Beth A. Winkelstein

The temporomandibular joint (TMJ) features unique tissue structures that support its complex functional demands. Alterations in these structures are often linked to jaw dysfunction, with pain being one of the most prevalent symptoms. However, the mechanisms underlying TMJ pain and its relationship with structural deterioration or functional impairment remain poorly understood. A comprehensive understanding of the interplay among TMJ structure, function, and pain is essential for uncovering disease mechanisms and developing effective therapies. To date, TMJ research in humans and animal models has been predominantly conducted in separate domains of structure, function, and pain, limiting integrative insights. Clinical studies also show inconsistent correlations among joint structural changes, jaw dysfunctions, and craniofacial pain, complicating diagnosis and treatments. This review aims to bridge these traditionally fragmented areas by synthesizing current knowledge across macroscopic and microscopic scales in human and animal models. TMJ diseases involve spatially proximate cellular, extracellular, and neural components that undergo multiscale spatiotemporal changes. These components experience complex mechanical loading during joint movement, triggering mechanical, neural, and immune responses that interact bidirectionally to influence TMJ integrity and pain. In turn, the brain modulates motor output and autonomic function, further affecting joint mechanics and cellular and nociceptive responses. To holistically and quantitatively assess these spatiotemporal dynamic processes, we propose a multiscale and multiphysics framework that integrates joint and tissue biomechanics, biochemical signals, cellular responses, nociception, and psychosocial influences. Realizing this vision requires a transdisciplinary effort and the development and adaptation of advanced methods to study TMJ at unprecedented resolution and details. By unifying structural, functional, and pain-related data, this integrated multiscale approach holds promise for elucidating new mechanisms of TMJ development, disease onset and progression, and pain chronicity. Ultimately, it may guide more effective diagnostics and treatments, including the combined use of physical therapy, neuromodulation, and biologically targeted interventions.

Temporomandibular disorders (TMDs) are complex conditions characterized by orofacial pain and dysfunction, affecting a significant portion of the population. TMDs may involve joint and/or muscle pain, dysfunction (e.g., noise, limited or altered jaw movements), or both, leading to a marked decrease in quality of life. Patients often experience functional limitations that hinder eating, speaking, and daily activities. Additionally, TMDs are frequently associated with psychological distress, including anxiety and depression, which further impacts overall well-being. Despite the profound individual and societal impact of TMDs, effective therapies remain elusive, partly due to deficiencies in translational research. A primary limitation in the TMD field is the scarcity of animal models that accurately replicate disease features in humans. This may ultimately be due to species differences, but likely also reflects the etiological and symptomatic heterogeneities of TMDs, as there are over 30 different conditions in this umbrella term. Both factors pose a significant challenge in developing and using animal models for TMD research. This review highlights preclinical TMD research to enhance clinical care, focusing on anatomy/physiology, pain and behavior models, functional and tissue modeling, biopsychosocial factors, and technological considerations. The “TMD Research Community” collaborated to produce this review, with the Discussion offering a proposal for a path forward.

INTRODUCTION: Manual therapies are forms of force-based manipulations (FBM) and involve the application of mechanical force to the outside of the body with therapeutic intent. The United States National Institutes of Health (NIH) U24 FBM Taxonomy and Terminology Committee (FBM-TTC) was formed to better understand why responses to FBM differ between individuals. One objective for this multi-disciplinary working group was to develop a framework outlining factors that should be considered, measured, and reported when developing and performing studies on FBM. METHODS: The workgroup collaborated to develop a model outlining elements to consider during FBM research and practice. Three different models were proposed by members of the group who voted on a preferred model using a rank-ordered process and refined the selected model based on consensus and published literature. RESULTS: A 3-dimensional (3D) matrix model was chosen that includes three elements: contextual factors influencing FBM outcomes, structure and function levels focusing on biological and physiological aspects, and force parameters. Each element expands into different components and sub-levels. The model is designed to be interactive, integrative, and dynamic. DISCUSSION: The model provides a framework to guide protocol development for FBM mechanistic research and clinical outcome studies. For example, researchers can design more robust studies systematically varying force parameters by considering other matrix components, while clinicians may develop more personalized treatment plans. The model supports the complexity of mechanistic responses to FBM by integrating the multitude of intrinsic and extrinsic factors that impact responses. Detailed discussion of each element is beyond the scope of this paper; however, content experts are encouraged to expand on this dynamic model. CONCLUSIONS: An innovative 3D model was developed to guide FBM research. The framework integrates foundational elements and accommodates new insights, making it a valuable tool to advance FBM science and practice.

PURPOSE: Adolescent idiopathic scoliosis (AIS) affects a significant portion of the adolescent population, leading to severe spinal deformities if untreated. Diagnosis, surgical planning, and assessment of outcomes are determined primarily by the Cobb angle on anteroposterior spinal radiographs. Screening for scoliosis enables early interventions and improved outcomes. However, screenings are often conducted through school entities where a trained radiologist may not be available to accurately interpret the imaging results. METHODS: In this study, we developed an artificial intelligence tool utilizing a keypoint region-based convolutional neural network (KR-CNN) for automated thoracic Cobb angle (TCA) measurement. The KR-CNN was trained on 609 whole-spine radiographs of AIS patients and validated using our institutional AIS registry, which included 83 patients who underwent posterior spinal fusion with both preoperative and postoperative anteroposterior X-ray images. RESULTS: The KR-CNN model demonstrated superior performance metrics, including a mean absolute error (MAE) of 2.22, mean squared error (MSE) of 9.1, symmetric mean absolute percentage error (SMAPE) of 4.29, and intraclass correlation coefficient (ICC) of 0.98, outperforming existing methods. CONCLUSION: This method will enable fast and accurate screening for AIS and assessment of postoperative outcomes and provides a development framework for further automation and validation of spinopelvic measurements.

BACKGROUND: Accumulating evidence demonstrates that the therapeutic effects of stem cells are most likely attributed to their secretome, composed of a myriad of bioactive factors, including small extracellular vesicles (EVs). Due to the potential benefits over cells in term of handling, preservation, stability, and safety, MSC-derived secretome is emerging as a novel cell-free therapeutic for regenerative therapy of various diseases. The purpose of this study is to optimize the xeno-free culture conditions to improve the secretome production by human gingiva-derived mesenchymal stem cells (GMSCs) and test their regenerative potential using an experimental rat model of tongue muscle defect. METHODS: Next-generation mRNA sequencing was performed to compare the gene expression profiles between GMSCs cultured under the defined xeno-free induction culture conditions (iGMSCs) and their 2D-cultured counterparts under regular serum-free conditions. The conditioned media (CM) from iGMSCs and 2D-GMSCs were harvested and concentrated through ultrafiltration to obtain secretomes. The EVs and soluble protein/peptide factor fractions (SPs) from the concentrated CM/secretome were separated using the 35 nm qEVoriginal size exclusion columns. The EVs were confirmed by Nanoparticle Tracking Analysis (NTA), Western blot, and transmission electron microscopy (TEM). The functional effects of secretomes derived from iGMSCs and 2D-GMSCs on macrophage polarization and skeletal muscle progenitor cells were compared both in vitro and in vivo using a rat tongue defect model. RESULTS: Next-generation mRNA sequencing showed profound transcriptomic changes in iGMSCs compared to their 2D counterparts. Further Gene Ontology (GO)-term annotation and Gene Set Enrichment Analysis (GSEA) revealed significant upregulation of a panel of differentially expressed genes (DEGs) related to EVs and secreted cellular components (GO_CCs) and enriched pathways in oxidative phosphorylation, Wnt/β-catenin signaling, Notch signaling, and inflammatory responses in iGMSCs compared to 2D-GMSCs. iGMSC-derived CM/secretome showed a significant enrichment of both EVs and SPs compared to that derived from 2D-GMSCs, as confirmed by Nanoparticle Tracking Analysis (NTA), Western blot, and transmission electron microscopy (TEM). In vitro functional assays revealed a markedly enhanced secretion of IL-10, whilst suppressed LPS-stimulated secretion of TNF-α in macrophages treated with iGMSC-derived CM/secretome in comparison with that from 2D-GMSCs. In addition, iGMSC-derived CM/secretome potently induced the expression of myogenic transcriptional factors in both murine myoblasts and human skeletal muscle progenitors in comparison with 2D-GMSC-derived CM/secretome. Notably, in vivo studies using a rat tongue wound defect model, iGMSC-derived CM/secretome applied topically at the excised wound bed promoted rapid tissue repair/regeneration without fibrosis/scar and shape deformity. CONCLUSION: Secretome derived from GMSCs cultured under optimized xeno-free induction displayed enrichment of EVs and SPs and enhanced pro-myogenic potentials and anti-inflammatory effect on macrophages. These findings have shed light on the potential applications of the optimized iGMSC-derived secretome as cell-free therapeutics for regenerative therapy of tongue wound defects and other muscular diseases.

Treatment mechanisms (TM) reflect the steps or processes through which a treatment unfolds. However, TM research faces challenges due to inconsistent terminology and varying measurement approaches for each mechanism, which creates confusion and controversy among clinicians and scientists. In this paper, we: 1) define key terms associated with TM, 2) provide recommended categories of study that reflect intervention domains, and 3) present examples of measures of TM within the defined categories. Our recommended definitions differentiate associated TM (a finding that occurs following administration of a treatment that may or may not influence outcomes) from causal TM (which directly affects the clinical outcome). When measuring causal TM, we recommend that researchers consider three potential categories of interventional domains: a) anatomical, b) psychological/cognitive and c) behavioral. Lastly, we argue that within each interventional domain, TM can be measured across a spectrum that includes physiological (e.g., brain activity, nerve activity, biomarkers, etc.) and functional (e.g., range of motion, stiffness, cognition measures, etc.) mechanisms. Measuring both physiological and functional mechanisms improves the likelihood of understanding the complexity of clinical recovery. Harmonizing TM terminology, categories, and measurements across a spectrum, while providing examples of each, may reduce confusion and assist researchers and funding sources in targeting specific mechanistic-related questions.

Background: Matching disease and treatment mechanisms is a goal of the Precision Medicine Initiative. Pro- and anti-inflammatory cytokines (e.g., Tumor Necrosis Factor-alpha, Transforming Growth Factor-beta, and Interleukin-2, 10, and 12) have gained a significant amount of interest in their potential role in persistent pain for musculoskeletal (MSK) conditions. Manual therapy (MT) and exercise are two guideline-recommended approaches for treating MSK conditions. The objective of this narrative overview was to investigate of the effects of MT and exercise on pro- and anti-inflammatory cytokines and determine the factors that lead to variability in results. Methods: Two reviewers evaluated the direction and variabilities of MT and exercise literature. A red, yellow, and green light scoring system was used to define consistencies. Results: Consistencies in responses were seen with acute and chronic exercise and both pro- and anti-inflammatory cytokines. Chronic exercise is associated with a consistent shift towards a more anti-inflammatory cytokine profile (Transforming Growth Factor-beta, and Interleukin-2 and 13, whereas acute bouts of intense exercise can transiently increase pro-inflammatory cytokine levels. The influence of MT on cytokines was less commonly studied and yielded more variable results. Conclusion: Variability in findings is likely related to the subject and their baseline condition or disease, when measurement occurs, and the exercise intensity, duration, and an individual's overall health and fitness.

Low back pain is a prevalent condition that affects the global population. The lumbar facet capsular ligament is a source of pain since the collagenous tissue of the ligament is innervated with sensory neurons that deform with the capsule’s stretch. Regional differences in the microstructural and macrostructural anatomy of the spinal facets affect its capsule’s mechanical behavior. Although there are many studies of the cervical facet in human and rodent models, the lumbar capsular ligament’s multiscale behavior is less well-defined. This study characterizes the macroscale and fiber-scale changes of the rat lumbar facet capsule during tensile failure loading. An integrated polarized light imaging setup captured local fiber alignment during 0.08mm/s distraction of 7 lumbar facets. Force, displacement, strain, and circular variance were measured at several points along the failure curve: the first instance when the local collagen fiber network realigns differentially (anomalous realignment), yield, the first peak in force corresponding to the capsule’s first failure, and peak force, defined as ultimate rupture. Those outcomes were compared across events. While each of force, displacement, and average maximum principal strain increased with applied tension, so did the circular variance of the collagen, suggesting that the fibers were becoming more disorganized. From the fiber alignment maps collected at each mechanical event, the number of anomalous realignment events were counted and found to increase dramatically with loading. The increased collagen disorganization and increasing regions of such disorganization in the facet capsule during loading can provide insights about how loading to the ligament afferent nerves may be activated and thereby produce pain.

Background: To understand the facet capsular ligament's (FCL) role in cervical spine mechanics, the interactions between the FCL and other spinal components must be examined. One approach is to develop a subject-specific finite element (FE) model of the lower cervical spine, simulating the motion segments and their components' behaviors under physiological loading conditions. This approach can be particularly attractive when a patient's anatomical and kinematic data are available. Methods: We developed and demonstrated methodology to create 3D subject-specific models of the lower cervical spine, with a focus on facet capsular ligament biomechanics. Displacement-controlled boundary conditions were applied to the vertebrae using kinematics extracted from biplane videoradiography during planar head motions, including axial rotation, lateral bending, and flexion-extension. The FCL geometries were generated by fitting a surface over the estimated ligament-bone attachment regions. The fiber structure and material characteristics of the ligament tissue were extracted from available human cervical FCL data. The method was demonstrated by application to the cervical geometry and kinematics of a healthy 23-year-old female subject. Results: FCL strain within the resulting subject-specific model were subsequently compared to models with generic: (1) geometry, (2) kinematics, and (3) material properties to assess the effect of model specificity. Asymmetry in both the kinematics and the anatomy led to asymmetry in strain fields, highlighting the importance of patient-specific models. We also found that the calculated strain field was largely independent of constitutive model and driven by vertebrae morphology and motion, but the stress field showed more constitutive-equation-dependence, as would be expected given the highly constrained motion of cervical FCLs. Conclusions: The current study provides a methodology to create a subject-specific model of the cervical spine that can be used to investigate various clinical questions by coupling experimental kinematics with multiscale computational models.