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Various nutritional supplements are available over the counter, yet few have been investigated in randomized controlled trials. The rationale for using the specific mix of nutritional substances including collagen type II, hyaluronic acid, n-acetyl-glucosamine, bamboo extract, L-lysine, and vitamin C is the assumption that combining naturally occurring ingredients of the intervertebral disc would maintain spine function. This double-blinded, placebo-controlled randomized trial aimed to evaluate the efficacy of a nutraceutical supplement mix in the management of lumbar osteochondrosis. Fifty patients were randomly assigned to either the supplement or placebo group in a 1:1 ratio. Patient-Reported Outcome Measures (PROMs) included the Oswestry Disability Index (ODI), the visual analogue scale for pain (pVAS), short form-12 (SF-12) physical and mental component summary subscale scores (PCS and MCS, respectively), and global physical activity questionnaire (GPAQ). Magnetic resonance imaging (MRI) was used to evaluate degenerative changes of intervertebral discs (IVD) including Pfirrmann grades as well as three-dimensional (3D) volume measurements. Data were collected at baseline and after the 3-month intervention. None of the PROMs were significantly different between the supplement and placebo groups. Disc degeneration according to Pfirrmann classifications remained stable during the 3-month intervention in both groups. Despite no significance regarding the distribution of Pfirrmann grade changes (improvement, no change, worsening; p = 0.259), in the supplement group, one patient achieved a three-grade improvement, and worsening of Pfirrmann grades were only detected in the placebo group (9.1%). Furthermore, in-depth evaluations of MRIs showed significantly higher 3D-measured volume changes (increase) in the supplement (+740.3 ± 796.1 mm3) compared to lower 3D-measured volume changes (decrease) in the placebo group (−417.2 ± 875.0 mm3; p < 0.001). In conclusion, this multi-nutrient supplement might not only stabilize the progression of lumbar osteochondrosis, but it might also potentially even increase IVD volumes as detected on MRIs. [ABSTRACT FROM AUTHOR]

Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis, development of targeted prevention, and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analyses of disease data sets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and mechanobiology. Our 3D convolutional neural network recognized TMJ disorder patients through participant-specific morphological features in condylar, ramus, and chin. Driven by deep learning model outputs, biomechanical modeling revealed that small mandibular size and flat condylar shape were associated with increased TMJ disorder risk through increased joint force, decreased tissue nutrient availability and cell ATP production, and increased TMJ disc strain energy density. Combining explainable deep learning and multiscale biomechanical modeling addresses the "mechanism unknown" limitation undermining translational confidence in clinical applications of deep learning and increases methodological accessibility for smaller clinical data sets by providing the crucial biomechanical context.

Introduction: Functional impairment of the masticatory region can have significant consequences that range from a loss of quality of life to severe health issues. Increased temporomandibular joint loading is often connected with temporomandibular disorders, but the effect of morphological factors on joint loading is a heavily discussed topic. Due to the small size and complex structure of the masticatory region in vivo investigations of these connections are difficult to perform., Objectives: We propose a novel in silico approach for the investigation of the effect of wear facet inclination and position on TMJ stress., Methods: We use a forward-dynamics tracking approach to simulate lateral bruxing on the canine and first molar using 6 different inclinations, resulting in a total of 12 simulated cases. By using a computational model, we control a single variable without interfering with the system. Muscle activation pattern, maximum bruxing force as well as TMJ disc stress are reported for all simulations., Results: Muscle activation patterns and bruxing forces agree well with previously reported EMG findings and in vivo force measurements. The simulation results show that an increase in inclination leads to a decrease in TMJ loading. Wear facet position seems to play a smaller role with regard to bruxing force but might be more relevant for TMJ loading., Conclusion: Together these results suggest a possible effect of tooth morphology on TMJ loading during bruxism., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University.)