bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal self-compression: Behavioral and neural evidence that past and future selves are compressed as they move away from the present
Authors: Brietzke Sasha , Meyer Meghan L. 
Published: November 2021

SignificanceFor centuries, great thinkers have struggled to understand how people represent a personal identity that changes over time. Insight may come from a basic principle of perception: as objects become distant, they also become less discriminable or “compressed.” In Studies 1–3, we demonstrate that people’s ratings of their own personality become increasingly less differentiated as they consider more distant past and future selves. In Study 4, we found neural evidence that the brain compresses self-representations with time as well. When we peer out a window, objects close to us are in clear view, whereas distant objects are hard to tell apart. We provide evidence that self-perception may operate similarly, with the nuance of distant selves increasingly harder to perceive.
Structural basis for substrate specificity of heteromeric transporters of neutral amino acids
Authors: Rodriguez Carlos F. , Escudero-Bravo Paloma , Díaz Lucía , Bartoccioni Paola , García-Martín Carmen , Gilabert Joan G. , Boskovic Jasminka , Guallar Víctor , Errasti-Murugarren Ekaitz , Llorca Oscar , Palacín Manuel 
Published: November 2021

Significance
The transport of amino acids across the plasma membrane plays a central role in physiology. The heteromeric amino acid transporters (HATs) of neutral amino acids (LAT1/CD98hc, LAT2/CD98hc, and Asc1/CD98hc) participate in a variety of processes such as modulation of glutamatergic neurotransmission and synaptic plasticity, auditory function, and promotion of brain development and tumor growth by supporting mTORC1 activity. We identify substrate specificity determinants of neutral amino acids HATs within the substrate-binding cavity and in a nearby region that holds the conformation of the substrate-binding site. LAT2 mutations in this scaffold region are associated with human diseases, and our results pave the way to understand the molecular mechanisms of these pathologies.
Reconsidering theshi…(de)construction in spoken Mandarin
Authors: Cook Angela 
Published: November 2021

AbstractThis paper revisits the use of theshi…deconstruction, based on the analysis of structures with predicative adjectives in a 500,000-character corpus of spoken Mandarin assembled from transcripts of a popular Chinese chat show. Overall,dewas omitted more than 40% of the time with a predicative adjective, a significantly higher rate than that found in previous studies. The data reveal a number of factors that may all play a role in determining the likelihood ofdeomission or retention: the time dependency of the adjective, the particular intensifier chosen to modify the adjective, the discourse function of the utterance and the presence of certain markers of epistemic modality. The findings also lend support to the hypothesis thatshiis grammaticalizing to a bound morpheme in some so-called ‘conventionalised forms’ involving epistemic and evidentiality markers.
Revisions to the Siraya lexicon based on the original Utrecht Manuscript
Authors: Joby Christopher 
Published: November 2021

Summary
Linguistic historiography analyzes how linguistic knowledge has been acquired, stored, used and diffused. This article examines what can happen if linguists rely on copies of source data rather than the source data itself. It takes as a case study linguistic data from Siraya, a now-extinct Formosan language. Documents compiled in the seventeenth century by Dutch missionaries in Taiwan form a significant source of data for Siraya. One such document, a wordlist known as the Utrecht Manuscript (UM), is the principal source for the lexicon of one variety of Siraya, “Siraya Proper”. It has been published three times. Each edition, however, contains many errors. These editions, rather than the manuscript, have been used by scholars investigating Siraya. This article aims to correct errors in the editions and secondary literature on the UM with my readings of the manuscript itself. It therefore presents a more accurate record of the lexicon of “Siraya Proper” as well as illustrating the importance of using primary rather than secondary sources of linguistic data. Finally, it introduces an online edition of the UM, which will provide scholars and language revivalists with a useful resource for this lexicon.
Discoursal representation of masculine parenting in Arabic and English websites
Authors: Al-Ali Mohammed Nahar , Shatat Hanan A. 
Published: November 2021

Abstract
The purpose of this study is to investigate the differences and similarities between Arabic and English parents’ role in
Arabic and English parenting website texts and the linguistic exponents used to address parents and signal their roles, and to find out the
socio-cultural ideologies that have given rise to variations in gender roles. To this end, a corpus of 40 articles targeting gender-neutral
titles and father related ones were selected equally from English and Arabic websites. Drawing on Van
Leeuwen’s (2008) framework on critical discourse analysis (CDA) and Sunderland’s (2000,
2006) framework of analysis, the data were analysed and contrasted. The English texts reflected the prevalence of ‘shared parenting’
discourse, whereas the Arabic ones revealed a ‘very traditional parenthood’ discourse. These differences can be attributed to variation in
the socio-cultural practices dominant in Arab and Western societies. Such findings will hopefully provide some useful insights for family
life educators and parents who resort to such websites.
L2 Theme development in Discursive and Experimental undergraduate student writing
Authors: Chen Xiao , Gardner Sheena 
Published: November 2021

Abstract
To complement earlier studies of writing development in the BAWE corpus of successful student writing (Nesi & Gardner 2012; Staples et al. 2016), we examine the Systemic Functional Linguistics notion of Theme as used by L2 writers across first- and third-year and in two distinctive discourse types: persuasive/argumentative Discursive writing of assignments in the soft disciplines and Experimental report writing of assignments in the hard sciences. Theme analysis reveals more substantial differences across the two discourse types than between first- and third-year L2 undergraduate writing. Textual Themes are consistently more frequent than interpersonal Themes, and some variance is found within subcategories of each. Significant differences in lexical density occur across third-year discourse types and between first- and third-year Experimental writing where a predominance of N+N topical Themes is also found. These findings are important as previous research has tended to focus on L1 Discursive writing.
Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier
Authors: Liu Yushuang , Jin Shuping , Gao Hongli , Wang Xue , Wang Congjing , Zhou Weifeng , Yu Bin 
Published: November 2021

Abstract

Motivation
Multi-label (ML) protein subcellular localization (SCL) is an indispensable way to study protein function. It can locate a certain protein (such as the human transmembrane protein that promotes the invasion of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) or expression product at a specific location in a cell, which can provide a reference for clinical treatment of diseases such as coronavirus disease 2019 (COVID-19).

Results
The article proposes a novel method named ML-locMLFE. First of all, six feature extraction methods are adopted to obtain protein effective information. These methods include pseudo amino acid composition, encoding based on grouped weight, gene ontology, multi-scale continuous and discontinuous, residue probing transformation and evolutionary distance transformation. In the next part, we utilize the ML information latent semantic index method to avoid the interference of redundant information. In the end, ML learning with feature-induced labeling information enrichment is adopted to predict the ML protein SCL. The Gram-positive bacteria dataset is chosen as a training set, while the Gram-negative bacteria dataset, virus dataset, newPlant dataset and SARS-CoV-2 dataset as the test sets. The overall actual accuracy of the first four datasets are 99.23%, 93.82%, 93.24% and 96.72% by the leave-one-out cross validation. It is worth mentioning that the overall actual accuracy prediction result of our predictor on the SARS-CoV-2 dataset is 72.73%. The results indicate that the ML-locMLFE method has obvious advantages in predicting the SCL of ML protein, which provides new ideas for further research on the SCL of ML protein.

Availability and implementation
The source codes and datasets are publicly available at https://github.com/QUST-AIBBDRC/ML-locMLFE/.

Supplementary information
Supplementary data are available at Bioinformatics online.
RCSB Protein Data Bank: improved annotation, search and visualization of membrane protein structures archived in the PDB
Authors: Bittrich Sebastian , Rose Yana , Segura Joan , Lowe Robert , Westbrook John D , Duarte Jose M , Burley Stephen K 
Published: November 2021

Abstract

Motivation
Membrane proteins are encoded by approximately one fifth of human genes but account for more than half of all US FDA approved drug targets. Thanks to new technological advances, the number of membrane proteins archived in the PDB is growing rapidly. However, automatic identification of membrane proteins or inference of membrane location is not a trivial task.

Results
We present recent improvements to the RCSB Protein Data Bank web portal (RCSB PDB, rcsb.org) that provide a wealth of new membrane protein annotations integrated from four external resources: OPM, PDBTM, MemProtMD and mpstruc. We have substantially enhanced the presentation of data on membrane proteins. The number of membrane proteins with annotations available on rcsb.org was increased by ∼80%. Users can search for these annotations, explore corresponding tree hierarchies, display membrane segments at the 1D amino acid sequence level, and visualize the predicted location of the membrane layer in 3D.

Availability and implementation
Annotations, search, tree data and visualization are available at our rcsb.org web portal. Membrane visualization is supported by the open-source Mol* viewer (molstar.org and github.com/molstar/molstar).

Supplementary information
Supplementary data are available at Bioinformatics online.
Identification, semantic annotation and comparison of combinations of functional elements in multiple biological conditions
Authors: Leone Michele , Galeota Eugenia , Masseroli Marco , Pelizzola Mattia 
Published: November 2021

Abstract

Motivation
Approaches such as chromatin immunoprecipitation followed by sequencing (ChIP-seq) represent the standard for the identification of binding sites of DNA-associated proteins, including transcription factors and histone marks. Public repositories of omics data contain a huge number of experimental ChIP-seq data, but their reuse and integrative analysis across multiple conditions remain a daunting task.

Results
We present the Combinatorial and Semantic Analysis of Functional Elements (CombSAFE), an efficient computational method able to integrate and take advantage of the valuable and numerous, but heterogeneous, ChIP-seq data publicly available in big data repositories. Leveraging natural language processing techniques, it integrates omics data samples with semantic annotations from selected biomedical ontologies; then, using hidden Markov models, it identifies combinations of static and dynamic functional elements throughout the genome for the corresponding samples. CombSAFE allows analyzing the whole genome, by clustering patterns of regions with similar functional elements and through enrichment analyses to discover ontological terms significantly associated with them. Moreover, it allows comparing functional states of a specific genomic region to analyze their different behavior throughout the various semantic annotations. Such findings can provide novel insights by identifying unexpected combinations of functional elements in different biological conditions.

Availability and implementation
The Python implementation of the CombSAFE pipeline is freely available for non-commercial use at: https://github.com/DEIB-GECO/CombSAFE.

Supplementary information
Supplementary data are available at Bioinformatics online.
springD2A: capturing uncertainty in disease–drug association prediction with model integration
Authors: Wang Weiwen , Zhang Xiwen , Dai Dao-Qing 
Published: November 2021

Abstract

Motivation
Drug repositioning that aims to find new indications for existing drugs has been an efficient strategy for drug discovery. In the scenario where we only have confirmed disease–drug associations as positive pairs, a negative set of disease–drug pairs is usually constructed from the unknown disease–drug pairs in previous studies, where we do not know whether drugs and diseases can be associated, to train a model for disease–drug association prediction (drug repositioning). Drugs and diseases in these negative pairs can potentially be associated, but most studies have ignored them.

Results
We present a method, springD2A, to capture the uncertainty in the negative pairs, and to discriminate between positive and unknown pairs because the former are more reliable. In springD2A, we introduce a spring-like penalty for the loss of negative pairs, which is strong if they are too close in a unit sphere, but mild if they are at a moderate distance. We also design a sequential sampling in which the probability of an unknown disease–drug pair sampled as negative is proportional to its score predicted as positive. Multiple models are learned during sequential sampling, and we adopt parameter- and feature-based ensemble schemes to boost performance. Experiments show springD2A is an effective tool for drug-repositioning.

Availability and implementation
A python implementation of springD2A and datasets used in this study are available at https://github.com/wangyuanhao/springD2A.

Supplementary information
Supplementary data are available at Bioinformatics online.
HDMC: a novel deep learning-based framework for removing batch effects in single-cell RNA-seq data
Authors: Wang Xiao , Wang Jia , Zhang Han , Huang Shenwei , Yin Yanbin 
Published: November 2021

Abstract

Motivation
With the development of single-cell RNA sequencing (scRNA-seq) techniques, increasingly more large-scale gene expression datasets become available. However, to analyze datasets produced by different experiments, batch effects among different datasets must be considered. Although several methods have been recently published to remove batch effects in scRNA-seq data, two problems remain to be challenging and not completely solved: (i) how to reduce the distribution differences of different batches more accurately; and (ii) how to align samples from different batches to recover the cell type clusters.

Results
We proposed a novel deep-learning approach, which is a hierarchical distribution-matching framework assisted with contrastive learning to address these two problems. Firstly, we design a hierarchical framework for distribution matching based on a deep autoencoder. This framework employs an adversarial training strategy to match the global distribution of different batches. This provides an improved foundation to further match the local distributions with a maximum mean discrepancy-based loss. For local matching, we divide cells in each batch into clusters and develop a contrastive learning mechanism to simultaneously align similar cluster pairs and keep noisy pairs apart from each other. This allows to obtain clusters with all cells of the same type (true positives), and avoid clusters with cells of different type (false positives). We demonstrate the effectiveness of our method on both simulated and real datasets. Results show that our new method significantly outperforms the state-of-the-art methods and has the ability to prevent overcorrection.

Availability and implementation
The python code to generate results and figures in this article is available at https://github.com/zhanglabNKU/HDMC, the data underlying this article is also available at this github repository.

Supplementary information
Supplementary data are available at Bioinformatics online.
Personalized subcutaneous implantable cardioverter-defibrillator sensing vectors generated by mathematical rotation increase device eligibility whilst preserving device performance
Authors: Wiles Benedict M , Roberts Paul R , Allavatam Venugopal , Acharyya Amit , Vemishetty Naresh , ElRefai Mohamed , Wilson David G , Maharatna Koushik , Chen Hanjie , Morgan John M 
Published: November 2021

Abstract

Aims
Approximately 5.7% of potential subcutaneous implantable cardioverter-defibrillator (S-ICD) recipients are ineligible by virtue of their vector morphology, with higher rates of ineligibility observed in some at-risk groups. Mathematical vector rotation is a novel technique that can generate a personalized sensing vector, one with maximal R:T ratio, using electrocardiogram (ECG) signal recorded from the present S-ICD location.

Methods and results
A cohort of S-ICD ineligible patients were identified through ECG screening of ICD patients with no ventricular pacing requirement and their personalized vectors were generated using ECG signal from a Holter monitor. Subcutaneous ICD eligibility in this cohort was then recalculated. In a separate cohort, episodes of arrhythmia were recorded in patients undergoing arrhythmia induction, and arrhythmia detection in standard S-ICD vectors was compared to rotated vectors using an S-ICD simulator. Ninety-two participants (mean age 64.9 ± 2.7 years) underwent screening and 5.4% were found to be S-ICD ineligible. Personalized vector generation increased the R:T ratio in these vectors from 2.21 to 7.21 (4.54–9.88, P &lt; 0.001) increasing the cohort eligibility from 94.6% to 100%. Rotated S-ICD vectors also showed high ventricular fibrillation (VF) detection sensitivity (97.8%), low time to VF detection (6.1 s), and excellent tachycardia discrimination (sensitivity 96%, specificity 88%), with no significant differences between rotated and standard vectors.

Conclusion
In S-ICD ineligible patients, mathematical vector rotation can generate a personalized vector that is associated with a significant increase in R:T ratio, resulting in universal device eligibility in our cohort. Ventricular fibrillation detection efficacy, time to VF detection, and tachycardia discrimination were not affected by vector rotation.
Hybridization Dynamics and Extensive Introgression in theDaphnia longispinaSpecies Complex: New Insights from a High-QualityDaphnia galeataReference Genome
Authors: Nickel Jana , Schell Tilman , Holtzem Tania , Thielsch Anne , Dennis Stuart R , Schlick-Steiner Birgit C , Steiner Florian M , Möst Markus , Pfenninger Markus , Schwenk Klaus , Cordellier Mathilde 
Published: November 2021

AbstractHybridization and introgression are recognized as an important source of variation that influence adaptive processes; both phenomena are frequent in the genus Daphnia, a keystone zooplankton taxon in freshwater ecosystems that comprises several species complexes. To investigate genome-wide consequences of introgression between species, we provide here the first high-quality genome assembly for a member of the Daphnia longispina species complex, Daphnia galeata. We further resequenced 49 whole genomes of three species of the complex and their interspecific hybrids both from genotypes sampled in the water column and from single resting eggs extracted from sediment cores. Populations from habitats with diverse ecological conditions offered an opportunity to study the dynamics of hybridization linked to ecological changes and revealed a high prevalence of hybrids. Using phylogenetic and population genomic approaches, we provide first insights into the intra- and interspecific genome-wide variability in this species complex and identify regions of high divergence. Finally, we assess the length of ancestry tracts in hybrids to characterize introgression patterns across the genome. Our analyses uncover a complex history of hybridization and introgression reflecting multiple generations of hybridization and backcrossing in the Daphnia longispina species complex. Overall, this study and the new resources presented here pave the way for a better understanding of ancient and contemporary gene flow in the species complex and facilitate future studies on resting egg banks accumulating in lake sediment.
Regulation of bla system in ST59-related oxacillin-susceptible mecA-positive Staphylococcus aureus
Authors: Jian Ying , Li Tianming , Zhao Lin , Zhao Na , Liu Yao , Lv Huiying , Wang Ya’nan , Liu Qian , Li Min 
Published: November 2021

Abstract

Objectives
Oxacillin-susceptible mecA-positive Staphylococcus aureus (OS-MRSA) is clinically significant and isolated globally but the mechanism of its occurrence remains indistinct. We sought to assess the mechanism of regulating oxacillin susceptibility in OS-MRSA isolates by evaluating the evolutionary dynamics of OS-MRSA and the discrepancies of mecA-regulating genes in OS-MRSA and oxacillin-resistant MRSA (OR-MRSA).

Methods
Nine OS-MRSA isolates and 77 OR-MRSA isolates were sequenced using next-generation sequencing (NGS) platforms. Two representative OS-MRSA isolates (ET-13, ET-16) were induced to be oxacillin resistant and sequenced also. OS-MRSA ET-16 and its counterpart isolate with induced oxacillin resistance, ET-16I, and their mutants were used to confirm the role of the bla system in regulating methicillin susceptibility. Oxacillin MICs were determined using Etests. Expression of mecA and blaR1 was quantified by quantitative RT–PCR.

Results
A deletion in blaR1 in most OS-MRSA isolates (7/9; 77.78%) was found using NGS data, and overexpression of OR-blaR1 in OS-MRSA isolate ET-16 restored its oxacillin resistance. OS-MRSA could be induced to be oxacillin resistant, while growth was suppressed in the induced isolates. Plasmid containing the bla locus was lost in most induced isolates during the induction process and complementation of blaR1-blaI from OS-MRSA ET-16 to the induced isolate ET-16I converted its oxacillin susceptibility.

Conclusions
Deletion in blaR1 resulted in oxacillin susceptibility in OS-MRSA, and loss of the bla regulator in OS-MRSA restored oxacillin resistance. The bla system played a crucial role in regulating oxacillin susceptibility in OS-MRSA isolates.