Miracle-dz/UniFAR-FTUs huggingface dataset:
Chondrotoxicity and Toxicokinetics of Sparfloxacin in Juvenile Rats

ABSTRACT Sparfloxacin is a fluoroquinolone with improved antibacterial activity against gram-positive pathogens. Like other quinolones, use of this drug is contraindicated in children and adolescents because of its potential chondrotoxicity in juveniles. We performed histological and immunohistochemical studies on the knee joint cartilage in 5-week-old rats after treatment with 600 or 1,800 mg of sparfloxacin/kg of body weight. Treatment with single or multiple oral doses of 600 mg of sparfloxacin/kg was not sufficient to induce joint cartilage lesions. However, five of eight rats treated with a single oral dose of 1,800 mg of sparfloxacin/kg of body weight showed typical cartilage lesions in the femoral part of the knee joint. The concentrations of the drug in plasma measured 0.25, 0.75, 1.5, 3, 6, 12, and 24 h after the administration of an oral dose of 600 mg of sparfloxacin/kg were 6.3 ± 1.8, 9.2 ± 1.7, 9.6 ± 2.7, 13.0 ± 1.8, 12.3 ± 1.6, 3.4 ± 0.4, and 0.30 ± 0.20 mg/liter, respectively (mean ± standard deviation [SD];n = 5 to 6 per group). The concentrations in plasma measured 0.75, 1.5, 3, 6, 24, and 48 h after the administration of an oral dose of 1,800 mg of sparfloxacin/kg were 10.9 ± 1.5, 15.9 ± 1.6, 19.1 ± 1.7, 14.9 ± 3.1, 4.1 ± 0.6, and 0.46 ± 0.37 mg/liter, respectively (mean ± SD;n = 3 to 4 per group). The concentrations of sparfloxacin in joint cartilage were significantly higher at all time points studied (114.8 ± 80, 99.4 ± 31.5, 84.9 ± 16.8, 44.4 ± 13.9, and 14.2 ± 4.8 mg of sparfloxacin/kg at 1.5, 3, 6, 24, and 48 h after the administration of 1,800 mg/kg, respectively). The range of concentrations in bone were similar to the range of concentrations in cartilage (peak, 115 ± 12 mg/kg after 3 h). Our data indicate that chondrotoxic doses of sparfloxacin in juvenile rats are approximately 300 times higher than the doses of sparfloxacin used therapeutically (1,800 versus approximately 6 mg/kg of body weight), but due to species differences in kinetics, concentrations in plasma differ by a factor of only approximately 15. More data on quinolone concentrations in cartilage from animals and humans could provide a better basis for a reasonable risk assessment.
Prosthetic replacement of chest-wall defects; an experimental and clinical study.

The increasingly frequent occurrence of a chest-wall defect secondary to trauma or to surgery for various tumors of this area of the body has focused attention on the problem of repairing the resultant chest-wall defect. Since the thoracic cage is solid yet in constant motion, any acceptable method of repair should offer the properties of mobility as well as stability. We and others * have utilized locally available tissue, such as the latissimus dorsi or pectoralis major muscle or the opposite breast, as a means to repair a thoracicwall defect. In certain instances this practice has been satisfactory, and, whenever possible, locally available tissue should be utilized if it can offer the desired stability. Unfortunately, such local tissue often is not practical, either because of its instability or because the neurovascular supply of the tissue is removed incident to its mobilization. Occasionally, conditions prevailing at surgery make it undesirable to prolong
oPOSSUM: integrated tools for analysis of regulatory motif over-representation

The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg. ca/oPOSSUM/
Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools

Binding of short antigenic peptides to major histocompatibility complex (MHC) molecules is a core step in adaptive immune response. Precise identification of MHC-restricted peptides is of great significance for understanding the mechanism of immune response and promoting the discovery of immunogenic epitopes. However, due to the extremely high MHC polymorphism and huge cost of biochemical experiments, there is no experimentally measured binding data for most MHC molecules. To address the problem of predicting peptides binding to these MHC molecules, recently computational approaches, called pan-specific methods, have received keen interest. Pan-specific methods make use of experimentally obtained binding data of multiple alleles, by which binding peptides (binders) of not only these alleles but also those alleles with no known binders can be predicted. To investigate the possibility of further improvement in performance and usability of pan-specific methods, this article extensively reviews existing pan-specific methods and their web servers. We first present a general framework of pan-specific methods. Then, the strategies and performance as well as utilities of web servers are compared. Finally, we discuss the future direction to improve pan-specific methods for MHC-peptide binding prediction.
Curse-of-complexity attenuation in the curse-of-dimensionality-free method for HJB PDEs

Recently, a curse-of-dimensionality-free method was developed for solution of Hamilton-Jacobi-Bellman partial differential equations (HJB PDEs) for nonlinear control problems, using semiconvex duality and max-plus analysis. The curse-of-dimensionality-free method may be applied to HJB PDEs where the Hamiltonian is given as (or well-approximated by) a pointwise maximum of quadratic forms. Such HJB PDEs also arise in certain switched linear systems. The method constructs the correct solution of an HJB PDE from a max-plus linear combination of quadratics. The method completely avoids the curse-of-dimensionality, and is subject to cubic computational growth as a function of space dimension. However, it is subject to a curse-of-complexity. In particular, the number of quadratics in the approximation grows exponentially with the number of iterations. Efficacy of such a method depends on the pruning of quadratics to keep the complexity growth at a reasonable level. Here we apply a pruning algorithm based on semidefinite programming. Computational speeds are exceptional, with an example HJB PDE in six-dimensional Euclidean space solved to the indicated quality in approximately 30 minutes on a typical desktop machine.
Adaptive Configuration Selection for Power-Constrained Heterogeneous Systems

As power becomes an increasingly important design factor in high-end supercomputers, future systems will likely operate with power limitations significantly below their peak power specifications. These limitations will be enforced through a combination of software and hardware power policies, which will filter down from the system level to individual nodes. Hardware is already moving in this direction by providing power-capping interfaces to the user. The power/performance trade-off at the node level is critical in maximizing the performance of power-constrained cluster systems, but is also complex because of the many interacting architectural features and accelerators that comprise the hardware configuration of a node. The key to solving this challenge is an accurate power/performance model that will aid in selecting the right configuration from a large set of available configurations. In this paper, we present a novel approach to generate such a model offline using kernel clustering and multivariate linear regression. Our model requires only two iterations to select a configuration, which provides a significant advantage over exhaustive search-based strategies. We apply our model to predict power and performance for different applications using arbitrary configurations, and show that our model, when used with hardware frequency-limiting, selects configurations with significantly higher performance at a given power limit than those chosen by frequency-limiting alone. When applied to a set of 36 computational kernels from a range of applications, our model accurately predicts power and performance, it maintains 91% of optimal performance while meeting power constraints 88% of the time. When the model violates a power constraint, it exceeds the constraint by only 6% in the average case, while simultaneously achieving 54% more performance than an oracle.
Evidence for widespread dysregulation of circadian clock progression in human cancer

The ubiquitous daily rhythms in mammalian physiology are guided by progression of the circadian clock. In mice, systemic disruption of the clock can promote tumor growth. In vitro, multiple oncogenes can disrupt the clock. However, due to the difficulties of studying circadian rhythms in solid tissues in humans, whether the clock is disrupted within human tumors has remained unknown. We sought to determine the state of the circadian clock in human cancer using publicly available transcriptome data. We developed a method, called the clock correlation distance (CCD), to infer circadian clock progression in a group of samples based on the co-expression of 12 clock genes. Our method can be applied to modestly sized datasets in which samples are not labeled with time of day and coverage of the circadian cycle is incomplete. We used the method to define a signature of clock gene co-expression in healthy mouse organs, then validated the signature in healthy human tissues. By then comparing human tumor and non-tumor samples from twenty datasets of a range of cancer types, we discovered that clock gene co-expression in tumors is consistently perturbed. Subsequent analysis of data from clock gene knockouts in mice suggested that perturbed clock gene co-expression in human cancer is not caused solely by the inactivation of clock genes. Furthermore, focusing on lung cancer, we found that human lung tumors showed systematic changes in expression in a large set of genes previously inferred to be rhythmic in healthy lung. Our findings suggest that clock progression is dysregulated in many solid human cancers and that this dysregulation could have broad effects on circadian physiology within tumors. In addition, our approach opens the door to using publicly available data to infer circadian clock progression in a multitude of human phenotypes.
CONVERGENCE AND COEVOLUTION IN A MUTUALISM: EVIDENCE FROM A MOLECULAR PHYLOGENY OF FICUS

Abstract The interaction between Ficus (Moraceae) and their pollinating wasps (Chalcidoidea: Agaonidae; more than 700 species-specific couples) is one of the most specialized mutualisms found in nature. Both partners of this interaction show extensive variation in their respective biology. Here we investigate Ficus life-history trait evolution and fig/fig wasp coadaptation in the context of a well-resolved molecular phylogeny. Mapping out variations in Ficus life-history traits on an independently derived phylogeny constructed from ribosomal DNA sequences (external and internal transcribed spacer) reveals several parallel transitions in Ficus growth habit and breeding system. Convergent trait evolution might explain the discrepancies between morphological analyses and our molecular reconstruction of the genus. Morphological characters probably correlate with growth habit and breeding system and could therefore be subject to convergent evolution. Furthermore, we reconstruct the evolution of Ficus inflorescence characters that are considered adaptations to the pollinators. Our phylogeny reveals convergences in ostiole shape, stigma morphology, and stamen:ovule ratio. Statistical tests taking into account the phylogenetic relationship of the species show that transitions in ostiole shape are correlated with variation in wasp pollinator head shape, and evolutionary changes in stigma morphology and stamen:ovule ratio correlate with changes in the pollination behavior of the associated wasp. These correlations provide evidence for reciprocal adaptations of morphological characters between these mutualistic partners that have interacted over a long evolutionary time. In light of previous ecological studies on mutualism, we discuss the adaptive significance of these correlations and what they can tell us about the coevolutionary process occurring between figs and their pollinators.
Stimulation of the Human Motor Cortex Alters Generalization Patterns of Motor Learning

It has been hypothesized that the generalization patterns that accompany learning carry the signatures of the neural systems that are engaged in that learning. Reach adaptation in force fields has generalization patterns that suggest primary engagement of a neural system that encodes movements in the intrinsic coordinates of joints and muscles, and lesser engagement of a neural system that encodes movements in the extrinsic coordinates of the task. Among the cortical motor areas, the intrinsic coordinate system is most prominently represented in the primary sensorimotor cortices. Here, we used transcranial direct current stimulation (tDCS) to alter mechanisms of synaptic plasticity and found that when it was applied to the motor cortex, it increased generalization in intrinsic coordinates but not extrinsic coordinates. However, when tDCS was applied to the posterior parietal cortex, it had no effects on learning or generalization in the force field task. The results suggest that during force field adaptation, the component of learning that produces generalization in intrinsic coordinates depends on the plasticity in the sensorimotor cortex.
A location-based routing algorithm for vehicle to vehicle communication

We present a location-based routing algorithm with cluster-based flooding for vehicle to vehicle communication. We consider a motorway environment with associated high mobility and contrast and compare position-based and non-position-based routing strategies, along with a limiting function for flood mechanisms in reactive ad-hoc protocols. The performance of dynamic source routing (DSR) and ad-hoc on-demand distance vector routing (AODV) for non-positional and location routing algorithm with cluster-based flooding (LORA/spl I.bar/CBF) for positional algorithms are considered. Our proposed flooding limiting technique is compared with AODV and DSR by simulation. The mobility of the vehicles on a motorway using a microscopic traffic model developed in OPNET has been used to evaluate average route discovery (RD) time, end-to-end delay (EED), routing load, routing overhead, overhead, and delivery ratio.
Second-Order Cone Programming-Based Optimal Control Strategy for Wind Energy Conversion Systems Over Complete Operating Regions

An efficient control strategy of a wind energy conversion system (WECS) plays a crucial role in wind power utilization. In this paper, a novel multivariable control strategy for a variable-speed variable-pitch WECS is proposed. It is designed for the complete operating regions of a wind turbine, including both of the partial load region and the full load region, with the objectives of maximizing energy capture, smoothing power output, alleviating drive train transient loads, and reducing pitch actuator activities. In particular, this paper considers the wind speed disturbance as norm-bounded, instead of deterministic or chance constraints in the widely used quadratic control methods such as linear quadratic Gaussian control and model predictive control. Moreover, the WECS control with the norm-bounded disturbance is formulated as a second-order cone programming (SOCP) problem that has not been previously employed for wind power control. Finally, simulation results are provided to demonstrate the validity of the proposed method.
Regulatory T Cells Control Autoimmunity In Vivo by Inducing Apoptotic Depletion of Activated Pathogenic Lymphocytes1

Clinical autoimmunity requires both activation of self-reactive T cells as well as a failure of peripheral tolerance mechanisms. We previously identified one such mechanism that involves regulatory T cells recognizing TCR Vβ8. 2 chain-derived peptides in the context of MHC. How this regulation affects the fate of target Vβ8. 2+ T lymphocytes in vivo that mediate experimental autoimmune encephalomyelitis has remained unknown. The present study using immunoscope and CFSE-labeling analysis demonstrates that the expansion of regulatory CD4 and CD8 T cells in vivo results in apoptotic depletion of the dominant, myelin basic protein-reactive Vβ8. 2+ T cells, but not subdominant Vβ13+ T cells. The elimination of only activated T cells by this negative feedback mechanism preserves the remainder of the naive Vβ8. 2+ T cell repertoire and at the same time results in protection from disease. These studies are the first in clearly elucidating the fate of myelin basic protein-specific encephalitogenic T cells in vivo following regulation.
A crucial role of the alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid subtype of glutamate receptors in piriform and perirhinal cortex for the initiation and propagation of limbic motor seizures.

The role of alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors in the initiation and propagation of limbic motor seizures in rats was examined by the intracerebral and systemic administration of 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo (f) quinoxaline (NBQX), a selective antagonist of the AMPA subtype of glutamate receptor. Limbic motor seizures were evoked focally by the application of the gamma-aminobutyric acid receptor antagonist, bicuculline, into area tempestas, an epileptogenic site in the deep anterior piriform cortex. Before eliciting seizures, NBQX was applied focally into either 1) area tempestas or 2) perirhinal or posterior piriform cortex ipsilateral to the area tempestas from which seizures were evoked. In addition, pretreatment with i.p. NBQX was evaluated for anticonvulsant actions against area tempestas-evoked clonic or systemically evoked tonic seizures. In all conditions, a dose-dependent decrease in the severity of seizures was obtained with NBQX. With focal intracerebral administration, a dose of 500 pmol of NBQX consistently protected against limbic motor seizures, with partial protection achieved with 100 pmol. After i.p. administration, 2.5 and 5.0 mg/kg significantly protected the rats from both limbic motor seizures and tonic extensor seizures. No overt disturbance of spontaneous behavior was associated with the anticonvulsant doses of NBQX. Moreover, both forebrain substrates of limbic motor seizures and hindbrain substrates of tonic extensor seizures were highly susceptible to disruption by NBQX. The results indicate that AMPA subtype of glutamate receptors are crucial mediators of seizure propagation via perirhinal and piriform cortics.
Deriving cramér-rao bounds and maximum likelihood estimators for traffic matrix inference

Traffic matrix estimation has caught numerous attentions these days due to its importance on network management tasks such as traffic engineering and capacity planning for Internet Service Providers (ISP). Various estimation models and methods have been proposed to estimate the traffic matrix. However, it is difficult to compare these methods since they adopt different model assumptions. Currently most evaluations are based on some particular realization of data. We propose to use the (Bayesian) Cramér-Rao Bound (CRB) as a benchmark on these estimators. We also derive the maximum likelihood estimator (MLE) for certain models. With coupled mean and variance, our simulations show that the least squares (LS) estimator reaches the CRB asymptotically, while the MLEs are difficult to calculate when the dimension is high.
ElasticTree: Saving Energy in Data Center Networks

Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
Dynamic output feedback H∞ control of discrete-time Markov jump linear systems through Linear Matrix Inequalities

This paper addresses the H∞ dynamic output feedback control design problem of discrete-time Markov jump linear systems. Under the mode-dependent assumption, which means that the Markov parameters are available for feedback, the main contribution is on the complete characterization of all full order proper controllers such that the H∞ norm of the closed loop system remains bounded by a given pre-specified level, yielding the global solution to the corresponding mode-dependent optimal control design problem, expressed in terms of pure linear matrix inequalities. LMIs. A practical application, consisting the networked control of a vehicle platoon using measurement signals transmitted in a Markov channel, as initially proposed in Seiler, P and Sengupta, R. , (2005), is considered.
Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts.