Background: During the last few decades the prevalence of lumbar disc herniation has been increasing constantly, thereby imposing a significant socioeconomic burden. Physiotherapy plays a crucial role in both surgical and conservative treatment of lumbar disc herniation, consequently the current COVID-19 pandemic with concomitant lockdowns has led to a shortage of physiotherapeutical care. In the light of these recent events publicly available physiotherapy tutorials may be a useful tool to address this problem. Aim: The main aim of this study was to assess the quality of online physiotherapy exercise tutorials for lumbar disc herniation. Materials & Methods: With YouTube being a widely known and used platform we screened 240 of the most viewed videos. A total of 76 videos met the inclusion criteria and were statistically analyzed. The videos were assessed using Global Quality Score, DISCERN Score and JAMA benchmark criteria and in regard to their applicability. Results: They displayed a wide range of views (44,969 to 5,448,717), likes (66 to 155,079) and dislikes (6 to 2339). The videos were assessed using Global Quality Score, DISCERN Score and JAMA benchmark criteria and in regard to their applicability. Neither the number of “Views”, “Likes”, nor “Dislikes” was found to have a significant association with any of the quality measures used in this study. Conclusion: Overall quality grade was determined as “moderate”. Based on the data examined in this study, the use of YouTube videos as a source of therapy advice for lumbar spine disc herniation cannot be recommended universally.

Over the last few decades, the number of lumbar interbody fusion surgeries performed has been constantly increasing, with transforaminal lumbar interbody fusion (TLIF) being one of the most common surgical techniques. Due to easy accessibility, patients frequently use YouTube to obtain information on health-related issues. Consequently, online video platforms may be a valuable tool for patient education. The aim of this study was to assess the quality, reliability, and comprehensiveness of online videos on TLIF. We screened 180 videos on YouTube, yielding a total of 30 videos that met the inclusion criteria. These videos were evaluated using Global Quality Scale, DISCERN reliability tool, and JAMA Benchmark Score, and assessed in regard to their comprehensiveness and coverage of relevant aspects. At the time of rating, the videos had between 9188 and 1,530,408 views and between 0 and 3344 likes. The median rater assessment for all videos was “moderate quality”. GQS and subjective grades showed a moderate to strong statistically significant association with views and likes. Considering this association of GQS and subjective grade with views and likes, these criteria could be used by laypersons to identify good-quality content. Nevertheless, there is an urgent need for peer-reviewed content that covers all of the relevant aspects.

Background: The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT-4, is transforming healthcare. ChatGPT’s potential to assist in decision-making for complex cases, such as spinal metastasis treatment, is promising but widely untested. Especially in cancer patients who develop spinal metastases, precise and personalized treatment is essential. This study examines ChatGPT-4’s performance in treatment planning for spinal metastasis cases compared to experienced spine surgeons. Materials and Methods: Five spine metastasis cases were randomly selected from recent literature. Consequently, five spine surgeons and ChatGPT-4 were tasked with providing treatment recommendations for each case in a standardized manner. Responses were analyzed for frequency distribution, agreement, and subjective rater opinions. Results: ChatGPT’s treatment recommendations aligned with the majority of human raters in 73% of treatment choices, with moderate to substantial agreement on systemic therapy, pain management, and supportive care. However, ChatGPT’s recommendations tended towards generalized statements, with raters noting its generalized answers. Agreement among raters improved in sensitivity analyses excluding ChatGPT, particularly for controversial areas like surgical intervention and palliative care. Conclusions: ChatGPT shows potential in aligning with experienced surgeons on certain treatment aspects of spinal metastasis. However, its generalized approach highlights limitations, suggesting that training with specific clinical guidelines could potentially enhance its utility in complex case management. Further studies are necessary to refine AI applications in personalized healthcare decision-making.

Demineralized bone matrices (DBMs) are widely used in bone replacement therapy. Bone tissue of either cancellous or cortical origin is decellularized, demineralized, and sterilized during processing, while retaining portions of native organic extracellular matrix (ECM) proteins that regulate cell–matrix interactions during bone repair. The ECM largely accounts for the distinct functions of cortical and cancellous bone. Differences in three-dimensional architecture and matrix density between cancellous and cortical bone may therefore affect ECM proteome signatures and the resulting cellular microenvironment. In this study, ECM proteins were extracted from processed cancellous and cortical allografts at multiple processing steps and analyzed by quantitative mass spectrometry. We identified distinct extractable proteome signatures associated with bone metabolic functions. Cancellous grafts were relatively enriched in proteins associated with inflammatory, coagulative, and immune-related processes, whereas cortical grafts showed higher abundance of structural and matrix-organization-associated proteins. More extensively processed product formats showed fewer significant protein differences between the cortical and cancellous bone type. Within the limitations of pooled donor material and absent functional validation, these findings provide a proteomic framework for future characterization and evaluation of DBM-based allograft products.

Demineralized bone matrix (DBM)-derived allografts retain extracellular matrix (ECM)-associated factors involved in bone repair, but biochemical protein recovery alone may not predict functional pathway activation. We evaluated the HEK-Blue™ TGF-β Reporter Assay as a targeted method for assessing Smad-dependent reporter activity in DBM-derived materials. ECM proteins were extracted from cortical demineralized bone granules (DBG) using guanidine hydrochloride (GuHCl) or urea and quantified after extraction, dialysis, and sterile filtration. Reporter cells were stimulated with extracted ECM proteins or directly with processed cortical and cancellous products, including DBG, wet heat-treated DBG formulated as Putty (PHT), and gamma-irradiated PHT (PGI). Non-pooled DBM sponge samples were also tested. Secreted embryonic alkaline phosphatase (SEAP) activity served as the functional reporter readout. Material-only no-cell controls assessed material-derived background. PrestoBlue™ readouts served as exploratory quality controls. The urea-derived extract yielded a higher apparent BCA-detectable protein concentration than the GuHCl-derived extract. Only the GuHCl-derived extract induced increasing SEAP activity at matched protein input. Direct stimulation showed reporter activation above the TNF-α pathway-negative cytokine control for cortical DBG, PHT, PGI, and cancellous DBG. DBM sponges also induced detectable SEAP activity. These findings support targeted functional screening of Smad-dependent TGF-β reporter activation in DBM-derived materials, but not total osteoinductivity assessment.