21st international Biometals Webinars
Notice bibliographique
Résumé
The 21st International Biometals Webinar featured two distinct yet complementary perspectives on the role of metals in biology, addressing both contemporary bioinorganic chemistry and the origins of life. The first presentation detailed the development and application of liquid chromatography (LC)-based metallomics tools to investigate toxic metal species in mammalian blood plasma, focusing on exposure–disease relationships at the blood–organ interface. Using size-exclusion and reversed-phase chromatography coupled with inductively coupled plasma atomic emission spectrometry (ICP-AES), the study elucidated mechanisms of methylmercury transport from blood to brain, identifying homocysteine as a chaperone facilitating methylmercury translocation across the blood–brain barrier. Additional findings revealed that toxic metals such as mercury and cadmium bind to hemoglobin and carbonic anhydrase released upon red blood cell rupture, implicating these metalloproteins in disease processes like neurotoxicity and atherosclerosis. The second presentation challenged the prevailing organic-centric paradigm of life’s emergence by emphasizing the fundamental and catalytic roles of transition metals in bioenergetics and enzyme function. It argued that life is as much “metallic” as organic, with transition metal ions mediating redox reactions essential for free energy conversion and low-entropy maintenance. This metallic perspective suggests that the origin of life was driven by metal-containing minerals harnessing environmental redox gradients, providing a thermodynamically plausible pathway distinct from the classical “primordial soup” hypothesis. Together, these contributions underscore the critical importance of metals in both understanding disease mechanisms and re-evaluating life’s biochemical and evolutionary foundations. Introduction to the 21st international Biometals Webinars Application of LC-based metallomics tools to probe the exposure-disease relationship of toxic metal species at the blood-organ nexus There are two types of metal species that can enter the human bloodstream but for which the outcome at the organ level is not well understood: toxic metal species (Cd2+, Hg2+, CH3Hg+, thimerosal, phenylmercuric acetate) and gold-nanoparticles, which offer considerable potential to selectively deliver immobilized drugs to target tissues after attaching a targeting sequence. We employ liquid chromatography-based metallomics approaches to better understand these processes in conjunction with electrospray ionization mass spectrometry, X-ray absorption spectroscopy and/or transmission electron microscopy. While different LC-separation modes in conjunction with different mobile phase compositions allow to probe bioinorganic processes that unfold in blood plasma, red blood cells cytosol and/or protein-free hepatocyte cytosol,1 the utilization of an inductively coupled plasma atomic emission spectrometer as a metal-specific detector provides the unique capability to simultaneously detect a large variety of metals.2 This presentation will highlight how the integration of the results that are obtained with this analytical approach into the biochemistry of the whole organism3 provides a powerful means to effectively address pertinent health relevant bioinorganic chemistry problems which have a strong toxicological chemistry and/or pharmacological flavor to significantly advance human health in the 21st century. [1] N. Pourzadi, J. Gailer, J. Chromatogr. A 2024, 1736, 465409 [2] N. Pourzadi, et al., Nanomedicine 2025, 20, 1127-1138 [3] M. Degorge, J. Gailer, Toxics, 2025, 13, 636 Is Life organic or metallic? ... and why does that matter in trying to deduce its emergence? Is Life organic or metallic? … and why that matters with respect to its emergence The notion that life is (basically) all about organic molecules, and that consequently it must have emerged out of a mixture of organic molecules, is generally considered an obvious truism. I will try to trace this mindset back to its origins more than 200 years ago and confront its development during the 19th and early 20th century with the major advances in the physical sciences and in particular in thermodynamics. If all goes according to plan, your certainties about the primacy of organics in life and in its emergence will be somewhat shaken after you have listened to this webinar ...
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 | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,360 | 0,246 |
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 ».