Miracle-dz/UniFAR-FTUs huggingface dataset:
Antioxidant and hepatoprotective role of gold nanoparticles against murine hepatic schistosomiasis

In recent years, gold nanoparticles (AuNPs) have become the focus of much attention in biomedical research, especially in the context of nanomedicine, due to their distinctive physicochemical properties. The current study was planned to assess the effect of three dose levels of AuNPs on the gene expression, histology, and oxidative stress status of Schistosoma mansoni-infected mice liver. Inoculation of mice with 100 μL AuNPs at different doses (0.25, 0.5, and 1 mg/kg mice body weight) twice on day 46 and day 49 postinfection reduced the total worm burden, the egg load in the liver, and the granuloma size. AuNPs also appeared to decrease the activities of malondialdehyde and nitric oxide significantly, and increase the level of glutathione compared to the infected untreated group. Concomitantly, AuNPs ameliorated the inflammatory response by decreasing the mRNA expression of interleukin-1β, interleukin-6, tumor necrosis factor-α, interferon-γ, and inducible nitric oxide synthase. These consistent molecular, histopathological, and biochemical data suggest that AuNPs could ameliorate infection-induced damage in the livers of mice. Our results indicated that AuNPs are effective anti-schistosomal and antioxidant agents. Further confirmation of the role of nanogold as an anti-schistosomal agent, as well as its mechanism of action, requires further studies to be undertaken in the future.
A Tale of Three Cell Types: Alkaloid Biosynthesis Is Localized to Sieve Elements in Opium Poppy Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.015396.

Opium poppy produces a diverse array of pharmaceutical alkaloids, including the narcotic analgesics morphine and codeine. The benzylisoquinoline alkaloids of opium poppy accumulate in the cytoplasm, or latex, of specialized laticifers that accompany vascular tissues throughout the plant. However, immunofluorescence labeling using affinity-purified antibodies showed that three key enzymes, (S)-N-methylcoclaurine 3′-hydroxylase (CYP80B1), berberine bridge enzyme (BBE), and codeinone reductase (COR), involved in the biosynthesis of morphine and the related antimicrobial alkaloid sanguinarine, are restricted to the parietal region of sieve elements adjacent or proximal to laticifers. The localization of laticifers was demonstrated using antibodies specific to the major latex protein (MLP), which is characteristic of the cell type. In situ hybridization showed that CYP80B1, BBE, and COR gene transcripts were found in the companion cell paired with each sieve element, whereas MLP transcripts were restricted to laticifers. The biosynthesis and accumulation of alkaloids in opium poppy involves cell types not implicated previously in plant secondary metabolism and dramatically extends the function of sieve elements beyond the transport of solutes and information macromolecules in plants.
Four Serologic Tests for Syphilis: Results with Comparison of Selected Groups of Sera

The specificity of the fluorescent treponemal antibody-absorbed (FTA-Abs) test was assessed for 17 sera from syphilitic patients that were nonreactive in the Treponema pallidum immobilization (TPI) test but reactive in the FTA-Abs test. Thirty-three other sera from syphilitic patients and 19 sera from nonsyphilitic individuals were also examined by fluorescent treponemal and microhemagglutination Treponema pallidum (MHA-TP) tests and by the enzyme-linked immunosorbent assay (ELISA). Specific absorptions of sera with calf thymus DNA or Treponema pallidum biotype Reiter (Reiter treponemes) were performed. In quantitative immunofluorescence assays (IFA) with antihuman IgG and IgM conjugates, results were similar to those for reactive sera from a control group. Results of both the MHA-TP and ELISA tests supported the specificity of the FTA-Abs test; reactivity in the latter was not removed by specific absorption either with calf thymus DNA or with Reiter treponemes. This evaluation suggests a format for serodiagnosis in cases in which test results are discrepant.
A Maximum-Likelihood Method for the Estimation of Pairwise Relatedness in Structured Populations

A maximum-likelihood estimator for pairwise relatedness is presented for the situation in which the individuals under consideration come from a large outbred subpopulation of the population for which allele frequencies are known. We demonstrate via simulations that a variety of commonly used estimators that do not take this kind of misspecification of allele frequencies into account will systematically overestimate the degree of relatedness between two individuals from a subpopulation. A maximum-likelihood estimator that includes FST as a parameter is introduced with the goal of producing the relatedness estimates that would have been obtained if the subpopulation allele frequencies had been known. This estimator is shown to work quite well, even when the value of FST is misspecified. Bootstrap confidence intervals are also examined and shown to exhibit close to nominal coverage when FST is correctly specified.
A Polyhedral Approximation Framework for Convex and Robust Distributed Optimization

In this paper, we consider a general problem setup for a wide class of convex and robust distributed optimization problems in peer-to-peer networks. In this setup, convex constraint sets are distributed to the network processors who have to compute the optimizer of a linear cost function subject to the constraints. We propose a novel fully distributed and asynchronous algorithm, named cutting-plane consensus, to solve the problem, based on a polyhedral outer approximation of the constraint sets. Processors running the algorithm compute and exchange linear approximations of their locally feasible sets. Independently of the number of processors in the network, each processor stores only a small number of linear constraints, making the algorithm scalable to large networks. The cutting-plane consensus algorithm is presented and analyzed for the general framework. Specifically, we prove the correctness of the algorithm, and show its robustness against communication or processor failures. Then, the cutting-plane consensus algorithm is specified to three different classes of distributed optimization problems, namely 1) inequality constrained problems, 2) robust optimization problems, and 3) almost separable optimization problems. For each one of these problem classes we solve a concrete problem and present computational results. That is, we show how to solve: position estimation in wireless sensor networks, a distributed robust linear program, and a distributed microgrid control problem.
Optimization of non-linear image registration in AFNI

The Analysis of Functional Neuroimaging (AFNI) suite [1], a set of C programs and auxiliary scripts for processing, analyzing, and displaying functional Magnetic Resonance Imaging (fMRI) data (a technique for mapping human brain activity), is a widely adopted open-source tool in the MRI data analysis community. For many types of analysis pipelines, a key step is to register a subject's image to a pre-defined template so different images can be compared within a normalized coordinate. Although a 12-point affine transformation that includes translation, rotation, scaling, and shear works fine for some standard cases, it is usually found to be insufficient for voxel-wise types of analyses. The need for some other approach is exacerbated if the subject has brain atrophy due to some kind of neurological conditions such as Parkinson's disease. The 3dQwarp code in AFNI is a non-linear image registration procedure that overcomes the drawbacks of a canonical affine transformation. However, the existing OpenMP parallelization in 3dQwarp does not scale well when warping at an ultra fine level, and the hard-coded number of iterations of the iterative algorithm also limits the accuracy. Based on profiling and benchmark analysis, we improve the parallel efficiency of 3dQwarp by the optimization of its OpenMP structure and obtain about a 2x speedup for a normalized workload. With the incorporation of convergence criteria, we are able to perform warping at a much finer resolution than before and achieve on average 20% improvement in accuracy with respect to Pearson correlation measure.
Coupling of Fc&ggr; Receptor I to Fc&ggr; Receptor IIB by Src Kinase Mediates C-Reactive Protein Impairment of Endothelial Function

Rationale: Elevations in C-reactive protein (CRP) are associated with increased cardiovascular disease risk and endothelial dysfunction. CRP antagonizes endothelial nitric oxide synthase (eNOS) through processes mediated by the IgG receptor Fc&ggr; receptor IIB (Fc&ggr;RIIB), its immunoreceptor tyrosine-based inhibitory motif, and SH2 domain-containing inositol 5′-phosphatase 1. In mice, CRP actions on eNOS blunt carotid artery re-endothelialization. Objective: How CRP activates Fc&ggr;RIIB in endothelium is not known. We determined the role of Fc&ggr; receptor I (Fc&ggr;RI) and the basis for coupling of Fc&ggr;RI to Fc&ggr;RIIB in endothelium. Methods and Results: In cultured endothelial cells, Fc&ggr;RI-blocking antibodies prevented CRP antagonism of eNOS, and CRP activated Src via Fc&ggr;RI. CRP-induced increases in Fc&ggr;RIIB immunoreceptor tyrosine-based inhibitory motif phosphorylation and SH2 domain-containing inositol 5′-phosphatase 1 activation were Src-dependent, and Src inhibition prevented eNOS antagonism by CRP. Similar processes mediated eNOS antagonism by aggregated IgG used to mimic immune complex. Carotid artery re-endothelialization was evaluated in offspring from crosses of CRP transgenic mice (TG-CRP) with either mice lacking the &ggr; subunit of Fc&ggr;RI (FcR&ggr;−/−) or Fc&ggr;RIIB−/− mice. Whereas re-endothelialization was impaired in TG-CRP vs wild-type, it was normal in both FcR&ggr;−/−; TG-CRP and Fc&ggr;RIIB−/−; TG-CRP mice. Conclusions: CRP antagonism of eNOS is mediated by the coupling of Fc&ggr;RI to Fc&ggr;RIIB by Src kinase and resulting activation of SH2 domain-containing inositol 5′-phosphatase 1, and consistent with this mechanism, both Fc&ggr;RI and Fc&ggr;RIIB are required for CRP to blunt endothelial repair in vivo. Similar mechanisms underlie eNOS antagonism by immune complex. Fc&ggr;RI and Fc&ggr;RIIB may be novel therapeutic targets for preventing endothelial dysfunction in inflammatory or immune complex-mediated conditions.
Inhibited growth of colon cancer carcinomatosis by antibodies to vascular endothelial and epidermal growth factor receptors

Vascular endothelial growth factor (VEGF) and epidermal growth factor (EGF) regulate colon cancer growth and metastasis. Previous studies utilizing antibodies against the VEGF receptor (DC101) or EGF receptor (C225) have demonstrated independently that these agents can inhibit tumour growth and induce apoptosis in colon cancer in in vivo and in vitro systems. We hypothesized that simultaneous blockade of the VEGF and EGF receptors would enhance the therapy of colon cancer in a mouse model of peritoneal carcinomatosis. Nude mice were given intraperitoneal injection of KM12L4 human colon cancer cells to generate peritoneal metastases. Mice were then randomized into one of four treatment groups: control, anti-VEGFR (DC101), anti-EGFR (C225), or DC101 and C225. Relative to the control group, treatment with DC101 or with DC101+C225 decreased tumour vascularity, growth, proliferation, formation of ascites and increased apoptosis of both tumour cells and endothelial cells. Although C225 therapy did not change any of the above parameters, C225 combined with DC101 led to a significant decrease in tumour vascularity and increases in tumour cell and endothelial cell apoptosis (vs the DC101 group). These findings suggest that DC101 inhibits angiogenesis, endothelial cell survival, and VEGF-mediated ascites formation in a murine model of colon cancer carcinomatosis. The addition of C225 to DC101 appears to lead to a further decrease in angiogenesis and ascites formation. Combination anti-VEGF and anti-EGFR therapy may represent a novel therapeutic strategy for the management of colon peritoneal carcinomatosis. © 2001 Cancer Research Campaign http://www.bjcancer. com
Neural signatures of strategic types in a two-person bargaining game

The management and manipulation of our own social image in the minds of others requires difficult and poorly understood computations. One computation useful in social image management is strategic deception: our ability and willingness to manipulate other people's beliefs about ourselves for gain. We used an interpersonal bargaining game to probe the capacity of players to manage their partner's beliefs about them. This probe parsed the group of subjects into three behavioral types according to their revealed level of strategic deception; these types were also distinguished by neural data measured during the game. The most deceptive subjects emitted behavioral signals that mimicked a more benign behavioral type, and their brains showed differential activation in right dorsolateral prefrontal cortex and left Brodmann area 10 at the time of this deception. In addition, strategic types showed a significant correlation between activation in the right temporoparietal junction and expected payoff that was absent in the other groups. The neurobehavioral types identified by the game raise the possibility of identifying quantitative biomarkers for the capacity to manipulate and maintain a social image in another person's mind.
Genetic Algorithm for Balancing WiFi and LTE Coexistence in the Unlicensed Spectrum

In order to expand the Long Term Evolution (LTE) to the unlicensed spectrum, its coexistence with WiFi must be carefully considered. In this paper, we propose a multiobjective optimization framework to balance the performances of WiFi and LTE in the unlicensed spectrum. In particular, three objectives are simultaneously optimized, namely, the WiFi throughput, the LTE throughput, and the average packet delay of WiFi. Furthermore, we utilize the non-dominated sorting genetic algorithm II (NSGA-II) to obtain the complete Pareto optimal solution set of the optimization problem. The algorithm has the merits of low- complexity, robustness, fast convergence, and completeness. Simulation results demonstrate that the proposed method is able to generate a satisfactory Pareto optimal solution plane, which provides a good reference for network operator to determine the appropriate system operation point.
Gradient-Like Observers for Invariant Dynamics on a Lie Group

This paper proposes a design methodology for non-linear state observers for invariant kinematic systems posed on finite dimensional connected Lie groups, and studies the associated fundamental system structure. The concept of synchrony of two dynamical systems is specialized to systems on Lie groups. For invariant systems this leads to a general factorization theorem of a nonlinear observer into a synchronous (internal model) term and an innovation term. The synchronous term is fully specified by the system model. We propose a design methodology for the innovation term based on gradient-like terms derived from invariant or non-invariant cost functions. The resulting nonlinear observers have strong (almost) global convergence properties and examples are used to demonstrate the relevance of the proposed approach.
The Impact of a Physical Activity Session on Year Two Students' Subsequent Classroom Behaviour

The purpose of this study was to examine the impact of a 30-minute physical activity (PA) session on Year Two students’ subsequent classroom behaviour. Forty-eight students from three Year Two classes at a NSW private school participated in the study. The number of disciplinary comments directed by the class teacher to individual students (Individual Disciplinary Corrections, IDC) and the class as a whole (General Disciplinary Corrections, GDC) were recorded during a 30-minute lesson with and without previous PA. Subsequent to PA, there were 40% fewer IDCs (p=0.008) and 59% fewer GDCs (p=0.003), amounting to a 49% overall reduction in disciplinary corrections (p = 0.012). The PA session had a positive effect on the Year Two students’ classroom on-task behaviour, as measured by a reduction in disciplinary corrections directed by the class teacher. These findings highlight the potential value of physical activity as a strategy for increasing student classroom on-task behaviour.
ADHD-200 Patient Characterization and Classification using Resting State Networks: A Dissertation

Attention Deficit/Hyperactivity Disorder (ADHD) is a common psychiatric disorder of childhood that is characterized by symptoms of inattention, impulsivity/hyperactivity, or a combination of both. Intrinsic brain dysfunction in ADHD can be examined through various methods including resting state functional Magnetic Resonance Imaging (rs-fMRI), which investigates patients’ functional brain connections in the absence of an explicit task. To date, studies of group differences in resting brain connectivity between patients with ADHD and typically developing controls (TDCs) have revealed reduced connectivity within the Default Mode Network (DMN), a resting state network implicated in introspection, mind-wandering, and day-dreaming. However, few studies have addressed the use of resting state connectivity measures as a diagnostic aide for ADHD on the individual patient level. In the current work, we attempted first to characterize the differences in resting state networks, including the DMN and three attention networks (the salience network, the left executive network, and the right executive network), between a group of youth with ADHD and a group of TDCs matched for age, IQ, gender, and handedness. Significant over- and under-connections were found in the ADHD group in all of these networks compared with TDCs. We then attempted to use a support vector machine (SVM) based on the information extracted from resting state network connectivity to classify participants as “ADHD” or “TDC. ” The IFGmiddle temporal network (66.8% accuracy), the parietal association network (86.6% specificity and 48.5% PPV), and a physiological noise component (sensitivity 39.7% and NPV 69.6%) performed the best classifications. Finally, we attempted to combine and utilize information from all the resting state networks that we identified to improve classification accuracy. Contrary to our hypothesis, classification accuracy decreased to 54-55% when this information was combined. Overall, the work presented here supports the theory that the ADHD brain is differently connected at rest than that of TDCs, and that this information may be useful for developing a diagnostic aid. However, because ADHD is such a heterogeneous disorder, each ADHD patient’s underlying brain deficits may be unique making it difficult to determine what connectivity information is diagnostically useful.
Order-Extended Sparse RLS Algorithm for Doubly-Selective MIMO Channel Estimation

We develop a recursive least-squares (RLS) algorithm which employs L1-Lq regularized sparse regressions to estimate a sparse channel matrix in frequency-and-time selective fading for multi-input multi-output (MIMO) wireless communications. We propose an improved sparse RLS by using an order extension technique for rapid fading channels. Simulation results demonstrate that the proposed sparse RLS algorithm offers a significant improvement over the conventional RLS algorithm.
A user-programmable vertex engine

In this paper we describe the design, programming interface, and implementation of a very efficient user-programmable vertex engine. The vertex engine of NVIDIA's GeForce3 GPU evolved from a highly tuned fixed-function pipeline requiring considerable knowledge to program. Programs operate only on a stream of independent vertices traversing the pipe. Embedded in the broader fixed function pipeline, our approach preserves parallelism sacrificed by previous approaches. The programmer is presented with a straightforward programming model, which is supported by transparent multi-threading and bypassing to preserve parallelism and performance. In the remainder of the paper we discuss the motivation behind our design and contrast it with previous work. We present the programming model, the instruction set selection process, and details of the hardware implementation. Finally, we discuss important API design issues encountered when creating an interface to such a device. We close with thoughts about the future of programmable graphics devices.
Topological SLAM using neighbourhood information of places

Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM (simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.
An approach to the measurement of intangible assets in dot com

A sample of 40 firms that operate on the Internet is studied to explore ways of identifying and measuring intangible assets in this area of business. The firms meet three conditions: operate on the Internet, have available accounting information, and are quoted on the stock exchange. Data was obtained for four web metrics indicators, 30 ratios that combine accounting and web traffic information, and a measure of efficiency based on Data Envelopment Analysis. Modelling relied on multivariate statistical approaches. Two intangible assets were identified: one was related to internal structure and was associated with managerial efficiency in achieving an impact in the Internet; and another one was associated with external image and customer loyalty.
A radioactive antigen-binding assay for Neisseria meningitidis polysaccharide antibody.

A modification of the Farr technique (see reference 7) was used to develop a highly sensitive and specific radioactive antigen-binding assay for the detection of antipolysaccharide antibody to the groups B and C meningococci. Labeled polysaccharide was extracted from 16-hr culture supernatants of organisms grown in modified Frantz medium containing 14C sodium acetate. The polysaccharide was precipitated by Cetavlon and purified by CaCl2 extraction, ethanol fractionation and Sepharose 4B chromatography. The assay was shown to be highly reproducible and group specific. An unexpected cross-reaction was demonstrated between certain anti-B antisera with the group C antigen. Complete agreement was found between the group C antigen-binding assay and the group C hemagglutination test in detecting antibody rises in adults who were asymptomatic nasopharyngeal carriers, clinical cases or vaccine recipients. Nineteen paired sera from group B meningitis patients all showed antibody rises in the B antigen-binding assay whereas only 14 showed rises by the B hemagglutination test. Only 3 of 11 group B nasopharyngeal carriers showed an antibody response in the radioactive antigen-binding test. In young children immunized with the group C polysaccharide vaccine, the sensitive group C antigen-binding assay demonstrated antibody rises in 93% of the children, most of whom showed borderline or negative response as measured by the hemagglutination test.