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Abstract Objective In gout, monosodium urate crystals are taken up by macrophages, triggering the activation of the NLRP3 inflammasome and the maturation of IL-1β. This study aimed to investigate the role of integrin CD11b in inflammasome activation in macrophages stimulated by MSU. Methods BMDM from WT and CD11b KO mice were stimulated in vitro with MSU crystals. Cellular supernatants were collected to assess the expression of the inflammatory cytokines by enzyme-linked immunosorbent assay and western blot methods. The role of integrin CD11b in MSU-induced gouty arthritis in vivo was investigated by intra-articular injection of MSU crystals. Real-time extracellular acidification rate and oxygen consumption rate of BMDMs were measured by Seahorse Extracellular Flux Analyzer. Results We demonstrate that CD11b-deficient mice developed exacerbated gouty arthritis with increased recruitment of leukocytes in the joint and higher IL-1β levels in the sera. In macrophages, genetic deletion of CD11b induced a shift of macrophage metabolism from oxidative phosphorylation to glycolysis, thus decreasing the overall generation of intracellular ATP. Upon MSU stimulation, CD11b-deficient macrophages showed an exacerbated secretion of IL-1β. Treating wild-type macrophages with a CD11b agonist, LA1, inhibited MSU-induced release of IL-1β in vitro and attenuated the severity of experimental gouty arthritis. Importantly, LA1, was also effective in human cells as it inhibited MSU-induced release of IL-1β by peripheral blood mononuclear cells from healthy donors. Conclusion Our data identified the CD11b integrin as a principal cell membrane receptor that modulates NLRP3 inflammasome activation by MSU crystal in macrophages, which could be a potential therapeutic target to treat gouty arthritis in human patients.

Lysyl oxidases (LOX(L)) are enzymes that catalyze the formation of cross-links in collagen and elastin fibers during physiologic calcification of bone. However, it remains unknown whether they may promote pathologic calcification of articular cartilage, an important hallmark of debilitating arthropathies. Here, we have studied the possible roles of LOX(L) in cartilage calcification, related and not related to their cross-linking activity. We first demonstrated that inhibition of LOX(L) by β-aminoproprionitrile (BAPN) significantly reduced calcification in murine and human chondrocytes, and in joint of meniscectomized mice. These BAPN’s effects on calcification were accounted for by different LOX(L) roles. Firstly, reduced LOX(L)-mediated extracellular matrix cross-links downregulated Anx5, Pit1 and Pit2 calcification genes. Secondly, BAPN reduced collagen fibrotic markers Col1 and Col3. Additionally, LOX(L) inhibition blocked chondrocytes hypertrophic differentiation (Runx2 and COL10), pro-inflammatory IL-6 release and reactive oxygen species (ROS) production, all triggers of chondrocyte calcification. Through unbiased transcriptomic analysis we confirmed a positive correlation between LOX(L) genes and genes for calcification, hypertrophy and extracellular matrix catabolism. This association was conserved throughout species (mouse, human) and tissues that can undergo pathologic calcification (kidney, arteries, skin). Overall, LOX(L) play a critical role in the process of chondrocyte calcification and may be therapeutic targets to treat cartilage calcification in arthropathies.

Abstract In this work we compare the current experimental LHC limits of the 2HDM + scalar and pseudoscalar for the t t ¯ $$ t\overline{t} $$ , mono-Z and mono-h signatures and forecast the reach of future LHC upgrades for the mono-Z channel. Furthermore, we comment on the possibility, in case of a signal detection, to discriminate between the two models. The 2HDM+S and 2HDM+PS are two notable examples of the so-called next generation of Dark Matter Simplified Models. They allow for a renormalizable coupling of fermionic, Standard Model singlet, Dark Matter with a two Higgs doublet sector, through the mixing of the latter with a scalar or pseudoscalar singlet.

Abstract Many models of physics beyond the Standard Model predict a strong first-order phase transition (SFOPT) in the early Universe that leads to observable gravitational waves (GWs). In this paper, we propose a novel method for presenting and comparing the GW signals that are predicted by different models. Our approach is based on the observation that the GW signal has an approximately model-independent spectral shape. This allows us to represent it solely in terms of a finite number of observables, that is, a set of peak amplitudes and peak frequencies. As an example, we consider the GW signal in the real-scalar-singlet extension of the Standard Model (xSM). We construct the signal region of the xSM in the space of observables and show how it will be probed by future space-borne interferometers. Our analysis results in sensitivity plots that are reminiscent of similar plots that are typically shown for dark-matter direct-detection experiments, but which are novel in the context of GWs from a SFOPT. These plots set the stage for a systematic model comparison, the exploration of underlying model-parameter dependencies, and the construction of distribution functions in the space of observables. In our plots, the experimental sensitivities of future searches for a stochastic GW signal are indicated by peak-integrated sensitivity curves. A detailed discussion of these curves, including fit functions, is contained in a companion paper [1].

We investigate the dark matter phenomenology of a Dirac fermion together with kinetic mixing in the context of an Lμ−Lτ model. We analyze which part of the parameter space can provide a viable dark matter candidate and explain the B-decay anomaly, while obeying current data. Although the allowed region of parameter space, satisfying these requirements, is still large at the moment, future direct detection experiments like XENONnT and DARWIN will, in case of null results, significantly strengthen the limits and push the model to a corner of the parameter space.

Objective Overlapping chronic pain syndromes, including fibromyalgia, are heterogeneous and often treatment‐resistant entities carrying significant socioeconomic burdens. Individualized treatment approaches from both a somatic and psychological side are necessary to improve patient care. The objective of this study was to identify and visualize patient clusters in refractory musculoskeletal pain syndromes through an extensive set of clinical variables, including immunologic, psychosomatic, wearable, and sleep biomarkers. Methods Data were collected during a multimodal pain program involving 202 patients. Seventy‐eight percent of the patients fulfilled the criteria for fibromyalgia, 77% had a concomitant psychiatric‐mediated disorder, and 22% a concomitant rheumatic immune‐mediated disorder. Five patient phenotypes were identified by hierarchical agglomerative clustering as a form of unsupervised learning, and a predictive model for the Brief Pain Inventory (BPI) response was generated. Based on the clustering data, digital personas were created with DALL‐E (OpenAI). Results The most relevant distinguishing factors among clusters were living alone, body mass index, peripheral joint pain, alexithymia, psychiatric comorbidity, childhood pain, neuroleptic or benzodiazepine medication, and response to virtual reality. Having an immune‐mediated disorder was not discriminatory. Three of five clusters responded to the multimodal treatment in terms of pain (BPI intensity), one cluster responded in terms of functional improvement (BPI interference), and one cluster notably responded to the virtual reality intervention. The independent predictive model confirmed strong opioids, trazodone, neuroleptic treatment, and living alone as the most important negative predictive factors for reduced pain after the program. Conclusion Our model identified and visualized clinically relevant chronic musculoskeletal pain subtypes and predicted their response to multimodal treatment. Such digital personas and avatars may play a future role in the design of personalized therapeutic modalities and clinical trials.

Abstract Background The histopathological analysis of minor salivary gland biopsies, particularly through the quantification of the Focus Score (FS), is pivotal in the diagnostic workflow for Sjögren's Syndrome (SS). AI-based image recognition using deep learning models has demonstrated potential in enhancing diagnostic accuracy and efficiency in preclinical research. Objectives The primary aim of this investigation was to utilize an auto-machine learning (autoML) platform for the automated segmentation and quantification of FS on histopathological slides, aiming to augment diagnostic precision and speed in SS. Methods A cohort comprising 86 patients with sicca syndrome (37 diagnosed with SS based on the 2016 ACR/EULAR Classification Criteria and 49 non-SS) was selected for an in-depth histological examination. A repository of 172 slides (two per patient) was assembled, encompassing 74 slides meeting the classificatory thresholds for SS (FS ≥ 1, indicative of lymphocytic infiltration) and 98 slides showcasing normal salivary gland histology. The autoML platform utilized (Giotto, L2F, Lausanne Switzerland) employed a Convolutional Neural Network (CNN) architecture (ResNet-152) for the training and validation phases, using a dataset of 172 slides. Results The developed model exhibited a reliability score of 0.88, proficiently distinguishing SS cases, with a sensitivity of 89.47% (95% CI: 66.86% to 98.70%) and a specificity of 88.24% (95% CI: 63.56% to 98.54%). The model found histological slides of suboptimal quality (e.g., those compromised during fixation or staining processes) to be the most challenging for accurate classification. Conclusion AutoML platforms offer a rapid and flexible approach to developing machine learning models, even with smaller datasets, as demonstrated in this study for SS. These platforms hold significant potential for enhancing diagnostic precision and efficiency in both clinical and research settings. Multicentric studies with larger patient cohorts are essential for thorough evaluation and validation of this innovative diagnostic approach.

Objective Automated machine learning (autoML) platforms allow health care professionals to play an active role in the development of machine learning (ML) algorithms according to scientific or clinical needs. The aim of this study was to develop and evaluate such a model for automated detection and grading of distal hand osteoarthritis (OA). Methods A total of 13,690 hand radiographs from 2,863 patients within the Swiss Cohort of Quality Management (SCQM) and an external control data set of 346 non‐SCQM patients were collected and scored for distal interphalangeal OA (DIP‐OA) using the modified Kellgren/Lawrence (K/L) score. Giotto (Learn to Forecast [L2F]) was used as an autoML platform for training two convolutional neural networks for DIP joint extraction and subsequent classification according to the K/L scores. A total of 48,892 DIP joints were extracted and then used to train the classification model. Heatmaps were generated independently of the platform. User experience of a web application as a provisional user interface was investigated by rheumatologists and radiologists. Results The sensitivity and specificity of this model for detecting DIP‐OA were 79% and 86%, respectively. The accuracy for grading the correct K/L score was 75%, with a κ score of 0.76. The accuracy per DIP‐OA class differed, with 86% for no OA (defined as K/L scores 0 and 1), 71% for a K/L score of 2, 46% for a K/L score of 3, and 67% for a K/L score of 4. Similar values were obtained in an independent external test set. Qualitative and quantitative user experience testing of the web application revealed a moderate to high demand for automated DIP‐OA scoring among rheumatologists. Conversely, radiologists expressed a low demand, except for the use of heatmaps. Conclusion AutoML platforms are an opportunity to develop clinical end‐to‐end ML algorithms. Here, automated radiographic DIP‐OA detection is both feasible and usable, whereas grading among individual K/L scores (eg, for clinical trials) remains challenging.

BACKGROUND: Chronic musculoskeletal pain syndromes, including fibromyalgia, are heterogeneous entities with a major socioeconomic burden. Multimodal treatment programmes have shown greater efficacy than conventional approaches for these patients, at least in the short term. A profound understanding of chronic musculoskeletal pain syndrome patients treated in multimodal treatment programmes is important for their development and to provide insight into these conditions. AIM: To provide a comprehensive and objective description of medical, psychosocial and sleep characteristics of the treatment-refractory chronic musculoskeletal pain syndrome patients treated at the multimodal treatment programmes provided by our tertiary service in Switzerland. METHODS: This was a cross-sectional analysis of 202 refractory chronic musculoskeletal pain syndrome patients with or without a concomitant autoimmune disorder hospitalised between 2018 and 2022 in a 12-day Swiss multimodal treatment programme. They underwent a comprehensive self-assessment with eight different questionnaires and assessments by a psychiatrist, rheumatologist, pain specialist, occupational therapist and physiotherapist. Sleep assessment was performed via actigraphy. Clinical and demographic variables were selected by consensus of three experienced rheumatologists and chronic pain specialists. The Fibromyalgia Rapid Screening Test (FiRST), American College of Rheumatology (ACR)-2010 criteria (ACR2010) and Toronto Alexithymia Scale-20 (TAS-20) were also applied. RESULTS: The mean age of the patients was 47 years (SD = 10), 73% were female, and 30% were obese. Half (50%) were not from Switzerland, and 12% came from conflict zones. Almost half (40%) lived alone. Back pain was the principal site (90%). Of the patients, 78% fulfilled the ACR2010 criteria for fibromyalgia, and 17% were diagnosed with an underlying immune-mediated disorder, mostly spondylarthritis. Pain since childhood occurred in 45% of the patients, and 68% had pain since adolescence. Disability financial aid had been pursued by 69%, and 46% were still awaiting a response. Psychiatric comorbidities were highly prevalent (73%), of which 56% consisted of depression. Of all patients, 15% were diagnosed with enduring personality changes after a catastrophic experience (EPCACE), and 10% had post-traumatic stress disorder. Alexithymia affected 34% of patients. Objective sleep disorder was observed in 78% of patients, and 41% were under opioid therapy. CONCLUSION: This analysis reveals the complex psychosomatic and socioeconomic patterns of the patients treated in Switzerland with refractory chronic musculoskeletal pain syndromes, often originating in childhood and adolescence. Obesity, immigration, social isolation, psychiatric comorbidities, sleep deprivation and opiate use, among others, stood out as target characteristics for further research.

BackgroundCalcium pyrophosphate deposition (CPPD) disease is a leading cause of arthritis, which can mimic or strongly interfere with other rheumatic diseases such as gout, osteoarthritis (OA) or rheumatoid arthritis (RA). In the recently established ACR/EULAR CPPD classification criteria, calcification and OA features of the wrist and hand joints are substantial features.ObjectivesTo develop and test a deep-learning algorithm for automatically and reliably detecting CPPD features in hand radiographs, focusing on calcification of the triangular fibrocartilage complex (TFCC) and metacarpophalangeal (MCP)-2 and -3 joints, in separate or combined models.MethodsTwo radiologists independently labeled a dataset of 926 hand radiographs, yielding 319 CPPD positive and 607 CPPD negative cases across the three sites of interest after adjudicating discrepant cases. CPPD presence was then predicted using a convolutional neural network. We tested seven CPPD models, each with a different combination of sites out of TFCC, MCP-2 and MCP-3. The model performance was assessed using the area under the receiver operating characteristic (AUROC) and area under the precision-recall (AUPR) curves, with heatmaps (Grad-CAM) aiding in case discrimination.ResultsAll models trialed gave good class separation, with the combined TFCC, MCP-2 and MCP-3 model showing the most robust performance with a mean AUROC of 0.86, mean AUPR of 0.77, sensitivity of 0.77, specificity of 0.80, and precision of 0.67. The TFCC-alone model had a slightly lower mean AUROC of 0.85 with a mean AUPR of 0.73. The MCP-2-alone and MCP-3-alone models exhibited mean AUROCs of 0.78–0.87, but lower mean AUPRs of 0.29–0.47. Heatmap analysis revealed activation in the regions of interest for positive cases (true and false positives), but unexpected highlights were encountered possibly due to correlated features in different hand regions.ConclusionA combined deep-learning model detecting CPPD at the TFCC and MCP-2/3 joints in hand radiographs provides the highest diagnostic performance. The algorithm could be used to screen larger OA or RA databases or electronic medical records for CPPD cases. Future work includes dataset expansion and validation with external datasets.

BackgroundDigital therapeutics (DTx) in the form of mobile health (mHealth) self-management programs have demonstrated effectiveness in reducing disease activity across various diseases, including fibromyalgia and arthritis. However, the content of online self-management programs varies widely, making them difficult to compare.AimThis study aims to employ generative artificial intelligence (AI)-based knowledge graphs and network analysis to categorize and structure mHealth content at the example of a fibromyalgia self-management program.MethodsA multimodal mHealth online self-management program targeting fibromyalgia and post-viral fibromyalgia-like syndromes was developed. In addition to general content, the program was customized to address specific features and digital personas identified through hierarchical agglomerative clustering applied to a cohort of 202 patients with chronic musculoskeletal pain syndromes undergoing multimodal assessment. Text files consisting of 22,150 words divided into 24 modules were used as the input data. Two generative AI web applications, ChatGPT-4 (OpenAI) and Infranodus (Nodus Labs), were used to create knowledge graphs and perform text network analysis, including 3D visualization. A sentiment analysis of 129 patient feedback entries was performed.ResultsThe ChatGPT-generated knowledge graph model provided a simple visual overview with five primary edges: “Mental health challenges”, “Stress and its impact”, “Immune system function”, “Long COVID and fibromyalgia” and “Pain management and therapeutic approaches”. The 3D visualization provided a more complex knowledge graph, with the term “pain” appearing as the central edge, closely connecting with “sleep”, “body”, and “stress”. Topical cluster analysis identified categories such as “chronic pain management”, “sleep hygiene”, “immune system function”, “cognitive therapy”, “healthy eating”, “emotional development”, “fibromyalgia causes”, and “deep relaxation”. Gap analysis highlighted missing links, such as between “negative behavior” and “systemic inflammation”. Retro-engineering of the self-management program showed significant conceptual similarities between the knowledge graph and the original text analysis. Sentiment analysis of free text patient comments revealed that most relevant topics were addressed by the online program, with the exception of social contacts.ConclusionGenerative AI tools for text network analysis can effectively structure and illustrate DTx content. Knowledge graphs are valuable for increasing the transparency of self-management programs, developing new conceptual frameworks, and incorporating feedback loops.

Objective: To assess morphological and histological features of cartilage at the posterior medial condyle in advanced pre-prosthetic osteoarthritis (OA), which is notably thicker compared to non-OA knees. Design: Cartilage thickness was measured pre-operatively using MRI in 10 subjects with medial femorotibial OA (mean age: 70.2 years). Posterior condyles were obtained during arthroplasty and cartilage thickness, relative collagen content and subchondral bone volume fraction (BV/TV) were determined using phosphotungstic acid (PTA)-enhanced micro-CT. Regions of interest (ROI) around the maximum cartilage thickness were further analyzed through histomorphometry (Mankin score) and immunohistochemistry (cell density and apoptosis rates). Results: Maximum cartilage thickness was 2.63 ​± ​0.51 ​mm in vivo and 3.04 ​± ​0.55 ​mm ex vivo and both measurements were strongly correlated (r ​= ​0.84, p ​= ​0.003). Cartilaginous collagen content measured by PTA-enhanced micro-CT was negatively correlated with maximum cartilage thickness (r ​= ​–0.70, p ​= ​0.02). Average subchondral BV/TV was 31.6 ​± ​3.4% and did not correlate with cartilage thickness. Extensive loss of proteoglycan staining and tidemark multiplication were common histomorphological features around the maximum cartilage thickness. Chondrocyte densities were 315 ​± ​67 and 194 ​± ​36 ​cells/mm2 at the superficial and transitional cartilage zones, respectively. Chondrocyte apoptosis rates were approximately 70% in both zones. Maximum cartilage thickness correlated with superficial chondrocyte densities (r ​= ​0.79, p ​= ​0.01). Conclusions: Thicker cartilage at the posterior medial condyle in OA knees displayed degenerative changes both in cartilage tissue and at the osteochondral junction. Cartilage thickening may be influenced by alterations in the superficial zone, necessitating further investigation through molecular studies.

Analysing complex diseases such as chronic inflammatory joint diseases (CIJDs), where many factors influence the disease evolution over time, is a challenging task. CIJDs are rheumatic diseases that cause the immune system to attack healthy organs, mainly the joints. Different environmental, genetic and demographic factors affect disease development and progression. The Swiss Clinical Quality Management in Rheumatic Diseases (SCQM) Foundation maintains a national database of CIJDs documenting the disease management over time for 19'267 patients. We propose the Disease Activity Score Network (DAS-Net), an explainable multi-task learning model trained on patients' data with different arthritis subtypes, transforming longitudinal patient journeys into comparable representations and predicting multiple disease activity scores. First, we built a modular model composed of feed-forward neural networks, long short-term memory networks and attention layers to process the heterogeneous patient histories and predict future disease activity. Second, we investigated the utility of the model's computed patient representations (latent embeddings) to identify patients with similar disease progression. Third, we enhanced the explainability of our model by analysing the impact of different patient characteristics on disease progression and contrasted our model outcomes with medical expert knowledge. To this end, we explored multiple feature attribution methods including SHAP, attention attribution and feature weighting using case-based similarity. Our model outperforms temporal and non-temporal neural network, tree-based, and naive static baselines in predicting future disease activity scores. To identify similar patients, a k-nearest neighbours regression algorithm applied to the model's computed latent representations outperforms baseline strategies that use raw input features representation.

Background: Hip osteoarthritis (OA) involves structural degeneration of different joint compartments, including femoral head cartilage, periarticular ligaments and the acetabular labrum. However, the molecular mechanisms underlying labrum degeneration in hip OA remain poorly understood. Aim: To assess secretion of putative biomarkers for OA from explanted human labrum tissues under basal and inflammatory conditions and to determine whether these could differentiate between OA and calcification status compared to fracture controls. Methods: Intact labrum specimens were collected from patients undergoing joint arthroplasty for primary hip OA (n ​= ​15, mean age 70) or non-OA femoral neck fracture (n ​= ​5, mean age 64). Tissues were dissected in equal-sized samples and explanted for one week. To mimic activation of inflammatory signaling by endogenous damage-associated molecular patterns (DAMP) tissue were stimulated with a toll-like receptor 4 (TLR4) agonist (1 ​μg/mL LPS). The involvement of transforming growth factor-beta (TGF-beta) signaling was evaluated by treatment with a TGF-beta type 1 receptor inhibitor (10 ​μM SB-505124). Secretion of aggrecan (ACAN), pro-collagen-I alpha (Pro-Col-Iα), cartilage oligomeric matrix protein (COMP), interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) was assessed by enzyme-linked immunosorbent assay (ELISA). Labrum calcification was evaluated by 3D whole mount fluorescent microscopy of ethyl cinnamate-based optically cleared tissues stained with Alcian blue/Alizarin red. Results: Whole mount microscopy revealed non-OA fracture controls were non-calcified, whereas six OA labra (40%) were partially calcified or ossified. Basal secretion of Pro-Col-Iα and VEGF was increased four-fold in OA versus non-OA labra. Pro-Col-Iα levels were correlated with those of VEGF (r ​= ​0.65) and COMP (r ​= ​0.54). Stimulation of DAMP signaling through TLR4 affected secretion of IL-6, VEGF, COMP and Pro-Col-Iα, with distinct responses between non-OA and OA tissues. Inhibition of TGF-beta signaling specifically reduced elevated secretion of Pro-Col- Iα and VEGF in calcified OA labrum. Conclusions: Secretion of the putative OA biomarkers Pro-Col-Iα and VEGF is elevated in degenerated human acetabular labrum and may serve as indicators of OA and calcification status. Secretion of both factors was partially regulated by TGF-beta signaling in calcified OA labrum tissues.The Translational potential of this article:Our findings suggest that a biomarker panel consisting of Pro-Col-Iα/VEGF/COMP may be valuable for assessing subradiographic labrum degeneration and calcification in hip OA. Targeting TGF-beta signaling may offer a means to reduce vascular invasion and fibrosis in acetabular labrum tissue.

BackgroundPersistent fibromyalgia-like symptoms have been increasingly reported following viral infections, including SARS-CoV-2. About 30% of patients with post–COVID-19 syndrome fulfill the fibromyalgia criteria. This complex condition presents significant challenges in terms of self-management. Digital health interventions offer a viable means to assist patients in managing their health conditions. However, the challenge of ensuring their widespread adoption and adherence persists. This study responds to this need by developing a patient-centered digital health management app, incorporating patient preferences to enhance usability and effectiveness, ultimately aiming to improve patient outcomes and quality of life. ObjectiveThis research aims to develop a digital health self-management app specifically for patients experiencing postviral fibromyalgia-like symptoms. By prioritizing patient preferences and engagement through the app’s design and functionality, the study intends to facilitate better self-management practices and improve adherence. MethodsUsing an exploratory study design, the research used patient preference surveys and usability testing as primary tools to inform the development process of the digital health solution. We gathered and analyzed patients’ expectations regarding design features, content, and usability to steer the iterative app development. ResultsThe study uncovered crucial insights from patient surveys and usability testing, which influenced the app’s design and functionality. Key findings included a preference for a symptom list over an automated chatbot, a desire to report on a moderate range of symptoms and activities, and the importance of an intuitive onboarding process. While usability testing identified some challenges in the onboarding process, it also confirmed the importance of aligning the app with patient needs to enhance engagement and satisfaction. ConclusionsIncorporating patient feedback has been a significant factor in the development of the digital health app. Challenges encountered with user onboarding during usability testing have highlighted the importance of this process for user adoption. The study acknowledges the role of patient input in developing digital health technologies and suggests further research to improve onboarding procedures, aiming to enhance patient engagement and their ability to manage digital health resources effectively. International Registered Report Identifier (IRRID)RR2-10.2196/32193

Abstract Background In Switzerland, rituximab (RTX) is licenced for the treatment of rheumatoid arthritis (RA) and ANCA-associated vasculitis (AAV) but is frequently used off-label to treat other auto-immune diseases (AID), especially connective tissue diseases (CTD). We aimed to characterise the use of RTX in AID in a real-life Swiss setting and compare RTX retention rates and safety outcomes between patients treated for RA, CTD and AAV. Methods A retrospective cohort study of patients who started RTX in the Rheumatology Department for RA or AID. The RTX retention rate was analysed using Kaplan–Meier survival curves. Occurrences of serious adverse events (SAE), low IgG levels and anti-drug antibodies (ADA) were reported. Results Two hundred three patients were treated with RTX: 51.7% had RA, 29.6% CTD, 9.9% vasculitis and 8.9% other AIDs. The total observation time was 665 patient-years. RTX retention probability at 2 years (95%CI) was similar for RA and CTD 0.65 (0.55 to 0.73), 0.60 (0.47 to 0.72) and lower for vasculitis 0.25 (0.09 to 0.45). Survival curves for RTX retention matched closely (p = 0.97) between RA and CTD patients but were lower for patients with vasculitis due to a higher percentage of induced remission. Patients with vasculitis (95%) and CTD (75%) had a higher rate of concomitant glucocorticoid use than RA (60%). Moderate to severe hypogammaglobulinaemia was observed more frequently in patients with vasculitis (35%) than with RA (13%) or CTD (9%) and was associated with an increased risk of presenting a first infectious SAE (HR 2.01, 95% CI 1.04 to 3.91). The incidence rate of SAE was 23.3 SAE/100 patient-years (36% were infectious). When searched, ADAs were observed in 18% of the patients and were detected in 63% of infusions-related SAE. 10 patients died during RTX treatment and up to 12 months after the last RTX infusion, 50% from infection. Conclusion RTX retention rates are similar for patients with RA and CTD but lower for those with vasculitis due to more frequent remission. Patients treated with RTX for vasculitis present more SAE and infectious SAE than patients with RA and CTD, potentially due to a higher use of concomitant glucocorticoids and the occurrence of hypogammaglobulinaemia.

Objective To characterise the population fulfilling the Assessment of SpondyloArthritis international Society (ASAS) consensus definition of early axial spondyloarthritis (axSpA) and to determine the effectiveness of a first tumour necrosis factor inhibitor (TNFi) in early versus established axSpA in a large observational registry.Methods A total of 3064 patients with axSpA in the Swiss Clinical Quality Management registry with data on duration of axial symptoms were included (≤2 years=early axSpA, N=658; >2 years=established axSpA, N=2406). Drug retention was analysed in patients starting a first TNFi in early axSpA (N=250) versus established axSpA (N=874) with multiple-adjusted Cox proportional hazards models. Adjusted logistic regression analyses were used to determine the achievement of the ASAS criteria for 40% improvement (ASAS40) at 1 year.Results Sex distribution, disease activity, impairments of function and health-related quality of life were comparable between patients with early and established axSpA. Patients with established disease were older, had more prevalent axial radiographical damage and had a higher impairment of mobility. A comparable TNFi retention was found in early versus established disease after adjustment for age, sex, human leucocyte antigen-B27 status, education, body mass index, smoking, elevated C reactive protein and sacroiliac inflammation on MRI (HR 1.05, 95% CI 0.78 to 1.42). The adjusted ASAS40 response was similar in the two groups (OR 1.09, 95% CI 0.67 to 1.78). Results were confirmed in the population fulfilling the ASAS classification criteria.Conclusion Considering the recent ASAS definition of early axSpA, TNFi effectiveness seems comparable in early versus established disease.

Digital transformation has a significant impact on efficiency and quality in hospitals. New solutions can support the management of data overload and the shortage of qualified staff. However, the timely and effective integration of these new digital tools in the healthcare setting poses challenges and requires guidance. The balanced scorecard (BSC) is a managerial method used to translate new strategies into action and measure their impact in an institution, going beyond financial values. This framework enables quicker operational adjustments and enhances awareness of real-time performance from multiple perspectives, including customers, internal procedures, and the learning organization. The aim of this study was to adapt the BSC to the evolving digital healthcare environment, encompassing factors like the recent pandemic, new technologies such as artificial intelligence, legislation, and user preferences. A strategic mapping with identification of corresponding key performance indicators was performed. To achieve this, we employed a qualitative research approach involving retreats, interdisciplinary working groups, and semi-structured interviews with different stakeholders (administrative, clinical, computer scientists) in a rheumatology department. These inputs served as the basis for customizing the BSC according to upcoming or already implemented solutions and to define actionable, cross-level performance indicators for all perspectives. Our defined values include quality of care, patient empowerment, employee satisfaction, sustainability and innovation. We also identified substantial changes in our internal processes, with the electronic medical record (EMR) emerging as a central element for vertical and horizontal digitalization. This includes integrating patient-reported outcomes, disease-specific digital biomarker, prediction algorithms to increase the quality of care as well as advanced language models in order save resources. Gaps in communication and collaboration between medical departments have been identified as a main target for new digital solutions, especially in patients with more than one disorder. From a learning institution's perspective, digital literacy among patients and healthcare professionals emerges as a crucial lever for successful implementation of internal processes. In conclusion, the BSC is a helpful tool for guiding digitalization in hospitals as a horizontally and vertically connected process that affects all stakeholders. Future studies should include empirical analyses and explore correlations between variables and above all input and user experience from patients.

Objectives Treatment response is worse in obese patients with rheumatoid arthritis (RA), including patients on weight-adjusted therapies like infliximab. We aimed to assess the association between body mass index (BMI) and changes in RA disease activity and radiographic progression over time.Methods We included infliximab users with an RA diagnosis in the Swiss Clinical Quality Management in Rheumatic Diseases registry (1997–2020). Two cohorts were defined: (1) starting from their first BMI measurement or disease activity score (DAS28-esr), and (2) from their first BMI measurement or radiographic assessment (Rau score). We evaluated the coefficient and 95% CI of BMI with changes in mean DAS28-esr (cohort 1) and mean Rau scores (a structural joint damage score, cohort 2) using generalised estimation equations, overall and stratified by BMI categories.Results Cohort 1 comprised 412 patients (74% women, mean age 53 years, mean BMI 25). We observed no change in mean DAS28-esr with increasing BMI overall (adjusted coefficient: 0.00, 95% CI −0.02 to 0.02), or in BMI categories. Cohort 2 comprised 187 patients highly alike to those in cohort 1. We observed a significant decrease of 1.05 in mean Rau scores for every increase in BMI unit (adjusted coefficient: −1.05, 95% CI −1.92 to −0.19). Results remained statistically non-significant across BMI categories.Conclusions Our longitudinal investigation suggests that BMI increase may not lead to changes in DAS28-esr in patients receiving infliximab, despite the weight-adapted dose. Yet, there may be a decrease in erosions with increasing weight non-limited to obese patients.

Cycling of biologic or targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) in rheumatoid arthritis (RA) patients due to non-response is a problem preventing and delaying disease control. We aimed to assess and validate treatment response of b/tsDMARDs among clusters of RA patients identified by deep learning. We clustered RA patients clusters at first-time b/tsDMARD (cohort entry) in the Swiss Clinical Quality Management in Rheumatic Diseases registry (SCQM) [1999-2018]. We performed comparative effectiveness analyses of b/tsDMARDs (ref. adalimumab) using Cox proportional hazard regression. Within 15 months, we assessed b/tsDMARD stop due to non-response, and separately a ≥20% reduction in DAS28-esr as a response proxy. We validated results through stratified analyses according to most distinctive patient characteristics of clusters. Clusters comprised between 362 and 1481 patients (3516 unique patients). Stratified (validation) analyses confirmed comparative effectiveness results among clusters: Patients with ≥2 conventional synthetic DMARDs and prednisone at b/tsDMARD initiation, male patients, as well as patients with a lower disease burden responded better to tocilizumab than to adalimumab (hazard ratio [HR] 5.46, 95% confidence interval [CI] [1.76-16.94], and HR 8.44 [3.43-20.74], and HR 3.64 [2.04-6.49], respectively). Furthermore, seronegative women without use of prednisone at b/tsDMARD initiation as well as seropositive women with a higher disease burden and longer disease duration had a higher risk of non-response with golimumab (HR 2.36 [1.03-5.40] and HR 5.27 [2.10-13.21], respectively) than with adalimumab. Our results suggest that RA patient clusters identified by deep learning may have different responses to first-line b/tsDMARD. Thus, it may suggest optimal first-line b/tsDMARD for certain RA patients, which is a step forward towards personalizing treatment. However, further research in other cohorts is needed to verify our results.

Digital biomarkers such as wearables are of increasing interest in monitoring rheumatic diseases, but they usually lack disease specificity. In this study, we apply convolutional neural networks (CNN) to real-world hand photographs in order to automatically detect, extract, and analyse dorsal finger fold lines as a correlate of proximal interphalangeal (PIP) joint swelling in patients with rheumatoid arthritis (RA). Hand photographs of RA patients were taken by a smartphone camera in a standardized manner. Overall, 190 PIP joints were categorized as either swollen or not swollen based on clinical judgement and ultrasound. Images were automatically preprocessed by cropping PIP joints and extracting dorsal finger folds. Subsequently, metrical analysis of dorsal finger folds was performed, and a CNN was trained to classify the dorsal finger lines into swollen versus non-swollen joints. Representative horizontal finger folds were also quantified in a subset of patients before and after resolution of PIP swelling and in patients with disease flares. In swollen joints, the number of automatically extracted deep skinfold imprints was significantly reduced compared to non-swollen joints (1.3, SD 0.8 vs. 3.3, SD 0.49, p < 0.01). The joint diameter/deep skinfold length ratio was significantly higher in swollen (4.1, SD 1.4) versus non-swollen joints (2.1, SD 0.6, p < 0.01). The CNN model successfully differentiated swollen from non-swollen joints based on finger fold patterns with a validation accuracy of 0.84, a sensitivity of 88%, and a specificity of 75%. A heatmap of the original images obtained by an extraction algorithm confirmed finger folds as the region of interest for correct classification. After significant response to disease-modifying antirheumatic drug ± corticosteroid therapy, longitudinal metrical analysis of eight representative deep finger folds showed a decrease in the mean diameter/finger fold length (finger fold index, FFI) from 3.03 (SD 0.68) to 2.08 (SD 0.57). Conversely, the FFI increased in patients with disease flares. In conclusion, automated preprocessing and the application of CNN algorithms in combination with longitudinal metrical analysis of dorsal finger fold patterns extracted from real-world hand photos might serve as a digital biomarker in RA.

Background: Age-related hyperkyphosis is multifactorial and involves alterations of vertebral bone, intervertebral discs (IVD) and paraspinal muscles. The relative contribution of these tissues remains unclear. Here, we compared differences in vertebral bone microarchitecture and IVD thickness between prematurely aging mice with spinal hyperkyphosis and wild type littermates. Methods: Thoracolumbar vertebral columns were dissected from homozygous PolgD257A and age-matched wild type littermates. Micro-computed tomography was performed to quantify cortical and trabecular bone parameters at anterior and posterior portions of T8-L4 vertebrae. In addition, vertebral shape, transaxial facet joint orientation and IVD thickness were quantified. Differences in anterior/posterior ratios between genotypes were compared by Student's t-test and association between vertebral bone and IVD parameters was investigated using Pearson correlation analysis. Results: Hyperkyphotic homozygous mice displayed generalized osteopenia that was more pronounced at the posterior compared with anterior portion of thoracolumbar vertebrae. An increase in the anterior/posterior ratio of trabecular bone parameters was revealed at the thoracolumbar junction (T13-L1). PolgD257A displayed diffuse loss of cortical bone thickness, yet anterior/posterior ratios were unchanged. Despite generalized and regional bone loss, vertebral shape was unaffected. PolGD257A mice showed a 10–20 % reduction of IVD thickness at both thoracic and lumbar levels, with only minimal histopathological changes. IVD thickness was negatively correlated with anterior/posterior ratios of trabecular bone parameters, as well as with more coronally oriented facet joints, but negatively correlated with the anterior/posterior ratio of cortical bone thickness. Conclusions: Aging-induced regional changes of vertebral trabecular and cortical bone did not lead to altered vertebral shape in PolgD257A mice but may indirectly cause hyperkyphosis through reduction of IVD thickness. These findings suggest a limited role for aging-induced bone loss in spinal hyperkyphosis and warrants further research on the involvement of paraspinal muscle degeneration.

In each era we need to balance between being able to provide care with our “technical skill, scientific knowledge, and human understanding” (Harrison's Principles of Internal Medicine, 1950) to the individual patient and simultaneously ensure that our healthcare serves all. With the increasing demand of healthcare by an aging population and the lack of specialists, accessible healthcare within a reasonable time frame is not always guaranteed. E-health provides solutions for current situations where we do not meet our own aims of good healthcare, such as restrictions in access to care and a reduction in care availability by a reducing workforce. In addition, telemedicine offers opportunities to improve our healthcare beyond what is possible by in person visits. However, e-health is often viewed as an deficient version of healthcare of low quality. We disagree with this view. In this article we will discuss how to position e-health in the current situation of healthcare, given the continuing rapid development of digital technologies and the changing needs of healthcare professionals and patients. We will address the evolution of e-health towards connected and intelligent systems and the stakeholders perspective, aiming to open up the discussion on e-Health.

Abstract Background Enthesitis is a hallmark of spondyloarthritis (SpA) with a substantial impact on quality of life. Reports of treatment effectiveness across individual enthesitis sites in real-world patients with axial SpA (axSpA) are limited. We investigated the evolution of enthesitis following tumor necrosis factor inhibitor (TNFi) initiation in axSpA patients, both cumulatively and at specific axial and peripheral sites. Methods AxSpA patients in the Swiss Clinical Quality Management Registry were included if they initiated a TNFi, had an available Maastricht Ankylosing Spondylitis Enthesitis Score, modified to include the plantar fascia (mMASES, 0–15), at start of treatment and after 6 and/or 12 months and ≥12 months follow-up. Logistic regression models were utilized to analyze explanatory variables for enthesitis resolution. Results Overall, 1668 TNFi treatment courses (TCs) were included, of which 1117 (67%) had active enthesitis at baseline. Reduction in mMASES at the 6- and 12-month timepoints was experienced in 72% and 70% of TCs, respectively. Enthesitis resolution at 6/12 months occurred in 37.9%/43.0% of all TNFi TCs and 40.7%/50.9% of first TNFi TCs. At 6 months, a significant reduction in the frequency of enthesitis was observed at all sites, except for the Achilles tendon and plantar fascia among first TNFi TCs, while at 12 months, reduction was significant at all sites in both TC groups. Enthesitis resolved in 60.3–77% across anatomical sites, while new incident enthesitis occurred in 4.0–13.5% of all TNFi TCs at 12 months. Both baseline and new-incident enthesitis occurred most frequently at the posterior superior iliac spine and the fifth lumbar spinous process. Younger age and lower mMASES at baseline were predictors of complete enthesitis resolution, while female sex and second- or later-line TNFi treatment were associated with persistence of enthesitis at 12 months. Conclusion In real-world axSpA patients treated with a TNFi, enthesitis improved in the majority of patients across all anatomical sites. Significant improvement at the Achilles and plantar fascia entheses was observed only at 12 months. Complete and site-specific enthesitis resolution occurred in ≥40% and ≥60% of TCs evaluated at 12 months, with a low incidence of new site-specific enthesitis. Trial registration Not applicable.

Summary: Background: Cartilage damage in inflammatory arthritis is attributed to inflammatory cytokines and pannus infiltration. Activation of the coagulation system is a well known feature of arthritis, especially in rheumatoid arthritis (RA). Here we describe mechanisms by which fibrin directly mediates cartilage degeneration. Methods: Fibrin deposits were stained on cartilage and synovial tissue of RA and osteoarthritis (OA) patients and in murine adjuvant-induced arthritis (AIA) in wild-type or fibrinogen deficient mice. Fibrinogen expression and procoagulant activity in chondrocytes were evaluated using qRT-PCR analysis and turbidimetry. Chondro-synovial adhesion was studied in co-cultures of human RA cartilage and synoviocytes, and in the AIA model. Calcific deposits were stained in human RA and OA cartilage and in vitro in fibrinogen-stimulated chondrocytes. Findings: Fibrin deposits on cartilage correlated with the severity of cartilage damage in human RA explants and in AIA in wild-type mice, whilst fibrinogen deficient mice were protected. Fibrin upregulated Adamts5 and Mmp13 in chondrocytes. Chondro-synovial adhesion only occurred in fibrin-rich cartilage areas and correlated with cartilage damage. In vitro, autologous human synoviocytes, cultured on RA cartilage explants, adhered exclusively to fibrin-rich areas. Fibrin co-localized with calcification in human RA cartilage and triggered chondrocyte mineralization by inducing pro-calcification genes (Anx5, Pit1, Pc1) and the IL-6 cytokine. Similar fibrin-mediated mechanisms were observed in OA models, but to a lesser extent and without pseudo-membranes formation. Interpretation: In arthritis, fibrin plaques directly impair cartilage integrity via a triad of catabolism, adhesion, and calcification. Funding: None.

Objective: To investigate the associations between bariatric surgery and hip or knee arthroplasty, and secondary care hip or knee osteoarthritis (OA). Methods: We performed cohort studies using data from Swedish nationwide healthcare registries. Patients aged 18–79 years who underwent bariatric surgery between 2006 and 2019 were matched on their propensity score (PS) to up to 2 obese patients (“unexposed episodes”) in risk-set sampling. After a 1-year run-in period, episodes were followed in an “as-treated” approach. Using Cox proportional hazard regression, we calculated hazard ratios (HR) with 95% confidence intervals (CIs) of hip or knee arthroplasty overall and in subgroups of age, sex, joint location, arthroplasty type, bariatric surgery type, and by duration of follow-up if proportional hazard assumptions were violated. In a secondary cohort, we assessed the outcome incident secondary care hip or knee osteoarthritis (OA). Results: Among 39‘392 bariatric surgery episodes when compared to 61’085 ​PS-matched unexposed episodes (47′594 unique patients), the risk of hip or knee arthroplasty was strongest increased within the first three years of follow-up (HR 1.79, 95% CI 1.56–2.07), decreased thereafter, but remained elevated throughout follow-up. In a secondary cohort of 37′929 exposed when compared to 58′600 ​PS-matched unexposed episodes, the risk of hip or knee osteoarthritis was decreased (HR 0.84, 95% CI 0.79–0.90). Conclusion: Bariatric surgery is associated with increased risks of hip or knee arthroplasty, but also with decreased risks of secondary care OA. This contradiction supports the hypothesis that bariatric surgery may act as an enabler for hip or knee arthroplasty.

PurposeNerve Growth Factor (NGF) is a pivotal mediator of chronic pain and plays a role in bone remodelling. Through its high affinity receptor TrkA, NGF induces substance P (SP) as key downstream mediator of pain and local inflammation. Here we analysed NGF, TrkA and SP tissue distribution in facet joint osteoarthritis (FJOA), a major cause of chronic low back pain.MethodsFJOA specimens (n=19) were harvested from patients undergoing intervertebral fusion surgery. Radiologic grading of FJOA and spinal stenosis, followed by immunohistochemistry for NGF, TrkA and SP on consecutive tissue sections, was performed in ten specimens. Explant cultures (n=9) were used to assess secretion of NGF, IL-6, and SP by FJOA osteochondral tissues under basal and inflammatory conditions.ResultsNGF was predominantly expressed in damaged cartilaginous tissues (80%), occasionally in bone marrow (20%), but not in osteochondral vascular channels. NGF area fraction in cartilage was not associated with the extent of proteoglycan loss or radiologic FJOA severity. Consecutive sections showed that NGF and SP expression was localized at structurally damaged cartilage, in absence of TrkA expression. SP and TrkA were expressed in subchondral bone marrow in both presence and absence of NGF. Low level NGF, but not SP secretion, was detected in four out of eighteen FJOA explants under both basal or inflammatory conditions (n=2 each).ConclusionNGF is associated with SP expression and structural cartilage damage in osteoarthritic facet joints, but not with radiologic disease severity. NGF tissue distribution in FJOA differs from predominant subchondral bone expression reported for knee OA.

Objectives To identify differing patient characteristics at the time of stop and restart of biological or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in rheumatoid arthritis (RA), stratified by stop reason.Design Explorative descriptive cohort study.Setting Swiss Clinical Quality Management in Rheumatic Diseases (1999–2018).Participants Patients with RA who stopped their first b/tsDMARD.Outcome measures We assessed patient characteristics at b/tsDMARD stop and restart, stratified by stop reason (non-response, adverse event, remission, other).Results Among 2526 eligible patients, most patients (38%) stopped their b/tsDMARD due to non-response. At treatment stop, most characteristics did not differ by stop reason, yet some differed significantly (p

BackgroundPost–COVID-19 syndrome, also referred as “long covid,” describes persisting symptoms after SARS-CoV-2 infection, including myalgia, fatigue, respiratory, or neurological symptoms. Objective symptoms are often lacking, thus resembling a fibromyalgia-like syndrome. Digital therapeutics have shown efficiency in similar chronic disorders such as fibromyalgia, offering specific disease monitoring and interventions such as cognitive behavioral therapy or physical and respiratory exercise guidance. ObjectiveThis protocol aims to study the requirements and features of a new mobile health (mHealth) app among patients with fibromyalgia-like post–COVID-19 syndrome in a clinical trial. MethodsWe created a web application prototype for the post–COVID-19 syndrome called “POCOS,” as a web-based rehabilitation tool aiming to improve clinical outcomes. Patients without organ damage or ongoing inflammation will be included in the study. App use will be assessed through user experience questionnaires, focus groups, and clinical data analysis. Subsequently, we will analyze cross-sectional and longitudinal clinical data. ResultsThe developed mHealth app consists of a clinically adapted app interface with a simplified patient-reported outcome assessment, monitoring of medical interventions, and disease activity as well as web-based instructions for specific physical and respiratory exercises, stress reduction, and lifestyle instructions. The enrollment of participants is expected to be carried out in November 2021. ConclusionsUser experience plays an important role in digital therapeutics and needs to be clinically tested to allow further improvement. We here describe this process for a new app for the treatment of the fibromyalgia-like post–COVID-19 syndrome and discuss the relevance of the potential outcomes such as natural disease course and disease phenotypes. International Registered Report Identifier (IRRID)PRR1-10.2196/32193

Abstract Background/purpose Elevated levels of C-reactive protein (CRP) in systemic sclerosis (SSc) have been linked to early inflammatory stages of the disease. This study has been designed to investigate CRP levels longitudinally in a cohort of SSc patients and to correlate these findings with comorbidities and disease characteristics. Methods In this retrospective study, patients with SSc treated at the outpatient clinic of the Department of Rheumatology and Clinical Immunology, University Medical Center Freiburg, were analyzed. Only patients with at least three consecutive visits and at least 1 year follow-up were included in this study. CRP serum levels were measured at every visit and categorized as positive if CRP concentrations were ≥ 5 mg/l. Subjects with elevated CRP levels at more than 80% of visits were defined as inflammatory SSc. The longitudinal CRP profiles were correlated with disease characteristics and comorbidities. Results A total of 1815 consecutive visits of 131 SSc patients were analyzed. Over the observed time span (7.6 (1.0–19.5) years), 18.3% (n = 24) of patients had continuously elevated CRP levels (inflammatory SSc), whereas in 29% (n = 38), CRP levels were always in the normal range. There was no association between disease duration and CRP levels at first visit. Inflammatory SSc was associated with male gender (p = 0.022), anti-Scl-70 antibodies (p = 0.009), diffuse cutaneous SSc (p = 0.036), pulmonary fibrosis (p

BackgroundDeep neural networks learn from former experiences on a large scale and can be used to predict future disease activity as potential clinical decision support. AdaptiveNet is a novel adaptive recurrent neural network optimized to deal with heterogeneous and missing clinical data.ObjectiveWe investigate AdaptiveNet for the prediction of individual disease activity in patients from a rheumatoid arthritis (RA) registry.MethodsDemographic and disease characteristics from over 9500 patients and 65.000 visits from the Swiss Quality Management (SCQM) database were used to train and evaluate the network. Patient characteristics, clinical and patient reported outcomes, laboratory values and medication were used as input features. DAS28-BSR served as a target to predict active RA and future numeric individual disease activity by classification and regression.ResultsAdaptiveNet predicted active disease defined as DAS28-BSR >2.6 at the next visit with an overall accuracy of 75.6% (SD +- 0.7%) and a sensitivity and specificity of 84.2% (SD +- 1.6%) and 61.5% (SD +- 3.6%), respectively. Prediction performance was significantly higher in patients with a disease duration >3 years and positive rheumatoid factor. Regression allowed forecasting individual DAS28-BSR values with a mean squared error (MSE) of 0.9 (SD +- 0.05). This corresponds to a 8% deviation between estimated and real DAS28-BSR values. Compared to linear regression, random forest and support vector machines, AdaptiveNet showed an increased performance of over 7% in MSE. Medication played a minor role in the prediction of RA disease activity.ConclusionAdaptiveNet has a superior capacity to predict numeric RA disease activity compared to classical machine learning architectures. All investigated models had limitations in low specificity.

Osteoarthritis (OA) is a progressive joint disease that is strongly associated with calcium-containing crystal formation (mineralization) by chondrocytes leading ultimately to cartilage calcification. However, this calcification process is poorly understood and treatments targeting the underlying disease mechanisms are lacking. The CD11b/CD18 integrin (Mac-1 or αMβ2), a member of the beta 2 integrin family of adhesion receptors, is critically involved in the development of several inflammatory diseases, including rheumatoid arthritis and systemic lupus erythematosus. We found that in a collagen-induced arthritis, CD11b-deficient mice exhibited increased cartilage degradation compared to WT control animals. However, the functional significance of CD11b integrin signaling in the pathophysiology of chondrocytes remains unknown. CD11b expression was found in the extracellular matrix and in chondrocytes in both healthy and damaged human and murine articular cartilage. Primary murine CD11b KO chondrocytes showed increased mineralization when induced in vitro by secondary calciprotein particles (CPP) and quantified by Alizarin Red staining. This increased propensity to mineralize was associated with an increased alkaline phosphatase (Alp) expression (measured by qRT-PCR and activity assay) and an enhanced secretion of the pro-mineralizing IL-6 cytokine compared to control wild-type cells (measured by ELISA). Accordingly, addition of an anti-IL-6 receptor antibody to CD11b KO chondrocytes reduced significantly the calcification and identified IL-6 as a pro-mineralizing factor in these cells. In the same conditions, the ratio of qRT-PCR expression of collagen X over collagen II, and that of Runx2 over Sox9 (both ratio being indexes of chondrocyte hypertrophy) were increased in CD11b-deficient cells. Conversely, the CD11b activator LA1 reduced chondrocyte mineralization, Alp expression, IL-6 production and collagen X expression. In the meniscectomy (MNX) model of murine knee osteoarthritis, deficiency of CD11b led to more severe OA (OARSI scoring of medial cartilage damage in CD11b: 5.6 ± 1.8, in WT: 1.2 ± 0.5, p < 0.05, inflammation in CD11b: 2.8 ± 0.2, in WT: 1.4 ± 0.5). In conclusion, these data demonstrate that CD11b signaling prevents chondrocyte hypertrophy and chondrocyte mineralization in vitro and has a protective role in models of OA in vivo.

Background and Objectives: Knee osteoarthritis (OA) is a frequent cause of pain, functional limitations, and a common reason for surgical treatment, such as joint replacement. Conservative therapies can reduce pain and improve function; thus, delaying or even preventing surgical intervention. Various individual conservative therapies show benefits, but combination therapies remain underexplored. The aim of this prospective case-study was to assess the effect of a conservative combination therapy in patients with painful varus knee OA. Materials and Methods: With strong inclusion and exclusion criteria, nine patients with painful varus knee OA (mean age 56 years (range 51–63 years) were selected and monitored over six months, using the following clinical outcome scores: pain visual analog scale (VAS), Western Ontario and McMaster Universities osteoarthritis index (WOMAC score), short-form–36 items (SF-36) quality of life score, and the sports frequency score. All patients received a standardized conservative trio-therapy with varus-reducing hindfoot shoe-insoles with a lateral hindfoot wedge, oral viscosupplementation, and physiotherapy for six months. Results: The pain was reduced significantly from initial VAS values of 5.4 points (range, 3–10) to values of 0.6 points (range, 0–3; p < 0.01), at the end of treatment. After six months, seven out of nine patients reported no pain at all (VAS 0). The WOMAC score improved significantly, from initial values of 35 (range, 10–56) to values of 2 (range, 0–9; p < 0.01). The SF-36 score showed significant improvement after six months in all four domains of physical health (p < 0.01) and in two of the four domains of mental health (p < 0.05). The sports frequency score increased by at least one level in six out of nine patients after six months. Conclusions: The conservative trio-therapy in patients with varus knee OA showed positive initial clinical results: less pain, higher function, better quality of life, and higher sport activity. Further studies are required to evaluate the long-term effect.

OBJECTIVE To characterise adherence and treat-to-target (T2T) strategy in gout patients within a Swiss tertiary hospital. METHODS Consecutive presenting patients with proven gout were prospectively included in this cohort. Symptoms, comorbidities, medication and laboratory values were assessed (during hospitalisation and at planned 3- and 12-month follow-up assessments). RESULTS 116 patients (98 men) with a mean age of 67 (range 23–94 years) were included, 74% of whom had active arthritis. Comorbidities were frequent: hypertension, renal impairment, and obesity were present in 72, 55 and 35% of patients, respectively. Thirty-five percent of patients received urate-lowering treatment at inclusion. Only 62 and 50% attended the 3- and 12-month follow-up. The target serum uric acid level of

Thomas HügleDepartment of Rheumatology, Felix-Platter-Spital, University of Basel, Basel, SwitzerlandAbstract: Interstitial lung disease (ILD) and lung fibrosis are characterized by different grades of fibrosis and inflammation. Persistent low-grade inflammation is believed to play a major pathogenic role, leading to an imbalance of cytokines, growth factors, and tissue proteinases. Recruited monocytes and macrophages play a pivotal role through their cytokine expression and possibly differentiation into fibrocytes, pericytes, or myofibroblasts. Atypical bacterial infections can cause ILD, although not usually in the form of usual interstitial pneumonia. On the other hand, bacterial colonization is frequently encountered in patients with chronic fibrotic lung disorders, and patients regularly undergo antibacterial treatment. As demonstrated in patients with diffuse panbronchiolitis and other chronic respiratory disorders, treatment with macrolides can be beneficial. This is partly explained by their antimicrobial effects but, for macrolides, immunomodulatory properties have been identified which might also be beneficial in patients with ILD or lung fibrosis. This article reviews the immunology of lung fibrogenesis and putative implications of macrolides for reinstallation of tolerance.Keywords: lung fibrosis, inflammation, pneumonia

Subchondral bone tissue plays a key role in the initiation and progression of human and experimental osteoarthritis and has received considerable interest as a treatment target. Elevated bone turnover and remodeling leads to subchondral bone sclerosis that is characterized by an increase in bone material that is less mineralized. The aim of this study was to investigate whether perturbations in subchondral bone-resident progenitor cells might play a role in aberrant bone formation in osteoarthritis. Colony formation assays indicated similar clonogenicity of progenitor cells from non-sclerotic and sclerotic subchondral trabecular bone tissues of osteoarthritic knee and hip joints compared with controls from iliac crest bone. However, the osteogenic potential at the clonal level was approximately two-fold higher in osteoarthritis than controls. An osteogenic differentiation assay indicated an efficient induction of alkaline phosphatase activity but blunted in vitro matrix mineralization irrespective of the presence of sclerosis. Micro-computed tomography and histology demonstrated the formation of de novo calcified tissues by osteoblast-like cells in an ectopic implantation model. The expression of bone sialoprotein, a marker for osteoblast maturation and mineralization, was significantly less in sclerotic progenitor cells. Perturbation of resident progenitor cell function is associated with subchondral bone sclerosis and may be a treatment target for osteoarthritis.

Mast cells are tissue-bound cells of the innate immune system which are well known for immunoglobuline (Ig)E-triggered degranulation in allergic reactions. More recently, an important role of mast cells has been described in chronic inflammatory and autoimmune disorders which are often associated with fibrosis or sclerosis. Innate immune receptors such as Fc-, toll-like- or NOD-like receptors stimuli can trigger mast cell degranulation and enhance immunological danger signals. Whereas fulminant degranulation of mast cell vesicles is observed in anaphylaxis, piecemeal degranulation or transgranulation are mechanisms for a slower release of their granula. A cocktail of cytokines, growth factors and proteoglycans is produced and stored in granula of mast cells. Mast cells are a substantial reservoir of both preformed inflammatory factors (i.e., TNF-alpha and IL-17) and factors that can trigger a profibrotic, Th-2–polarised inflammation (i.e., IL-4 and IL-10). In systemic sclerosis, mast cell vesicles are the main source of transforming growth factor (TGF)-beta. Cell-to-cell contact between mast cells and fibroblasts occurs in the affected tissue, supporting the hypothesis that transgranulation might be an important mechanism in fibrosis. The direct release of proteoglycans such as hyaluronic acid into the interstitial space is a further stimulus for matrix remodelling. Mast cell hyperactivity has also been demonstrated in primary fibrotic disorders such as lung, cardiac or renal fibrosis. The exact trigger for mast cell degranulation however is not known. Notwithstanding, at a very early time point of fibrosis, mast cell inhibition by stabilisers or blockage of the tyrosine kinase receptor c-kit by masitinib could be a therapeutic option.

Synovial biopsies of the knee joint are commonly performed arthroscopically with the patient under full or regional anesthesia. To overcome the effort, costs, and potential risks of surgery, we developed an office-based technique for retrograde synovial biopsy using a designated novel biopsy forceps. Using this technique, no arthroscopic or radiologic control is needed to perform rapid synovial biopsies of the knee joint. Concomitant aspiration of synovial fluid can be performed. A technical description of the procedure is given.

Today, the most frequent chronic musculoskeletal disorder and the leading cause of disability in the elderly is osteoarthritis (OA). Approximately 43 million people in the United States and 15% of the world population are affected. Due to demographic changes, the incidence of OA is rapidly increasing, leading to an ascending socioeconomical and personal burden. Despite the exact cause of OA remains unknown, the pathogenic role of biomechanical dysfunction in OA is well established. For weight-bearing joints altered loading mechanisms, increased mechanical forces and changed biomechanics are significant contributing factors for initiation and progression of OA. Thus, OA is a disease of the whole joint, including muscles, tendons, ligaments, synovium and bone. This review focuses on the influence of biomechanics on the pathogenesis and progression of OA. We notably illustrate the pathological bioreactivity of soft tissues, subchondral bone and joint inflammation. Procedures, conservative or surgical, which actively alter the biomechanics of the lower limb, are promising strategies to treat symptoms as well as to influence disease progression in OA.

Osteoarthritis (OA) is a major health burden of our time. Age is the most prominent risk factor for the development and progression of OA. The mechanistic influence of aging on OA has different facets. On a molecular level, matrix proteins such as collagen or proteoglycans are modified, which alters cartilage function. Collagen cross-linking within the bone results in impaired plasticity and increased stiffness. Synovial or fat tissue, menisci but also ligaments and muscles play an important role in the pathogenesis of OA. In the elderly, sarcopenia or other causes of muscle atrophy are frequently encountered, leading to a decreased stability of the joint. Inflammation in form of cellular infiltration of synovial tissue or subchondral bone and expression of inflammatory cytokines is more and more recognized as trigger of OA. It has been demonstrated that joint movement can exhibit anti-inflammatory mechanisms. Therefore physical activity or physiotherapy in the elderly should be encouraged, also in order to increase the muscle mass. A reduced stem cell capacity in the elderly is likely associated with a decrease of repair mechanisms of the musculoskeletal system. New treatment strategies, for example with mesenchymal stem cells (MSC) are investigated, despite clear evidence for their efficacy is lacking.

BACKGROUND: Circulating monocytes are a highly plastic and functionally heterogeneic cell type with an activated phenotype in patients with systemic sclerosis (SSc). CD14(+) monocytes have the potential to differentiate into extra-cellular matrix (ECM) producing cells, possibly participating in fibrogenesis. AIM: To study the effect of GM-CSF, IL-4 and endothelin -1 (ET-1) alone or in combination on monocyte differentiation into myofibroblasts. METHODS: CD14(+) cells were isolated from peripheral blood from 14 SSc patients and healthy controls by positive selection and incubated with different combinations of GM-CSF, IL-4 and ET-1 for 14 days. Type-1 collagen and α-SMA were detected by Western blot, qPCR and confocal microscopy. HLA-DR, CD11c and CD14 expression was analysed by flow cytometry. A collagen gel contraction assay was performed for functional myofibroblast assessment. RESULTS: GM-CSF both induced collagen and α-SMA expression after 14 days. ET-1 further increased GM-CSF-induced collagen expression in a dose dependent manner up to 30-fold. IL-4/GM-CSF combination leads to a more DC-like phenotype of monocytes associated with reduced collagen and α-SMA expression compared to GM-CSF alone. Collagen and α-SMA expression was higher in monocytes from SSc patients and monocytes were more prone to obtain a spindle form. In contrast to controls, ET-1 and IL-4 alone were sufficient to induce α-SMA expression in monocytes from SSc patients. Despite the induction of α-SMA expression, monocyte-derived myofibroblasts only had a moderate capability of contraction in functional analyses. CONCLUSION: SSc monocytes display increased maturation towards myofibroblasts demonstrated by their phenotype and α-SMA expression when compared to monocytes from healthy controls, however only with minor functional contraction properties.