260 research outputs found
Diagnostic criteria for primary autoimmune cerebellar ataxia—guidelines from an international task force on immune-mediated cerebellar ataxias
Aside from well-characterized immune-mediated ataxias with a clear trigger and/or association with specific neuronal antibodies, a large number of idiopathic ataxias are suspected to be immune mediated but remain undiagnosed due to lack of diagnostic biomarkers. Primary autoimmune cerebellar ataxia (PACA) is the term used to describe this later group. An International Task Force comprising experts in the field of immune ataxias was commissioned by the Society for Research on the Cerebellum and Ataxias (SRCA) in order to devise diagnostic criteria aiming to improve the diagnosis of PACA. The proposed diagnostic criteria for PACA are based on clinical (mode of onset, pattern of cerebellar involvement, presence of other autoimmune diseases), imaging findings (MRI and if available MR spectroscopy showing preferential, but not exclusive involvement of vermis) and laboratory investigations (CSF pleocytosis and/or CSF-restricted IgG oligoclonal bands) parameters. The aim is to enable clinicians to consider PACA when encountering a patient with progressive ataxia and no other diagnosis given that such consideration might have important therapeutic implications
Paraneoplastic encephalitis: clinically based approach on diagnosis and management
Paraneoplastic neurological syndromes (PNSs) comprise a subset of immune-mediated nervous system diseases triggered by an underlying malignancy. Each syndrome usually shows a distinct clinical presentation and outcome according to the associated neural antibodies. PNSs generally have a subacute onset with rapid progression and severe neurological disability. However, some patients may have hyperacute onset or even show chronic progression mimicking neurodegenerative diseases. Updated diagnostic criteria for PNS have been recently established in order to increase diagnostic specificity and to encourage standardisation of research initiatives related to PNS. Treatment for PNS includes oncological therapy and immunomodulation to halt neurological deterioration although current treatment options are seldom effective in reversing disability. Nevertheless, growing knowledge and better understanding of PNS pathogenesis promise better recognition, earlier diagnosis and novel treatment strategies. Considering that PNSs provide a model of effective anticancer immunity, the impact of these studies will extend far beyond the field of neurology
Assimilation of Remote Sensing Data for River Flows
Abstract. We address the problem of parameters identification and data assimilation for river flows modeled by the 2D St-Venant equations. In practice, available observations are very sparse especially during flood events (very few measurements of elevation at gauging stations in the main channel). We assume we have in addition either surface trajectories extracted from video images (lagrangian data) or space distributed water levels extracted from one satellite image. Then we identify parameters such as the inflow discharge or the topography and/or the initial state (depending on the configuration and the observations available). Numerical twin experiments demonstrate the efficiency of the present method for toy test cases
Consensus Paper: Latent Autoimmune Cerebellar Ataxia (LACA)
Immune-mediated cerebellar ataxias (IMCAs) have diverse etiologies. Patients with IMCAs develop cerebellar symptoms, characterized mainly by gait ataxia, showing an acute or subacute clinical course. We present a novel concept of latent autoimmune cerebellar ataxia (LACA), analogous to latent autoimmune diabetes in adults (LADA). LADA is a slowly progressive form of autoimmune diabetes where patients are often initially diagnosed with type 2 diabetes. The sole biomarker (serum anti-GAD antibody) is not always present or can fluctuate. However, the disease progresses to pancreatic beta-cell failure and insulin dependency within about 5 years. Due to the unclear autoimmune profile, clinicians often struggle to reach an early diagnosis during the period when insulin production is not severely compromised. LACA is also characterized by a slowly progressive course, lack of obvious autoimmune background, and difficulties in reaching a diagnosis in the absence of clear markers for IMCAs. The authors discuss two aspects of LACA: (1) the not manifestly evident autoimmunity and (2) the prodromal stage of IMCA’s characterized by a period of partial neuronal dysfunction where non-specific symptoms may occur. In order to achieve an early intervention and prevent cell death in the cerebellum, identification of the time-window before irreversible neuronal loss is critical. LACA occurs during this time-window when possible preservation of neural plasticity exists. Efforts should be devoted to the early identification of biological, neurophysiological, neuropsychological, morphological (brain morphometry), and multimodal biomarkers allowing early diagnosis and therapeutic intervention and to avoid irreversible neuronal loss
Cytokine dynamics and targeted immunotherapies in autoimmune encephalitis
Autoimmune encephalitides constitute a diverse group of immune-mediated central nervous system disorders mainly characterized by the presence of antibodies targeting neuronal or glial antigens. Despite the notable contribution of antibody discovery to the understanding of their physiopathology, the specific immune cells and inflammatory mediators involved in autoimmune encephalitis are still poorly defined. However, cytokines have recently emerged as crucial signalling molecules in the pathogenesis of autoimmune encephalitis. Cytokines are biologically active, soluble, low-molecular-weight proteins or glycoproteins involved in a wide variety of physiological functions, including central nervous system development and homeostasis, immune surveillance, as well as proliferation and maturation of immune cells. Since unbalanced cytokine expression is considered a hallmark of many autoimmune central nervous system disorders, their identification and quantification has become an essential element in personalized medicine applied to the field of neuroimmunology. Several studies have explored the cytokine profile of autoimmune encephalitis, but their interpretation and comparison is challenging due to their small sample sizes and extremely high heterogeneity, especially regarding the cytokines analysed, type of sample used, and associated neural antibody. Only the cytokine profile of anti-N-methyl-D-aspartate receptor encephalitis has extensively been investigated, with findings suggesting that, although humoral immunity is the main effector, T cells may also be relevant for the development of this disorder. A better understanding of cytokine dynamics governing neuroinflammation might offer the opportunity of developing new therapeutic strategies against specific immune cells, cytokines, antibodies, or intracellular signalling cascades, therefore leading to better outcomes and preventing undesired side effects of the presently used strategies. In this review, we first summarize the current knowledge about the role of cytokines in the pathogenesis of autoimmune encephalitis, combining theoretical analysis with experimental validations, to assess their suitability as clinical biomarkers. Second, we discuss the potential applicability of the novel targeted immunotherapies in autoimmune encephalitis depending on the immunobiology of the associated antibody, their limitations, as well as the main limitations that should be addressed in future studies
Cerebellar ataxia associated to anti-glutamic acid decarboxylase autoantibody (anti-GAD): partial improvement with intravenous immunoglobulin therapy
Epidemiology of paraneoplastic neurologic syndromes and autoimmune encephalitides in France
OBJECTIVE: To determine the observed and expected incidence rates of paraneoplastic neurologic syndromes (PNSs) and autoimmune encephalitides (AEs) diagnosed in France between 2016 and 2018, we conducted a population-based epidemiologic study. METHODS: Observed incidence rates were stratified by sex, age groups, region of care, year of diagnosis, and disease subgroups. National expected incidence rates were calculated based on rates obtained in the area directly adjacent to the Reference Center using a mixed Poisson model and compared with observed incidence rates. RESULTS: Six hundred thirty-two patients with definite PNS or AE met the inclusion criteria. The observed incidence rate of definite PNS and AE in France was 3.2 per million person-years (CI95%: 2.9-3.4) compared with an expected incidence rate of 7.1 per million person-years (CI95%: 3.9-11.4). The national observed incidence rate for the antibody-positive AE subgroup increased from 1.4 per million person-years (CI95%: 1.2-1.7) in 2016 to 2.1 per million person-years (CI95%: 1.7-2.4) in 2018, thus surpassing the incidence rate of classical PNS (1.2 per million person-years [CI95%: 1.0-1.5]) of 2018. CONCLUSIONS: There was a significant widespread year-to-year increase in the incidence of diagnoses registered with the Reference Center for all subgroups of PNS and AE studied. The national observed incidence rate is likely underestimated due to underdiagnosis and underreporting
Prediction of Response to Temozolomide in Low-Grade Glioma Patients Based on Tumor Size Dynamics and Genetic Characteristics
International audienceBoth molecular profiling of tumors and longitudinal tumor size data modeling are relevant strategies to predict cancer patients' response to treatment. Herein we propose a model of tumor growth inhibition integrating a tumor's genetic characteristics (p53 mutation and 1p/19q codeletion) that successfully describes the time course of tumor size in patients with low-grade gliomas treated with first-line temozolomide chemotherapy. The model captures potential tumor progression under chemotherapy by accounting for the emergence of tissue resistance to treatment following prolonged exposure to temozolomide. Using information on individual tumors' genetic characteristics, in addition to early tumor size measurements, the model was able to predict the duration and magnitude of response, especially in those patients in whom repeated assessment of tumor response was obtained during the first 3 months of treatment. Combining longitudinal tumor size quantitative modeling with a tumor''s genetic characterization appears as a promising strategy to personalize treatments in patients with low-grade gliomas. WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? þ First-line temozolomide is frequently used to treat low-grade gliomas (LGG), which are slow-growing brain tumors. The duration of response depends on genetic characteristics such as 1p/19q chromosomal codeletion, p53 mutation, and IDH mutations. However, up to now there are no means of predicting, at the individual level, the duration of the response to TMZ and its potential benefit for a given patient. • WHAT QUESTION DID THIS STUDY ADDRESS? þ The present study assessed whether combining longitudinal tumor size quantitative modeling with a tumor's genetic characterization could be an effective means of predicting the response to temozolomide at the individual level in LGG patients. • WHAT THIS STUDY ADDS TO OUR KNOWLEDGE þ For the first time, we developed a model of tumor growth inhibition integrating a tumor's genetic characteristics which successfully describes the time course of tumor size and captures potential tumor progression under chemotherapy in LGG patients treated with first-line temozolomide. The present study shows that using information on individual tumors' genetic characteristics, in addition to early tumor size measurements, it is possible to predict the duration and magnitude of response to temozolomide. • HOW THIS MIGHT CHANGE CLINICAL PHARMACOLOGY AND THERAPEUTICS þ Our model constitutes a rational tool to identify patients most likely to benefit from temozolomide and to optimize in these patients the duration of temozolomide therapy in order to ensure the longest duration of response to treatment. Response evaluation criteria such as RECIST—or RANO for brain tumors—are commonly used to assess response to anticancer treatments in clinical trials. 1,2 They assign a patient's response to one of four categories, ranging from " complete response " to " disease progression. " Yet, criticisms have been raised regarding the use of such categorical criteria in the drug development process, 3,4 and regulatory agencies have promoted the additional analysis of longitudinal tumor size measurements through the use of quantitative modeling. 5 Several mathematical models of tumor growth and response to treatment have been developed for this purpose. 6,7 These analyses have led to th
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