Miracle-dz/UniFAR-FTUs huggingface dataset:
Informed Genome‐Wide Association Analysis With Family History As a Secondary Phenotype Identifies Novel Loci of Lung Cancer

Lung cancer is the leading cause of cancer death worldwide. Although several genetic variants associated with lung cancer have been identified in the past, stringent selection criteria of genome‐wide association studies (GWAS) can lead to missed variants. The objective of this study was to uncover missed variants by using the known association between lung cancer and first‐degree family history of lung cancer to enrich the variant prioritization for lung cancer susceptibility regions. In this two‐stage GWAS study, we first selected a list of variants associated with both lung cancer and family history of lung cancer in four GWAS (3,953 cases, 4,730 controls), then replicated our findings for 30 variants in a meta‐analysis of four additional studies (7,510 cases, 7,476 controls). The top ranked genetic variant rs12415204 in chr10q23.33 encoding FFAR4 in the Discovery set was validated in the Replication set with an overall OR of 1.09 (95% CI = 1.04, 1.14, P = 1.63 × 10−4). When combining the two stages of the study, the strongest association was found in rs1158970 at Ch4p15.2 encoding KCNIP4 with an OR of 0.89 (95% CI = 0.85, 0.94, P = 9.64 × 10−6). We performed a stratified analysis of rs12415204 and rs1158970 across all eight studies by age, gender, smoking status, and histology, and found consistent results across strata. Four of the 30 replicated variants act as expression quantitative trait loci (eQTL) sites in 1,111 nontumor lung tissues and meet the genome‐wide 10% FDR threshold.
Curvature-Aware Regularization on Riemannian Submanifolds

One fundamental assumption in object recognition as well as in other computer vision and pattern recognition problems is that the data generation process lies on a manifold and that it respects the intrinsic geometry of the manifold. This assumption is held in several successful algorithms for diffusion and regularization, in particular, in graph-Laplacian-based algorithms. We claim that the performance of existing algorithms can be improved if we additionally account for how the manifold is embedded within the ambient space, i.e., if we consider the extrinsic geometry of the manifold. We present a procedure for characterizing the extrinsic (as well as intrinsic) curvature of a manifold M which is described by a sampled point cloud in a high-dimensional Euclidean space. Once estimated, we use this characterization in general diffusion and regularization on M, and form a new regularizer on a point cloud. The resulting re-weighted graph Laplacian demonstrates superior performance over classical graph Laplacian in semi-supervised learning and spectral clustering.
Identification of an alternative transcript of ABCA1 gene in different human cell types.

We have observed two ABCA1 gene transcripts in human skin fibroblasts. The RT-PCR amplification of the exon 3-exon 8 region generated a normal fragment (740 bp) and an abnormal fragment (600 bp) in a ratio ranging from 3:1 to 8/9:1. These two transcripts were present in other cells such as leukemia T-cells, endothelial and smooth muscle cells as well human hepatoma cells (HepG2). Restriction enzyme analysis and sequencing indicated that in the abnormal fragment exon 3 was followed by exon 5. The complete skipping of exon 4 leads to a premature stop and a predicted translation product of 74 amino acids. The ratio between the normal and alternative transcript is not affected by variation in ABCA1 gene expression induced by incubating cells in serum-free medium and in the presence of cholesterol. It is possible that this alternative splicing represents as mechanism that regulates the ABCA1 content in tissues.
Evaluation of the antidiabetic and antilipaemic activities of the hydroalcoholic extract of phoenix dactylifera palm leaves and its fractions in alloxan-induced diabetic rats.

BACKGROUND The antidiabetic and antilipaemic effects of Phoenix dactylifera leaf extract (PDE) and its fractions were investigated in various rat models. METHODS Diabetes was induced in male Wistar rats by alloxan monohydrate. Diabetic animals were randomly divided into 8 groups (1 diabetic control and 7 treated groups). Diabetic control animals received saline (5 mL/kg) orally, whereas the treatment groups received different doses of PDE (100, 200, and 400 mg/kg), PDE fractions (50, 100, and 200 mg/kg), or glibenclamide (4 mg/kg) orally once a day for 14 days. Blood was withdrawn for glucose determination on the 1(st), 6(th), 10(th), and 14(th) days. The rats were fasted overnight and then sacrificed on the 14(th) day; blood was collected for biochemical evaluation, including the levels of blood glucose, plasma insulin, serum triglyceride, and cholesterol. RESULTS Subacute administration of PDE or its fractions in alloxan-induced diabetic rats significantly reduced blood glucose (P < 0.01). Water intake, serum triglyceride, and cholesterol also decreased in treated animals compared with the control group (P < 0.01). Plasma insulin level increased in the treated groups relative to the control group (P < 0.01). CONCLUSION The results suggested that PDE exhibits antidiabetic and antilipaemic effects in alloxan-induced diabetic rats.
Music Preferences With Hearing Aids: Effects of Signal Properties, Compression Settings, and Listener Characteristics

Objectives: Current knowledge of how to design and fit hearing aids to optimize music listening is limited. Many hearing-aid users listen to recorded music, which often undergoes compression limiting (CL) in the music industry. Therefore, hearing-aid users may experience twofold effects of compression when listening to recorded music: music-industry CL and hearing-aid wide dynamic-range compression (WDRC). The goal of this study was to examine the roles of input-signal properties, hearing-aid processing, and individual variability in the perception of recorded music, with a focus on the effects of dynamic-range compression. Design: A group of 18 experienced hearing-aid users made paired-comparison preference judgments for classical and rock music samples using simulated hearing aids. Music samples were either unprocessed before hearing-aid input or had different levels of music-industry CL. Hearing-aid conditions included linear gain and individually fitted WDRC. Combinations of four WDRC parameters were included: fast release time (50 msec), slow release time (1,000 msec), three channels, and 18 channels. Listeners also completed several psychophysical tasks. Results: Acoustic analyses showed that CL and WDRC reduced temporal envelope contrasts, changed amplitude distributions across the acoustic spectrum, and smoothed the peaks of the modulation spectrum. Listener judgments revealed that fast WDRC was least preferred for both genres of music. For classical music, linear processing and slow WDRC were equally preferred, and the main effect of number of channels was not significant. For rock music, linear processing was preferred over slow WDRC, and three channels were preferred to 18 channels. Heavy CL was least preferred for classical music, but the amount of CL did not change the patterns of WDRC preferences for either genre. Auditory filter bandwidth as estimated from psychophysical tuning curves was associated with variability in listeners’ preferences for classical music. Conclusions: Fast, multichannel WDRC often leads to poor music quality, whereas linear processing or slow WDRC are generally preferred. Furthermore, the effect of WDRC is more important for music preferences than music-industry CL applied to signals before the hearing-aid input stage. Variability in hearing-aid users’ perceptions of music quality may be partially explained by frequency resolution abilities.
A Study of Fourth-Grade Reading Vocabulary of Native Spanish-Speaking Children

were selected and presented individually to each of 84 native Spanishspeaking fourth-grade pupils. The child was asked to pronounce each word and to explain its meaning. If he was unable to explain its meaning, he was asked to use it in a sentence. His responses were recorded in writing, but, since the investigator was not a trained phonetician, no attempt was made to make a phonetic transcription.
Towards Robust Chemical Recognition with TaggerOne at the BioCreative V . 5 CEMP Task

We describe our submissions to the BioCreative V.5 CEMP task for chemical named entity recognition in patents. We experimented with improving the robustness of the predictions made by TaggerOne ± a biomedical named entity recognition system intended to be generic to any entity type ± through three methods. First, we improve the feature representation for out-of-vocabulary words with Brown clusters. Second, we improved the generalization of the model under cross-domain shifts with adversarial training. Third, we apply an ensemble approach. We find all three approaches to improve performance. Our highest performance was 0.8847 F-score. TaggerOne is publicly available at https://www.ncbi. nlm.nih. gov/bionlp/tools/taggerone/
Effect of Vitamin D3 Supplementation on Respiratory Tract Infections in Healthy Individuals: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Objective Vitamin D supplementation may be a simple preventive measure against respiratory tract infections (RTIs) but evidence from randomized controlled trials is inconclusive. We aimed to systematically summarize results from interventions studying the protective effect of vitamin D supplementation on clinical and laboratory confirmed RTIs in healthy adults and children. Methods Medline, EMBASE, CENTRAL, and CINAHL were screened from inception until present (last updated in January 2016) completed by a search of the grey literature, clinical trial registers and conference abstracts. We included randomized trials comparing vitamin D versus placebo or no treatment. Two independent reviewers were responsible for study selection and data extraction. Cochrane’s risk of bias tool and the GRADE approach were used for quality assessment. Estimates were pooled with random-effects models. Heterogeneity was explored by sub-group and meta-regression analyses. Results Of 2627 original hits, 15 trials including 7053 individuals were ultimately eligible. All used oral cholecalciferol. We found a 6% risk reduction with vitamin D3 supplementation on clinical RTIs, but the result was not statistically significant (RR 0.94; 95% CI 0.88 to 1.00). Heterogeneity was large (I-square 57%) and overall study quality was low. There were too few studies to reliably assess a potential risk reduction of laboratory confirmed RTI. Evidence was insufficient to demonstrate an association between vitamin D supplementation and risk of clinical RTI in sub-groups with vitamin D deficiency. Conclusions In previously healthy individuals vitamin D supplementation does not reduce the risk of clinical RTIs. However, this conclusion is based on a meta-analysis where the included studies differed with respect to population, baseline vitamin D levels and study length. This needs to be considered when interpreting the results. Future trials should focus on vitamin D deficient individuals and apply more objective and standardized outcome measurements.
A probabilistic graphical model approach to the structure-and-motion problem

We present a means of formulating and solving the well known structure-and-motion problem in computer vision with probabilistic graphical models. We model the unknown camera poses and 3D feature coordinates as well as the observed 2D projections as Gaussian random variables, using sigma point parameterizations to effectively linearize the nonlinear relationships between these variables. Those variables involved in every projection are grouped into a cluster, and we connect the clusters in a cluster graph. Loopy belief propagation is performed over this graph, in an iterative re-initialization and estimation procedure, and we find that our approach shows promise in both simulation and on real-world data. The PGM is easily extendable to include additional parameters or constraints.
Defective biosynthesis of proteolipid protein in pelizaeus‐merzbacher disease

The brain of an 18‐year‐old patient with Pelizaeus‐Merzbacher disease was examined by standard neuropathological and biochemical methods and by immunocytochemical and immunochemical techniques. Analysis revealed a lack of myelin‐specific lipids, but showed a residual immunoreactivity for myelin basic protein, myelin‐associated glycoprotein, and 2,3‐cyclic nucleotide‐3‐phosphodiesterase. Examination by immunocytochemistry and enzyme‐linked immunosorbent assay showed an absence of proteolipid apoprotein (lipophilin). The peripheral nervous system was normal. Pelizaeus‐Merzbacher disease in humans shares many neuropathological and biochemical features with X‐linked mutations in animals, e.g., the jimpy mouse and myelin‐deficient rat. The specificity of this protein deficiency in Pelizaeus‐Merzbacher disease gains additional support from the recent mapping of the lipophilin gene to the human X chromosome.
Functional Properties of AMPA and NMDA Receptors Expressed in Identified Types of Basal Ganglia Neurons

AMPA- and NMDA-type glutamate receptors (AMPARs and NMDARs) mediate excitatory synaptic transmission in the basal ganglia and may contribute to excitotoxic injury. We investigated the functional properties of AMPARs and NMDARs expressed by six main types of basal ganglia neurons in acute rat brain slices (principal neurons and cholinergic interneurons of striatum, GABAergic and dopaminergic neurons of substantia nigra, globus pallidus neurons, and subthalamic nucleus neurons) using fast application of glutamate to nucleated and outside-out membrane patches. AMPARs in different types of basal ganglia neurons were functionally distinct. Those expressed in striatal principal neurons exhibited the slowest gating (desensitization time constant τ = 11.5 msec, 1 mm glutamate, 22°C), whereas those in striatal cholinergic interneurons showed the fastest gating (desensitization time constant τ = 3.6 msec). The lowest Ca2+ permeability of AMPARs was observed in nigral dopaminergic neurons (PCa/PNa = 0.10), whereas the highest Ca2+ permeability was found in subthalamic nucleus neurons (PCa/PNa = 1.17). NMDARs of different types of basal ganglia neurons were less variable in their functional properties; those expressed in nigral dopaminergic neurons exhibited the slowest gating (deactivation time constant of predominant fast component τ1 = 150 msec, 100 μm glutamate), and those of globus pallidus neurons showed the fastest gating (τ1 = 67 msec). The Mg2+ block of NMDARs was similar; the average chord conductance ratiog−60mV/g+40mVwas 0.18–0.22 in 100 μm external Mg2+. Hence, AMPARs expressed in different types of basal ganglia neurons are markedly diverse, whereas NMDARs are less variable in functional properties that are relevant for excitatory synaptic transmission and neuronal vulnerability.
Controlling Anxiety Mediates the Influence of Childhood Adversities on Risky Sexual Behaviors Among Emerging Adults

Relatively little research has assessed the exposure-response relationship of childhood adversities on engaging in risky sexual behaviors. Also, no previous research has examined the interrelationship among childhood adversities, adult anxiety and depressive symptoms, and risky sexual behaviors. This study aimed to investigate their interrelationships. We used data from a multisite survey of emerging adults aged 18 to 29 studying at four universities in Hong Kong between September and December 2015. Structural equation modeling (SEM) was used to examine the pathways from childhood adversities to risky sexual behaviors. Participants who had higher childhood adversity scores reported more severe adult anxiety symptoms (β = 0.20, p = 0.002); and adult anxiety symptoms were associated with significantly more risky sexual behaviors (β = 0.46, p < 0.0001). The model with adult anxiety symptoms as the mediator between childhood adversities and risky sexual behaviors showed good fit (root mean square error of approximation [RMSEA] = 0.04, comparative fit index [CFI] = 0.96, Tucker-Lewis index [TLI] = 0.94 and standardized root mean square residual [SRMSR] = 0.04). However, adult depressive symptoms failed to mediate between childhood adversities and risky sexual behaviors. This study demonstrates the link between childhood adversities and risky sexual behaviors via adult anxiety but not adult depressive symptoms. It is essential to reduce anxious symptoms in dealing with emerging adults who have risky sexual behaviors to prevent sexually transmitted infections (STIs) and unintended pregnancy.
Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities

We consider the input variable selection in complex Bayesian hierarchical models. Our goal is to find a model with the smallest number of input variables having statistically or practically at least the same expected utility as the full model with all the available inputs. A good estimate for the expected utility can be computed using cross-validation predictive densities. In the case of input selection and a large number of input combinations, the computation of the cross-validation predictive densities for each model easily becomes computationally prohibitive. We propose to use the posterior probabilities obtained via variable dimension MCMC methods to find out potentially useful input combinations, for which the final model choice and assessment is done using the expected utilities. Variable dimension MCMC methods visit the models according to their posterior probabilities. As models with negligible probability are probably not visited in a finite time, the computational savings can be considerable compared to going through all possible models. If there is problem of obtaining enough samples in reasonable time to estimate the probabilities of the models well, we propose to use the marginal posterior probabilities of the inputs to estimate their relevance. As illustrative examples we use MLP neural networks and Gaussian processes in one toy problem and in two challenging real world problems. Results show that using posterior probability estimates computed with variable dimension MCMC helps finding useful models. Furthermore, benefits of using expected utilities for input variable selection are that it is less sensitive to prior choices and it provides useful model assessment.
Fostering communication and shared play between mainstream peers and children with autism: approaches, outcomes and experiences

More pupils with autism are now being educated in mainstream settings and inevitably there is increased interest in their interactions with their peers. In this article, Philip Whitaker, of the Educational Psychology Service in Northamptonshire, describes his study of shared play between children with autism and their mainstream peers. The study involved ten youngsters with severe autism, educated in a unit attached to a mainstream school, and a group of volunteer ‘peer tutors’. The children met in weekly interaction sessions designed to promote shared play and communication. The peer tutors were provided with some coaching in interaction techniques and the impact of the intervention was evaluated through analysis of video recordings of play sessions made at the beginning and end of the project. The peer tutors and their parents were also interviewed at the end of the project to explore their experiences. The results Philip Whitaker reports are encouraging. All parents were strongly supportive of their children's participation. All but one of the peer tutors found the experience challenging but rewarding and wanted to continue their involvement beyond the 20-week project. The video evidence revealed that the peer tutors, with relatively limited preparation, were able to engage the youngsters with autism in high and sustained levels of shared play. The frequency of requesting by children with autism increased substantially over the course of the project, although levels of initiation of shared attention remained consistently low. Philip Whitaker concludes his report with a series of suggestions for enhancing the impact of this interesting work.
Jazz: an extensible zoomable user interface graphics toolkit in Java

Abstract : In this paper the authors investigate the use of scene graphs as a general approach for implementing two-dimensional (2D) graphical applications, and in particular Zoomable User Interfaces (ZUIs). Scene graphs are typically found in three-dimensional (3D) graphics packages such as Sun's Java3D and SGI's OpenInventor. They have not been widely adopted by 2D graphical user interface toolkits. To explore the effectiveness of scene graph techniques, the authors have developed Jazz, a general-purpose 2D scene graph toolkit. Jazz is implemented in Java using Java2D, and runs on all platforms that support Java 2. This paper describes Jazz and the lessons we learned using Jazz for ZUIs. It also discusses how 2D scene graphs can be applied to other application areas. (5 figures, 27 refs.)
Multi-Document Relationship Fusion via Constraints on Probabilistic Databases

Abstract : Previous multi-document relationship extraction and fusion research has focused on single relationships. Shifting the focus to multiple relationships allows for the use of mutual constraints to aid extraction. This paper presents a fusion method which uses a probabilistic database model to pick relationships which violate few constraints. This model allows improved performance on constructing corporate succession timelines from multiple documents with respect to a multi-document fusion baseline.
Prediction of Protein-Protein Interactions from Phylogenetic Trees Using Partial Correlation Coefficient

[2] has been proposed as a generalization of the idea of the phylogenetic prole in order to measure the evolutionary distance between proteins more precisely. Both methods basically stem from the assumption that functionally correlated proteins evolve in a correlated manner. In the mirror tree method, the intensity of the correlation between proteins is evaluated by Peason’s correlation coecient based on phylogenetic trees, but it has been pointed out that a number of false positives tend to be introduced in the prediction. This paper presents a new method to predict protein-protein interactions from the evolutionary information by using partial correlation coecien t in order to extract direct interactions rather than indirect interactions between proteins. Our method is successfully tested on its ability to predict physical protein interactions, from the comparison of phylogenetic trees of proteins. Using the dataset containing known interactions, we show that our approach removes false positives to a large extent and improves the specicit y for predicting physical protein-protein interactions. 2 Method
Humanoid robot motion generation for nailing task

In order to exert a large force on the environment, it is effective to apply impulsive force. We describe the motions that perform tasks by applying impulsive force as ldquoimpact motionrdquo. In this research, a nailing task is taken as an example of impact motion. This paper proposes a way to generate impact motions for humanoid robots to exert a large force and the feedback control method for driving a nail robustly. In order to validate the proposed scheme, experiments are carried out using life-sized humanoid robot HRP-2. The motion for nailing task generated by the proposed method is compared with the motion designed heuristically by a human. The driving depth is clearly increased by the proposed method.