bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of Heavy Metals in Wheat and Barley Grains Using ICP-MS/MS
Authors: Thabit Tamer M A M , Shokr Shokr Abdelsalam , Elgeddawy Dalia I H , El-Naggar Medhat A H 
Published: February 2020

Abstract
Wheat and barley grains are two of the most important nutritional grains for humans and animals and they play an essential role in the nutritional cycle by different ratios according to people's nutritional habits. This work aimed to monitor ten of the most important heavy metals in some European-origin wheat and barley grains during the season of 2018. The measured elements, Al, As, Cd, Co, Cr, Hg, Mo, Ni, Pb, and V, are of importance ecologically and biologically and may be involved in many health disorders affecting the human body. Moisture, protein, and specific grain weights were checked. Samples were digested using microwave acid digestion and the elements measured with ICP-MS/MS in He mode to increase sensitivity, lower the background, and avoid interference. Method validation and verification were carried out through spiking at two levels (2.0 and 10 ppb), then RSD, LOD, and LOQ were calculated. Recoveries were &gt;97% for all elements at both levels with an RSD of &lt;7.6%. Results revealed that As, Cd, Hg, and Pb were not detected in most wheat and barley samples, whereas Cd was detected in one sample of Ukrainian wheat and two samples of Estonian barley (but in very small traces). Pb was detected in three samples of Polish wheat (in very small traces). Al, Mo, and Ni were detected in some samples of wheat and barley of all origins, whereas other elements were at very low levels considered to be negligible concentrations.
Single-Laboratory Validation of UHPLC-MS/MS Assays for Red Clover Isoflavones in Human Serum and Dietary Supplements
Authors: Muchiri Ruth N , van Breemen Richard B 
Published: February 2020

Abstract

Background
Extracts of red clover (Trifolium pratense L.) containing estrogenic and pro-estrogenic isoflavones are used in dietary supplements primarily for the management of menopausal symptoms in women.

Objective
A UHPLC-MS/MS assay was developed and validated for the quantitative analysis of the six major red clover isoflavones in dietary supplements and in human serum in support of clinical trials.

Methods
Enzymatic deconjugation of isoflavone glucuronides and sulfate conjugates in human serum specimens was carried out followed by protein precipitation. Isoflavones in red clover dietary supplements were acid hydrolyzed to release aglycons from glycosides. UHPLC separations (&lt; 4 min) were combined with MS/MS using collision-induced dissociation, selective reaction monitoring and deuterated internal standards to measure biochanin A, formononetin, daidzein, genistein, irilone, and prunetin.

Results
The method was validated with respect to selectivity, specificity, accuracy, linearity, precision, LOD, and LOQ. The calibration curves for all analytes were linear (R2 &gt; 0.998). The mean recovery for low-, medium- and high-quality control standards ranged between 80% and 108%. The precision of the method was assessed using coefficients of variation, which were &lt;15%.

Conclusions
The UHPLC-MS/MS method is fast, precise, sensitive, selective, accurate, and applicable to the quantitative analysis of red clover isoflavones in different matrices.

Highlights
This validated UHPLC-MS/MS assay is applicable to the rapid quantitative analysis of red clover isoflavones in human serum and in dietary supplements.
DGINN, an automated and highly-flexible pipeline for the Detection of Genetic INNovations on protein-coding genes
Authors: Picard Lea , Ganivet Quentin , Allatif Omran , Cimarelli Andrea , Guéguen Laurent , Etienne Lucie 
Published: February 2020

AbstractAdaptive evolution has shaped major biological processes. Finding the protein-coding genes and the sites that have been subjected to adaptation during evolutionary time is a major endeavor. However, very few methods fully automate the identification of positively selected genes, and widespread sources of genetic innovations as gene duplication and recombination are absent from most pipelines. Here, we developed DGINN, a highly-flexible and public pipeline to Detect Genetic INNovations and adaptive evolution in protein-coding genes. DGINN automates, from a gene’s sequence, all steps of the evolutionary analyses necessary to detect the aforementioned innovations, including the search for homologues in databases, assignation of orthology groups, identification of duplication and recombination events, as well as detection of positive selection using five different methods to increase precision and ranking of genes when a large panel is analyzed. DGINN was validated on nineteen genes with previously-characterized evolutionary histories in primates, including some engaged in host-pathogen arms-races. The results obtained with DGINN confirm and also expand results from the literature, establishing DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user’s gene of interest to a large gene list in any species range.
What do adversarial images tell us about human vision?
Authors: Dujmović Marin , Malhotra Gaurav , Bowers Jeffrey 
Published: February 2020

AbstractDeep convolutional neural networks (DCNNs) are frequently described as promising models of human and primate vision. An obvious challenge to this claim is the existence ofadversarial imagesthat fool DCNNs but are uninterpretable to humans. However, recent research has suggested that there may be similarities in how humans and DCNNs interpret these seemingly nonsense images. In this study, we reanalysed data from a high-profile paper and conducted four experiments controlling for different ways in which these images can be generated and selected. We show that agreement between humans and DCNNs is much weaker and more variable than previously reported, and that the weak agreement is contingent on the choice of adversarial images and the design of the experiment. Indeed, it is easy to generate images with no agreement. We conclude that adversarial images still challenge the claim that DCNNs constitute promising models of human and primate vision.
Sensitive, highly multiplexed sequencing of microhaplotypes from thePlasmodium falciparumheterozygome
Authors: Tessema Sofonias K , Hathaway Nicholas J , Teyssier Noam B , Murphy Maxwell , Chen Anna , Aydemir Ozkan , Duarte Elias M , Simone Wilson , Colborn James , Saute Francisco , Crawford Emily , Aide Pedro , Bailey Jeffrey A , Greenhouse Bryan 
Published: February 2020

AbstractBackgroundTargeted next generation sequencing offers the potential for consistent, deep coverage of information rich genomic regions to characterize polyclonalPlasmodium falciparuminfections. However, methods to identify and sequence these genomic regions are currently limited.MethodsA bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, WGS data were generated for the same controls.ResultsUsing publicly available genomes, 4465 high diversity genomic regions suited for targeted sequencing were identified, representing theP. falciparumheterozygome. For this study, 93 microhaplotypes with high diversity (median HE= 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%) and sensitivity (90% for haplotypes with 5% within sample frequency in DBS with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic SNP barcodes.DiscussionThe bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high throughput interrogation of theP. falciparumgenome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.
Semi-analytical dynamic modeling of DNA surface-hybridization via AC Electro-kinetic steering
Authors: Capaldo P. , Zilio S. D. , Torre V. , Yang Y. 
Published: February 2020

ABSTRACTThe change in electrical property (capacitance) upon hybridization of the desired ssDNA to a capture probe has been proposed as a promising technology platform in biomedical research and practice. An appropriate mathematical model is needed for understanding and optimizing the process occurring at the electrode/electrolyte interface. It is also informative for examining the forces generated by the AC electric fields on the DNA molecules as well as the suspending buffer solution in the experimental pool. Here, we provide the development, formulation and validation of a semi-analytical model of DNA hybridization with deoxynucleotide molecules chemically tethered to a solid gold electrode. The parameters of the proposed model have been estimated using available experimental data. We demonstrate that the detection limit and specificity of our surface-based genosensor are not only dependent on the probe/target binding affinity, but also on the Self-Assembled Monolayer (SAM) density and on the interfacial electric field. The label-free Electrochemical Impedance Spectroscopy (EIS)-based oligonucleotide biosensor with integrated DC-biased can achieve rapid hybridization, high selectivity and sensitive detection for DNA target samples.SIGNIFICANCEDNA hybridization, wherein strands of DNA form duplex through noncovalent, sequence-specific interactions, is one of the most fundamental processes in biology. Fast and reliable determination of miniature amounts of DNA plays important role in clinical forensic and pharmaceutical applications. Thus, developing a better understanding of the kinetic and dynamic properties of DNA hybridization will help in the elucidation of all mechanisms involved in numerous biochemical processes. Moreover, because DNA hybridization has been widely adapted in biotechnology, its study is invaluable to the development of a range of commercially important processes.To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the characteristics of the strands is crucial, and hence a computer aided numerical model for the design and optimization of a DNA biosensor has been implemented.
Optogenetic control of gut bacterial metabolism to promote longevity
Authors: Hartsough Lucas A. , Kotlajich Matthew V. , Han Bing , Lin Chih-Chun J. , Gambill Lauren , Wang Meng C. , Tabor Jeffrey J. 
Published: February 2020

AbstractGut microbial metabolism is associated with host longevity. However, because it requires direct manipulation of microbial metabolismin situ, establishing a causal link between these two processes remains challenging. We demonstrate an optogenetic method to control gene expression and metabolite production from bacteria residing in the host gut. We genetically engineer anEscherichia colistrain that synthesizes and secretes colanic acid (CA) under the quantitative control of light. Using this optogenetically-controlled strain to induce CA production directly in theCaenorhabditis elegansgut, we reveal the local effect of CA in protecting intestinal mitochondria from stress-induced hyper-fragmentation. We also exploit different intensities of light to determine that the lifespan-extending effect of CA is positively correlated with its levels produced from bacteria. Our results show that optogenetic control offers a rapid, reversible and quantitative way to fine-tune gut bacterial metabolism and uncover its local and systemic effects on host health and aging.
Predicting Endometrial Cancer Subtypes and Molecular Features from Histopathology Images Using Multi-resolution Deep Learning Models
Authors: Hong Runyu , Liu Wenke , DeLair Deborah , Razavian Narges , Fenyö David 
Published: February 2020

SummaryThe determination of endometrial carcinoma histological subtypes, molecular subtypes, and mutation status is a critical diagnostic process that directly affects patients’ prognosis and treatment options. Compared to the histopathological approach, however, the availability of molecular subtyping is limited as it can only be accurately obtained by genomic sequencing, which may be cost prohibitive. Here, we implemented a customized multi-resolution deep convolutional neural network, Panoptes, that predicts not only the histological subtypes, but also molecular subtypes and 18 common gene mutations based on digitized H&E stained pathological images. The model achieved high accuracy and generalized well on independent datasets. Our results suggest that Panoptes has potential clinical application of helping pathologists determine molecular subtypes and mutations of endometrial carcinoma without sequencing.SignificanceRecently, molecular subtyping and mutation status are increasingly utilized in clinical practice as they offer better-informed prognosis and the possibility of individualized therapies for endometrial carcinoma patients. Taking advantage of the multi-resolution nature of the whole slide digital histopathology images, our Panoptes models integrate features of different magnification and make accurate predictions of histological subtypes, molecular subtypes, and key mutations in much faster workflows compared to conventional sequencing-based analyses. Feature extraction and visualization revealed that the model relied on human-interpretable patterns. Overall, our multi-resolution deep learning model is capable of assisting pathologists determine molecular subtypes of endometrial carcinoma, which can potentially accelerate diagnosis process.
A rapid, accurate approach to inferring pedigrees in endogamous populations
Authors: Williams Cole M. , Scelza Brooke A. , Slack Sarah D. , Mathias Rasika A. , Watson Harold , Barnes Kathleen C. , Lange Ethan , Johnson Randi K. , Gignoux Christopher R. , Ramachandran Sohini , Henn Brenna M. 
Published: February 2020

ABSTRACTAccurate reconstruction of pedigrees from genetic data remains a challenging problem. Pedigree inference algorithms are often trained only on European-descent families in urban locations. Many relationship categories can be difficult to distinguish (e.g. half-sibships versus avuncular) without external information. Furthermore, existing methods perform poorly in endogamous populations for which there may be reticulations within the pedigrees and elevated haplotype sharing. We present a simple, rapid algorithm which initially uses only high-confidence first-degree relationships to seed a machine learning step based on summary statistics of identity-by-descent (IBD) sharing. One of these statistics, our “haplotype score”, is novel and can be used to: (1) distinguish half-sibling pairs from avuncular or grandparent-grandchildren pairs; and (2) assign individuals to ancestor versus descendant generation. We test our approach in a sample of 700 individuals from northern Namibia, sampled from an endogamous population called the Himba. Due to a culture of concurrent relationships in the Himba, there is a high proportion of half-sibships. We accurately identify first through fourth-degree relationships and distinguish between various second-degree relationships: half-sibships, avuncular pairs, and grandparent-grandchildren. We further validate our approach in a second diverse African-descent dataset, the Barbados Asthma Genetics Study (BAGS). Accurate reconstruction of pedigrees holds promise for tracing allele frequency trajectories, improved phasing and other population genomic questions.
Case fatality rate of novel coronavirus disease 2019 in China
Authors: Qi Rui , Ye Chao , Qin Xiang-rong , Yu Xue-Jie 
Published: February 2020

AbstractBackgroundA pandemic of coronavirus disease 2019 (COVID-19) which have caused more than 80 thousand persons infected globally is still ongoing. This study aims to calculate its case fatality rate (CFR).MethodsThe method, termed as converged CFR calculation, was based on the formula of dividing the number of known deaths by the number of confirmed cases T days before, where T was an average time period from case confirmation to death. It was found that supposing a T, if it was smaller (bigger) than the true T, calculated CFRs would gradually increase (decrease) to infinitely near the true T with time went on. According to the law, the true T value could be determined by trends of daily CFRs calculated with different assumed T values (left of true T is decreasing, right is increasing). Then the CFR could be calculated.ResultsCFR of COVID-19 in China except Hubei Province was 0.8% to 0.9%. So far, the CFR had accurately predicted the death numbers more than 3 weeks. CFR in Hubei of China was 5.4% by which the calculated death number corresponded with the reported number for 2 weeks.ConclusionThe method could be used for CFR calculating while pandemics are still ongoing. Dynamic monitoring of the daily CFRs trends could help outbreak-controller to have a clear vision in the timeliness of the case confirmation.
Testing the association between tobacco and cannabis use and cognitive functioning: Findings from an observational and Mendelian randomization study
Authors: Mahedy Liam , Wootton Robyn , Suddell Steph , Skirrow Caroline , Field Matt , Heron Jon , Hickman Matthew , Munafò Marcus R. 
Published: February 2020

ABSTRACTBackgroundAlthough studies have examined the association between tobacco and cannabis use in adolescence with subsequent cognitive functioning, study designs are usually not able to distinguish correlation from causation.MethodsSeparate patterns of tobacco and cannabis use were derived using longitudinal latent class analysis based on measures assessed on five occasions from age 13 to 18 in a large UK population cohort (ALSPAC). Cognitive functioning measures comprised of working memory, response inhibition, and emotion recognition assessed at 24 years of age. Mendelian randomization was used to examine the possible causal relationship.ResultsWe found evidence of a relationship between tobacco and cannabis use and diminished cognitive functioning for each of the outcomes in the observational analyses. There was evidence to suggest that late-onset regular tobacco smokers (b=−0.29, 95%CI=−0.45 to −0.13), early-onset regular tobacco smokers (b=−0.45, 95%CI=−0.84 to −0.05), and early-onset regular cannabis users (b=−0.62, 95%CI=−0.93 to −0.31) showed poorer working memory. Early-onset regular tobacco smokers (b=0.18, 95%CI=0.07 to 0.28), and early-onset regular cannabis users (b=0.30, 95%CI=0.08 to 0.52) displayed poorer ability to inhibit responses. Late-onset regular (b=−0.02, 95%CI=−0.03 to −0.00), and early-onset regular tobacco smokers (b=−0.04, 95%CI=−0.08 to −0.01) showed poorer ability to recognise emotions. Mendelian randomization analyses were imprecise and did not provide additional support for the observational results.ConclusionThere was some evidence to suggest that adolescent tobacco and cannabis use were associated with deficits in working memory, response inhibition and emotion recognition. Better powered genetic studies are required to determine whether these associations are causal.
Movement of transposable elements contributes to cichlid diversity
Authors: Carleton Karen L. , Conte Matt , Malinsky Milan , Nandamuri Sri Pratima , Sandkam Ben , Meier Joana I , Mwaiko Salome , Seehausen Ole , Kocher Thomas D 
Published: February 2020

AbstractAfrican cichlid fishes are a prime model for studying the mechanisms of speciation. Despite the development of extensive genomic resources, it has been difficult to determine which sources of genetic variation are responsible for variation in cichlid phenotypes. Cichlids have some of the largest known shifts in vertebrate visual sensitivity. These shifts arise mainly from the differential expression of seven cone opsin genes. By mapping expression quantitative trait loci (eQTL) in intergeneric crosses of Lake Malawi (LM) cichlids, we have thus far identified four causative genetic variants that correspond to indels in the promoters of either key transcription factors or of the opsin gene itself. Here we show that these indels are caused by the movement of transposable elements (TEs). These precise indels are not found outside of LM, suggesting that these TEs are recently active and are segregating within the Malawi cichlid lineage. A similar indel has arisen independently outside of LM at one locus, suggesting that some locations are primed for TE insertion and the resulting indels. Increased TE mobility may be associated with interspecific hybridization, which disrupt mechanisms of TE suppression. Overall, our study suggests that TEs may contribute to key regulatory changes, and may facilitate rapid phenotypic change and possibly speciation in African cichlids.
Are bivalves susceptible to domestication selection? Using starvation tolerance to test for potential trait changes in eastern oyster larvae
Authors: McFarland Katherine , Plough Louis V. , Nguyen Michelle , Hare Matthew P. 
Published: February 2020

AbstractConservation efforts are increasingly being challenged by a rapidly changing environment, and for some aquatic species the use of captive rearing or selective breeding is an attractive option. However, captivity itself can impose unintended artificial selection known as domestication selection (adaptation to culture conditions). For most marine species, it is not known to what degree domestication selection affects traits related to fitness in the wild. To test for domestication selection in a marine bivalve, we focused on a fitness-related trait (larval starvation resistance) that could be altered under artificial selection. Using larvae produced from a wild population ofCrassostrea virginicaand a selectively bred, disease-resistant line we measured growth and survival during starvation versus standard algal diet (control) conditions. Larvae from both lineages showed a remarkable resilience to food limitation, possibly mediated by an ability to uptake and utilize dissolved organic matter for somatic maintenance. Water chemistry analysis showed dissolved organic carbon in filtered tank water to be at concentrations similar to natural river water. We observed that survival in larvae produced from the aquaculture line was significantly lower compared to larvae produced from wild broodstock (8 ± 3% and 21 ± 2%, respectively) near the end of a 10-day period with no food (phytoplankton). All larval cohorts had arrested growth during the starvation period and took at least two days to recover once food was reintroduced before resuming growth. Phenotypic differences between the wild and aquaculture lines suggest potential differences in the capacity to sustain extended food limitation, but this work requires replication with multiple selection lines and wild populations to make more general inferences about domestication selection. With this contribution we explore the potential for domestication selection in bivalves, discuss the physiological and fitness implications of reduced starvation tolerance, and aim to inspire further research on the topic.