Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploration of unitization processes in episodic memory in Alzheimer's disease

Binding (i.e., to link different components together) is a key mechanism for episodic memory formation. Normal aging is characterized by a decrease in episodic memory for associations. However, associative memory performance can be improved and age -related differences can even be suppressed when associations are unitized, that is when they are encoded as an integrated whole. A previous study in Alzheimer's disease (AD) showed that patients do not benefit from this particular type of encoding in episodic memory, so that their performance for unitized representations remains very poor. The aim of the current study was to assess whether the unitization mechanism itself (i.e., to integrate components into a whole) is impaired in AD or whether a global memory impairment affects all kinds of representations (unitized and non-unitized). We evaluated this hypothesis in thirteen mild Alzheimer patients and twenty healthy control participants. To systematically increase the demands on unitization, pictures of objects and animals were either left intact, separated into two fragments, or separated into four fragments. Participants viewed the pictures and had to unitize them first in order to recognize it and judge whether it would fit into a shoebox. In a subsequent recognition test where all pictures were intact, they had to retrieve pictures they saw earlier. An analysis of correct recognition of studied pictures showed a significant interaction between group and fragmentation level, indicating a decrease in Alzheimer patients’ performance compared to control participants for pictures that were fragmented at study but not for pictures that were intact at encoding. These preliminary findings may suggest that the perceptual mechanism of unitization of fragmented stimuli is impaired in Alzheimer's disease.
The Anticipation of a Severe Initiation

A 2 (anticipated initiation or control) by 2 (male or female) laboratory study (N = 72) sought to delineate factors explaining the effects of severe initiations on group attraction. Building upon Schachter’s affiliation theory, the authors formulated a severity-affiliation-attraction hypothesis (SAAH). SupportingSAAH, an anticipated-initiationconditionincreased participants’level of affiliationtendencyandgroupattractioncompared to a control condition. Also supporting the hypothesis, affiliation tendency significantly mediated the severity-attraction relationship. Interaction effects further indicated that SAAH held only for males, not for females, for whom a mere affiliation-attraction relationship was observed. Results suggest that, contrary to males, the anticipation of a threatening initiation does not appear to be effective in strengthening group attraction via affiliation-related processes for females.
HOMOLOGY MODELLING AND SEQUENCE ANALYSIS OF anxC 3 . 1

During the last two decades, the number of sequence known proteins has increased rapidly. In contrast, the corresponding increment of structure known protein is much slower. The unbalanced situation has critically limited our ability to understand the molecular mechanism of protein and conduct structure based drug design timely by using updated information of newly found sequences. Therefore it is highly desired to model 3D structure of protein by using structural bioinformatics approach by homology modeling. In this study homology modelling approach was utilized to develop 3D structure of Aspergillus fumigatusAf293(anxc3.1). An annexin, (anxC3.1), was isolated and characterized from the industrially important filamentous fungus Aspergillus niger. anxC3.1 is a single copy gene encoding a 506 amino acid predicted protein which contains four annexin repeats. AnxC3.1 expression was found to be unaltered under a variety of conditions such as increased secretion, altered nitrogen source, heat shock, and decreased Ca levels, indicating that anxC3.1 is constitutively expressed. This is the first reported functional characterization of a fungal annexin. So it highly desired to develop model to this protein. Pair wise sequence alignment program like BLAST was employed to study the influence of matrix on sequence alignment. Blosum 62 matrix by BLAST program revealed a clear evolutionary relationship, and this analysis displayed( 30%) identity with the PDB protein 1M9IA. Homology derived, model is generated using geno3d and the model with lowest energy( -14401.90 kcal/mol), RMSD(0.9843A) was considered as the best optimized and superimposed model, and the structure was validated by using prochek analysis.
Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis.

BACKGROUND Serum cystatin C (Cys C) has been proposed as a simple, accurate, and rapid endogenous marker of glomerular filtration rate (GFR) in research and clinical practice. However, there are conflicting reports regarding the superiority of Cys C over serum creatinine (Cr), with a few studies suggesting no significant difference. METHODS We performed a meta-analysis of available data from various studies to compare the accuracy of Cys C and Cr in relation to a reference standard of GFR. A bibliographic search showed 46 articles until December 31, 2001. We also retrieved data from eight other studies presented and published in abstract form. RESULTS The overall correlation coefficient for the reciprocal of serum Cys C (r = 0.816; 95% confidence interval [CI], 0.804 to 0.826) was superior to that of the reciprocal of serum Cr (r = 0.742; 95% CI, 0.726 to 0.758; P < 0.001). Similarly, receiver operating characteristic (ROC)-plot area under the curve (AUC) values for 1/Cys C had greater identity with the reference test for GFR (mean ROC-plot AUC for Cys C, 0.926; 95% CI, 0.892 to 0.960) than ROC-plot AUC values for 1/Cr (mean ROC-plot AUC for serum Cr, 0.837; 95% CI, 0.796 to 0.878; P < 0.001). Immunonephelometric methods of Cys C assay produced significantly greater correlations than other assay methods (r = 0.846 versus r = 0.784; P < 0.001). CONCLUSION In this meta-analysis using currently available data, serum Cys C is clearly superior to serum Cr as a marker of GFR measured by correlation or mean ROC-plot AUC.
Coupled Projections for Adaptation of Dictionaries

Data-driven dictionaries have produced the state-of-the-art results in various classification tasks. However, when the target data has a different distribution than the source data, the learned sparse representation may not be optimal. In this paper, we investigate if it is possible to optimally represent both source and target by a common dictionary. In particular, we describe a technique which jointly learns projections of data in the two domains, and a latent dictionary which can succinctly represent both the domains in the projected low-dimensional space. The algorithm is modified to learn a common discriminative dictionary, which can further improve the classification performance. The algorithm is also effective for adaptation across multiple domains and is extensible to nonlinear feature spaces. The proposed approach does not require any explicit correspondences between the source and target domains, and yields good results even when there are only a few labels available in the target domain. We also extend it to unsupervised adaptation in cases where the same feature is extracted across all domains. Further, it can also be used for heterogeneous domain adaptation, where different features are extracted for different domains. Various recognition experiments show that the proposed method performs on par or better than competitive state-of-the-art methods.
DNA Computing Approach to Semantic Model

In this paper, we propose a new semantic model based on DNA computing. In the model the vertexes denote either a name of the target or both the attributes and attribute values. One path from an initial vertex to a terminal vertex means one object named on the tag. We name this model a semantic model based on DNA computing. The model explains a target object is reasoned out by the combinations between the vertexes. We describe its application to reasoning system by using DNA computing algorithm from theoretical point of a view. Vertexes and edges of the model are encoded to four kinds of nucleotides. The model is represented by double-stranded DNAs. Single-stranded DNAs are hybridized and ligated to let them the double-stranded DNAs, with the complementary sequences of input molecules and knowledge based ones. The generated DNAs are analyzed into necessary strands which are double-stranded DNAs representing the target objects. We discuss the proposed model and application with a simulation of computational complexity.
Ischemia-induced spreading depolarization in the retina

Cortical spreading depolarization is a metabolically costly phenomenon that affects the brain in both health and disease. Following severe stroke, subarachnoid hemorrhage, or traumatic brain injury, cortical spreading depolarization exacerbates tissue damage and enlarges infarct volumes. It is not known, however, whether spreading depolarization also occurs in the retina in vivo. We report now that spreading depolarization episodes are generated in the in vivo rat retina following retinal vessel occlusion produced by photothrombosis. The properties of retinal spreading depolarization are similar to those of cortical spreading depolarization. Retinal spreading depolarization waves propagate at a velocity of 3.0 ± 0.1 mm/min and are associated with a negative shift in direct current potential, a transient cessation of neuronal spiking, arteriole constriction, and a decrease in tissue O2 tension. The frequency of retinal spreading depolarization generation in vivo is reduced by administration of the NMDA antagonist MK-801 and the 5-HT(1D) agonist sumatriptan. Branch retinal vein occlusion is a leading cause of vision loss from vascular disease. Our results suggest that retinal spreading depolarization could contribute to retinal damage in acute retinal ischemia and demonstrate that pharmacological agents can reduce retinal spreading depolarization frequency after retinal vessel occlusion. Blocking retinal spreading depolarization generation may represent a therapeutic strategy for preserving vision in branch retinal vein occlusion patients.
Multivariate logistic regression prediction of fault-proneness in software modules

This paper explores additional features, provided by stepwise logistic regression, which could further improve performance of fault predicting model. Three different models have been used to predict fault-proneness in NASA PROMISE data set and have been compared in terms of accuracy, sensitivity and false alarm rate: one with forward stepwise logistic regression, one with backward stepwise logistic regression and one without stepwise selection in logistic regression. Despite an obvious trade-off between sensitivity and false alarm rate, we can conclude that backward stepwise regression gave the best model.
Structural interpretation of mutations and SNPs using STRAP‐NT

Visualization of residue positions in protein alignments and mapping onto suitable structural models is an important first step in the interpretation of mutations or polymorphisms in terms of protein function, interaction, and thermodynamic stability. Selecting and highlighting large numbers of residue positions in a protein structure can be time‐consuming and tedious with currently available software. Previously, a series of tasks and analyses had to be performed one‐by‐one to map mutations onto 3D protein structures; STRAP‐NT is an extension of STRAP that automates these tasks so that users can quickly and conveniently map mutations onto 3D protein structures. When the structure of the protein of interest is not yet available, a related protein can frequently be found in the structure databases. In this case the alignment of both proteins becomes the crucial part of the analysis. Therefore we embedded these program modules into the Java‐based multiple sequence alignment program STRAP‐NT. STRAP‐NT can simultaneously map an arbitrary number of mutations denoted using either the nucleotide or amino acid sequence. When the designations of the mutations refer to genomic sites, STRAP‐NT translates them into the corresponding amino acid positions, taking intron–exon boundaries into account. STRAP‐NT tightly integrates a number of current protein structure viewers (currently PYMOL, RASMOL, JMOL, and VMD) with which mutations and polymorphisms can be directly displayed on the 3D protein structure model. STRAP‐NT is available at the PDB site and at http://www.charite. de/bioinf/strap/ or http://strapjava.de.
Enhanced Sarcoplasmic Reticulum Ca2+ Leak and Increased Na+-Ca2+ Exchanger Function Underlie Delayed Afterdepolarizations in Patients With Chronic Atrial Fibrillation

Background— Delayed afterdepolarizations (DADs) carried by Na+-Ca2+-exchange current (INCX) in response to sarcoplasmic reticulum (SR) Ca2+ leak can promote atrial fibrillation (AF). The mechanisms leading to delayed afterdepolarizations in AF patients have not been defined. Methods and Results— Protein levels (Western blot), membrane currents and action potentials (patch clamp), and [Ca2+]i (Fluo-3) were measured in right atrial samples from 76 sinus rhythm (control) and 72 chronic AF (cAF) patients. Diastolic [Ca2+]i and SR Ca2+ content (integrated INCX during caffeine-induced Ca2+ transient) were unchanged, whereas diastolic SR Ca2+ leak, estimated by blocking ryanodine receptors (RyR2) with tetracaine, was ≈50% higher in cAF versus control. Single-channel recordings from atrial RyR2 reconstituted into lipid bilayers revealed enhanced open probability in cAF samples, providing a molecular basis for increased SR Ca2+ leak. Calmodulin expression (60%), Ca2+/calmodulin-dependent protein kinase-II (CaMKII) autophosphorylation at Thr287 (87%), and RyR2 phosphorylation at Ser2808 (protein kinase A/CaMKII site, 236%) and Ser2814 (CaMKII site, 77%) were increased in cAF. The selective CaMKII blocker KN-93 decreased SR Ca2+ leak, the frequency of spontaneous Ca2+ release events, and RyR2 open probability in cAF, whereas protein kinase A inhibition with H-89 was ineffective. Knock-in mice with constitutively phosphorylated RyR2 at Ser2814 showed a higher incidence of Ca2+ sparks and increased susceptibility to pacing-induced AF compared with controls. The relationship between [Ca2+]i and INCX density revealed INCX upregulation in cAF. Spontaneous Ca2+ release events accompanied by inward INCX currents and delayed afterdepolarizations/triggered activity occurred more often and the sensitivity of resting membrane voltage to elevated [Ca2+]i (diastolic [Ca2+]i–voltage coupling gain) was higher in cAF compared with control. Conclusions— Enhanced SR Ca2+ leak through CaMKII-hyperphosphorylated RyR2, in combination with larger INCX for a given SR Ca2+ release and increased diastolic [Ca2+]i-voltage coupling gain, causes AF-promoting atrial delayed afterdepolarizations/triggered activity in cAF patients.
Symbol error probabilities for general cooperative links

Cooperative diversity (CD) networks have been receiving a lot of attention recently as a distributed means of improving error performance and capacity. This paper derives the average symbol error probability (SEP) for amplify and forward CD links. The resulting expressions are general as they hold for an arbitrary number of cooperating branches, arbitrary number of cooperating hops per branch, and many channel fading models. Their simplicity provides valuable insights to the performance of CD networks and allows their optimization. Besides revealing the diversity advantage, they clearly show from where this advantage comes from and prove that the diversity advantage holds independently of the channel fading model. Finally, explain how diversity is improved in multihop CD networks.
Iterative Resource Allocation for Memory Intensive Parallel Search Algorithms on Clouds, Grids, and Shared Clusters

The increasing availability of “utility computing” resources such as clouds, grids, and massively parallel shared clusters can provide practically unlimited processing and memory capacity on demand, at some cost per unit of resource usage. This requires a new perspective in the design and evaluation of parallel search algorithms. Previous work in parallel search implicitly assumed ownership of a cluster with a static amount of CPU cores and RAM, and emphasized wallclock runtime. With utility computing resources, trade-offs between performance and monetary costs must be considered. This paper considers dynamically increasing the usage of utility computing resources until a problem is solved. Efficient resource allocation policies are analyzed in comparison with an optimal allocation strategy. We evaluate our iterative allocation strategy by applying it to the HDA* parallel search algorithm. The experimental results validate our theoretical predictions. They show that, in practice, the costs incurred by iterative allocation are reasonably close to an optimal (but a priori unknown) policy, and are significantly better than the worst-case analytical bounds.
DaRPC: Data Center RPC

Remote Procedure Call (RPC) has been the cornerstone of distributed systems since the early 80s. Recently, new classes of large-scale distributed systems running in data centers are posing extra challenges for RPC systems in terms of scaling and latency. We find that existing RPC systems make very poor usage of resources (CPU, memory, network) and are not ready to handle these upcoming workloads. In this paper we present DaRPC, an RPC framework which uses RDMA to implement a tight integration between RPC message processing and network processing in user space. DaRPC efficiently distributes computation, network resources and RPC resources across cores and memory to achieve a high aggregate throughput (2-3M ops/sec) at a very low per-request latency (10μs with iWARP). In the evaluation we show that DaRPC can boost the RPC performance of existing distributed systems in the cloud by more than an order of magnitude for both throughput and latency.
UNISIM: An Open Simulation Environment and Library for Complex Architecture Design and Collaborative Development

Simulator development is already a huge burden for many academic and industry research groups; future complex or heterogeneous multi-cores, as well as the multiplicity of performance metrics and required functionality, will make matters worse. We present a new simulation environment, called UNISIM, which is designed to rationalize simulator development by making it possible and efficient to distribute the overall effort over multiple research groups, even without direct cooperation. UNISIM achieves this goal with a combination of modular software development, distributed communication protocols, multilevel abstract modeling, interoperability capabilities, a set of simulator services APIs, and an open library/repository for providing a consistent set of simulator modules.
Psychometric properties of the Social Phobia Inventory (SPIN)

Background Of available self-rated social phobia scales, none assesses the spectrum of fear, avoidance, and physiological symptoms, all of which are clinically important. Because of this limitation, we developed the Social Phobia Inventory (SPIN). Aims To establish psychometric validation of the SPIN. Method Subjects from three clinical trials and two control groups were given the 17-item, self-rated SPIN. Validity was assessed against several established measures of social anxiety, global assessments of severity and improvement, and scales assessing physical health and disability. Results Good test – retest reliability, internal consistency, convergent and divergent validity were obtained. A SPIN score of 19 distinguished between social phobia subjects and controls. The SPIN was responsive to change in symptoms over time and reflected different responses to active drugs v. placebo. Factorial analysis identified five factors. Conclusions The SPIN demonstrates solid psychometric properties and shows promise as a measurement for the screening of, and treatment response to, social phobia.
Biophysics, pathophysiology, and pharmacology of ion channel gating pores

Voltage sensor domains (VSDs) are a feature of voltage gated ion channels (VGICs) and voltage sensitive proteins. They are composed of four transmembrane (TM) segments (S1–S4). Currents leaking through VSDs are called omega or gating pore currents. Gating pores are caused by mutations of the highly conserved positively charged amino acids in the S4 segment that disrupt interactions between the S4 segment and the gating charge transfer center (GCTC). The GCTC separates the intracellular and extracellular water crevices. The disruption of S4–GCTC interactions allows these crevices to communicate and create a fast activating and non-inactivating alternative cation-selective permeation pathway of low conductance, or a gating pore. Gating pore currents have recently been shown to cause periodic paralysis phenotypes. There is also increasing evidence that gating pores are linked to several other familial diseases. For example, gating pores in Nav1.5 and Kv7.2 channels may underlie mixed arrhythmias associated with dilated cardiomyopathy (DCM) phenotypes and peripheral nerve hyperexcitability (PNH), respectively. There is little evidence for the existence of gating pore blockers. Moreover, it is known that a number of toxins bind to the VSD of a specific domain of Na+ channels. These toxins may thus modulate gating pore currents. This focus on the VSD motif opens up a new area of research centered on developing molecules to treat a number of cell excitability disorders such as epilepsy, cardiac arrhythmias, and pain. The purpose of the present review is to summarize existing knowledge of the pathophysiology, biophysics, and pharmacology of gating pore currents and to serve as a guide for future studies aimed at improving our understanding of gating pores and their pathophysiological roles.
Regulation of a TATA-binding Protein-associated Factor during Cellular Differentiation*

RNA polymerase III transcription is down-regulated when F9 embryonal carcinoma cells differentiate into parietal endoderm. This reflects a decrease in the activity of TFIIIB, a multisubunit complex that is required for all class III gene expression. Two essential components of TFIIIB are the TATA-binding protein (TBP) and an associated polypeptide called BRF that is specific to this complex. The abundance of both TBP and BRF decreases during F9 cell differentiation. Whereas the amount of TBP assembled into TFIIIB is down-regulated, this is not the case for all TBP-containing complexes. BRF levels show a more dramatic decline that appears sufficient to account for the overall change in transcriptional activity. Developmental regulation of a specific class of genes may therefore be achieved through changes in the availability of a TBP-associated factor.
Space-efficient closure representations

Many modern compilers implement function calls (or returns) in two steps: first, a closure environment is properly installed to provide access for free variables in the target program fragment; second, the control is transferred to the target by a “jump with arguments (or results)”. Closure conversion, which decides where and how to represent closures at runtime, is a crucial step in compilation of functional languages. We have a new algorithm that exploits the use of compile-time control and data flow information to optimize closure representations. By extensive closure sharing and allocating as many closures in registers as possible, our new closure conversion algorithm reduces heap allocation by 36% and memory fetches for local/global variables by 43%; and improves the already-efficient code generated by the Standard ML of New Jersey compiler by about 17% on a DECstation 5000. Moreover, unlike most other approaches, our new closure allocation scheme satisfies the strong “safe for space complexity” rule, thus achieving good asymptotic space usage.