Miracle-dz/UniFAR-FTUs huggingface dataset:
A chromosomally integrated bacteriophage in invasive meningococci

Cerebrospinal meningitis is a feared disease that can cause the death of a previously healthy individual within hours. Paradoxically, the causative agent, Neisseria meningitidis, is a common inhabitant of the human nasopharynx, and as such, may be considered a normal, commensal organism. Only in a small proportion of colonized people do the bacteria invade the bloodstream, from where they can cross the blood–brain barrier to cause meningitis. Furthermore, most meningococcal disease is caused by bacteria belonging to only a few of the phylogenetic groups among the large number that constitute the population structure of this genetically variable organism. However, the genetic basis for the differences in pathogenic potential remains elusive. By performing whole genome comparisons of a large collection of meningococcal isolates of defined pathogenic potential we brought to light a meningococcal prophage present in disease-causing bacteria. The phage, of the filamentous family, excises from the chromosome and is secreted from the bacteria via the type IV pilin secretin. Therefore, this element, by spreading among the population, may promote the development of new epidemic clones of N. meningitidis that are capable of breaking the normal commensal relationship with humans and causing invasive disease.
Ontology-based annotations and semantic relations in large-scale (epi)genomics data

Abstract Public repositories of large-scale biological data currently contain hundreds of thousands of experiments, including high-throughput sequencing and microarray data. The potential of using these resources to assemble data sets combining samples previously not associated is vastly unexplored. This requires the ability to associate samples with clear annotations and to relate experiments matched with different annotation terms. In this study, we illustrate the semantic annotation of Gene Expression Omnibus samples metadata using concepts from biomedical ontologies, focusing on the association of thousands of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) samples with a given target, tissue and disease state. Next, we demonstrate the feasibility of quantitatively measuring the semantic similarity between different samples, with the aim of combining experiments associated with the same or similar semantic annotations, thus allowing the generation of large data sets without the need of additional experiments. We compared tools based on Unified Medical Language System with tools that use topic-specific ontologies, showing that the second approach outperforms the first both in the annotation process and in the computation of semantic similarity measures. Finally, we demonstrated the potential of this approach by identifying semantically homogeneous groups of ChIP-seq samples targeting the Myc transcription factor, and expanding this data set with semantically coherent epigenetic samples. The semantic information of these data sets proved to be coherent with the ChIP-seq signal and with the current knowledge about this transcription factor.
Independent component analysis in angiography images

An important source for information about digital image content is the texture of image regions. This paper presents a feature extraction approach that is based on independent component analysis (ICA). In ICA a transformation of measured vectored time series is discovered via blind signal processing that gives statistically indep endent source signals. In our approach every textured region is considered as a mixture of (initial ly unknown) statistically independent source regions, scanned to 1-D time series. After these sources, called independent components, are extracted by ICA, optimally for given image type, the mixing coefficients of particular region constitute its feature vector. The quality of such feat ures is experimentally verified and compared to other common feature schemas. The comparison procedure explores the Fisher information criterion and classification results for featu re evaluation. Our application field is the analysis of angiography images. It is difficult for medic al doctors properly to classify such images, hence an automatic tool could provide support in this matter. We demonstrate the usefulness of ICA-based features for automatic evaluation of angiography images
Combining Symbolic Execution and Model Checking to Verify MPI Programs

Message Passing Interface (MPI) has become the standard programming paradigm in high performance computing. It is challenging to verify MPI programs because of high parallelism and non-determinism. This paper presents MPI symbolic verifier (MPI-SV), the first symbolic execution based tool for verifying MPI programs having both blocking and non-blocking operations. MPI-SV exploits symbolic execution to automatically generate path-level models, and performs model checking on the models w.r. t. expected properties. The results of model checking are leveraged to prune redundant paths. We have implemented MPI-SV and the extensive evaluation demonstrates MPI-SV's effectiveness and efficiency.
Dictionary learning for spontaneous neural activity modeling

Modeling the activity of an ensemble of neurons can provide critical insights into the workings of the brain. In this work we examine if learning based signal modeling can contribute to a high quality modeling of neuronal signal data. To that end, we employ the sparse coding and dictionary learning schemes for capturing the behavior of neuronal responses into a small number of representative prototypical signals. Performance is measured by the reconstruction quality of clean and noisy test signals, which serves as an indicator of the generalization and discrimination capabilities of the learned dictionaries. To validate the merits of the proposed approach, a novel dataset of the actual recordings from 183 neurons from the primary visual cortex of a mouse in early postnatal development was developed and investigated. The results demonstrate that high quality modeling of testing data can be achieved from a small number of training examples and that the learned dictionaries exhibit significant specificity when introducing noise.
Designing a pain management protocol for craniotomy: A narrative review and consideration of promising practices

Background: Craniotomy is a relatively common surgical procedure with a high incidence of postoperative pain. Development of standardized pain management and enhanced recovery after surgery (ERAS) protocols are necessary and crucial to optimize outcomes and patient satisfaction and reduce health care costs. Methods: This work is based upon a literature search of published manuscripts (between 1996 and 2017) from Pubmed, Cochrane Central Register, and Google Scholar. It seeks to both synthesize and review our current scientific understanding of postcraniotomy pain and its part in neurosurgical ERAS protocols. Results: Strategies to ameliorate craniotomy pain demand interventions during all phases of patient care: preoperative, intraoperative, and postoperative interventions. Pain management should begin in the perioperative period with risk assessment, patient education, and premedication. In the intraoperative period, modifications in anesthesia technique, choice of opioids, acetaminophen and nonsteroidal anti-inflammatory drugs (NSAIDs), regional techniques, dexmedetomidine, ketamine, lidocaine, corticosteroids, and interdisciplinary communication are all strategies to consider and possibly deploy. Opioids remain the mainstay for pain relief, but patient-controlled analgesia, NSAIDs, standardization of pain management, bio/behavioral interventions, modification of head dressings as well as patient-centric management are useful opportunities that potentially improve patient care. Conclusions: Future research on mechanisms, predictors, treatments, and pain management pathways will help define the combinations of interventions that optimize pain outcomes.
Beamforming Design for Joint Localization and Data Transmission in Distributed Antenna System

A distributed antenna system whose goal is to provide data communication and positioning functionalities to mobile stations (MSs) is studied. Each MS receives data from a number of base stations (BSs) and uses the received signal not only to extract the information but to determine its location as well. This is done based on time-of-arrival or time-difference-of-arrival measurements, depending on the assumed synchronization conditions. The problem of minimizing the overall power expenditure of the BSs under data throughput and localization accuracy requirements is formulated with respect to the beamforming vectors used at the BSs. The analysis covers both frequency-flat and frequency-selective channels and accounts for robustness constraints in the presence of parameter uncertainty as well. The proposed algorithmic solutions are based on rank-relaxation and difference-of-convex programming.
Visually Evoked Visual-Auditory Changes Associated with Auditory Performance in Children with Cochlear Implants

Activation of the auditory cortex by visual stimuli has been reported in deaf children. In cochlear implant (CI) patients, a residual, more intense cortical activation in the frontotemporal areas in response to photo stimuli was found to be positively associated with poor auditory performance. Our study aimed to investigate the mechanism by which visual processing in CI users activates the auditory-associated cortex during the period after cochlear implantation as well as its relation to CI outcomes. Twenty prelingually deaf children with CI were recruited. Ten children were good CI performers (GCP) and ten were poor (PCP). Ten age- and sex- matched normal-hearing children were recruited as controls, and visual evoked potentials (VEPs) were recorded. The characteristics of the right frontotemporal N1 component were analyzed. In the prelingually deaf children, higher N1 amplitude was observed compared to normal controls. While the GCP group showed significant decreases in N1 amplitude, and source analysis showed the most significant decrease in brain activity was observed in the primary visual cortex (PVC), with a downward trend in the primary auditory cortex (PAC) activity, but these did not occur in the PCP group. Meanwhile, higher PVC activation (comparing to controls) before CI use (0M) and a significant decrease in source energy after CI use were found to be related to good CI outcomes. In the GCP group, source energy decreased in the visual-auditory cortex with CI use. However, no significant cerebral hemispheric dominance was found. We supposed that intra- or cross-modal reorganization and higher PVC activation in prelingually deaf children may reflect a stronger potential ability of cortical plasticity. Brain activity evolution appears to be related to CI auditory outcomes.
Review Paper: Friction Stir Welding (FSW)

Friction stir Welding is the type of welding used as a solid state joining process for materials that is different alloys of aluminum, magnesium etc. and also for hard materials like steels because it avoids the common problems obtained in conventional welding processes. The fact that joining of alloys could be usually faced problems in many sectors that includes automotive, aerospace, ship building industries, electronics etc. where fusion welding is not possible due to large difference in physical and chemical properties of the components to be joined. Difficulties in conventional welding processes is porosity formation, solidification cracking, and chemical reaction may arise during welding of dissimilar materials although sound welds may be obtained in some limited cases with special attentions to the joint design and preparation, process parameters and filler metals.
MeasuRouting: A Framework for Routing Assisted Traffic Monitoring

Monitoring transit traffic at one or more points in a network is of interest to network operators for reasons of traffic accounting, debugging or troubleshooting, forensics, and traffic engineering. Previous research in the area has focused on deriving a placement of monitors across the network toward the end of maximizing the monitoring utility of the network operator for a given traffic routing. However, both traffic characteristics and measurement objectives can dynamically change over time, rendering a previously optimal placement of monitors suboptimal. It is not feasible to dynamically redeploy/reconfigure measurement infrastructure to cater to such evolving measurement requirements. We address this problem by strategically routing traffic subpopulations over fixed monitors. We refer to this approach as MeasuRouting. The main challenge for MeasuRouting is to work within the constraints of existing intradomain traffic engineering operations that are geared for efficiently utilizing bandwidth resources, or meeting quality-of-service (QoS) constraints, or both. A fundamental feature of intradomain routing, which makes MeasuRouting feasible, is that intradomain routing is often specified for aggregate flows. MeasuRouting can therefore differentially route components of an aggregate flow while ensuring that the aggregate placement is compliant to original traffic engineering objectives. In this paper, we present a theoretical framework for MeasuRouting. Furthermore, as proofs of concept, we present synthetic and practical monitoring applications to showcase the utility enhancement achieved with MeasuRouting.
Comparison of a newly established emotional stimulus approach to a classical assessment-driven approach in BLS training: a randomised controlled trial

Objective The study objective was to implement two strategies (short emotional stimulus vs announced practical assessment) in the teaching of resuscitation skills in order to evaluate whether one led to superior outcomes. Setting This study is an educational intervention provided in one German academic university hospital. Participants First-yearmedical students (n=271) during the first3 weeks of their studies. Interventions Participants were randomly assigned to one of two groups following a sequence of random numbers: the emotional stimulus group (EG) and the assessment group (AG). In the EG, the intervention included watching an emotionally stimulating video prior to the Basic Life Support (BLS) course. In the AG, a practical assessment of the BLS algorithm was announced and tested within a 2 min simulated cardiac arrest scenario. After the baseline testing, a standardised BLS course was provided. Evaluation points were defined 1 week and 6 months after. Primary outcome measures Compression depth (CD) and compression rate (CR) were recorded as the primary endpoints for BLS quality. Results Within the study, 137 participants were allocated to the EG and 134 to the AG. 104 participants from EG and 120 from AG were analysed1 week after the intervention, where they reached comparable chest-compression performance without significant differences (CR P=0.49; CD P=0.28). The chest-compression performance improved significantly for the EG (P<0.01) and the AG (P<0.01) while adhering to the current resuscitation guidelines criteria for CD and CR. Conclusions There was no statistical difference between both groups’ practical chest-compression-performance. Nevertheless, the 2 min video sequence used in the EG with its low production effort and costs, compared with the expensive assessment approach, provides broad opportunities for applicability in BLS training.
Suppression of allergic airway inflammation by helminth-induced regulatory T cells

Allergic diseases mediated by T helper type (Th) 2 cell immune responses are rising dramatically in most developed countries. Exaggerated Th2 cell reactivity could result, for example, from diminished exposure to Th1 cell–inducing microbial infections. Epidemiological studies, however, indicate that Th2 cell–stimulating helminth parasites may also counteract allergies, possibly by generating regulatory T cells which suppress both Th1 and Th2 arms of immunity. We therefore tested the ability of the Th2 cell–inducing gastrointestinal nematode Heligmosomoides polygyrus to influence experimentally induced airway allergy to ovalbumin and the house dust mite allergen Der p 1. Inflammatory cell infiltrates in the lung were suppressed in infected mice compared with uninfected controls. Suppression was reversed in mice treated with antibodies to CD25. Most notably, suppression was transferable with mesenteric lymph node cells (MLNC) from infected animals to uninfected sensitized mice, demonstrating that the effector phase was targeted. MLNC from infected animals contained elevated numbers of CD4+CD25+Foxp3+ T cells, higher TGF-β expression, and produced strong interleukin (IL)-10 responses to parasite antigen. However, MLNC from IL-10–deficient animals transferred suppression to sensitized hosts, indicating that IL-10 is not the primary modulator of the allergic response. Suppression was associated with CD4+ T cells from MLNC, with the CD4+CD25+ marker defining the most active population. These data support the contention that helminth infections elicit a regulatory T cell population able to down-regulate allergen induced lung pathology in vivo.
Mutational Evidence for the Critical Role of CBF Transcription Factors in Cold Acclimation in Arabidopsis1

The three CBF genes are essential for freezing tolerance and affect seedling development and salt tolerance. The three tandemly arranged CBF genes, CBF1, CBF2, and CBF3, are involved in cold acclimation. Due to the lack of stable loss-of-function Arabidopsis (Arabidopsis thaliana) mutants deficient in all three CBF genes, it is still unclear whether the CBF genes are essential for freezing tolerance and whether they may have other functions besides cold acclimation. In this study, we used the CRISPR/Cas9 system to generate cbf single, double, and triple mutants. Compared to the wild type, the cbf triple mutants are extremely sensitive to freezing after cold acclimation, demonstrating that the three CBF genes are essential for cold acclimation. Our results show that the three CBF genes also contribute to basal freezing tolerance. Unexpectedly, we found that the cbf triple mutants are defective in seedling development and salt stress tolerance. Transcript profiling revealed that the CBF genes regulate 414 cold-responsive (COR) genes, of which 346 are CBF-activated genes and 68 are CBF-repressed genes. The analysis suggested that CBF proteins are extensively involved in the regulation of carbohydrate and lipid metabolism, cell wall modification, and gene transcription. Interestingly, like the triple mutants, cbf2 cbf3 double mutants are more sensitive to freezing after cold acclimation compared to the wild type, but cbf1 cbf3 double mutants are more resistant, suggesting that CBF2 is more important than CBF1 and CBF3 in cold acclimation-dependent freezing tolerance. Our results not only demonstrate that the three CBF genes together are required for cold acclimation and freezing tolerance, but also reveal that they are important for salt tolerance and seedling development.
Evaluation of Two-Diabetes Related microRNAs Suitability as Earlier Blood Biomarkers for Detecting Prediabetes and type 2 Diabetes Mellitus

Increased the incidence of prediabetes and type 2 diabetes (T2D) worldwide raises an urgent need to develop effective tools for early disease detection to facilitate future preventive interventions and improve patient’s care. We evaluated the suitability of diabetes-related miR-375 and miR-9 as earlier biomarkers for detecting prediabetes and T2D.TaqMan-based RT-qPCR was used to quantify the expression of miRNAs in peripheral blood of 30 prediabetes patients, 30 T2D patients and 30 non-diabetic healthy controls. Compared to controls, miR-375 and miR-9 were expressed at higher levels in prediabetes patients and progressively more enriched in T2D patients. Both miRNAs were directly associated with the presence of prediabetes and T2D independently of known risk factors to T2D and miR-375 was independently associated with the development of T2D. Both miRNAs were positively correlated with the glycemic status and other T2D risk factors. The ROC analysis indicated good diagnostic abilities for miR-375 to distinguish overall patients from control and prediabetes from T2D patients. Whereas, miR-9 showed lower values and borderline significance in discriminating the subject groups. The combination of miRNAs enhanced the predictability to discriminate patients from control. These results suggest that miR-375 and miR-9 are associated with the susceptibility to developing T2D and miR-375 alone or in combination with miR-9 could serve as biomarkers for early detection of prediabetes and T2D.
Universität Des Saarlandes Fachrichtung 6.1 – Mathematik Integrodifferential Equations for Multiscale Wavelet Shrinkage: the Discrete Case Integrodifferential Equations for Multiscale Wavelet Shrinkage: the Discrete Case Integrodifferential Equations for Multiscale Wavelet Shrinkage: the Discrete Ca

We investigate the relations between wavelet shrinkage and integrod-ifferential equations for image simplification and denoising in the discrete case. Previous investigations in the continuous one-dimensional setting are transferred to the discrete multidimentional case. The key observation is that a wavelet transform can be understood as derivative operator in connection with convolution with a smoothing kernel. In this paper, we extend these ideas to the practically relevant discrete formulation with both orthogonal and biorthogonal wavelets. In the discrete setting, the behaviour of the smoothing kernels for different scales is more complicated than in the continuous setting and of special interest for the understanding of the filters. With the help of tensor product wavelets and special shrinkage rules, the approach is extended to more than one spatial dimension. The results of wavelet shrinkage and related integrodifferential equations are compared in terms of quality by numerical experiments.
Trends in suicide ideation, plans, gestures, and attempts in the United States, 1990-1992 to 2001-2003.

CONTEXT Little is known about trends in suicidal ideation, plans, gestures, or attempts or about their treatment. Such data are needed to guide and evaluate policies to reduce suicide-related behaviors. OBJECTIVE To analyze nationally representative trend data on suicidal ideation, plans, gestures, attempts, and their treatment. DESIGN, SETTING, AND PARTICIPANTS Data came from the 1990-1992 National Comorbidity Survey and the 2001-2003 National Comorbidity Survey Replication. These surveys asked identical questions to 9708 people aged 18 to 54 years about the past year's occurrence of suicidal ideation, plans, gestures, attempts, and treatment. Trends were evaluated by using pooled logistic regression analysis. Face-to-face interviews were administered in the homes of respondents, who were nationally representative samples of US English-speaking residents. MAIN OUTCOME MEASURE Self-reports about suicide-related behaviors and treatment in the year before interview. RESULTS No significant changes occurred between 1990-1992 and 2001-2003 in suicidal ideation (2.8% vs 3.3%; P = .43), plans (0.7% vs 1.0%; P = .15), gestures (0.3% vs 0.2%; P = .24), or attempts (0.4%-0.6%; P = .45), whereas conditional prevalence of plans among ideators increased significantly (from 19.6% to 28.6%; P = .04), and conditional prevalence of gestures among planners decreased significantly (from 21.4% to 6.4%; P = .003). Treatment increased dramatically among ideators who made a gesture (40.3% vs 92.8%) and among ideators who made an attempt (49.6% vs 79.0%). CONCLUSIONS Despite a dramatic increase in treatment, no significant decrease occurred in suicidal thoughts, plans, gestures, or attempts in the United States during the 1990s. Continued efforts are needed to increase outreach to untreated individuals with suicidal ideation before the occurrence of attempts and to improve treatment effectiveness for such cases.