Recent Advances in Focused Ion Beam Methodologies for 3D Analysis of Biomineralizing Tissues across Multiple Length Scales
Notice bibliographique
Résumé
Biomineralizing tissues such as bone, cartilage, and tendon exhibit a remarkable hierarchical organization, with structural features spanning the macro- to nanometer length scales [1,2]. Historically, capturing these features in 3D posed a significant challenge because conventional methods such as transmission electron microscopy (TEM) and laboratory micro-CT cannot simultaneously provide ultrastructural details and a sufficiently large volume to encompass entire cells and their surrounding matrix. Focused ion beam-scanning electron microscopy (FIB-SEM), originally developed in the semiconductor industry, has emerged as a powerful solution to bridge this gap, enabling researchers to examine how minerals and organic matrices interrelate at multiple length scales – a key step for understanding tissue formation, growth, adaptation, and disease progression. Early FIB tomography studies of bone often involved partial or complete demineralization, following approaches pioneered by Reznikov et al., to circumvent difficulties in milling the hard mineral phase of the tissue [3–5]. While these studies yielded valuable insights into collagen fibril organization [4], the required sample processing risked introducing artifacts or altering the native bone ultrastructure. More recently, direct FIB tomography of fully mineralized bone has been demonstrated using Ga FIB, providing deeper understanding of lamellar organization, cement sheaths, and osteocyte canaliculi within the mineralized matrix [6]. Among the most notable findings from these direct 3D studies is the discovery of an extensive network of nanochannels, each roughly an order of magnitude smaller in diameter than osteocyte canaliculi yet the network possessing a much higher overall volume fraction [7–9]. The nanochannels appear to serve as alternative pathways for ion and small molecule transport within the bone extracellular matrices, a result supported by subsequent work on human cortical bone showing an inverse correlation between nanochannel volume and local calcium content [8]. In addition, unpublished data from lactation mouse models suggest that their nanochannels may participate in osteocytic osteolysis, enabling rapid mineral turnover in the pericellular bone matrix. Despite these advances, the milling volume achievable with Ga FIB remains a key limitation to this technique, generally restricting the field of view to tens of micrometers. Plasma FIB (PFIB) systems – often employing xenon ions – have overcome this barrier, allowing faster material removal and the reconstruction of larger volumes. This capability has allowed the capture of more complete aspects of osteocyte lacunocanalicular networks (LCN) and mineral ellipsoids across mesoscale volumes [10]. By integrating PFIB with X-ray microscopy (XRM), subsurface features of interest at the scale of hundreds of micrometers or more can be identified and selectively milled, an approach recently applied to human trabecular bone [11]. An emerging next step is femtosecond laser FIB (LaserFIB), which uses ultra-short laser pulses to ablate millimeter-scale volumes rapidly before final polishing or tomography with either Ga or Xe FIB. This correlative pipeline has already been shown to expose deeply buried trabeculae in human bone with minimal damage [11], and the application of direct LaserFIB serial sectioning – though still under development – could further accelerate throughput and expand sampling volumes for 3D structural analysis. Meanwhile, other ion species (e.g., oxygen, argon, helium, and neon) have seen specialized use in semiconductor and materials science for milling with low level damage or enhanced chemical contrast [12], but their utility remains largely unexplored for biomineralizing tissues. Some preliminary work has explored oxygen PFIB to mill resin-embedded brain tissue [13] and argon PFIB to prepare cryogenic cellular samples [14], but comprehensive 3D tomography with oxygen, argon, or neon beams for mineralized tissues is largely uncharted. Nonetheless, the distinct sputtering properties and reduced sample damage profiles of these ions suggest potential advantages in future studies of calcified tissues. Altogether, these FIB-based innovations from conventional Ga FIB to PFIB and now LaserFIB are transforming our ability to study 3D mineral-organic interactions in biomineralizing tissues. As these technologies continue to evolve, combining high-resolution volume imaging with targeted site-specific sample preparation should further elucidate how nanoscale pathways, mineral distributions, and structural hierarchies converge to determine tissue function in health and disease [15].
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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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».