Miracle-dz/UniFAR-FTUs huggingface dataset:
FOXD3 is a novel tumor suppressor that affects growth, invasion, metastasis and angiogenesis of neuroblastoma

The transcription factor forkhead box D3 (FOXD3) plays a crucial role in the development of neural crest cells. However, the function and underlying mechanisms of FOXD3 in the progression of neuroblastoma (NB), an embryonal tumor that is derived from the neural crest, still remain largely unknown. Here, we report that FOXD3 is an important oncosuppressor of NB tumorigenicity and aggressiveness. We found that FOXD3 was down-regulated in NB tissues and cell lines. Patients with high FOXD3 expression have greater survival probability. Over-expression or knockdown of FOXD3 responsively altered both the protein and mRNA levels of N-myc downstream regulated 1 (NDRG1) and its downstream genes, vascular endothelial growth factor and matrix metalloproteinase 9, in cultured NB cell lines SH-SY5Y and SK-N-SH. Luciferase reporter and chromatin immunoprecipitation assays indicated that FOXD3 directly targeted the binding site within NDRG1 promoter to facilitate its transcription. Ectopic expression of FOXD3 suppressed the growth, invasion, metastasis and angiogenesis of SH-SY5Y and SK-N-SH cells in vitro and in vivo. Conversely, knockdown of FOXD3 promoted the growth, migration, invasion and angiogenesis of NB cells. In addition, rescue experiments in FOXD3 over-expressed or silenced NB cells showed that restoration of NDRG1 expression prevented the tumor cells from FOXD3-mediated changes in these biological features. Our results indicate that FOXD3 exhibits tumor suppressive activity that affects the growth, aggressiveness and angiogenesis of NB through transcriptional regulation of NDRG1.
Pseudoachondroplasia and Multiple Epiphyseal Dysplasia: A 7-Year Comprehensive Analysis of the Known Disease Genes Identify Novel and Recurrent Mutations and Provides an Accurate Assessment of Their Relative Contribution

Pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (MED) are relatively common skeletal dysplasias resulting in short‐limbed dwarfism, joint pain, and stiffness. PSACH and the largest proportion of autosomal dominant MED (AD‐MED) results from mutations in cartilage oligomeric matrix protein (COMP); however, AD‐MED is genetically heterogenous and can also result from mutations in matrilin‐3 (MATN3) and type IX collagen (COL9A1, COL9A2, and COL9A3). In contrast, autosomal recessive MED (rMED) appears to result exclusively from mutations in sulphate transporter solute carrier family 26 (SLC26A2). The diagnosis of PSACH and MED can be difficult for the nonexpert due to various complications and similarities with other related diseases and often mutation analysis is requested to either confirm or exclude the diagnosis. Since 2003, the European Skeletal Dysplasia Network (ESDN) has used an on‐line review system to efficiently diagnose cases referred to the network prior to mutation analysis. In this study, we present the molecular findings in 130 patients referred to ESDN, which includes the identification of novel and recurrent mutations in over 100 patients. Furthermore, this study provides the first indication of the relative contribution of each gene and confirms that they account for the majority of PSACH and MED. Hum Mutat 33:144–157, 2012. © 2011 Wiley Periodicals, Inc.
Target-Specific Effects of Somatostatin-Expressing Interneurons on Neocortical Visual Processing

A diverse array of interneuron types regulates activity in the mammalian neocortex. Two of the most abundant are the fast-spiking, parvalbumin-positive (PV+) interneurons, which target the axosomatic region of pyramidal cells, and the somatostatin-positive (SOM+) interneurons, which target the dendrites. Recent work has focused on the influence of PV+ and SOM+ interneurons on pyramidal cells. However, the connections among PV+ and SOM+ interneurons are poorly understood and could play an important role in cortical circuitry, since their interactions may alter the net influence on pyramidal cell output. We used an optogenetic approach to investigate the effect of SOM+ interneurons on pyramidal cells and PV+ interneurons during visual stimulation in mouse primary visual cortex. We find that SOM+ interneuron activation suppresses PV+ cell spiking at least twice as potently as pyramidal cell spiking during visual stimulation. This differential effect of SOM+ cell stimulation is detectable even when only two to three SOM+ cells are activated. Importantly, the remaining responses to oriented gratings in PV+ cells are more orientation tuned and temporally modulated, suggesting that SOM+ activity unmasks this tuning by suppressing untuned input. Our results highlight the importance of SOM+ inhibition of PV+ interneurons during sensory processing. This prominent competitive inhibition between interneuron types leads to a reconfiguration of inhibition along the somatodendritic axis of pyramidal cells, and enhances the orientation selectivity of PV+ cells.
Locality sensitive hashing for fast computation of correlational manifold learning based feature space transformations

Manifold learning based techniques have been found to be useful for feature space transformations and semi-supervised learning in speech processing. However, the immense computational requirements in building neighborhood graphs have hindered the application of these techniques to large speech corpora. This paper presents an approach for fast computation of neighborhood graphs in the context of manifold learning. The approach, known as locality sensitive hashing (LSH), has been applied to a discriminative manifold learning based feature space transformation technique that utilizes a cosine-correlation based distance measure. Performance is evaluated first in terms computational savings at a given level of ASR performance. The results demonstrate that LSH provides a factor of 9 reduction in the computational complexity with minimal impact on speech recognition performance. A study is also performed comparing the efficiency of the LSH algorithm presented here and other LSH approaches in identifying nearest neighbors.
WOO: A Scalable and Multi-tenant Platform for Continuous Knowledge Base Synthesis

Search, exploration and social experience on the Web has recently undergone tremendous changes with search engines, web portals and social networks offering a different perspective on information discovery and consumption. This new perspective is aimed at capturing user intents, and providing richer and highly connected experiences. The new battleground revolves around technologies for the ingestion, disambiguation and enrichment of entities from a variety of structured and unstructured data sources - we refer to this process as knowledge base synthesis. This paper presents the design, implementation and production deployment of the Web Of Objects (WOO) system, a Hadoop-based platform tackling such challenges. WOO has been designed and implemented to enable various products in Yahoo! to synthesize knowledge bases (KBs) of entities relevant to their domains. Currently, the implementation of WOO we describe is used by various Yahoo! properties such as Intonow, Yahoo! Local, Yahoo! Events and Yahoo! Search. This paper highlights: (i) challenges that arise in designing, building and operating a platform that handles multi-domain, multi-version, and multi-tenant disambiguation of web-scale knowledge bases (hundreds of millions of entities), (ii) the architecture and technical solutions we devised, and (iii) an evaluation on real-world production datasets.
Race and Obesity in Adolescent Hypertension

By using data collected from school-based screenings, this study reveals unique relationships between body mass and hypertension amongst adolescents of different races and ethnicities. BACKGROUND AND OBJECTIVES: The overall prevalence of essential hypertension in adolescents may be growing. Differences in blood pressure (BP) are well established in adults, but are less clear in adolescents. We hypothesize that the prevalence of hypertension differs by race/ethnicity among adolescents at school-based screenings. METHODS: We performed school-based BP screening in over 20 000 adolescents from 2000 to 2015. Race/ethnicity was self-reported. Height and weight were measured to determine BMI, and BP status was confirmed on 3 occasions to diagnose sustained hypertension according to Fourth Working Group Report criteria. RESULTS: We successfully screened 21 062 adolescents aged 10 to 19 years (mean, 13.8 years). The final prevalence of sustained hypertension in all subjects was 2.7%. Obesity rates were highest among African American (3.1%) and Hispanic (2.7%) adolescents. The highest rate of hypertension was seen in Hispanic (3.1%), followed by African American (2.7%), white (2.6%), and Asian (1.7%) adolescents (P = .019). However, obese white adolescents had the highest prevalence of sustained hypertension (7.4%) compared with obese African American adolescents (4.5%, P < .001). At lower BMI percentiles (<60th percentile), Hispanic adolescents actually had the lowest predicted prevalence of hypertension among the 4 groups. CONCLUSIONS: The prevalence of hypertension varies among different race/ethnicities. Although obesity remains the strongest predictor of early hypertension, the strength of this relationship is intensified in Hispanic and white adolescents, whereas it is lessened in African American adolescents.
Antimicrobial susceptibility profiling and genomic diversity of Acinetobacter baumannii isolates: A study in western Iran

Background and Objective Acinetobacter baumannii is an aerobic non-motile Gram-negative bacterial pathogen that is resistant to most antibiotics. Carbapenems are the most common antibiotics for the treatment of infections caused by this pathogen. Mechanisms of antibiotic-resistance in A. baumannii are mainly mediated by efflux pumps-lactamases. The aim of this study was to determine antibiotic susceptibility, the possibility of existence of OXAs genes and fingerprinting by Pulsed-Field Gel Electrophoresis (PFGE) among clinical isolates of Acinetobacter collected from Kermanshah hospitals. Materials and Methods One hundred and four isolates were collected from patients attending Imam Reza, Taleghani and Imam Khomeini hospitals of Kermanshah (Iran). Isolates were identified by biochemical tests and API 20NE kit. The susceptibility to different antibiotics was assessed with Kirby-Bauer disk diffusion method. PCR was performed for detection of bla OXA-23, bla OXA-24, bla OXA-51 and bla OXA-58 beta-lactamase genes. Clonal relatedness was estimated by PFGE (with the restriction enzyme Apa I) and DNA patterns were analyzed by Gel compare II 6.5 software. Results All isolates showed high-level of resistance to imipenem, meropenem as well as to other antimicrobial agents, while no resistance to polymyxin B, colistin, tigecylcine and minocycline was observed. The bla OXA-23like and bla OXA-24 like were found among 77.9% and 19.2% of the isolates, respectively. All isolates were positive for bla OXA-51, but none produced any amplicon for bla OXA-58. PFGE genotype analysis suggested the existence of eight clones among the 104 strains [A (n = 35), B (n = 29), C (n = 19), D (n = 10), E (n = 4), F (n = 3), G (n = 3), H (n = 1)]. Clone A was the dominant clone in hospital settings particularly infection wards so that the isolates in this group, compared to the other clones, showed higher levels of resistance to antibiotics. Conclusion The bla OXA-51-like and bla OXA-23like were the predominant mechanisms of resistance to imipenem in A. baumannii. A high prevalence of clone A, B and C in different parts of the healthcare system showed that hospitalized patients should be safeguarded to prevent the spread of these clones. Early recognition of the presence of carbapenem-resistant A. baumannii clones is useful for preventing their spread within the hospital environment.
Modeling instrumental conditioning - the behavioral regulation approach

Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high "instrumental response") is reinforced, and that which produces negative effects (low "instrumental response") is weakened. Instrumental conditioning plays a major role in learning, but the content of such learning might be desired (e.g. correct cause-effect association) or undesired (superstitious behavior/beliefs). We apply the (relatively) recent behavioral regulation approach to develop a generic system dynamic model of a "classroom example" of instrumental conditioning. The model captures essential aspects of the theory and it enhances understanding of how desirable learning may be promoted and undesired outcomes restrained during an instrumental conditioning process.
Ranking and averaging independent component analysis by reproducibility (RAICAR)

Independent component analysis (ICA) is a data‐driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient‐based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between‐realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Hum Brain Mapp, 2008. © 2007 Wiley‐Liss, Inc.
A Systematic Review of the Efficacy and Safety Experience Reported for Sorafenib in Advanced Renal Cell Carcinoma (RCC) in the Post-Approval Setting

Background Sorafenib was FDA approved in 2005 for treatment of renal cell carcinoma (RCC) based on the results of the pivotal phase 3 clinical trial, TARGET (Treatment Approaches in Renal Cancer Global Evaluation Trial). Since that time, numerous clinical studies have been undertaken that substantially broaden our knowledge of the use of sorafenib for this indication. Methods We systematically reviewed PubMed, Web of Science, Embase, Cochrane Library, and www.clinicaltrials. gov for prospective clinical studies using single agent sorafenib in RCC and published since 2005. Primary endpoints of interest were progression-free survival (PFS) and safety. PROSPERO International prospective register of systematic reviews #CRD42014010765. Results We identified 30 studies in which 2182 patients were treated with sorafenib, including 1575 patients who participated in randomized controlled phase 3 trials. In these trials, sorafenib was administered as first-, second- or third-line treatment. Heterogeneity among trial designs and reporting of data precluded statistical comparisons among trials or with TARGET. The PFS appeared shorter in second- vs. first-line treatment, consistent with the more advanced tumor status in the second-line setting. In some trials, incidences of grade 3/4 hypertension or hand-foot skin reaction (HFSR) were more than double that seen in TARGET (4% and 6%, respectively). These variances may be attributable to increased recognition of HFSR, or potentially differences in dose adjustments, that could be consequences of increased familiarity with sorafenib usage. Several small studies enrolled exclusively Asian patients. These studies reported notably longer PFS than was observed in TARGET. However, no obvious corresponding differences in disease control rate and overall survival were seen. Conclusions Collectively, more recent experiences using sorafenib in RCC are consistent with results reported for TARGET with no marked changes of response endpoints or new safety signals observed.
Interactive spacetime control of deformable objects

Creating motions of objects or characters that are physically plausible and follow an animator's intent is a key task in computer animation. The spacetime constraints paradigm is a valuable approach to this problem, but it suffers from high computational costs. Based on spacetime constraints, we propose a framework for controlling the motion of deformable objects that offers interactive response times. This is achieved by a model reduction of the underlying variational problem, which combines dimension reduction, multipoint linearization, and decoupling of ODEs. After a preprocess, the cost for creating or editing a motion is reduced to solving a number of one-dimensional spacetime problems, whose solutions are the wiggly splines introduced by Kass and Anderson [2008]. We achieve interactive response times through a new fast and robust numerical scheme for solving the one-dimensional problems that is based on a closed-form representation of the wiggly splines.
Efficient processor support for DRFx, a memory model with exceptions

A longstanding challenge of shared-memory concurrency is to provide a memory model that allows for efficient implementation while providing strong and simple guarantees to programmers. The C++0x and Java memory models admit a wide variety of compiler and hardwareoptimizations and provide sequentially consistent (SC) semantics for data-race-free programs. However, they either do not provide any semantics (C++0x) or provide a hard-to-understand semantics (Java) for racy programs, compromising the safety and debuggability of such programs. In earlier work we proposed the DRFx memory model, which addresses this problem by dynamically detecting potential violations of SC due to the interaction of compiler or hardware optimizations with data races and halting execution upon detection. In this paper, we present a detailed micro-architecture design for supporting the DRFx memory model, formalize the design and prove its correctness, and evaluate the design using a hardware simulator. We describe a set of DRFx-compliant complexity-effective optimizations which allow us to attain performance close to that of TSO (Total Store Model) and DRF0 while providing strong guarantees for all programs.
Sinonasal Microbiome Sampling: A Comparison of Techniques

Background The role of the sino-nasal microbiome in CRS remains unclear. We hypothesized that the bacteria within mucosal-associated biofilms may be different from the more superficial-lying, free-floating bacteria in the sinuses and that this may impact on the microbiome results obtained. This study investigates whether there is a significant difference in the microbiota of a sinonasal mucosal tissue sample versus a swab sample. Methods Cross-sectional study with paired design. Mucosal biopsy and swab samples were obtained intra-operatively from the ethmoid sinuses of 6 patients with CRS. Extracted DNA was sequenced on a Roche-454 sequencer using 16S-rRNA gene targeted primers. Data were analyzed using QIIME 1.8 software package. Results At a maximum subsampling depth of 1,100 reads, the mean observed species richness was 33.3 species (30.6 for swab, versus 36 for mucosa; p > 0.05). There was no significant difference in phylogenetic and non-phylogenetic alpha diversity metrics (Faith’s PD_Whole_Tree and Shannon’s index) between the two sampling methods (p > 0.05). The type of sample also had no significant effect on phylogenetic and non-phylogenetic beta diversity metrics (Unifrac and Bray-Curtis; p > 0.05). Conclusion We observed no significant difference between the microbiota of mucosal tissue and swab samples. This suggests that less invasive swab samples are representative of the sinonasal mucosa microbiome and can be used for future sinonasal microbiome studies.
On the NP-hardness of bounded distance decoding of Reed-Solomon codes

Guruswami and Vardy (IEEE Trans. Inf. Theory, 2005) show that given a Reed-Solomon code over a finite field F, of length n and dimension k, and given a target vector v ε Fn, it is NP-hard to decide if there is a codeword that disagrees with v on at most n - k - 1 coordinates. Understanding the complexity of this Bounded Distance Decoding problem as the amount of error in the target decreases is an important open problem in the study of Reed-Solomon codes. In this work, we extend the result of Guruswami and Vardy by proving that it is NP-hard to decide the existence of a codeword that disagrees with v on n - k - 2, and on n - k - 3 coordinates. No other NP-hardness results were known before for an amount of error <; n - k - 1. The core of our proofs is showing the NP-hardness of a parameterized generalization of the Subset-Sum problem to higher degrees (called Moments Subset-Sum) that may be of independent interest.
The Test Authors Speak: Reporting on an Author Survey of the Leading Tests Used in Gifted Assessment

The conceptualization of giftedness continues to be a widely debated topic within the field. Recently, there has been a shift from a psychometric view of giftedness to inclusion of conative and contextual factors. How one defines and conceptualizes “gifted” drives assessment and identification practices. Conceptualization also guides the development of measures used in gifted assessment; however, the perceptions of giftedness held by test authors have not yet been explored empirically. The aim of this study was to investigate the perspectives of giftedness held by authors of the leading tests in gifted assessment. Test authors provided their views on topics, including gifted identification, use of cutoff scores, and how their tests serve the needs of this unique population. Findings indicate that there are varying opinions and views of giftedness, although most test authors in the sample embrace a multi-dimensional approach to gifted assessment. This article includes a discussion of clinical implications and future directions.
Anticipating Discussion Activity on Community Forums

Attention economics is a vital component of the Social Web, where the sheer magnitude and rate at which social data is published forces web users to decide on what content to focus their attention on. By predicting popular posts on the Social Web, that contain lengthy discussions and debates, analysts can focus their attention more effectively on content that is deemed more influential. In this paper we present a two-step approach to anticipate discussions in community forums by a) identifying seed posts - i.e., posts that generate discussions, and b) predicting the length of these discussions. We explore the effectiveness of a range of features in anticipating discussions such as user and content features, and present 'focus' features that capture the topical concentration of a user. For identifying seed posts we show that content features are better predictors than user features, while achieving an F1 value of 0.792 when using all features. For predicting discussion activity we find a positive correlation between the focus of the user and discussion volumes, and achieve an nDCG@1 value of 0.89 when predicting using user features.