Resveratrol in Health and Disease. B. Aggarwal and S. Shishodia, eds. Boca Raton, FL: CRC Press, Taylor & Francis Group, 2006, 712 pp., $199.95, hardcover. ISBN 0-8493-3371-7.
Notice bibliographique
Résumé
In little more than a decade, resveratrol has advanced from an obscure constituent of Oriental folk medicine to a wonder drug that, according to the authors of the 27 chapters in this volume, inhibits carcinogenesis as well as actual tumors; protects against cardiovascular, neurodegenerative, and anti-inflammatory diseases as well as radiation damage; and displays antibacterial, antifungal, and antioxidant properties. These beneficial effects are apparently mediated through modulation of gene expression, signal transduction, cell cycle progression, prostaglandin biosynthesis, and angiogenesis. No other plant-based compound, not even quinine or digitalis, comes close to matching resveratrol’s array of benefits. One would have to go back to the birth of penicillin to discover a natural agent to match its potential. Before rushing to the nearest purveyor of herbal medicine for a personal supply, the reader should be warned that most of these reported miracles have taken place in test tubes and cell cultures, that results of in vivo studies have been rather mixed, that human trials are only now beginning, and that there is a large question mark over resveratrol’s bioavailability. It is the paradox of promise and uncertainty surrounding resveratrol that makes this volume so welcome and timely. The editors have explored every nook and cranny of their territory. In doing so, they have assembled an excellent team of contributors whose writing is clear, rarely dull, and often accompanied by exemplary illustrations. Several of the pioneers and leaders of the field are represented: John Pezzuto by a chapter on carcinogenesis that is a masterpiece spanning 150 pages, Barry Gehm by a chapter on the estrogenic effects of resveratrol that is shorter but highly informative, and Alberto Bertelli by the final chapter, describing resveratrol’s pharmacokinetics and metabolism. Even those authors whose work I was reading for the first time impressed me with their grasp of the subject. If there is one thing lacking in this entire volume, it is a healthy dose of skepticism. It is true that the writers of reviews have to describe the literature as it exists, but in doing so it is appropriate to make judgements between good papers and bad papers, between core observations and those that are more likely to be epiphenomena, or worse still, the results of poor science. The tone of the volume is dominated by enthusiasm for its protagonist rather than the cautious exercise of critical thought. It seems to me to be axiomatic that a simple trihydroxy-stilbene cannot be all things to all people. Some of its properties must be much more important than others. A decade from now, we are virtually certain to discover that only a modest proportion of its putative benefits are actually deliverable to suffering humanity; there is no way to tell from this book which of those benefits these are likely to be. However, as a superbly presented account of a volcano of knowledge in the midst of erupting, this book can be thoroughly recommended. The readers of this journal will not find its concepts and vocabulary unfamiliar, even if they will be encountering Polygonum cuspidatum, resveratrol’s most prolific plant source, for the first time.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,020 |
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 ».