Nanocrystal residual strains and density layers enhance failure resistance in the cleithrum bone of evolutionary advanced pike fish.

Failure-resistant designs are particularly crucial for bones subjected to rapid loading, as is the case for the ambush-hunting northern pike (Esox lucius). These fish have slim and low-density osteocyte-lacking bones. As part of the swallowing mechanism, the cleithrum bone opens and closes the jaw. The cleithrum needs sufficient strength and damage tolerance, to withstand years of repetitive rapid gape-and-suck cycles of feeding. The thin wing-shaped bone comprises anisotropic layers of mineralized collagen fibers that exhibit periodic variations in mineral density on the mm and micrometer length scales. Wavy collagen fibrils interconnect these layers yielding a highly anisotropic structure. Hydrated cleithra exhibit Young's moduli spanning 3-9 GPa where the yield stress of ∼40 MPa increases markedly to exceed ∼180 MPa upon drying. This 5x observation of increased strength corresponds to a change to brittle fracture patterns. It matches the emergence of compressive residual strains of ∼0.15% within the mineral crystals due to forces from shrinking collagen layers. Compressive stresses on the nanoscale, combined with the layered anisotropic microstructure on the mm length scale, jointly confer structural stability in the slender and lightweight bones. By employing a range of X-ray, electron and optical imaging and mechanical characterization techniques, we reveal the structure and properties that make the cleithra impressively damage resistant composites. STATEMENT OF SIGNIFICANCE: By combining structural and mechanical characterization techniques spanning the mm to the sub-nanometer length scales, this work provides insights into the structural organization and properties of a resilient bone found in pike fish. Our observations show how the anosteocytic bone within the pectoral gridle of these fish, lacking any biological (remodeling) repair mechanisms, is adapted to sustain natural repeated loading cycles of abrupt jaw-gaping and swallowing. We find residual strains within the mineral apatite nanocrystals that contribute to forming a remarkably resilient composite material. Such information gleaned from bony structures that are different from the usual bones of mammals showcases how nature incorporates smart features that induce damage tolerance in bone material, an adaptation acquired through natural evolutionary processes.

Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone.

Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacunae, voids that house osteocytes, and submicrometer-sized canaliculi that connect bone cells. Characterization of this network in three dimensions is crucial for many bone studies. To quantify X-ray Zernike phase-contrast nanotomography data, deep learning is used to isolate and assess porosity in artifact-laden tomographies of zebrafish bones. A technical solution is proposed to overcome the halo and shade-off domains in order to reliably obtain the distribution and morphology of the LCN in the tomographic data. Convolutional neural network (CNN) models are utilized with increasing numbers of images, repeatedly validated by `error loss' and `accuracy' metrics. U-Net and Sensor3D CNN models were trained on data obtained from two different synchrotron Zernike phase-contrast transmission X-ray microscopes, the ANATOMIX beamline at SOLEIL (Paris, France) and the P05 beamline at PETRA III (Hamburg, Germany). The Sensor3D CNN model with a smaller batch size of 32 and a training data size of 70 images showed the best performance (accuracy 0.983 and error loss 0.032). The analysis procedures, validated by comparison with human-identified ground-truth images, correctly identified the voids within the bone matrix. This proposed approach may have further application to classify structures in volumetric images that contain non-linear artifacts that degrade image quality and hinder feature identification.

Implantação de serviço de reabilitação profissional: a experiência da UFMG / Onsetting an occupational rehabilitation service at the Federal University of Minas Gerais

Visando implementar políticas de promoção da saúde no trabalho, a UFMG (Universidade de Minas Gerais) criou em 1999 o Serviço de Atenção à Saúde do Trabalhador (SAST Pampulha/UFMG). Entre outras atividades, o SAST desenvolve um programa de reabilitação profissional para os servidores da instituição parcialmente incapacitados para o trabalho, tendo atendido 78 trabalhadores entre junho de 1999 e dezembro de 2001, dos quais 65 foram considerados aptos para o trabalho e 13 foram aposentados. Este estudo visa avaliar os resultados do programa e traçar o perfil dos atendidos, com base em questionários e protocolos aplicados a 51 servidores.

In order to implement policies to promote health in the workplace, the Federal University of State of Minas Gerais (UFMG) created in 1999 the Worker Health Attention Service (SAST). Among other activities, SAST runs a professional rehabilition program to assist partially disabled workers, having attended 78 workers between June 1999 and December 2001, of which 65 were considered able to work and 13 were retired. This study assesses the results of the program and dresses a profile of the workers, drawing on questionnaires and protocols applied to 51 of them...