Influencing factors on the safety and effectiveness of venom immunotherapy.

BACKGROUND AND OBJECTIVE: The safety profile of venom immunotherapy (VIT) is a relevant issue and considerable differences in safety and efficacy of VIT have been reported. The primary aim of this study was to evaluate the safety of ACE inhibitors and beta-blockers during VIT, which has already been published. For a second analysis, data concerning premedication and venom preparations in relation to systemic adverse events (AE) during the up-dosing phase and the first year of the maintenance phase were evaluated as well as the outcome of field stings and sting challenges. METHODS: The study was conducted as an open, prospective, observational, multicenter study. In total, 1,425 patients were enrolled and VIT was performed in 1,342 patients. RESULTS: Premedication with oral antihistamines was taken by 52.1% of patients during the up-dosing and 19.7% of patients during the maintenance phase. Taking antihistamines had no effect on the frequency of systemic AE (p=0.11) but large local reactions (LLR) were less frequently seen (OR: 0.74; 95% CI: 0.58-0.96; p=0.02). Aqueous preparations were preferentially used for up-dosing (73.0%) and depot preparations for the maintenance phase (64.5%). The type of venom preparation neither had an influence on the frequency of systemic AE nor on the effectiveness of VIT (p=0.26 and p=0.80, respectively), while LLR were less frequently seen when depot preparations were used (p<0.001). CONCLUSION: Pretreatment with oral antihistamines during VIT significantly reduces the frequency of LLR but not systemic AE. All venom preparations used were equally effective and did not differ in the frequency of systemic AE.

Reconstructing in-depth activity for chaotic 3D spatiotemporal excitable media models based on surface data.

Motivated by potential applications in cardiac research, we consider the task of reconstructing the dynamics within a spatiotemporal chaotic 3D excitable medium from partial observations at the surface. Three artificial neural network methods (a spatiotemporal convolutional long-short-term-memory, an autoencoder, and a diffusion model based on the U-Net architecture) are trained to predict the dynamics in deeper layers of a cube from observational data at the surface using data generated by the Barkley model on a 3D domain. The results show that despite the high-dimensional chaotic dynamics of this system, such cross-prediction is possible, but non-trivial and as expected, its quality decreases with increasing prediction depth.

Harnessing the wisdom of crowds can improve guideline compliance of antibiotic prescribers and support antimicrobial stewardship.

Antibiotic overprescribing is a global challenge contributing to rising levels of antibiotic resistance and mortality. We test a novel approach to antibiotic stewardship. Capitalising on the concept of "wisdom of crowds", which states that a group's collective judgement often outperforms the average individual, we test whether pooling treatment durations recommended by different prescribers can improve antibiotic prescribing. Using international survey data from 787 expert antibiotic prescribers, we run computer simulations to test the performance of the wisdom of crowds by comparing three data aggregation rules across different clinical cases and group sizes. We also identify patterns of prescribing bias in recommendations about antibiotic treatment durations to quantify current levels of overprescribing. Our results suggest that pooling the treatment recommendations (using the median) could improve guideline compliance in groups of three or more prescribers. Implications for antibiotic stewardship and the general improvement of medical decision making are discussed. Clinical applicability is likely to be greatest in the context of hospital ward rounds and larger, multidisciplinary team meetings, where complex patient cases are discussed and existing guidelines provide limited guidance.

Convolutional autoencoder and conditional random fields hybrid for predicting spatial-temporal chaos.

We present an approach for data-driven prediction of high-dimensional chaotic time series generated by spatially-extended systems. The algorithm employs a convolutional autoencoder for dimension reduction and feature extraction combined with a probabilistic prediction scheme operating in the feature space, which consists of a conditional random field. The future evolution of the spatially-extended system is predicted using a feedback loop and iterated predictions. The excellent performance of this method is illustrated and evaluated using Lorenz-96 systems and Kuramoto-Sivashinsky equations of different size generating time series of different dimensionality and complexity.

How to detect high-performing individuals and groups: Decision similarity predicts accuracy.

Distinguishing between high- and low-performing individuals and groups is of prime importance in a wide range of high-stakes contexts. While this is straightforward when accurate records of past performance exist, these records are unavailable in most real-world contexts. Focusing on the class of binary decision problems, we use a combined theoretical and empirical approach to develop and test a approach to this important problem. First, we use a general mathematical argument and numerical simulations to show that the similarity of an individual's decisions to others is a powerful predictor of that individual's decision accuracy. Second, testing this prediction with several large datasets on breast and skin cancer diagnostics, geopolitical forecasting, and a general knowledge task, we find that decision similarity robustly permits the identification of high-performing individuals and groups. Our findings offer a simple, yet broadly applicable, heuristic for improving real-world decision-making systems.

Immunological differences between insect venom-allergic patients with and without immunotherapy and asymptomatically sensitized subjects.

BACKGROUND: Currently available tests are unable to distinguish between asymptomatic sensitization and clinically relevant Hymenoptera venom allergy. A reliable serological marker to monitor venom immunotherapy (VIT) does also not exist. Our aim was to find reliable serological markers to predict tolerance to bee and vespid stings. METHODS: We included 77 asymptomatically sensitized subjects, 85 allergic patients with acute systemic sting reactions, and 61 allergic patients currently treated with VIT. Levels of sIgE and sIgG4 to bee and vespid venom, rApi m 1, and rVes v 5 were measured immediately after allergic sting reactions or before sting challenges and 4 weeks later. All sting challenges were tolerated. The inhibitory activity was determined using BAT inhibition and ELIFAB assay. RESULTS: Median sIgG4 levels were 96-fold higher in VIT patients (P < .001) while sIgE/sIgG4 ratios were consistently lower (P < .001). The ELIFAB assay was paralleled by low sIgE/sIgG4 ratios in VIT patients, showing markedly higher allergen-blocking capacity (P < .001). An almost complete inhibition of the basophil response was seen in all patients treated with vespid venom, but not in those treated with bee venom. Four weeks after the sting, sIgE and sIgG4 levels were increased in allergic and asymptomatically sensitized patients, but not in VIT patients. CONCLUSION: Immunological responses after stings varied in bee and vespid venom-allergic patients. In patients under VIT, sIgE and sIgG4 remained completely stable after sting challenges. Monitoring VIT efficacy was only possible in vespid venom allergy, and the sIgG4 threshold for rVes v 5 had the highest sensitivity to confirm tolerance. The BAT inhibition test was the most reliable tool to confirm tolerance on an individual basis.

Impact of grassland management regimes on bacterial endophyte diversity differs with grass species.

UNLABELLED: Most plant species are colonized by endophytic bacteria. Despite their importance for plant health and growth, the response of these bacteria to grassland management regimes is still not understood. Hence, we investigated the bacterial community structure in three agricultural important grass species Dactylis glomerata L., Festuca rubra L. and Lolium perenne L. with regard to fertilizer application and different mowing frequencies. For this purpose, above-ground plant material was collected from the Grassland Management Experiment (GrassMan) in Germany in September 2010 and 2011. DNA was extracted from surface-sterilized plant tissue and subjected to 16S rRNA gene PCRs. Endophytic community structures were assessed by denaturing gradient gel electrophoresis (DGGE)-based analysis of obtained PCR products. DGGE fingerprints revealed that fertilizer application significantly altered the endophytic communities in L. perenne and F. rubra but not in D. glomerata. Although no direct effect of mowing was observed, mowing frequencies in combination with fertilizer application had a significant impact on endophyte bacterial community structures. However, this effect was not observed for all three grass species in both years. Therefore, our results showed that management regimes changed the bacterial endophyte communities, but this effect was plant-specific and varied over time. SIGNIFICANCE AND IMPACT OF THE STUDY: Endophytic bacteria play an important role in plant health and growth. However, studies addressing the influence of grassland management regimes on these bacteria in above-ground plant parts are still missing. In this study, we present first evidence that fertilizer application significantly impacted bacterial community structures in three agricultural important grass species, whereas mowing had only a minor effect. Moreover, this effect was plant-specific and thus not visible for all grass species in each year. Consequently, this study sheds new light into the complex interaction of microbes and plants.

MAP3K11 is a tumor suppressor targeted by the oncomiR miR-125b in early B cells.

MicroRNAs (miRNAs) are a class of small, non-coding RNAs that posttranscriptionally regulate gene expression and thereby control most, if not all, biological processes. Aberrant miRNA expression has been linked to a variety of human diseases including cancer, but the underlying molecular mechanism often remains unclear. Here we have screened a miRNA expression library in a growth factor-dependent mouse pre-B-cell system to identify miRNAs with oncogenic activity. We show that miR-125b is sufficient to render pre-B cells growth factor independent and demonstrate that continuous expression of miR-125b is necessary to keep these cells in a transformed state. Mechanistically, we find that the expression of miR-125b protects against apoptosis induced by growth factor withdrawal, and that it blocks the differentiation of pre-B to immature B cells. In consequence, miR-125b-transformed cells maintain expression of their pre-B-cell receptor that provides signals for continuous proliferation and survival even in the absence of growth factor. Employing microarray analysis, we identified numerous targets of miR-125b, but only reconstitution of MAP3K11, a critical regulator of mitogen- and stress-activated kinase signaling, interferes with the cellular fitness of the transformed cells. Together, this indicates that MAP3K11 might function as an important tumor suppressor neutralized by oncomiR-125b in B-cell leukemia.

Conditional knockdown of BCL2A1 reveals rate-limiting roles in BCR-dependent B-cell survival.

Bcl2 family proteins control mitochondrial apoptosis and its members exert critical cell type and differentiation stage-specific functions, acting as barriers against autoimmunity or transformation. Anti-apoptotic Bcl2a1/Bfl1/A1 is frequently deregulated in different types of blood cancers in humans but its physiological role is poorly understood as quadruplication of the Bcl2a1 gene locus in mice hampers conventional gene targeting strategies. Transgenic overexpression of A1, deletion of the A1-a paralogue or constitutive knockdown in the hematopoietic compartment of mice by RNAi suggested rate-limiting roles in lymphocyte development, granulopoiesis and mast cell activation. Here we report on the consequences of conditional knockdown of A1 protein expression using a reverse transactivator (rtTA)-driven approach that highlights a critical role for this Bcl2 family member in the maintenance of mature B-cell homeostasis. Furthermore, we define the A1/Bim (Bcl-2 interacting mediator of cell death) axis as a target of key kinases mediating B-cell receptor (BCR)-dependent survival signals, such as, spleen tyrosine kinase (Syk) and Brutons tyrosine kinase (Btk). As such, A1 represents a putative target for the treatment of B-cell-related pathologies depending on hyperactivation of BCR-emanating survival signals and loss of A1 expression accounts, in part, for the pro-apoptotic effects of Syk- or Btk inhibitors that rely on the 'BH3-only' protein Bim for cell killing.

Maternal and neonatal outcomes in pregnant women with PCOS: comparison of different diagnostic definitions.

STUDY QUESTION: Does the prevalence of adverse maternal and neonatal outcomes vary in women diagnosed with polycystic ovary syndrome (PCOS) according to different definitions? SUMMARY ANSWER: A comparison of different criteria revealed that there is a substantial risk for perinatal complications in PCOS women, regardless of the used definition. WHAT IS KNOWN ALREADY: Pregnant women with PCOS are susceptible to perinatal complications. At present, there are three main definitions for PCOS. So far, we are aware of only one study, which found that the elevated risk for complications varied widely depending on the different phenotypes and features but only considered a relatively small sample size for some of the phenotypes. STUDY DESIGN, SIZE, DURATION: Retrospective matched cohort study. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data of primiparous women with PCOS according to ESHRE/ASRM 2003 criteria and healthy controls giving birth to neonates ≥500 g were included. A total of 885 women were analysed: out of 177 women with PCOS, 85 (48.0%) met the National Institutes of Health (NIH) 1990 criteria, another 14 (7.9%) featured the additional phenotypes defined by The Androgen Excess and PCOS Society (AE-PCOS) 2006 criteria, 78 (44.1%) were classified as PCOS exclusively by the ESHRE/ASRM 2003 definition, and 708 represented the control group. MAIN RESULTS AND THE ROLE OF CHANCE: The prevalence of adverse maternal (49.4 versus 64.3 versus 60.3%, P = 0.313) and neonatal (27.1 versus 35.7 versus 23.1%, P = 0.615) outcomes did not differ within the three PCOS groups (ESHRE/ASRM, NIH, AE-PCOS, respectively). Compared with healthy controls, the risk for maternal complications was increased in PCOS patients [odds ratio (OR) 2.57; 95% confidence interval (CI) 1.82-3.64; P < 0.001] while there was no difference in neonatal complications (OR 0.83; 95% CI 0.56-1.21; P = 0.343). LIMITATIONS, REASONS FOR CAUTION: A limitation of our study is its retrospective design and the relatively small sample size, particularly in the AE-PCOS subgroup. WIDER IMPLICATIONS OF THE FINDINGS: Since women with PCOS have, regardless of the used definition, a high risk of maternal and neonatal complications they should be informed and advised to follow regular checks in units where problems can be detected early to allow specialized care. STUDY FUNDING/COMPETING INTERESTS: Marietta Blau Grant (Austrian Agency for International Cooperation in Education and Research; OeAD-GmbH) and mobility scholarship (Medical University of Graz).