Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of Evolutionarily Conserved Motifs of Epidermal Growth Factor Receptor 2 (HER2) Predicts Novel Potential Therapeutic Epitopes

Overexpression of human epidermal growth factor receptor 2 (HER2) is associated with tumor aggressiveness and poor prognosis in breast cancer. With the availability of therapeutic antibodies against HER2, great strides have been made in the clinical management of HER2 overexpressing breast cancer. However, de novo and acquired resistance to these antibodies presents a serious limitation to successful HER2 targeting treatment. The identification of novel epitopes of HER2 that can be used for functional/region-specific blockade could represent a central step in the development of new clinically relevant anti-HER2 antibodies. In the present study, we present a novel computational approach as an auxiliary tool for identification of novel HER2 epitopes. We hypothesized that the structurally and linearly evolutionarily conserved motifs of the extracellular domain of HER2 (ECD HER2) contain potential druggable epitopes/targets. We employed the PROSITE Scan to detect structurally conserved motifs and PRINTS to search for linearly conserved motifs of ECD HER2. We found that the epitopes recognized by trastuzumab and pertuzumab are located in the predicted conserved motifs of ECD HER2, supporting our initial hypothesis. Considering that structurally and linearly conserved motifs can provide functional specific configurations, we propose that by comparing the two types of conserved motifs, additional druggable epitopes/targets in the ECD HER2 protein can be identified, which can be further modified for potential therapeutic application. Thus, this novel computational process for predicting or searching for potential epitopes or key target sites may contribute to epitope-based vaccine and function-selected drug design, especially when x-ray crystal structure protein data is not available.
Phylogenetic models of rate heterogeneity: a high performance computing perspective

Inference of phylogenetic trees using the maximum likelihood (ML) method is NP-hard. Furthermore, the computation of the likelihood function for huge trees of more than 1,000 organisms is computationally intensive due to a large amount of floating point operations and high memory consumption. Within this context, the present paper compares two competing mathematical models that account for evolutionary rate heterogeneity: the Gamma and CAT models. The intention of this paper is to show that - from a purely empirical point of view - CAT can be used instead of Gamma. The main advantage of CAT over Gamma consists in significantly lower memory consumption and faster inference times. An experimental study using RAxML has been performed on 19 real-world datasets comprising 73 up to 1,663 DNA sequences. Results show that CAT is on average 5.5 times faster than Gamma and - surprisingly enough - also yields trees with slightly superior Gamma likelihood values. The usage of the CAT model decreases the amount of average L2 and L3 cache misses by factor 8.55
Enforcement of Role Based Access Control in Social Network Environments

Role-based access control (RBAC) policies have been implemented in many social network environments to enforce the security. However, enforcing RBAC policies in a social network environment also brings the design complexity and potential security vulnerabilities which may cause insecure information flows. In this paper, we present a framework for formally modeling and analyzing RBAC policies using high level Petri nets and model checking techniques. The high level Petri nets called PZ nets that have been developed based on Predicate/Transitions nets and Z notation have significant benefits for modeling security models through combining modeling capacities from both formalisms, and the analysis technique based on model checking tool SPIN provides an automatic conformance checking of RBAC policies in applications. A case study of the enforcement of RBAC policies in an online file sharing system is performed to demonstrate the effectiveness of the proposed approach.
A practical forwarding scheme for wireless relay channels based on the quantization of log-likelihood ratios

This paper considers a wireless relay network with one source, one relay, and one destination. We propose a low-complexity quantize-and-forward (QF) scheme in which the relay calculates log-likelihood ratios (LLRs) for the code bits transmitted by the source and passes quantized versions of these LLRs on to the destination. The destination combines the LLRs from the source-destination link and the quantized LLRs from the source-relay link to obtain improved information bit estimates. We verify the usefulness of the proposed scheme via numerical simulations in block and fast fading.
Axcaliber: A method for measuring axon diameter distribution from diffusion MRI

The diameter of a myelinated nerve axon is directly proportional to its conduction velocity, so the axon diameter distribution helps determine the channel capacity of nervous transmission along fascicles in the central (CNS) and peripheral nervous systems (PNS). Previously, this histological information could only be obtained using invasive tissue biopsies. Here we propose a new NMR‐based approach that employs a model of water diffusion within “restricted” cylindrical axons to estimate their diameter distribution within a nerve bundle. This approach can be combined with MRI to furnish an estimate of the axon diameter distribution within each voxel. This method is validated by comparing the diameter distributions measured using the NMR and histological techniques on sciatic and optic nerve tissue specimens. The axon diameter distribution measured in each voxel of porcine spinal cord using MRI and using histological methods were similar. Applications are expected in longitudinal studies designed to follow nerve growth in normal and abnormal development, as well as in diagnosing disorders and diseases affecting specific populations of axons in the CNS and PNS. Magn Reson Med 59:1347–1354, 2008. © 2008 Wiley‐Liss, Inc.
Recursive Binary Neural Network Learning Model with 2.28b/Weight Storage Requirement

This paper presents a storage-efficient learning model titled Recursive Binary Neural Networks for sensing devices having a limited amount of on-chip data storage such as < 100's kilo-Bytes. The main idea of the proposed model is to recursively recycle data storage of synaptic weights (parameters) during training. This enables a device with a given storage constraint to train and instantiate a neural network classifier with a larger number of weights on a chip and with a less number of off-chip storage accesses. This enables higher classification accuracy, shorter training time, less energy dissipation, and less on-chip storage requirement. We verified the training model with deep neural network classifiers and the permutation-invariant MNIST benchmark. Our model uses only 2.28 bits/weight while for the same data storage constraint achieving ~1% lower classification error as compared to the conventional binary-weight learning model which yet has to use 8 to 16 bit storage per weight. To achieve the similar classification error, the conventional binary model requires ~4x more data storage for weights than the proposed model.
Water Channels Aquaporin 4 and -1 Expression in Subependymoma Depends on the Localization of the Tumors

Background We analyzed aquaporin 4 and -1 expression in subependymomas, benign and slow growing brain tumors WHO grade I. Ten subependymoma cases were investigated, five of the fossa inferior and five of the fossa superior. Methods and Results Using immunohistochemistry, we observed different aquaporin expression patterns depending on localization: aquaporin 4 and -1 were detected in infratentorial subependymomas in the entire tumor tissue. In contrast, supratentorial subependymomas revealed aquaporin 4 and -1 expression only in border areas of the tumor. PCR analyses however showed no difference in aquaporin 4 expression between all subependymomas independent of localization but at higher levels than in normal brain. In contrast, aquaporin 1 RNA levels were found to be higher only in infratentorial samples compared to supratentorial and normal brain samples. The reason for the different distribution pattern of aquaporin 4 in subependymomas still remains unclear. On the cellular level, aquaporin 4 was redistributed on the surface of the tumor cells, and in freeze fracture replicas no orthogonal arrays of particles were found. This was similar to our previous findings in malignant glioblastomas. From these studies, we know that extracellular matrix molecules within the tumor like agrin and its receptor alpha-dystroglycan are involved in forming orthogonal arrays of particles. In subependymomas neither agrin nor alpha-dystroglycan were detected around blood vessels. Conclusions Taken together, we show in this study that in the benign subependymomas aquaporins 1 and 4 are dramatically redistributed and upregulated. We speculate that extracellular environments of infra- and supratentorial subependymomas are different and lead to different distribution patterns of aquaporin 4 and -1.
The timely expression of myelin basic protein gene in cultured rat brain oligodendrocytes is independent of continuous neuronal influences

The developmental expression of the myelin basic protein (MBP) gene was studied in rat cultured oligodendrocytes using immunofluorescence and in situ hybridization. In newborn rat brain cultures, which contain only glial cells, large amounts of MBP-specific mRNA (as assayed by grain counts in autoradiograms) abruptly accumulated within immature oligodendrocytes 5 to 6 days postnatal. MBP always emerged 6 to 8 days after birth; thus, a week after, galactocerebroside (GC), an early oligodendrocyte marker, had appeared. The percentage of MBP mRNA and MBP-positive cells peaked at about 15 days postnatal and decreased thereafter. The time of emergence of MBP in these cultured oligodendrocytes appears to be determined at a very early stage in their development and independent of continuous neuronal influences. There is a striking correspondence between the times of appearance of MBP in cultured oligodendrocytes and those in the intact animal. Thus, primary cultures made from 5-day prenatal, newborn, and 2-day postnatal animals all express MBP at about the same developmental stage, namely, after 14, 8, and 6 days in culture, respectively. Furthermore, cultured oligodendrocytes obtained from the spinal cord express MBP before those obtained from midbrain or hemispheres, as they would in the intact animal. Thus, the developmental expression of the MBP gene occurs in a similar time frame in vitro and in vivo. In oligodendrocyte-enriched cultures, where 60% to 80% of the cells express MBP, in situ hybridization with the cDNA clone revealed MBP-specific mRNA in the cell body and sometimes in the processes of the differentiated oligodendrocytes. (ABSTRACT TRUNCATED AT 250 WORDS)
Olfactory ensheathing glia express aquaporin 1

Olfactory ensheathing glia (OEG) are distinct from other glia in their developmental origin, presence in both the peripheral and central nervous systems, and highly restricted location. OEG are present only in the olfactory lamina propria, olfactory nerve, and the outer two layers of the olfactory bulb, where they envelop bundles of olfactory sensory neuron axons in a manner distinct from myelination. Because of their unique properties and their association with the continually generated olfactory sensory neurons, OEG have attracted interest for their potential capacity to support axonal regeneration, for example, after spinal cord injury. However, study of the properties and function of OEG has been hampered by a paucity of neurochemical markers with which to identify and distinguish them definitively from other types of glia. Here we provide evidence through anatomical colocalization studies that OEG express the water channel aquaporin 1 (AQP1), both in vivo and in vitro. We propose that AQP1 expression represents an important distinguishing characteristic of OEG, which may impart unique function to these glia. J. Comp. Neurol. 518:4329–4341, 2010. © 2010 Wiley‐Liss, Inc.
Transgenic strategy for identifying synaptic connections in mice by fluorescence complementation (GRASP)

In the “GFP reconstitution across synaptic partners” (GRASP) method, non-fluorescent fragments of GFP are expressed in two different neurons; the fragments self-assemble at synapses between the two to form a fluorophore. GRASP has proven useful for light microscopic identification of synapses in two invertebrate species, Caenorhabditis elegans and Drosophila melanogaster, but has not yet been applied to vertebrates. Here, we describe GRASP constructs that function in mammalian cells and implement a transgenic strategy in which a Cre-dependent gene switch leads to expression of the two fragments in mutually exclusive neuronal subsets in mice. Using a transgenic line that expresses Cre selectively in rod photoreceptors, we demonstrate labeling of synapses in the outer plexiform layer of the retina. Labeling is specific, in that synapses made by rods remain labeled for at least 6 months whereas nearby synapses made by intercalated cone photoreceptors on many of the same interneurons remain unlabeled. We also generated antisera that label reconstituted GFP but neither fragment in order to amplify the GRASP signal and thereby increase the sensitivity of the method.
Credit Risk Assessment Model of Commercial Banks Based on Support Vector Machines

Scope: Commercial banks, as the key of the nation's economy and the center of financial credit, play a multiple irreplaceable role in the financial system. Credit risks threaten the economic system as a whole. Therefore, predicting bank financial credit risks is crucial to prevent and lessen the incoming negative effects on the economic system. Objective: This study aims to apply a credit risk assessment model based on support vector machines (SVMs) in a Chinese case, after analyzing the credit risk rules and building a credit risk system. After the modeling, it presents a comprehensive computational comparison of the classification performances of the techniques tested, including Back-Propagation Neural Network (BPN) and SVMs. Method: In this empirical study, we utilize statistical product and service solutions (SPSS) for the factor analysis on the financial data from the 157 companies and Matlab and Libsvm toolbox for the experimental analysis. Conclusion: We compare the assessment results of SVMs and BPN and get the indication that SVMs are very suitable for the credit risk assessment of commercial banks. Empirical results show that SVMs are effective and more advantageous than BPN. SVMs, with the features of simple classification hyperplane, good generalization ability, accurate goodness of fit, and strong robustness, have a better developing prospect although there are still some problems with them, such as the space mapping of the kernels, the optimizing scale, and so on. They are worthy of our further exploration and research.
Self-Experimentation for Behavior Change: Design and Formative Evaluation of Two Approaches

Desirable outcomes such as health are tightly linked to behaviors, thus inspiring research on technologies that support people in changing those behaviors. Many behavior-change technologies are designed by HCI experts but this approach can make it difficult to personalize support to each user's unique goals and needs. This paper reports on the iterative design of two complementary support strategies for helping users create their own personalized behavior-change plans via self-experimentation: One emphasized the use of interactive instructional materials, and the other additionally introduced context-aware computing to enable user creation of "just in time" home-based interventions. In a formative trial with 27 users, we compared these two approaches to an unstructured sleep education control. Results suggest great promise in both strategies and provide insights on how to develop personalized behavior-change technologies.
MyD88-Dependent Recruitment of Monocytes and Dendritic Cells Required for Protection from Pulmonary Burkholderia mallei Infection

ABSTRACT The Gram-negative bacterium Burkholderia mallei causes rapidly fatal illness in equines and humans when contracted by inhalation and also has the potential to be used as a bioweapon. However, little is known regarding the early innate immune responses and signaling mechanisms required to generate protection from pneumonic B. mallei infection. We showed previously that monocyte chemoattractant protein 1 (MCP-1) was a critical chemokine required for protection from pneumonic B. mallei infection. We have now extended those studies to identify key Toll-like receptor (TLR) signaling pathways, effector cells, and cytokines required for protection from respiratory B. mallei infection. We found that MyD88−/− mice were highly susceptible to pulmonary challenge with B. mallei and had significantly short survival times, increased bacterial burdens, and severe organ pathology compared to wild-type mice. Notably, MyD88−/− mice had significantly fewer monocytes and dendritic cells (DCs) in lung tissues and airways than infected wild-type mice despite markedly higher bacterial burdens. The MyD88−/− mice were also completely unable to produce gamma interferon (IFN-γ) at any time points following infection. In wild-type mice, NK cells were the primary cells producing IFN-γ in the lungs following B. mallei infection, while DCs and monocytes were the primary cellular sources of interleukin-12 (IL-12) production. Treatment with recombinant IFN-γ (rIFN-γ) was able to significantly restore protective immunity in MyD88−/− mice. Thus, we conclude that the MyD88-dependent recruitment of inflammatory monocytes and DCs to the lungs and the local production of IL-12, followed by NK cell production of IFN-γ, are the key initial cellular responses required for early protection from B. mallei infection.
General dominant relationship analysis based on partial order models

Due to the importance of skyline query in many applications, it has been attracted much attention recently. Given an N-dimensional dataset D, a point p is said to dominate another point q if p is better than q in at least one dimension and equal to or better than q in the remaining dimensions. Recently, Li et al. [9] proposed to analyze more general dominant relationship in a business model that, users are more interested in the details of the dominant relationship in a dataset, i.e., a point p dominates how many other points. In this paper, we further generalize this problem that, users are more interested in whom these dominated points are. We show that the framework proposed in [9] can not efficiently solve this problem. We find the interrelated connection between the partial order and the dominant relationship. Based on this discovery, we propose efficient algorithms to answer the general dominant relationship queries by querying the partial order representation of spatial datasets. Extensive experiments illustrate the effectiveness and efficiency of our methods.
Efficient Animation of Point‐Sampled Thin Shells

We present a novel framework for the efficient simulation and animation of discrete thin shells. Our method takes a point sampled surface as input and performs all necessary computations without intermediate triangulation. We discretize the thin shell functional using so-called fibers. Such fibers are locally embedded parametric curves crisscrossing individual point samples. In combination, they create a dense mesh representing the surface structure and connectivity for the shell computations. In particular, we utilize the fibers to approximate the differential surface operators of the thin shell functional. The polynomials underlying the fiber representation allow for a robust and fast simulation of thin shell behavior. Our method supports both elastic and plastic deformations as well as fracturing and tearing of the material. To compute surfaces with rich surface detail, we designed a multiresolution representation which maps a high-resolution surface onto a fiber network of lower resolution. This makes it possible to animate densely sampled models of very high surface complexity. While being tuned for point sampled objects, the presented framework is versatile and can also take triangle meshes or triangle soups as input.
Evaluating the effectiveness of Bayesian and Neural Networks for Adaptive Schedulling Systems

The ability to adjust itself to users' profile is imperative in modern system, given that many people interact with a lot of information in different ways. The creation of adaptive systems is a complex domain that requires very specific methods and the integration of several intelligent techniques, from an intelligent systems development perspective. Designing an adaptive system requires planning and training of user modelling techniques combined with existing system components. Based on the architecture for user modelling on Intelligent and Adaptive Scheduling Systems, this paper presents an analysis of using the mentioned architecture to characterize user's behaviours and a case study comparing the employment of different user classifiers. Bayesian and Artificial Neural Networks were selected as the elements of the computational study and this paper presents a description on how to prepare them to deal with user information.
Lifetime physical activity in postmenopausal Caucasian and Chinese–Canadian women

Physical activity is recognized as a modifiable lifestyle risk factor that may prevent breast cancer. The aim of this cross-sectional study was to compare the physical activity patterns in two populations with different risks for breast cancer. We collected physical activity information from two groups of postmenopausal Canadian women with substantially different risks of developing breast cancer – Caucasians (N=372) and recent Chinese migrants from urban China (N=352). The frequency, duration, and intensity of occupational, household, and recreational activities were measured throughout the lifetime using the interviewer-administered Lifetime Total Physical Activity Questionnaire. Compared with Caucasians, Chinese migrants reported lower average total physical activity over their lifetime and for each age period (0–21, 21–29, 30–39, 40–49, and ≥50 years). Compared with Caucasians, Chinese migrants reported greater lifetime occupational activity, but lower levels of lifetime activity for both household and recreation activity. Among Chinese migrants, reported levels of occupational, household, and recreational activities were all greater in migrants from Mainland China than in migrants from Hong Kong. In conclusion, our results show that total activity was greater amongst Caucasians than Chinese migrants, suggesting that the lower breast cancer risk in urban Chinese women is not likely to be explained by greater total physical activity.