Miracle-dz/UniFAR-FTUs huggingface dataset:
SPP1 genotype is a determinant of disease severity in Duchenne muscular dystrophy

# {#article-title-2} To the Editor: Variability in disease severity in Duchenne muscular dystrophy (DMD) is considered a biological phenomenon, possibly due to genetic or epigenetic mechanisms. It was exciting to read the article by Pegoraro et al.1 describing the discovery of osteopontin as a possible modifier gene. As discussed in the accompanying editorial by Drs. Nelson and Griggs,2 utrophin and myostatin are 2 other proteins modifying disease severity in the mdx mouse. However, human data supporting an important role for utrophin were not mentioned. Kleopas et al.3 demonstrated that utrophin expression in the initial diagnostic muscle biopsies of …
Facile detection of specific RNA‐polypeptide interactions by MALDI‐TOF mass spectrometry

A simple method for the detection of specific RNA‐polypeptide interactions using MALDI‐TOF mass spectroscopy is described. Instead of direct observation of the RNA‐polypeptide complex, we attempted the indirect observation of the binding event by focusing on the disappearance of the free polypeptide signal upon interaction with RNA. As a result, specific binding of the Rev‐response element (RRE) RNA of the HIV with two RRE‐binding peptide aptamers, DLA and RLA peptides, as well as the bacteriophage λ boxB RNA with the λ N peptide was observed. We also show that specific RNA‐binding peptides can be identified from a mixture of peptides with varying RNA‐binding affinity, showing that the method could be applied to high‐throughput screening from simple peptide libraries. The method described in this study provides a quick and simple method for detecting specific RNA–polypeptide interactions that avoids difficulties associated with direct observation of RNA and RNA–polypeptide complexes, which may find various applications in the analysis of RNA–polypeptide interactions and in the identification of novel RNA‐binding polypeptides. Copyright © 2008 European Peptide Society and John Wiley & Sons, Ltd.
Usefulness of real-time three-dimensional echocardiography to quantify global left ventricular function and mechanical dyssynchrony after heart transplantation

Objective The purpose of this study was to examine left ventricular global function and left ventricular mechanical dyssynchrony (LVMD) after heart transplantation using three-dimensional echocardiography (RT-3DE) and to evaluate the value for RT-3DE in predicting cardiac allograft rejection (CAR). Methods and results A total of 95 consecutive patients undergoing orthotropic heart transplantation, of whom 20 had CAR and 75 had no CAR, were enrolled in this study. Forty healthy volunteers were included as the control group. All patients underwent RT-3DE examination. Time to minimum systolic volume (Tmsv) of each left ventricular segment was measured. The parameters of LVMD including the standard deviation (SD) of Tmsv of 16 segments (Tmsv 16-SD), 12 segments (Tmsv 12-SD), and 6 basal segments (Tmsv 6-SD) were automatically calculated. The parameters of LVMD were adjusted by cardiac cycle and presented in terms of percentage as Tmsv 16-SD%, Tmsv 12-SD%, and Tmsv 6-SD%. Results The excursion average (Avg), excursion max (Max) and left ventricular ejection fraction (LVEF) were lower in patients with CAR than in those without CAR (all P < 0.05), while not diff erent between patients without CAR and control subjects (all P > 0.05). The LVMD parameters, including Tmsv 16-SD, Tmsv 12-SD, Tmsv 6-SD, Tmsv 16-SD%, Tmsv 12-SD%, and Tmsv 6-SD%, were greater in patients with CAR than in those without CAR, while not diff erent between patients without CAR and control subjects. All the RT-3DE parameters (LVEF and LVMD parameters) can predict CAR. However, Tmsv 16-SD (AUC 0.89 ± 0.039, P < 0.001; sensitivity 85% and specifi city 68%) and Tmsv 16-SD% (AUC 0.89 ± 0.037, P < 0.001; sensitivity 95% and specifi city 73%) off ered the strongest power for detecting CAR. Conclusion CAR can induce LVMD. LVMD parameters obtained by 3D-RTE, especially Tmsv 16-SD and Tmsv 16-SD%, provides a good sensitivity and specifi city for predicting CAR after heart transplantation.
How sympathetic are your spinal cord circuits?

What is the topic of this review? This review focuses on the role of gap junctions and interneurones in sympathetic control at the spinal cord level. What advances does it highlight? The review considers the importance of these local spinal circuits in contributing to rhythmic autonomic activity and enabling appropriate responses to homeostatic perturbations.
Combining Background Knowledge and Learned Topics

Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. Although topic models can potentially discover a broad range of themes in a data set, the interpretability of the learned topics is not always ideal. Human-defined concepts, however, tend to be semantically richer due to careful selection of words that define the concepts, but they may not span the themes in a data set exhaustively. In this study, we review a new probabilistic framework for combining a hierarchy of human-defined semantic concepts with a statistical topic model to seek the best of both worlds. Results indicate that this combination leads to systematic improvements in generalization performance as well as enabling new techniques for inferring and visualizing the content of a document.
Ion-mediated nucleation as an important global source of tropospheric aerosols

Aerosol nucleation events have been observed at a variety of locations worldwide, and may have signifi- cant climatic and health implications. While ions have long been suggested as favorable nucleation embryos, their sig- nificance as a global source of particles has remained uncer- tain. Here, an ion-mediated nucleation (IMN) mechanism, which incorporates new thermodynamic data and physical algorithms, has been integrated into a global chemical trans- port model (GEOS-Chem) to study ion-mediated particle for- mation in the global troposphere. The simulated annual mean results have been compared to a comprehensive set of data relevant to particle nucleation around the globe. We show that predicted annual spatial patterns of particle formation agree reasonably well with land-, ship-, and aircraft-based observations. Our simulations show that, globally, IMN in the boundary layer is largely confined to two broad latitude belts: one in the northern hemisphere ( 20 N-70 N), and one in the southern hemisphere ( 30 S-90 S). In the mid- dle latitude boundary layer over continents, the annual mean IMN rates are generally above 10 4 cm 3 day 1 , with some hot spots reaching 10 5 cm 3 day 1 . The zonally-averaged vertical distribution of IMN rates indicates that IMN is sig- nificant in the tropical upper troposphere, the entire middle latitude troposphere, and over Antarctica. Comparing the rel- ative strengths of particle sources due to IMN and due to pri- mary particle emissions demonstrates that IMN is significant on a global scale. Further research is needed to reduce mod- eling uncertainties and to understand the ultimate contribu- tion of freshly nucleated particles to the abundance of cloud condensation nuclei.
Locally recoverable codes on algebraic curves

A code over a finite alphabet is called locally recoverable (LRC code) if every symbol in the encoding is a function of a small number (at most r) other symbols. A family of linear LRC codes that generalize the classic construction of Reed-Solomon codes was constructed in a recent paper by I. Tamo and A. Barg (IEEE Trans. Inform. Theory, vol. 60, no. 8, 2014, pp. 4661-4676). In this paper we extend this construction to codes on algebraic curves. We give a general construction of LRC codes on curves and compute some examples, including asymptotically good families of codes derived from the Garcia-Stichtenoth towers. The local recovery procedure is performed by polynomial interpolation over r coordinates of the codevector. We also obtain a family of Hermitian codes with two disjoint recovering sets for every symbol of the codeword.
Image Recognition Based on Kernel Self-Optimized Learning

Image recognition technologies have been used in many areas, and feature extraction of image is key step for image recognition. A novel feature extraction method using kernel self-optimized learning for image recognition. The scheme of image feature extraction includes textural extraction using Gabor wavelet, textural features reduction based on class-wise locality preserving projection with the nearest neighbor graph and common kernel discriminant vector. The nearest neighbor classifier is applied to image classification. The feasibility and performance of the algorithm are testified in the public image databases.
iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System

This paper proposes an implementation of a Kalman filter, using inertial sensors of a smartphone, to estimate 3-D angulation of the trunk. The developed system monitors the trunk angular evolution during bipedal stance and helps the user to improve balance through a configurable and integrated auditory-biofeedback (ABF) loop. A proof-of-concept study was performed to assess the effectiveness of this so-called iBalance-ABF-smartphone-based audio-biofeedback system-in improving balance during bipedal standing. Results showed that young healthy individuals were able to efficiently use ABF on sagittal trunk tilt to improve their balance in the medial-lateral direction. These findings suggest that the iBalance-ABF system as a telerehabilitation system could represent a suitable solution for ambient assisted living technologies.
Epidermal growth factor receptor tyrosine kinase inhibitors as first-line treatment in advanced nonsmall-cell lung cancer

Purpose of review Classic activating mutations in the form of deletions in exon 19 or a missense mutation L858R in the tyrosine kinase domain of the epidermal growth factor receptor (EGFR) predict dramatic responses to EGFR tyrosine kinase inhibitors such as gefitinib and erlotinib. We review here the clinical benefits of targeted therapy with erlotinib and gefitinib in white and Asian nonsmall-cell lung cancer patients. Recent findings Two separate analyses of pooled data from small phase II prospective studies show that therapy with gefitinib and erlotinib induces responses in over 70% of nonsmall-cell lung cancer patients harboring classic EGFR mutations, with progression-free survival ranging from 9 to 13 months and median survival of around 23 months. Two separate studies in white and Asian patients have recently confirmed that these subgroups of patients attain response rates of 70% with erlotinib and gefitinib, including complete responses, progression-free survival of up to 14 months, and median survival of up to 27 months. The serial monitoring of EGFR mutations in the blood will permit the assessment of molecular responses and be an important tool for the surveillance of clinical progression. Summary Nonsmall-cell lung cancer with EGFR mutations constitute a new entity with a unique opportunity for further refinement of different genetic subgroups among patients with EGFR mutations, requiring different personalized treatment strategies. Despite the impressive outcomes attained with EGFR tyrosine kinase inhibitors, patients with EGFR mutations at present require continuous treatment, and only a fraction of these patients will reach sustainable long-term survival.
Early Improvement in One Week Predicts the Treatment Response to Escitalopram in Patients with Social Anxiety Disorder: A Preliminary Study

Objective Social anxiety disorder (SAD) shows relatively delayed responses to pharmacotherapy when compared to other anxiety disorders. Therefore, more effective early therapeutic decisions can be made if the therapeutic response is predictable as early as possible. We studied whether the therapeutic response at 12 weeks is predictable based on the early improvement with escitalopram at 1 week. Methods The subjects were 28 outpatients diagnosed with SAD. The subjects took 10–20 mg/day of escitalopram. The results of the Liebowitz social anxiety scale (LSAS), Hamilton anxiety rating scale, and Montgomery-Asberg depression rating scale were evaluated at 0, 1, 4, 8, and 12 weeks of treatment. Early improvement was defined as a ≥10% reduction in the LSAS total at 1 week of treatment, and endpoint response was defined as a ≥35% reduction in the LSAS total score. The correlation between clinical characteristics and therapeutic responses was analyzed by simple linear regression. The correlation between early improvement responses and endpoint responses was analyzed by multivariate logistic regression analysis and receiver operating characteristic curves. Results When we adjusted the influence of a ≥35% reduction in the LSAS total endpoint score on a ≥10% reduction of the LSAS total score at 1 week of treatment for the patients’ age, the early improvement group at 1 week of treatment was expected to show stronger endpoint responses compared to the group with no early improvement. Conclusion The results suggest that a ≥10% reduction in the LSAS total score in a week can predict endpoint treatment response.
Performance analysis in heterogeneous cloud radio access networks with non-uniform device-to-device deployment

In this paper, we consider Heterogeneous Cloud Radio Access Network (H-CRAN) with non-uniform Device-to-Device (D2D) communication. Specifically, D2D transmission are only utilized outside a prescribed distance from any high power node (HPN). Based on the analytical framework provided in this paper, the average ergodic rate of a typical user equipment (UE) is characterized. Through appropriate definition of the exclusion area, the non-uniform D2D deployment can achieve performance improvement compared with uniform D2D deployment. In addition, to account for capacity constraint fronhaul of the remote radio heads (RRHs), we characterize the average traffic delivery latency experience by a typical UE when served by RRH as a quality of service (QoS) metric. Our results show that for lower fronthaul capacity regime, the non-uniform D2D deployment achieves lower average traffic delivery latency compared to both the uniform D2D deployment in H-CRAN and the pure H-CRAN scenarios.
The Sonic Visualiser: A Visualisation Platform for Semantic Descriptors from Musical Signals

Sonic Visualiser is the name for an implementation of a system to assist study and comprehension of the contents of audio data, particularly of musical recordings. It is a C++ application with a Qt4 GUI that runs on Windows, Mac, and Linux. It embodies a number of concepts which are intended to improve interaction with audio data and features, most notably with respect to the representation of time-synchronous information. The architecture of the application allows for easy integration of third party algorithms for the extraction of low and mid-level features from musical audio data. This paper describes some basic principles and functionalities of Sonic Visualiser.
The concept of dynamic analysis

Dynamic analysis is the analysis of the properties of a running program. In this paper, we explore two new dynamic analyses based on program profiling:Frequency Spectrum Analysis. We show how analyzing the frequencies of program entities in a single execution can help programmers to decompose a program, identify related computations, and find computations related to specific input and output characteristics of a program. Coverage Concept Analysis. Concept analysis of test coverage data computes dynamic analogs to static control flow relationships such as domination, postdomination, and regions. Comparison of these dynamically computed relationships to their static counterparts can point to areas of code requiring more testing and can aid programmers in understanding how a program and its test sets relate to one another.
Relational Group Psychotherapy: the Healing of Stress, Neglect and Trauma

This article is the Keynote Address given at the 4th International Integrative Psychotherapy Association Conference, April 17, 2009. In speaking to the conference theme of “Acute Trauma, Cumulative Neglect, and Chronic Stress” the article describes some of the principles of Relational Group Psychotherapy. The theory of methods is based on the concept that the healing of trauma, neglect and stress occurs through a contactful therapeutic relationship. Relational group psychotherapy draws from several developments in group therapy, particularly the cybernetic feedback and other-centered models. It emphasizes the healing power of relationships between group members and the importance of phenomenological inquiry, affective attunement, identification, and relational-needs. The leader’s tasks are to stimulate the flow of contactful dialogue and to teach about human needs and healthy relationships.
Cooperative MIMO Channel Modeling and Multi-Link Spatial Correlation Properties

In this paper, a novel unified channel model framework is proposed for cooperative multiple-input multiple-output (MIMO) wireless channels. The proposed model framework is generic and adaptable to multiple cooperative MIMO scenarios by simply adjusting key model parameters. Based on the proposed model framework and using a typical cooperative MIMO communication environment as an example, we derive a novel geometry-based stochastic model (GBSM) applicable to multiple wireless propagation scenarios. The proposed GBSM is the first cooperative MIMO channel model that has the ability to investigate the impact of the local scattering density (LSD) on channel characteristics. From the derived GBSM, the corresponding multi-link spatial correlation functions are derived and numerically analyzed in detail.
A phase II trial of bevacizumab plus everolimus for patients with refractory metastatic colorectal cancer.

PURPOSE For patients with metastatic colorectal cancer (mCRC), no standard therapy exists after progression on 5-fluorouracil, oxaliplatin, irinotecan, bevacizumab, and cetuximab or panitumumab. Preclinical data demonstrated that combined vascular endothelial growth factor and mammalian target of rapamycin inhibition has greater antiangiogenic and antitumor activity than either monotherapy. A phase I study of bevacizumab plus everolimus demonstrated that the combination is safe; activity was seen in several patients with refractory mCRC. METHODS Fifty patients with refractory mCRC were enrolled and received bevacizumab at 10 mg/kg every 2 weeks and everolimus at 10 mg orally daily. RESULTS Of the 50 patients enrolled, the median age was 56 years and the median number of prior regimens was four. Forty-seven patients (96%) had prior bevacizumab exposure and 42 patients (84%) had documented progression on prior bevacizumab-based therapy. Forty-nine patients were evaluable for response; eight patients had minor responses (16%) and an additional 15 patients (30%) had stable disease (SD). No complete or partial responses were seen. The median progression-free survival interval was 2.3 months; however, 26% of patients achieved prolonged SD for ≥6 months, and three patients (6%) were on study for >1 year. The median overall survival duration was 8.1 months. The most common grade 1-2 toxicities were mucositis (68%) and hyperlipidemia (64%). Clinically significant grade ≥3 toxicities included hypertension (14%), fistula/abscess/perforation (8%), mucositis (6%), and hemorrhage (2%). CONCLUSIONS Bevacizumab plus everolimus is generally tolerable but may have risks related to mucosal damage and/or wound healing. Bevacizumab plus everolimus appears to have modest activity in refractory mCRC in patients.
EFFECTS OF DIFFERENTIAL VALUE AND EXPOSURE TIME UPON THE DETECTION AND MEMORY OF SYMBOLS IN A VISUAL SEARCH TASK

Abstract : The accuracy of reporting data from briefly-ex posed, multi-target symbolic displays in which the value or importance of the targets varies within the display was shown to vary inversely with the differential ratio of value of the tar gets. The data also suggested that (1) an in crease in differential ratio does not facilitate the reporting of more important targets, but rather decreases reports of less important ones, (2) the difference in accuracy of report to high and low valued targets varies directly with exposure time up to 2.5 sec for the display used with 1.5 sec as a possible optimum. The results are consistent with the hypothesis that differential value produces a selective recall from short-term memory storage.
Elite Multi-Group Differential Evolution

An Elite Multi-Group Differential Evolution algorithm for unconstrained single objective optimization is proposed. In the novel algorithm, the population is divided into sub-groups with different parameters setting to balance the global and local search ability. The good information collected in the search process is exchanged among groups. Experiments are conducted on seven commonly used benchmark functions and two new constructed harder test functions which are useful to test the local search ability of the algorithms and the proposed algorithm shows its effectiveness and efficiency.
Heuristic Methods for Solving Job-Shop Scheduling Problems

Solving scheduling problems with Constraint Satisfaction Problems (CSP’s) techniques implies a wide space search with a large number of variables, each one of them with a wide interpretation domain. This paper discusses the application of CSP heuristic techniques (based on the concept of slack of activities) for variable and value ordering on a special type of job-shop scheduling problems in which the operations must schedule inside of temporal windows. These techniques are improved by introducing the concepts of slack probability and the find-hole method. Thus, a more flexible heuristic technique is obtained, which improves empirical efficiency and allows early detection of unfeasible problems.
Confidence-based Rewriting of Machine Translation Output

Numerous works in Statistical Machine Translation (SMT) have attempted to identify better translation hypotheses obtained by an initial decoding using an improved, but more costly scoring function. In this work, we introduce an approach that takes the hypotheses produced by a state-ofthe-art, reranked phrase-based SMT system, and explores new parts of the search space by applying rewriting rules selected on the basis of posterior phraselevel confidence. In the medical domain, we obtain a 1.9 BLEU improvement over a reranked baseline exploiting the same scoring function, corresponding to a 5.4 BLEU improvement over the original Moses baseline. We show that if an indication of which phrases require rewriting is provided, our automatic rewriting procedure yields an additional improvement of 1.5 BLEU. Various analyses, including a manual error analysis, further illustrate the good performance and potential for improvement of our approach in spite of its simplicity.