bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phytest: quality control for phylogenetic analyses
Authors: Wirth Wytamma , Mutch Simon , Turnbull Robert , Duchene Sebastian 
Published: October 2022

Abstract

Motivation
The ability to automatically conduct quality control checks on phylogenetic analyses is becoming more important with the increase in genetic sequencing and the use of real-time pipelines e.g. in the SARS-CoV-2 era. Implementations of real-time phylogenetic analyses require automated testing to make sure that problems in the data are caught automatically within analysis pipelines and in a timely manner. Here, we present Phytest (version 1.1) a tool for automating quality control checks on sequences, trees and metadata during phylogenetic analyses.

Results
Phytest is a phylogenetic analysis testing program that easily integrates into existing phylogenetic pipelines. We demonstrate the utility of Phytest with real-world examples.

Availability and implementation
Phytest source code is available on GitHub (https://github.com/phytest-devs/phytest) and can be installed via PyPI with the command ‘pip install phytest’. Extensive documentation can be found at https://phytest-devs.github.io/phytest/.

Supplementary information
Supplementary data are available at Bioinformatics online.
RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data
Authors: Shehwana Huma , Kumar Shwetha V , Melott James M , Rohrdanz Mary A , Wakefield Chris , Ju Zhenlin , Siwak Doris R , Lu Yiling , Broom Bradley M , Weinstein John N , Mills Gordon B , Akbani Rehan 
Published: October 2022

Abstract

Summary
Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge. SuperCurve has been used to normalize over 170 000 samples to date. RPPA SPACE allows exclusion of poor-quality samples from the normalization process to improve the quality of the remaining samples. It also features a novel quality-control metric, ‘noise’, that estimates the level of random errors present in each RPPA slide. The noise metric can help to determine the quality and reliability of the data. In addition, RPPA SPACE has simpler input requirements and is more flexible than SuperCurve, it is much faster with greatly improved error reporting.

Availability and implementation
The standalone RPPA SPACE R package, tutorials and sample data are available via https://rppa.space/, CRAN (https://cran.r-project.org/web/packages/RPPASPACE/index.html) and GitHub (https://github.com/MD-Anderson-Bioinformatics/RPPASPACE).

Supplementary information
Supplementary data are available at Bioinformatics online.
scHiCPTR: unsupervised pseudotime inference through dual graph refinement for single-cell Hi-C data
Authors: Lyu Hongqiang , Liu Erhu , Wu Zhifang , Li Yao , Liu Yuan , Yin Xiaoran 
Published: October 2022

Abstract

Motivation
The emerging single-cell Hi-C technology provides opportunities to study dynamics of chromosomal organization. How to construct a pseudotime path using single-cell Hi-C contact matrices to order cells along developmental trajectory is a challenging topic, since these matrices produced by the technology are inherently high dimensional and sparse, they suffer from noises and biases, and the topology of trajectory underlying them may be diverse.

Results
We present scHiCPTR, an unsupervised graph-based pipeline to infer pseudotime from single-cell Hi-C contact matrices. It provides a workflow consisting of imputation and embedding, graph construction, dual graph refinement, pseudotime calculation and result visualization. Beyond the few existing methods, scHiCPTR ties to optimize graph structure by two parallel procedures of graph pruning, which help reduce the spurious cell links resulted from noises and determine a global developmental directionality. Besides, it has an ability to handle developmental trajectories with multiple topologies, including linear, bifurcated and circular ones, and is competitive with methods developed for single-cell RNA-seq data. The comparative results tell that our scHiCPTR can achieve higher performance in pseudotime inference, and the inferred developmental trajectory exhibit a reasonable biological significance.

Availability and implementation
scHiCPTR is freely available at https://github.com/lhqxinghun/scHiCPTR.

Supplementary information
Supplementary data are available at Bioinformatics online.
MSNet-4mC: learning effective multi-scale representations for identifying DNA N4-methylcytosine sites
Authors: Liu Chunting , Song Jiangning , Ogata Hiroyuki , Akutsu Tatsuya 
Published: October 2022

Abstract

Motivation
N4-methylcytosine (4mC) is an essential kind of epigenetic modification that regulates a wide range of biological processes. However, experimental methods for detecting 4mC sites are time-consuming and labor-intensive. As an alternative, computational methods that are capable of automatically identifying 4mC with data analysis techniques become a reasonable option. A major challenge is how to develop effective methods to fully exploit the complex interactions within the DNA sequences to improve the predictive capability.

Results
In this work, we propose MSNet-4mC, a lightweight neural network building upon convolutional operations with multi-scale receptive fields to perceive cross-element relationships over both short and long ranges of given DNA sequences. With strong imbalances in the number of candidates in different species in mind, we compute and apply class weights in the cross-entropy loss to balance the training process. Extensive benchmarking experiments show that our method achieves a significant performance improvement and outperforms other state-of-the-art methods.

Availability and implementation
The source code and models are freely available for download at https://github.com/LIU-CT/MSNet-4mC, implemented in Python and supported on Linux and Windows.

Supplementary information
Supplementary data are available at Bioinformatics online.
CAMML with the Integration of Marker Proteins (ChIMP)
Authors: Schiebout Courtney , Frost H Robert 
Published: October 2022

Abstract

Motivation
Cell typing is a critical task in the analysis of single-cell data, particularly when studying complex diseased tissues. Unfortunately, the sparsity and noise of single-cell data make accurate cell typing of individual cells difficult. To address these challenges, we previously developed the CAMML method for multi-label cell typing of single-cell RNA-sequencing (scRNA-seq) data. CAMML uses weighted gene sets to score each profiled cell for multiple potential cell types. While CAMML outperforms other scRNA-seq cell typing techniques, it only leverages transcriptomic data so cannot take advantage of newer multi-omic single-cell assays that jointly profile gene expression and protein abundance (e.g. joint scRNA-seq/CITE-seq).

Results
We developed the CAMML with the Integration of Marker Proteins (ChIMP) method to support multi-label cell typing of individual cells jointly profiled via scRNA-seq and CITE-seq. ChIMP combines cell type scores computed on scRNA-seq data via the CAMML approach with discretized CITE-seq measurements for cell type marker proteins. The multi-omic cell type scores generated by ChIMP allow researchers to more precisely and conservatively cell type joint scRNA-seq/CITE-seq data.

Availability and implementation
An implementation of this work is available on CRAN at https://cran.r-project.org/web/packages/CAMML/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Cortical neuronal hyperexcitability and synaptic changes in SGCE mutation-positive myoclonus dystonia
Authors: Sperandeo Alessandra , Tamburini Claudia , Noakes Zoe , de la Fuente Daniel Cabezas , Keefe Francesca , Petter Olena , Plumbly William , Clifton Nicholas E , Li Meng , Peall Kathryn J 
Published: October 2022

Abstract
Myoclonus dystonia is a childhood-onset hyperkinetic movement disorder with a combined motor and psychiatric phenotype. It represents one of the few autosomal dominant inherited dystonic disorders and is caused by mutations in the ε-sarcoglycan (SGCE) gene. Work to date suggests that dystonia is caused by disruption of neuronal networks, principally basal ganglia-cerebello-thalamo-cortical circuits. Investigation of cortical involvement has primarily focused on disruption to interneuron inhibitory activity, rather than the excitatory activity of cortical pyramidal neurons. Here, we have sought to examine excitatory cortical glutamatergic activity using two approaches: the CRISPR/Cas9 editing of a human embryonic cell line, generating an SGCE compound heterozygous mutation, and three patient-derived induced pluripotent stem cell lines, each gene edited to generate matched wild-type SGCE control lines. Differentiation towards a cortical neuronal phenotype demonstrated no significant differences in either early- (PAX6, FOXG1) or late-stage (CTIP2, TBR1) neurodevelopmental markers. However, functional characterization using Ca2+ imaging and microelectrode array approaches identified an increase in network activity, while single-cell patch clamp studies found a greater propensity towards action potential generation with larger amplitudes and shorter half-widths associated with SGCE mutations. Bulk RNA sequencing analysis identified gene ontological enrichment for ‘neuron projection development’, ‘synaptic signalling’ and ‘synaptic transmission’. Examination of dendritic morphology found SGCE mutations to be associated with a significantly higher number of branches and longer branch lengths, together with longer ion-channel dense axon initial segments, particularly towards the latter stages of differentiation (Days 80 and 100). Gene expression and protein quantification of key synaptic proteins (synaptophysin, synapsin and PSD95), AMPA and NMDA receptor subunits found no significant differences between the SGCE mutation and matched wild-type lines. By contrast, significant changes to synaptic adhesion molecule expression were identified, namely higher presynaptic neurexin-1 and lower postsynaptic neuroligin-4 levels in the SGCE mutation carrying lines. Our study demonstrates an increased intrinsic excitability of cortical glutamatergic neuronal cells in the context of SGCE mutations, coupled with a more complex neurite morphology and disruption to synaptic adhesion molecules. These changes potentially represent key components to the development of the hyperkinetic clinical phenotype observed in myoclonus dystonia, as well a central feature to the wider spectrum of dystonic disorders, potentially providing targets for future therapeutic development.
Gone with the wind: The consequences of US drone strikes in Pakistan
Authors: Mahmood Rafat , Jetter Michael 
Published: October 2022

Abstract
Employing day-to-day wind conditions as an identification strategy, we explore the consequences of the 420 US drone strikes in Pakistan between 2006 and 2016. Results suggest that drone strikes encourage terrorism over the upcoming days and weeks, causing up to 19% of all terror attacks with more than 3,000 terror deaths in Pakistan during that period. Studying a leading Pakistani newspaper, we identify a polarised response to drone strikes as negative emotions and anger, but also positive emotions, in drone-related articles increase. Finally, anti-US protests and online searches exhibiting radical Islamist concepts increase as a consequence of drone strikes.
The impact of machine-learning-derived lean psoas muscle area on prognosis of type B aortic dissection patients undergoing endovascular treatment
Authors: Liu Jitao , Su Sheng , Liu Weijie , Xie Enmin , Hu Xiaolu , Lin Wenhui , Ding Huanyu , Luo Songyuan , Liu Yuan , Huang Wenhui , Li Jie , Yang Fan , Luo Jianfang 
Published: October 2022

Abstract

OBJECTIVES
The aim of this work was to investigate the impact of machine-learning-derived baseline lean psoas muscle area (LPMA) for patients undergoing thoracic endovascular aortic repair.

METHODS
A retrospective study was undertaken of acute and subacute complicated type B aortic dissection patients who underwent endovascular treatment from 2010 to 2017. LPMA (a marker of frailty) was calculated by multiplying psoas muscle area and density measured at L3 level from the computed tomography. The optimal cut-off value of LPMA was determined by the Cox hazard model with restricted cubic spline.

RESULTS
A total of 428 patients who met the inclusion criteria were included in this study. Patients were classified into low LPMA group (n = 218) and high LPMA group (n = 210) using the cut-off value of 395 cm2 Hounsfield unit. An automatic muscle segmentation algorithm was developed based on U-Net architecture. There was high correlation between machine-learning method and manual measurement for psoas muscle area (r = 0.91, P &lt; 0.001) and density (r = 0.90, P &lt; 0.001). Multivariable regression analyses revealed that baseline low LPMA (&lt;395 cm2 Hounsfield unit) was an independent positive predictor for 30-day (odds ratio 5.62, 95% confidence interval 1.20–26.23, P = 0.028) and follow-up (hazard ratio 5.62, 95% confidence interval 2.68–11.79, P &lt; 0.001) mortality. Propensity score matching and subgroup analysis based on age (&lt;65 vs ≥65 years) confirmed the independent association between baseline LPMA and follow-up mortality.

CONCLUSIONS
Baseline LPMA could profoundly affect the prognosis of patients undergoing thoracic endovascular aortic repair. It was feasible to integrate the automatic muscle measurements into clinical routine.
When Is a Potassium Channel Not a Potassium Channel?
Authors: Accili Eric 
Published: October 2022

AbstractEver since they were first observed in Purkinje fibers of the heart, funny channels have had close connections to potassium channels. Indeed, funny channels were initially thought to produce a potassium current in the heart called IK2. However, funny channels are completely unlike potassium channels in ways that make their contributions to the physiology of cells unique. An important difference is the greater ability for sodium to permeate funny channels. Although it does not flow through the funny channel as easily as does potassium, sodium does permeate well enough to allow for depolarization of cells following a strong hyperpolarization. This is critical for the function of funny channels in places like the heart and brain. Computational analyses using recent structures of the funny channels have provided a possible mechanism for their unusual permeation properties.
Draft genome and multi-tissue transcriptome assemblies of the Neotropical leaf-frog Phyllomedusa bahiana
Authors: Andrade Pedro , Lyra Mariana L , Zina Juliana , Bastos Deivson F O , Brunetti Andrés E , Baêta Délio , Afonso Sandra , Brunes Tuliana O , Taucce Pedro P G , Carneiro Miguel , Haddad Célio F B , Sequeira Fernando 
Published: October 2022

Abstract
Amphibians are increasingly threatened worldwide, but the availability of genomic resources that could be crucial for implementing informed conservation practices lags well behind that for other vertebrate groups. Here, we describe draft de novo genome, mitogenome, and transcriptome assemblies for the Neotropical leaf-frog Phyllomedusa bahiana native to the Brazilian Atlantic Forest and Caatinga. We used a combination of PacBio long reads and Illumina sequencing to produce a 4.74-Gbp contig-level genome assembly, which has a contiguity comparable to other recent nonchromosome level assemblies. The assembled mitogenome comprises 16,239 bp and the gene content and arrangement are similar to other Neobratrachia. RNA-sequencing from 8 tissues resulted in a highly complete (86.3%) reference transcriptome. We further use whole-genome resequencing data from P. bahiana and from its sister species Phyllomedusa burmeisteri, to demonstrate how our assembly can be used as a backbone for population genomics studies within the P. burmeisteri species group. Our assemblies thus represent important additions to the catalog of genomic resources available from amphibians.
Clinical outcomes of asymptomatic low-grade esophagitis: results from a multicenter Chinese cohort
Authors: Chen Songfeng , Xiang Xuelian , Zhang Xiaohao , Zhuang Qianjun , Tan Niandi , Hou Xun , Zhang Mengyu , Hu Junnan , Duan Chaofan , Cui Yi , Wang Jinhui , Xing Xiangbin , Zhang Nina , Xiao Yinglian 
Published: October 2022

Abstract

Background
Asymptomatic low-grade (Los Angeles Classification Grades A and B) esophagitis is common in clinical practice with unclear clinical outcomes. This study aimed to explore the clinical outcomes of asymptomatic low-grade esophagitis.

Methods
This was a multicenter cohort study conducted by three academic hospitals in China. Asymptomatic low-grade esophagitis patients between January 2015 and December 2019 were included. Mucosal healing condition 1 year after initial diagnosis, symptom outcomes, and proton-pump inhibitor (PPI) use within 1 year after initial diagnosis were studied and compared.

Results
A total of 248 asymptomatic low-grade esophagitis patients were included. Esophagitis disappeared in 76.2% of patients 1 year after initial diagnosis. In terms of symptom outcomes, 89.9% of patients did not present gastroesophageal reflux disease (GERD) symptoms within 1 year after initial diagnosis. No significant difference was found in the proportion of patients who presented GERD symptoms and in the proportion of patients with persistent esophagitis between the PPI group and the non-PPI group (all P &gt; 0.05). Patients with initial Grade B esophagitis were more likely to present follow-up GERD symptoms (16.0% vs 7.5%, P = 0.041) and had more severe follow-up esophagitis than those with Grade A (P &lt; 0.001). Patients with follow-up GERD symptoms were more likely to have persistent esophagitis than those without.

Conclusions
This study demonstrated that asymptomatic low-grade esophagitis had relatively benign clinical outcomes. Patients with initial Grade B esophagitis and patients with follow-up GERD symptoms were more likely to be those who are in genuine need of further follow-up and treatments.
The Role of Adverse Childhood Experiences in Multidimensional Nature of Subjective Age
Authors: Xie Donghong , Wang Jiwen , Huang Fan 
Published: October 2022

AbstractObjectivesAge stereotypes and expectations about one’s own aging commence in childhood, while most research focuses on predictive associations with midlife cognition and health outcomes in later life. This study instead aims to examine adverse childhood experiences (ACEs) contributing to multiple measures of subjective age (SA) among Chinese older adults and test whether these relationships differ by household registration (hukou).MethodsIn a representative sample of Chinese older adults aged 60 and older from the 2018 China Longitudinal Aging and Social Survey (n = 7,815), ordinary least squares is used to examine the associations between ACEs and 3 facets of SA: felt age, look age, and self-defined aging standard.ResultsChildhood starvation experience and limited health care access predict older felt age and look age, while parental death is associated with lower self-defined aging standard. Zooming in on hukou-specific associations shows that the dose–response relationship on older adults with rural hukou is particularly pronounced.DiscussionFindings provide empirical support for views of aging from a life-course perspective and highlight the enduring impact of ACEs for late-adulthood SA, as well as their differential influence on multiple indicators of SA. Interventions that focus on promoting health and development in childhood could potentially have effects beyond the childhood phase, and benefit for their positive aging attitude in later life.
X-ray imaging of 30 year old wine grape wood reveals cumulative impacts of rootstocks on scion secondary growth and Ravaz index
Authors: Migicovsky Zoë , Quigley Michelle Y , Mullins Joey , Ali Tahira , Swift Joel F , Agasaveeran Anita Rose , Dougherty Joseph D , Grant Brendan Michael , Korkmaz Ilayda , Malpeddi Maneesh Reddy , McNichol Emily L , Sharp Andrew W , Harris Jackie L , Hopkins Danielle R , Jordan Lindsay M , Kwasniewski Misha T , Striegler R Keith , Dowtin Asia L , Stotts Stephanie , Cousins Peter , Chitwood Daniel H 
Published: October 2022

SummaryAnnual rings from 30 year old vines in a California rootstock trial were measured to determine the effects of 15 different rootstocks on Chardonnay and Cabernet Sauvignon scions. Viticultural traits measuring vegetative growth, yield, berry quality, and nutrient uptake were collected at the beginning (1995 to 1999) and end (2017 to 2020) of the lifetime of a vineyard initially planted in 1991 and removed in 2021. X-ray Computed Tomography (CT) was used to measure ring widths in 103 vines. Ring width was modeled as a function of ring number using a negative exponential model. Early and late wood ring widths, cambium width, and scion trunk radius were correlated with 27 traits. Modeling of annual ring width shows that scions alter the width of the first rings but that rootstocks alter the decay of later rings, consistently shortening ring width throughout the lifetime of the vine. Ravaz index, juice pH, photosynthetic assimilation and transpiration rates, and instantaneous water use efficiency are correlated with scion trunk radius. Ultimately, our research indicates that rootstocks modulate secondary growth over years, altering physiology and agronomic traits. Rootstocks act in similar but distinct ways from climate to modulate ring width, which borrowing techniques from dendrochronology, can be used to monitor both genetic and environmental effects in woody perennial crop species.