Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative expression software tool (REST©) for group-wise comparison and statistical analysis of relative expression results in real-time PCR

Real-time reverse transcription followed by polymerase chain reaction (RT–PCR) is the most suitable method for the detection and quantification of mRNA. It offers high sensitivity, good reproducibility and a wide quantification range. Today, relative expression is increasingly used, where the expression of a target gene is standardised by a non-regulated reference gene. Several mathematical algorithms have been developed to compute an expression ratio, based on real-time PCR efficiency and the crossing point deviation of an unknown sample versus a control. But all published equations and available models for the calculation of relative expression ratio allow only for the determination of a single transcription difference between one control and one sample. Therefore a new software tool was established, named REST© (relative expression software tool), which compares two groups, with up to 16 data points in a sample and 16 in a control group, for reference and up to four target genes. The mathematical model used is based on the PCR efficiencies and the mean crossing point deviation between the sample and control group. Subsequently, the expression ratio results of the four investigated transcripts are tested for significance by a randomisation test. Herein, development and application of REST© is explained and the usefulness of relative expression in real-time PCR using REST© is discussed. The latest software version of REST© and examples for the correct use can be downloaded at http://www.wzw. tum.de/gene-quantification/.
Clone detection in source code by frequent itemset techniques

In this paper we describe a new approach for the detection of clones in source code, which is inspired by the concept of frequent itemsets from data mining. The source code is represented as an abstract syntax tree in XML. Currently, such XML representations exist for instance for Java, C++, or PROLOG. Our approach is very flexible; it can be configured easily to work with multiple programming languages
Extracellular vesicle in vivo biodistribution is determined by cell source, route of administration and targeting

Extracellular vesicles (EVs) have emerged as important mediators of intercellular communication in a diverse range of biological processes. For future therapeutic applications and for EV biology research in general, understanding the in vivo fate of EVs is of utmost importance. Here we studied biodistribution of EVs in mice after systemic delivery. EVs were isolated from 3 different mouse cell sources, including dendritic cells (DCs) derived from bone marrow, and labelled with a near-infrared lipophilic dye. Xenotransplantation of EVs was further carried out for cross-species comparison. The reliability of the labelling technique was confirmed by sucrose gradient fractionation, organ perfusion and further supported by immunohistochemical staining using CD63-EGFP probed vesicles. While vesicles accumulated mainly in liver, spleen, gastrointestinal tract and lungs, differences related to EV cell origin were detected. EVs accumulated in the tumour tissue of tumour-bearing mice and, after introduction of the rabies virus glycoprotein-targeting moiety, they were found more readily in acetylcholine-receptor-rich organs. In addition, the route of administration and the dose of injected EVs influenced the biodistribution pattern. This is the first extensive biodistribution investigation of EVs comparing the impact of several different variables, the results of which have implications for the design and feasibility of therapeutic studies using EVs.
Experimental Analysis of the Rice Mitochondrial Proteome, Its Biogenesis, and Heterogeneity1[W][OA]

Mitochondria in rice (Oryza sativa) are vital in expanding our understanding of the cellular response to reoxygenation of tissues after anaerobiosis, the crossroads of carbon and nitrogen metabolism, and the role of respiratory energy generation in cytoplasmic male sterility. We have combined density gradient and surface charge purification techniques with proteomics to provide an in-depth proteome of rice shoot mitochondria covering both soluble and integral membrane proteins. Quantitative comparisons of mitochondria purified by density gradients and after further surface charge purification have been used to ensure that the proteins identified copurify with mitochondria and to remove contaminants from the analysis. This rigorous approach to defining a subcellular proteome has yielded 322 nonredundant rice proteins and highlighted contaminants in previously reported rice mitochondrial proteomes. Comparative analysis with the Arabidopsis (Arabidopsis thaliana) mitochondrial proteome reveals conservation of a broad range of known and unknown function proteins in plant mitochondria, with only approximately 20% not having a clear homolog in the Arabidopsis mitochondrial proteome. As in Arabidopsis, only approximately 60% of the rice mitochondrial proteome is predictable using current organelle-targeting prediction tools. Use of the rice protein data set to explore rice transcript data provided insights into rice mitochondrial biogenesis during seed germination, leaf development, and heterogeneity in the expression of nucleus-encoded mitochondrial components in different rice tissues. Highlights include the identification of components involved in thiamine synthesis, evidence for coexpressed and unregulated expression of specific components of protein complexes, a selective anther-enhanced subclass of the decarboxylating segment of the tricarboxylic acid cycle, the differential expression of DNA and RNA replication components, and enhanced expression of specific metabolic components in photosynthetic tissues.
Helicobacter pylori infection in oral lesions of patients with recurrent aphthous stomatitis.

BACKGROUND Recurrent aphthous stomatitis (RAS) is a disorder distinguished by ulcers restricted to the oral mucosa. Because of the histological similarities between peptic ulcers and RAS and the identified role of Helicobacter pylori (H. pylori) in peptic ulcer, the possibility of bacterial involvement in the progression of aphthae has been suggested. Our aim was to find H. Pylori in brushed samples of oral aphthous ulcers by the polymerase chain reaction (PCR) method. MATERIAL/METHODS The evaluated patients were referred to the laboratory with the diagnosis of RAS from the beginning of 2001 throughout 2002 in Rasht city. We collected oral aphthous specimens by toothbrush from these patients. PCR was used to isolate H. Pylori in the samples of RAS lesions and other parts of the oral cavity. Enzyme-linked immunosorbant assay (ELISA) was also done in all patients to determine IgG antibody RESULTS We studied 50 patients with ages between 18 to 60 years (mean+/-SD: 32.38+/-11.30). Twenty-six patients (52%) had positive ELISA test and we obtained H. Pylori DNA in only one patient (2%). CONCLUSIONS According to the results of this study, H. Pylori DNA could not be found in the aphthous ulcers of these patients, even in those with positive anti-H. Pylori antibody (IgG), and it is probable that these bacteria are not involved in recurrent oral aphthous ulcers.
Cloning and sequence analysis of Hemonchus Contortus HC58cDNA

The complete coding sequence of Hemonchus contortus HC58cDNA was generated by rapid amplification of cDNA ends and polymerase chain reaction using primers based on the 5′ and 3′ ends of the parasite mRNA, accession no. AF305964. The HC58cDNA gene was 851 bp long, with open reading frame of 717 bp, precursors to 239 amino acids coding for approximately 27 kDa protein. Analysis of amino acid sequence revealed conserved residues of cysteine, histidine, asparagine, occluding loop pattern, hemoglobinase motif and glutamine of the oxyanion hole characteristic of cathepsin B like proteases (CBL). Comparison of the predicted amino acid sequences showed the protein shared 33.5–58.7% identity to cathepsin B homologues in the papain clan CA family (family C1). Phylogenetic analysis revealed close evolutionary proximity of the protein sequence to counterpart sequences in the CBL, suggesting that HC58cDNA was a member of the papain family.
A GPU accelerated storage system

Massively multicore processors, like, for example, Graphics Processing Units (GPUs), provide, at a comparable price, a one order of magnitude higher peak performance than traditional CPUs. This drop in the cost of computation, as any order-of-magnitude drop in the cost per unit of performance for a class of system components, triggers the opportunity to redesign systems and to explore new ways to engineer them to recalibrate the cost-to-performance relation. In this context, we focus on data storage: We explore the feasibility of harnessing the GPUs' computational power to improve the performance, reliability, or security of distributed storage systems. In this context we present the design of a storage system prototype that uses GPU offloading to accelerate a number of computationally intensive primitives based on hashing. We evaluate the performance of this prototype under two configurations: as a content addressable storage system that facilitates online similarity detection between successive versions of the same file and as a traditional system that uses hashing to preserve data integrity. Further, we evaluate the impact of offloading to the GPU on competing applications' performance. Our results show that this technique can bring tangible performance gains without negatively impacting the performance of concurrently running applications. Further, this work sheds light on the use of heterogeneous multicore processors for enhancing low-level system primitives, and introduces techniques to efficiently leverage the processing power of GPUs.
DeepDTA: deep drug–target binding affinity prediction

Motivation The identification of novel drug‐target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where the goal is to determine whether a DT pair interacts or not. However, protein‐ligand interactions assume a continuum of binding strength values, also called binding affinity and predicting this value still remains a challenge. The increase in the affinity data available in DT knowledge‐bases allows the use of advanced learning techniques such as deep learning architectures in the prediction of binding affinities. In this study, we propose a deep‐learning based model that uses only sequence information of both targets and drugs to predict DT interaction binding affinities. The few studies that focus on DT binding affinity prediction use either 3D structures of protein‐ligand complexes or 2D features of compounds. One novel approach used in this work is the modeling of protein sequences and compound 1D representations with convolutional neural networks (CNNs). Results The results show that the proposed deep learning based model that uses the 1D representations of targets and drugs is an effective approach for drug target binding affinity prediction. The model in which high‐level representations of a drug and a target are constructed via CNNs achieved the best Concordance Index (CI) performance in one of our larger benchmark datasets, outperforming the KronRLS algorithm and SimBoost, a state‐of‐the‐art method for DT binding affinity prediction. Availability and implementation https://github.com/hkmztrk/DeepDTA Supplementary information Supplementary data are available at Bioinformatics online.
Network-based H∞ fuzzy control for a self-balancing two-wheeled inverted pendulum

This paper investigates network-based H∞ fuzzy control for a self-balancing two-wheeled inverted pendulum via a T-S fuzzy model. Due to the insertion of a communication network between the pendulum and a fuzzy controller, the fuzzy control is implemented in an asynchronous way. Unlike the existing works, asynchronous constraints on fuzzy membership functions are introduced in deriving some delay-dependent criteria for H∞ performance analysis and controller design. A numerical example shows that the proposed method using asynchronous constrains can stabilize the pendulum and achieve a better H∞ performance.
Exemplar-based voice conversion in noisy environment

This paper presents a voice conversion (VC) technique for noisy environments, where parallel exemplars are introduced to encode the source speech signal and synthesize the target speech signal. The parallel exemplars (dictionary) consist of the source exemplars and target exemplars, having the same texts uttered by the source and target speakers. The input source signal is decomposed into the source exemplars, noise exemplars obtained from the input signal, and their weights (activities). Then, by using the weights of the source exemplars, the converted signal is constructed from the target exemplars. We carried out speaker conversion tasks using clean speech data and noise-added speech data. The effectiveness of this method was confirmed by comparing its effectiveness with that of a conventional Gaussian Mixture Model (GMM)-based method.
Semi-automatic matching of OCT and IVUS images for image fusion

Medical imaging is essential in the diagnosis of atherosclerosis. In this paper, we propose the semi-automatic matching of two promising and complementary intravascular imaging techniques, Intravascular Ultrasound (IVUS) and Optical Coherence Tomography (OCT), with the ultimate goal of producing hybrid images with increased diagnostic value for assessing arterial health. If no ECG gating has been performed on the IVUS and OCT pullbacks, there is typically an anatomical shuffle (displacement in time and space) in the image sequences due to the catheter motion in the artery during the cardiac cycle, and thus, this is not possible to perform a 3D registration. Therefore, the goal of our work is to detect semi-automatically the corresponding images in both modalities as a preprocessing step for the fusion. Our method is based on the characterization of the lumen shape by a set of Gabor Jets features. We also introduce different correction terms based on the approximate position of the slice in the artery. Then we train different support vector machines based on these features to recognize these correspondences. Experimental results demonstrate the usefulness of our approach, which achieves up to 95% matching accuracy for our data.
Bag of subjects: lecture videos multimodal indexing

In this paper, we address multimodal indexing and retrieval for videos of lectures or seminars. This paper proposes a combination of technologies respectively issuing from image document analysis and text mining. Based on visual information and textual information extracted from slide images, we investigate a Bag of mixed Words (visual words and textual words) model to represent lecture slide's contents. Lecture videos are indexed and retrieved by using extended Bag of Words model. In this model, it is assumed that a video may contain multiple subjects; and this model discovers the visual representation of these subjects automatically and indexes the video accordingly. We discuss the mixed text/image query and proposed indexing approach for retrieval lecture videos and report a quantitative evaluation on lecture videos of our Lab.
Applying Model Checking to an Automotive Microcontroller Application

Microcontrollers in automotive applications perform more and more safety critical functions. The reliability of these systems is of great importance and model checking is seen as a promising future tool for the analysis of the corresponding software. For this purpose an explicit, on-the-fly CTL model checker for assembly code called [mc]square was developed at our institute. This paper describes a case study that was conducted using [mc] square. The aim of this case study was to model check programs that solve an automotive problem, namely a four channel speed measurement with CAN bus interface. The programs were written by students in a lab course without the application of model checking in mind. Hence, these programs contain all features which can be found in real world software. This case study showed that small or medium sized microcontroller programs can be verified without respectively with minor modifications. Additional potentials for future improvements to handle more complex programs have been identified.
Continuum variational and diffusion quantum Monte Carlo calculations

This topical review describes the methodology of continuum variational and diffusion quantum Monte Carlo calculations. These stochastic methods are based on many-body wavefunctions and are capable of achieving very high accuracy. The algorithms are intrinsically parallel and well suited to implementation on petascale computers, and the computational cost scales as a polynomial in the number of particles. A guide to the systems and topics which have been investigated using these methods is given. The bulk of the article is devoted to an overview of the basic quantum Monte Carlo methods, the forms and optimization of wavefunctions, performing calculations under periodic boundary conditions, using pseudopotentials, excited-state calculations, sources of calculational inaccuracy, and calculating energy differences and forces.
Adalimumab Treatment in Biologically Naïve Crohn's Disease: Relationship with Ectopic MUC5AC Expression and Endoscopic Improvement

Background. Adalimumab (ADA) is effective for patients with Crohn's disease (CD). However, there have been few reports on ADA therapy with respect to its relationship with pathologic findings and drug efficacy in biologically naïve CD cases. Methods. Fifteen patients with active biologically naïve CD were treated with ADA. We examined them clinically and pathologically with ectopic MUC5AC expression in the lesions before and after 12 and 52 weeks of ADA therapy, retrospectively. Results. Both mean CD activity index scores and serum C-reactive protein values were significantly lower after ADA therapy (P < 0.001). In the MUC5AC negative group, all cases exhibited clinical remission (CR) and endoscopic improvement at 52 weeks. In MUC5AC positive groups, loss of MUC5AC expression was detected in cases having CR and endoscopic improvement at 52 weeks, while remnant ectopic MUC5AC expression was observed in those exhibiting no endoscopic improvement and flare up after 52 weeks. Conclusions. ADA leads to CR and endoscopic improvement in biologically naïve CD cases. In addition, ectopic MUC5AC expression may be a predictive marker of flare up and endoscopic improvement in the intestines of CD patients.
Enhanced depth estimation by using object placement relation

Depth estimation from a scene is an important task in computer vision and 3-d image reconstruction. Normally, human being has an amazing ability to understand a scene quickly by extracting visual information such as object shape, stereo vision cue, size, placement and etc. However, in computer vision, finding 3-d position from an image is still a challenging task, though many researches have been proposed for decades. Many methods have been presented some efficient solutions using image acquisition from both one and several images. Nevertheless, there is no generic solution to recover precise depth from a single image without any prior knowledge. Object placement is one of vision cues usually used to identify 3-d position efficiently, while extraction of such information is not so trivial. Our approach presents an adaptive algorithm defining placement information as a constraint to estimate depth from a single scene image having many arbitrary objects. Our experimental result shows that our algorithm can estimate precise depth from a wide range of image scenes.
Endotoxemia reduces cerebral perfusion but enhances dynamic cerebrovascular autoregulation at reduced arterial carbon dioxide tension*

Objective:The administration of endotoxin to healthy humans reduces cerebral blood flow but its influence on dynamic cerebral autoregulation remains unknown. We considered that a reduction in arterial carbon dioxide tension would attenuate cerebral perfusion and improve dynamic cerebral autoregulation in healthy subjects exposed to endotoxemia. Design:Prospective descriptive study. Setting:Hospital research laboratory. Subjects:Ten healthy young subjects (age: 32 ± 8 yrs [mean ± SD]; weight: 84 ± 10 kg; weight: 184 ± 5 cm; body mass index: 25 ± 2 kg/m2) participated in the study. Interventions:Systemic hemodynamics, middle cerebral artery mean flow velocity, and dynamic cerebral autoregulation evaluated by transfer function analysis in the very low (<0.07 Hz), low (0.07–0.15 Hz), and high (>0.15 Hz) frequency ranges were monitored in these volunteers before and after an endotoxin bolus (2 ng/kg; Escherichia coli). Measurements and Main Results:Endotoxin increased body temperature of the subjects from 36.8 ± 0.4°C to 38.6 ± 0.5°C (p < .001) and plasma tumor necrosis factor-&agr; from 5.6 (2.8–6.7) pg/mL to 392 (128–2258) pg/mL (p < .02). Endotoxemia had no influence on mean arterial pressure (95 [74–103] mm Hg vs. 92 [78–104] mm Hg; p = .75), but increased cardiac output (8.3 [6.1–9.5] L·min–1 vs. 6.0 [4.5–8.2] L·min–1; p = .02) through an elevation in heart rate (82 ± 9 beats·min–1 vs. 63 ± 10 beats·min–1; p < .001), whereas arterial carbon dioxide tension (37 ± 5 mm Hg vs. 41 ± 2 mm Hg; p < .05) and middle cerebral artery mean flow velocity (37 ± 9 cm·sec–1 vs. 47 ± 10 cm·sec–1; p < .01) were reduced. In regard to dynamic cerebral autoregulation, endotoxemia was associated with lower middle cerebral artery mean flow velocity variability (1.0 ± 1.0 [cm·sec–1] Hz–1 vs. 2.8 ± 1.5 [cm·sec–1] Hz–1; p < .001), reduced gain (0.52 ± 0.11 cm·sec–1.mm Hg–1 vs. 0.74 ± 0.17 cm·sec–1.mm Hg–1; p < .05), normalized gain (0.22 ± 0.05 vs. 0.40 ± 0.17%·%–1; p < .05), and higher mean arterial pressure-to-middle cerebral artery mean flow velocity phase difference (p < .05) in the low frequency range (0.07–0.15 Hz). Conclusions:These data support that the reduction in arterial carbon dioxide tension explains the improved dynamic cerebral autoregulation and the reduced cerebral perfusion encountered in healthy subjects during endotoxemia.
T Lymphocyte Priming by Neutrophil Extracellular Traps Links Innate and Adaptive Immune Responses

Polymorphonuclear neutrophils constitute the first line of defense against infections. Among their strategies to eliminate pathogens they release neutrophil extracellular traps (NETs), being chromatin fibers decorated with antimicrobial proteins. NETs trap and kill pathogens very efficiently, thereby minimizing tissue damage. Furthermore, NETs modulate inflammatory responses by activating plasmacytoid dendritic cells. In this study, we show that NETs released by human neutrophils can directly prime T cells by reducing their activation threshold. NETs-mediated priming increases T cell responses to specific Ags and even to suboptimal stimuli, which would not induce a response in resting T cells. T cell priming mediated by NETs requires NETs/cell contact and TCR signaling, but unexpectedly we could not demonstrate a role of TLR9 in this mechanism. NETs-mediated T cell activation adds to the list of neutrophil functions and demonstrates a novel link between innate and adaptive immune responses.