High-resolution study of the 3D collagen fibrillary matrix of Achilles tendons without tissue labelling and dehydrating

Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields

Osteoarthritis (OA) is a degenerative joint disease with significant clinical and societal impact. Traditional diagnostic methods, including subjective clinical assessments and imaging techniques such as X-rays and MRIs, are often limited in their ability to detect early-stage OA or capture subtle joint changes. These limitations result in delayed diagnoses and inconsistent outcomes. Additionally, the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets, making it difficult to identify key molecular mechanisms and biomarkers. Recent advancements in artificial intelligence (AI) offer transformative potential to address these challenges. This review systematically explores the integration of AI into OA research, focusing on applications such as AI-driven early screening and risk prediction from electronic health records (EHR), automated grading and morphological analysis of imaging data, and biomarker discovery through multi-omics integration. By consolidating progress across clinical, imaging, and omics domains, this review provides a comprehensive perspective on how AI is reshaping OA research. The findings have the potential to drive innovations in personalized medicine and targeted interventions, addressing longstanding challenges in OA diagnosis and management.

Bibliometric analysis of chondrocyte apoptosis in knee osteoarthritis

BACKGROUND

Apoptosis, a form of programmed cell death, plays a significant role in osteoarthritis; however, bibliometric studies in this field remain scarce. Bibliometrics provides a visual representation of research outcomes and trends, guiding future investigations.

METHOD

Journal data from January 1, 2013, to December 31, 2023, in this field were obtained from the Web of Science (WOS) core database. Analysis was conducted using VOSviewer and CiteSpace.

RESULTS

Analysis revealed that over the past decade, 794 articles were published in 299 journals by 4447 authors from 49 countries and 877 institutions. The top contributors were China, the United States, and the United Kingdom. Zhuang Chao emerged as the most prolific author, and "osteoarthritis and cartilage" ranked as the most frequently cited journal. Keyword clustering focused on mechanisms, inflammation, and cartilage. The most-cited article was "chondrocyte apoptosis in the pathogenesis of osteoarthritis" in the "International Journal of Molecular Sciences." Burst word analysis highlighted extracellular matrix, circular RNA, micro RNA, indicating current research hotspots.

CONCLUSION

Utilizing bibliometrics and visual analysis, we explored the hotspots and trends in the field of chondrocyte apoptosis in osteoarthritis. Extracellular matrix, Circular RNA, Micro RNA, among others, are likely to become future research focal points and frontiers.

The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries

This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.

Investigating cartilage-related diseases by polarization-resolved second harmonic generation (P-SHG) imaging

Establishing quantitative parameters for differentiating between healthy and diseased cartilage tissues by examining collagen fibril degradation patterns facilitates the understanding of tissue characteristics during disease progression. These findings could also complement existing clinical methods used to diagnose cartilage-related diseases. In this study, cartilage samples from normal, osteoarthritis (OA), and rheumatoid arthritis (RA) tissues were prepared and analyzed using polarization-resolved second harmonic generation (P-SHG) imaging and quantitative image texture analysis. The enhanced molecular contrast obtained from this approach is expected to aid in distinguishing between healthy and diseased cartilage tissues. P-SHG image analysis revealed distinct parameters in the cartilage samples, reflecting variations in collagen fibril arrangement and organization across different pathological states. Normal tissues exhibited distinct χ33/χ31 values compared with those of OA and RA, indicating collagen type transition and cartilage erosion with chondrocyte swelling, respectively. Compared with those of normal tissues, OA samples demonstrated a higher degree of linear polarization, suggesting increased tissue birefringence due to the deposition of type-I collagen in the extracellular matrix. The distribution of the planar orientation of collagen fibrils revealed a more directional orientation in the OA samples, associated with increased type-I collagen, while the RA samples exhibited a heterogeneous molecular orientation. This study revealed that the imaging technique, the quantitative analysis of the images, and the derived parameters presented in this study could be used as a reference for disease diagnostics, providing a clear understanding of collagen fibril degradation in cartilage.

High Resolution and Labeling Free Studying the 3D Microstructure of the Pars Tensa-Annulus Unit of Mice

Hearing loss is a serious illness affecting people’s normal life enormously. The acoustic properties of a tympanic membrane play an important role in hearing, and highly depend on its geometry, composition, microstructure and connection to the surrounding annulus. While the conical geometry of the tympanic membrane is critical to the sound propagation in the auditory system, it presents significant challenges to the study of the 3D microstructure of the tympanic membrane using traditional 2D imaging techniques. To date, most of our knowledge about the 3D microstructure and composition of tympanic membranes is built from 2D microscopic studies, which precludes an accurate understanding of the 3D microstructure, acoustic behaviors and biology of the tissue. Although the tympanic membrane has been reported to contain elastic fibers, the morphological characteristic of the elastic fibers and the spatial arrangement of the elastic fibers with the predominant collagen fibers have not been shown in images. We have developed a 3D imaging technique for the three-dimensional examination of the microstructure of the full thickness of the tympanic membranes in mice without requiring tissue dehydration and stain. We have also used this imaging technique to study the 3D arrangement of the collagen and elastic fibrillar network with the capillaries and cells in the pars tensa-annulus unit at a status close to the native. The most striking findings in the study are the discovery of the 3D form of the elastic and collagen network, and the close spatial relationships between the elastic fibers and the elongated fibroblasts in the tympanic membranes. The 3D imaging technique has enabled to show the 3D waveform contour of the collagen and elastic scaffold in the conical tympanic membrane. Given the close relationship among the acoustic properties, composition, 3D microstructure and geometry of tympanic membranes, the findings may advance the understanding of the structure—acoustic functionality of the tympanic membrane. The knowledge will also be very helpful in the development of advanced cellular therapeutic technologies and 3D printing techniques to restore damaged tympanic membranes to a status close to the native.

A Quantitative Analysis of Bone Lamellarity and Bone Collagen Linearity Induced by Distinct Dosing and Frequencies of Teriparatide Administration in Ovariectomized Rats and Monkeys

The lamellar structure of bone, which endows biomechanical rigidity to support the host organism, is observed in mammals, including humans. It is therefore essential to develop a quantitative analysis to evaluate the lamellarity of bone, which would especially be useful for the pharmacological evaluation of anti-osteoporotic drugs. This study applied a current system for the semi-automatic recognition of fluorescence signals to the analysis of un-decalcified bone sections from rat and monkey specimens treated with teriparatide (TPTD). Our analyses on bone formation pattern and collagen topology indicated that TPTD augmented bone lamellarity and bone collagen linearity, which were possibly associated with the recovery of collagen cross-linking, thus endowing bone rigidity.

Quantification of collagen fiber structure using second harmonic generation imaging and two-dimensional discrete Fourier transform analysis: Application to the human optic nerve head

Second harmonic generation (SHG) microscopy is widely used to image collagen fiber microarchitecture due to its high spatial resolution, optical sectioning capabilities and relatively nondestructive sample preparation. Quantification of SHG images requires sensitive methods to capture fiber alignment. This article presents a two-dimensional discrete Fourier transform (DFT)-based method for collagen fiber structure analysis from SHG images. The method includes integrated periodicity plus smooth image decomposition for correction of DFT edge discontinuity artefact, avoiding the loss of peripheral image data encountered with more commonly used windowing methods. Outputted parameters are as follows: the collagen fiber orientation distribution, aligned collagen content and the degree of collagen fiber dispersion along the principal orientation. We demonstrate its application to determine collagen microstructure in the human optic nerve head, showing its capability to accurately capture characteristic structural features including radial fiber alignment in the innermost layers of the bounding sclera and a circumferential collagen ring in the mid-stromal tissue. Higher spatial resolution rendering of individual lamina cribrosa beams within the nerve head is also demonstrated. Validation of the method is provided in the form of correlative results from wide-angle X-ray scattering and application of the presented method to other fibrous tissues.

Nonuniformity in ligaments is a structural strategy for optimizing functionality

Ligaments serve as compliant connectors between hard tissues. In that role, they function under various load regimes and directions. The 3D structure of ligaments is considered to form as a uniform entity that changes due to function. The periodontal ligament (PDL) connects the tooth to the bone and sustains different types of loads in various directions. Using the PDL as a model, employing a fabricated motorized setup in a microCT, we demonstrate that the fibrous network structure within the PDL is not uniform, even before the tooth becomes functional. Utilizing morphological automated segmentation methods, directionality analysis, as well as second harmonic generation imaging, we find high correlation between blood vessel distribution and fiber density. We also show a structural feature in a form of a dense collar around the neck of the tooth as well as a preferred direction of the fibrous network. Finally, we show that the PDL develops as a nonuniform structure, with an architecture designed to sustain specific types of load in designated areas. Based on these findings, we propose that ligaments in general should be regarded as nonuniform entities, structured already at developmental stages for optimal functioning under variable load regimes.

Investigating mechanisms of tendon damage by measuring multi-scale recovery following tensile loading

Tendon pathology is associated with damage. While tendon damage is likely initiated by mechanical loading, little is known about the specific etiology. Damage is defined as an irreversible change in the microstructure that alters the macroscopic mechanical parameters. In tendon, the link between mechanical loading and microstructural damage, resulting in macroscopic changes, is not fully elucidated. In addition, tendon damage at the macroscale has been proposed to initiate when tendon is loaded beyond a strain threshold, yet the metrics to define the damage threshold are not determined. We conducted multi-scale mechanical testing to investigate the mechanism of tendon damage by simultaneously quantifying macroscale mechanical and microstructural changes. At the microscale, we observe full recovery of the fibril strain and only partial recovery of the interfibrillar sliding, indicating that the damage initiates at the interfibrillar structures. We show that non-recoverable sliding is a mechanism for tendon damage and is responsible for the macroscale decreased linear modulus and elongated toe-region observed at the fascicle-level, and these macroscale properties are appropriate metrics that reflect tendon damage. We concluded that the inflection point of the stress-strain curve represents the damage threshold and, therefore, may be a useful parameter for future studies. Establishing the mechanism of damage at multiple length scales can improve prevention and rehabilitation strategies for tendon pathology.

STATEMENT OF SIGNIFICANCE

Tendon pathology is associated with mechanically induced damage. Damage, as defined in engineering, is an irreversible change in microstructure that alters the macroscopic mechanical properties. Although microstructural damage and changes to macroscale mechanics are likely, this link to microstructural change was not yet established. We conducted multiscale mechanical testing to investigate the mechanism of tendon damage by simultaneously quantifying macroscale mechanical and microstructural changes. We showed that non-recoverable sliding between collagen fibrils is a mechanism for tendon damage. Establishing the mechanism of damage at multiple length scales can improve prevention and rehabilitation strategies for tendon pathology.