Miracle-dz/UniFAR-FTUs huggingface dataset:
Glibenclamide Decreases ATP-Induced Intracellular Calcium Transient Elevation via Inhibiting Reactive Oxygen Species and Mitochondrial Activity in Macrophages

Increasing evidence has revealed that glibenclamide has a wide range of anti-inflammatory effects. However, it is unclear whether glibenclamide can affect the resting and adenosine triphosphate (ATP)-induced intracellular calcium ([Ca2+]i) handling in Raw 264.7 macrophages. In the present study, [Ca2+]i transient, reactive oxygen species (ROS) and mitochondrial activity were measured by the high-speed TILLvisION digital imaging system using the indicators of Fura 2-am, DCFDA and rhodamine-123, respectively. We found that glibenclamide, pinacidil and other unselective K+ channel blockers had no effect on the resting [Ca2+]i of Raw 264.7 cells. Extracellular ATP (100 µM) induced [Ca2+]i transient elevation independent of extracellular Ca2+. The transient elevation was inhibited by an ROS scavenger (tiron) and mitochondria inhibitor (rotenone). Glibenclamide and 5-hydroxydecanoate (5-HD) also decreased ATP-induced [Ca2+]i transient elevation, but pinacidil and other unselective K+ channel blockers had no effect. Glibenclamide also decreased the peak of [Ca2+]i transient induced by extracellular thapsigargin (Tg, 1 µM). Furthermore, glibenclamide decreased intracellular ROS and mitochondrial activity. When pretreated with tiron and rotenone, glibenclamide could not decrease ATP, and Tg induced maximal [Ca2+]i transient further. We conclude that glibenclamide may inhibit ATP-induced [Ca2+]i transient elevation by blocking mitochondria KATP channels, resulting in decreased ROS generation and mitochondrial activity in Raw 264.7 macrophages.
Generalized Power Method for Sparse Principal Component Analysis

In this paper we develop a new approach to sparse principal component analysis (sparse PCA). We propose two single-unit and two block optimization formulations of the sparse PCA problem, aimed at extracting a single sparse dominant principal component of a data matrix, or more components at once, respectively. While the initial formulations involve nonconvex functions, and are therefore computationally intractable, we rewrite them into the form of an optimization program involving maximization of a convex function on a compact set. The dimension of the search space is decreased enormously if the data matrix has many more columns (variables) than rows. We then propose and analyze a simple gradient method suited for the task. It appears that our algorithm has best convergence properties in the case when either the objective function or the feasible set are strongly convex, which is the case with our single-unit formulations and can be enforced in the block case. Finally, we demonstrate numerically on a set of random and gene expression test problems that our approach outperforms existing algorithms both in quality of the obtained solution and in computational speed.
Effects of Empathic Paraphrasing – Extrinsic Emotion Regulation in Social Conflict

In the present study, we investigated the effects of empathic paraphrasing as an extrinsic emotion regulation technique in social conflict. We hypothesized that negative emotions elicited by social conflict can be regulated extrinsically in a conversation by a listener following the narrator’s perspective and verbally expressing cognitive empathy. Twenty participants were interviewed on an ongoing or recently self-experienced social conflict. The interviewer utilized 10 standardized open questions inviting participants to describe their perception of the conflict. After each of the 10 descriptions, the interviewer responded by either paraphrasing or taking notes (control condition). Valence ratings pertaining to the current emotional state were assessed during the interview along with psychophysiological and voice recordings. Participants reported feeling less negative after hearing the interviewer paraphrase what they had said. In addition, we found a lower sound intensity of participants’ voices when answering to questions following a paraphrase. At the physiological level, skin conductance response, as well as heart rate, were higher during paraphrasing than during taking notes, while blood volume pulse amplitude was lower during paraphrasing, indicating higher autonomic arousal. The results show that demonstrating cognitive empathy through paraphrasing can extrinsically regulate negative emotion on a short-term basis. Paraphrasing led to enhanced autonomic activation in recipients, while at the same time influencing emotional valence in the direction of feeling better. A possible explanation for these results is that being treated in an empathic manner may stimulate a more intense emotion processing helping to transform and resolve the conflict.
The Anna Karenina principle: A mechanism for the explanation of success in science

The first sentence of Leo Tolstoy's novel Anna Karenina is: "Happy families are all alike; every unhappy family is unhappy in its own way. " Here Tolstoy means that for a family to be happy, several key aspects must be given (such as good health of all family members, acceptable financial security, and mutual affection). If there is a deficiency in any one or more of these key aspects, the family will be unhappy. In this paper we introduce the Anna Karenina principle as a concept that can explain success in science. Here we will refer to three central areas in modern science in which scarce resources will most usually lead to failure: (1) peer review of research grant proposals and manuscripts (money and journal space as scarce resources), (2) citation of publications (reception as a scarce resource), and (3) new scientific discoveries (recognition as a scarce resource). If resources are scarce (journal space, funds, reception, and recognition), there can be success only when several key prerequisites for the allocation of the resources are fulfilled. If any one of these prerequisites is not fulfilled, the grant proposal, manuscript submission, the published paper, or the discovery will not be successful.
Subsidized optimal ART for HIV-positive temporary residents of Australia improves virological outcomes: results from the Australian HIV Observational Database Temporary Residents Access Study

HIV‐positive (HIV+) temporary residents living in Australia legally are unable to access government subsidized antiretroviral treatment (ART) which is provided via Medicare to Australian citizens and permanent residents. Currently, there is no information systematically being collected on non‐Medicare eligible HIV+ patients in Australia. The objectives of this study are to describe the population recruited to the Australian HIV Observational Database (AHOD) Temporary Residents Access Study (ATRAS) and to determine the short‐ and long‐term outcomes of receiving (subsidized) optimal ART and the impact on onwards HIV transmission.
CRISPR-Cas Genome Surgery in Ophthalmology

Genetic disease affecting vision can significantly impact patient quality of life. Gene therapy seeks to slow the progression of these diseases by treating the underlying etiology at the level of the genome. Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated systems (Cas) represent powerful tools for studying diseases through the creation of model organisms generated by targeted modification and by the correction of disease mutations for therapeutic purposes. CRISPR-Cas systems have been applied successfully to the visual sciences and study of ophthalmic disease – from the modification of zebrafish and mammalian models of eye development and disease, to the correction of pathogenic mutations in patient-derived stem cells. Recent advances in CRISPR-Cas delivery and optimization boast improved functionality that continues to enhance genome-engineering applications in the eye. This review provides a synopsis of the recent implementations of CRISPR-Cas tools in the field of ophthalmology.
Identification and Molecular Epidemiology of Campylobacter coli Isolates from Human Gastroenteritis, Food, and Animal Sources by Amplified Fragment Length Polymorphism Analysis and Penner Serotyping

ABSTRACT Campylobacter coli is an infrequently studied but important food-borne pathogen with a wide natural distribution. We investigated its molecular epidemiology by use of amplified fragment length polymorphism (AFLP)-based genotyping and Penner serotyping. Serotype reference strains and 177 Danish isolates of diverse origin identified by routine phenotyping as C. coli were examined. Molecular tools identified some 12% of field isolates as Campylobacter jejuni, emphasizing the need for improved identification methods in routine laboratories. Cluster analysis of AFLP profiles of 174 confirmed C. coli isolates revealed a difference in the distribution of isolates from pig and poultry (chicken, duck, turkey, and ostrich) species and indicated the various poultry species, but not pigs, to be likely sources of human C. coli infection. A poor correlation was observed between serotyping and AFLP profiling, suggesting that the former method has limited value in epidemiological studies of this species.
Hippocampal Context Processing during Acquisition of a Predictive Learning Task Is Associated with Renewal in Extinction Recall

Renewal is defined as the recovery of an extinguished response if extinction and retrieval contexts differ. The context dependency of extinction, as demonstrated by renewal, has important implications for extinction-based therapies. Persons showing renewal (REN) exhibit higher hippocampal activation during extinction in associative learning than those without renewal (NOREN), demonstrating hippocampal context processing, and recruit ventromedial pFC in retrieval. Apart from these findings, brain processes generating renewal remain largely unknown. Conceivably, processing differences in task-relevant brain regions that ultimately lead to renewal may occur already in initial acquisition of associations. Therefore, in two fMRI studies, we investigated overall brain activation and hippocampal activation in REN and NOREN during acquisition of an associative learning task in response to presentation of a context alone or combined with a cue. Results of two studies demonstrated significant activation differences between the groups: In Study 1, a support vector machine classifier correctly assigned participants' brain activation patterns to REN and NOREN groups, respectively. In Study 2, REN and NOREN showed similar hippocampal involvement during context-only presentation, suggesting processing of novelty, whereas overall hippocampal activation to the context–cue compound, suggesting compound encoding, was higher in REN. Positive correlations between hippocampal activation and renewal level indicated more prominent hippocampal processing in REN. Results suggest that hippocampal processing of the context–cue compound rather than of context only during initial learning is related to a subsequent renewal effect. Presumably, REN participants use distinct encoding strategies during acquisition of context-related tasks, which reflect in their brain activation patterns and contribute to a renewal effect.
Joint sparsity and frequency estimation for spectral compressive sensing

Parameter estimation from compressively sensed signals has recently received some attention. We here also consider this problem in the context of frequency sparse signals which are encountered in many application. Existing methods perform the estimation using finite dictionaries or incorporate various interpolation techniques to estimate the continuous frequency parameters. In this paper, we show that solving the problem in a probabilistic framework instead produces an asymptotically efficient estimator which outperforms existing methods in terms of estimation accuracy while still having a low computational complexity. Moreover, the proposed algorithm is also able to make inference about the sparsity level of the measured signal. The simulation code is available online.
Effect of reinforcement volume fraction on mechanical alloying of Al–SiC nanocomposite powders

Mixtures of aluminium powder and nanoscaled SiC particles (n-SiC) at various volume fractions of 0, 1, 3, 5, 7 and 10 are comilled in a high energy planetary ball mill under an argon atmosphere to produce nanocrystalline Al–SiC nanocomposites. High resolution scanning electron microscopy (HRSEM), X-ray diffraction (XRD) method, laser particle size analysis and powder density measurement were used to study the morphological changes and microstructural evolution occurred during mechanical alloying. Al–SiC composite powder with microscaled SiC particles (1 m m) was also synthesised and characterised to examine the influence of reinforcement particle size on the milling process. It was found that with increasing volume fraction of n-SiC, a finer composite powder with more uniform particle size distribution is obtained. The morphology of the particles also became more equiaxed at shorter milling times. Furthermore, the analysis of XRD patterns by Williamson–Hall method indicated that the crystallite size of the aluminium matrix decreases with increasing reinforcement volume content while the lattice strain changes marginally. As compared with microscaled SiC particles, it appeared that the effect of n-SiC on the milling stages is more pronounced. The results clearly show that the reinforcement particles influence the work hardening and fracture of the metal matrix upon milling, affecting the structural evolution. With decreasing size of the ceramic particles to nanoscale, this influence becomes more pronounced as the surface to volume fraction increases.
Fast and accurate algorithms for protein side-chain packing

This article studies the protein side-chain packing problem using the tree-decomposition of a protein structure. To obtain fast and accurate protein side-chain packing, protein structures are modeled using a geometric neighborhood graph, which can be easily decomposed into smaller blocks. Therefore, the side-chain assignment of the whole protein can be assembled from the assignment of the small blocks. Although we will show that the side-chain packing problem is still <i>NP</i>-hard, we can achieve a tree-decomposition-based globally optimal algorithm with time complexity of <i>O</i>(<i>Nn</i><sub><i>rot</i></sub><sup><i>tw</i> + 1)</sup> and several polynomial-time approximation schemes (PTAS), where <i>N</i> is the number of residues contained in the protein, <i>n</i><sub><i>rot</i></sub> the average number of rotamers for each residue, and <i>tw</i> = <i>O</i>(<i>N</i><sup>2/3</sup> log <i>N</i>) the treewidth of the protein structure graph. Experimental results indicate that after Goldstein dead-end elimination is conducted, <i>n</i><sub><i>rot</i></sub> is very small and <i>tw</i> is equal to 3 or 4 most of the time. Based on the globally optimal algorithm, we developed a protein side-chain assignment program TreePack, which runs up to 90 times faster than SCWRL 3.0, a widely-used side-chain packing program, on some large test proteins in the SCWRL benchmark database and an average of five times faster on all the test proteins in this database. There are also some real-world instances that TreePack can solve but that SCWRL 3.0 cannot. The TreePack program is available at http://ttic.uchicago. edu/~jinbo/TreePack.htm.
Receding horizon control of hybrid linear delayed systems: Application to sewer networks

A control-oriented hybrid linear model for water transport in sewer networks is proposed as a suitable framework for the computation of real-time controllers for the minimization of flooding in presence of heavy-rain events. The model is based on individual network elements (sewers, gates, weirs and tanks) and does not rely on topological simplifications, thus providing a better description of the hydrological and hydraulic phenomena than in similar works. Using a generic form of a hybrid linear model, a simple matrix-based procedure for the formulation and solution of an optimal control problem is also presented. This procedure is applied to the sewer network model for the case study of a part of the Barcelona sewer network in a receding horizon control strategy, showing the effectiveness of the proposed control approach.
Replication-based efficient data delivery scheme (red) for delay/fault-tolerant mobile sensor network (DFT-MSN)

The delay/fault-tolerant mobile sensor network (DFT-MSN) has been proposed recently for pervasive information gathering. DFT-MSN distinguishes itself from conventional sensor networks by several unique characteristics such as sensor mobility, loose connectivity, and delay/fault tolerability. The mainstream approaches for sensor networking/communication cannot be applied in DFT-MSN directly. In this paper we propose a replication-based efficient data delivery (RED) scheme based on erasure coding technology tailored for DFT-MSN. RED consists of two key components for data transmission and message management, respectively. The former makes decision on when and where to transmit data messages according to the delivery probability. The latter decides the optimal erasure coding parameters (including the number of data blocks and the needed redundancy) based on its current delivery probability, in order to achieve the desired data delivery ratio while minimizing overhead at the same time. Extensive simulation has been carried out for performance evaluation. Compared with other approaches, the proposed RED data delivery scheme achieves high message delivery ratio with low transmission overhead and data management complexity
SHaDe, a new 3-DOF haptic device

This paper presents a new type of haptic device using spherical geometry. The basic idea of haptic devices is to provide users with feedback information on the motion and/or force that he or she generates. Haptic devices have several potential applications such as, for example, fine compliant assembly, VR environment simulation, and high-precision teleoperation, especially in hazardous or hostile areas. The particular architecture of the spherical haptic device developed here will be presented and its advantages will be highlighted. Then, its basic kinematic properties, which shall be used for control and geometric optimization purposes, will be reviewed. The design optimization itself will then highlight some important features of the mechanism. The control scheme and real-time force feedback issues will then be presented. Finally, the results obtained with the prototype will be discussed.
Disorders of iron metabolism.

Iron has the capacity to accept and donate electrons readily, interconverting between ferric (Fe2+) and ferrous (Fe3+) forms. This capability makes it a useful component of cytochromes, oxygen-binding molecules (i.e., hemoglobin and myoglobin), and many enzymes. However, iron can also damage tissues by catalyzing the conversion of hydrogen peroxide to free-radical ions that attack cellular membranes, proteins, and DNA. Proteins sequester iron to reduce this threat. Iron ions circulate bound to plasma transferrin and accumulate within cells in the form of ferritin. Iron protoporphyrin (heme) and iron–sulfur clusters serve as enzyme cofactors. Under normal circumstances, only trace amounts .
GIS and Multi-Criteria Decision Analysis for Land Use Resource Planning

Natural resources management is indispensable in ensuring environmental sustainability and reducing the risk associated with climate change and increasing demand for ecological goods and services. Natural resources planners need to have at their disposal tools that can objectively help in prioritizing land use allocation. Traditional application of land use change model based on economic model, trend analysis, and or scenario analysis present some challenges of data availability and reliability necessary for implementation of the models. However, with the advent of information technology, GIS and remote sensing, biophysical data known for having influence on land use allocation can easily be accessed. The current study explores the application of GIS-Multi-criteria analysis in modeling future land use scenarios for resources planning and management using easy to construct biophysical parameters known for influencing future land use allocation. The decision problems in this study are to find the best spatial allocation of land to future agriculture and forest development, which are considered to present critical land use change in the study area. The afforestation scenarios are meant to offset the pressure on the native forest resources due to the increased demand for fuel and timber and also to contribute to the environmental protection and the agricultural land use scenarios are meant to increase productivity and ensure environmental protection. The land use scenarios did not consider “when” in the future the land use pattern may develop. The analyses of scenarios indicate that afforestation extent in the basin can be increased from 4.6% to 42.9% of the total basin area. However, the afforestation extent of 42.9% may be considered unrealistic, since in practice, it may not be possible to realize up to 42.9% afforestation, nevertheless, the spatial pattern of the afforestation may provide crucial insight into spatial afforestation policies and it future consequences. The agricultural land use can increase from 6.2% to 53.7% of the basin area. The agricultural land use expansion can be realised since the expansion of farm land is primarily the main option to achieve food production increase in the near future. The findings indicate potential use of the methodology in land use planning.
Towards Explaining the Use of Self-Tracking Devices: Conceptual Development of a Continuance and Discontinuance Model

Users of digital self-tracking devices benefit from information about themselves. Thereby, the explanatory power of this information heavily depends on post-adoption continued usage of these devices. Thus, the aim of our research is to empirically analyze the factors that lead to continuous use of self-tracking devices. So far, research has largely focused on phases until IS adoption in a work environment and little on postadoption use in a consumer context which centers on either continuance or discontinuance. To advance research in this area, we develop a conceptual model that combines both in one comprehensive model by building on established post-adoption theories. We will continue our research with a quantitative-empirical evaluation of the developed model. With our research, we aim at contributing to both a better theoretical understanding in the field of IS post-adoption in a consumer context and giving practical implications for producers of self-tracking devices.