Miniaturized Fractionation and Purific ation of Analytes of Interest in Complex Mixtures: Protein Enrichment and Purific ation with Capillary Electrophoresis and Identific ation of Pesticide Chemicals in Bio-oils
Bibliographic record
Abstract
The ability to isolate and detect an analyte of interest is vital for many different facets of life today, from disease detection to environmental safety. The goal of the method development discussed within this thesis is to isolate and identify unique analytes from complex matrices and to do so in a scaled down approach. Removal of an analyte from a diverse background of molecules is often required for successful detection and determination of analyte properties. As well, many samples are only available at low volumes and at trace levels so miniaturized techniques that only require small sample volumes are designed and discussed herein. Two unique classes of analytes are examined with one common theme of isolation for successful detection.\nProteins and peptides are enriched and purified from permanently charged and buffering ions, which are common biological contaminants, using discontinuous buffers with capillary electrophoresis. This method only uses sub-microliter quantities of sample and exploits the isoelectric point of the biological macromolecules in buffers of different pH. Successful removal of sodium chloride, TRIS, phosphate, and MES is demonstrated. Subsequent enhanced mass spectral detection and separation of a protein mixture exhibited the improved analyte detection by employing discontinuous buffers. Magnetic beads are used to isolate phosphorylated peptides at micro to nanoliter volumes by covalent derivatization of the post-translational modification and selective enrichment, further demonstrating the online CE sample preparation capabilities.\nThe second challenging sample examined is bio-oil, a complex mixture of thousands of chemicals. The novel pesticide properties of this sample are explored as the chemical complexity of pyrolysis bio-oil from tobacco leaves is reduced through isolation by solid phase extraction, liquid-liquid extraction, and heating. Mass spectrometry is used to identify the compounds after separation by gas chromatography. Three problematic microorganisms in Canada, S. scabies, C. michiganensis, and P. ultimum, are negatively affected by the bio-oil. It is determined that the most abundant phenolic species are not responsible for the observed pesticide activity from the bio-oil. A few minor components are identified that could contribute to the observed antimicrobial activity, but no abundant, active chemicals could be identified with the current technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".