Miracle-dz/UniFAR-FTUs huggingface dataset:
Downregulation of TESTIN and its association with cancer history and a tendency toward poor survival in head and neck squamous cell carcinoma.

OBJECTIVE To examine the role of TESTIN as a candidate tumor suppressor gene in head and neck carcinogenesis. DESIGN Mutation and messenger RNA (mRNA) expression analyses. SETTING Academic research. PATIENTS Paired normal and tumor samples were obtained from 38 patients with primary head and neck squamous cell carcinoma. MAIN OUTCOME MEASURES Analysis and comparison of TESTIN gene mRNA expression and its relationship to clinicopathologic variables. RESULTS Mutation analysis showed a nucleotide and amino acid change in 6 of the 38 tumor samples (16.0%). Semiquantitative mRNA expression analysis of TESTIN revealed a decreased expression in approximately 50% of the tumors compared with their matched normal controls. Interestingly, comparison of clinicopathologic variables to mRNA expression status of TESTIN revealed a significant difference in terms of cancer history (P = .03). Moreover, a higher smoking ratio and a family cancer history were also associated with downregulation of TESTIN, although the difference was not statistically significant (P = .43 and P = .16, respectively). Kaplan-Meier survival analysis demonstrated a worse survival rate among the patients with low TESTIN expression compared with the patients with normal-high TESTIN expression. CONCLUSIONS Our findings suggest that inactivation of TESTIN is involved in head and neck carcinogenesis through its downregulation. Further studies in various human cancer tissues using a large sample size and in vitro functional studies as well as clinical comparison research studies would give us a better evaluation of TESTIN's role and its possible future application in molecular diagnosis and treatment of different cancer types, including head and neck squamous cell carcinoma.
Learning Value Predictors for the Speculative Execution of Information Gathering Plans

Speculative execution of information gathering plans can dramatically reduce the effect of source I/O latencies on overall performance. However, the utility of speculation is closely tied to how accurately data values are predicted at runtime. Caching is one approach that can be used to issue future predictions, but it scales poorly with large data sources and is unable to make intelligent predictions given previously unseen input data, even when there is an obvious relationship between past input and the output it generated. In this paper, we describe a novel way to combine classification and transduction for a more efficient and accurate value prediction strategy, one capable of issuing predictions about previously unseen hints. We show how our approach results in significant speedups for plans that query multiple sources or sources that require multi-page navigation.
Repeatability, Sensitivity, and Uncertainty Analyses of the BANCS Model Developed to Predict Annual Streambank Erosion Rates

Accelerated streambank erosion caused by channel instability can be the leading cause of sediment impairment of streams. Obtaining accurate streambank erosion rates for sediment budgeting and prioritizing mitigation efforts can be difficult and costly. One approach to quantifying streambank erosion rates is through the development and implementation of an empirically derived “Bank Assessment for Non‐point Source Consequences of Sediment” (BANCS) model. This study aims to improve the BANCS model application by evaluating repeatability between users and identifying sensitive and/or uncertain model inputs. Statistical analysis of streambank evaluations conducted by 10 different individuals suggests the implementation of the BANCS model may not be repeatable. This finding may be due to sensitive model inputs, such as streambank height and near‐bank stress level prediction method selection, and/or uncertain model inputs, such as bank material identification and the associated adjustment of erosion potential. Furthermore, it was found assessing streambanks as a group by obtaining a measure of central tendency from individual evaluations, as well as obtaining a higher level of training, may improve model implementation precision. Application of these suggestions may result in improved prediction of streambank erosion rates utilizing the BANCS model methodology.
Visual Speech Speeds Up Auditory Identification Responses

Auditory speech perception is more accurate when combined with visual speech. Recent ERP studies suggest that visual speech helps 'predict' which phoneme will be heard via feedback from visual to auditory areas, with more visual salient articulations associated with greater facilitation. Two experiments tested this hypothesis with a speeded auditory identification measure. Stimuli consisted of the sounds 'apa’, 'aka' and 'ata', with matched and mismatched videos that showed the talker’s whole face or upper face (control). The percentage of matched AV videos was set at 85% in Experiment 1 and 15% in Experiment 2. Results showed that responses to matched whole face stimuli were faster than both upper face and mismatched videos in both experiments. Furthermore, salient phonemes (aPa) showed a greater reduction in reaction times than ambiguous ones (aKa). The current study provides support for the proposal that visual speech speeds up processing of auditory speech.
Clinical Prognostic Messages From a Systematic Review on Cerebral Palsy

OBJECTIVE: To summarize evidence on the rates of co-occurring impairments, diseases, and functional limitations with cerebral palsy into succinct clinical messages. METHODS: A search was conducted of the databases PubMed, Medline, CINAHL, and PsycINFO, and the results were supplemented with hand searches. Two independent reviewers determined whether retrieved abstracts met the following inclusion criteria: human subjects; >90% were children or adults with cerebral palsy; published after 1999; and population-based data. Articles were appraised, analyzing design, participants, level of evidence, rates of impairments, and functional implications. Methodologic quality was rated by using a standardized checklist. RESULTS: A total of 1366 papers were identified in the search; 82 were appraised and 30 were included in the meta-analyses. High-level evidence existed, as rated on the Oxford 2011 Levels of Evidence: 97% of prevalence studies were level 1. The data were of a moderate to high quality grade (with the exception of sleep disorders), allowing plain English clinical messages to be developed. CONCLUSIONS: Among children with cerebral palsy, 3 in 4 were in pain; 1 in 2 had an intellectual disability; 1 in 3 could not walk; 1 in 3 had a hip displacement; 1 in 4 could not talk; 1 in 4 had epilepsy; 1 in 4 had a behavior disorder; 1 in 4 had bladder control problems; 1 in 5 had a sleep disorder; 1 in 5 dribbled; 1 in 10 were blind; 1 in 15 were tube-fed; and 1 in 25 were deaf.
3-D motion recovery via low rank matrix restoration on articulation graphs

This paper addresses the challenge of 3-D skeleton recovery by exploiting the spatio-temporal correlations of corrupted 3D skeleton sequences. A skeleton sequence is represented as a matrix. We propose a novel low-rank solution that effectively integrates both a low-rank model for robust skeleton recovery based on temporal coherence, and an articulation-graph-based isometric constraint for spatial coherence, namely consistency of bone lengths. The proposed model is formulated as a constrained optimization problem, which is efficiently solved by the Augmented Lagrangian Method with a Gauss-Newton solver for the subproblem of isometric optimization. Experimental results on the CMU motion capture dataset and a Kinect dataset show that the proposed approach achieves better recovery accuracy over a state-of-the-art method. The proposed method has wide applicability for skeleton tracking devices, such as the Kinect, because these devices cannot provide accurate reconstructions of complex motions, especially in the presence of occlusion.
Salt-sensitive hypertension: food for thought.

See related article, pp 447–455 Epidemiological studies demonstrating an increase in cardiovascular disease in adult children born of women who suffered nutritional privation during World War II led to many subsequent studies, demonstrating that diverse conditions leading to intrauterine growth retardation had similar effects on cardiovascular disease including hypertension.1 Relatively mild maternal protein deficiency leads to abnormal nephron structure and dysregulation of the renin–angiotensin II–aldosterone system.2,3 The report in this issue, by Geurts et al4 builds on the finding that a protein-sufficient casein-based diet significantly increases the degree of salt-induced hypertension and renal damage in the inbred Dahl Salt-Sensitive rat strains SS/Mcw when compared with SS/Crl fed a grain-based diet with similar proportions of protein, fat, and carbohydrates.5 SS/Mcw rats were derived from Dahl SS/Jr rats purchased from Harlan Sprague Dawley Laboratories and maintained by brother-sister mating at the Medical College of Wisconsin since 1991, where they were fed a purified diet using casein as the protein source. SS/Crl rats were derived from SS/Mcw given to Charles River Laboratories in 2001 and fed a grain-based diet. In the present study, progeny of 4-way embryo transfers between SS/Mcw and SS/Crl dams fed their usual diets, progeny of parental strains on their usual diets, and SS/Crl rats after 1 generation of the purified casein-based diet were studied with or without 3 weeks on a high casein-based diet. Blood pressure, albuminuria, renal histopathology, and transcriptome …
Entity-based Classification of Twitter Messages

Twitter is a popular micro-blogging service on theWeb, where people can enter short messages, which then become visible to some other users of the service. While the topics of these messages varies, there are a lot of messages where the users express their opinions about some companies or their products. These messages are a rich source of information for companies for sentiment analysis or opinion mining. There is however a great obstacle for analyzing the messages directly: as the company names are often ambiguous (e.g. apple, the fruit vs. Apple Inc.), one needs first to identify, which messages are related to the company. In this paper we address this question. We present various techniques for classifying tweet messages containing a given keyword, whether they are related to a particular company with that name or not. We first present simple techniques, which make use of company profiles, which we created semi-automatically from external Web sources. Our advanced techniques take ambiguity estimations into account and also automatically extend the company profiles from the twitter stream itself. We demonstrate the effectiveness of our methods through an extensive set of experiments. Moreover, we extensively analyze the sources of errors in the classification. The analysis not only brings further improvement, but also enables to use the human input more efficiently.
Altered circadian responses to light in streptozotocin-induced diabetic mice.

Diabetes mellitus affects the daily expression of many behavioral and metabolic processes. Recent studies indicate that changes in brain glucose metabolism alter the entraining effects of light of the circadian pacemaker. To test whether diabetes-associated diurnal changes are related to alterations in the responses of the circadian pacemaker to light, photic phase resetting of the circadian rhythm of locomotor activity was analyzed in diabetic mice housed in constant darkness. Multiple low doses of streptozotocin, which damages pancreatic β-insulin-producing cells, were used to render C57BL/6J mice mildly diabetic. In those mice treated with streptozotocin, serum glucose was increased by 25% and circadian responses to light either were increased by 40% for phase delays or were close to those observed in control animals for phase advances. Furthermore, insulin-induced hypoglycemia normalized light-induced phase delays in diabetic animals, without altering those in nondiabetic mice. These results show that abnormalities of daily temporal organization associated with diabetes can result from altered circadian responses to the daily variation in ambient light. Such alterations could be normalized with appropriate insulin therapy.
Uni-axial stretching regulates intracellular localization of Hic-5 expressed in smooth-muscle cells in vivo

Hic-5 is a focal adhesion protein belonging to the paxillin LIM family that shuttles in and out of the nucleus. In the present study, we examined the expression of Hic-5 among mouse tissues by immunohistochemistry and found its expression only in smooth-muscle cells in several tissues. This result is consistent with a previous report on adult human tissues and contradicts the relatively ubiquitous expression of paxillin, the protein most homologous to Hic-5. One factor characterizing smooth-muscle cells in vivo is a continuous exposure to mechanical stretching in the organs. To study the involvement of Hic-5 in cellular responses to mechanical stress, we exposed mouse embryo fibroblasts to a uni-axial cyclic stretching and found that Hic-5 was relocalized from focal adhesions to stress fibers through its C-terminal LIM domains during the stress. In sharp contrast to this, paxillin did not change its focal-adhesion-based localization. Of the factors tested, which included interacting partners of Hic-5, only CRP2 (an only-LIM protein expressed in vascular smooth-muscle cells) and GIT1 were, like Hic-5, localized to stress fibers during the cyclic stretching. Interestingly, Hic-5 showed a suppressive effect on the contractile capability of cells embedded in three-dimensional collagen gels, and the effect was further augmented when CRP2 co-localized with Hic-5 to fiber structures of those cells. These results suggested that Hic-5 was a mediator of tensional force, translocating directly from focal adhesions to actin stress fibers upon mechanical stress and regulating the contractile capability of cells in the stress fibers.
Textual CBR in jCOLIBRI : From Retrieval to Reuse ?

In this paper we first review the functionality that jcolibri offers related to textual CBR: statistical retrieval for textual cases based on Information Retrieval and Information Extraction methods to capture features from texts. The novelty of this paper is an approach to userguided adaptation of texts based on Information Retrieval + Clustering techniques. This method uses two pre-existing engines: Lucene to retrieve the most similar documents and Carrot2 to cluster the documents and to guide the adaptation process. We illustrate the application of this method in a system that addresses the workshop challenge. This system has been developed using jcolibri (version 2) [13] and is available at: http://gaia.fdi. ucm.es/grupo/software.html (open-source licensed).
A Decade in the Life of EXO 2030+375: A Multiwavelength Study of an Accreting X-Ray Pulsar

Using BATSE and RXTE observations from 1991 April to 2001 August, we have detected 71 outbursts from 82 periastron passages of EXO 2030+375, a 42 s transient X-ray pulsar with a Be star companion, including several outbursts from 1993 August to 1996 April, when the source was previously believed to be quiescent. Combining BATSE, RXTE, and EXOSAT data, we have derived an improved orbital solution. Applying this solution results in a smooth profile for the spin-up rate during the giant outburst and results in evidence for a correlation between the spin-up rate and observed flux in the brighter BATSE outbursts. Infrared and Hα measurements show a decline in the density of the circumstellar disk around the Be star. This decline is followed by a sudden drop in the X-ray flux and a turnover from a spin-up trend to spin-down in the frequency history. This is the first Be/X-ray binary that shows an extended interval, about 2.5 yr, in which the global trend is spin-down, but the outbursts continue. In 1995 the orbital phase of EXO 2030+375's outbursts shifted from peaking about 6 days after periastron to peaking before periastron. The outburst phase slowly recovered to peaking at about 2.5 days after periastron. We interpret this shift in orbital phase followed by a slow recovery as evidence of a global one-armed oscillation propagating in the Be disk. This is further supported by changes in the shape of the Hα profile, which are commonly believed to be produced by a reconfiguration of the Be disk. The truncated viscous decretion disk model provides an explanation for the long series of normal outbursts and the evidence of an accretion disk in the brighter normal outbursts. Long-term multiwavelength observations such as these clearly add considerably to our knowledge of Be/X-ray binaries and the relationship among optical, infrared, and X-ray observations.
Model Selection using Sparse Dataand Backward Sequential Search

This paper presents an empirical comparison of a variety of model evaluation criteria used in backwards sequential search (BSS). Both information criteria (IC) and signiicance tests are compared when applied to the problem of word sense disambigua-tion. We present experimental results that show the evaluation criteria that selects the most accurate models for classiication. When the degrees of freedom of the model are adjusted the Log-likelihood ratio G 2 and Akaike's Information Criteria (AIC) select the most accurate models. If the degrees of freedom are not adjusted then the most accurate evaluation criteria for word sense disambiguation is IC = 1.
Disambiguating “DE” for Chinese-English Machine Translation

Linking constructions involving [Abstract contained text which could not be captured. ] (DE) are ubiquitous in Chinese, and can be translated into English in many different ways. This is a major source of machine translation error, even when syntax-sensitive translation models are used. This paper explores how getting more information about the syntactic, semantic, and discourse context of uses of [Abstract contained text which could not be captured. ] (DE) can facilitate producing an appropriate English translation strategy. We describe a finer-grained classification of [Abstract contained text which could not be captured. ] (DE) constructions in Chinese NPs, construct a corpus of annotated examples, and then train a log-linear classifier, which contains linguistically inspired features. We use the DE classifier to preprocess MT data by explicitly labeling [Abstract contained text which could not be captured. ] (DE) constructions, as well as reordering phrases, and show that our approach provides significant BLEU point gains on MT02 (+1.24), MT03 (+0.88) and MT05 (+1.49) on a phrased-based system. The improvement persists when a hierarchical reordering model is applied.
Genome Sequencing of Ralstonia solanacearum FQY_4, Isolated from a Bacterial Wilt Nursery Used for Breeding Crop Resistance

ABSTRACT Ralstonia solanacearum strain FQY_4 was isolated from a bacterial wilt nursery, which is used for breeding crops for Ralstonia resistance in China. Here, we report the complete genome sequence of FQY_4 and its comparison with other published R. solanacearum genomes, especially with the strains GMI1000 and Y45 in the same group.
Recurrent Filter Learning for Visual Tracking

Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images. Recent methods perform online tracking by fine-tuning a pre-trained CNN model to the specific target object using stochastic gradient descent (SGD) back-propagation, which is usually time-consuming. In this paper, we propose a recurrent filter generation methods for visual tracking. We directly feed the target's image patch to a recurrent neural network (RNN) to estimate an object-specific filter for tracking. As the video sequence is a spatiotemporal data, we extend the matrix multiplications of the fully-connected layers of the RNN to a convolution operation on feature maps, which preserves the target's spatial structure and also is memory-efficient. The tracked object in the subsequent frames will be fed into the RNN to adapt the generated filters to appearance variations of the target. Note that once the off-line training process of our network is finished, there is no need to fine-tune the network for specific objects, which makes our approach more efficient than methods that use iterative fine-tuning to online learn the target. Extensive experiments conducted on widely used benchmarks, OTB and VOT, demonstrate encouraging results compared to other recent methods.
Cell Therapy Augments Myocardial Perfusion and Improves Quality of Life in Patients With Refractory Angina.

Refractory angina pectoris is a chronic disabling condition affecting ≈850 000 patients in the United States.1 It is characterized by frequent angina attacks unresponsive to maximal medical therapy and obstructive coronary artery disease not amenable to coronary revascularization.2 Although major progress has been made in medical therapy and cardiovascular interventions,1 up to 43% of patients continue to experience symptoms and 33% have positive exercise tests after angioplasty.3 It is now well recognized that these patients have concomitant microvascular disease, with reduced coronary and systemic flow reserve at a microvascular level and impaired endothelium-mediated vasorelaxation, that is, endothelial dysfunction.4 Currently, the treatment of these patients remains a major clinical challenge. Article, see p 984 To address this large unmet therapeutic need, research has focused on biological strategies for refractory angina. A key effort is the use of cell therapy, which has the potential to restore the microcirculation and improve myocardial tissue perfusion by stimulating neoangiogenesis.5 In this regard, accumulating evidence supports the idea that cell-based therapy can improve clinical outcomes, including frequency of angina episodes, myocardial infarction (MI) rate, and exercise tolerance, in patients with refractory angina5,6 and, thus, should be subject to further trials to evaluate this treatment option for this patient population. In this issue of Circulation Research , Khan et al present a comprehensive meta-analysis of cell-based therapy for refractory angina. Importantly, their analysis addresses the heterogeneity of the included trials, the problem of missing data, and limitations of the study.5 Six single- and double-blinded, randomized clinical trials were included in this meta-analysis, comprising a patient population that had class III-IV Canadian Cardiovascular Society angina, were refractory to medical therapy, and were not coronary revascularization candidates (Table). The study included 192 patients who received cell therapy plus standard …
On Visualization and Comprehension of Scenario-Based Programs

We address the problem of comprehending cause and effect relationships between relatively independent behavior components of a single application. Our focus is on the paradigm of behavioral, scenario-based, programming, as captured by the language of live sequence charts (LSC) or its Java-based counterpart, BPJ. In this programming paradigm, multi-modal behaviors can be specified separately, and are integrated only at run time. We present a tool, with which the user can easily follow the decisions of the collective execution mechanism. It shows the behaviors and events that were executed at each point in time, and those that were delayed or abandoned, as well as the causes and reasons behind these run-time choices. The dynamic effects of such decisions on thesystem's behavior can be seen easily too.