bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seeing Nemo: molecular evolution of ultraviolet visual opsins and spectral tuning of photoreceptors in anemonefishes (Amphiprioninae)
Authors: Mitchell Laurie J. , Cheney Karen L. , Chung Wen-Sung , Marshall N. Justin , Michie Kyle , Cortesi Fabio 
Published: June 2020

ABSTRACTMany animals can see ultraviolet (UV) light (shorter than 400 nm) undetectable to human vision. UV vision may have functional importance in many taxa including for foraging and communication in birds, reptiles, insects and teleost fishes. Shallow coral reefs transmit a broad spectrum of light and are rich in UV; driving the evolution of diverse spectral sensitivities in teleost reef fishes, including UV-sensitivity. However, the identities and sites of the specific visual genes that underly vision in reef fishes remain elusive and are useful in determining how molecular evolution has tuned vision to meet the ecological demands of life on the reef. We investigated the visual systems of eleven anemonefish (Amphiprioninae) species, specifically probing for the molecular pathways that facilitate UV-sensitivity. Searching the genomes of anemonefishes, we identified a total of seven functional visual genes from all five vertebrate opsin gene subfamilies. We found rare instances of UV-sensitiveSWS1opsin gene duplications, that produced two functional paralogs (SWS1αandSWS1β) and a pseudogene. We also found separateRH2Aopsin gene duplicates not yet reported in the family Pomacentridae. Finally, we report on both qualitative and quantitative aspects of opsin gene expression found in the adult retina of the false clown anemonefish (Amphiprion ocellaris), and their photoreceptor spectral sensitivities measured using microspectrophotometry.
A Mesoscale Finite Element Modelling Approach for Understanding Brain Morphology and Material Heterogeneity Effects in Chronic Traumatic Encephalopathy
Authors: Bakhtairydavijani A. , Khalid G. , Murphy M.A. , Johnson K.L. , Peterson L. E. , Jones M. , Horstemeyer M.F. , Dobbins A.C. , Prabhu R. K. 
Published: June 2020

AbstractChronic Traumatic Encephalopathy (CTE) affects a significant portion of athletes in contact sports but is difficult to quantify using clinical examinations and modelling approaches. We use anin silicoapproach to quantify CTE biomechanics using mesoscale Finite Element (FE) analysis that bridges with macroscale whole head FE analysis. The sulci geometry produces complex stress waves that interact with each another to create increased shear stresses at the sulci depth that are significantly larger than in analyses without sulci (from 0.5 kPa to 18.0 kPa). Also, Peak sulci stresses are located where CTE has been experimentally observed in the literature.Highlights3 to 5 bullet points 85 characters maxSulci introduce stress localizations at their depth in the gray matterSulci stress fields interact to produce stress concentration sites in white matterDifferentiating brain tissue properties did not significantly affect peak stresses
Spatiotemporal sequence of mesoderm and endoderm lineage segregation during mouse gastrulation
Authors: Probst Simone , Sagar  , Tosic Jelena , Schwan Carsten , Grün Dominic , Arnold Sebastian J. 
Published: June 2020

AbstractAnterior mesoderm (AM) and definitive endoderm (DE) progenitors represent the earliest embryonic cell types that are specified during germ layer formation at the primitive streak (PS) of the mouse embryo. Genetic experiments indicate that both lineages segregate fromEomesexpressing progenitors in response to different NODAL signaling levels. However, the precise spatiotemporal pattern of the emergence of these cell types and molecular details of lineage segregation remain unexplored. We combined genetic fate labeling and imaging approaches with scRNA-seq to follow the transcriptional identities and define lineage trajectories ofEomesdependent cell types. All cells moving through the PS during the first day of gastrulation expressEomes. AM and DE specification occurs before cells leave the PS from discrete progenitor populations that are generated in distinct spatiotemporal patterns. Importantly, we don’t find evidence for the existence of progenitors that co-express markers of both cell lineages suggesting an immediate and complete separation of AM and DE lineages.Summary statementCells lineages are specified in the mouse embryo already within the primitive streak whereMesp1+ mesoderm andFoxa2+ endoderm are generated in a spatial and temporal sequence from unbiased progenitors.
Estimating daily intakes of manganese due to breast milk, infant formulas, or young child nutritional beverages in the United States and France: Comparison to sufficiency and toxicity thresholds
Authors: Mitchell Erika J. , Frisbie Seth H. , Roudeau Stéphane , Carmona Asuncion , Ortega Richard 
Published: June 2020

AbstractBackgroundAlthough manganese (Mn) is an essential nutrient, recent research has revealed that excess Mn in early childhood may have adverse effects on neurodevelopment.MethodsWe estimated daily total Mn intake due to breast milk at average body weights by reviewing reported concentrations of breast milk Mn and measurements of body weight and breast milk intake at 3 weeks, 4.25 months, 7 months, and 18 months. We compared these figures to the Mn content measured in 44 infant, follow-up, and toddler formulas purchased in the United States and France. We calculated Mn content of formula products made with ultra-trace elemental analysis grade water (0 µg Mn/L) and with water containing 250 µg Mn/L, a concentration which is relatively high but less than the World Health Organization Health-based value of 400 µg Mn/L or the United States Environmental Protection Agency Health Advisory of 350 µg Mn/L.ResultsEstimated mean daily Mn intake from breast milk ranged from 1.2 µg Mn/kg/day (3 weeks) to 0.16 µg Mn/kg/day (18 months), with the highest intakes at the youngest age stage we considered, 3 weeks. Estimated daily Mn intake from formula products reconstituted with 0 µg Mn/L water ranged from 130 µg Mn/kg/day (3 weeks) to 4.8 µg Mn/kg/day (18 months) with the highest intakes at 3 weeks. Formula products provided 28 to 520 times greater than the mean daily intake of Mn from breast milk for the 4 age stages that we considered. Estimated daily Mn intake from formula products reconstituted with water containing 250 µg Mn/L ranged from 12 µg Mn/kg/day to 170 µg Mn/kg/day, which exceeds the United States Environmental Protection Agency Reference Dose of 140 µg Mn/kg/day for adults.ConclusionsMn deficiency is highly unlikely with exclusive breast milk or infant formula feeding, but established tolerable daily intake levels for Mn may be surpassed by some of these products when following labeled instructions.HighlightsMn deficiency is unlikely with exclusive breast milk or infant formula feeding.Breast milk Mn mean intake is 1.2 µg/kg/day (3 weeks)-0.16 µg/kg/day (18 months).Formula Mn intake range is 130 µg/kg/day (3 weeks)-4.8 µg/kg/day (18 months).Formula products reconstituted with 250 µg Mn/L water may exceed 140 µg Mn/kg/day.Formula products may surpass regulatory tolerable daily intake levels for Mn.
V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput sequencing data
Authors: Posada-Céspedes Susana , Seifert David , Topolsky Ivan , Metzner Karin J. , Beerenwinkel Niko 
Published: June 2020

AbstractHigh-throughput sequencing technologies are used increasingly, not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence, and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations. To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, calledngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape. V-pipe is freely available athttps://github.com/cbg-ethz/V-pipe.
Digital twinning of Cellular Capsule Technology: emerging outcomes from the perspective of porous media mechanics
Authors: Stéphane Urcun , Pierre-Yves Rohan , Wafa Skalli , Pierre Nassoy , Bordas Stéphane P.A. , Giuseppe Sciumè 
Published: June 2020

AbstractSpheroids encapsulated within alginate capsules are emerging as suitablein vitrotools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT).We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells.The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design.
Swan: a library for the analysis and visualization of long-read transcriptomes
Authors: Reese Fairlie , Mortazavi Ali 
Published: June 2020

AbstractMotivationLong-read RNA-sequencing technologies such as PacBio and Oxford Nanopore have discovered an explosion of new transcript isoforms that are difficult to visually analyze using currently available tools. We introduce the Swan Python library, which is designed to analyze and visualize transcript models.ResultsSwan finds 4,909 differentially expressed transcripts between cell lines HepG2 and HFFc6, including 279 that are differentially expressed even though the parent gene is not. Additionally, Swan discovers 1,021 reproducible exon skipping and 73 intron retention events not recorded in the GENCODE v29 annotation.AvailabilityThe Swan library for Python 3 is available on PyPi and on GitHub athttps://pypi.org/project/swan-vis/1.0/andhttps://github.com/mortazavilab/swan_paper.
MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors
Authors: Williams Justin , Xu Beisi , Putnam Daniel , Thrasher Andrew , Li Chunliang , Yang Jun , Chen Xiang 
Published: June 2020

AbstractAlthough genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities (H3K4me3 and H3K27ac enrichment) from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.
Differential expression of COVID-19-related genes in European Americans and African Americans
Authors: Singh Urminder , Wurtele Eve Syrkin 
Published: June 2020

ABSTRACTThe Coronavirus disease 2019 (COVID-19) pandemic has affected African American populations disproportionately in regards to both morbidity and mortality. A multitude of factors likely account for this discrepancy. Gene expression represents the interaction of genetics and environment. To elucidate whether levels of expression of genes implicated in COVID-19 vary in African Americans as compared to European Americans, we re-mine The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) RNA-Seq data. Multiple genes integral to infection, inflammation and immunity are differentially regulated across the two populations. Most notably, F8A2 and F8A3, which encode the HAP40 protein that mediates early endosome movement in Huntington’s Disease, are more highly expressed by up to 24-fold in African Americans. Such differences in gene expression can establish prognostic signatures and have critical implications for precision treatment of diseases such as COVID-19. We advocate routine inclusion of information such as postal code, education level, and profession (as a proxies for socioeconomic condition) and race in the metadata about each individual sampled for sequencing studies. This relatively simple change would enable large-scale data-driven approaches to dissect relationships among race, socio-economic factors, and disease.
A Genome-based Model to Predict the Virulence ofPseudomonas aeruginosaIsolates
Authors: Pincus Nathan B. , Ozer Egon A. , Allen Jonathan P. , Nguyen Marcus , Davis James J. , Winter Deborah R. , Chuang Chih-Hsien , Chiu Cheng-Hsun , Zamorano Laura , Oliver Antonio , Hauser Alan R. 
Published: June 2020

ABSTRACTVariation in the genome ofPseudomonas aeruginosa, an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence ofP. aeruginosaisolates based upon their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinicalP. aeruginosaisolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithm’s performance, suggesting instead that the virulence prediction derives from a diffuse genomic signature. These results were validated with an independent test set of 25P. aeruginosaisolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single nucleotide variants and whole genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity inP. aeruginosaand highlight the potential of this approach for predicting patient outcomes.IMPORTANCEPseudomonas aeruginosais a clinically important gram-negative opportunistic pathogen. As a species,P. aeruginosahas a large degree of heterogeneity both through variation in sequences found throughout the species (core genome) and the presence or absence of sequences in different isolates (accessory genome).P. aeruginosaisolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level ofP. aeruginosaisolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genome are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.
Trajectories of depressive symptoms among vulnerable groups in the UK during the COVID-19 pandemic
Authors: Frank Philipp , Iob Eleonora , Steptoe Andrew , Fancourt Daisy 
Published: June 2020

ABSTRACTObjectiveThe coronavirus disease 2019 (COVID-19) pandemic has affected many aspects of the human condition, including mental health and psychological wellbeing. This study examined trajectories of depressive symptoms (DST) over time among vulnerable individuals in the UK during the COVID-19 pandemic.MethodsThe sample consisted of 51,417 adults recruited from the COVID-19 Social Study. Depressive symptoms were measured on seven occasions (21st March - 2nd April), using the Patient Health Questionnaire (PHQ-9). Sociodemographic vulnerabilities included non-white ethnic background, low socio-economic position (SEP), and type of work (keyworker versus no keyworker). Health-related and psychosocial vulnerabilities included pre-existing physical and mental health conditions, experience of psychological and/or physical abuse, and low social support. Group-based DST were derived using latent growth mixture modelling and multivariate logistic regression models were fitted to examine the association between these vulnerabilities and DSTs. Model estimates were adjusted for age, sex, and suspected COVID-19 diagnosis.ResultsThree DSTs were identified: low [N=30,850 (60%)] moderate [N=14,911 (29%)], and severe [N=5,656 (11%)] depressive symptoms. DSTs were relatively stable across the first 6 weeks of lockdown. After adjusting for covariates, experiences of physical/psychological abuse (OR 13.16, 95% CI 12.95-13.37), pre-existing mental health conditions (OR 13.00 95% CI 12.87-13.109), pre-existing physical health conditions (OR 3.41, 95% CI 3.29-3.54), low social support (OR 12.72, 95% CI 12.57-12.86), and low SEP (OR 5.22, 95% CI 5.08-5.36) were significantly associated with the severe DST. No significant association was found for ethnicity (OR 1.07, 95% 0.85-1.28). Participants with key worker roles were less likely to experience severe depressive symptoms (OR 0.66, 95% 0.53-0.80). Similar but smaller patterns of associations were found for the moderate DST.ConclusionsPeople with psychosocial and health-related risk factors, as well as those with low SEP seem to be most vulnerable to experiencing moderate or severe depressive symptoms during the COVID-19 pandemic.
Detection of SARS-CoV-2 in wastewater in Japan by multiple molecular assays-implication for wastewater-based epidemiology (WBE)
Authors: Hata Akihiko , Honda Ryo , Hara-Yamamura Hiroe , Meuchi Yuno 
Published: June 2020

ABSTRACTPresence of SARS-coronavirus-2 (SARS-CoV-2) in wastewater sample has been documented in several countries. Wastewater-based epidemiology (WBE) is potentially effective for early warning of COVID-19 outbreak. The purpose of this study was to verify the detection limit of WBE for COVID-19. In total, 27 influent wastewater samples were collected from four wastewater treatment plants in Ishikawa and Toyama prefectures in Japan. During the study period, numbers of the confirmed COVID-19 cases in these prefectures increased from almost 0 to around 20 per 100,000 peoples. SARS-CoV-2 RNA in the samples were identified by several PCR-based assays. Among the 27 samples, 7 were positive for SARS-CoV-2 by at least one out of the three quantitative RT-PCR assays. These samples were also positive by RT-nested PCR assays. The detection frequency became higher when the number of total confirmed SARS-CoV-2 cases in 100,000 peoples became above 10 in each prefecture. However, SARS-CoV-2 could also be detected with a low frequency when the number was below 1.0. Considering that the number of the confirmed cases does not necessarily reflect the actual prevalence of the infection at the time point, data on the relationship between the number of infection cases and concentration in wastewater needs to be accumulated further.
Elevated levels of hoarding in ADHD: a special link with inattention
Authors: Morein-Zamir Sharon , Kasese Michael , Chamberlain Samuel R , Trachtenberg Estherina 
Published: June 2020

AbstractHoarding Disorder (HD) is under recognised and under-treated. Though HD develops by early adulthood, patients present only later in life, resulting in research based largely on samples of predominantly older females. Whilst formerly associated with Obsessive-Compulsive Disorder (OCD), it is now recognised that individuals with HD often have inattention symptoms reminiscent of Attention Deficit/Hyperactivity Disorder (ADHD). Here, we investigated HD in adults with ADHD. Patients in an ADHD clinic (n=88) reported on ADHD, HD and OCD-related symptoms, and compared with age, gender and education matched controls (n=90). Findings were assessed independently in an online UK sample to verify replication using a dimensional approach (n=220). Clinically significant hoarding symptoms were found in ~20% versus 2% of ADHD and control groups, respectively, with those with hoarding being on average in their thirties and with approximately half being male. Greater hoarding severity was noted even in the remaining patients compared with controls (d=0.89). Inattention was the only significant statistical predictor of hoarding severity in patients. Similarly, inattention, alongside depression and anxiety were the greatest predictors of hoarding in the independent sample where 3.2% identified as having clinically significant hoarding. Patients with ADHD had a high frequency of hoarding symptoms, which were specifically linked to inattention. HD should be routinely assessed in individuals with ADHD, as they do not typically disclose associated difficulties, despite these potentially leading to impaired everyday functioning. Research in HD should also investigate adults with ADHD, who are younger and with a greater prevalence of males than typical HD samples.