bluuebunny/crossref_metadata_2025_split huggingface dataset:
Behavioral and neural decomposition of skull-induced death awareness
Authors: Gao Tianyu , Pu Yue , Zhou Jingyi , Zheng Guo , Zhou Yuqing , Han Shihui 
Published: April 2020

AbstractDeath awareness influences multiple aspects of human lives, but its psychological constructs and underlying brain mechanisms remain unclear. We address these by measuring behavioral and brain responses to images of human skulls. We show that skulls relative to control stimuli delay responses to life-related words but speed responses to death-related words. Skulls compared to the control stimuli induce early deactivations in the posterior ventral temporal cortex followed by activations in the posterior and anterior ventral temporal cortices. The early and late neural modulations by perceived skulls respectively predict skull-induced changes of behavioral responses to life- and death-related words and the early neural modulation further predicts death anxiety. Our findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life.One sentence summaryBehavioral and brain imaging findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life.
Cost-effectiveness of genetic and clinical predictors for choosing combined psychotherapy and pharmacotherapy in major depression
Authors: Fabbri Chiara , Kasper Siegfried , Zohar Joseph , Souery Daniel , Montgomery Stuart , Albani Diego , Forloni Gianluigi , Ferentinos Panagiotis , Rujescu Dan , Mendlewicz Julien , Serretti Alessandro , Lewis Cathryn M. 
Published: April 2020

AbstractBackgroundPredictors of treatment outcome in major depressive disorder (MDD) could contribute to evidence-based therapeutic choices. This study tested the cost-effectiveness of a pharmacogenetic and clinical predictive model (PGx-CL-R) vs a clinical risk (CL-R) predictive model in guiding the assignment of combined pharmacotherapy and psychotherapy vs pharmacotherapy in MDD.MethodsWe hypothesized that the prescription of combined treatment, a strategy with evidence of increased efficacy vs pharmacotherapy, may be optimized based on the baseline risk of pharmacotherapy resistance, estimated through PGx-CL-R or CL-R predictive models. Both strategies were compared to standard care (ST, pharmacotherapy to all subjects). Treatment effects, costs and utilities (quality adjusted life years, QALYs) were based on the literature and included in a three-years Markov model.ResultsCL-R was cost-effective compared to PGx-CL-R, with ICER (incremental cost effect ratio) of £2341 (CL-R) and £3937 (PGx-CL-R) per QALY compared to ST. PGx-CL-R had similar or better ICER compared to ST only when 1) the cost of genotyping was £100 per subject or less or 2) the sensitivity of the PGx-CL-R test was at least 0.90 and the specificity at least 0.85. CL-R had ICER of £3664 and of £4110 when the CL-R model was tested in two independent samples.Limitationslack of validation in clinical trial.ConclusionsPrediction of pharmacotherapy resistance according to clinical risk might be a cost-effective strategy if confirmed on large samples from the general population. Combined treatment with drugs having a very good tolerability profile could be a cheaper alternative to psychotherapy.
Blood glucose levels in elderly subjects with type 2 diabetes during COVID-19 outbreak: a retrospective study in a single center
Authors: Xue Ting , Li Qianwen , Zhang Qiongyao , Lin Wei , Wen Junping , Li Li , Chen Gang 
Published: April 2020

AbstractAimsIdeal glycemic control is of great importance for diabetic patients during public health emergencies of infectious diseases as long-term hyperglycemic are not only associated with chronic complications but also vital drivers of common and life-threatening infections. The present study was designed to investigate the changes of blood glucose levels in elderly subjects with type 2 diabetes(T2D) during COVID-19 outbreak.MethodsThis retrospective study focused on the T2D outpatients at Fujian Provincial Hospital aged 65 years old and above who received baseline test for fasting plasma glucose and/or glycated hemoglobin (HbA1c) between January 1, 2019 and March 8, 2019 and were followed up on fasting plasma glucose and/or HbA1c in the same period in 2020. The baseline and follow-up data were analyzed with the paired-samples T-test.ResultsA total of 135 elderly subjects with T2D with baseline and follow-up fasting plasma glucose and 50 elderly subjects with T2D with baseline and follow-up HbA1c were analyzed, respectively. The baseline and follow-up fasting plasma glucose were 7.08 ± 1.80 and 7.48±2.14 mmol/L, respectively (P=0.008). The baseline and follow-up HbA1c were 7.2±1.7% and 7.4±1.8%, respectively (P=0.158).ConclusionsElderly subjects with T2D had higher fasting plasma glucose levels during COVID-19 outbreak. We should pay more attension to the management of diabetics during public health emergencies.
Association of extended dosing intervals or delays in pembrolizumab-based regimens with survival outcomes in advanced non-small cell lung cancer
Authors: Sehgal Kartik , Bulumulle Anushi , Brody Heather , Gill Ritu R. , Macherla Shravanti , Qilleri Aleksandra , McDonald Danielle C. , Cherry Cynthia R. , Shea Meghan , Huberman Mark S. , VanderLaan Paul A. , Weiss Glen J. , Walker Paul R. , Costa Daniel B. , Rangachari Deepa 
Published: April 2020

AbstractBackgroundBesides modeling/simulation-based analysis, no post-approval studies have evaluated optimal administration frequency of pembrolizumab in non-small cell lung cancer (NSCLC).Patients and MethodsWe performed a multicenter retrospective cohort study to evaluate association between survival outcomes and treatment extensions/delays of pembrolizumab-based regimens in advanced NSCLC patients. Those who had received at least four cycles in routine practice were divided into two groups: non-standard (Non-Std: ≥2 cycles at intervals >3weeks ±3days) and standard (Std: all cycles every 3weeks or 1 cycle >3weeks ±3days).ResultsAmong 150 patients, 92 (61%) were eligible for the study (Non-Std:27, Std:65). Reasons for patients with extensions/delays in the Non-Std group included: immune-related adverse events (irAEs,33%), non-irAE-related medical issues (26%), and patient-physician preference (41%). Non-Std group was more likely to have higher PD-L1 tumor proportion score, higher number of treatment cycles and pembrolizumab monotherapy. Univariate and 6-month landmark analyses showed longer median overall survival (OS) and progression-free survival (PFS) in Non-Std group compared to the Std group. After multivariable adjustment for confounding factors, there was no significant difference in OS [HR 1.1 (95%C.I.: 0.3–4.7), p=0.874] or PFS [HR 2.7 (95%C.I.: 0.8–8.8), p=0.094] between the two groups.ConclusionOur study shows that a significant proportion of advanced NSCLC patients receive pembrolizumab-based regimens with extended intervals or delays in routine clinical practice and with similar outcomes to those receiving treatment at label-specified 3-week intervals. Given the durability of benefit seen and the potential for cost reduction and decreased infusion frequency in these patients, this requires validation in prospective trials.MicroAbstractThe most cost-effective administration frequency of pembrolizumab in advanced non-small cell lung cancer (NSCLC) is unknown. We found that a significant proportion of these patients receive pembrolizumab-based regimens with extended intervals or delays in routine practice, with similar outcomes to those on label-specified 3-week interval treatments. Prospective evaluation of alternative dosing strategies is warranted to develop a more fiscally viable and patient-centered model.
Differences in power-law growth over time and indicators of COVID-19 pandemic progression worldwide
Authors: Merrin Jack 
Published: April 2020

1AbstractAn automated statistical and error analysis of 45 countries or regions with more than 1000 cases of COVID-19 as of March 28, 2020, has been performed. This study reveals differences in the rate of disease spreading rate over time in different countries. This survey observes that most countries undergo a beginning exponential growth phase, which transitions into a power-law phase, as recently suggested by Ziff and Ziff. Tracking indicators of growth, such as the power-law exponent, are a good indication of the relative danger different countries are in and show when social measures are effective towards slowing the spread. The data compiled here are usefully synthesizing a global picture, identifying country to country variation in spreading, and identifying countries most at risk. This analysis may factor into how best to track the effectiveness of social distancing policies and quarantines in real-time as data is updated each day.
Phenotypic Associations and Shared Genetic Etiology between Bipolar Disorder and Cardiometabolic Traits
Authors: Fürtjes Anna E. , Coleman Jonathan R.I. , Tyrrell Jess , Lewis Cathryn M. , Hagenaars Saskia P. 
Published: April 2020

AbstractBackgroundPeople with bipolar disorder (BPD) are more likely to die prematurely, which is partly attributed to comorbid cardiometabolic traits. BPD has a bidirectional relationship with cardiometabolic traits, but their shared etiology is poorly understood. This study aimed to examine the phenotypic associations and shared genetic etiology between BPD and various cardiometabolic traits.MethodsIn a subset of the UK Biobank sample (N = 67,317) we investigated phenotypic associations between BPD (n = 4,155) and cardiometabolic traits, represented by biomarkers, anthropometric traits and cardiometabolic diseases. To determine the shared genetic etiology, polygenic risk scores and genetic correlations were calculated between BPD and these traits.ResultsSeveral cardiometabolic traits were significantly associated with increased risk for BPD, namely low total cholesterol, low high-density lipoprotein cholesterol, high triglycerides, high glycated haemoglobin (HbA 1c), low systolic blood pressure, high body mass index, high waist-to-hip ratio, as well as stroke, coronary artery disease and type 2 diabetes diagnosis. Polygenic risk score regressions showed that higher polygenic risk for triglycerides, waist-to-hip ratio, coronary artery disease, and type 2 diabetes was associated with increased risk for bipolar disorder. These associations were not replicated when using genetic correlations.ConclusionsThis large study identified phenotypic cardiometabolic risk factors for BPD. Moreover, it found that comorbidities between BPD and waist-to-hip ratio, triglycerides, type 2 diabetes and coronary artery disease may be based on shared genetic etiology. These results provide a better understanding of the phenotypic and genetic comorbidity between BPD and cardiometabolic traits.
Metagenome-Assembled Genome Binning Methods with Short Reads Disproportionately Fail for Plasmids and Genomic Islands
Authors: Maguire Finlay , Jia Baofeng , Gray Kristen , Lau Wing Yin Venus , Beiko Robert G. , Brinkman Fiona S.L. 
Published: April 2020

AbstractMetagenomic methods are an important tool in the life sciences, as they enable simultaneous characterisation of all microbes in a community without time-consuming and bias-inducing culturing. Metagenome-assembled genome (MAG) binning methods have emerged as a promising approach to recover individual genomes from metagenomic data. However, MAG binning has not been well assessed for its ability to recover mobile genetic elements (MGEs), such as plasmids and genomic islands (GIs), that have very high clinical/agricultural/environmental importance. Certain antimicrobial resistance (AMR) genes and virulence factor (VF) genes are noted to be disproportionately associated with MGEs, making studying their transmission a public health priority. However, the variable copy number and sequence composition of MGEs relative to the majority of the host genome makes them potentially problematic for MAG binning methods. To systematically investigate this, we simulated a low-complexity metagenome comprising 30 GI-rich and plasmid-containing bacterial genomes. MAGs were then recovered using 12 current prediction pipelines and evaluated for recovery of MGE-associated AMR/VF genes. Here we show that while 82-94% of chromosomes could be correctly recovered and binned, only 38-44% of GIs were recovered and, even more notably, only 1-29% of plasmid sequences were found. Most strikingly, no plasmid-borne VF or AMR genes were recovered and within GIs, only between 0-45% of AMR or VF genes were identified. We conclude that short-read MAGs are largely ineffective for the analysis of mobile genes, including those of public-health importance like AMR and VF genes. We propose that microbiome researchers should instead primarily utilise unassembled short reads and/or long-read approaches to more accurately analyse metagenomic data
Dynamic structural order of a low complexity domain facilitates assembly of intermediate filaments
Authors: Sysoev Vasily O. , Kato Masato , Sutherland Lillian , Hu Rong , McKnight Steven L. , Murray Dylan T. 
Published: April 2020

AbstractThe coiled-coil domains of intermediate filament (IF) proteins are flanked by regions of low sequence complexity. Whereas IF coiled-coil domains assume dimeric and tetrameric conformations on their own, maturation of eight tetramers into cylindrical IFs is dependent upon either “head” or “tail” domains of low sequence complexity. Here we confirm that the tail domain required for assembly ofDrosophilaTm1 IFs functions by forming labile cross-β interactions. These interactions are seen in polymers made from the tail domain alone as well as assembled IFs formed by the intact Tm1 protein. The ability to visualize such interactionsin situwithin the context of a discrete cellular assembly lends support to the concept that equivalent interactions may be used in organizing other dynamic aspects of cell morphology.One Sentence SummaryA new form of protein folding that interconverts between the structured and unstructured states controls assembly of intermediate filaments.
A demogenetic individual based model for the evolution of traits and genome architecture under sexual selection
Authors: Chevalier Louise , De Coligny François , Labonne Jacques 
Published: April 2020

AbstractSexual selection has long been known to favor the evolution of mating behaviors such as mate preference and competitiveness, and to affect their genetic architecture, for instance by favoring genetic correlation between some traits. Reciprocally, genetic architecture can affect the expression and the evolvability of traits and mating behaviors. But sexual selection is highly context-dependent, making interactions between individuals a central process in evolution, governing the transmission of genotypes to the next generation. This loop between the genetic structure conditioning the expression and evolution of traits and behaviour, and the feedback of this phenotypic evolution on the architecture of the genome in the dynamic context of sexual selection, has yet to be thoroughly investigated. We argue that demogenetic agent-based models (DG-ABM) are especially suited to tackle such a challenge because they allow explicit modelling of both the genetic architecture of traits and the behavioural interactions in a dynamic population context. We here present a DG-ABM able to simultaneously track individual variation in traits (such as gametic investment, preference, competitiveness), fitness and genetic architecture throughout evolution. Using two simulation experiments, we compare various mating systems and show that behavioral interactions during mating triggered some complex feedback in our model, between fitness, population demography, and genetic architecture, placing interactions between individuals at the core of evolution through sexual selection. DG-ABMs can, therefore, relate to theoretical patterns expected at the population level from simpler analytical models in evolutionary biology, and at the same time provide a more comprehensive framework regarding individual trait and behaviour variation, that is usually envisioned separately from genome architecture in behavioural ecology.
A novel CRISPR-based malaria diagnostic capable ofPlasmodiumdetection, speciation, and drug-resistance genotyping
Authors: Cunningham CH , Hennelly CM , Lin JT , Ubalee R , Boyce RM , Mulogo EM , Hathaway N , Thwai KL , Phanzu F , Kalonji A , Mwandagalirwa K , Tshefu A , Meshnick SR , Juliano JJ , Parr JB 
Published: April 2020

ABSTRACTCRISPR-based diagnostics are a new class of highly sensitive and specific assays with multiple applications in infectious disease diagnosis. SHERLOCK, or Specific High-Sensitivity Enzymatic Reporter UnLOCKing, is one such CRISPR-based diagnostic that combines recombinase polymerase pre-amplification, CRISPR-RNA base-pairing, and LwCas13a activity for nucleic acid detection. We developed SHERLOCK assays for malaria capable of detecting allPlasmodiumspecies known to cause malaria in humans and species-specific detection ofP. vivaxandP. falciparum, the species responsible for the majority of malaria cases worldwide. We validated these assays against parasite genomic DNA and achieved analytical sensitivities ranging from 2.5-18.8 parasites per reaction. We further tested these assays using a diverse panel of 123 clinical samples from the Democratic Republic of the Congo, Uganda, and Thailand and pools ofAnophelesmosquitoes from Thailand. When compared to real-time PCR, theP. falciparumassay achieved 94% sensitivity and 94% specificity in clinical samples. In addition, we developed a SHERLOCK assay capable of detecting the dihydropteroate synthetase (dhps) single nucleotide variant A581G associated withP. falciparumsulfadoxine-pyrimethamine resistance. Compared to amplicon-based deep sequencing, thedhpsSHERLOCK assay achieved 73% sensitivity and 100% specificity when applied to a panel of 43 clinical samples, with false-negative calls only at lower parasite densities. These novel SHERLOCK assays have potential to spawn a new generation of molecular diagnostics for malaria and demonstrate the versatility of CRISPR-based diagnostic approaches.One-sentence summaryNovel malaria SHERLOCK assays enabled robust detection, speciation, and genotyping ofPlasmodium spp. in diverse samples collected in Africa and Asia.
aradeepopsis: From images to phenotypic traits using deep transfer learning
Authors: Hüther Patrick , Schandry Niklas , Jandrasits Katharina , Bezrukov Ilja , Becker Claude 
Published: April 2020

AbstractLinking plant phenotype to genotype, i.e., identifying genetic determinants of phenotypic traits, is a common goal of both plant breeders and geneticists. While the ever-growing genomic resources and rapid decrease of sequencing costs have led to enormous amounts of genomic data, collecting phenotypic data for large numbers of plants remains a bottleneck. Many phenotyping strategies rely on imaging plants, which makes it necessary to extract phenotypic measurements from these images rapidly and robustly. Common image segmentation tools for plant phenotyping mostly rely on color information, which is error-prone when either background or plant color deviate from the underlying expectations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner.aradeepopsiswas built around the deep-learning model DeepLabV3+ that was re-trained for segmentation ofArabidopsis thalianarosettes. It uses semantic segmentation to classify leaf tissue into up to three categories: healthy, anthocyanin-rich, and senescent. This makesaradeepopsisparticularly powerful at quantitative phenotyping from early to late developmental stages, of mutants with aberrant leaf color and/or phenotype, and of plants growing in stressful conditions where leaf color may deviate from green. Using our tool on a panel of 210 natural Arabidopsis accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to map known loci related to anthocyanin production and early necrosis using thearadeepopsisoutput in genome-wide association analyses. Our pipeline is able to handle images of diverse origins, image quality, and background composition, and could even accurately segment images of a distantly related Brassicaceae. Because it can be deployed on virtually any common operating system and is compatible with several high-performance computing environments,aradeepopsiscan be used independently of bioinformatics expertise and computing resources.aradeepopsisis available athttps://github.com/Gregor-Mendel-Institute/aradeepopsis.
Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge
Authors: Hem Ingeborg Gullikstad , Selle Maria Lie , Gorjanc Gregor , Fuglstad Geir-Arne , Riebler Andrea 
Published: April 2020

AbstractWe propose a novel Bayesian approach that robustifies genomic modelling by leveraging expert knowledge through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and non-additive genetic variation, which leads to an intuitive model parameterization that can be visualised as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which expert knowledge is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates expert knowledge through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of expert knowledge in the context of plant breeding. A simulation study shows that the proposed priors implementing expert knowledge improve the robustness of genomic modelling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study expert knowledge increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of expert knowledge priors for genomic modelling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modelling.
miR-183/96/182 cluster is an important morphogenetic factor targetingPAX6expression in differentiating human retinal organoids
Authors: Peskova Lucie , Jurcikova Denisa , Vanova Tereza , Krivanek Jan , Capandova Michaela , Sramkova Zuzana , Kolouskova Magdalena , Kotasova Hana , Streit Libor , Barta Tomas 
Published: April 2020

AbstractMicroRNAs (miRNAs), a class of small, non-coding RNA molecules represent important regulators of gene expression. Recent reports have implicated their role in the cell specification process acting as “fine-tuners” to ensure the precise gene expression at the specific stage of cell differentiation. Here we used retinal organoids differentiated from human pluripotent stem cells (hPSCs) as a model to closely investigate the role of a sensory organ-specific and evolutionary conserved miR-183/96/182 cluster. Using a miRNA tough decoy approach, we inhibited the miR-183/96/182 cluster in hPSCs. Inhibition of the miRNA cluster resulted in an increased expansion of neuroepithelium leading to abnormal “bulged” neural retina in organoids, associated with upregulation of neural-specific and retinal-specific genes. Importantly, we identifiedPAX6, a well-known essential gene in neuroectoderm specification, as a target of the miR-183/96/182 cluster members. Taken together, the miR-183/96/182 cluster not only represents an important regulator ofPAX6expression, but it also plays a crucial role in retinal tissue morphogenesis.