Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Uniform Distribution Pattern for Differentially Expressed Genes of Transgenic Rice Huahui 1 at Different Developmental Stages and Environments

DNA microarray analysis is an effective method to detect unintended effects by detecting differentially expressed genes (DEG) in safety assessment of genetically modified (GM) crops. With the aim to reveal the distribution of DEG of GM crops under different conditions, we performed DNA microarray analysis using transgenic rice Huahui 1 (HH1) and its non-transgenic parent Minghui 63 (MH63) at different developmental stages and environmental conditions. Considerable DEG were selected in each group of HH1 under different conditions. For each group of HH1, the number of DEG was different; however, considerable common DEG were shared between different groups of HH1. These findings suggested that both DEG and common DEG were adequate for investigation of unintended effects. Furthermore, a number of significantly changed pathways were found in all groups of HH1, indicating genetic modification caused everlasting changes to plants. To our knowledge, our study for the first time provided the non-uniformly distributed pattern for DEG of GM crops at different developmental stages and environments. Our result also suggested that DEG selected in GM plants at specific developmental stage and environment could act as useful clues for further evaluation of unintended effects of GM plants.
GSK-3β Overexpression Alters the Dendritic Spines of Developmentally Generated Granule Neurons in the Mouse Hippocampal Dentate Gyrus

The dentate gyrus (DG) plays a crucial role in hippocampal-related memory. The most abundant cellular type in the DG, namely granule neurons, are developmentally generated around postnatal day P6 in mice. Moreover, a unique feature of the DG is the occurrence of adult hippocampal neurogenesis, a process that gives rise to newborn granule neurons throughout life. Adult-born and developmentally generated granule neurons share some maturational aspects but differ in others, such as in their positioning within the granule cell layer. Adult hippocampal neurogenesis encompasses a series of plastic changes that modify the function of the hippocampal trisynaptic network. In this regard, it is known that glycogen synthase kinase 3β (GSK-3β) regulates both synaptic plasticity and memory. By using a transgenic mouse overexpressing GSK-3β in hippocampal neurons, we previously demonstrated that the overexpression of this kinase has deleterious effects on the maturation of newborn granule neurons. In the present study, we addressed the effects of GSK-3β overexpression on the morphology and number of dendritic spines of developmentally generated granule neurons. To this end, we performed intracellular injections of Lucifer Yellow in developmentally generated granule neurons of wild-type and GSK-3β-overexpressing mice and analyzed the number and morphologies of dendritic spines (namely, stubby, thin and mushroom). GSK-3β overexpression led to a general reduction in the number of dendritic spines. In addition, it caused a slight reduction in the percentage, head diameter and length of thin spines, whereas the head diameter of mushroom spines was increased.
Distributed Declarative Computing

In this paper we present a general framework for the specification and analysis of declarative distributed computing applications using Answer Set Programming solvers. We first provide an operational semantics of a single computational node, based on Datalog and then show how our framework captures the semantics of a network of computational nodes working together. The framework can express several communication models (e.g. synchronous vs. asynchronous) and distributed solutions to computational tasks can be specified in terms of declarative programs that are not only executable but verifiable. Programs can be analysed with respect to a variety of properties and under different communication models. We take a simple but sufficiently interesting example in the domain of voting/gossip distributed algorithms to illustrate how a distributed computing algorithm can be specified in our framework and show examples of analysis tasks reporting on some experimental results.
Cohesiveness of spatial and directional representations recorded from neural ensembles in the anterior thalamus, parasubiculum, medial entorhinal cortex, and hippocampus

Anatomical and physiological evidence suggests that hippocampal place cells derive their spatial firing properties from the medial entorhinal cortex (MEC) and other parahippocampal areas that send spatial and directional input to the MEC. MEC neurons fire in a precise, geometric pattern, forming a hexagonal grid that tessellates the surface of environments. Similar to place cells and head direction cells, the orientation of grid cell firing patterns can be controlled by visual landmarks, but the cells maintain their firing patterns even in the dark. Place cells and head direction cells can also completely decouple from external landmarks in the light, but it is not known whether the MEC and parahippocampal regions exhibit similar properties or are more explicitly tied to external landmarks. We recorded neurons in the MEC, parasubiculum, and CA1 and head direction cells of the anterior thalamus as the rat's internal direction sense was pitted against a salient visual landmark by slowly rotating the rat in a covered bucket while counter‐rotating the visual cue. In different sessions, spatial firing rate maps and head direction tuning curves either rotated their preferred firing locations/directions by the same amount as the bucket rotation or maintained their preferences in the external laboratory framework. In few cases, the firing preferences rotated with the cue card. When cells from different regions were recorded simultaneously, the dominant response in one area almost always matched the response of the other areas. Although dominant responses were consistent throughout the recording regions, CA1 ensembles exhibited a greater degree of response heterogeneity than other regions, which nearly all exhibited internally consistent responses. Thus, the parahippocampal and MEC input to the hippocampus can be controlled by the animal's internal direction sense (presumably reflected in the firing of head direction cells) and become completely decoupled from external sensory input, yet maintain internal coherence with each other and in general with the place cell system of the hippocampus. © 2007 Wiley‐Liss, Inc.
Budding Yeast Bub2 Is Localized at Spindle Pole Bodies and Activates the Mitotic Checkpoint via a Different Pathway from Mad2

The mitotic checkpoint blocks cell cycle progression before anaphase in case of mistakes in the alignment of chromosomes on the mitotic spindle. In budding yeast, the Mad1, 2, 3, and Bub1, 2, 3 proteins mediate this arrest. Vertebrate homologues of Mad1, 2, 3, and Bub1, 3 bind to unattached kinetochores and prevent progression through mitosis by inhibiting Cdc20/APC-mediated proteolysis of anaphase inhibitors, like Pds1 and B-type cyclins. We investigated the role of Bub2 in budding yeast mitotic checkpoint. The following observations indicate that Bub2 and Mad1, 2 probably activate the checkpoint via different pathways: (a) unlike the other Mad and Bub proteins, Bub2 localizes at the spindle pole body (SPB) throughout the cell cycle; (b) the effect of concomitant lack of Mad1 or Mad2 and Bub2 is additive, since nocodazole-treated mad1 bub2 and mad2 bub2 double mutants rereplicate DNA more rapidly and efficiently than either single mutant; (c) cell cycle progression of bub2 cells in the presence of nocodazole requires the Cdc26 APC subunit, which, conversely, is not required for mad2 cells in the same conditions. Altogether, our data suggest that activation of the mitotic checkpoint blocks progression through mitosis by independent and partially redundant mechanisms.
Vascular endothelial growth factor-A enhances indoleamine 2,3-dioxygenase expression by dendritic cells and subsequently impacts lymphocyte proliferation

Dendritic cells (DCs) are antigen (Ag)-presenting cells that activate and stimulate effective immune responses by T cells, but can also act as negative regulators of these responses and thus play important roles in immune regulation. Pro-angiogenic vascular endothelial growth factor (VEGF) has been shown to cause defective DC differentiation and maturation. Previous studies have demonstrated that the addition of VEGF to DC cultures renders these cells weak stimulators of Ag-specific T cells due to the inhibitory effects mediated by VEGF receptor 1 (VEGFR1) and/or VEGFR2 signalling. As the enzyme indoleamine 2,3-dioxygenase (IDO) is recognised as an important negative regulator of immune responses, this study aimed to investigate whether VEGF affects the expression of IDO by DCs and whether VEGF-matured DCs acquire a suppressor phenotype. Our results are the first to demonstrate that VEGF increases the expression and activity of IDO in DCs, which has a suppressive effect on Ag-specific and mitogen-stimulated lymphocyte proliferation. These mechanisms have broad implications for the study of immunological responses and tolerance under conditions as diverse as cancer, graft rejection and autoimmunity.
Classification in Networked Data with Heterophily

In the real world, a large amount of data can be described by networks using relations between data. The data described by networks can be called networked data. Classification is one of the main tasks in analyzing networked data. Most of the previous methods find the class of the unlabeled node using the classes of its neighbor nodes. However, in the networks with heterophily, most of connected nodes belong to different classes. It is hard to get the correct class using the classes of neighbor nodes, so the previous methods have a low level of performance in the networks with heterophily. In this paper, a probabilistic method is proposed to address this problem. Firstly, the class propagating distribution of the node is proposed to describe the probabilities that its neighbor nodes belong to each class. After that, the class propagating distributions of neighbor nodes are used to calculate the class of the unlabeled node. At last, a classification algorithm based on class propagating distribution is presented in the form of matrix operations. In empirical study, we apply the proposed algorithm to the real-world datasets, compared with some other algorithms. The experimental results show that the proposed algorithm performs better when the networks are of heterophily.
CD 18-dependent activation of the neutrophil NADPH oxidase during phagocytosis of Escherichia coli or Staphylococcus aureus is regulated by class III but not class I or II PI 3 Ks

Phagocytosis and activation of the NADPH oxidase are important mechanisms by which neutrophils and macrophages engulf and kill microbial pathogens. We investigated the role of PI3K signaling pathways in the regulation of the oxidase during phagocytosis of Staphylococcus aureus and Escherichia coli by mouse and human neutrophils, a mouse macrophage-like cell line and a human myeloid-like cell line. Phagocytosis of these bacteria was promoted by serum, independent of serum-derived antibodies, and effectively abolished in mouse neutrophils lacking the 2-integrin common chain, CD18. A combination of PI3K isoform-selective inhibitors, mouse knock-outs, and RNA-interference indicated CD18-dependent activation of the oxidase was independent of class I and II PI3Ks, but substantially dependent on the single class III isoform (Vps34). Class III PI3K was responsible for the synthesis of PtdIns(3)P on phagosomes containing either bacteria. The use of mouse neutrophils carrying an appropriate knock-in mutation indicated that PtdIns(3)P binding to the PX domain of their p40phox oxidase subunit is important for oxidase activation in response to both S aureus and E coli. This interaction does not, however, account for all the PI3K sensitivity of these responses, particularly the oxidase response to E coli, suggesting that additional mechanisms for PtdIns(3)Pregulation of the oxidase must exist. (Blood. 2008;112:5202-5211)
Network Intrusion Alert Aggregation Based on PCA and Expectation Maximization Clustering Algorithm

Most of the organizations implemented various security sensors for increased information security and assurance. A popular choice is Network Intrusion Detection Systems (NIDSs). Unfortunately, NIDSs trigger a massive amount of alerts even for a day and overwhelmed security experts. Worse, a large number of these alerts are false positives, and redundant warnings for the same attack, or alert notifications from erroneous activity. Such low quality of alerts gives negative impact to the alert analysis. We propose an alert aggregation model based on Principal Component Analysis (PCA) coupled with unsupervised learning clustering algorithm - Expectation Maximization for Gaussian Mixture (EM_GM) to aggregate similar alerts and to reduce the number of alerts. Our empirical results show that the proposed model effectively clustered NIDSs alerts and significantly reduced the alert volume.
Voronoi-based Variational Reconstruction of Unoriented Point Sets

1. Briefly summarize the paper's contributions. Does it address a new problem? Does it present a new approach? Does it show new types of results?  [AS] This paper presents a new approach to estimating unoriented normals from an unoriented set of input points, and using this tensor field to find an implicit function representing the surface defined by the input point set.  [DS] The paper presents an algorithm for reconstructing (debatably) watertight surfaces from unoriented point sets. They use the Voronoi diagram of the point set to compute a tensor field that represents the most likely direction of the normal to the surface and the confidence of the estimate. An implicit function is found by solving a generalized eigenvalue problem so that the gradient is aligned with the normal direction estimates. The approach is resilient to noise, and provides parameters to adjust data fitting and smoothness of the reconstructed surface. require of accurate surface normal at sample position. When this normal is not provided, traditional approaches to compute it are based in PCA (e.g. Hoppe 1992), or Voronoi Poles. Global orientation of normal is then attained using MST on a normal propagation graph. This paper looks for a simultaneous solution of the implicit surface and the normal orientation problems, by minimizing a global energy on a tensor field. This tensor field is given by the covariance matrix on expanded Voronoi regions. The optimization step compute an implicit function whose gradient align with the principal directions of the tensor field and is constrained both in smoothness of the gradient field and data fitting (i.e., sample positions at zero level).  [JD]  [LF] The paper presents a new technique for approximating unoriented normals that combines qualities of the PCA and Voronoi pole approaches for doing so and outperforms those two approaches.  [MK] The paper proposes a new variational approach to surface reconstruction that does not require knowing, or even estimating, surface normals. 2. What is the key insight of the paper? (in 1-2 sentences)  [AS] The key insight of this paper is that by combining the idea behind PCA and Voronoi poles, and estimating unoriented normals from covariance matrices of a union of Voronoi cells, we can obtain better estimates of the normal direction. Isosurfacing the implicit function whose gradient is best aligned with the principal axes of this covariant tensor field will provide the best fitting …
Trust Management for Web Services

In this paper, we propose a comprehensive trust management approach for Web services that covers the analysis/modelling of trust relationships and the development of trust management layer in a consistent manner. The specific characteristics of trust relationships in Web services are discussed. We introduce a separated trust management layer for Web services that can hold computing components for trust management tasks. A trust management architecture for Web services is proposed for building up the trust management layer. The proposed trust management architecture for Web services deals with trust requirements, trust evaluation, and trust consumption in Web services under a unified umbrella and it provides a solid foundation upon which may evolve the trust management layer for Web services.
IEEE 802.15.4 low rate - wireless personal area network coexistence issues

IEEE 802.15. 4 is a proposed standard addressing the needs of low-rate wireless personal area networks or LR-WPAN with a focus on enabling wireless sensor networks. The standard is characterized by maintaining a high level of simplicity, allowing for low cost and low power implementations. Its operational frequency band includes the 2.4 GHz industrial, scientific and medical band providing nearly worldwide availability; additionally, this band is also used by other IEEE 802 wireless standards. Coexistence among diverse collocated devices in the 2.4 GHz band is an important issue in order to ensure that each wireless service maintains its desired performance requirements. This paper presents a brief technical introduction of the IEEE 802.15. 4 standard and analyzes the coexistence impact of an IEEE 802.15. 4 network on the IEEE 802.11b devices.
On MIMO for UTRA LTE

The long term evolution of UMTS (Universal Mobile Telecommunications System), UTRA LTE, is based on OFDM (orthogonal frequency division multiplexing) combined with MIMO (multiple-input multiple-output) techniques. In particular, the Alamouti and the V-BLAST (Vertical Bell Labs Layered Space Time) schemes are seen as interesting MIMO concepts. In this communication, the authors will compare these two MIMO schemes w.r. t. the achievable performance in the UTRA LTE downlink using up to two transmit and two receive antennas.
Glucose Metabolism during Liver Transplantation in Dogs

Arterial and hepatic venous blood levels of glucose were studied in 12 dogs during orthotopic liver transplantation performed under ketamine anesthesia without exogenous glucose administration. During the early part of surgery, arterial blood glucose levels were stable: 161 ± 12 mg/dl (mean ± SEM) after laparotomy and 183 ± 16mg/dl 5 min before the anhepatic stage. During the anhepatic stage, arterial blood glucose levels decreased progressively to 135 ± 9 and 88 ± 8 mg/dl, 5 min in the anhepatic stage and 5 min before reperfusion of the graft liver, respectively (P < 0.05). Reperfusion of the graft liver resulted in an increase in arterial glucose levels to 206 ± 17 and 240 ± 24 mg/dl, 5 and 30 min after reperfusion, respectively (P < 0.05). Hepatic venous blood glucose levels increased after reperfusion (405 ± 37 and 346 ± 41 mg/dl, 5 and 30 min after reperfusion, respectively) and were significantly higher than in arterial blood (P < 0.05). Arterial plasma insulin, measured in five animals, did not change significantly during the procedure, whereas plasma glucagon levels, stable during the preanhepatic and anhepatic stages, increased steadily after reperfusion of the graft liver, from 66.1 ± 14.2 to 108.4 ± 38.1 pg/ml (P < 0.05). This study shows that in dogs with ketamine anesthesia mild hypoglycemia occurs during the anhepatic stage of liver transplantation without exogenous glucose administration followed by hyperglycemia on reperfusion of the graft liver, possibly secondary to the release of glucose from the donor liver.
Molecular Characteristics of Extended-Spectrum Cephalosporin-Resistant Enterobacteriaceae from Humans in the Community

Objective To investigate the molecular characteristics of extended-spectrum cephalosporin (ESC)-resistant Enterobacteriaceae collected during a cross-sectional study examining the prevalence and risk factors for faecal carriage of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae in humans living in areas with high or low broiler density. Methods ESC-resistant Enterobacteriaceae were identified by combination disc-diffusion test. ESBL/AmpC/carbapenemase genes were analysed using PCR and sequencing. For E. coli, phylogenetic groups and MLST were determined. Plasmids were characterized by transformation and PCR-based replicon typing. Subtyping of plasmids was done by plasmid multilocus sequence typing. Results 175 ESC-resistant Enterobacteriaceae were cultured from 165/1,033 individuals. The isolates were Escherichia coli(n=65), Citrobacter freundii (n=52), Enterobacter cloacae (n=38), Morganella morganii (n=5), Enterobacter aerogenes (n=4), Klebsiella pneumoniae (n=3), Hafnia alvei (n=2), Shigella spp. (n=2), Citrobacter amalonaticus (n=1), Escherichia hermannii (n=1), Kluyvera cryocrescens (n=1), and Pantoea agglomerans (n=1). The following ESBL genes were recovered in 55 isolates originating from 49 of 1,033 (4.7 %) persons: bla CTX-M-1 (n=17), bla CTX-M-15 (n=16), bla CTX-M-14 (n=9), bla CTX-M-2 (n=3), bla CTX-M-3 (n=2), bla CTX-M-24 (n=2), bla CTX-M-27 (n=1), bla CTX-M-32 (n=1), bla SHV-12 (n=2), bla SHV-65 (n=1) and bla TEM-52 (n=1). Plasmidic AmpC (pAmpC) genes were discovered in 6 out of 1,033 (0.6 %) persons. One person carried two different E. coli isolates, one with bla CTX-M-1 and the other with bla CMY-2 and therefore the prevalence of persons carrying Enterobacteriaceae harboring ESBL and/or pAmpC genes was 5.2 %. In eight E. coli isolates the AmpC phenotype was caused by mutations in the AmpC promoter region. No carbapenemase genes were identified. A large variety of E. coli genotypes was found, ST131 and ST10 being most common. Conclusions ESBL/pAmpC genes resembled those from patients in Dutch hospitals, indicating that healthy humans form a reservoir for transmission of these determinants to vulnerable people. The role of poultry in the transmission to humans in the community remains to be elucidated.
Swarm Intelligence in Educational Data Mining

This paper explores the potential intersection of two fascinating and increasingly burgeoning fields: Swarm Intelligence and Educational Data Mining. A thorough review of the existing works in both fields has revealed a lack of Swarm Intelligence applications in Educational Data Mining, despite its successful applications in other data mining domain. Consequently, this paper launches the intersection of the two emerging fields by applying Swarm Intelligence techniques to an Educational Data Mining classification problem. More specifically, it proposes the use of Particle Swarm Classification to classify teachers' classroom questions into the cognitive levels identified in Bloom's taxonomy. To do so, a dataset of questions has been collected and classified manually into Bloom's cognitive levels. Preprocessing steps have been applied to convert questions into a suitable representation. Using the dataset, the performance of Particle Swarm Classification is evaluated against several traditional machine learning approaches. The initial results provide evidences on the superiority of Particle Swarm Classification technique over the best traditional machine learning approaches.
Physics Computing

Computing is the third mode of research in physics which bridges the gap between analytical theory and laboratory experiment (1). Experiments search for patterns in complex natural phenomena. Theories encode the discovered patterns into mathematical equations that provide predictive laws for the behavior of nature. Computer simulations solve these equations numerically in their full complexity, where analytical solutions are prohibitive due to a large number of degree of freedom, nonlinearity, or lack of symmetry. In computer simulations, environments are controlled perfectly and extreme conditions are accessible beyond the scope of laboratory experiments.