bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional and structural characterization of H105Y mutation in MtrR protein ofNeisseria gonorrhoeae
Authors: Sachdev Divya , Kumari Indu , Chopra Madhu , Singh Laishram R. , Saluja Daman 
Published: July 2020

AbstractMtrR is a negative regulator of MtrCDE efflux pump. Various N-Terminal and C-Terminal mutations have been reported in different multidrug resistant clinical isolates ofNeisseria gonorrhoeaeacross the world. Mutations in N-terminal region of MtrR, are known to abrogate its binding with the promoter thereby providing an evidence that this region encodes for DNA binding domain. In contrast, mechanism of action of mutations in C-terminal, known to play a role in protein dimerization and has site for ligand binding, is left unexplored. In the present study, usingin silicoapproach, we observed that H105Y mutation affects the conformation of the protein and its binding with penicillin. Purified, recombinant wild type and mutant MtrR were compared for their binding to promoter region and various antibiotics. Fluorescence spectroscopy, CD spectroscopy and dynamic light scattering assay with wild type and mutant MtrR suggested decreased binding of H105Y MtrR with its promoter without affecting protein dimerization, but due to altered conformation of mutant dimer. Ourin silicoresults also suggest altered conformation of the mutant dimer protein leading to difference in the posture of homodimer formed and hence altered binding with DNA. Mutant protein also showed stronger binding with various antibiotics: penicillin, ceftriaxone and ofloxacin. Binding of drugs also leads to altered conformation of the protein which may lead to its decreased binding with the promoter DNA.ImportanceMutations in MtrR, a transcriptional repressor of MtrCDE efflux pump have been reported in various multi-drug resistantNeisseria gonorrhoeaeacross the world. We identified that a C-terminal mutation H105Y, outside the DNA binding domain of MtrR, decreases the binding of MtrR with its promoter. We identified that the mutation alters the structure of the dimer, as well as enhances the antibiotic binding. We envisage that the altered structure of MtrR affects its DNA binding thereby increasing efflux of antibiotics and increased resistance. These findings could be used as a guide to design novel drugs that should either not bind to MtrR or could surpass the conformational change and decreased DNA binding.
Continuous flexibility analysis of SARS-CoV-2 Spike prefusion structures
Authors: Melero Roberto , Sorzano Carlos Oscar S. , Foster Brent , Vilas José-Luis , Martínez Marta , Marabini Roberto , Ramírez-Aportela Erney , Sanchez-Garcia Ruben , Herreros David , del Caño Laura , Losana Patricia , Fonseca-Reyna Yunior C. , Conesa Pablo , Wrapp Daniel , Chacon Pablo , McLellan Jason S. , Tagare Hemant D. , Carazo Jose-Maria 
Published: July 2020

AbstractWith the help of novel processing workflows and algorithms, we have obtained a better understanding of the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state. We have re-analyzed previous cryo-EM data combining 3D clustering approaches with ways to explore a continuous flexibility space based on 3D Principal Component Analysis. These advanced analyses revealed a concerted motion involving the receptor-binding domain (RBD), N-terminal domain (NTD), and subdomain 1 and 2 (SD1 & SD2) around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. We show that in this dataset there are not well-defined, stable, spike conformations, but virtually a continuum of states moving in a concerted fashion. We obtained an improved resolution ensemble map with minimum bias, from which we model by flexible fitting the extremes of the change along the direction of maximal variance. Moreover, a high-resolution structure of a recently described biochemically stabilized form of the spike is shown to greatly reduce the dynamics observed for the wild-type spike. Our results provide new detailed avenues to potentially restrain the spike dynamics for structure-based drug and vaccine design and at the same time give a warning of the potential image processing classification instability of these complicated datasets, having a direct impact on the interpretability of the results.
Striatal cholinergic interneuron numbers are increased in a rodent model of dystonic cerebral palsy
Authors: Gandham Sushma , Tak Yearam , Aravamuthan Bhooma R. 
Published: July 2020

AbstractNeonatal brain injury leading to cerebral palsy (CP) is the most common cause of childhood dystonia, a painful and functionally debilitating movement disorder. Rare monogenic etiologies of dystonia have been associated with striatal cholinergic interneuron (ChI) pathology. However it is unclear whether striatal ChI pathology is also associated with dystonia following neonatal brain injury. We used unbiased stereology to estimate striatal ChI and parvalbumin-positive GABAergic interneuron (PVI) numbers in a rodent model of neonatal brain injury that demonstrates electrophysiological markers of dystonia and spasticity. Striatal ChI numbers are increased following neonatal brain injury while PVI numbers are unchanged. These numbers do not correlate with electrophysiologic measures of dystonia severity. This suggests that striatal ChI pathology, though present, may not be the primary pathophysiologic contributor to dystonia following neonatal brain injury. Increased striatal ChI numbers could instead represent a passenger or protective phenomenon in the setting of dystonic CP.
DeepCDR: a hybrid graph convolutional network for predicting cancer drug response
Authors: Liu Qiao , Hu Zhiqiang , Jiang Rui , Zhou Mu 
Published: July 2020

AbstractMotivationAccurate prediction of cancer drug response (CDR) is challenging due to the uncertainty of drug efficacy and heterogeneity of cancer patients. Strong evidences have implicated the high dependence of CDR on tumor genomic and transcriptomic profiles of individual patients. Precise identification of CDR is crucial in both guiding anti-cancer drug design and understanding cancer biology.ResultsIn this study, we present DeepCDR which integrates multi-omics profiles of cancer cells and explores intrinsic chemical structures of drugs for predicting cancer drug response. Specifically, DeepCDR is a hybrid graph convolutional network consisting of a uniform graph convolutional network (UGCN) and multiple subnetworks. Unlike prior studies modeling hand-crafted features of drugs, DeepCDR automatically learns the latent representation of topological structures among atoms and bonds of drugs. Extensive experiments showed that DeepCDR outperformed state-of-the-art methods in both classification and regression settings under various data settings. We also evaluated the contribution of different types of omics profiles for assessing drug response. Furthermore, we provided an exploratory strategy for identifying potential cancer-associated genes concerning specific cancer types. Our results highlighted the predictive power of DeepCDR and its potential translational value in guiding disease-specific drug design.AvailabilityDeepCDR is freely available athttps://github.com/kimmo1019/DeepCDRContactruijiang@tsinghua.edu.cn;muzhou@sensebrain.siteSupplementary informationSupplementary data are available atBioinformaticsonline.
Subjective visibility report is facilitated by conscious predictions only
Authors: Alilović Josipa , Slagter Heleen A. , van Gaal Simon 
Published: July 2020

AbstractPredictions in the visual domain have been shown to modulate conscious access. Yet, little is known about how predictions may do so and to what extent they need to be consciously implemented to be effective. To address this, we administered an attentional blink (AB) task in which target 1 (T1) identity predicted target 2 (T2) identity, while participants rated their perceptual awareness of validly versus invalidly predicted T2s (Experiment 1 & 2) or reported T2 identity (Experiment 3). Critically, we tested the effects of conscious and non-conscious predictions, after seen and unseen T1s, on T2 visibility. We found that valid predictions increased subjective visibility reports and discrimination of T2s, but only when predictions were generated by a consciously accessed T1, irrespective of the timing at which the effects were measured (short vs. longs lags). These results further our understanding of the intricate relationship between predictive processing and consciousness.
Whole genome survey of big cats (Genus:Panthera) identifies novel microsatellites of utility in conservation genetic study
Authors: Hyun Jee Yun , Pandey Puneet , Kim Kyung Seok , Chon Alvin , Jeong Daecheol , Bhak Jong , Yoo Mi-Hyun , Song Hey-Kyung , Singh Randeep , Min Mi-Sook , Goyal Surendra Prakash , Bayarkhagva Damdingiin , Lee Hang 
Published: July 2020

AbstractBig cats (Genus:Panthera) are among the most threatened mammal groups of the world, owing to illegal transnational trade. Conservation genetic studies and effective curbs on poaching are important for the conservation of these charismatic apex predators. A limited number of microsatellite markers exists forPantheraspecies and researchers often cross-amplify domestic cat microsatellites to study these species. We conducted data mining of sevenPantheragenome sequences to discover microsatellites for conservation genetic studies of four threatened big cat species. A total of 32 polymorphic microsatellite loci were identified in silico and tested with 99 big cat individuals and 7 Eurasian lynx. The developed markers were polymorphic in most of the tested species. We propose a set of 15 novel microsatellite markers for use in conservation genetics and wildlife forensic investigations of big cat species. Cumulatively, these markers have a high discriminatory power of one in a million for unrelated individuals and one in a thousand for siblings. Similar PCR conditions of these markers increase the prospects of achieving efficient multiplex PCR assays. This study is a pioneering attempt to synthesise genome wide microsatellite markers for big cats.
Production of benzylglucosinolate by engineering and optimizing the biosynthetic pathway inSaccharomyces cerevisiae
Authors: Wang Cuiwei , Crocoll Christoph , Nødvig Christina Spuur , Mortensen Uffe Hasbro , Clemmensen Sidsel Ettrup , Halkier Barbara Ann 
Published: July 2020

AbstractGlucosinolates are amino acid-derived defense compounds characteristic of the Brassicales order. Benzylglucosinolate (BGLS) derived from phenylalanine is associated with health-promoting effects, which has primed a desire to produce BGLS in microorganisms for a stable and rich source. In this study, we engineered the BGLS production inSaccharomyces cerevisiaeby either stably integrating the biosynthetic genes into the genome or introducing them from plasmids. A comparison of the two approaches exhibited a significantly higher level of BGLS production (9.3-fold) by expression of the genes from genome than from plasmids. Towards optimization of BGLS production from genes stably integrated into the genome, we enhanced expression of the entry point enzymes CYP79A2 and CYP83B1 resulting in a 2-fold increase in BGLS production, but also a 4.8-fold increase in the biosynthesis of the last intermediate desulfo-benzylglucosinolate (dsBGLS). To alleviate the metabolic bottleneck in the last step converting dsBGLS to BGLS by 3’-phosphoadenosine-5’-phosphosulfate (PAPS)-dependent sulfotransferase, SOT16, we first obtained an increased BGLS production by 1.7-fold when overexpressingSOT16. Next, we introduced APS kinase APK1 ofArabidopsis thalianafor efficient PAPS regeneration, which improved the level of BGLS production by 1.7-fold. Our work shows an optimized production of BGLS inS. cerevisiaeand the effect of different approaches for engineering the biosynthetic pathway (plasmid expression and genome integration) on the production level of BGLS.
Genomic and phylogenomic insights into the familyStreptomycetaceaelead to proposal ofCharcoactinosporaceaefam. nov. and 8 novel genera with emended descriptions ofStreptomyces calvus
Authors: Madhaiyan Munusamy , Saravanan Venkatakrishnan Sivaraj , See-Too Wah-Seng 
Published: July 2020

AbstractStreptomycetaceaeis one of the oldest families within phylumActinobacteriaand it is large and diverse in terms of number of described taxa. The members of the family are known for their ability to produce medically important secondary metabolites and antibiotics. In this study, strains showing low 16S rRNA gene similarity (<97.3 %) with other members ofStreptomycetaceaewere identified and subjected to phylogenomic analysis using 33 orthologous gene clusters (OGC) for accurate taxonomic reassignment resulted in identification of eight distinct and deeply branching clades, further average amino acid identity (AAI) analysis showed lower AAI values or AAI within the range of 60-80 % which was previously observed in related but different genera of bacteria. The whole genome phylogeny based on concatenated core genes and AAI analyses supported the claim that those phylogenetically distinct members may be assigned to 8 novel genera namelyActinoacidiphila, Actinomesophilus, Charcoactinospora, Curviacidiphilus, Kafeoacidiphilus, Mangroviactinospora, Peterkaempfera,andStreptantibioticus.In addition, based on the core genome phylogeny and 16S rRNA tree topology and distinct chemotaxonomic and physiological properties, the sequence belonged toStreptomyces thermoautotrophicuswas assigned to a novel generaCharcoactinosporawhich is placed under novel familyCharcoactinosporaceae. Lastly, a clade comprising of strains that showed high 16S rRNA gene similarity (100 %) with similar tree topology in phylogenetic trees was subjected to overall genome related indices analyses such as digital DNA – DNA hybridization, and average nucleotide identity that supported the claim thatStreptomyces asterosporusis a later heterotypic synonym ofStreptomyces calvus.
A novel algorithm to detect non-wear time from raw accelerometer data using convolutional neural networks
Authors: Syed Shaheen , Morseth Bente , Hopstock Laila A. , Horsch Alexander 
Published: July 2020

ABSTRACTCurrent non-wear detection algorithms frequently employ a 30- to 90-minute interval in which recorded acceleration needs to be below a threshold value. Such intervals need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives (type II errors), limiting their ability to achieve a high F1 score. In this paper, we propose a novel non-wear detection algorithm that eliminates the need for an interval. Rather than inspecting acceleration within intervals, we explore acceleration patterns right before and right after an episode of non-wear time. By drawing on insights from the field of activity type recognition, we propose an algorithm that uses a convolutional neural network to detect the preceding activity ‘taking off the accelerometer’ and the following activity ‘placing it back on’. We evaluate our algorithm against several baseline and existing non-wear algorithms for raw accelerometer data, and our algorithm achieves a perfect precision, a recall of 0.9962, and an F1 score of 0.9981, outperforming all evaluated baseline and non-wear algorithms. Although our algorithm was developed using patterns learned from a hip-worn accelerometer, we propose algorithmic steps that can easily be applied to a wrist-worn accelerometer and a retrained classification model.
A novel method of multiple adaptive notch filtering for flexible missile vibration suppression
Authors: Chen Gong , Liu Shaojie , Tang Zhigong , Xu Jiangtao , Wang Wenzheng 
Published: July 2020

Purpose
The modern missile has low uncertain and wide range vibration frequency. The conventional notch filter with the fixed notch frequency is less effective than that of the adaptive notch filter (ANF) in vibration suppression for the time-varying vibration frequency.

Design/methodology/approach
To overcome the drawback, a novel method is based on frequency estimators made by interpolation of three discrete Fourier transform (DFT) spectral lines. The modified frequency estimators based on the interpolation of three DFT spectral lines are presented to identify and track the vibration frequency. Then the notch frequencies of multiple ANFs are real-timely tuned according to estimators.

Findings
Finally, taking the second-order flexible missile as an example, the performance of the proposed method is verified. The verified simulation results show that multiple ANFs are effective in vibration suppression.

Practical implications
Cascading multiple ANFs to achieve multi-order vibration suppression is more efficient and feasible than conventional fixed-parameter notch filtering.

Originality/value
The frequency estimation method based on three DFT spectral lines proposed in this paper can effectively identify and track signals in the noise environment. Compared with conventional methods, the method pretended in this paper has high identification accuracy and a stronger ability to track signals. It can meet the fast frequency identification requirements of the actual flexible missile.
Formation of higher education (HE) learner identity among community college transfer students in Hong Kong
Authors: Dang Beatrice Yan-yan 
Published: July 2020

PurposeThis study aims to explore the opportunities and constraints for learner identity formation among community college transfer students.Design/methodology/approachData were collected from four in-depth interviews with five transfer students across an academic year (i.e. 20 interviews in total). The first interview allowed the current researcher to explore the context of students' community college experiences and their first semester in the university. The second and third interview had two purposes: (1) to provide an opportunity for students to discuss their second semester experiences and (2) to understand the process of learner identity formation. The last interview allowed the students to reflect on their time in the university after studying for one year.FindingsThe findings reveal that higher education (HE) learner identity was nurtured by peer support, orientation activities and mentorship programme. While, striving for self-improvement and developing into an autonomous and active learner are essential in the formation of the HE learner identity in university.Originality/valueThis study represents the local students' voice that enrolling in community colleges with the goal of transferring to University Grant Committee (UGC)-funded universities. Transition is a process of change in the course of life and also a shift from one identity to another (Ecclestone et al., 2010). A smooth transition may contribute to the formation of positive learner identity, which is essential to student retention and persistence.
Guests’ perceptions of robot concierge and their adoption intentions
Authors: Shin Hyejo Hailey , Jeong Miyoung 
Published: July 2020

PurposeThe hotel industry has witnessed an increasing number of service automation through service robots such as robot concierges. However, few studies have documented how to identify how hotel guests perceive a robot concierge for their service encounter. Therefore, the purpose of this study is to examine the effects of robot concierges on hotel guests’ attitudes and adoption intentions of robot concierges.Design/methodology/approachThis study investigated the effects of robot concierges’ morphology and their level of interactivity with guests at different levels of hotel service on guests’ attitudes and their intentions to adopt robot concierges. To achieve the study’s objectives, this study conducted a 3 × 2 × 3 between-subjects factorial design experiment. Moreover, the survey asked questions about subjects’ preferences of their service encounters (e.g. human employees, robot concierges and/or no preference) and reasons for their selected preference.FindingsThe results demonstrated that the robot’s morphology significantly influenced guests’ attitudes toward robot concierges. In particular, the caricatured robot was the most preferred morphology of robot concierges. The findings showed that even if guests had favorable attitudes toward robot concierges, they preferred human employees to robot concierges because of humans’ sincere and genuine interactions.Originality/valueThis study contributes to the literature by investigating the causal impacts of the morphology of robot concierges, level of interactivity and level of hotel service on guests’ attitudes toward robot concierges. The thematic analysis of service encounter preference provides an overview of the factors that guests expect for their service encounters in a hotel setting.
A framework of smart pedagogy based on the facilitating of high order thinking skills
Authors: Meng Qingquan , Jia Jiyou , Zhang Zhiyong 
Published: July 2020

Purpose
The purpose of this study is to verify the effect of smart pedagogy to facilitate the high order thinking skills of students and to provide the design suggestion of curriculum and intelligent tutoring systems in smart education.

Design/methodology/approach
A smart pedagogy framework was designed. The quasi-experiment was conducted in a junior high school. The experimental class used the smart pedagogy and smart learning environment. The control class adopted conventional teaching strategies. The math test scores of these two classes were compared to verify the effectiveness of smart pedagogy.

Findings
The smart pedagogy framework contains three sections including the situated learning (S), mastery learning (M), adaptive learning (A), reflective learning (R) and thinking tools (T) (SMART) key elements model, the curriculum design method and detailed teaching strategy. The SMART key elements model integrates the situated learning, mastery learning, adaptive learning, reflective learning and thinking tools to facilitate the high order thinking. The curriculum design method of smart pedagogy combines the first five principles of instruction and the SMART key elements model to design the curriculum. The detailed teaching strategies of smart pedagogy contain kinds of innovative learning methods. The results of the quasi-experiment proved that the learning outcome was significantly promoted by using smart pedagogy.

Originality/value
This research investigates a general framework that can be used to cultivate the high order thinking skills in different subjects and grades was one of the first to introduce high order thinking skills into smart education. The framework of smart pedagogy was innovative and effect in practice.