Biology subjects

Shenker, N.

Publications and source records attributed to Shenker, N..

5 recordsLinked to original sources

bioRxiv2026

Circulating pre-osteoclasts are primed for osteoclast fate and synovial tissue homing in psoriatic arthritis.

Psoriatic arthritis (PsA) is a complex immune-mediated inflammatory disease with heterogenous clinical features. Osteoclasts have a unique ability to destroy bone, playing key roles in both healthy bone turnover and pathological erosions in arthritis. They are believed to arise from monocytic precursors migrating to inflamed synovial tissue, though the identity of this precursor in humans has remained elusive. Here, we sought to determine whether monocytes home to psoriatic joints and their phenotype. We find that monocytes are recruited to inflamed joints in PsA but not uninvolved or healthy joints, and identify a pre-osteoclast (preOC) cell state derived from classical monocytes. PreOC are transcriptionally distinct from classical monocytes, are enriched for NFACT1, the master regulator of osteoclastogenesis, and form multinucleated osteoclasts in vitro without exogenous RANKL. They are expanded in the circulation of donors with active treatment naive PsA, compared to both healthy controls and those with cutaneous psoriasis only. Finally, using a customised spatial transcriptomics workflow, we identified these cells within human synovial tissue, and radiolabelling confirmed their recruitment from the circulation. These findings highlight the role of systemic immune priming in macrophage pathophysiology.

immunology↗

bioRxiv2024

Enhanced behavioural and neural sensitivity to punishments in chronic pain and fatigue

Chronic pain and fatigue in musculoskeletal disease contribute significantly to disability, and recent studies suggest an association with reduced motivation and excessive fear avoidance. In this behavioural neuroimaging study in chronic inflammatory arthritis participants and healthy controls, we aimed to identify the specific behavioral and neural changes associated pain and fatigue during reward and loss decision-making. Computational modeling of behaviour identified a parametric signature, characterized most notably by increased punishment sensitivity. This signature is distinct from patterns previously reported in psychiatric conditions and it aligns with predictions of mechanistic models of chronic pain such as the fear avoidance model. Neural activity associated with the punishment prediction error was enhanced in the right posterior insular cortex, putamen, pallidum, and dorsolateral prefrontal cortex. Functional network connectivity analysis showed that insula centrality correlated with subjective reports of fatigue and pain. Overall, the findings show that pain and fatigue in chronic pain relate to objective behavioural changes, and can be mapped to a specific pattern of activity in brain circuits of motivation and decision-making.

neuroscience↗

bioRxiv2019

Sub-Optimal Learning of Tactile-Spatial Predictions in Patients with Complex Regional Pain Syndrome

In Complex Regional Pain Syndrome (CRPS), tactile sensory deficits have motivated the therapeutic use of sensory discrimination training. However, the hierarchical organisation of the brain is such that low-level sensory processing can be dynamically influenced by higher-level knowledge, e.g. knowledge learnt from statistical regularities in the environment. It is unknown whether the learning of such statistical regularities is impaired in CRPS. Here, we employed a hierarchical Bayesian model of predictive coding to investigate statistical learning of tactile-spatial predictions in CRPS. Using a sensory change-detection task, we manipulated bottom-up (spatial displacement of a tactile stimulus) and top-down (probabilistic structure of occurrence) factors to estimate hierarchies of prediction and prediction error signals, as well as their respective precisions or reliability. Behavioural responses to spatial changes were influenced by both the magnitude of spatial displacement (bottom-up) and learnt probabilities of change (top-down). The Bayesian model revealed that patients predictions (of spatial displacements) were found to be less precise, deviating further from the ideal (statistical optimality) compared to healthy controls. This imprecision was less context-dependent, i.e. more enduring across changes in probabilistic context and less finely-tuned to statistics of the environment. This caused greater precision on prediction errors, resulting in predictions that were driven more by momentary spatial changes and less by the history of spatial changes. These results suggest inefficiencies in higher-order statistical learning in CRPS. This may have implications for therapies based on sensory re-training whose effects may be more short-lived if success depends on higher-order learning.

neuroscience↗

bioRxiv2017

Classification and characterisation of brain network changes in chronic back pain: a multicenter study.

Chronic pain is a common and often disabling condition, and is thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. Here, we investigated brain network architecture using resting state fMRI data collected from chronic back pain patients in UK and Japan (41 patients, 56 controls). Using a machine learning approach (support vector machine), we found that brain network patterns reliably classified chronic pain patients in a third, independent open data set with an accuracy of 63%, whilst 68% was attained in cross validation of all data. We then developed a deep learning classifier using a conditional variational autoencoder, which also yield yielded 63% generalisation and 68% cross-validation accuracy. Given the existence of reliable network changes, we next studied the graph topology of the network, and found consistent evidence of hub disruption based on clustering and betweenness centrality of brain nodes in pain patients. To examine this in more detail, we developed a multislice modularity algorithm to identify a consensus pattern of modular reorganisation of brain nodes across the entire data set. This revealed evidence of significant changes in the modular identity of several brain regions, most notably including broad regions of bilateral sensorimotor cortex, subregions of which also contributed to classifier performance. These results provide evidence of consistent and characteristic brain network changes in chronic pain, and highlight extensive reorganisaton of the network architecture of sensorimotor cortex.

neuroscience↗

bioRxiv2017

Altered neurocognitive processing of tactile stimuli in patients with Complex Regional Pain Syndrome (CRPS)

Chronic pain in CRPS has been linked to tactile misperceptions and deficits in somatotopic representation of the affected limb. Here, we identify altered cognitive processing of tactile stimuli in CRPS patients that we propose marks heterogeneity in tactile decision-making mechanisms. In a case-control design, we compared middle and late-latency somatosensory-evoked potentials (SEPs) in response to pseudo-randomised mechanical stimulation of the digits of both hands (including CRPS-affected and non-affected sides) between 13 CRPS patients and 13 matched healthy controls. During a task to discriminate the digit simulated, patients (compared to controls) had significantly lower accuracy and slowed response times but with high between-subject variability. At middle latencies (124-132 ms), tactile processing in patients relative to controls showed decrements in superior parietal lobe and precuneus (that were independent of task demands) but enhanced activity in superior frontal lobe (that were task-dependent). At late latencies, patients showed an augmented P300-like response under task demands that localised to supplementary motor area (SMA). Source activity in SMA correlated with slowed response times, while its scalp representation intriguingly correlated with better functioning of the affected limb, suggesting a compensatory mechanism. Future research should investigate the clinical utility of these putative markers of tactile decision-making mechanisms in CRPS.\n\nDisclosuresThe research was supported by funding from Cambridge Arthritis Research Endeavour (CARE). The study was sponsored by Cambridge University Hospitals NHS Foundation Trust and supported by its Rheumatology department. The authors report no conflicts of interest.\n\nPerspectiveWe present evidence of altered but highly variable cognitive processing (124 - 268ms latency) in response to mechanical tactile stimuli in patients with CRPS compared to healthy controls. Such mid-to-late latency responses could potentially provide convenient and robust biomarkers of abnormal perceptual decision-making mechanisms in CRPS to aid in clinical detection and treatment.

neuroscience↗