Miracle-dz/UniFAR-FTUs huggingface dataset:
Sigma-1 Receptor Regulates Early Steps of Viral RNA Replication at the Onset of Hepatitis C Virus Infection

ABSTRACT Hepatitis C virus (HCV) genome replication is thought to occur in a membranous cellular compartment derived from the endoplasmic reticulum (ER). The molecular mechanisms by which these membrane-associated replication complexes are formed during HCV infection are only starting to be unraveled, and both viral and cellular factors contribute to their formation. In this study, we describe the discovery of nonopioid sigma-1 receptor (S1R) as a cellular factor that mediates the early steps of viral RNA replication. S1R is a cholesterol-binding protein that resides in lipid-rich areas of the ER and in mitochondrion-associated ER membranes (MAMs). Several functions have been ascribed to this ER-resident chaperone, many of which are related to Ca2+ signaling at the MAMs and lipid storage and trafficking. Downregulation of S1R expression by RNA interference (RNAi) in Huh-7 cells leads to a proportional decrease in susceptibility to HCV infection, as shown by reduced HCV RNA accumulation and intra- and extracellular infectivity in single-cycle infection experiments. Similar RNAi studies in persistently infected cells indicate that S1R expression is not rate limiting for persistent HCV RNA replication, as marked reduction in S1R in these cells does not lead to any decrease in HCV RNA or viral protein expression. However, subgenomic replicon transfection experiments indicate that S1R expression is rate limiting for HCV RNA replication without impairing primary translation. Overall, our data indicate that the initial steps of HCV infection are regulated by S1R, a key component of MAMs, suggesting that these structures could serve as platforms for initial RNA replication during HCV infection.
Tracing software developers' eyes and interactions for change tasks

What are software developers doing during a change task? While an answer to this question opens countless opportunities to support developers in their work, only little is known about developers' detailed navigation behavior for realistic change tasks. Most empirical studies on developers performing change tasks are limited to very small code snippets or are limited by the granularity or the detail of the data collected for the study. In our research, we try to overcome these limitations by combining user interaction monitoring with very fine granular eye-tracking data that is automatically linked to the underlying source code entities in the IDE. In a study with 12 professional and 10 student developers working on three change tasks from an open source system, we used our approach to investigate the detailed navigation of developers for realistic change tasks. The results of our study show, amongst others, that the eye tracking data does indeed capture different aspects than user interaction data and that developers focus on only small parts of methods that are often related by data flow. We discuss our findings and their implications for better developer tool support.
Effects of naltrexone on the ethanol-induced changes in the rat central dopaminergic system.

AIMS The opioid antagonist naltrexone may reduce ethanol reward, but the underlying neurochemical mechanisms has yet to be clarified. The afferent projections to the nucleus accumbens from the ventral tegmental area (VTA) provide a potential substrate by which endogenous opioids may modulate the dopaminergic rewarding effects of ethanol. We assessed mRNA levels of tyrosine hydroxylase (TH), a major regulatory enzyme in the dopamine synthesis and levels of dopamine and its metabolites after chronic ethanol administration with and without concomitant naltrexone. METHODS Sprague-Dawley rats were exposed to chronic ethanol consumption (5%, 4 weeks) with and without concomitant naltrexone administration. Levels of TH mRNA in the VTA and substantia nigra (SN) and dopamine and its metabolites in the striatum of the rats were measured by in situ hybridization and by high performance liquid chromatography, respectively. RESULTS Chronic ethanol consumption increased TH mRNA levels in the VTA, but did not cause any significant change in the SN. With naltrexone treatment, ethanol-induced increase in the TH mRNA level was reduced in the VTA. Chronic ethanol consumption did not cause any change in the levels of dopamine and its metabolites in most brain regions. Only in the striatum, ethanol consumption with naltrexone treatment significantly increases the dopamine level. CONCLUSION This finding supports the presence of interactions of opioid and dopaminergic systems in the VTA in mediating ethanol reward, and thus naltrexone attenuates the rewarding properties of ethanol by interfering with the ethanol-induced stimulation of the mesolimbic dopaminergic pathway.
Magnetoelastic effect in soft amorphous and nanocrystalline FeCuNbSiB thin films

Thin films of FeCuNbSiB have been sputtered on SiO2/Si substrates with thickness varying from 50 nm to 1.8 microns, then annealed at temperature ranging from 200 to 500 °C. The coercivity globally decreases with the film thickness down to 100 A m−1 for as-deposited samples and 10 A m−1 for annealed samples. However, it appears a local maximum for thickness close to 1 micron (i.e. the exchange length), regardless the annealing temperature. This behavior is supposed to be related to a modification of the magnetic domain structure, as the RAM applied to thin films and the dependence of the transitions points (glass state temperature Tg and crystallization temperature Tx) on the film dimension are monotonous. In addition, the films have been annealed under magnetic field and strong anisotropy energy has been reached, in the range of 150 J m−3.
IMPROVED TARGET RECOGNITION AND TARGET DETECTION ALGORITHMS USING HRR PROFILES AND SAR IMAGES

In this thesis, a new algorithm to improve automatic target recognition techniques on High Range Resolution (HRR) Profiles is presented and also a number of ways are investigated for target detection using Synthetic Aperture Radar (SAR) images. A new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for sequential High Range Resolution (HRR) radar signatures. The proposed hybrid algorithm combines Eigen-Template based Matched Filtering (ETMF) and Hidden Markov modeling (HMM) techniques to achieve superior HRR-ATR performance. In the proposed hybrid approach, each HRR test profile is first scored by ETMF that is then followed by independent HMM scoring. The first ETMF scoring step produces a limited number of " most likely " models that are target and aspect dependent. These reduced numbers of models are then used for improved HMM scoring in the second step. Finally, the individual scores of ETMF and HMM are combined using Maximal Ratio Combining to render a classification decision. Classification results are presented for the MSTAR data set via ROC curves. An ultra-wideband (UWB) synthetic aperture radar (SAR) simulation technique that employs physical and statistical models is developed and presented. This joint i v physics/statistics based technique generates images that have many of the " blob-like " and " spiky " clutter characteristics of UWB radar data in forested regions while avoiding the intensive computations required for the implementation of low-frequency numerical electromagnetic simulation techniques. Comparative results from three SVD-based subspace filtering approaches on target detection algorithms are reported. These approaches are denoted as " Energy-Normalized SVD " , " Condition-Statistics SVD " , and " Terrain-Filtered SVD ". Approaches towards developing " self-training " algorithms for UWB radar target detection are investigated using the results of this simulation process.
Finite element simulations of microvoid growth due to selective oxidation in binary alloys

Selective oxidation induced void growth is observed in thermal barrier coating systems used in gas turbines. These voids occur at the interface between the bond coat (BC) and the thermally grown oxide (TGO) layer. In this paper we develop the modelling framework to simulate microvoid growth due to coupled diffusion and creeping in binary alloys. We have implemented the modelling framework into an existing finite element programme. The developed modelling framework and programme is used to simulate microvoid growth driven by selective oxidation in a binary β-NiAl alloy. Axisymmetric void growth due to the combined action of interdiffusion and creeping is simulated. The sharpness of the void and direction of creeping are considered as parameters in our study. Our simulations show that the voids dilate without any change in shape when creeping is equally likely in all the directions (isotropic). Void growth patterns similar to those observed in experiments are predicted when the creeping is restricted to occur only along the radial and tangential directions. A hemispherical void grows faster compared to a sharp void. The sharpness increases in the case of a sharp void and could lead to interactions with the neighbouring voids leading to spallation of the TGO layer as observed in experiments.
State-of-the-Art in Vision-Based Topological Mapping and Localization Methods∗

Topological maps model the environment as a graph, where nodes are distinctive places of the environment and edges indicate the relationships between them. They present an interesting alternative to the classic metric maps, due to their simplicity and storage needs, which convert them in an active research area. Several kinds of sensors have been used during years for topological mapping and localization. However, in the last decades, vision approaches have emerged because of the technology improvements and the amount of useful information that a camera can provide. In this paper, we review the main solutions presented in the last 15 years, and classify them in accordance to the kind of image descriptor employed. Advantages and disadvantages of each approach are thoroughly reviewed and discussed. ∗This work is supported by the European Social Fund through the grant FPI11-43123621R (Conselleria d’Educacio, Cultura i Universitats, Govern de les Illes Balears) and by FP7 project INCASS (GA 605200).
No cause for pause: new analyses of ramping and stepping dynamics in LIP (Rebuttal to Response to Reply to Comment on Latimer et al 2015)

We recently presented a statistical comparison between two models of latent dynamics in macaque lateral intraparietal (LIP) area spike trains—a continuous ‘ramping’ (diffusion-to-bound) model, and a discrete ‘stepping’ model—and found that a substantial fraction of neurons (recorded in two different studies) were better supported by the stepping model (Latimer et al., 2015). Here, we respond to a recent challenge to the validity of these findings that focuses primarily on the possibility of a lower bound on LIP firing rates (Zylberberg & Shadlen, 2016). The paper in question proposed alternate formulations of the ramping model, and argued (via indirect analyses) that half the neurons in the population were better explained by the new model; if correct, this would lead to an even split in the number of neurons better explained by each model. These analyses, while interesting, do not alter the conclusions of our original paper. Here, we review the criticisms raised by Zylberberg & Shadlen and report several new analyses using models with lower bounds. First, we show that the stepping model continued to provide a better description of LIP spike trains when fit using only an early period of each trial. Second, we performed a direct model comparison between our stepping model and a ramping-with-baseline model proposed by Zylberberg & Shadlen; we found that (in a pleasing moment of agreement) roughly half the neurons were better explained by each model. Interestingly, inspection of the cells that switched classifications revealed that many did not strictly exhibit the classical ramping PSTHs that motivated these analyses in the first place. We also examined two other issues raised in recent discussions of LIP: (1) We show that a non-integrating model is consistent with some core aspects of behavioral data previously offered as evidence for continuous integration; and (2) We examine analyses based on the response covariance (“CorCE”), and show that it does not reliably distinguish ramping and stepping dynamics for our dataset. Taken together, these discussions highlight the value of data-driven characterizations of both neural and behavioral dynamics with appropriate statistical tools.
Ablation of the single dynamin of T. brucei blocks mitochondrial fission and endocytosis and leads to a precise cytokinesis arrest

Mitochondrial fission is mediated by dynamin-like proteins (DLPs). Trypanosoma brucei contains a single DLP, which is the only member of the dynamin superfamily. We have previously shown that expression of the human proapoptotic Bax in T. brucei induces extensive mitochondrial fragmentation. Here we report that Baxinduced mitochondrial fission is abolished in cell lines lacking functional DLP suggesting that the protein is also required for mitochondrial division during the cell cycle. Furthermore, DLP-ablated cells are deficient for endocytosis and as a consequence accumulate enlarged flagellar pockets. Thus, besides its expected role in mitochondrial fission the trypanosomal DLP is required for endocytosis, a function thought to be restricted to classical dynamins. In agreement with its dual function, the DLP localizes to both the mitochondrion and the flagellar pocket, the site where endocytosis occurs. Unexpectedly, ablation of DLP also causes an arrest of cytokinesis. The fact that no multinucleation is observed in the arrested cells argues for a precise cell-cycle block. Furthermore, analysis of a clathrin-knockdown cell line suggests that the cytokinesis arrest is not due to the endocytosis defect. Thus, our results support a working model in which mitochondrial fission triggers a checkpoint for cytokinesis.
Will Fault Localization Work for These Failures? An Automated Approach to Predict Effectiveness of Fault Localization Tools

Debugging is a crucial yet expensive activity to improve the reliability of software systems. To reduce debugging cost, various fault localization tools have been proposed. A spectrum-based fault localization tool often outputs an ordered list of program elements sorted based on their likelihood to be the root cause of a set of failures (i.e., their suspiciousness scores). Despite the many studies on fault localization, unfortunately, however, for many bugs, the root causes are often low in the ordered list. This potentially causes developers to distrust fault localization tools. Recently, Parnin and Orso highlight in their user study that many debuggers do not find fault localization useful if they do not find the root cause early in the list. To alleviate the above issue, we build an oracle that could predict whether the output of a fault localization tool can be trusted or not. If the output is not likely to be trusted, developers do not need to spend time going through the list of most suspicious program elements one by one. Rather, other conventional means of debugging could be performed. To construct the oracle, we extract the values of a number of features that are potentially related to the effectiveness of fault localization. Building upon advances in machine learning, we process these feature values to learn a discriminative model that is able to predict the effectiveness of a fault localization tool output. In this preliminary work, we consider an output of a fault localization tool to be effective if the root cause appears in the top 10 most suspicious program elements. We have experimented our proposed oracle on 200 faulty programs from Space, NanoXML, XML-Security, and the 7 programs in Siemens test suite. Our experiments demonstrate that we could predict the effectiveness of fault localization tool with a precision, recall, and F-measure (harmonic mean of precision and recall) of 54.36%, 95.29%, and 69.23%. The numbers indicate that many ineffective fault localization instances are identified correctly, while only very few effective ones are identified wrongly.
Model-independent measurements of bar pattern speeds

The pattern speed is one of the fundamental parameters that determines the structure of barred galaxies. This quantity is usually derived from indirect methods or by employing model assumptions. The number of bar pattern speeds derived using the model-independent Tremaine & Weinberg technique is still very limited. We present the results of model-independent measurements of the bar pattern speed in four galaxies ranging in Hubble type from SB0 to SBbc. Three of the four galaxies in our sample are consistent with bars being fast rotators. The lack of slow bars is consistent with previous observations and suggests that barred galaxies do not have centrally concentrated dark matter haloes. This contradicts simulations of cosmological structure formation and observations of the central mass concentration in nonbarred galaxies.
The Geobacillus Pan-Genome: Implications for the Evolution of the Genus

The genus Geobacillus is comprised of a diverse group of spore-forming Gram-positive thermophilic bacterial species and is well known for both its ecological diversity and as a source of novel thermostable enzymes. Although the mechanisms underlying the thermophilicity of the organism and the thermostability of its macromolecules are reasonably well understood, relatively little is known of the evolutionary mechanisms, which underlie the structural and functional properties of members of this genus. In this study, we have compared 29 Geobacillus genomes, with a specific focus on the elements, which comprise the conserved core and flexible genomes. Based on comparisons of conserved core and flexible genomes, we present evidence of habitat delineation with specific Geobacillus genomes linked to specific niches. Our analysis revealed that Geobacillus and Anoxybacillus share a high proportion of genes. Moreover, the results strongly suggest that horizontal gene transfer is a major factor deriving the evolution of Geobacillus from Bacillus, with genetic contributions from other phylogenetically distant taxa.
Patterns of altered functional connectivity in mesial temporal lobe epilepsy

Purpose: In mesial temporal lobe epilepsy (MTLE) the epileptogenic area is confined to the mesial temporal lobe, but other cortical and subcortical areas are also affected and cognitive and psychiatric impairments are usually documented. Functional connectivity methods are based on the correlation of the blood oxygen level dependent (BOLD) signal between brain regions, which exhibit consistent and reproducible functional networks from resting state data. The aim of this study is to compare functional connectivity of patients with MTLE during the interictal period with healthy subjects. We hypothesize that patients show reduced functional connectivity compared to controls, the interest being to determine which regions show this reduction.
Arthroscopic Single-Row Modified Mason-Allen Repair Versus Double-Row Suture Bridge Reconstruction for Supraspinatus Tendon Tears

Background: Arthroscopic double-row fixation of supraspinatus tendon tears compared with single-row techniques is still a matter of debate. Hypothesis: Arthroscopic double-row rotator cuff repair using the suture bridge technique provides better clinical results and lower retear rates than does single-row repair using a modified Mason-Allen stitch technique. Study Design: Cohort study; Level of evidence 3. Methods: Forty patients underwent either an arthroscopic single-row modified Mason-Allen stitch (SR) (n = 20; mean age ± SD, 61.5 ± 7.4 y) or a modified suture bridge double-row repair (DR) (n = 20; age, 61.2 ± 7.5 y). The anteroposterior extension was classified as Bateman I in 10% and Bateman II in 90% of patients in the SR group and as Bateman II in 80% and Bateman III in 20% of patients in the DR group. Patients were matched for sex and age. The subjective shoulder value (SSV), Constant-Murley score (CS), and Western Ontario Rotator Cuff Index (WORC) were used for clinical follow-up. Furthermore, MRI scans were conducted for analysis of tendon integrity, muscle atrophy, and fatty infiltration via semiquantitative signal intensity analysis. In addition, re-defect patterns were evaluated. Results: The mean follow-up time in the SR group was 16.8 ± 4.6 months. The mean SSV was 91.0% ± 8.8%, mean CS was 82.2 ± 8.1 (contralateral side, 88.8 ± 5.3), and mean WORC score was 96.5% ± 3.2%. The mean follow-up time in the DR group was 23.4 ± 2.9 months, with patients achieving scores of 92.9% ± 9.6% for the SSV, 77.0 ± 8.6 for the CS (contralateral side, 76.7 ± 17.1), and 90.7% ± 12.6% for the WORC (P > .05). No significant differences were detected in the clinical outcome between groups. Tendon integrity was as follows. Type 1, none in either group; type 2, 4 SR and 5 DR; type 3, 9 SR and 10 DR; type 4, 3 SR and 3 DR; and type 5, 3 SR and 2 DR. The failure rate was 31.6% (n = 6) in the SR group and 25% (n = 5) in the DR group (P > .05). No significant differences were obtained for muscular atrophy or fatty degeneration (SR group, 0.94 ± 0.16; DR group, 1.15 ± 0.5) (P > .05). Re-defects revealed lateral cuff failure in 83.3% of SR patients in contrast to patients treated with DR techniques. The re-defect pattern was medial cuff failure in 80% of the patients. Conclusion: The clinical results after modified Mason-Allen single-row versus double-mattress suture bridge technique did not demonstrate significant differences in a matched patient cohort. Concerning the failure mode, single- and double-row techniques seem to demonstrate different re-defect patterns.
Assembly Line Polyketide Synthases: Mechanistic Insights and Unsolved Problems

Two hallmarks of assembly line polyketide synthases have motivated an interest in these unusual multienzyme systems, their stereospecificity and their capacity for directional biosynthesis. In this review, we summarize the state of knowledge regarding the mechanistic origins of these two remarkable features, using the 6-deoxyerythronolide B synthase as a prototype. Of the 10 stereocenters in 6-deoxyerythronolide B, the stereochemistry of nine carbon atoms is directly set by ketoreductase domains, which catalyze epimerization and/or diastereospecific reduction reactions. The 10th stereocenter is established by the sequential action of three enzymatic domains. Thus, the problem has been reduced to a challenge in mainstream enzymology, where fundamental gaps remain in our understanding of the structural basis for this exquisite stereochemical control by relatively well-defined active sites. In contrast, testable mechanistic hypotheses for the phenomenon of vectorial biosynthesis are only just beginning to emerge. Starting from an elegant theoretical framework for understanding coupled vectorial processes in biology [Jencks, W. P. (1980) Adv. Enzymol. Relat. Areas Mol. Biol. 51, 75–106], we present a simple model that can explain assembly line polyketide biosynthesis as a coupled vectorial process. Our model, which highlights the important role of domain–domain interactions, not only is consistent with recent observations but also is amenable to further experimental verification and refinement. Ultimately, a definitive view of the coordinated motions within and between polyketide synthase modules will require a combination of structural, kinetic, spectroscopic, and computational tools and could be one of the most exciting frontiers in 21st Century enzymology.