bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hypoxic conditions promote a proliferative, poorly differentiated, and pro-secretory phenotype in COPD lung tissue progenitor cells in vitro
Authors: Dale Tina P. , Santer Michael D. , Haris Mohammed , Zuo Wei , Forsyth Nicholas R. 
Published: March 2022

AbstractChronic obstructive pulmonary disease patients experience variable symptoms dependent on the presence of an emphysematous versus a chronic bronchitis phenotype. Both presentations can be associated with lung tissue and systemic hypoxia, at its most severe leading to Cor pulmonale. Despite this, minimal attention has been given to the effects of hypoxia at the cellular disease level.We isolated and cultured progenitor cells from the distal lung tissue of a 64 year-old, male, emphysematous donor in ambient (21%) and hypoxic (2%) oxygen conditions. Proliferative capacity was determined on collagen coated culture plastic and growth-inactivated 3T3-J2 co-cultures. Epithelial (E-cadherin and pan-cytokeratin) and progenitor (TP63, cytokeratin 5) marker expression were examined. Expanded cells were differentiated at air-liquid interface and ciliated, mucous producing, and club cell populations identified.Isolated cells were positive for the epithelial, pan-cytokeratin and E-cadherin, and progenitor, TP63 and cytokeratin 5, cell markers at isolation and again at passage 5. Passage 5 expanded cells in hypoxia had increased the proportion of TP63 expressing cells by 10% from 51.6 ± 1.2% to 62.6 ± 2.3% (p ≤ 0.01). Proliferative capacity was greater in 3T3J2 co-cultured cells overall and in 2% oxygen this supported the emergence of a proliferation unrestricted population with a limited differentiation capacity. Cells expanded on collagen I in either oxygen underwent differentiation having been expanded with the production of ciliated cells positive for βIV tubulin, and mucin 5ac, mucin 5b and CC10 positive secretory cells. Epithelial barrier formation was reduced significantly (p ≤ 0.0001) in hypoxia-expanded cells compared to normoxia. qRT-PCR showed higher expression of mucins in 2% expanded cells, significantly so withMUC5B(P ≤ 0.05) although mucin protein secretion was greater in 21% expanded cells.Concomitantly these results demonstrate that hypoxia promotes a proliferative phenotype while reducing the overall differentiation capacity of the cells. Further, the retained differentiation potential becomes skewed to a more secretory phenotype demonstrating that hypoxia may be contributing to disease symptom and severity in COPD patients.
Systematic analysis of cilia characteristics and Hedgehog signaling in five immortal cell lines
Authors: Gómez Arianna , Van De Weghe Julie Craft , Finn Malaney , Doherty Dan 
Published: March 2022

AbstractDysfunction of the primary cilium, a microtubule-based signaling organelle, leads to genetic conditions called ciliopathies. Hedgehog (Hh) signaling is mediated by the primary cilium in vertebrates and is therefore implicated in ciliopathies; however, it is not clear which immortal cell lines are the most appropriate for modeling pathway response in human disease; therefore we systematically evaluated Hh in five commercially available, immortal mammalian cell lines: ARPE-19, HEK293T, hTERT RPE-1, NIH/3T3, and SH-SY5Y. All of the cell lines ciliated adequately for our subsequent experiments, except for SH-SY5Y which were excluded from further analysis. hTERT RPE-1 and NIH/3T3 cells relocalized Hh pathway components Smoothened (SMO) and GPR161 and upregulated Hh target genes in response to pathway stimulation. In contrast, pathway stimulation did not induce target gene expression in ARPE-19 and HEK293T cells, despite SMO and GPR161 relocalization. These data indicate that human hTERT RPE-1 cells and murine NIH/3T3 cells, but not ARPE-19 and HEK293T cells, are suitable for modeling the role of Hh signaling in ciliopathies.
The effect of migration and variation on populations of Escherichia coli adapting to complex fluctuating environments
Authors: Selveshwari S , Khaire Kaustubh Chandrakant , Kadam Aditee , Dey Sutirth 
Published: March 2022

AbstractMigration, a critical evolutionary force, can have contrasting effects on adaptation. It can aid as well as impede adaptation. The effects of migration on microbial adaptation have been studied primarily in simple constant environments. Very little is known about the effects of migration on adaptation to complex, fluctuating environments. In our study, we subjected replicate populations of Escherichia coli, adapting to complex and unpredictably fluctuating environments to different proportions of clonal ancestral immigrants. Contrary to the results from simple/constant environments, the presence of clonal immigrants reduced all measured proxies of fitness. However, migration from a source population with a greater variance in fitness resulted in no change in fitness w.r.t the no-migration control, except at the highest level of migration. Thus, the presence of variation in the immigrants could counter the adverse effects of migration in complex and unpredictably fluctuating environments. Our study demonstrates that the effects of migration are strongly dependent on the nature of the destination environment and the genetic makeup of immigrants. These results enhance our understanding of the influences of migrating populations, which could help better predict the consequences of migration.
Maximum likelihood pandemic-scale phylogenetics
Authors: De Maio Nicola , Kalaghatgi Prabhav , Turakhia Yatish , Corbett-Detig Russell , Minh Bui Quang , Goldman Nick 
Published: March 2022

SummaryPhylogenetics plays a crucial role in the interpretation of genomic data1. Phylogenetic analyses of SARS-CoV-2 genomes have allowed the detailed study of the virus’s origins2, of its international3,4and local4–9spread, and of the emergence10and reproductive success11of new variants, among many applications. These analyses have been enabled by the unparalleled volumes of genome sequence data generated and employed to study and help contain the pandemic12. However, preferred model-based phylogenetic approaches including maximum likelihood and Bayesian methods, mostly based on Felsenstein’s ‘pruning’ algorithm13,14, cannot scale to the size of the datasets from the current pandemic4,15, hampering our understanding of the virus’s evolution and transmission16. We present new approaches, based on reworking Felsenstein’s algorithm, for likelihood-based phylogenetic analysis of epidemiological genomic datasets at unprecedented scales. We exploit near-certainty regarding ancestral genomes, and the similarities between closely related and densely sampled genomes, to greatly reduce computational demands for memory and time. Combined with new methods for searching amongst candidate evolutionary trees, this results in our MAPLE (‘MAximum Parsimonious Likelihood Estimation’) software giving better results than popular approaches such as FastTree 217, IQ-TREE 218, RAxML-NG19and UShER15. Our approach therefore allows complex and accurate proba-bilistic phylogenetic analyses of millions of microbial genomes, extending the reach of genomic epidemiology. Future epidemiological datasets are likely to be even larger than those currently associated with COVID-19, and other disciplines such as metagenomics and biodiversity science are also generating huge numbers of genome sequences20–22. Our methods will permit continued use of preferred likelihood-based phylogenetic analyses.
Introgression between highly divergent sea squirt genomes: an adaptive breakthrough?
Authors: Fraïsse Christelle , Le Moan Alan , Roux Camille , Dubois Guillaume , Daguin-Thiébaut Claire , Gagnaire Pierre-Alexandre , Viard Frédérique , Bierne Nicolas 
Published: March 2022

AbstractHuman-mediated introductions are reshuffling species distribution on a global scale. Consequently, an increasing number of allopatric taxa are now brought into contact, promoting introgressive hybridization between incompletely isolated species and new adaptive gene transfer. The broadcast spawning marine species,Ciona robusta, has been recently introduced in the native range of its sister taxa,Ciona intestinalis, in the English Channel and North-East Atlantic. These sea squirts are highly divergent, yet hybridization has been reported by crossing experiments and genetic studies in the wild. Here, we examined the consequences of secondary contact betweenC. intestinalisandC. robustain the English Channel. We produced genomes phased by transmission to infer the history of divergence and gene flow, and analyzed introgressed genomic tracts. Demographic inference revealed a history of secondary contact with a low overall rate of introgression. Introgressed tracts were short, segregating at low frequency, and scattered throughout the genome, suggesting traces of past contacts during the last 30 ky. However, we also uncovered a hotspot of introgression on chromosome 5, characterized by several hundred kb-longC. robustahaplotypes segregating inC. intestinalis, that introgressed during contemporary times the last 75 years. Although locally more frequent than the baseline level of introgression,C. robustaalleles are not fixed, even in the core region of the introgression hotspot. Still, linkage-disequilibrium patterns and haplotype-based tests suggest this genomic region is under recent positive selection. We further detected in the hotspot an over-representation of candidate SNPs lying on a cytochrome P450 gene with a high copy number of tandem repeats in the introgressed alleles. Cytochromes P450 are a superfamily of enzymes involved in detoxifying exogenous compounds, constituting a promising avenue for functional studies. These findings support that introgression of an adaptive allele is possible between very divergent genomes and that anthropogenic hybridization can provide the raw material for adaptation of native lineages in the Anthropocene.
Validation of Reference Genes for RT-qPCR Relative Expression Analysis in Pre-Adult Stages ofTaenia solium
Authors: Castaneda-Carpio David , Maravi Jose , Gutierrez-Loli Renzo , Villar Valeria , Blume La Torre Juan , Del Aguila Segundo W. , Guerra-Giraldez Cristina 
Published: March 2022

SUMMARYThe larvae-to-adult development of the zoonotic parasitic tapewormTaenia soliuminvolves significant but often clinically overlooked events crucial in cestode biology. The early-adult stages can be studied in vitro, providing a valuable model to examine scolex evagination, strobilation, and worm development. Without a stage-specific transcriptome, postgenomic data exploration followed by single-gene relative expression analysis using RT-qPCR (reverse transcription-quantitative PCR) are effective strategies to study gene regulation during parasite development. However, achieving accurate comparisons with this approach requires the validation of an endogenous reference gene (RG).To address this, we analyzed the expression stability of 17 candidate reference genes (RGs), representing various biological processes, in the context of the in vitro-induced early adult stages ofT. soliumlarvae (cysts). RT-qPCR of the candidate RGs was performed on different stages, defined by distinct morphology in culture, and gene expression stability was comprehensively analyzed using the RefFinder tool. Genespgk1, bact1, mapk3, tbp, rpl13, andcox1were ranked as the most stable and were used to normalize the expression ofh2bandwnt11a, which are involved in proliferation and strobilation processes in parasitic tapeworms. This study represents the first attempt to identify reliable normalization standards for transcript analysis in the genusTaenia.
Analysis of calcium dynamics for dim-light responses in rod and cone photoreceptors
Authors: Abtout Annia , Reingruber Jürgen 
Published: March 2022

AbstractRod and cone photoreceptors in the retina of vertebrate eyes are fundamental sensory neurons underlying vision. They use a sophisticated signal transduction pathway consisting of a series of biochemical processes to convert the absorption of light into an electrical current response. Several of these processes are modulated by feedback that depends on the intracellular Ca2+ concentration. In this work we use a representative phototransduction model to study how changing the Ca2+ kinetics by fast buffering affects sensitivity and dynamics of the light response in mouse rod and cone photoreceptors. We derive analytic results for dim-light stimulations that provide quantitative and conceptual insight. We show that flash responses are monophasic with low buffering, and the change in the Ca2+ concentration occurs in proportion to the current. If the amount of fast buffering is increased, the Ca2+ kinetics becomes slowed down and delayed with respect to the current, and biphasic responses emerge (damped oscillations). This shows that a biphasic response is not necessarily a manifestation of slow buffering reactions. A phase space analysis shows that the emergence of biphasic responses depends on the ratio between the effective rate μca that controls the Ca2+ kinetics, and the dark turnover rate of cyclic GMP βd. We further investigate how the light response is altered by modifying the extracellular Ca2+ concentration. In summary, we provide a comprehensive quantitative analysis that precisely links the dynamics of Ca2+ concentration to the observed current response.
Premature translation of the zygotic genome activator Zelda is not sufficient to precociously activate gene expression
Authors: Larson Elizabeth D. , Komori Hideyuki , Fitzpatrick Zoe A. , Krabbenhoft Samuel D. , Lee Cheng-Yu , Harrison Melissa 
Published: March 2022

AbstractFollowing fertilization, the unified germ cells rapidly transition to a totipotent embryo. Maternally deposited mRNAs encode the proteins necessary for this reprogramming as the zygotic genome remains transcriptionally quiescent during the initial stages of development. The transcription factors required to activate the zygotic genome are among these maternally deposited mRNAs and are robustly translated following fertilization. In Drosophila, the mRNA encoding Zelda, the major activator of the zygotic genome, is not translated until one hour after fertilization. Here we demonstrate that zelda translation is repressed following fertilization by the TRIM-NHL protein Brain tumor (BRAT). BRAT also regulates Zelda levels in the larval neuroblast lineage. In the embryo, BRAT-mediated translational repression is regulated by the Pan Gu (PNG) kinase, which is triggered by egg activation. The PNG kinase phosphorylates translational regulators, suggesting that PNG kinase activity alleviates translational repression of zelda by BRAT and coupling translation of zelda with that of other regulators of early embryonic development. Using the premature translation of zelda in embryos lacking BRAT activity, we showed that early translation of a zygotic genome activator is not sufficient to drive precocious gene expression. Instead, Zelda-target genes showed increased expression at the time they are normally activated. We propose that transition through early development requires the integration of multiple processes, including the slowing of the nuclear division cycle and activation of the zygotic genome. These processes are coordinately controlled by PNG kinase-mediated regulation of translation.
Explainable machine learning for real-time hypoglycaemia and hyperglycaemia prediction and personalised control recommendations
Authors: Duckworth Christopher , Guy Matthew J , Kumaran Anitha , O’Kane Aisling Ann , Ayobi Amid , Chapman Adriane , Marshall Paul , Boniface Michael 
Published: March 2022

AbstractBackgroundThe occurrences of acute complications arising from hypoglycaemia and hyperglycaemia peak as young adults with type 1 diabetes (T1D) take control of their own care. Continuous glucose monitoring (CGM) devices provide real-time blood glucose readings enabling users to manage their control pro-actively. Machine learning algorithms can use CGM data to make ahead-of-time risk predictions and provide insight into an individual’s longer-term control.MethodsWe introduce explainable machine learning to make predictions of hypoglycaemia (<70mg/dL) and hyperglycaemia (>270mg/dL) 60 minutes ahead-of-time. We train our models using CGM data from 153 people living with T1D in the CITY survey totalling over 28000 days of usage, which we summarise into (short-term, medium-term, and long-term) blood glucose features along with demographic information. We use machine learning explanations (SHAP) to identify which features have been most important in predicting risk per user.ResultsMachine learning models (XGBoost) show excellent performance at predicting hypoglycaemia (AUROC: 0.998) and hyperglycaemia (AUROC: 0.989) in comparison to a baseline heuristic and logistic regression model.ConclusionsMaximising model performance for blood glucose risk prediction and management is crucial to reduce the burden of alarm-fatigue on CGM users. Machine learning enables more precise and timely predictions in comparison to baseline models. SHAP helps identify what about a CGM user’s blood glucose control has led to predictions of risk which can be used to reduce their long-term risk of complications.
Bipartite recruitment of PCH2 and COMET to the synaptonemal complex drives chromosome axis reconstruction leading to crossover restriction
Authors: Yang Chao , Sofroni Kostika , Hamamura Yuki , Hu Bingyan , Elbasi Hasibe Tunçay , Balboni Martina , Heese Maren , Schnittger Arp 
Published: March 2022

AbstractChromosome axis-associated HORMA domain proteins (HORMADs), e.g., ASY1 in Arabidopsis, are crucial for meiotic recombination. ASY1, as other HORMADs, is assembled on the axis at early meiosis and depleted when homologous chromosomes synapse. Puzzlingly, both processes are catalyzed by AAA+ ATPase PCH2 together with its cofactor COMET. Here, we show that the ASY1 remodeling complex is temporally and spatially differently assembled. While PCH2 and COMET appear to directly interact in the cytoplasm in early meiosis, PCH2 is recruited by the transverse filament protein ZYP1 and brought to the ASY1-bound COMET assuring the timely removal of ASY1 during chromosome synapsis. Since we found that the PCH2 homolog TRIP13 also binds to the ZYP1 homolog SYCP1 in mouse, we postulate that this mechanism is conserved among eukaryotes. Deleting the PCH2 binding site of ZYP1 led to a failure of ASY1 removal. Interestingly, the placement of one obligatory crossover per homologous chromosome pair, compromised by ZYP1 depletion, is largely restored in this engineered zyp1 allele suggesting that crossover assurance is promoted by synapsis. In contrast, the engineered zyp1 allele, similar to the zyp1 null mutant, showed elevated type I crossover numbers indicating that PCH2-mediated eviction of ASY1 from the axis restricts crossover formation.
Methodological Insights “Materiality is …”: sensemaking and sensegiving through storytelling
Authors: Bolt Rebecca , Tregidga Helen 
Published: March 2022

PurposeThe purpose of this paper is to explore the role and implications of storytelling and narrative as a means of making sense of, and giving sense to, the ambiguous concept of materiality.Design/methodology/approachThe use of stories was “discovered” through the authors' attempts to “make sense” of data from 16 interviews with participants from the financial and nonfinancial reporting and assurance contexts. The authors analyse the participants' use of stories through a sensemaking/sensegiving lens.FindingsWhile participants struggle to define what materiality is, they are able to tell “stories” about materiality in action. The authors find stories are a key vehicle through which participants make sense of and give sense to materiality, for themselves and (an)other. Participants tell three types of stories in sensemaking/sensegiving processes: the lived, the adopted and the hypothetical. The authors further identify “rehearsed” and “ongoing” narratives, which take any of the three story types. The use of stories to make and give sense to materiality reveals a disconnect between the static, technical definitions of materiality currently favoured by standard setters and guidance providers, and the creative authoring processes the participants employ.Practical implicationsThe authors argue for a move towards the use of stories and narratives about materiality in standard setting, specifically “materiality in action”, which the findings suggest may assist in creating shared understandings of the ambiguous concept.Originality/valueWhile previous research considers what materiality means within financial and nonfinancial reporting and assurance contexts, the authors empirically analyse how people understand and make sense/give sense to materiality. The authors also contribute to the use of sensemaking/sensegiving processes within the accounting literature.
Credit default swap prediction based on generative adversarial networks
Authors: Lin Shu-Ying , Liu Duen-Ren , Huang Hsien-Pin 
Published: March 2022

PurposeFinancial price forecast issues are always a concern of investors. However, the financial applications based on machine learning methods mainly focus on stock market predictions. Few studies have explored credit risk predictions. Understanding credit risk trends can help investors avoid market risks. The purpose of this study is to investigate the prediction model that can effectively predict credit default swaps (CDS).Design/methodology/approachA novel generative adversarial network (GAN) for CDS prediction is proposed. The authors take three features into account that are highly relevant to the future trends of CDS: historical CDS price, news and financial leverage. The main goal of this model is to improve the existing GAN-based regression model by adding finance and news feature extraction approaches. The proposed model adopts an attentional long short-term memory network and convolution network to process historical CDS data and news information, respectively. In addition to enhancing the effectiveness of the GAN model, the authors also design a data sampling strategy to alleviate the overfitting issue.FindingsThe authors conduct an experiment with a real dataset and evaluate the performance of the proposed model. The components and selected features of the model are evaluated for their ability to improve the prediction performance. The experimental results show that the proposed model performs better than other machine learning algorithms and traditional regression GAN.Originality/valueThere are very few studies on prediction models for CDS. With the proposed novel approach, the authors can improve the performance of CDS predictions. The proposed work can thereby increase the commercial value of CDS predictions to support trading decisions.