3D printed hybrid scaffolds do not induce adverse inflammation in mice and direct human BM-MSC chondrogenesis in vitro.

Biomaterials that can improve the healing of articular cartilage lesions are needed. To address this unmet need, we developed novel 3D printed silica/poly(tetrahydrofuran)/poly(ε-caprolactone) (SiO2/PTHF/PCL-diCOOH) hybrid scaffolds. Our aim was to carry out essential studies to advance this medical device towards functional validation in pre-clinical trials. First, we show that the chemical composition, microarchitecture and mechanical properties of these scaffolds were not affected by sterilisation with gamma irradiation. To evaluate the systemic and local immunogenic reactivity of the sterilised 3D printed hybrid scaffolds, they were implanted subcutaneously into Balb/c mice. The scaffolds did not trigger a systemic inflammatory response over one week of implantation. The interaction between the host immune system and the implanted scaffold elicited a local physiological reaction with infiltration of mononuclear cells without any signs of a chronic inflammatory response. Then, we investigated how these 3D printed hybrid scaffolds direct chondrogenesis in vitro. Human bone marrow-derived mesenchymal stem/stromal cells (hBM-MSCs) seeded within the 3D printed hybrid scaffolds were cultured under normoxic or hypoxic conditions, with or without chondrogenic supplements. Chondrogenic differentiation assessed by both gene expression and protein production analyses showed that 3D printed hybrid scaffolds support hBM-MSC chondrogenesis. Articular cartilage-specific extracellular matrix deposition within these scaffolds was enhanced under hypoxic conditions (1.7 or 3.7 fold increase in the median of aggrecan production in basal or chondrogenic differentiation media). Our findings show that 3D printed SiO2/PTHF/PCL-diCOOH hybrid scaffolds have the potential to support the regeneration of cartilage tissue.

Artificial intelligence-based analyses of varus leg alignment and after high tibial osteotomy show high accuracy and reproducibility.

PURPOSE: The aim of this study was to investigate the performance of an artificial intelligence (AI)-based software for fully automated analysis of leg alignment pre- and postoperatively after high tibial osteotomy (HTO) on long-leg radiographs (LLRs). METHODS: Long-leg radiographs of 95 patients with varus malalignment that underwent medial open-wedge HTO were analyzed pre- and postoperatively. Three investigators and an AI software using deep learning algorithms (LAMA™, ImageBiopsy Lab, Vienna, Austria) evaluated the hip-knee-ankle angle (HKA), mechanical axis deviation (MAD), joint line convergence angle (JLCA), medial proximal tibial angle (MPTA), and mechanical lateral distal femoral angle (mLDFA). All measurements were performed twice and the performance of the AI software was compared with individual human readers using a Bayesian mixed model. In addition, the inter-observer intraclass correlation coefficient (ICC) for inter-observer reliability was evaluated by comparing measurements from manual readers. The intra-reader variability for manual measurements and the AI-based software was evaluated using the intra-observer ICC. RESULTS: Initial varus malalignment was corrected to slight valgus alignment after HTO. Measured by the AI algorithm and manually HKA (5.36° ± 3.03° and 5.47° ± 2.90° to - 0.70 ± 2.34 and - 0.54 ± 2.31), MAD (19.38 mm ± 11.39 mm and 20.17 mm ± 10.99 mm to - 2.68 ± 8.75 and - 2.10 ± 8.61) and MPTA (86.29° ± 2.42° and 86.08° ± 2.34° to 91.6 ± 3.0 and 91.81 ± 2.54) changed significantly from pre- to postoperative, while JLCA and mLDFA were not altered. The fully automated AI-based analyses showed no significant differences for all measurements compared with manual reads neither in native preoperative radiographs nor postoperatively after HTO. Mean absolute differences between the AI-based software and mean manual observer measurements were 0.5° or less for all measurements. Inter-observer ICCs for manual measurements were good to excellent for all measurements, except for JLCA, which showed moderate inter-observer ICCs. Intra-observer ICCs for manual measurements were excellent for all measurements, except for JLCA and for MPTA postoperatively. For the AI-aided analyses, repeated measurements showed entirely consistent results for all measurements with an intra-observer ICC of 1.0. CONCLUSIONS: The AI-based software can provide fully automated analyses of native long-leg radiographs in patients with varus malalignment and after HTO with great accuracy and reproducibility and could support clinical workflows. LEVEL OF EVIDENCE: Diagnostic study, Level III.

Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings.

BACKGROUND: Radiographic knee osteoarthritis (OA) severity and clinical severity are often dissociated. Artificial intelligence (AI) aid was shown to increase inter-rater reliability in radiographic OA diagnosis. Thus, AI-aided radiographic diagnoses were compared against AI-unaided diagnoses with regard to their correlations with clinical severity. METHODS: Seventy-one DICOMs (m/f = 27:42, mean age: 27.86 ± 6.5) (X-ray format) were used for AI analysis (KOALA software, IB Lab GmbH). Subjects were recruited from a physiotherapy trial (MLKOA). At baseline, each subject received (i) a knee X-ray and (ii) an assessment of five main scores (Tegner Scale (TAS); Knee Injury and Osteoarthritis Outcome Score (KOOS); International Physical Activity Questionnaire; Star Excursion Balance Test; Six-Minute Walk Test). Clinical assessments were repeated three times (weeks 6, 12 and 24). Three physicians analyzed the presented X-rays both with and without AI via KL grading. Analyses of the (i) inter-rater reliability (IRR) and (ii) Spearman's Correlation Test for the overall KL score for each individual rater with clinical score were performed. RESULTS: We found that AI-aided diagnostic ratings had a higher association with the overall KL score and the KOOS. The amount of improvement due to AI depended on the individual rater. CONCLUSION: AI-guided systems can improve the ratings of knee radiographs and show a stronger association with clinical severity. These results were shown to be influenced by individual readers. Thus, AI training amongst physicians might need to be increased. KL might be insufficient as a single tool for knee OA diagnosis.

Deep Learning for Fully Automated Radiographic Measurements of the Pelvis and Hip.

The morphometry of the hip and pelvis can be evaluated in native radiographs. Artificial-intelligence-assisted analyses provide objective, accurate, and reproducible results. This study investigates the performance of an artificial intelligence (AI)-based software using deep learning algorithms to measure radiological parameters that identify femoroacetabular impingement and hip dysplasia. Sixty-two radiographs (124 hips) were manually evaluated by three observers and fully automated analyses were performed by an AI-driven software (HIPPO™, ImageBiopsy Lab, Vienna, Austria). We compared the performance of the three human readers with the HIPPO™ using a Bayesian mixed model. For this purpose, we used the absolute deviation from the median ratings of all readers and HIPPO™. Our results indicate a high probability that the AI-driven software ranks better than at least one manual reader for the majority of outcome measures. Hence, fully automated analyses could provide reproducible results and facilitate identifying radiographic signs of hip disorders.

Artificial intelligence in osteoarthritis: repair by knee joint distraction shows association of pain, radiographic and immunological outcomes.

OBJECTIVES: Knee joint distraction (KJD) has been associated with clinical and structural improvement and SF marker changes. The current objective was to analyse radiographic changes after KJD using an automatic artificial intelligence-based measurement method and relate these to clinical outcome and SF markers. METHODS: Twenty knee osteoarthritis patients were treated with KJD in regular care. Radiographs and WOMAC were collected before and ∼1 year post-treatment. SF was aspirated before, during and after treatment; biomarker levels were assessed by immunoassay. Radiographs were analysed to obtain compartmental minimum and standardized joint space width (JSW), Kellgren-Lawrence (KL) grades, compartmental joint space narrowing (JSN) scores, and osteophytosis and sclerosis scores. Results were analysed for the most affected compartment (MAC) and least affected compartment. Radiographic changes were analysed using the Wilcoxon signed rank test for categorical and paired t-test for continuous variables. Linear regression was used to calculate associations between changes in JSW, WOMAC pain and SF markers. RESULTS: Sixteen patients could be evaluated. JSW, KL and JSN improved in around half of the patients, significant only for MAC JSW (P < 0.05). MAC JSW change was positively associated with WOMAC pain change (P < 0.04). Greater monocyte chemoattractant protein 1 (MCP-1) and lower TGFß-1 increases were significantly associated with changes in MAC JSW (P < 0.05). MCP-1 changes were positively associated with WOMAC pain changes (P < 0.05). CONCLUSION: Automatic radiographic measurements show improved joint structure in most patients after KJD in regular care. MAC JSW increased significantly and was associated with SF biomarker level changes and even with improvements in pain as experienced by these patients.

Adhesive Hydrogels for Maxillofacial Tissue Regeneration Using Minimally Invasive Procedures.

Minimally invasive surgical procedures aiming to repair damaged maxillofacial tissues are hampered by its small, complex structures and difficult surgical access. Indeed, while arthroscopic procedures that deliver regenerative materials and/or cells are common in articulating joints such as the knee, there are currently no treatments that surgically place cells, regenerative factors or materials into maxillofacial tissues to foster bone, cartilage or muscle repair. Here, hyaluronic acid (HA)-based hydrogels are developed, which are suitable for use in minimally invasive procedures, that can adhere to the surrounding tissue, and deliver cells and potentially drugs. By modifying HA with both methacrylate (MA) and 3,4-dihydroxyphenylalanine (Dopa) groups using a completely aqueous synthesis route, it is shown that MA-HA-Dopa hydrogels can be applied under aqueous conditions, gel quickly using a standard surgical light, and adhere to tissue. Moreover, upon oxidation of the Dopa, human marrow stromal cells attach to hydrogels and survive when encapsulated within them. These observations show that when incorporated into HA-based hydrogels, Dopa moieties can foster cell and tissue interactions, ensuring surgical placement and potentially enabling delivery/recruitment of regenerative cells. The findings suggest that MA-HA-Dopa hydrogels may find use in minimally invasive procedures to foster maxillofacial tissue repair.

Combined Anti-inflammatory and Neuroprotective Treatments Have the Potential to Impact Disease Phenotypes in Cln3 -/- Mice.

Batten disease, or juvenile NCL, is a fatal neurodegenerative disorder that occurs due to mutations in the CLN3 gene. Because the function of CLN3 remains unclear, experimental therapies for JNCL have largely concentrated upon the targeting of downstream pathomechanisms. Neuron loss is preceded by localized glial activation, and in this proof-of-concept study we have investigated whether targeting this innate immune response with ibuprofen in combination with the neuroprotective agent lamotrigine improves the previously documented beneficial effects of immunosuppressants alone. Drugs were administered daily to symptomatic Cln3 -/- mice over a 3 month period, starting at 6 months of age, and their impact was assessed using both behavioral and neuropathological outcome measures. During the treatment period, the combination of ibuprofen and lamotrigine significantly improved the performance of Cln3 -/- mice on the vertical pole test, slowing the disease-associated decline, but had less of an impact upon their rotarod performance. There were also moderate and regionally dependent effects upon astrocyte activation that were most pronounced for ibuprofen alone, but there was no overt effect upon microglial activation. Administering such treatments for longer periods will enable testing for any impact upon the neuron loss that occurs later in disease progression. Given the partial efficacy of these treatments, it will be important to test further drugs of this type in order to find more effective combinations.

Author Correction: Bi-directional cell-pericellular matrix interactions direct stem cell fate.

The original version of this Article contained an error in the author affiliations. The affiliation of Marjan Enayati with 'Ludwig Boltzmann Cluster for Cardiovascular Research at the Center for Biomedical Research, Medical University of Vienna, Austria' was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article.

Author Correction: Bi-directional cell-pericellular matrix interactions direct stem cell fate.

In the original version of this Article the dataset identifier in the Data Availability statement was incorrect. The correct dataset identifier is PXD009500. This has been corrected in the HTML and PDF versions of this Article.

Bi-directional cell-pericellular matrix interactions direct stem cell fate.

Modifiable hydrogels have revealed tremendous insight into how physical characteristics of cells' 3D environment drive stem cell lineage specification. However, in native tissues, cells do not passively receive signals from their niche. Instead they actively probe and modify their pericellular space to suit their needs, yet the dynamics of cells' reciprocal interactions with their pericellular environment when encapsulated within hydrogels remains relatively unexplored. Here, we show that human bone marrow stromal cells (hMSC) encapsulated within hyaluronic acid-based hydrogels modify their surroundings by synthesizing, secreting and arranging proteins pericellularly or by degrading the hydrogel. hMSC's interactions with this local environment have a role in regulating hMSC fate, with a secreted proteinaceous pericellular matrix associated with adipogenesis, and degradation with osteogenesis. Our observations suggest that hMSC participate in a bi-directional interplay between the properties of their 3D milieu and their own secreted pericellular matrix, and that this combination of interactions drives fate.

Optimisation of lithium-substituted bioactive glasses to tailor cell response for hard tissue repair.

Bioactive glasses (BG) are used clinically because they can both bond to hard tissue and release therapeutic ions that can stimulate nearby cells. Lithium has been shown to regulate the Wnt/ß-catenin cell signalling pathway, which plays important roles in the formation and repair of bone and teeth. Lithium-releasing BG, therefore, have the potential to locally regulate hard tissue formation; however, their design must be tailored to induce an appropriate biological response. Here, we optimised the release of lithium from lithium-substituted BG by varying BG composition, particle size and concentration to minimise toxicity and maximise upregulation of the Wnt target gene Axin2 in in vitro cell cultures. Our results show that we can tailor lithium release from BG over a wide therapeutic and non-toxic range. Increasing the concentration of BG in cell culture medium can induce toxicity, likely due to modulations in pH. Nevertheless, at sub-toxic concentrations, lithium released from BG can upregulate the Wnt pathway in 17IA4 cells, similarly to treatment with LiCl. Taken together, these data demonstrate that ion release from lithium-substituted BG can be tailored to maximise biological response. These data may be important in the design of BG that can regulate the Wnt/ß-catenin pathway to promote hard tissue repair or regeneration.