Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeting miR-423-5p Reverses Exercise Training–Induced HCN4 Channel Remodeling and Sinus Bradycardia

Rationale: Downregulation of the pacemaking ion channel, HCN4 (hyperpolarization-activated cyclic nucleotide gated channel 4), and the corresponding ionic current, If, underlies exercise training–induced sinus bradycardia in rodents. If this occurs in humans, it could explain the increased incidence of bradyarrhythmias in veteran athletes, and it will be important to understand the underlying processes. Objective: To test the role of HCN4 in the training-induced bradycardia in human athletes and investigate the role of microRNAs (miRs) in the repression of HCN4. Methods and Results: As in rodents, the intrinsic heart rate was significantly lower in human athletes than in nonathletes, and in all subjects, the rate-lowering effect of the HCN selective blocker, ivabradine, was significantly correlated with the intrinsic heart rate, consistent with HCN repression in athletes. Next-generation sequencing and quantitative real-time reverse transcription polymerase chain reaction showed remodeling of miRs in the sinus node of swim-trained mice. Computational predictions highlighted a prominent role for miR-423-5p. Interaction between miR-423-5p and HCN4 was confirmed by a dose-dependent reduction in HCN4 3′-untranslated region luciferase reporter activity on cotransfection with precursor miR-423-5p (abolished by mutation of predicted recognition elements). Knockdown of miR-423-5p with anti-miR-423-5p reversed training-induced bradycardia via rescue of HCN4 and If. Further experiments showed that in the sinus node of swim-trained mice, upregulation of miR-423-5p (intronic miR) and its host gene, NSRP1, is driven by an upregulation of the transcription factor Nkx2.5. Conclusions: HCN remodeling likely occurs in human athletes, as well as in rodent models. miR-423-5p contributes to training-induced bradycardia by targeting HCN4. This work presents the first evidence of miR control of HCN4 and heart rate. miR-423-5p could be a therapeutic target for pathological sinus node dysfunction in veteran athletes.
Efficient Online Learning and Prediction of Users' Desktop Actions

We investigate prediction of users' desktop activities in the Unix domain. The learning techniques we explore do not require explicit user teaching. We show that simple efficient many-class learning can perform well for action prediction, significantly improving over previously published results and baselines. This finding is promising for various human-computer interaction scenarios where a rich set of potentially predictive features is available, where there can be many different actions to predict, and where there can be considerable nonstationarity.
Validation of the Executive Function Route-Finding Task (EFRT) in People with Mild Cognitive Impairment

Reliability and validity of the Executive Function Route-finding Task (EFRT) with people diagnosed as having mild cognitive impairment was examined. Twenty-three people with mild cognitive impairment with a mean age of 77.4 (± 7.5) years and 23 healthy controls with a mean age of 74.3 (± 4.9) years participated. The EFRT was administered along with other tests for executive functions: Executive Interview and two subtests from the Executive Functions Performance Test (EFPT). Findings showed high inter-rater reliability for the EFRT. In addition, the control group performed significantly better on all tests, thus confirming the construct validity of the EFRT. However, further examination into the clinical significance of these findings is needed. Concurrent validity was partially demonstrated by low to moderate significant correlation between the EFRT and one subtest from the EFPT. The results of this study support the reliability and validity of the EFRT among people with mild cognitive impairment.
Fast Ray Tracing of Arbitrary Implicit Surfaces with Interval and Affine Arithmetic

Existing techniques for rendering arbitrary‐form implicit surfaces are limited, either in performance, correctness or flexibility. Ray tracing algorithms employing interval arithmetic (IA) or affine arithmetic (AA) for root‐funding are robust and general in the class of surfaces they support, but traditionally slow. Nonetheless, implemented efficiently using a stack‐driven iterative algorithm and SIMD vector instructions, these methods can achieve interactive performance for common algebraic surfaces on the CPU. A similar algorithm can also be implemented stacklessly, allowing for efficient ray tracing on the GPU. This paper presents these algorithms, as well as an inclusion‐preserving reduced affine arithmetic (RAA) for faster ray‐surface intersection. Shader metaprogramming allows for immediate and automatic generation of symbolic expressions and their interval or affine extensions. Moreover, we are able to render even complex forms robustly, in real‐time at high resolution.
A Biomimetic Collagen Derived Peptide Exhibits Anti-Angiogenic Activity in Triple Negative Breast Cancer

We investigated the application of a mimetic 20 amino acid peptide derived from type IV collagen for treatment of breast cancer. We showed that the peptide induced a decrease of proliferation, adhesion, and migration of endothelial and tumor cells in vitro. We also observed an inhibition of triple negative MDA-MB-231 xenograft growth by 75% relative to control when administered intraperitoneally for 27 days at 10 mg/kg. We monitored in vivo the changes in vascular properties throughout the treatment using MRI and found that the vascular volume and permeability surface area product decreased significantly. The treatment also resulted in an increase of caspase-3 activity and in a reduction of microvascular density. The multiple mode of action of this peptide, i.e., anti-angiogenic, and anti-tumorigenic, makes it a viable candidate as a therapeutic agent as a monotherapy or in combination with other compounds.
Nonlinear Constraint Network Optimization for Efficient Map Learning

Learning models of the environment is one of the fundamental tasks of mobile robots since maps are needed for a wide range of robotic applications, such as navigation and transportation tasks, service robotic applications, and several others. In the past, numerous efficient approaches to map learning have been proposed. Most of them, however, assume that the robot lives on a plane. In this paper, we present a highly efficient maximum-likelihood approach that is able to solve 3-D and 2-D problems. Our approach addresses the so-called graph-based formulation of simultaneous localization and mapping (SLAM) and can be seen as an extension of Olson's algorithm toward non-flat environments. It applies a novel parameterization of the nodes of the graph that significantly improves the performance of the algorithm and can cope with arbitrary network topologies. The latter allows us to bound the complexity of the algorithm to the size of the mapped area and not to the length of the trajectory. Furthermore, our approach is able to appropriately distribute the roll, pitch, and yaw error over a sequence of poses in 3-D mapping problems. We implemented our technique and compared it with multiple other graph-based SLAM solutions. As we demonstrate in simulated and real-world experiments, our method converges faster than the other approaches and yields accurate maps of the environment.
A comparison of photometric normalisation algorithms for face verification

The variation of illumination conditions of an object can produce large changes in tthe image plane, significantl impairing the performance of face verification algorithms. We present a comparison of five photometric normalisation algorithms for use in pre-processing face images for the purpose of verification. The algorithms are tested on various configurations of three contrasting databases, namely the Yale B database, the XM2VTS database and the BANCA database.
Preventing control constraint violations by use of energy balances for a class of coupled systems: Applied to a power plant

In this paper a scheme is presented for preventing violations of control signal constraints in a class of coupled systems. The scheme is an add-on solution to the existing control system; it works like a fault tolerant scheme, by accommodating the problem then occurring. The proposed scheme recomputes the reference values to the system such that control signal constraint violations are avoided. The new reference values are found using an energy balance of the system. The scheme is intended to handle rarely occurring constraint violations, so the only concern is that the system should be stable and not to optimize performance during all conditions. The scheme is applied to an example with a coal mill pulverizing coal for a power plant.
Monte Carlo Simulations of Single-Molecule Fluorescence Detection Experiments

A microfluidic device has been developed wherein single molecules in solution are electrokinetically transported along a nanochannel. The nanochannel is irradiated by two adjacently focused laser beams so that the timing of fluorescence photons induced by each beam indicates the position of a molecule along the nanochannel. This is then used to actively control the electrokinetic flow, so that the molecule may be held within the confocal volume for a prolonged time and then rapidly replaced following photobleaching or completion of the single-molecule measurement. Here we focus on Monte Carlo computer simulations of the physical processes that occur during the delivery and trapping. The simulations help in understanding the constraints imposed by experimental limitations, such as the latency of feedback, the maximum achievable speed of electrokinetic flow, and photophysical processes such as triplet crossing and photobleaching. They also aid in evaluating the effects of shot noise and photon timing error and in predicting optimum experimental operating parameters. Studies indicate that the 6 μs latency of feedback in our experiments is well below that required for stable trapping (~100 μs); for small freely diffusing molecules, a limited flow speed of ~2 μm/ms can result in ~10–20 % of molecules escaping before they photobleach; there is an optimum laser power of ~30–40 μW that provides a sufficient rate of fluorescence photons for trapping while reducing loss due to photobleaching; an increase in the spacing between the beams or increase in relative power of the down-stream beam increases the trapping time.
PESTO: A Tool for Migrating DOM-Based to Visual Web Tests

Automated testing of web applications reduces the effort needed in manual testing. Old 1st generation tools, based on screen coordinates, produce quite fragile test suites, tightly coupled with the specific screen resolution, window position and size experienced during test case recording. These tools have been replaced by a 2nd generation of tools, which offer easy selection and interaction with the web elements, based on DOM-oriented commands. Recently, a new 3rd generation of tools came up based on visual image recognition, bringing the promise of wider applicability and simplicity. A tester might ask if the migration towards such new technology is worthwhile, since the manual effort to rewrite a test suite might be overwhelming. In this paper, we propose PESTO, a tool facing the problem of the automated migration of 2nd generation test suites to the 3rd generation. PESTO determines automatically the screen position of each web element located on the DOM by a 2nd generation test case. It then calculates a screenshot image centred around the web element so as to ensure unique visual matching. Then, the entire source code of the DOM-based test suite is transformed into a visual test suite, based on such automatically extracted images and using specific visual commands.
Identification of direct residue contacts in protein–protein interaction by message passing

Understanding the molecular determinants of specificity in protein–protein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein–protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.
Metallothionein 1E mRNA is highly expressed in oestrogen receptor-negative human invasive ductal breast cancer

Metallothioneins (MTs), a group of ubiquitous metalloproteins, comprise isoforms encoded by ten functional genes in humans. Different MT isoforms possibly play different functional roles during development or under various physiological conditions. The MT-1E isoform mRNA has been recently shown to be differentially expressed in oestrogen receptor (OR)-positive and OR-negative breast cancer cell lines. In this study, we evaluated MT-1E mRNA expression via semi-quantitative RT-PCR in 51 primary invasive ductal breast cancer tissues, concurrently with OR-positive and progesterone receptor (PR)-positive MCF7 cells, OR-negative and PR-negative MDA-MB-231 cells and PR-transfected MDA-MB-231 breast cancer cells (ABC28). We demonstrated significantly higher MT-1E mRNA expression in OR-negative compared with OR-positive breast cancer tissues (P= 0.026). MCF7 cells lacked MT-1E mRNA expression, while both OR- and PR-negative MDA-MD-231 cells exhibited a high level of MT-1E mRNA expression. The level of MT-1E mRNA expression in progesterone-treated and -untreated ABC28 cells remained similar as the parental cell line MDA-MB-231-C2 cells. The results suggest that MT-1E may have specific and functional roles in OR-negative invasive ductal breast cancers, possibly mediated via effector genes downstream of the oestrogen receptor, but not through the PR pathway. © 2000 Cancer Research Campaign
Cone-based clustering heuristic for list-scheduling algorithms

List scheduling algorithms attempt to minimize latency under resource constraints using a priority list. We propose a new heuristic that can be used in conjunction with any priority function. At each time-step, the proposed clustering heuristic tries to find a best match between ready operations and the resource set. The heuristic arbitrates among equal priority operations based on operation-clusters formed from the dependency graph. Based on this heuristic we have presented a new Cone-Based List Scheduling (CBLS) algorithm. Results presented in this paper compare CBLS with the well-known Force Directed List Scheduling (FDLS) algorithm, for several synthesis benchmarks. In cases where FDLS produces sub-optimal schedules, CBLS produces better schedules and in other cases CBLS performs as good as FDLS. Moreover, in conjunction with a simple priority function (namely the self-force of an operator), CBLS results in considerable improvement in latency when compared to FDLS that has the same priority function. Finally, we show that CBLS with the simple priority function performs better in execution time as well as latency when compared to the original FDLS that has a relatively complex priority function.
A Note on Forbidding Clique Immersions

Robertson and Seymour proved that the relation of graph immersion is well-quasi-ordered for finite graphs. Their proof uses the results of graph minors theory. Surprisingly, there is a very short proof of the corresponding rough structure theorem for graphs without $K_t$-immersions; it is based on the Gomory-Hu theorem. The same proof also works to establish a rough structure theorem for Eulerian digraphs without $\vec{K}_t$-immersions, where $\vec{K}_t$ denotes the bidirected complete digraph of order $t$.
One-class classification for spontaneous facial expression analysis

In this paper, we explore one-class classification application in recognizing emotional and nonemotional facial expressions occurred in a realistic human conversation setting - adult attachment interview (AAI). Although emotional facial expressions are defined in terms of facial action units in the psychological study, non-emotional facial expressions have not distinct description. It is difficult and expensive to model non-emotional facial expressions. Thus, we treat this facial expression recognition as a one-class classification problem which is to describe target objects (i.e. emotional facial expressions) and distinguish them from outliers (i. e. non-emotional ones). We first apply Kernel whitening to map the emotional data in a kernel subspace with unit variances in all directions. Then, we use support vector data description (SVDD) for the classification which is to directly fit a boundary with minimal volume around the target data. We present our preliminary experiments on the AAI data, and compare Kernel whitening SVDD with PCA+SVDD and PCA+Gaussian methods
Metagene, a C++ meta-program generation tool

The C++ language offers a two layer evaluation model. Thus, it is possible to evaluate a program in two steps: the so-called static and dynamic evaluations. Static evaluation is used for reducing the amount of work done at execution-time. Programs executed statically (called metaprograms) are written in C++ through an intensive use of template classes. Due to the complexity of these structures, writing, debugging and maintaining C++ meta-programs is a difficult task. Metagene is a program transformation tool which simplifies the development of such programs. Due to the similarities between C++ meta-programming and functional programming, the input language of Metagene is an ML language. Given a functional input program, Metagene outputs the corresponding C++ meta-program expressed using template classes.
Racial and ethnic disparities in access to liver transplantation

Access to liver transplantation is reportedly inequitable for racial/ethnic minorities, but inadequate adjustments for geography and disease progression preclude any meaningful conclusions. We aimed to evaluate the association between candidate race/ethnicity and liver transplant rates after thorough adjustments for these factors and to determine how uniform racial/ethnic disparities were across Model for End‐Stage Liver Disease (MELD) scores. Chronic end‐stage liver disease candidates initially wait‐listed between February 28, 2002 and February 27, 2007 were identified from Scientific Registry for Transplant Recipients data. The primary outcome was deceased donor liver transplantation (DDLT); the primary exposure covariate was race/ethnicity (white, African American, Hispanic, Asian, and other). Cox regression was used to estimate the covariate‐adjusted DDLT rates by race/ethnicity, which were stratified by the donation service area and MELD score. With averaging across all MELD scores, African Americans, Asians, and others had similar adjusted DDLT rates in comparison with whites. However, Hispanics had an 8% lower DDLT rate versus whites [hazard ratio (HR) = 0.92, P = 0.011]. The disparity among Hispanics was concentrated among patients with MELD scores < 20, with HR = 0.84 (P = 0.021) for MELD scores of 6 to 14 and HR = 0.85 (P = 0.009) for MELD scores of 15 to 19. Asians with MELD scores < 15 had a 24% higher DDLT rate with respect to whites (HR = 1.24, P = 0.024). However, Asians with MELD scores of 30 to 40 had a 46% lower DDLT rate (HR = 0.54, P = 0.004). In conclusion, although African Americans did not have significantly different DDLT rates in comparison with similar white candidates, race/ethnicity‐based disparities were prominent among subgroups of Hispanic and Asian candidates. By precluding the survival benefit of liver transplantation, this inequity may lead to excess mortality for minority candidates. Liver Transpl 16:1033–1040, 2010. © 2010 AASLD.
Environmental biotechnology in China: Progress and prospect

Biotechnology could be widely applied in the technological development of environmental protection. This report gives a brief Chinese review on the major progress of environmental biotechnology in the following fields: Monitoring technology and treatment of dioxin‐like chemicals and cyanobacterial toxins, biofiltration for air pollution control, solid waste treatment and reutilization, bioremediation of soil pollution, risk assessment and control of endocrine disturbing substances in environment, wastewater treatment, clean production and recycling economy. The effect of government policy and fund on the progress of environmental biotechnology is also discussed.
Energy-Management Strategy for Embedded Fuel-Cell Systems Using Fuzzy Logic

This paper presents a fuzzy-logic approach to the energy management of an embedded fuel-cell system. The main objective is to study one of the most technological bolts to be overcome for embedded fuel-cell systems: Their energy optimization. To reach this aim, experimentally validated models of a low-power 5-kW proton-exchange-membrane fuel cell and its most power-hungry ancillary (the fuel-cell air-supply system) are described. All simulation results have been performed using Matlab/Simulink environment. Two fuzzy controllers will be proposed for both the internal air-supply control loop and for the whole-embedded energy-management strategy