bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic impact of type 1 and type 2 diabetes mellitus in atrial fibrillation and the effect of severe hypoglycaemia: a nationwide cohort study
Authors: Karayiannides Stelios , Norhammar Anna , Landstedt-Hallin Lena , Friberg Leif , Lundman Pia 
Published: May 2022

Abstract

Aims
To compare prognosis between individuals without diabetes, type 1 and type 2 diabetes in a nationwide atrial fibrillation cohort in Sweden and study the significance of severe hypoglycaemia.

Methods
Using data from all-inclusive national registers, 309,611 patients with non-valvular atrial fibrillation were enrolled during 2013–2014. Of these, 2,221 had type 1 and 58,073 had type 2 diabetes. Patients were followed for all-cause mortality until 27 March 2017, and for myocardial infarction, ischaemic stroke and first-ever diagnosis of heart failure or dementia until 31 December 2015. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox and competing risk regression.

Results
Using individuals without diabetes as reference (HR = 1), the adjusted HRs in type 1 vs. type 2 diabetes were for mortality 1.87 (CI 1.73–2.02) vs. 1.51 (CI 1.47–1.55), heart failure 1.59 (CI 1.42–1.78) vs. 1.41 (CI 1.34–1.48), myocardial infarction 2.49 (CI 2.17–2.85) vs. 1.70 (CI 1.59–1.81), ischaemic stroke 1.59 (CI 1.35–1.87) vs. 1.31 (CI 1.22–1.40), and dementia 1.46 (CI 1.15–1.85) vs. 1.28 (CI 1.18–1.40). Among individuals with type 2 diabetes, those with previous severe hypoglycaemia had increased risk of mortality (HR 1.26; CI 1.17–1.36) and dementia (HR 1.37; CI 1.08–1.73) compared with those without previous severe hypoglycaemia.

Conclusion
Presence of diabetes—regardless of type— in atrial fibrillation is associated with an increased risk of premature death, cardiovascular events and dementia. This increase is more pronounced in type 1 than in type 2 diabetes. A history of severe hypoglycaemia is associated with a worsened prognosis in type 2 diabetes.
Evolutionary jumps in bacterial GC content
Authors: Mahajan Saurabh , Agashe Deepa 
Published: May 2022

Abstract
Genomic GC (Guanine-Cytosine) content is a fundamental molecular trait linked with many key genomic features such as codon and amino acid use. Across bacteria, GC content is surprisingly diverse and has been studied for many decades; yet its evolution remains incompletely understood. Since it is difficult to observe GC content evolve on laboratory time scales, phylogenetic comparative approaches are instrumental; but this dimension is rarely studied systematically in the case of bacterial GC content. We applied phylogenetic comparative models to analyze GC content evolution in multiple bacterial groups across 2 major bacterial phyla. We find that GC content diversifies via a combination of gradual evolution and evolutionary “jumps.” Surprisingly, unlike prior reports that solely focused on reductions in GC, we found a comparable number of jumps with both increased and decreased GC content. Overall, many of the identified jumps occur in lineages beyond the well-studied peculiar examples of endosymbiotic and AT-rich marine bacteria and do not support the predicted role of oxygen dependence. Our analysis of rapid and large shifts in GC content thus identifies new clades and novel contexts to further understand the ecological and evolutionary drivers of this important genomic trait.
Variation in leaf transcriptome responses to elevated ozone corresponds with physiological sensitivity to ozone across maize inbred lines
Authors: Nanni Adalena V , Morse Alison M , Newman Jeremy R B , Choquette Nicole E , Wedow Jessica M , Liu Zihao , Leakey Andrew D B , Conesa Ana , Ainsworth Elizabeth A , McIntyre Lauren M 
Published: May 2022

AbstractWe examine the impact of sustained elevated ozone concentration on the leaf transcriptome of 5 diverse maize inbred genotypes, which vary in physiological sensitivity to ozone (B73, Mo17, Hp301, C123, and NC338), using long reads to assemble transcripts and short reads to quantify expression of these transcripts. More than 99% of the long reads, 99% of the assembled transcripts, and 97% of the short reads map to both B73 and Mo17 reference genomes. Approximately 95% of the genes with assembled transcripts belong to known B73–Mo17 syntenic loci and 94% of genes with assembled transcripts are present in all temperate lines in the nested association mapping pan-genome. While there is limited evidence for alternative splicing in response to ozone stress, there is a difference in the magnitude of differential expression among the 5 genotypes. The transcriptional response to sustained ozone stress in the ozone resistant B73 genotype (151 genes) was modest, while more than 3,300 genes were significantly differentially expressed in the more sensitive NC338 genotype. There is the potential for tandem duplication in 30% of genes with assembled transcripts, but there is no obvious association between potential tandem duplication and differential expression. Genes with a common response across the 5 genotypes (83 genes) were associated with photosynthesis, in particular photosystem I. The functional annotation of genes not differentially expressed in B73 but responsive in the other 4 genotypes (789) identifies reactive oxygen species. This suggests that B73 has a different response to long-term ozone exposure than the other 4 genotypes. The relative magnitude of the genotypic response to ozone, and the enrichment analyses are consistent regardless of whether aligning short reads to: long read assembled transcripts; the B73 reference; the Mo17 reference. We find that prolonged ozone exposure directly impacts the photosynthetic machinery of the leaf.
Serotonin signals through postsynaptic Gαq, Trio RhoGEF, and diacylglycerol to promote Caenorhabditis elegans egg-laying circuit activity and behavior
Authors: Dhakal Pravat , Chaudhry Sana I , Signorelli Rossana , Collins Kevin M 
Published: May 2022

Abstract
Activated Gαq signals through phospholipase-Cβ and Trio, a Rho GTPase exchange factor (RhoGEF), but how these distinct effector pathways promote cellular responses to neurotransmitters like serotonin remains poorly understood. We used the egg-laying behavior circuit of Caenorhabditis elegans to determine whether phospholipase-Cβ and Trio mediate serotonin and Gαq signaling through independent or related biochemical pathways. Our genetic rescue experiments suggest that phospholipase-Cβ functions in neurons while Trio Rho GTPase exchange factor functions in both neurons and the postsynaptic vulval muscles. While Gαq, phospholipase-Cβ, and Trio Rho GTPase exchange factor mutants fail to lay eggs in response to serotonin, optogenetic stimulation of the serotonin-releasing HSN neurons restores egg laying only in phospholipase-Cβ mutants. Phospholipase-Cβ mutants showed vulval muscle Ca2+ transients while strong Gαq and Trio Rho GTPase exchange factor mutants had little or no vulval muscle Ca2+ activity. Treatment with phorbol 12-myristate 13-acetate that mimics 1,2-diacylglycerol, a product of PIP2 hydrolysis, rescued egg-laying circuit activity and behavior defects of Gαq signaling mutants, suggesting both phospholipase-C and Rho signaling promote synaptic transmission and egg laying via modulation of 1,2-diacylglycerol levels. 1,2-Diacylglycerol activates effectors including UNC-13; however, we find that phorbol esters, but not serotonin, stimulate egg laying in unc-13 and phospholipase-Cβ mutants. These results support a model where serotonin signaling through Gαq, phospholipase-Cβ, and UNC-13 promotes neurotransmitter release, and that serotonin also signals through Gαq, Trio Rho GTPase exchange factor, and an unidentified, phorbol 12-myristate 13-acetate-responsive effector to promote postsynaptic muscle excitability. Thus, the same neuromodulator serotonin can signal in distinct cells and effector pathways to coordinate activation of a motor behavior circuit.
Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data
Authors: Mas-Sandoval Alex , Pope Nathaniel S , Nielsen Knud Nor , Altinkaya Isin , Fumagalli Matteo , Korneliussen Thorfinn Sand 
Published: May 2022

Abstract

Background
The site frequency spectrum summarizes the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping.

Results
Here we design and implement a method to efficiently and accurately estimate the multidimensional joint site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximizes a likelihood function that represents the probability of the sequencing data observed given a multidimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximization algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. On the basis of extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen Neonectria neomacrospora, results recapitulate the patterns of population differentiation generated using the original high-coverage data.

Conclusion
The new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage datasets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.
NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer
Authors: Amgad Mohamed , Atteya Lamees A , Hussein Hagar , Mohammed Kareem Hosny , Hafiz Ehab , Elsebaie Maha A T , Alhusseiny Ahmed M , AlMoslemany Mohamed Atef , Elmatboly Abdelmagid M , Pappalardo Philip A , Sakr Rokia Adel , Mobadersany Pooya , Rachid Ahmad , Saad Anas M , Alkashash Ahmad M , Ruhban Inas A , Alrefai Anas , Elgazar Nada M , Abdulkarim Ali , Farag Abo-Alela , Etman Amira , Elsaeed Ahmed G , Alagha Yahya , Amer Yomna A , Raslan Ahmed M , Nadim Menatalla K , Elsebaie Mai A T , Ayad Ahmed , Hanna Liza E , Gadallah Ahmed , Elkady Mohamed , Drumheller Bradley , Jaye David , Manthey David , Gutman David A , Elfandy Habiba , Cooper Lee A D 
Published: May 2022

Abstract

Background
Deep learning enables accurate high-resolution mapping of cells and tissue structures that can serve as the foundation of interpretable machine-learning models for computational pathology. However, generating adequate labels for these structures is a critical barrier, given the time and effort required from pathologists.

Results
This article describes a novel collaborative framework for engaging crowds of medical students and pathologists to produce quality labels for cell nuclei. We used this approach to produce the NuCLS dataset, containing &gt;220,000 annotations of cell nuclei in breast cancers. This builds on prior work labeling tissue regions to produce an integrated tissue region- and cell-level annotation dataset for training that is the largest such resource for multi-scale analysis of breast cancer histology. This article presents data and analysis results for single and multi-rater annotations from both non-experts and pathologists. We present a novel workflow that uses algorithmic suggestions to collect accurate segmentation data without the need for laborious manual tracing of nuclei. Our results indicate that even noisy algorithmic suggestions do not adversely affect pathologist accuracy and can help non-experts improve annotation quality. We also present a new approach for inferring truth from multiple raters and show that non-experts can produce accurate annotations for visually distinctive classes.

Conclusions
This study is the most extensive systematic exploration of the large-scale use of wisdom-of-the-crowd approaches to generate data for computational pathology applications.
HaploMaker: An improved algorithm for rapid haplotype assembly of genomic sequences
Authors: Fruzangohar Mario , Timmins William A , Kravchuk Olena , Taylor Julian 
Published: May 2022

Abstract

Background
In diploid organisms, whole-genome haplotype assembly relies on the accurate identification and assignment of heterozygous single-nucleotide polymorphism alleles to the correct homologous chromosomes. This appropriate phasing of these alleles ensures that combinations of single-nucleotide polymorphisms on any chromosome, called haplotypes, can then be used in downstream genetic analysis approaches including determining their potential association with important phenotypic traits. A number of statistical algorithms and complementary computational software tools have been developed for whole-genome haplotype construction from genomic sequence data. However, many algorithms lack the ability to phase long haplotype blocks and simultaneously achieve a competitive accuracy.

Results
In this research we present HaploMaker, a novel reference-based haplotype assembly algorithm capable of accurately and efficiently phasing long haplotypes using paired-end short reads and longer Pacific Biosciences reads from diploid genomic sequences. To achieve this we frame the problem as a directed acyclic graph with edges weighted on read evidence and use efficient path traversal and minimization techniques to optimally phase haplotypes. We compared the HaploMaker algorithm with 3 other common reference-based haplotype assembly tools using public haplotype data of human individuals from the Platinum Genome project. With short-read sequences, the HaploMaker algorithm maintained a competitively low switch error rate across all haplotype lengths and was superior in phasing longer genomic regions. For longer Pacific Biosciences reads, the phasing accuracy of HaploMaker remained competitive for all block lengths and generated substantially longer block lengths than the competing algorithms.

Conclusions
HaploMaker provides an improved haplotype assembly algorithm for diploid genomic sequences by accurately phasing longer haplotypes. The computationally efficient and portable nature of the Java implementation of the algorithm will ensure that it has maximal impact in reference-sequence–based haplotype assembly applications.
A decade of GigaScience: 10 years of the evolving genomic and biomedical standards landscape
Authors: Schriml Lynn M 
Published: May 2022

Abstract
Standardization of omics data drives FAIR data practices through community-built genomic data standards and biomedical ontologies. Use of standards has progressed from a foreign concept to a sought-after solution, moving from efforts to coordinate data within individual research projects to research communities coming together to identify solutions to common challenges. Today we are seeing the benefits of this multidecade groundswell to coordinate, exchange, and reuse data; to compare data across studies; and to integrate data across previously siloed resources.
Integrated multi-omics analysis provides insights into genome evolution and phosphorus deficiency adaptation in pigeonpea (Cajanus cajan)
Authors: Liu Chun , Tai Yuling , Luo Jiajia , Wu Yuanhang , Zhao Xingkun , Dong Rongshu , Ding Xipeng , Zhao Shancen , Luo Lijuan , Liu Pandao , Liu Guodao 
Published: May 2022

Abstract
Pigeonpea (Cajanus cajan) is an important legume food crop and plays a crucial role in a secure food supply in many developing countries. Several previous studies have suggested that pigeonpea has great potential for phosphorus (P) deficiency tolerance, but little is known about the underlying mechanism. In this study, the physiological and molecular responses of pigeonpea roots to phosphate (Pi) starvation were investigated through integrating phenotypic, genomic, transcriptomic, metabolomic, and lipidomic analyses. The results showed that low-Pi treatment increased total root length, root surface area, and root acid phosphatase activity, and promoted the secretion of organic acids (e.g. citric acids, piscidic acids, and protocatechuic acids) and the degradation of phospholipids and other P-containing metabolites in the roots of pigeonpea. Consistent with the morphological, physiological, and biochemical changes, a large number of genes involved in these Pi-starvation responses were significantly upregulated in Pi-deficient pigeonpea roots. Among these Pi-starvation response genes upregulated by low-Pi treatment, four gene families were expanded through recent tandem duplication in the pigeonpea genome, namely phosphate transporter 1 (PHT1), phosphoethanolamine/phosphocholine phosphatase (PECP), fasciclin-like arabinogalactan protein (FLA), and glutamate decarboxylase (GAD). These gene families may be associated with Pi uptake from the soil, phospholipid recycling, root morphological remodeling, and regulation of organic acid exudation. Taken together, our results suggest that pigeonpea employs complex Pi-starvation responses to strengthen P acquisition and utilization during low-Pi stress. This study provides new insights into the genome evolution and P deficiency adaptation mechanism of pigeonpea.
Genome-wide clonal variability in European pear “Rocha” using high-throughput sequencing
Authors: Serra Octávio , de Sousa Rui Maia , Guimarães Joana Bagoin , Matos José , Vicente Patricia , de Sousa Miguel Leão , Simões Fernanda 
Published: May 2022

Abstract
Pears (Pyrus) are one of the most economically important fruits worldwide. The Pyrus genus is characterized by a high degree of genetic variability between species and interspecific hybrids, and several studies have been performed to assess this variability for both cultivated and wild accessions. These studies have mostly been limited by the resolving power of traditional molecular markers, although in the recent past the availability of reference genome sequences or SNP arrays for pear have enhanced the capability of high-resolution genomics studies. These tools can also be applied to better understand the intra-varietal (or clonal) variability in pear. Here we report the first high resolution genomics analysis of a pear clonal population using whole genome sequencing (WGS). Results showed unique signatures for the accumulation of mutations and transposable element insertions in each clone, which are likely related to their history of propagation and cultivation. The nucleotide diversity remained low in the clonal collection with the exception of few genomic windows, suggesting that balancing selection may be occurring. These windows included mainly genes related to plant fertility. Regions with higher mutational load were partially associated with transcription factors, probably reflecting the distinctive phenotypes in the collection. The annotation of variants also revealed the theoretical disruption of relevant genes in pear. Taken together, the results from this study show that pear clones accumulate mutations differently, and that those mutations can play a role on pear phenotypes, meaning that the study of pear clonal populations can be relevant in genetic studies, mainly when comparing with traditional association studies.
Comparison of Performances of Adalimumab Biosimilars SB5, ABP501, GP2017, and MSB11022 in Treating Patients with Inflammatory Bowel Diseases: A Real-Life, Multicenter, Observational Study
Authors: Tursi Antonio , Mocci Giammarco , Allegretta Leonardo , Aragona Giovanni , Bianco Maria Antonia , Colucci Raffaele , Cuomo Antonio , Della Valle Nicola , Ferronato Antonio , Forti Giacomo , Gaiani Federica , Giorgetti GianMarco , Graziani Maria Giovanna , Lofano Katia , Lorenzetti Roberto , Larussa Tiziana , Penna Antonio , Pica Roberta , Pranzo Giuseppe , Rodino’ Stefano , Scarcelli Antonella , Zampaletta Costantino , Bassotti Gabrio , Cazzato Alessia Immacolata , Chiri Stefania , Clemente Valeria , Cocco Andrea , de’ Angelis Gianluigi , Donnarumma Laura , Faggiani Roberto , Graziosi Camilla , Le Grazie Marco , Luzza Francesco , Meucci Costantino , Monterubbianesi Rita , Pagnini Cristiano , Perazzo Patrizia , Picchio Marcello , Sacco Rodolfo , Sebkova Ladislava , Serio Mariaelena , Napolitano Daniele , Pugliese Daniela , Scaldaferri Franco , Schiavoni Elisa , Turchini Laura , Armuzzi Alessandro , Elisei Walter , Maconi Giovanni , Papa Alfredo 
Published: May 2022

Abstract

Background
Adalimumab (ADA) biosimilars have entered the therapeutic armamentarium of inflammatory bowel disease (IBD), allowing for the treatment of a greater number of patients for their reduced cost than the originator. However, comparative data on the efficacy and safety of the various ADA biosimilars remains scarce.
We compare the efficacy and safety of ADA biosimilars SB5, ABP501, GP2017, and MSB11022 in treating IBD outpatients in a real-life Italian setting.

Methods
A retrospective analysis was performed on consecutive IBD outpatients with complete clinical, laboratory, and endoscopic data. Clinical activity was measured using the Mayo score in ulcerative colitis (UC) and the Harvey-Bradshaw Index in Crohn’s disease (CD). The primary endpoints were the following: (1) induction of remission in patients new to biologics and patients new to ADA but previously exposed to other anti–tumor necrosis factor agents or other biologics; (2) maintenance of remission in patients switched from the ADA originator to an ADA biosimilar; and (3) safety of various biosimilars.

Results
A total of 533 patients were enrolled according to the inclusion criteria: 162 patients with UC and 371 patients with CD. Clinical remission was obtained in 79.6% of patients new to biologics and 59.2% of patients new to ADA but not to other biologics; clinical remission was maintained in 81.0% of patients switched from the originator, and adverse events were recorded in 6.7% of patients. There was no significant difference between the 4 ADA biosimilars for each predetermined endpoint.

Conclusions
Adalimumab biosimilars are effective and safe in IBD treatment, both in new patients and in patients switched from the ADA originator. No difference in efficacy and safety was found between ADA biosimilars.
Artificial intelligence for water–energy nexus demand forecasting: a review
Authors: Alhendi Alya A , Al-Sumaiti Ameena S , Elmay Feruz K , Wescaot James , Kavousi-Fard Abdollah , Heydarian-Forushani Ehsan , Alhelou Hassan Haes 
Published: May 2022

Abstract
Demand forecasting is an essential stage in the plan and management of resources for water and electrical utilities. With the emerging of the concept of water–energy nexus and the dependence of both resources on each other, intelligent approaches are needed for such resources’ prediction in smart communities. Over the past few decades, extensive research has been devoted to develop or improve forecasting techniques to accurately estimate the future demand. The purpose of this paper is to review the most important methods in the demand forecasting of both water and energy, focusing mainly on the most recent advancements and future possible trends, hence providing a guide and insight for future research in the field. With the recent developments in artificial intelligence, it has been observed that most research work in this area highlight the artificial intelligence–based models as promising approaches for short-term demand forecasting in terms of performance evaluation or improvement in accuracy. Finally, all metrics used by researchers to assess the water/energy demand forecast are gathered and compared to provide a solid ground for the future works.