SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models.

There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming. We demonstrate the tool through the reproduction and visualisation of published models and show simulation results using code generation interfaced directly into SpineCreator. As a unique application for the graphical creation of neural networks, SpineCreator represents an important step forward for neuronal modelling

Monocytes induce STAT3 activation in human mesenchymal stem cells to promote osteoblast formation

A major therapeutic challenge is how to replace bone once it is lost. Bone loss is a characteristic of chronic inflammatory and degenerative diseases such as rheumatoid arthritis and osteoporosis. Cells and cytokines of the immune system are known to regulate bone turnover by controlling the differentiation and activity of osteoclasts, the bone resorbing cells. However, less is known about the regulation of osteoblasts (OB), the bone forming cells. This study aimed to investigate whether immune cells also regulate OB differentiation. Using in vitro cell cultures of human bone marrow-derived mesenchymal stem cells (MSC), it was shown that monocytes/macrophages potently induced MSC differentiation into OBs. This was evident by increased alkaline phosphatase (ALP) after 7 days and the formation of mineralised bone nodules at 21 days. This monocyte-induced osteogenic effect was mediated by cell contact with MSCs leading to the production of soluble factor(s) by the monocytes. As a consequence of these interactions we observed a rapid activation of STAT3 in the MSCs. Gene profiling of STAT3 constitutively active (STAT3C) infected MSCs using Illumina whole human genome arrays showed that Runx2 and ALP were up-regulated whilst DKK1 was down-regulated in response to STAT3 signalling. STAT3C also led to the up-regulation of the oncostatin M (OSM) and LIF receptors. In the co-cultures, OSM that was produced by monocytes activated STAT3 in MSCs, and neutralising antibodies to OSM reduced ALP by 50%. These data indicate that OSM, in conjunction with other mediators, can drive MSC differentiation into OB. This study establishes a role for monocyte/macrophages as critical regulators of osteogenic differentiation via OSM production and the induction of STAT3 signalling in MSCs. Inducing the local activation of STAT3 in bone cells may be a valuable tool to increase bone formation in osteoporosis and arthritis, and in localised bone remodelling during fracture repair

Multi-color Molecular Visualization of Signaling Proteins Reveals How C-Terminal Src Kinase Nanoclusters Regulate T Cell Receptor Activation

Elucidating the mechanisms that controlled T cell activation requires visualization of the spatial organization of multiple proteins on the submicron scale. Here, we use stoichiometrically accurate, multiplexed, singlemolecule super-resolution microscopy (DNA-PAINT) to image the nanoscale spatial architecture of the primary inhibitor of the T cell signaling pathway, Csk, and two binding partners implicated in its membrane association, PAG and TRAF3. Combined with a newly developed co-clustering analysis framework, we find that Csk forms nanoscale clusters proximal to the plasma membrane that are lost post-stimulation and are re-recruited at later time points. Unexpectedly, these clusters do not co-localize with PAG at the membrane but instead provide a ready pool of monomers to downregulate signaling. By generating CRISPR-Cas9 knockout T cells, our data also identify that a major risk factor for autoimmune diseases, the protein tyrosine phosphatase non-receptor type 22 (PTPN22) locus, is essential for Csk nanocluster re-recruitment and for maintenance of the synaptic PAG population

Time-independent disease state identification defines distinct trajectories determined by localised vs systemic inflammation in patients with early rheumatoid arthritis

\ua9 2025 The Author(s)Objectives: Patients with rheumatoid arthritis (RA) display different trajectories towards improvement of disease. We aimed to disentangle the heterogeneity of RA disease trajectories from the first clinical visit onwards using graph-based pseudotime analysis. Methods: We studied early patients with RA over 1.5 years in 2 data sets: Leiden (Netherlands), n = 1237, with 5017 visits, and Towards a Cure for Early Rheumatoid Arthritis (TACERA) (United Kingdom), n = 243, with 750 visits. We created a pipeline for time-independent clustering of clinical and haematologic features to identify disease states. Sequence analyses of these states defined the trajectories. We studied the predictability of the trajectories with baseline features. Results: Clustering identified 8 disease states with localised inflammation (joints) and systemic inflammation (erythrocyte sedimentation rate [ESR] or leucocytes) as the main discriminating factors. The disease state sequences consisted of 4 trajectories, which we independently replicated in TACERA: A, high ESR; B, rapid progression from many inflamed joints towards remission; C, high leucocytes; and D, many inflamed joints with poor prognosis. Systemic vs local inflammation patterns showed moderate predictability at baseline (sensitivity of 71% and precision of 0.73 for trajectory A, although lower precision of 0.52 for trajectory B), while other trajectories were less predictable. Trajectories C and D had strong resemblance with B at baseline but deteriorated into less favourable trajectories. Patients in trajectory A were more often female and on average older. The trajectories were not explained by time till disease-modifying antirheumatic drug, baseline disease activity, or symptom duration. The suboptimal trajectories coincided with worse patient-reported outcomes, even when the inflammation was mainly systemic. Conclusions: We identified 4 distinct trajectories in early RA, differentiating RA into localised vs systemic inflammation. Our results highlight potential differences in disease pathology and opportunities for further targeted treatment. Inevitably, patterns without linkage to our selected features could not be detected

Optimizing treatment with tumour necrosis factor inhibitors in rheumatoid arthritis—a proof of principle and exploratory trial: is dose tapering practical in good responders?

Objectives: RA patients receiving TNF inhibitors (TNFi) usually maintain their initial doses. The aim of the Optimizing Treatment with Tumour Necrosis Factor Inhibitors in Rheumatoid Arthritis trial was to evaluate whether tapering TNFi doses causes loss of clinical response. Methods: We enrolled RA patients receiving etanercept or adalimumab and a DMARD with DAS28 under 3.2 for over 3 months. Initially (months 0-6) patients were randomized to control (constant TNFi) or two experimental groups (tapering TNFi by 33 or 66%). Subsequently (months 6-12) control subjects were randomized to taper TNFi by 33 or 66%. Disease flares (DAS28 increasing ⩾0.6 with at least one additional swollen joint) were the primary outcome. Results: Two hundred and forty-four patients were screened, 103 randomized and 97 treated. In months 0-6 there were 8/50 (16%) flares in controls, 3/26 (12%) with 33% tapering and 6/21 (29%) with 66% tapering. Multivariate Cox analysis showed time to flare was unchanged with 33% tapering but was reduced with 66% tapering compared with controls (adjusted hazard ratio 2.81, 95% CI: 0.99, 7.94; P = 0.051). Analysing all tapered patients after controls were re-randomized (months 6-12) showed differences between groups: there were 6/48 (13%) flares with 33% tapering and 14/39 (36%) with 66% tapering. Multivariate Cox analysis showed 66% tapering reduced time to flare (adjusted hazard ratio 3.47, 95% CI: 1.26, 9.58; P = 0.016). Conclusion: Tapering TNFi by 33% has no impact on disease flares and appears practical in patients in sustained remission and low disease activity states. Trail registration: EudraCT, https://www.clinicaltrialsregister.eu, 2010-020738-24; ISRCTN registry, https://www.isrctn.com, 28955701