Notice bibliographique
Résumé
My group focuses on several areas of biological mass spectrometry, including structural elucidation techniques, quantification, high-resolution MS and instrument development. We are also involved in metabolomics and lipidomics studies, with particular emphasis on small molecule indicators of disease and physiological status, for example, in recent years, we have become very interested in the metabolism of vitamin D. I entered the field of mass spectrometry in 1992, whilst working on my PhD research under the guidance of Karsten Levsen, a highly respected fundamental mass spectrometry researcher. During this time, I began my long interest in the application of mass spectrometry in analytical chemistry, which continues today, and will likely only end when my career does! The mass spec research was particularly refreshing back then as the early 1990s were the “wild west” of hyphenated chromatography and mass spectrometry methods and many interesting theories and ideas were developed during that time. During my PhD, I built a thermospray ionization LC/MS system, consisting of a Finnigan-MAT 4000 mass spectrometer (which was upgraded to a 4500 model) and a Vestec TSP interface. The Finnigan-MAT instrument was a single quadrupole mass spectrometer for GC/MS, which was quite dated (late 1970s!) when I was given it for my PhD research. The thermospray LC/MS system I put together was applied to the quantitative analysis of pesticides from water samples. The financial investment in this project was not without risk, as commercial electrospray instruments had started to appear on the market, fortunately (for me), then still with sub-mediocre performance. The data we obtained from the LC/TSP-MS instrument were phenomenal, however, and the analytical figures of merit still compare to today's LC/MS machines. Unfortunately, no MS/MS was possible, not even in-source CID. To obtain fragments, we had to heat the molecules in the vaporizer tube to induce thermal fragmentation. Extremely crude by today's standards, but surprisingly effective. I still enjoy the time we spent on trying to make MALDI-MS a quantitative technique for small molecules – comparable to LC/MS – in the early to mid 2000s, with excellent results. Even though we and other groups were able to demonstrate that the performance can be quite comparable to LC/MS (at much faster speeds!), MALDI-MS was never really accepted in routine laboratories, however, because of that preconception of MALDI being a non-reproducible technique. Thus, we never managed to get that idea out of peoples' heads. Fortunately, quantitative MALDI-MS research is currently undergoing a revival for application to imaging mass spectrometry. A solid understanding of the processes that control and impact quantification is vital and we will use our previous expertise to improve quantitative aspects of MALDI imaging in the future. I will give a very stereotypical answer here: you have to be persistent and never give up. While this is a textbook answer, it is nevertheless true. I think success in science usually does not require superior intelligence because many of the breakthroughs are the result of hard work and spending a lot of time in the lab. I believe scientists who take shortcuts or who are lazy will always fail eventually. On a practical note, but in the same context, an often-mentioned lab wisdom also holds true: if the mass spectrometer is running nicely, never interrupt the work and keep on running samples, even if it means staying late or until the next morning, or the entire weekend. We all know that mass spectrometers will eventually show their ugly side and break down, often for extended periods of time. I am most grateful to three individuals, who I had the pleasure of having as advisors and mentors, who were surprisingly similar in their approaches. Firstly, my PhD supervisor Karsten Levsen at the University of Hannover in Germany took a total hands-off approach to my project and he fully trusted that I could develop the project to a meaningful conclusion (which I mostly did). I then moved on to a postdoctoral position with Jon Wilkes at the National Center for Toxicological Research in Jefferson/AR in the United States, who allowed me to start an entirely independent research program in mass spectrometry and food analysis. And then, after moving to Canada, I joined Robert Boyd's group at the National Research Council in Halifax. He recently put his management style as head of department as follows (Boyd RK. From physical chemistry to mass spectrometry to government lab manager in half a century. Mass Spec Rev. 2016;35:272–310): “The most important support was the stream of talented Research Associates, Research Officers, and Postdoctoral Fellows who ended up working in the Analytical Chemistry Group. In approximate chronological order they were … , Dietrich Volmer, … “. I soon learned that with people of that quality, as their nominal ‘supervisor’ the best plan was to agree with each what they were interested in doing, then leave them to get on with it.” Nice! The single most important aspect to being successful in science is, in my opinion, to take ownership of the project that was given to you. I always considered every project I worked on (starting with the master's thesis) my personal, very own project, and the supervisor's main role was to give advice when needed (and to supply the necessary funds for the research). I am trying to use the same approach, to create independent thinkers and project managers. Obviously, the degree of support comes on a sliding scale, depending on the skills and the previous experiences of the students. The answer to this question is obviously influenced by the science I pursue. I am currently mostly excited about novel ways of ionizing molecules. The introduction of ambient ionization techniques in various shapes during the past 10 years has put the topic of ionization back into the spotlight and my group is working on unique ways of putting charge onto molecules, in particular those that won't respond to established techniques. The other area of current importance is the application of high-resolution mass spectrometry to very complex samples. This has been performed for a long time but the recent generation of affordable HRMS instruments has put the technology into the hands of many research laboratories, for example in the clinical field. I believe the future of mass spectrometry is even more exciting than 20 years ago. I sometimes hear fellow mass spectrometry scientists complain that mass spectrometry has moved away from being an independent discipline, into the routine laboratory, and that there is no room for individual science anymore. I believe the opposite is true. Fundamental mass spectrometry researchers are needed even more today, because the instruments and MS methods for the upcoming challenges in the biological sciences will not be developed in biological and medical laboratories. The future research questions will be even more challenging than today and will require novel instrumentation and methods, many of which likely do not even presently exist. Like almost every scientist, I am interested in very many things outside of science. One of those things is my interest in music reproduction. I am one of those audiophiles who still listens to vinyl, using tube amplifiers, with a stereo system that consists of so many individual components that half of my home-office space is needed to set it up. When I listen to digital music, I like it the way I like my mass spectrometers; that is, with the highest resolution possible. I would finally have the time to write the mass spectrometry textbook that I have been thinking about for at least 10 years. This would be great as I would be able to see whether students and colleagues actually like it, while I am still working in the field. Obviously, in reality this will never happen. It might be written once I retire though! None really. Perhaps Lady GaGa. Definitely Jerry Seinfeld.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,068 | 0,079 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».