bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian active learning for optimization and uncertainty quantification in protein docking
Authors: Cao Yue , Shen Yang 
Published: February 2019

AbstractMotivationAb initio protein docking represents a major challenge for optimizing a noisy and costly “black box”-like function in a high-dimensional space. Despite progress in this field, there is no docking method available for rigorous uncertainty quantification (UQ) of its solution quality (e.g. interface RMSD or iRMSD).ResultsWe introduce a novel algorithm, Bayesian Active Learning (BAL), for optimization and UQof such black-box functions and flexible protein docking. BAL directly models the posterior distribution of the global optimum (or native structures for protein docking) with active sampling and posterior estimation iteratively feeding each other. Furthermore, we use complex normal modes to represent a homogeneous Euclidean conformation space suitable for high-dimension optimization and construct funnel-like energy models for encounter complexes. Over a protein docking benchmark set and a CAPRI set including homology docking, we establish that BAL significantly improve against both starting points by rigid docking and refinements by particle swarm optimization, providing for one third targets a top-3 near-native prediction. BAL also generates tight confidence intervals with half range around 25% of iRMSD and confidence level at 85%. Its estimated probability of a prediction being native or not achieves binary classification AUROC at 0.93 and AUPRC over 0.60 (compared to 0.14 by chance); and also found to help ranking predictions. To the best of knowledge, this study represents the first uncertainty quantification solution for protein docking, with theoretical rigor and comprehensive assessment.AvailabilitySource codes are available at https://github.com/Shen-Lab/BAL.Contactyshen@tamu.eduSupplementary informationhttps://github.com/Shen-Lab/BAL/tree/master/Paper_SI/
SPDI: Data Model for Variants and Applications at NCBI
Authors: Holmes J. Bradley , Moyer Eric , Phan Lon , Maglott Donna , Kattman Brandi L. 
Published: February 2019

AbstractMotivationNormalizing diverse representations of sequence variants is critical to the elucidation of the genetic basis of disease and biological function. NCBI has long wrestled with integrating data from multiple submitters to build databases such as dbSNP and ClinVar. Inconsistent representation of variants among variant callers, local databases, and tools results in discrepancies and duplications that complicate analysis. Current tools are not robust enough to manage variants in different formats and different reference sequence coordinates.ResultsThe SPDI (pronounced “speedy”) data model defines variants as a sequence of 4 operations: start at the boundary before the first position in the sequence S, advance P positions, delete D positions, then insert the sequence in the string I, giving the data model its name, SPDI. The SPDI model can thus be applied to both nucleotide and protein variants, but the services discussed here are limited to nucleotide. Current services convert representations between HGVS, VCF, and SPDI and provide two forms of normalization. The first, based on the NCBI Variant Overprecision Correction Algorithm, returns a unique, normalized representation termed the “Contextual Allele” for any input. The SPDI name, with its four operations, defines exactly the reference subsequence potentially affected by the variant, even in low complexity regions such as homopolymer and dinucleotide sequence repeats. The second level of normalization depends on an alignment dataset (ADS). SPDI services perform remapping (AKA lift-over) of variants from the input reference sequence to return a list of all equivalent Contextual Alleles based on the transcript or genomic sequences that were aligned. One of these contextual alleles is selected to represent all, usually that based on the latest genomic assembly such as GRCh38 and is designated as the unique “Canonical Allele”. ADS includes alignments between non-assembly RefSeq sequences (prefixed NM, NR, NG), as well inter- and intra-assembly-associated genomic sequences (NCs, NTs and NWs) and this allow for robust remapping and normalization of variants across sequences and assembly versions.Availability and implementationThe SPDI services are available for open access at: https://api.ncbi.nlm.nih.gov/variation/v0/Contactholmesbr@ncbi.nlm.nih.gov
Deep Brain Stimulation of the Ventromedial Prefrontal Cortex Disrupts Consolidation of Fear Memories
Authors: Tan Shawn Zheng Kai , Poon Chi Him , Chan Ying-Shing , Lim Lee Wei 
Published: February 2019

ABSTRACTAnxiety disorders pose one of the biggest threats to mental health worldwide, yet current therapeutics have been mostly ineffective due to issues with relapse, efficacy, and toxicit. Deep brain stimulation (DBS) is a promising therapy for treatment-resistant psychiatric disorders including anxiety, but very little is known about the effects of DBS on fear memories. In this study, we used a modified plus-maze discriminative and showed that DBS of the ventromedial prefrontal cortex (vmPFC) was able to disrupt consolidation, but not acquisition or retrieval of fear memories. We validated these results using a standard tone-footshock fear conditioning paradigm. We further demonstrated short-term changes in dopaminergic receptor and c-Fos expression in the ventral hippocampus (vHPC) and established a partial casual role of dopamine 2 receptors in this effect. Lastly, we showed changes in neurotransmitter levels in the vHPC. This study highlights the potential therapeutic effect of vmPFC DBS to treat anxiety disorders.
Time Series Experiment Design Under One-Shot Sampling: The Importance of Condition Diversity
Authors: Kang Xiaohan , Hajek Bruce , Wu Faqiang , Hanzawa Yoshie 
Published: February 2019

AbstractMany biological data sets are prepared using one-shot sampling, in which each individual organism provides only one sample. Time series therefore do not follow trajectories of individuals over time. However, samples collected at different times from individuals grown/raised under the same conditions share the same perturbations of the biological processes, and hence behave as surrogates for multiple samples from a single individual at different times. This implies the importance of growing/raising individuals under multiple conditions if one-shot sampling is used. This paper models the condition effect explicitly by correlated perturbations in the variations driving the expression dynamics, quantifies the performance of the generalized likelihood-ratio test for network structure, and illustrates the difficulty in network reconstruction under one-shot sampling when the condition effect is absent.
Neuronal activity and learning in local cortical networks are modulated by the action-perception state
Authors: Engelhard Ben , Darshan Ran , Ozeri-Engelhard Nofar , Israel Zvi , Werner-Reiss Uri , Hansel David , Bergman Hagai , Vaadia Eilon 
Published: February 2019

SummaryDuring sensorimotor learning, neuronal networks change to optimize the associations between action and perception. In this study, we examine how the brain harnesses neuronal patterns that correspond to the current action-perception state during learning. To this end, we recorded activity from motor cortex while monkeys either performed a familiar motor task (movement-state) or learned to control the firing rate of a target neuron using a brain-machine interface (BMI-state). Before learning, monkeys were placed in an observation-state, where no action was required. We found that neuronal patterns during the BMI-state were markedly different from the movement-state patterns. BMI-state patterns were initially similar to those in the observation-state and evolved to produce an increase in the firing rate of the target neuron. The overall activity of the non-target neurons remained similar after learning, suggesting that excitatory-inhibitory balance was maintained. Indeed, a novel neural-level reinforcement-learning network model operating in a chaotic regime of balanced excitation and inhibition predicts our results in detail. We conclude that during BMI learning, the brain can adapt patterns corresponding to the current action-perception state to gain rewards. Moreover, our results show that we can predict activity changes that occur during learning based on the pre-learning activity. This new finding may serve as a key step toward clinical brain-machine interface applications to modify impaired brain activity.
Transposon-mediated, cell type-specific transcription factor recording in the mouse brain
Authors: Cammack Alexander J. , Moudgil Arnav , Lagunas Tomas , Vasek Michael J. , Shabsovich Mark , He June , Chen Xuhua , Wilkinson Michael N. , Miller Timothy M. , Mitra Robi D. , Dougherty Joseph D. 
Published: February 2019

AbstractTranscription factors (TFs) play a central role in the regulation of gene expression, controlling everything from cell fate decisions to activity dependent gene expression. However, widely-used methods for TF profiling in vivo (e.g. ChIP-seq) yield only an aggregated picture of TF binding across all cell types present within the harvested tissue; thus, it is challenging or impossible to determine how the same TF might bind different portions of the genome in different cell types, or even to identify its binding events at all in rare cell types in a complex tissue such as the brain. Here we present a versatile methodology, FLEX Calling Cards, for the mapping of TF occupancy in specific cell types from heterogenous tissues. In this method, the TF of interest is fused to a hyperactive piggyBac transposase (hypPB), and this bipartite gene is delivered, along with donor transposons, to mouse tissue via a Cre-dependent adeno-associated virus (AAV). The fusion protein is expressed in Cre-expressing cells where it inserts transposon “Calling Cards” near to TF binding sites. These transposons permanently mark TF binding events and can be mapped using high-throughput sequencing. Alternatively, unfused hypPB interacts with and records the binding of the super enhancer (SE)-associated bromodomain protein, Brd4. To demonstrate the FLEX Calling Card method, we first show that donor transposon and transposase constructs can be efficiently delivered to the postnatal day 1 (P1) mouse brain with AAV and that insertion profiles report TF occupancy. Then, using a Cre-dependent hypPB virus, we show utility of this tool in defining cell type-specific TF profiles in multiple cell types of the brain. This approach will enable important cell type-specific studies of TF-mediated gene regulation in the brain and will provide valuable insights into brain development, homeostasis, and disease.
Imaging artefacts of artificial diving waves in reverse time migration: cause analysis in the angle domain and an effective removal strategy
Authors: Liu Shaoyong , Yan Zhe , Gu Hanming , Tang Yongjie , Liu Chuncheng 
Published: February 2019

ABSTRACTIn areas with strong velocity gradients, traditional reverse time migration based on cross‐correlation imaging condition not only produces low‐frequency noise but also generates diving wave artefacts. The artefacts caused by diving waves have no typical low‐frequency characteristics and cannot be eliminated by simple high‐pass filtering approaches. We apply the wave‐field decomposition imaging condition to analyse the causes of false images in reverse time migration by decomposing the full wave‐field into up‐going and down‐going components in the angle domain. We find that artificial diving wave imaging artefacts, which are generated by the cross‐correlation between the up‐going source and down‐going receiver wave‐fields in areas with strong velocity gradients, arise at large angles. We propose an efficient strategy by means of the wavelength‐dependent smoothing operator to eliminate artefacts from artificial diving waves in reverse time migration. Specifically, the proposed method provides more reasonable down‐going wave‐fields in areas with sharp velocity constructs by considering the factor of varying seismic wavelengths during wave propagation, and the artificial components of diving waves are eliminated in a straightforward manner. Meanwhile, the other wave‐field components that contribute to true subsurface images are minimally affected. Benefiting from a smoothed velocity, the proposed method can be adapted to the traditional reverse time migration imaging frame, which reveals significant implementation potential for the seismic exploration industry. A salt model is designed and included to demonstrate the effectiveness of our approach.
Development of a diabetes‐related nutrition knowledge questionnaire for individuals with type 2 diabetes mellitus in Singapore
Authors: Han Chad Y. , Zheng Xiaomei , Lee Lin F. , Chan Cherie G.B. , Lee Yi Q. , Zailani Nani A. , Ng Karin , Bhaskaran Kalpana 
Published: February 2019

AimDiabetes‐related nutrition knowledge (DRNK) is essential for the self‐care of patients with type 2 diabetes mellitus (T2DM). A specific tool measuring DRNK can help us to understand awareness levels and tailor structured nutrition education programs. Our study aimed to develop a questionnaire to assess DRNK for individuals with T2DM in Singapore.MethodsAn expert panel was formed to consolidate in‐depth, culturally suitable, and current information on DRNK. A literature review of diabetes self‐care knowledge questionnaires was performed to outline the scope of the questionnaire and generate a question pool. User friendliness was tested in the first draft of the questionnaire (n = 21). Then, a second draft was tested for item difficulty, discrimination index, and internal consistency (n = 62). The final draft was examined for construct validity and test–retest reliability (n = 100).ResultsThe final questionnaire (four sections: 27 questions) was found to be consistent and reliable. The item difficulty scores of the selected questions ranged from difficult to desirable (2–85). There was fair to good internal consistency (Cronbach's alpha: 0.66, 0.79, 0.56, and 0.78 for Sections 1, 2, 3 and 4, respectively) and construct validity (independent t‐test: P < 0.001). Questions in the final questionnaire had an average discrimination index of 0.3 (reasonably good). The questionnaire was revealed to have good test–retest reliability (intraclass correlation: 0.82–0.84).ConclusionsThe DRNK questionnaire is a valid and reliable measure to complement assessment tools measuring self‐efficacy/behaviour in individuals with T2DM living in Singapore.
Quantification of the activity of detoxifying enzymes in terrestrial invertebrates: Optimization, evaluation and use of in vitro and ex vivo methods
Authors: Pedersen Kathrine E. , Fredensborg Brian L. , Jensen Annette B. , Cedergreen Nina 
Published: February 2019

Abstract

The negative effects of pesticides on beneficial terrestrial invertebrates have received much attention, and in this context quantification of the activity of metabolic enzymes provides an important tool. Unfortunately, current methodologies are limited in their use.

In this study, the grain beetle, Tenebrio molitor was used to illustrate why in vitro methods are ineffective to quantify metabolic enzymes in some insects. It was further used to optimize an ex vivo assay that can replace in vitro methods when these are ineffective. The ex vivo method can quantify metabolic enzymatic activities of cytochrome P450 mixed function oxidases (CYPs), general esterases (EST) and glutathione S‐transferases (GST).

In detail we show, that T. molitor produces inhibitory and/or degrading agents, which are released during tissue homogenization. As these agents inhibit the in vitro CYP activity of rat liver microsomes we suggest, that they are also responsible for the lack of in vitro CYP activity of T. molitor. We tested the effectiveness of broad‐spectrum protease inhibitors as protective agents and found, that they were only effective in concentrations that also interfered directly with the activity of CYP enzymes. As an alternative to in vitro measurements, we optimized an ex vivo method for quantification of CYP, EST and GST on individual gut systems of T. molitor. Our ex vivo method advances previous ex vivo methods, by allowing quantification of three major enzyme families, all in a single individual, and by exploiting real‐time kinetic measurements of the enzymatically produced product.

Subsequently, our method was successfully tested for its use on three different life stages: larvae, pupae, and adult insects from T. molitor and Apis mellifera. The method shows promise for expansion to other species and potentially other enzyme families and/or substrates.
Activation of MT2 receptor ameliorates dendritic abnormalities in Alzheimer’s disease via C/EBPα/miR‐125b pathway
Authors: Tang Hui , Ma Mei , Wu Ying , Deng Man‐Fei , Hu Fan , Almansoub Hasan.a.m.m. , Huang He‐Zhou , Wang Ding‐Qi , Zhou Lan‐Ting , Wei Na , Man Hengye , Lu Youming , Liu Dan , Zhu Ling‐Qiang 
Published: February 2019

AbstractImpairments of dendritic trees and spines have been found in many neurodegenerative diseases, including Alzheimer's disease (AD), in which the deficits of melatonin signal pathway were reported. Melatonin receptor 2 (MT2) is widely expressed in the hippocampus and mediates the biological functions of melatonin. It is known that melatonin application is protective to dendritic abnormalities in AD. However, whether MT2 is involved in the neuroprotection and the underlying mechanisms are not clear. Here, we first found that MT2 is dramatically reduced in the dendritic compartment upon the insult of oligomer Aβ. MT2 activation prevented the Aβ‐induced disruption of dendritic complexity and spine. Importantly, activation of MT2 decreased cAMP, which in turn inactivated transcriptional factor CCAAT/enhancer‐binding protein α(C/EBPα) to suppress miR‐125b expression and elevate the expression of its target, GluN2A. In addition, miR‐125b mimics fully blocked the protective effects of MT2 activation on dendritic trees and spines. Finally, injection of a lentivirus containing a miR‐125b sponge into the hippocampus of APP/PS1 mice effectively rescued the dendritic abnormalities and learning/memory impairments. Our data demonstrated that the cAMP‐C/EBPα/miR‐125b/GluN2A signaling pathway is important to the neuroprotective effects of MT2 activation in Aβ‐induced dendritic injuries and learning/memory disorders, providing a novel therapeutic target for the treatment of AD synaptopathy.
Comparison of the metabolomic profiles of irritable bowel syndrome patients with ulcerative colitis patients and healthy controls: new insights into pathophysiology and potential biomarkers
Authors: Keshteli Ammar Hassanzadeh , Madsen Karen L. , Mandal Rupasri , Boeckxstaens Guy E. , Bercik Premysl , De Palma Giada , Reed David E. , Wishart David , Vanner Stephen , Dieleman Levinus A. 
Published: February 2019

SummaryBackgroundEvaluation of the metabolomic profile of patients with irritable bowel syndrome offers an opportunity to identify novel pathophysiological targets and biomarkers that could discriminate this disorder from related conditions.AimTo identify potential urinary biomarkers that discriminate irritable bowel syndrome patients from ulcerative colitis patients in remission and healthy controls and to explore the pathophysiology of irritable bowel syndrome using a metabolomic approach.MethodsUrine samples were collected from 39 irritable bowel syndrome patients, 53 ulcerative colitis patients in clinical remission and 21 healthy controls. Urinary metabolites were identified and quantified using direct infusion/liquid chromatography tandem mass spectrometry and gas‐chromatography mass spectrometry.ResultsPatients with irritable bowel syndrome had a unique urinary metabolome that could separate them from ulcerative colitis patients with an area under the curve = 0.99 (95% confidence interval 0.95‐1.00). The most important metabolites for this separation were a group of amino acids and organic acids. In addition, subjects with irritable bowel syndrome could be discriminated from healthy controls using their metabolic fingerprints. Irritable bowel syndrome patients had lower urinary Phosphatidyl choline acyl‐alkyl C38:6, dopamine and p‐hydroxybenzoic acid than healthy controls. Levels of some urinary metabolites including histamine correlated significantly with irritable bowel syndrome symptom severity scores.ConclusionsIrritable bowel syndrome patients have a unique urinary metabolomic profile compared to ulcerative colitis patients in clinical remission or healthy subjects. These data suggest that metabolomic profiling may provide important insights into pathophysiology and testable biomarkers to discriminate irritable bowel syndrome from other disorders that can mimic this condition and can be used to assess its severity and identify potential novel pathophysiological pathways.
The role of echocardiographic parameters in predicting survival of patients with lung diseases referred for lung transplantation
Authors: Nowak Jolanta , Hudzik Bartosz , Niedziela Jacek T. , Rozentryt Piotr , Ochman Marek , Przybyłowski Piotr , Zembala Marian , Gąsior Mariusz 
Published: February 2019

AbstractIntroductionIdiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) show poor prognosis. The importance of left (LV) and right (RV) ventricular morphology and function in patients with end‐stage lung diseases referred for lung transplantation (LT) is not well established.ObjectivesTo assess whether LV and RV echocardiographic parameters influence survival of patients with IPF, COPD and other interstitial lung diseases (ILD) awaiting LT.MethodsIn 65 patients (20 patients with COPD, 37 with IPF and 8 with other ILD), we performed transthoracic echocardiography and right heart catheterization. Echocardiographic parameters were assessed with regard to 1‐year all‐cause mortality.ResultsThe mortality rate was higher in patients with smaller dimensions of LV end‐systolic (LVESD) and end‐diastolic (LVEDD) diameter (HR 3.03, 95% CI 1.16‐7.69, P = .023; and HR 2.9, 95% CI 1.16‐7.14, P = .022; respectively), higher RV‐to‐LV (RV/LV‐4CH) ratio (HR 7.6, 95% CI 1.6‐29.5, P = .009) and RV proximal outflow tract (RVOT‐PLAX) dilatation (HR 2.69, 95% CI 1.22‐5.96, P = .015). These associations were independent of age, gender, body mass index, VC, FEV1% and pulmonary diagnosis. The subanalysis of IPF patients demonstrated that the smaller LVESD and LVEDD increased mortality rate (HR 15.0, 95% CI 2.87‐89.72, P = .003; HR 4.95, 95% CI 1.5‐15.5, P = .006; respectively). No such associations were found in the COPD patients.ConclusionLV echocardiographic parameters (LVESD or LVEDD) are useful in predicting survival in patients with end‐stage lung diseases, mainly in IPF patients awaiting LT. Other parameters (RV/LV‐4CH and RVOT‐PLAX dilatation) may also influence survival.