Miracle-dz/UniFAR-FTUs huggingface dataset:
The performance of different propensity score methods for estimating marginal hazard ratios

Propensity score methods are increasingly being used to reduce or minimize the effects of confounding when estimating the effects of treatments, exposures, or interventions when using observational or non‐randomized data. Under the assumption of no unmeasured confounders, previous research has shown that propensity score methods allow for unbiased estimation of linear treatment effects (e.g., differences in means or proportions). However, in biomedical research, time‐to‐event outcomes occur frequently. There is a paucity of research into the performance of different propensity score methods for estimating the effect of treatment on time‐to‐event outcomes. Furthermore, propensity score methods allow for the estimation of marginal or population‐average treatment effects. We conducted an extensive series of Monte Carlo simulations to examine the performance of propensity score matching (1:1 greedy nearest‐neighbor matching within propensity score calipers), stratification on the propensity score, inverse probability of treatment weighting (IPTW) using the propensity score, and covariate adjustment using the propensity score to estimate marginal hazard ratios. We found that both propensity score matching and IPTW using the propensity score allow for the estimation of marginal hazard ratios with minimal bias. Of these two approaches, IPTW using the propensity score resulted in estimates with lower mean squared error when estimating the effect of treatment in the treated. Stratification on the propensity score and covariate adjustment using the propensity score result in biased estimation of both marginal and conditional hazard ratios. Applied researchers are encouraged to use propensity score matching and IPTW using the propensity score when estimating the relative effect of treatment on time‐to‐event outcomes. Copyright © 2012 John Wiley & Sons, Ltd.
Histochemical detection of the enzyme deficiency in blood films in Wolman's disease

The clinical diagnosis of Wolman's disease (acid esterase deficiency) can be confirmed by a histochemical staining method using blood films. Acid esterase activity is found normally in lymphocytes, but in Wolman's disease only a very low level of activity can be detected. An intermediate level of activity was demonstrated in heterozygotes. The method may also be applicable in the prenatal detection of the disease.
Using Abstraction in Modular Verification of Synchronous Adaptive Systems

Self-adaptive embedded systems autonomously adapt to changing environment conditions to improve their functionality and to increase their dependability by downgrading functionality in case of fail- ures. However, adaptation behaviour of embedded systems significantly complicates system design and poses new challenges for guaranteeing system correctness, in particular vital in the automotive domain. Formal verification as applied in safety-critical applications must therefore be able to address not only temporal and functional properties, but also dynamic adaptation according to external and internal stimuli. In this paper, we introduce a formal semantic-based framework to model, specify and verify the functional and the adaptation behaviour of syn- chronous adaptive systems. The modelling separates functional and adap- tive behaviour to reduce the design complexity and to enable modular reasoning about both aspects independently as well as in combination. By an example, we show how to use this framework in order to verify properties of synchronous adaptive systems. Modular reasoning in com- bination with abstraction mechanisms makes automatic model checking efficiently applicable.
Distinct subclasses of medium spiny neurons differentially regulate striatal motor behaviors

The direct and indirect pathways of the basal ganglia have been proposed to oppositely regulate locomotion and differentially contribute to pathological behaviors. Analysis of the distinct contributions of each pathway to behavior has been a challenge, however, due to the difficulty of selectively investigating the neurons comprising the two pathways using conventional techniques. Here we present two mouse models in which the function of striatonigral or striatopallidal neurons is selectively disrupted due to cell type–specific deletion of the striatal signaling protein dopamine- and cAMP-regulated phosphoprotein Mr 32kDa (DARPP-32). Using these mice, we found that the loss of DARPP-32 in striatonigral neurons decreased basal and cocaine-induced locomotion and abolished dyskinetic behaviors in response to the Parkinson's disease drug L-DOPA. Conversely, the loss of DARPP-32 in striatopallidal neurons produced a robust increase in locomotor activity and a strongly reduced cataleptic response to the antipsychotic drug haloperidol. These findings provide insight into the selective contributions of the direct and indirect pathways to striatal motor behaviors.
Pressure loading and ethanol exposure differentially modulate rat hepatic stellate cell activation

Ethanol may cause an increase in sinusoidal pressure accompanied by portal hypertension. Hepatic stellate cells (HSCs) located in hepatic sinusoids may therefore be frequently exposed to dual stimulations of mechanical pressure and ethanol exposure in alcoholic liver injury. In this study, the effects of pressure loading and ethanol exposure on activation of rat cultured HSCs were investigated using an in vitro pressure‐inducing apparatus. HSCs were cultured in media containing ethanol (0–100 mM) under different pressures (1–40 mmHg). Morphological changes and migration index were determined. We also determined the expression levels of α‐smooth muscle actin (α‐SMA) and mitogen‐activated protein kinases (MAPKs) by Western blot analysis and the level of collagen IV and transforming growth factor β1 (TGF‐β1) by ELISA. Pressure loading alone induced up‐regulation of α‐SMA via the extracellular signal‐regulated kinases 1 and 2 (ERK1/2) and c‐jun N‐terminal kinase (JNK) signaling pathways, prolonged extension of marginal length, and increased production of collagen IV. In contrast, ethanol exposure alone increased only extension of marginal length and cell migration. Dual stimulations of pressure loading and ethanol exposure enhanced the production of TGF‐β1 and migration index. The TGF‐β1‐dependent p38 MAPK pathway may operate for production of extracellular matrix (ECM) or enhanced migration in the case of dual stimulations. In conclusion, static pressure loading is an important factor directly accelerating the activation of HSCs. Although increased sinusoidal pressure and ethanol exposure might differentially modulate HSC activation, both stimuli are involved in an additive manner in some situations. J. Cell. Physiol. 215: 472–480, 2008. © 2007 Wiley‐Liss, Inc.
Fast 160-Bits GF (P) Elliptic Curve Crypto Hardware of High-Radix Scalable Multipliers

In this paper, a fast hardware architecture for elliptic curve cryptography computation in Galois Field GF(p) is proposed. The architecture is implemented for 160-bits, as its data size to handle. The design adopts projective coordinates to eliminate most of the required GF(p) inversion calculations replacing them with several multiplication operations. The hardware is intended to be scalable, which allows the hardware to compute long precision numbers in a repetitive way. The design involves four parallel scalable multipliers to gain the best speed. This scalable design was implemented in different versions depending on the area and speed. All scalable implementations were compared with an available FPGA design. The proposed scalable hardware showed interesting results in both area and speed. It also showed some area-time flexibility to accommodate the variation needed by different crypto applications.
Probabilistic declarative information extraction

Unstructured text represents a large fraction of the world's data. It often contains snippets of structured information (e.g., people's names and zip codes). Information Extraction (IE) techniques identify such structured information in text. In recent years, database research has pursued IE on two fronts: declarative languages and systems for managing IE tasks, and probabilistic databases for querying the output of IE. In this paper, we make the first step to merge these two directions, without loss of statistical robustness, by implementing a state-of-the-art statistical IE model - Conditional Random Fields (CRF) - in the setting of a Probabilistic Database that treats statistical models as first-class data objects. We show that the Viterbi algorithm for CRF inference can be specified declaratively in recursive SQL. We also show the performance benefits relative to a standalone open-source Viterbi implementation. This work opens up the optimization opportunities for queries involving both inference and relational operators over IE models.
Revisiting Winner Take All (WTA) Hashing for Sparse Datasets

WTA (Winner Take All) hashing has been successfully applied in many large scale vision applications. This hashing scheme was tailored to take advantage of the comparative reasoning (or order based information), which showed significant accuracy improvements. In this paper, we identify a subtle issue with WTA, which grows with the sparsity of the datasets. This issue limits the discriminative power of WTA. We then propose a solution for this problem based on the idea of Densification which provably fixes the issue. Our experiments show that Densified WTA Hashing outperforms Vanilla WTA both in image classification and retrieval tasks consistently and significantly.
Study on Characteristics of Chemokine CXCL10 Gene Cloned from cDNA Expression Library of Ujumqin Sheep

Chemokines were a major regulator of body's inflammatory and immune responses. In this study, the cDNA fragment of chemokine CXC ligand 10 (CXCL10) was cloned from the Ujumqin sheep ear marginal tissue cDNA expression library; the CXCL10 gene had 103 amino acids and a molecular weight of 11.47 kDa, and it shared a high homology among cattle, sheep, and goat, while a low homology compared with mouse. The CXCL10 protein had 4 conservative cysteine residues, located in 28, 30, 55, and 72 sites. The expression pattern and intracellular distribution of recombinant CXCL10 proteins in Ujumqin sheep fibroblast cells showed that there were green fluorescence signals both in cytoplasm and nucleolus after 24 h of transfection, the number of positive cells was increased with time, the peak level of fluorescence signal was reached after 48 h of transfection and the transfection efficiency was 33.3%; there was a significant decrease in fluorescence intensity after 72 h of transfection. Expression of recombinant CXCL10 gene in Escherichia coli had a time- and temperature-dependency on the amount of protein expression, and a small quantity of inducer was needed.
A Goal Oriented Numerical Simulation Approach for Computing Stress Intensity Factors in Bimaterials

We present a method for computing the stress intensity factors in bimaterials based on the goal oriented finite element error estimate. The goal oriented analysis focuses on computing the bounds on the local quantities of interest, e.g. local stresses, local displacements, stress intensity factors etc, of a structure, and with the bounds obtained on the coarse finite element mesh we can obtain the quantities of interest with nearly the same accuracy as that obtained on the fine finite element mesh. In this paper the stress intensity factors in bimaterials are first formulated as explicit computable linear function of the displacements by means of the two-points extrapolation method. Then the goal oriented finite element method is used to compute the lower and upper bounds on the stress intensity factors, and the average of the bounds is considered as a prediction of the stress intensity factor. At last, the stress intensity factors, 0 K and r K , in bimaterials are computed with the proposed method to show its efficiency.
Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts

Today’s biomedical research has become heavily dependent on access to the biological knowledge encoded in expert curated biological databases. As the volume of biological literature grows rapidly, it becomes increasingly difficult for biocurators to keep up with the literature because manual curation is an expensive and time-consuming endeavour. Past research has suggested that computer-assisted curation can improve efficiency, but few text-mining systems have been formally evaluated in this regard. Through participation in the interactive text-mining track of the BioCreative 2012 workshop, we developed PubTator, a PubMed-like system that assists with two specific human curation tasks: document triage and bioconcept annotation. On the basis of evaluation results from two external user groups, we find that the accuracy of PubTator-assisted curation is comparable with that of manual curation and that PubTator can significantly increase human curatorial speed. These encouraging findings warrant further investigation with a larger number of publications to be annotated. Database URL: http://www.ncbi. nlm.nih. gov/CBBresearch/Lu/Demo/PubTator/
Small Angle X-ray and Neutron Scattering: Powerful Tools for Studying the Structure of Drug-Loaded Liposomes

Nanovectors, such as liposomes, micelles and lipid nanoparticles, are recognized as efficient platforms for delivering therapeutic agents, especially those with low solubility in water. Besides being safe and non-toxic, drug carriers with improved performance should meet the requirements of (i) appropriate size and shape and (ii) cargo upload/release with unmodified properties. Structural issues are of primary importance to control the mechanism of action of loaded vectors. Overall properties, such as mean diameter and surface charge, can be obtained using bench instruments (Dynamic Light Scattering and Zeta potential). However, techniques with higher space and time resolution are needed for in-depth structural characterization. Small-angle X-ray (SAXS) and neutron (SANS) scattering techniques provide information at the nanoscale and have therefore been largely used to investigate nanovectors loaded with drugs or other biologically relevant molecules. Here we revise recent applications of these complementary scattering techniques in the field of drug delivery in pharmaceutics and medicine with a focus to liposomal carriers. In particular, we highlight those aspects that can be more commonly accessed by the interested users.
Detecting Interaction Coupling from Task Interaction Histories

A repository of task structures can reveal important latent knowledge about the development of a software system. Although approaches have been proposed to recover artifacts within a task structure, identifying relations that are relevant to a task remains a problem. In this work, we propose to detect "interaction coupling" from task interaction histories (i.e., records of when the artifacts were being used or modified in a task, as observed by the IDE), and use this information to mine patterns to aid in the comprehension of maintenance activities. In our case study, we found we were able to recover latent information about the development process; for example, our results suggest that restructuring is more costly than any other maintenance activity.
Endostar, a Modified Recombinant Human Endostatin, Suppresses Angiogenesis through Inhibition of Wnt/β-Catenin Signaling Pathway

Endostar, a novel modified recombinant human endostatin, is now widely studied for the treatment of diseases that are characterized or caused by pathological angiogenesis. However, its molecular mechanism remains unclear. In this study, we investigated the effects of Endostar on the Wnt/β-catenin signaling pathway, which has emerged as an important aspect of angiogenesis. We showed that Endostar significantly inhibited the proliferation, migration, invasion, and capillary-like tube formation of human umbilical vascular endothelial cells in a dose-dependent manner. Using a luciferase reporter assay, we also demonstrated that Endostar suppressed β-catenin-dependent T cell factor transcriptional activity in increasing doses. Moreover, we found that Endostar treatment also restricted the stabilized mutant β-catenin-mediated increase in transcriptional activity, suggesting that Endostar exerts its inhibitory influence on Wnt/β-catenin signaling by targeting β-catenin or its downstream molecules. Western blot and immunofluorescence results revealed that Endostar significantly decreased nuclear and total β-catenin levels. Finally, we discovered that Endostar down-regulated cyclin D1 and VEGF, two proteins that are known as the downstream targets of Wnt/β-catenin signaling and that also play important roles in angiogenesis. Our findings suggested that Endostar inhibits angiogenesis and that the downregulation of the Wnt/β-catenin signaling pathway may be involved in the inhibition of angiogenesis by Endostar. These results support the use of Endostar in further clinical applications.
Robust far-field spoken command recognition for home automation combining adaptation and multichannel processing

The paper presents our approach to speech-controlled home automation. We are focusing on the detection and recognition of spoken commands preceded by a key-phrase as recorded in a voice-enabled apartment by a set of multiple microphones installed in the rooms. For both problems we investigate robust modeling, environmental adaptation and multichannel processing to cope with a) insufficient training data and b) the far-field effects and noise in the apartment. The proposed integrated scheme is evaluated in a challenging and highly realistic corpus of simulated audio recordings and achieves F-measure close to 0.70 for key-phrase spotting and word accuracy close to 98% for the command recognition task.
Gaiku : Generating Haiku with Word Associations Norms

Word associations are an important element of linguistic creativity. Traditional lexical knowledge bases such as WordNet formalize a limited set of systematic relations among words, such as synonymy, polysemy and hypernymy. Such relations maintain their systematicity when composed into lexical chains. We claim that such relations cannot explain the type of lexical associations common in poetic text. We explore in this paper the usage of Word Association Norms (WANs) as an alternative lexical knowledge source to analyze linguistic computational creativity. We specifically investigate the Haiku poetic genre, which is characterized by heavy reliance on lexical associations. We first compare the density of WAN-based word associations in a corpus of English Haiku poems to that of WordNet-based associations as well as in other non-poetic genres. These experiments confirm our hypothesis that the non-systematic lexical associations captured in WANs play an important role in poetic text. We then present Gaiku, a system to automatically generate Haikus from a seed word and using WAN-associations. Human evaluation indicate that generated Haikus are of lesser quality than human Haikus, but a high proportion of generated Haikus can confuse human readers, and a few of them trigger intriguing reactions.
T‐Cell Antigen Receptor‐Induced Signaling Complexes: Internalization Via a Cholesterol‐Dependent Endocytic Pathway

T‐cell antigen receptor engagement causes the rapid assembly of signaling complexes. The adapter protein SLP‐76, detected as SLP‐yellow fluorescent protein, initially clustered with the TCR and other proteins, then translocated medially on microtubules. As shown by total internal reflection fluorescence microscopy and the inhibition of SLP‐76 movement at 16°C, this movement required endocytosis. Immunoelectron microscopy showed SLP‐76 staining of smooth pits and tubules. Cholesterol depletion decreased the movement of SLP‐76 clusters, as did coexpression of the ubiquitin‐interacting motif domain from eps15. These data are consistent with the internalization of SLP‐76 via a lipid raft‐dependent pathway that requires interaction of the endocytic machinery with ubiquitinylated proteins. The endocytosed SLP‐76 clusters contained phosphorylated SLP‐76 and phosphorylated LAT. The raft‐associated, transmembrane protein LAT likely targets SLP‐76 to endocytic vesicles. The endocytosis of active SLP‐76 and LAT complexes suggests a possible mechanism for downregulation of signaling complexes induced by TCR activation.
Mind the duality gap: safer rules for the Lasso

Screening rules allow to early discard irrelevant variables from the optimization in Lasso problems, or its derivatives, making solvers faster. In this paper, we propose new versions of the so-called $\textit{safe rules}$ for the Lasso. Based on duality gap considerations, our new rules create safe test regions whose diameters converge to zero, provided that one relies on a converging solver. This property helps screening out more variables, for a wider range of regularization parameter values. In addition to faster convergence, we prove that we correctly identify the active sets (supports) of the solutions in finite time. While our proposed strategy can cope with any solver, its performance is demonstrated using a coordinate descent algorithm particularly adapted to machine learning use cases. Significant computing time reductions are obtained with respect to previous safe rules.
Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball

We develop a machine learning approach to represent and analyze the underlying spatial structure that governs shot selection among professional basketball players in the NBA. Typically, NBA players are discussed and compared in an heuristic, imprecise manner that relies on unmeasured intuitions about player behavior. This makes it difficult to draw comparisons between players and make accurate player specific predictions. Modeling shot attempt data as a point process, we create a low dimensional representation of offensive player types in the NBA. Using non-negative matrix factorization (NMF), an unsupervised dimensionality reduction technique, we show that a low-rank spatial decomposition summarizes the shooting habits of NBA players. The spatial representations discovered by the algorithm correspond to intuitive descriptions of NBA player types, and can be used to model other spatial effects, such as shooting accuracy.
Learning From Disagreements : Discriminative Performance Evaluation

Selecting test cases in order to evaluate computer vision methods is important, albeit has not been addressed before. If the methods are evaluated on examples on which they perform very well or very poorly then no reliable conclusions can be made regarding the superiority of one method versus the others. In this paper we put forth the idea that algorithms should be evaluated on test cases they disagree most. We present a simple method which identifies the test cases that should be taken into account when comparing two algorithms and at the same time assesses the statistical significance of the differences in performance. We employ our methodology to compare two object detection algorithms and demonstrate its usefulness in enhancing the differences between the methods.