Miracle-dz/UniFAR-FTUs huggingface dataset:
Allergic reactions to small-molecule drugs: Will we move from reaction to prediction?

PURPOSE This primer provides background and an update on immune mechanisms which allow small-molecule drugs to trigger drug allergy. SUMMARY For many years, understanding of drug allergy was limited. The hapten model of drug allergy applies only to a subset of drugs known to cause allergic reactions. More recently, the understanding of immune reactions has expanded to include pharmacologic interactions with the molecules involved in immune identity and surveillance. These insights are presented and discussed here. CONCLUSION Greater understanding of allergic reactions to drugs offers the promise to move from a position of reacting to immune reactions to a more proactive model. This may translate to new opportunities to characterize risk in drug development, confirm the nature of reactions in clinical settings, enhance the targeting of alerts, and ultimately to allow patient-specific prediction.
The development of autoimmune thyroiditis in rabbits following injection of aqueous preparations of heterologous thyroglobulins.

Injection of rabbits with certain aqueous preparations of heterologous thyroglobulin results in the production of both thyroiditis and antibody to rabbit thyroglobulin. Injections of bovine and human thyroglobulin were effective, whereas injections of porcine thyroglobulin were relatively ineffective. Injections of a mixture of several thyroglobulins were more effective than injections of individual thyroglobulins. The thyroid lesions which developed in some of the rabbits injected with the mixture were very extensive, involving most of the thyroid tissue. Rabbits immunized with bovine thyroglobulin were responsive to injections of rabbit thyroglobulin given as late as 5 months after the injections of bovine thyroglobulin. However, the ability of these rabbits to respond to rabbit thyroglobulin decreased with time. The antibody produced as a result of the subsequent injections of rabbit thyroglobulin was directed to only the determinants on rabbit thyroglobulin related to determinants on bovine thyroglobulin. The similarities between the induction of autoimmune thyroiditis and termination of acquired immunologic unresponsiveness following injections of cross-reacting and altered antigens are discussed.
Dose-Dependent Immunomodulation of Human Dendritic Cells by the Probiotic Lactobacillus rhamnosus Lcr35

The response of the immune system to probiotics remains controversial. Some strains modulate the cytokine production of dendritic cells (DCs) in vitro and induce a regulatory response, while others induce conversely a pro-inflammatory response. These strain-dependent effects are thought to be linked to specific interactions between bacteria and pattern recognition receptors. We investigated the effects of a well characterized probiotic strain, Lactobacillus rhamnosus Lcr35, on human monocyte-derived immature DCs, using a wide range of bacterial concentrations (multiplicity of infection, MOI, from 0.01 to 100). DNA microarray and qRT-PCR analysis showed that the probiotic induced a large-scale change in gene expression (nearly 1,700 modulated genes, with 3-fold changes), but only with high doses (MOI, 100). The upregulated genes were mainly involved in immune response and identified a molecular signature of inflammation according to the model of Torri. Flow cytometry analysis also revealed a dose-dependent maturation of the DC membrane phenotype, until DCs reached a semi-mature state, with an upregulation of the membrane expression of CD86, CD83, HLA-DR and TLR4, associated with a down-regulation of DC-SIGN, MR and CD14. Measurement of the DC-secreted cytokines showed that Lcr35 induced a strong dose-dependent increase of the pro-Th1/Th17 cytokine levels (TNFα, IL-1β, IL-12p70, IL-12p40 and IL-23), but only a low increase in IL-10 concentration. The probiotic L. rhamnosus Lcr35 therefore induce a dose-dependent immunomodulation of human DCs leading, at high doses, to the semi-maturation of the cells and to a strong pro-inflammatory effect. These results contribute to a fuller understanding of the mechanism of action of this probiotic, and thus of its potential clinical indications in the treatment of either infectious or IgE-dependent allergic diseases.
Fault Ride Through Certification of Wind Turbines Based on a Hardware in the Loop Setup

This publication presents a practical experience in implementing fault ride through investigations on a multiphysics power hardware in the loop platform for wind turbine nacelles. Next to the aim of doing full-scale system investigations with the nacelle, the use for system certification is included in the planning. While it is quite clear that such an approach would bring significant advantages compared with in-field testing, it is also important to understand if it is possible to overcome all the challenges from a practical and, in particular, measurement point of view that system level test bench certification implies. This question is analyzed with the support a unique platform developed by the authors in collaboration with other researchers of RWTH Aachen University. The platform is able to support test activities up to 1 MW.
The Product Flow Model

We observed a new approach being adopted in the software industry that combines a business model with a specific structure of technical support. This Product Flow Model (PFM) combines aspects of the Product Line model with workflow concepts for virtual enterprises. To sustain software in an enterprise requires several categories of maintenance. Today enterprises acquire most general purpose software from outside suppliers, rather than writing such software in-house, reducing total software acquisition costs. This paper considers how maintenance of acquired software should be provided. When the enterprise assigns maintenance of acquired software to its internal information technology (IT) operations for software then little overall long-term cost reduction is been achieved, since over its lifetime the maintenance of software consumes 70 to 90% of total software costs. An alternative is that the software supplier also provides the ongoing maintenance to the customer. The PFM defines in more detail such a business model that is beneficial to the supplier as well as to the customer. For the product flow model to be effective there must be an effective information flow expressing the needs of the customer to the software supplier. We perceive three classes of needs, leading to corrective, adaptive, and perfective maintenance, each requiring distinct feedback mechanisms. These mechanisms represent control loops inducing system stability. Software suppliers that operate within the PFM can be assured of substantial continuing income and great customer loyalty. We will elaborate both on the information flow and on technologies needed to be successful in PFM services.
Compartmentation of Fyn Kinase with Glycosylphosphatidylinositol-anchored Molecules in Oligodendrocytes Facilitates Kinase Activation during Myelination*

In many cell types, glycosylphosphatidylinositol (GPI)-anchored proteins are sequestered in detergent-resistant membrane rafts. These are plasma membrane microdomains enriched in glycosphingolipids and cholesterol and are suggested to be platforms for cell signaling. Concomitant with the synthesis of myelin glycosphingolipids, maturing oligodendrocytes progressively associate GPI-anchored proteins, including the adhesion molecules NCAM 120 and F3, in rafts. Here we show that these microdomains include Fyn and Lyn kinases. Both kinases are maximally active in myelin prepared from young animals, correlating with early stages of myelination. In the rafts, Fyn kinase is tightly associated with NCAM 120 and F3. In contrast, in oligodendrocyte progenitor cells lacking rafts or in raft-free membrane domains of more mature cells, F3 does not associate with Fyn. The addition of anti-F3 antibodies to oligodendrocytes results in stimulation of Fyn kinase specifically in rafts. Compartmentation of oligodendrocyte GPI-anchored proteins in rafts is thus a prerequisite for association with Fyn, permitting kinase activation. Interaction of oligodendrocyte F3 with axonal ligands such as L1 and ensuing kinase activation may play a crucial role in initiating myelination.
Adipocyte Precursors : Developmental Origins , Self-Renewal , and Plasticity

M.E. Symonds (ed.), Adipose Tissue Biology, DOI 10.1007/978-1-4614-0965-6_1, © Springer Science+Business Media, LLC 2012 Abstract The current epidemic of obesity and overweight has caused a surge of interest in the study of adipose tissue formation. Much progress has been made in defi ning the transcriptional networks controlling the terminal differentiation of preadipocytes into mature adipocytes. However, the early steps that direct mesenchymal stem cells down the adipocyte lineage remain largely unknown. Similarly, the study of the developmental origin of adipocytes during embryogenesis has been largely disregarded until now. This review summarizes the surprising fi ndings that have recently emerged from in vivo lineage tracing studies, unraveling unsuspected developmental origins for white adipocytes. We will propose that the differential origin of adipocytes could also refl ect functional differences and site-specifi c regulations of adipose tissue. This chapter also reports recent work that has led to the identifi cation of discrete immature cell populations from which white adipocytes are derived in mice. A pool of adipocyte progenitors remains present in adipose tissue during adult life. This pool is responsible for the renewal of adipocytes and the potential of this tissue to expand in response to chronic energy overload. However, factors controlling proliferation and differentiation of human adipocyte progenitors are largely unknown. We will present stem cells derived from human adipose tissue (human Multipotent Adipose tissue Derived Stem (hMADS) cells) for studying proliferation and differentiation of adipocyte progenitors and will show that fi broblast growth factor 2 and activin A are key regulators of human adipocyte precursor self-renewal. Finally, we will discuss about the plasticity of hMADS cells.
Exact Learning of Bounded Tree-width Bayesian Networks

Inference in Bayesian networks is known to be NP-hard, but if the network has bounded treewidth, then inference becomes tractable. Not surprisingly, learning networks that closely match the given data and have a bounded tree-width has recently attracted some attention. In this paper we aim to lay groundwork for future research on the topic by studying the exact complexity of this problem. We give the first non-trivial exact algorithm for the NP-hard problem of finding an optimal Bayesian network of tree-width at most w, with running time 3 n n w+O(1) , and provide an implementation of this algorithm. Additionally, we propose a variant of Bayesian network learning with “super-structures”, and show that finding a Bayesian network consistent with a given super-structure is fixedparameter tractable in the tree-width of the super-structure.
Distributed Immersive Virtual Reality Simulation Development for Medical Education

Training professionals for real-world application of required knowledge and skills and assessing their competence are major challenges. Simulations are being used in education and training to enhance understanding, improve performance, and assess competence. Validated virtual reality (VR) simulations provide a means of making experiential learning reproducible and reusable. Advanced communication networks, such as Internet2 Access Grid, allow dissemination of these simulations and collaborative learning independent of distance. The prior experiences of our three universities led to an interdisciplinary collaboration to further develop and evaluate an integrated, fully immersive, interactive VR based system. This environment employs simulations that are visually three-dimensional and are driven dynamically by a rules-based artificial intelligence engine within Flatland, a virtual environments development software tool, and associated commodity hardware. Studies include usability and validation, deployment for distributed testing over Internet2, and evaluation of impact on training and performance using concept mapping and knowledge structure methods. Subject matter experts found face and content validity in our closed head injury simulation. Seven pairs of medical students participated collaboratively in problem solving and managing of the simulated patient in VR. Students stated that opportunities to make mistakes and repeat actions in VR were extremely helpful in learning specific principles and they felt more engaged than in standard text-based scenarios. 48 students participated in knowledge structure experiments pre and post simulation experiences. Knowledge structure relatedness ratings were significantly improved in those students with lower pre-VR relatedness ratings indicating a potential value of VR simulation in learning. This research cuts across the integration of computing, networking, human-computer interfaces, learning, and knowledge acquisition. VR creates a safe environment to make mistakes and could allow rapid deployment for just-in-time training or performance assessment.
Vascular endothelial growth factor-C expression and its relationship to pelvic lymph node status in invasive cervical cancer

Vascular endothelial growth factor-C (VEGF-C) has been implicated in lymphangiogenesis, the process of new lymphatics formation. The present study investigated VEGF-C mRNA expression in invasive cervical cancer tissue. Additionally, the association of VEGF-C mRNA with clinicopathological features was examined. VEGF-C mRNA expression was assessed by reverse transcription-polymerase chain reaction using β-action as an internal control. 75 patients presenting with invasive cervical cancer were included in the trial. VEGF-C mRNA expression was markedly higher in tumours in which pelvic lymph node metastasis was diagnosed by magnetic resonance (MR) imaging (P = 0.002). 53 patients displaying stage Ib–IIb cervical cancer underwent radical hysterectomy and pelvic lymphadenectomy. VEGF-C expression was significantly higher in tumours exhibiting deep stromal invasion, pelvic lymph node metastasis and lymph-vascular space involvement (P = 0.016, P = 0.006 and P = 0.036, respectively). Multivariate analysis revealed VEGF-C mRNA expression to be the sole independent factor influencing pelvic lymph node metastasis. Subjects demonstrating VEGF-C mRNA expression displayed significantly poorer prognoses than those lacking VEGF-C mRNA expression (P = 0.049). These findings provide evidence supporting the involvement of VEGF-C expression in the promotion of lymph node metastasis in cervical cancer. Furthermore, examination of VEGF-C expression in biopsy specimens may be beneficial in the prediction of pelvic lymph node metastasis. © 2001 Cancer Research Campaign http://www.bjcancer. com
Poster: AR-based social presence enhancement in video-chat communication

Video-mediated communication systems attempt to provide users with a channel that could bring out the “feeling” of face-to-face communication. Among the many qualities these systems aim for, a high level of Social Presence is unquestionably a desirable one; however, little effort has been made to improve upon the user's perception of “presence”. We propose an AR approach to enhance social presence for video-mediated systems by allowing one user to be present in the other user's video image. By using one extra camera on both sides, our system captures and merges the hand image from/to both sides resulting in an augmented experience where each user can “reach” to the other user's world. We conducted a preliminary pilot study with 10 participants coupled in 5 pairs in order to evaluate our system compared to the traditional video-chat setup. Tasks with varying equality of roles for the participants were performed. Results indicated that our system has higher degree of social presence compared to traditional video-chat systems. This conclusion was supported by the positive feedback from the subjects.
Estradiol Attenuates Ischemia-Induced Death of Hippocampal Neurons and Enhances Synaptic Transmission in Aged, Long-Term Hormone-Deprived Female Rats

Background Transient global forebrain ischemia causes selective, delayed death of hippocampal CA1 pyramidal neurons, and the ovarian hormone 17β-estradiol (E2) reduces neuronal loss in young and middle-aged females. The neuroprotective efficacy of E2 after a prolonged period of hormone deprivation is controversial, and few studies examine this issue in aged animals given E2 treatment after induction of ischemia. Methodology/Principal Findings The present study investigated the neuroprotective effects of E2 administered immediately after global ischemia in aged female rats (15–18 months) after 6 months of hormone deprivation. We also used electrophysiological methods to assess whether CA1 synapses in the aging hippocampus remain responsive to E2 after prolonged hormone withdrawal. Animals were ovariohysterectomized and underwent 10 min global ischemia 6 months later. A single dose of E2 (2.25 µg) infused intraventricularly after reperfusion significantly increased cell survival, with 45% of CA1 neurons surviving vs 15% in controls. Ischemia also induced moderate loss of CA3/CA4 pyramidal cells. Bath application of 1 nM E2 onto brain slices derived from non-ischemic aged females after 6 months of hormone withdrawal significantly enhanced excitatory transmission at CA1 synapses evoked by Schaffer collateral stimulation, and normal long-term potentiation (LTP) was induced. The magnitude of LTP and of E2 enhancement of field excitatory postsynaptic potentials was indistinguishable from that recorded in slices from young rats. Conclusions/Significance The data demonstrate that 1) acute post-ischemic infusion of E2 into the brain ventricles is neuroprotective in aged rats after 6 months of hormone deprivation; and 2) E2 enhances synaptic transmission in CA1 pyramidal neurons of aged long-term hormone deprived females. These findings provide evidence that the aging hippocampus remains responsive to E2 administered either in vivo or in vitro even after prolonged periods of hormone withdrawal.
[Palliative HDR and PDR brachytherapy in treatment of head and neck cancer relapses].

The preliminary results of palliative HDR and PDR brachytherapy in head and cancer relapses were presented. 47 patients with locoregional recurrenceses were treated by means of HDR and PDR brachytherapy between 05.06. 2001 and 31.12. 2002 in Great Poland Cancer Center and ENT Dept. K. Marcinkowski University of Medical Sciences. All patients were rejected from salvage surgery or distant field irradiation because of tumor advancement and previous treatment. The mean time of the recurrence after the diagnosing of the disease and first treatment was 9, 7 month. 34 patients were treated by the means of the HDR brachytherapy with the 5 doses of 4 Gy per fraction, 13 patients were treated by the means of the PDR brachytherapy with the one stage treatment (9 doses) or two stage treatment (4 doses) with total dose ranged between 20-40 Gy. The remission after 1, 3, 6 months after treatment and early complications were assessed. In 7 (15%) patients complete remission (CR), in 31 (65.9%) partial remission (PR) and in 5 (10.6) no response for the brachytherapy (NR) were stated; in the other 4 (8.5%) patients there were progression of the tumor. Percentages of remission after 3 and 6 months were as follows: CR - 5 (10.6%) and 3 (6.4%), PR - 25 (53.2%) and 17 (36.2%), NR and Progr - 17 (36.2%) and 27 (57.4)%. In 35 (74.5%) cases superficial necrosis was observed in 6 month time. The both methods had similar percentages of side effects. HDR or PDR brachytherapy are effective method of palliative treatment in head and neck cancer relapses. Early complications are frequent and demands intensive pharmacological treatment.
Learning from data streams and class imbalance

With the wide application of machine learning algorithms to the real world, class imbalanceandconceptdrift havebecomecrucial learning issues. Applications in variousdomains such as riskmanagement, anomaly detection, fraud detection, software engineering, social media mining, and recommender systems are affected by both class imbalance and concept drift. Class imbalance happens when the data categories are not equally represented, i.e., at least one category isminority compared toother categories. It can cause learningbias towards the majority class and poor generalisation. Concept drift is a change in the underlying distribution of the problem and is a significant issue specially when learning from data streams. It requires learners to be adaptive to dynamic changes. Class imbalance and concept drift can significantly hinder predictive performance. The problem becomes particularly challengingwhen they occur simultaneously, due to the fact that one problem can affect the treatment of the other. This special issue is composed of four high-quality papers studying the challenges andproposing new solutions for learning fromdata effectively and efficiently in the presence of class imbalance or concept drift. Resampling is the most popular set of techniques to overcome class imbalance in data. One-class learning methods can also be effective on imbalanced data. In the paper “Learning in Presence of Class Imbalance and Class Overlapping by Using One-class SVM and Undersampling Technique”, the authors proposed to use both undersampling and oneclass learning to preprocess data. One-class SVM is used to detect overlapping regions, and Tomek-link is used to further clean up the overlapping data and balance the data set. The proposed method is compared with other six state-of-the-art methods over seven binary and twomulti-class data sets, showingbetter accuracy onminority classeswithout harming majority-class accuracy. Different fromdata-level techniques and cost-sensitivemethods, the paper “AWeighted Pattern Matching Approach for Classification of Imbalanced Data with a Fireworks Based Algorithm for Feature Selection” proposed a novel weighted pattern matching method to classify imbalanced data, combining fireworks algorithms to select the best set of features for learning. The experiment was performed on 44 binary and 15multi-class data sets with class imbalance difficulty. The proposedmethod showed competitive performance in comparison with other state-of-the-art methods. As mentioned earlier, the class imbalance issue exists in many real-world applications. In the paper “Semantic Segmentation of High Resolution Remote Sensing Images Using Fully Convolutional Networkwith Adaptive Threshold”, the class imbalance issue in semantic segmentation is studied. Semantic segmentation is a multi-class classification problem in remote sensing. To overcome class imbalance, a fully convolutional neural network with an adaptive threshold of the Jaccard index is proposed. The experimental results showed superior classification performance on remote sensing images.
Channel Estimation Using 1-Bit Quantization and Oversampling for Large-scale Multiple-antenna Systems

Large-scale multiple-antenna systems have been identified as a promising technology for the next generation of wireless systems. However, by scaling up the number of receive antennas the energy consumption will also increase. One possible solution is to use low-resolution analog-to-digital converters at the receiver. This paper considers large-scale multiple-antenna uplink systems with 1-bit analog-to-digital converters on each receive antenna. Since oversampling can partially compensate for the information loss caused by the coarse quantization, the received signals are firstly oversampled by a factor M. We then propose a low-resolution aware linear minimum mean-squared error channel estimator for 1-bit oversampled systems. Moreover, we characterize analytically the performance of the proposed channel estimator by deriving an upper bound on the Bayesian Cramér-Rao bound. Numerical results are provided to illustrate the performance of the proposed channel estimator.