X-linked susceptibility to mycobacteria is caused by mutations in NEMO impairing CD40-dependent IL-12 production

Germline mutations in five autosomal genes involved in interleukin (IL)-12–dependent, interferon (IFN)-γ–mediated immunity cause Mendelian susceptibility to mycobacterial diseases (MSMD). The molecular basis of X-linked recessive (XR)–MSMD remains unknown. We report here mutations in the leucine zipper (LZ) domain of the NF-κB essential modulator (NEMO) gene in three unrelated kindreds with XR-MSMD. The mutant proteins were produced in normal amounts in blood and fibroblastic cells. However, the patients' monocytes presented an intrinsic defect in T cell–dependent IL-12 production, resulting in defective IFN-γ secretion by T cells. IL-12 production was also impaired as the result of a specific defect in NEMO- and NF-κB/c-Rel–mediated CD40 signaling after the stimulation of monocytes and dendritic cells by CD40L-expressing T cells and fibroblasts, respectively. However, the CD40-dependent up-regulation of costimulatory molecules of dendritic cells and the proliferation and immunoglobulin class switch of B cells were normal. Moreover, the patients' blood and fibroblastic cells responded to other NF-κB activators, such as tumor necrosis factor-α, IL-1β, and lipopolysaccharide. These two mutations in the NEMO LZ domain provide the first genetic etiology of XR-MSMD. They also demonstrate the importance of the T cell– and CD40L-triggered, CD40-, and NEMO/NF-κB/c-Rel–mediated induction of IL-12 by monocyte-derived cells for protective immunity to mycobacteria in humans

Is the high risk of anaphylaxis to omalizumab a contraindication to this treatment?

International audienceOmalizumab is a recombinant humanized monoclonal antibody (mAb) targeting IgE, produced using Chinese hamster ovary (CHO) cell culture. It has been approved for the treatment of severe allergic asthma (SAA) and chronic urticaria but not for allergic rhinitis (AR), atopic dermatitis (AD) or food allergy, despite some benefits against these diseases [1]. Omalizumab treatment associated with allergen immunotherapy (AIT) can increase the tolerability of AIT [1]. Some anaphylactic reactions have been [...

Emergence of azole resistant-Aspergillus fumigatus infections during STAT3-deficiency

International audienceIntroduction. Signal transducer and activator of transcription 3 (STAT3) deficiency is a rare primary immunodeficiency associated with increased susceptibility to bacterial and fungal infections, notably pulmonary aspergillosis.Aim. We describe the emergence of azole-resistant Aspergillus fumigatus infections in STAT3-deficient patients. Methodology. During a retrospective study of 13 pulmonary aspergillosis cases in STAT3-deficient patients conducted in France, we identified patients infected with azole-resistant A. fumigatus isolates.Results. Two out of the 13 STAT3-deficient patients with aspergillosis had azole-resistant A. fumigatus infection, indicating an unexpectedly high prevalence of resistance. The first patient with STAT3 deficiency presented several flares of allergic bronchopulmonary aspergillosis-like episodes. He was chronically infected with two azole-resistant A. fumigatus isolates (TR34/L98). Despite prolonged antifungal treatment, including caspofungin and amphotericin B, the patient was not able to clear the azoleresistant A. fumigatus. The second patient had chronic cavitary pulmonary aspergillosis (CCPA). The A. fumigatus isolate was initially azole susceptible but harboured three F46Y, M172V and E427K point mutations. Despite prolonged antifungal therapies, lesions worsened and the isolate became resistant to all azoles. Surgery and caspofungin treatments were then required to cure CCPA. Resistance was probably acquired from the environment (TR34/L98) in the first case whereas resistance developed under antifungal treatments in the second case. These infections required long-term antifungal treatments and surgery.Conclusions. The emergence of azole-resistant A. fumigatus infections in STAT3-deficiency dramatically impacts both curative and prophylactic antifungal strategies. Physicians following patients with primary immune-deficiencies should be aware of this emerging problem as it complicates management of the patient

Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification.

INTRODUCTION: To decipher the interaction between the molecular subtype classification and the probability of a non-sentinel node metastasis in breast cancer patients with a metastatic sentinel lymph-node, we applied two validated predictors (Tenon Score and MSKCC Nomogram) on two large independent datasets. MATERIALS AND METHODS: Our datasets consisted of 656 and 574 early-stage breast cancer patients with a metastatic sentinel lymph-node biopsy treated at first by surgery. We applied both predictors on the whole dataset and on each molecular immune-phenotype subgroups. The performances of the two predictors were analyzed in terms of discrimination and calibration. Probability of non-sentinel lymph node metastasis was detailed for each molecular subtype. RESULTS: Similar results were obtained with both predictors. We showed that the performance in terms of discrimination was as expected in ER Positive HER2 negative subgroup in both datasets (MSKCC AUC Dataset 1 = 0.73 [0.69-0.78], MSKCC AUC Dataset 2 = 0.71 (0.65-0.76), Tenon Score AUC Dataset 1 = 0.7 (0.65-0.75), Tenon Score AUC Dataset 2 = 0.72 (0.66-0.76)). Probability of non-sentinel node metastatic involvement was slightly under-estimated. Contradictory results were obtained in other subgroups (ER negative HER2 negative, HER2 positive subgroups) in both datasets probably due to a small sample size issue. We showed that merging the two datasets shifted the performance close to the ER positive HER2 negative subgroup. DISCUSSION: We showed that validated predictors like the Tenon Score or the MSKCC nomogram built on heterogeneous population of breast cancer performed equally on the different subgroups analyzed. Our present study re-enforce the idea that performing subgroup analysis of such predictors within less than 200 samples subgroup is at major risk of misleading conclusions

Reliability analysis of centralized versus decentralized zoning strategies for paratransit services

ADA paratransit services are a very large and ever-growing industry providing door-to-door transportation services for people with disability and elderly customers. Paratransit system, however, just like all other public transportation systems, suffers from travel time variability due to various factors and as a result gives its customers unreliable services. Although service reliability is a very important aspect in transportation study, it has not received much attention in the paratransit research community. A quantitative study evaluating the paratransit service reliability under different zoning strategies is yet to be found. This research filled this gap. Statistical models were proposed to represent travel time variability. Simulation experiments based on real demand data from Houston, Los Angeles and Boston were performed to quantitatively compare the reliability performance of centralized and decentralized operating strategies under different travel time variability levels. Results showed that the decentralized strategy, compared to the centralized no-zoning strategy, substantially improves the reliability of paratransit in terms of on-time performance. This research provides a framework for paratransit agencies to evaluate the service reliability of different organizational strategies through the simulation method

Mean predicted versus observed survival.

<p>French population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The grey thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.</p

Baseline characteristics, French and Dutch population.

a<p>mean (sd).</p

Mean predicted versus observed survival.

<p>Dutch population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.</p

Difference (Δ) between observed outcome and Adjuvant! Online prediction in three other major confirmation studies [9], [10], [11].

<p>Difference (Δ) between observed outcome and Adjuvant! Online prediction in three other major confirmation studies <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0027446#pone.0027446-Campbell1" target="_blank">[9]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0027446#pone.0027446-Mook1" target="_blank">[10]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0027446#pone.0027446-Olivotto1" target="_blank">[11]</a>.</p