Circulating gluten-specific FOXP3⁺CD39⁺ regulatory T cells have impaired suppressive function in patients with celiac disease

Background Celiac disease is a chronic immune-mediated inflammatory disorder of the gut triggered by dietary gluten. Although the effector T-cell response in patients with celiac disease has been well characterized, the role of regulatory T (Treg) cells in the loss of tolerance to gluten remains poorly understood. Objective We sought to define whether patients with celiac disease have a dysfunction or lack of gluten-specific forkhead box protein 3 (FOXP3)+ Treg cells. Methods Treated patients with celiac disease underwent oral wheat challenge to stimulate recirculation of gluten-specific T cells. Peripheral blood was collected before and after challenge. To comprehensively measure the gluten-specific CD4+ T-cell response, we paired traditional IFN-γ ELISpot with an assay to detect antigen-specific CD4+ T cells that does not rely on tetramers, antigen-stimulated cytokine production, or proliferation but rather on antigen-induced coexpression of CD25 and OX40 (CD134). Results Numbers of circulating gluten-specific Treg cells and effector T cells both increased significantly after oral wheat challenge, peaking at day 6. Surprisingly, we found that approximately 80% of the ex vivo circulating gluten-specific CD4+ T cells were FOXP3+CD39+ Treg cells, which reside within the pool of memory CD4+CD25+CD127lowCD45RO+ Treg cells. Although we observed normal suppressive function in peripheral polyclonal Treg cells from patients with celiac disease, after a short in vitro expansion, the gluten-specific FOXP3+CD39+ Treg cells exhibited significantly reduced suppressive function compared with polyclonal Treg cells. Conclusion This study provides the first estimation of FOXP3+CD39+ Treg cell frequency within circulating gluten-specific CD4+ T cells after oral gluten challenge of patients with celiac disease. FOXP3+CD39+ Treg cells comprised a major proportion of all circulating gluten-specific CD4+ T cells but had impaired suppressive function, indicating that Treg cell dysfunction might be a key contributor to disease pathogenesis

Pretest expectations strongly influence interpretation of abnormal laboratory results and further management

Contains fulltext : 89631.pdf (publisher's version ) (Open Access)BACKGROUND: Abnormal results of diagnostic laboratory tests can be difficult to interpret when disease probability is very low. Although most physicians generally do not use Bayesian calculations to interpret abnormal results, their estimates of pretest disease probability and reasons for ordering diagnostic tests may--in a more implicit manner--influence test interpretation and further management. A better understanding of this influence may help to improve test interpretation and management. Therefore, the objective of this study was to examine the influence of physicians' pretest disease probability estimates, and their reasons for ordering diagnostic tests, on test result interpretation, posttest probability estimates and further management. METHODS: Prospective study among 87 primary care physicians in the Netherlands who each ordered laboratory tests for 25 patients. They recorded their reasons for ordering the tests (to exclude or confirm disease or to reassure patients) and their pretest disease probability estimates. Upon receiving the results they recorded how they interpreted the tests, their posttest probability estimates and further management. Logistic regression was used to analyse whether the pretest probability and the reasons for ordering tests influenced the interpretation, the posttest probability estimates and the decisions on further management. RESULTS: The physicians ordered tests for diagnostic purposes for 1253 patients; 742 patients had an abnormal result (64%). Physicians' pretest probability estimates and their reasons for ordering diagnostic tests influenced test interpretation, posttest probability estimates and further management. Abnormal results of tests ordered for reasons of reassurance were significantly more likely to be interpreted as normal (65.8%) compared to tests ordered to confirm a diagnosis or exclude a disease (27.7% and 50.9%, respectively). The odds for abnormal results to be interpreted as normal were much lower when the physician estimated a high pretest disease probability, compared to a low pretest probability estimate (OR = 0.18, 95% CI = 0.07-0.52, p < 0.001). CONCLUSIONS: Interpretation and management of abnormal test results were strongly influenced by physicians' estimation of pretest disease probability and by the reason for ordering the test. By relating abnormal laboratory results to their pretest expectations, physicians may seek a balance between over- and under-reacting to laboratory test results

Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study

Application of Biomarkers in Cancer Risk Management: Evaluation from Stochastic Clonal Evolutionary and Dynamic System Optimization Points of View

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic “biomarkers” have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time

Raman spectroscopy: elucidation of biochemical changes in carcinogenesis of oesophagus

Several techniques are under development to diagnose oesophageal adenocarcinoma at an earlier stage. We have demonstrated the potential of Raman spectroscopy, an optical diagnostic technique, for the identification and classification of malignant changes. However, there is no clear recognition of the biochemical changes that distinguish between the different stages of disease. Our aim is to understand these changes through Raman mapping studies. Raman spectral mapping was used to analyse 20-μm sections of tissue from 29 snap-frozen oesophageal biopsies. Contiguous haematoxylin and eosin sections were reviewed by a consultant pathologist. Principal component analysis was used to identify the major differences between the spectra across each map. Pseudocolour score maps were generated and the peaks of corresponding loads identified enabling visualisation of the biochemical changes associated with malignancy. Changes were noted in the distribution of DNA, glycogen, lipids and proteins. The mean spectra obtained from selected regions demonstrate increased levels of glycogen in the squamous area compared with increased DNA levels in the abnormal region. Raman spectroscopy is a highly sensitive and specific technique for demonstration of biochemical changes in the carcinogenesis of Barrett's oesophagus. There is potential for in vivo application for real-time endoscopic optical diagnosis

Origin and Properties of Striatal Local Field Potential Responses to Cortical Stimulation: Temporal Regulation by Fast Inhibitory Connections

Evoked striatal field potentials are seldom used to study corticostriatal communication in vivo because little is known about their origin and significance. Here we show that striatal field responses evoked by stimulating the prelimbic cortex in mice are reduced by more than 90% after infusing the AMPA receptor antagonist CNQX close to the recording electrode. Moreover, the amplitude of local field responses and dPSPs recorded in striatal medium spiny neurons increase in parallel with increasing stimulating current intensity. Finally, the evoked striatal fields show several of the basic known properties of corticostriatal transmission, including paired pulse facilitation and topographical organization. As a case study, we characterized the effect of local GABAA receptor blockade on striatal field and multiunitary action potential responses to prelimbic cortex stimulation. Striatal activity was recorded through a 24 channel silicon probe at about 600 µm from a microdialysis probe. Intrastriatal administration of the GABAA receptor antagonist bicuculline increased by 65±7% the duration of the evoked field responses. Moreover, the associated action potential responses were markedly enhanced during bicuculline infusion. Bicuculline enhancement took place at all the striatal sites that showed a response to cortical stimulation before drug infusion, but sites showing no field response before bicuculline remained unresponsive during GABAA receptor blockade. Thus, the data demonstrate that fast inhibitory connections exert a marked temporal regulation of input-output transformations within spatially delimited striatal networks responding to a cortical input. Overall, we propose that evoked striatal fields may be a useful tool to study corticostriatal synaptic connectivity in relation to behavior

Planning Technologies for Interactive Storytelling

Since AI planning was first proposed for the task of narrative generation in interactive storytelling (IS), it has emerged as the dominant approach in this field. This chapter traces the use of planning technologies in this area, considers the core issues involved in the application of planning technologies in IS, and identifies some of the remaining challenges