Miracle-dz/UniFAR-FTUs huggingface dataset:
Grafting mouse brains: from neurocarcinogenesis to neurodegeneration

When I received a telephone call in early July 1998 breaking the news that I was to be awarded the EMBO gold medal, I could not help but remember the awe with which I had been looking upon my then‐supervisor Erwin Wagner a decade ago, when he was awarded the very same prize. Since I was asked to write an autobiographical review of my scientific activities, I dug out the medal review by Erwin Wagner (1990) in an attempt to gather some inspiration. The latter document is remarkable in its scientific clarity, but also in its candor, typical of Erwin's personality. Along lines similar to those of Erwin Wagner's review article, I will try to trace my scientific motives and achievements, and also describe the impact of the scientists who taught me how to research the molecular bases of diseases. In 1979, the Italian undergraduate curriculum in the medical sciences was utterly uninviting. Therefore, although my home town of Pavia sports a distinguished university, after no more than one semester I gave up my enrollment at the medical faculty and decided to continue my studies in Germany. Three years into medical school in Freiburg im Breisgau, I felt the urge to learn the methods of basic science. Thanks to the mediation of an old friend, Gianpaolo Merlini (then a postdoc in New York), I was given the opportunity to undertake an elective in Soldano Ferrone's laboratory at Columbia University, where Patrizio Giacomini taught me how to make monoclonal antibodies, and introduced me to the then‐omnipresent methods of immunochemistry: sandwich assays, radioimmunoprecipitation, immunofluorescence and so on. In 1983, as nave as this may seem with hindsight, immunotherapy of cancer seemed to lie just around the corner. A wealth of tumor antigens was being discovered, and the booming technology of monoclonal antibodies …
Comparison of 3 Estimation Methods of Mycophenolic Acid AUC based on a Limited Sampling Strategy in Renal Transplant Patients

A significant relationship between mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) and the risk for rejection has been reported. Based on 3 concentration measurements, 3 approaches have been proposed for the estimation of MPA AUC, involving either a multilinear regression approach model (MLRA) or a Bayesian estimation using either gamma absorption or zero-order absorption population models. The aim of the study was to compare the 3 approaches for the estimation of MPA AUC in 150 renal transplant patients treated with mycophenolate mofetil and tacrolimus. The population parameters were determined in 77 patients (learning study). The AUC estimation methods were compared in the learning population and in 73 patients from another center (validation study). In the latter study, the reference AUCs were estimated by the trapezoidal rule on 8 measurements. MPA concentrations were measured by liquid chromatography. The gamma absorption model gave the best fit. In the learning study, the AUCs estimated by both Bayesian methods were very similar, whereas the multilinear approach was highly correlated but yielded estimates about 20% lower than Bayesian methods. This resulted in dosing recommendations differing by 250 mg/12 h or more in 27% of cases. In the validation study, AUC estimates based on the Bayesian method with gamma absorption model and multilinear regression approach model were, respectively, 12% higher and 7% lower than the reference values. To conclude, the bicompartmental model with gamma absorption rate gave the best fit. The 3 AUC estimation methods are highly correlated but not concordant. For a given patient, the same estimation method should always be used.
EEG Spikes Detection, Sorting, and Localization

This study introduces a new method for detecting, sorting, and localizing spikes from multiunit EEG recordings. The method combines the wavelet transform, which localizes distinctive spike features, with Super-Paramagnetic Clustering (SPC) algorithm, which allows automatic classification of the data without assumptions such as low variance or Gaussian distributions. Moreover, the method is capable of setting amplitude thresholds for spike detection. The method makes use of several real EEG data sets, and accordingly the spikes are detected, clustered and their times were detected. Keywords—EEG time localizations, EEG spike detection, superparamagnetic algorithm, wavelet transform.
Cost minimization in utility computing systems

Utility computing is a form of computer service whereby the company providing the service charges the users for using the system resources. In this paper, we present system‐optimal and user‐optimal price‐based job allocation schemes for utility computing systems whose objective is to minimize the cost for the users. The system‐optimal scheme provides an allocation of jobs to the computing resources that minimizes the overall cost for executing all the jobs in the system. The user‐optimal scheme provides an allocation that minimizes the cost for individual users in the system for providing fairness. The system‐optimal scheme is formulated as a constraint minimization problem, and the user‐optimal scheme is formulated as a non‐cooperative game. The prices charged by the computing resource owners for executing the users jobs are obtained using a pricing model based on a non‐cooperative bargaining game theory framework. The performance of the studied job allocation schemes is evaluated using simulations with various system loads and configurations. Copyright © 2012 John Wiley & Sons, Ltd.
Ten Nights of Moderate Hypoxia Improves Insulin Sensitivity in Obese Humans

Hypoxia in obese adipose tissue (AT) plays an important role in the development of whole-body insulin resistance by inducing local inflammation and the release of proinflammatory cytokines (1). Yet, living at high altitude is associated with a lower prevalence of impaired fasting glucose and type 2 diabetes compared with living at low altitude (2). Furthermore, exposure to hypoxic environments increases whole-body glucose fluxes in healthy males and glucose uptake in human and murine skeletal muscle (3). In addition, exercising under hypoxic conditions improves glucose tolerance more than exercising under normoxia (4), strongly suggesting an insulin-sensitizing effect of hypoxia. Therefore, we hypothesized that exposing obese men to 10 consecutive nights of moderate hypoxia (15 ± 0.5% O2, ∼2,400 m elevation) would improve insulin sensitivity. Eight healthy obese men (4 Caucasians, 3 African Americans, and 1 Hispanic of mean ± SEM age 28 ± 1 years, weight 96.5 ± 5.3 kg, and BMI 32.7 ± 1.3 kg/m2) without evidence of chronic disease or sleep apnea and taking no medication participated in this study. The protocol was approved by the institutional review board at Pennington Biomedical Research Center (Baton Rouge, LA). Subjects slept for 10 consecutive nights (∼10 h/night, ≥100 h in total) in a hypoxic tent (Hypoxico Inc., New York, NY) maintained at ∼15% O2 (range 14.5–15.5% O2, ∼2,400 m above sea level) using nitrogen dilution. Biopsies of abdominal subcutaneous AT and skeletal muscle were obtained at baseline and on day 11 under …
Predictors of visual-motor integration in children with intellectual disability

The aim of this study was to assess the influence of sex, age, level and etiology of intellectual disability on visual-motor integration in children with intellectual disability. The sample consisted of 90 children with intellectual disability between 7 and15 years of age. Visual-motor integration was measured using the Acadia test of visual-motor integration. A multiple regression analysis was used for data analysis. The results of this study showed that sex, level of intellectual disability, and age were significant predictors of visual-motor integration. The etiology of intellectual disability did not play a significant role in predicting visual-motor integration. Visual-motor integration skills are very important for a child’s overall level of functioning. Individualized programs for the remediation of visual-motor integration skills should be a part of the curriculum for children with intellectual disability.
Formal Modeling and Analysis of Biological Regulatory Networks Using SPIN

In the last two decades, formal verification has emerged as an important technique for the formal modeling and analysis of real time reactive and unpredictable systems. The main advantage of model checking over simulation based analysis is its inherent soundness and reliability of computed results. In this paper, we propose to use explicit state model checker (SPIN) for formal modeling and Linear Temporal Logic(LTL) for the exploration of the complex dynamics (cycles) of biological regulatory networks (BRNs). The main contribution of this paper also includes the generalized framework for modeling BRNs based on well known Kinetic Logic of Ren´e Thomas and state-of-the-art SPIN model checker. To demonstrate the usefulness of current work, we utilized it for the analysis of mucus production system in Pseudomonas aeruginosa and BRN involving Indoleamine 2, 3-dioxygenase (IDO).
An ad hoc approach to the implementation of polymorphism

Polymorphic abstraction provides the ability to write programs that are independent of the form of the data over which they operate. It has proved difficult to provide efficient implementations of polymorphism. This paper addresses this problem and describes a new technique which can implement all forms of polymorphism, use a conventional machine architecture and support non-uniform data representations. Furthermore, the method ensures that any extra cost of implementation applies to polymorphic forms only and allows such polymorphic forms to persist over program invocations.
Earley-based stochastic context-free grammar estimation from bracketed corpora and its use in a hybrid language model

In this paper, we study the problem of estimating Stochastic Context-Free Grammars (SCFGs) in general format and their use in a hybrid langu ge model. In this work, we propose the estimation of a SCFG by means of a new bracketed v rsion of the Earley algorithm. A hybrid language model is defined as a combinatio of a word-based n-gram, which is used to capture the local relations between words, a nd a category-based SCFG with a word distribution in categories, which is defined to re present the long-term relations between these categories. Experiments on the UPenn Treeban k corpus are reported. These experiments have been carried out in terms of the test set per plexity and the word error rate in a speech recognition experiment.
Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community.
Efficiently reaching consensus on the largest entries of a vector

We consider a problem where agents gossip on a d-dimensional state vector. The goal is to achieve a consensus on the average. However, instead of computing the average of the entire d-dimensional state, the goal is to have all agents reach a consensus on the largest k entries of the average initial state vector. For example, the value in each entry could correspond to the agents' opinions about a different item, in which case the goal is to determine which are the k most popular items, on average. A primary challenge is that the indices of the k largest entries are not known a priori, and so the agents must adaptively identify which entries are the largest while also computing their values. We consider an asynchronous gossip-style algorithm where pairs of agents interact, communicate, and update only those state entries which either agent currently believes to be one of the largest k. We show that, as long as the underlying communication graph is connected, the algorithm converges to a state where all agents reach a consensus on the indices and values of the largest k entries of the initial average. We study, via numerical simulation, the convergence rate of the algorithm in terms of the total number of scalar values transmitted to reach a desired level of accuracy.
Emergent Literacy Supports for Students who are Deaf-Blind or Have Visual and Multiple Impairments: A Multiple-case Study

Seven classrooms of students with deaf-blindness or visual and multiple impairments were observed to document the emergent literacy supports that were present, including environmental characteristics, strategies, or activities. The findings revealed that the majority of classrooms used emergent literacy supports that were previously documented for students without disabilities. Implications for practice and suggestions for future research are discussed.
CDC28 phosphorylates Cac1p and regulates the association of chromatin assembly factor i with chromatin

Chromatin Assembly Factor I (CAF-I) plays a key role in the replication-coupled assembly of nucleosomes. It is expected that its function is linked to the regulation of the cell cycle, but little detail is available. Current models suggest that CAF-I is recruited to replication forks and to chromatin via an interaction between its Cac1p subunit and the replication sliding clamp, PCNA, and that this interaction is stimulated by the kinase CDC7. Here we show that another kinase, CDC28, phosphorylates Cac1p on serines 94 and 515 in early S phase and regulates its association with chromatin, but not its association with PCNA. Mutations in the Cac1p-phosphorylation sites of CDC28 but not of CDC7 substantially reduce the in vivo phosphorylation of Cac1p. However, mutations in the putative CDC7 target sites on Cac1p reduce its stability. The association of CAF-I with chromatin is impaired in a cdc28–1 mutant and to a lesser extent in a cdc7–1 mutant. In addition, mutations in the Cac1p-phosphorylation sites by both CDC28 and CDC7 reduce gene silencing at the telomeres. We propose that this phosphorylation represents a regulatory step in the recruitment of CAF-I to chromatin in early S phase that is distinct from the association of CAF-I with PCNA. Hence, we implicate CDC28 in the regulation of chromatin reassembly during DNA replication. These findings provide novel mechanistic insights on the links between cell-cycle regulation, DNA replication and chromatin reassembly.
Goodness-of-fit statistics for age-specific reference intervals.

The age-specific reference interval is a commonly used screening tool in medicine. It involves estimation of extreme quantile curves (such as the 5th and 95th centiles) of a reference distribution of clinically normal individuals. It is crucial that models used to estimate such intervals fit the data extremely well. However, few procedures to assess goodness-of-fit have been proposed in the literature, and even fewer have been evaluated systematically. Here we consider procedures based on the distribution of the Z-scores (standardized residuals) from a model and on Pearson chi(2) statistics for observed and expected counts in groups defined by age and the estimated reference centile curves. Two of the procedures (Q and grid tests) are mainly inferential, whereas the third (permutation bands and B-tests) is essentially graphical. We obtain approximations to the null distributions of several relevant test statistics and examine their size and power for a range of models based on real data sets. We recommend Q-tests in all situations where Z-scores are available since they are general, simple to calculate and usually have the highest power among the three classes of test considered. For the cases considered the grid tests are always inferior to the Q- and B- tests.
Semi-autonomous telerobotic assembly over high-latency networks

We report the development and a preliminary multi-user evaluation of an assisted teleoperation architecture for assembly tasks over high-latency networks. While such tasks still require human insight, there are often elements of these tasks which can be executed autonomously. Our architecture contextualizes a user's intended actions in a remote scene. It assists the user by performing the intended action more precisely based on the latest local scene model. We report the results of a multi-user study of nine participants to evaluate performance of this approach using a full-3D dynamic robotic simulation in a laboratory environment. The study required users to assemble part of a structure with 200 or 4000 milliseconds of time delay, with or without assistance from the reported system. For each condition, we evaluated performance based both on partial and final task completion times, and we estimated each user's workload with the NASA Task Load Index. The study showed that our architecture has the potential to increase feasibility of the task both with and without large telemetry delay and to enable users to complete elements of the task more rapidly. We also found that the assistance dramatically reduced the users' workload. We provide open-source implementations for all components of our system, which can be adapted to other robotic platforms.
Sets of Models and Prices of Uncertainty

A decision maker constructs a convex set of nonnegative martingales to use as likelihood ratios that represent parametric alternatives to a baseline model and also non-parametric models statistically close to both the baseline model and the parametric alternatives. Max-min expected utility over that set gives rise to equilibrium prices of model uncertainty expressed as worst-case distortions to drifts in a representative investor's baseline model. We offer quantitative illustrations for baseline models of consumption dynamics that display long-run risk. We describe a set of parametric alternatives that generates countercyclical prices of uncertainty.
Days and Knights Discussing Membrane Dynamics in Endocytosis: Meeting Report from the Euresco/EMBL Membrane Dynamics in Endocytosis, 6–11 October in Tomar, Portugal

The Euresco/EMBL sponsored meeting on ‘Membrane Dynamics in Endocytosis’ took place on 6–11 October in Tomar, Portugal. Here we report on the 5 full days of exciting talks and active poster sessions that covered topics ranging from the mechanisms of clathrin‐mediated endocytosis, the regulation of phagocytosis, caveolae dynamics and function, the role of lipids in regulating endocytic transport, the formation of and sorting into and out of multivesicular bodies, new links between the actin cytoskeleton and vesicular transport, and emerging roles for endocytic trafficking in signal transduction and development.
WOMAN ABUSE IN DATING RELATIONSHIPS: A CRITICAL EVALUATION OF RESEARCH AND THEORY

Research on woman abuse in dating relationships1 shows that violence between heterosexual intimates extends beyond the narrow boundaries of the conjugal home.2 This literature may be grouped under four headings: conceptions, definitions, research methods and theories. The primary objective of this paper is twofold: (1) to critically evaluate and build upon these contributions and (2) to make explicit their policy implications.
Building-Blocks for Performance Oriented DSLs

Domain-specific languages raise the level of abstraction in software development. While it is evident that programmers can more easily reason about very high-level programs, the same holds for compilers only if the compiler has an accurate model of the application domain and the underlying target platform. Since mapping high-level, general-purpose languages to modern, heterogeneous hardware is becoming increasingly difficult, DSLs are an attractive way to capitalize on improved hardware performance, precisely by making the compiler reason on a higher level. Implementing efficient DSL compilers is a daunting task however, and support for building performance-oriented DSLs is urgently needed. To this end, we present the Delite Framework, an extensible toolkit that drastically simplifies building embedded DSLs and compiling DSL programs for execution on heterogeneous hardware. We discuss several building blocks in some detail and present experimental results for the OptiML machine-learning DSL implemented on top of Delite.
Two New Weak Constraint Qualifications and Applications

We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients of the active constraints preserve positive linear dependence locally. A major open question was to identify the exact set of gradients whose properties had to be preserved locally and that would still work as a CQ. This is done in the first new CQ, which we call the constant rank of the subspace component (CRSC) CQ. This new CQ also preserves many of the good properties of RCPLD, such as local stability and the validity of an error bound. We also introduce an even weaker CQ, called the constant positive generator (CPG), which can replace RCPLD in the analysis of the global convergence of algorithms. We close this work by extending convergence results of algorithms belonging to all the main classes of nonlinear optimization methods: sequential quadratic programming, augmented Lagrangians, .
Laboratory experiments on the interaction of streamers

Pictures show that streamer or sprite discharge cha nnels emerging from the same electrode or position sometimes seem to reconnect or merge even though their heads carry electric charge of the sam e polarity; one might therefore suspect that reconnec tions are an artifact of the two-dimensional projec tion in the pictures. We have used stereo-photography of labora tory scale streamer discharges to investigate the f ull three-dimensional structure of such events. We anal yze reconnection, possibly an electrostatic effect in which a late thin streamer reconnects to an earlier thick s treamer channel, and merging, a suggested photo-ionization effect in which two simultaneously propagating stre amer heads merge into one new streamer. We also investigate the branching lengths and angles in the 3D streamer tree structures.