Long-term outcomes in corticosteroid-refractory Graves' orbitopathy treated with tocilizumab.

Up to 20% of patients with moderate to severe Graves' orbitopathy (GO) do not respond to high-dose glucocorticoids (GC). A few studies, including a randomized trial, have demonstrated the efficacy of interleukin-6 (IL-6) blockade with tocilizumab (TCZ) in GC-refractory GO. However, data on predictors of response to TCZ and long-term outcomes are lacking. Observational single-center study on ten consecutive patients treated with TCZ for GC-refractory GO, between 2016 and 2020. Median (interquartile range) follow-up was 24 (12-36) months. Inflammation and exophthalmos improved dramatically in all patients within months after starting TCZ. Mean Clinical Activity Score decreased from 4.80 ± 1.13 to 0.70 ± 0.82 points at 6 months (mean change: -4.10 ± 1.52; p < .0001). Proptosis improved from 23.2 ± 2.1 to 20.6 ± 2.0 mm at 6 months (mean change: -2.9 ± 1.4 mm; p < .0001). Diplopia resolved in 7 patients. Thyroid receptor antibodies decreased markedly during TCZ treatment. Baseline serum IL-6 levels did not predict clinical response. TCZ was well-tolerated. During follow-up, 3 patients were diagnosed with cancer (breast cancer in 2 and urothelial cancer in 1). TCZ was rapidly effective and well-tolerated in our patients with GC-refractory GO. Four patients experienced mild/moderate adverse events as neutropenia, hyperlipidemia, and infections; nearly a third developed cancer during the follow-up. The increased incidence observed could be explained by the high prevalence of smokers, that are at higher risk for Graves' orbitopathy and solid malignancies as breast cancer. Thus, regular cancer screening could be proposed to this vulnerable population receiving high doses of immunosuppressants

Genetic structure of the high dispersal Atlanto-Mediterreanean sea star Astropecten aranciacus revealed by mitochondrial DNA sequences and microsatellite loci

To investigate the impact of potential marine barriers on gene-flow in high dispersal marine invertebrates, we assessed the population genetic structure of the sea star Astropecten aranciacus. Samples were obtained from nine locations within the Atlantic and the Mediterranean Sea including populations east of the Siculo-Tunisian Strait. We obtained both DNA sequence data of the mitochondrial control region and genotype data at four microsatellite loci. Both markers were highly polymorphic and showed a great level of genetic diversity. Genetic differentiation between populations (F ST) was in general low, particularly for nuclear data, as is often the case in high dispersal marine invertebrates. Nevertheless, both marker sets indicated a significant genetic differentiation of the population from the island of Madeira to most other populations. Our results also demonstrate a clear pattern of isolation-by-distance supported by both mitochondrial and nuclear markers. Therefore, we conclude that larval dispersal of A. aranciacus is somewhat limited even within the basins of the Atlantic, the west Mediterranean and the east Mediterranean. Microsatellite loci further revealed genetic differentiation between the three basins; however, it is not clear whether this is truly caused by marine barriers. Genetic differentiation between basins might also be a result of isolation-by-distance allowing for any grouping to be significant as long as geographical neighbors are clustered together. Although levels of genetic differentiation were less pronounced in microsatellite data, both datasets were coherent and revealed similar patterns of genetic structure in A. aranciacu

Estimation de la température de l'eau de rivière en utilisant les réseaux de neurones et la régression linéaire multiple

La température de l'eau en rivière est un paramètre ayant une importance majeure pour la vie aquatique. Les séries temporelles décrivant ce paramètre thermique existent, mais elles sont moins nombreuses et souvent courtes, ou comptent parfois des valeurs manquantes. Cette étude présente la modélisation de la température de l'eau en utilisant des réseaux de neurones et la régression linéaire multiple pour relier la température de l'eau à celle de l'air et le débit du ruisseau Catamaran, situé au Nouveau-Brunswick, Canada. Une recherche multidisciplinaire à long terme se déroule présentement sur ce site. Les données utilisées sont de 1991 à 2000 et comprennent la température de l'air de la journée en cours, de la veille et de l'avant-veille, le débit ainsi que le temps transformé en série trigonométrique. Les données de 1991 à 1995 ont été utilisées pour l'entraînement ou la calibration du modèle tandis que les données de 1996 à 2000 ont été utilisées pour la validation du modèle. Les coefficients de détermination obtenus pour l'entraînement sont de 94,2 % pour les réseaux de neurones et de 92,6 % pour la régression linéaire multiple, ce qui donne un écart-type des erreurs de 1,01 C pour les réseaux de neurones et de 1,05 C pour la régression linéaire multiple. Pour la validation, les coefficients de détermination sont de 92,2 % pour les réseaux de neurones et de 91,6 % pour la régression linéaire multiple, ce qui se traduit en un écart-type des erreurs de 1,10 C pour les réseaux de neurones et de 1,25 C pour la régression linéaire multiple. Durant la période d'étude (1991-2000), le biais a été calculé à +0,11 C pour le modèle de réseaux de neurones et à -0,26 °C pour le modèle de régression. Ces résultats permettent de conclure qu'il est possible de prévoir la température de l'eau de petits cours d'eau en utilisant la température de l'air et le débit, aussi bien avec les réseaux de neurones qu'avec la régression linéaire multiple. Les réseaux de neurones semblent donner un ajustement aux données légèrement meilleur que celui offert par la régression linéaire multiple, toutefois ces deux approches de modélisation démontrent une bonne performance pour la prédiction de la température de l'eau en rivière.Water temperature is a parameter of great importance for water resources. For instance, modifications of the thermal regime of a river can have a significant impact on fish habitat. Therefore, understanding and predicting water temperatures is essential in order to help prevent or forecast high temperature problems. In order to predict water temperatures, data series are necessary. Many data series exist for air temperatures, but water temperature series are relatively scarce and those available are often short or have missing values. This study presents the modelling of water temperature using neural networks and multiple linear regression to relate water temperature to air temperature and discharge in Catamaran Brook, New Brunswick, Canada.Catamaran Brook is a small stream (51 km2) where long-term multidisciplinary habitat research is being carried out. Many variables can impact water temperatures in a river, such as air temperature, solar radiation, wind speed, discharge, groundwater flow, etc. For this study, only air temperature and discharge were used. These were judged to be the most often available parameters for modelling temperatures in rivers, and to have the greatest impact on water temperature. More precisely, input variables included current air temperature (°C), air temperature of the previous day (°C), air temperature two days earlier (°C), discharge (m3 /s) and a trigonometric function of time (days). Data used for the analysis were from 1991 to 2000. Data from 1991 to 1995 were used to calibrate the model while data from 1996 to 2000 were used for validation purposes. Observed and predicted water temperatures for each model were presented for the calibration data and the validation data. The coefficient of determination, R2, was used to compare the efficiency of both models as well as the residual standard deviation and the bias. This is equivalent to basing the comparison on the standard deviation (or variance) of the residuals. Coefficients of determination for calibration were 94.2% for the neural networks and 92.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.01°C for the neural networks and of 1.05°C for the multiple linear regression. For validation, coefficients of determination were 92.2% for the neural networks and 91.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.10°C for the neural networks, and of 1.25°C for the multiple regression. The overall bias during the study period (1991-2000) was calculated at +0.11°C for the neural network model and at -0.26°C for the regression model. Results indicated that it was possible to predict water temperature for a small stream using air temperature, flow and time, as input variables, with neural networks and multiple linear regression. The residual series obtained by both models were very similar. Of the two models, neural networks gave slightly better results in terms of fit, but the small difference in results lets us believe that both approaches are equally good in predicting stream water temperatures

Restoration of NK Cell Cytotoxic Function With Elotuzumab and Daratumumab Promotes Elimination of Circulating Plasma Cells in Patients With SLE.

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease characterized by multiple cellular and molecular dysfunctions of the innate and adaptive immunity. Cytotoxic function of NK cells is compromised in patients with SLE. Herein, we characterized the phenotypic alterations of SLE NK cells in a comprehensive manner to further delineate the mechanisms underlying the cytotoxic dysfunction of SLE NK cells and identify novel potential therapeutic targets. Therefore, we examined PBMC from SLE patients and matched healthy controls by single-cell mass cytometry to assess the phenotype of NK cells. In addition, we evaluated the cell function of NK cells (degranulation and cytokine production) and the killing of B cell subpopulations in a B cell-NK cell in vitro co-culture model. We found that SLE NK cells expressed higher levels of CD38 and were not able to adequately upregulate SLAMF1 and SLAMF7 following activation. In addition, ligation of SLAMF7 with elotuzumab or of CD38 with daratumumab on SLE NK cells enhanced degranulation of both healthy and SLE NK cells and primed them to kill circulating plasma cells in an in vitro co-culture system. Overall, our data indicated that dysregulated expression of CD38, SLAMF1 and SLAMF7 on SLE NK cells is associated with an altered interplay between SLE NK cells and plasma cells, thus suggesting their contribution to the accumulation of (auto)antibody producing cells. Accordingly, targeting SLAMF7 and CD38 may represent novel therapeutic approaches in SLE by enhancing NK cell function and promoting elimination of circulating plasma cell

Allergologie-immunologie - Maladies autoimmunes complexes : quand les glucocorticoïdes ne suffisent plus [Difficult to treat auto-immune diseases : when glucocorticoids are not enough]

Glucocorticosteroids (GC) remain the mainstay of treatment in most systemic inflammatory diseases. GC have a broad anti-inflammatory action of rapid onset. The downsides of prolonged GC therapy are well established and include infections, osteoporosis and metabolic adverse effects, among others. In systemic sclerosis, GC are associated with an increased risk of scleroderma renal crisis and must be avoided. Adjunction of second-line immunosuppressive drugs may improve disease control and limit GC usage. We summarize here the findings of two studies published in 2021, one reporting the benefits of combining GC with mycophenolate mofetil in immune thrombocytopenia, the other suggesting that blockage of interleukin-6 may decrease disease progression in systemic sclerosis with lung involvement

Experiences of people affected by cancer during the outbreak of the COVID-19 pandemic: an exploratory qualitative analysis of public online forums.

Studies focusing on patients with and survivors of cancer during the COVID-19 pandemic highlight unique psychological and behavioral challenges. These findings were obtained in surveys using self-report questionnaires with pre-specified response options that may not capture the broad range of experiences of individuals affected by cancer, including people with cancer and informal caregivers, in this unprecedented situation. Online forums produce a large amount of valuable first-hand user-generated content that can be used to better understand their day-to-day lives. This study, based on the analysis of narratives in cancer online forums, aims to describe and categorize the experiences of people affected by cancer during the outbreak of the COVID-19 pandemic. An inductive, descriptive, thematic approach was applied to publicly available cancer forums from Germany, the USA, the UK, and Ireland posted between mid-March and mid-April 2020. An analysis of the content of 230 main posts revealed three major themes: (1) concerns related to the impact of COVID-19 on cancer care, the risks and fears of getting infected, logistic issues, and economic impact; (2) adaptation challenges faced at the individual and societal level; and (3) the need for advice including information about COVID-19 and the (self-)management of cancer symptoms and treatment. Our qualitative description of the experiences of people affected by cancer during the COVID-19 pandemic outbreak can help to improve communication, education, and the development of supportive care strategies. Furthermore, the themes and subthemes identified could potentially inform item development for future self-report questionnaires

No association of complement mannose-binding lectin deficiency with cardiovascular disease in patients with Systemic Lupus Erythematosus.

Cardiovascular (CV) morbidity is the major cause of death in patients with Systemic Lupus Erythematosus (SLE). Previous studies on mannose-binding lectin (MBL) gene polymorphisms in SLE patients suggest that low levels of complement MBL are associated with cardiovascular disease (CVD). However, as large studies on MBL deficiency based on resulting MBL plasma concentrations are lacking, the aim of our study was to analyze the association of MBL concentrations with CVD in SLE patients. Plasma MBL levels SLE patients included in the Swiss SLE Cohort Study were quantified by ELISA. Five different CV organ manifestations were documented. Of 373 included patients (85.5% female) 62 patients had at least one CV manifestation. Patients with MBL deficiency (levels below 500 ng/ml or 1000 ng/ml) had no significantly increased frequency of CVD (19.4% vs. 15.2%, P = 0.3 or 17.7% vs. 15.7%, P = 0.7). After adjustment for traditional CV risk factors, MBL levels and positive antiphospholipid serology (APL+) a significant association of CVD with age, hypertension, disease duration and APL+ was demonstrated. In our study of a large cohort of patients with SLE, we could not confirm previous studies suggesting MBL deficiency to be associated with an increased risk for CVD

A severe case of neuroleukemiosis caused by B cell chronic lymphocytic leukemia, presenting as mononeuritis multiplex.

To report an exceptional case of nerve infiltration by an otherwise benign chronic B cell leukemia, inducing severe mononeuritis multiplex. The patient underwent extensive evaluation, including nerve conduction study and myography, brain and plexus MRI, and nerve biopsy. The clinical and electrophysiological diagnosis was a mononeuritis multiplex with severe motor and sensory involvement; only the nerve biopsy allowed definite diagnosis and introduction of chemotherapy, leading to resolution of sensory deficit and progressive motor improvement. Neuroleukemiosis caused by chronic lymphoid leukemia is an exceptional diagnosis. The presence of other possible causes like cryoglobulinemia could induce avoidance of nerve biopsy thus undertreating patient, since steroid treatment is not expected to be efficient on lymphocytic proliferation. Our case stretches the importance of nerve biopsy and raises neuromuscular specialist's awareness of this rare entity

SLAMF Receptor Expression Identifies an Immune Signature That Characterizes Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of unknown etiology, linked to alterations in both the innate and the adaptive immune system. Due to the heterogeneity of the clinical presentation, the diagnosis of SLE remains complicated and is often made years after the first symptoms manifest, delaying treatment, and worsening the prognosis. Several studies have shown that signaling lymphocytic activation molecule family (SLAMF) receptors are aberrantly expressed and dysfunctional in SLE immune cells, contributing to the altered cellular function observed in these patients. The aim of this study was to determine whether altered co-/expression of SLAMF receptors on peripheral blood mononuclear cells (PBMC) identifies SLE characteristic cell populations. To this end, single cell mass cytometry and bioinformatic analysis were exploited to compare SLE patients to healthy and autoimmune diseases controls. First, the expression of each SLAMF receptor on all PBMC populations was investigated. We observed that SLAMF1+ B cells (referred to as SLEB1) were increased in SLE compared to controls. Furthermore, the frequency of SLAMF4+ monocytes and SLAMF4+ NK were inversely correlated with disease activity, whereas the frequency SLAMF1+ CD4+ TDEM cells were directly correlated with disease activity. Consensus clustering analysis identified two cell clusters that presented significantly increased frequency in SLE compared to controls: switch memory B cells expressing SLAMF1, SLAMF3, SLAMF5, SLAMF6 (referred to as SLESMB) and circulating T follicular helper cells expressing the same SLAMF receptors (referred to as SLEcTFH). Finally, the robustness of the identified cell populations as biomarkers for SLE was evaluated through ROC curve analysis. The combined measurement of SLEcTFH and SLEB1 or SLESMB cells identified SLE patients in 90% of cases. In conclusion, this study identified an immune signature for SLE based on the expression of SLAMF receptors on PBMC, further highlighting the involvement of SLAMF receptors in the pathogenesis of SLE