction of small molecules; their aptness for immobilization in different support geometries; their inertness and robustness, which even enables their reusability in complex biological matrices; and their suitability towards in vivo extractions. In view of these advantages, the body of this doctoral thesis presents novel applications and developments of SPME for both targeted and untargeted analysis of different biological matrices such as biofluids and brain tissue. 
\nThe first part of the research conducted for this thesis encompasses the application of SPME in thin-film format for high throughput determination of multiple prohibited substances in plasma. A biocompatible SPME extraction phase made of hydrophilic-lipophilic balance (HLB) particles immobilized with PAN was employed for extractions, demonstrating satisfactory extraction capabilities for 25 compounds of a wide range of polarities (logP from -2 to 6.8). By taking full advantage of the 96 thin-film handling capability of the automated system, a preparation time of approximately 1.5 min per sample can be achieved. Rewarding results in terms of absolute matrix effects were found for the majority of the studied analytes, given that 24 out of 25 compounds exhibited values in the range 100 - 120%. The method was validated in terms of linearity (R2> 0.99), inter and intra-day accuracy (85 – 130%) and precision (< 20%), and limits of quantitation (0.25 – 10 ng mL-1 for most compounds). 
\nBased on the positive results obtained after employing the developed method for the analysis of doping compounds in plasma samples, and considering the need for cost-effective and single use devices, the possibility of employing alternative materials to manufacture SPME devices was explored. To that end, new thin-film SPME devices prepared on plastic as potential single-use samplers for bioanalysis were developed and tested. Polybutylene terephthalate (PBT) was selected as a support based on its chemical resistance, low cost, and suitability as a material for different medical grade components. The proposed devices were assessed in terms of robustness, chemical stability, and possible interferences upon exposure to different solvents and matrices. Satisfactory results were obtained upon utilization of the manufactured samplers for the quantitation of multiple drugs in biofluids such as urine, plasma, and whole blood. Interestingly, our results showed that more than 20 extractions in complex biofluids can be performed without incurring significant changes in coating performance. These findings evidenced the robustness of PAN-based coatings applied on polymeric substrates, and opened up opportunities for the introduction of new support materials for manufacture of SPME biocompatible devices aimed at a wide range of applications.
\nTaking into account that SPME is a non-exhaustive extraction technique where analytes are extracted via free concentration, assessing the effect of variable matrix composition on final SPME recoveries is invaluable in avoiding biased results. With this in mind, part of this thesis also involved the investigation of the effect of hematocrit (Hct) levels on SPME extractions from whole blood. The obtained results demonstrated that the Hct effect in SPME is dependent on the analytes of interest, and that different outcomes can be attained by varying experimental conditions such as coating type, convection, and extraction time. Interestingly, the relative affinities of target compounds for matrix components and coating materials were demonstrated to be one of the main determining factors on the final effect that erythrocyte levels impart on SPME recoveries. Although Hct content was shown to affect the extraction of each analyte differently, and be dependent on experimental parameters, correction of matrix variability is enabled through the use of appropriate internal standards.
\nIn view of the rewarding results obtained in the analysis of a broad range of target analytes, SPME in its fibre configuration was evaluated based on its performance for untargeted analysis of brain tissue. For that purpose, the metabolite coverage provided by C18, mixed mode (MM), and HLB 7 mm fibres following extraction from brain homogenate at static conditions was assessed. Our results demonstrated that for compounds of medium to high polarity, both HLB and MM coatings were able to offer similar coverage at the same desorption conditions. For extraction of lipids, C18 and HLB exhibited the best recoveries with the use of 1:1 methanol:isopropyl alcohol as desorption solvent. Interestingly, the use of different desorption solvents was found to greatly influence the final composition of the brain extract obtained via SPME. Other parameters such as extraction time, coating washing step, and inter-fibre reproducibility were also considered and discussed.
\nLastly, the balanced metabolite coverage provided by SPME was successfully utilized for in vivo monitoring of metabolic changes occurring in the hippocampus of rat brain after electrical stimulation (DBS) of the ventromedial prefrontal cortex (vmPFC), which has been previously shown to induce anti-depressant like effects in rodents. The use of in vivo SPME enabled the monitoring of significant variations, not only among small polar metabolites such as amino acids, but also in lipids belonging to different classes. Compounds such as citrulline, glutamate, taurine, uric acid, sphingomyelins, and phosphatidylethanolamines, among others, exhibited statistically significant changes after acute exposure of animals to electrical stimulation for 3 hours. Although additional studies are needed to establish the contribution of the biochemical changes observed in this study to the effect of DBS in the treatment of depression, our work provided new directions towards a better understanding of the mechanisms taking place in the brain upon application of electrical stimulation to the vmPFC.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,170
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,332
Écart entre enseignants0,308 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2017
Routes d'admission1
Résumé présentoui

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