bluuebunny/crossref_metadata_2025 huggingface dataset:
The global impact of the first Coronavirus Disease 2019 (COVID-19) pandemic wave on vascular services
Authors:   The VERN COVER study collaborative, Benson Ruth A , Nandhra Sandip
Published: July 2020

Background

The Coronavirus Disease 2019 (COVID-19) pandemic is having an unprecedented impact on healthcare delivery. This international qualitative study captured the global impact on vascular patient care during the first pandemic ‘wave’.

Methods

An online structured survey was used to collect regular unit-level data regarding the modification to a wide range of vascular services and treatment pathways on a global scale.

Results

The survey commenced on 23rd March 2020 worldwide. Over six weeks, 249 vascular units took part in 53 countries (465 individual responses). Overall, 65% of units stopped carotid surgery for anyone except patients with crescendo symptoms or offered surgery on a case-by-case basis, 25% only intervened for symptomatic aortic aneurysms cancelling all ‘elective’ repairs. For patients with symptomatic peripheral arterial disease 60% of units moved to an endovascular-first strategy. For patients who had previously undergone endovascular aortic aneurysm repair, 31.8% of units stopped all postoperative surveillance. Of those units regularly engaging in multidisciplinary team meetings, 59.5% of units stopped regular meetings and 39.1% had not replaced them. Further, 20% of units did not have formal personal protective equipment (PPE) guidelines in place and 25% reported insufficient PPE availability.

Conclusions

The COVID-19 pandemic has had a major impact on vascular services worldwide. There will be a significant vascular disease burden awaiting screening and intervention after the pandemic.
Triage-driven diagnosis for early detection of esophageal cancer using deep learning
Authors: Gehrung Marcel , Crispin-Ortuzar Mireia , Berman Adam G. , O’Donovan Maria , Fitzgerald Rebecca C. , Markowetz Florian
Published: July 2020

Deep learning methods have been shown to achieve excellent performance on diagnostic tasks, but it is still an open challenge how to optimally combine them with expert knowledge and existing clinical decision pathways. This question is particularly important for the early detection of cancer, where high volume workflows might potentially benefit substantially from automated analysis. Here, we present a deep learning framework to analyse samples of the Cytosponge®-TFF3 test, a minimally invasive alternative to endoscopy, for detecting Barrett’s Esophagus, the main precursor of esophageal cancer. We trained and independently validated the framework on data from two clinical trials, analysing a combined total of 4,662 pathology slides from 2,331 patients. Our approach exploits screening patterns of expert gastrointestinal pathologists and established decision pathways to define eight triage classes of varying priority for manual expert review. By substituting manual review with automated review in low-priority classes, we can reduce pathologist workload by up to 66% while matching the diagnostic performance of expert pathologists. These results lay the foundation for tailored, semi-automated decision support systems embedded in clinical workflows.
Fertility Transition in Currently Married Reproductive Age Women in India: 1985-2017
Authors: Chaurasia Aalok Ranjan
Published: July 2020

This paper analyses fertility transition in currently married women in India and states during 1985 through 2017 on the basis of average annual number of live births per currently married woman of reproductive age available through the sample registration system. The analysis reveals that in recent years there has been an increase in the average annual number of live births per currently married woman of reproductive age in India and in its most of the states. The analysis also reveals that there has been an increasing concentration of average annual number of live births per currently married woman of reproductive age in the younger ages of the reproductive period which has implications for population growth as more and more growth in the coming years will be due to the momentum for growth built in the age structure of the population. It is argued that in order to mitigate the impact of the observed transition in the average annual number of live births per currently married woman of reproductive age, fertility regulation efforts in India should be directed towards the ‘practice’ of family planning rather than ‘treatment’ of high fertility.
BaseQTL: a Bayesian method to detect eQTLs from RNA-seq data with or without genotypes
Authors: Vigorito Elena , Lin Wei-Yu , Starr Colin , Kirk Paul DW , White Simon R , Wallace Chris
Published: July 2020

Available methods to detect molecular quantitative trait loci (QTL) require study individuals to be genotyped. Here, we describe BaseQTL, a Bayesian method that exploits allele-specific expression to map molecular QTL from sequencing reads even when no genotypes are available. When used with genotypes, BaseQTL has lower error rates and increased power compared with existing QTL mapping methods. Running without genotypes limits how many tests can be performed, but due to the proximity of QTL variants to gene bodies, the 2.8% of variants within a 100kB-window that could be tested, contained 26% of QTL variants detectable with genotypes. eQTL effect estimates were invariably consistent between analyses performed with and without genotypes. Often, sequencing data may be generated in absence of genotypes on patients and controls in differential expression studies, and we identified an apparent psoriasis-specific effect forGSTP1in one such dataset, providing new insights into disease-dependent gene regulation.
Gene regulation of the avian malaria parasitePlasmodium relictum, during the different stages within the mosquito vector
Authors: Sekar V. , Rivero A. , Pigeault R. , Gandon S. , Drews A. , Ahren Dag , Hellgren O.
Published: July 2020

The malaria parasitePlasmodium relictumis one of the most widespread species of avian malaria. As is the case in its human counterparts, birdPlasmodiumundergoes a complex life cycle infecting two hosts: the arthropod vector and the vertebrate host. In this study, we examine the transcriptome ofP. relictum(SGS1) during crucial timepoints within its natural vector,Culex pipiens quinquefasciatus. Differential gene-expression analyses identified genes linked to the parasites life-stages at: i) a few minutes after the blood meal is ingested, ii) during peak oocyst production phase, iii) during peak sporozoite phase and iv) during the late-stages of the infection. A large amount of genes coding for functions linked to host-immune invasion and multifunctional genes was active throughout the infection cycle. One gene associated with a conservedPlasmodiummembrane protein with unknown function was upregulated throughout the parasite development in the vector, suggesting an important role in the successful completion of the sporogonic cycle. Transcript annotation further revealed novel genes, which were significantly differentially expressed during the infection in the vector as well as upregulation of reticulocyte-binding proteins, which raises the possibility of the multifunctionality of these RBPs. We establish the existence of highly stage-specific pathways being overexpressed during the infection. This first study of gene-expression of a non-human Plasmodium species in its natural vector provides a comprehensive insight into the molecular mechanisms of the common avian malaria parasiteP. relictumand provides essential information on the evolutionary diversity in gene regulation of the Plasmodium’s vector stages.
Growth of the Radiotrophic FungusCladosporium sphaerospermumaboard the International Space Station and Effects of Ionizing Radiation
Authors: Shunk Graham K. , Gomez Xavier R. , Kern Christoph , Averesch Nils J. H.
Published: July 2020

The greatest hazard for humans on deep-space exploration missions is radiation. To protect astronauts venturing out beyond Earth’s protective magnetosphere, advanced passive radiation protection is highly sought after. In search of innovative radiation-shields, biotechnology appeals with suitability forin-situresource utilization (ISRU), self-regeneration, and adaptability.

Certain fungi thrive in high-radiation environments on Earth, such as the contamination radius of the Chernobyl Nuclear Power Plant. Analogous to photosynthesis, these organisms appear to perform radiosynthesis, utilizing ionizing radiation to generate chemical energy. It has been postulated that the absorption of radiation is attributable to the pigment melanin. It is further hypothesized that this phenomenon translates to radiation-shielding properties.

Here, growth ofCladosporium sphaerospermumand its capability to attenuate ionizing radiation, was studied aboard the International Space Station (ISS) over a period of 26 days, as an analog to habitation on the surface of Mars. At full maturity, radiation beneath a ≈ 1.7 mm thick lawn of the dematiaceous radiotrophic fungus was approx. 0.84% lower as compared to the negative-control. In addition, a growth advantage in Space of ∼ 21% was observed, substantiating the thesis that the fungus’ radiotropism is extendable to Space radiation.
Near-infrared spectroscopy outperforms genomics for predicting sugarcane feedstock quality traits
Authors: Vital Gonçalves Mateus Teles , Morota Gota , de Almeida Costa Paulo Mafra , Pereira Vidigal Pedro Marcus , Pereira Barbosa Marcio Henrique , Peternelli Luiz Alexandre
Published: July 2020

The main objectives of this study were to evaluate the prediction performance of genomic and near-infrared spectroscopy (NIR) data and whether the integration of genomic and NIR predictor variables can increase the prediction accuracy of two feedstock quality traits (fiber and sucrose content) in a sugarcane population (Saccharumspp.). The following three modeling strategies were compared: M1 (genome-based prediction), M2 (NIR-based prediction), and M3 (integration of genomics s and NIR wavenumbers). Data were collected from a commercial population comprised of three hundred and eighty-five individuals, genotyped for single nucleotide polymorphisms (SNPs) and screened using NIR spectroscopy. We compared partial least squares (PLS) and BayesB regression methods to estimate marker and wavenumber effects. In order to assess model performance, we employed random sub-sampling cross-validation to calculate the mean Pearson correlation coefficient between observed and predicted genotypic values. Our results showed that models fitted using BayesB were most predictive than PLS models. We found that NIR (M2) provided the highest prediction accuracy, whereas genomics (M1) presented the lowest predictive ability, regardless of the measured traits and regression methods used. The integration of predictors derived from NIR spectroscopy and genomics into a single model (M3) did not significantly improve the prediction accuracy for the two traits evaluated. These findings suggest that NIR-based prediction can be an effective strategy for predicting the genotypic value of sugarcane clones.
ARPEGGIO: Automated Reproducible Polyploid EpiGenetic GuIdance workflOw
Authors: Milosavljevic Stefan , Kuo Tony , Decarli Samuele , Mohn Lucas , Sese Jun , Shimizu Kentaro K. , Shimizu-Inatsugi Rie , Robinson Mark D.
Published: July 2020

Whole genome duplication (WGD) events are common in the evolutionary history of many living organisms. For decades, researchers have been trying to understand the genetic and epigenetic impact of WGD and its underlying molecular mechanisms. Particular attention was given to allopolyploid study systems, species resulting from an hybridization event accompanied by WGD. Investigating the mechanisms behind the survival of a newly formed allopolyploid highlighted the key role of DNA methylation. With the improvement of high-throughput methods, such as whole genome bisulfite sequencing (WGBS), an opportunity opened to further understand the role of DNA methylation at a larger scale and higher resolution. However, only a few studies have applied WGBS to allopolyploids, which might be due to lack of genomic resources combined with a burdensome data analysis process. To overcome these problems, we developed the Automated Reproducible Polyploid EpiGenetic GuIdance workflOw (ARPEGGIO): the first workflow for the analysis of epigenetic data in polyploids. This workflow analyzes WGBS data from allopolyploid species via the genome assemblies of the allopolyploid’s parent species. ARPEGGIO utilizes an updated read classification algorithm (EAGLE-RC), to tackle the challenge of sequence similarity amongst parental genomes. ARPEGGIO offers automation, but more importantly, a complete set of analyses including spot checks starting from raw WGBS data: quality checks, trimming, alignment, methylation extraction, statistical analyses and downstream analyses. A full run of ARPEGGIO outputs a list of genes showing differential methylation. ARPEGGIO’s design focuses on ease of use and reproducibility. ARPEGGIO was made simple to set up, run and interpret, and its implementation includes both package management and containerization. Here we discuss all the steps, challenges and implementation strategies; example datasets are provided to show how to use ARPEGGIO. In addition, we also test EAGLE-RC with publicly available datasets given a ground truth, and we show that EAGLE-RC decreases the error rate by 3 to 4 times compared to standard approaches. The goal of ARPEGGIO is to promote, support and improve polyploid research with a reproducible and automated set of analyses in a convenient implementation.
Evolutionary history determines population spread rate in a stochastic, rather than in a deterministic way
Authors: Frederik Mortier , Stefano Masier , Dries Bonte
Published: July 2020

Fragmentation of natural landscapes results in habitat and connectedness loss, making it one of the most impactful avenues of anthropogenic environmental degradation. Populations living in a fragmented landscape can adapt to this context, as witnessed in changing dispersal strategies, levels of local adaptation and changing life-history traits. This evolution, however, can have ecological consequences beyond a fragmented range. Since invasive dynamics are driven by the same traits affected by fragmentation, the question arises whether fragmented populations evolve to be successful invaders.

In this study we assess population spread during three generations of two-spotted spider mite (Tetranychus urticae) population in a replicated experiment. Experimental populations evolved independently in replicated experimental metapopulations differing only in the level of habitat connectedness as determined by the inter-patch distance.

We find that habitat connectedness did not meaningfully explain variation in population spread rate. Rather, variation within experimental populations that shared the same level of connectedness during evolution was larger than the one across these levels. Therefore, we conclude that experimental populations evolved different population spread capacities as a result of their specific evolutionary background independent but of the connectedness of the landscape. While population spread capacities may be strongly affected by aspects of a population’s evolutionary history, predicting it from identifiable aspects of the evolutionary history may be hard to achieve.
Molecular and clinicopathological characterization of a prognostic immune gene signature associated with MGMT methylation in glioblastoma
Authors: Zhao Liang , Zhang Jiayue , Xuan Shurui , Liu Zhiyuan , Wang Yu , Zhao Peng
Published: July 2020

Background

O6-methylguanine-DNA methyltransferase (MGMT) methylation status affects tumor chemo-resistance and the prognosis of glioblastoma (GBM) patients. We aimed to investigate the role of MGMT methylation in the regulation of GBM immunophenotype and discover an effective biomarker to improve prognosis prediction of GBM patients.

Methods

A total of 769 GBM patients with clinical information from five independent cohorts were enrolled in the present study. Samples from the Cancer Genome Atlas (TCGA) dataset were used as the training set, whereas transcriptome data from the Chinese Glioma Genome Atlas (CGGA) RNA-seq, CGGA microarray, GSE16011, and the Repository for Molecular Brain Neoplasia (REMBRANDT) cohort were used for validation. A series of bioinformatics approaches were carried out to construct a prognostic signature based on immune-related genes, which were tightly related with the MGMT methylation status. The influence of the signature on immunosuppression and remodeling of the tumor microenvironment were comprehensively investigated. Then, the utility of this immune gene signature was analyzed by the development and evaluation of a nomogram.

Results

We found that MGMT unmethylation was closely associated with immune-related biological processes in GBM. Sixty-five immune genes were more highly expressed in the MGMT unmethylated than the MGMT methylated group. An immune gene-based risk model was further established to divide patients into high and low-risk groups, and the prognostic value of this signature was validated in several GBM cohorts. Functional analyses manifested a universal up-regulation of immune-related pathways in the high-risk group as compared to the low-risk group. Furthermore, the risk score was highly correlated to the immune cell infiltration, immunosuppression, inflammatory activities, as well as the expression levels of immune checkpoints. Finally, a nomogram was developed for clinical application.

Conclusions

MGMT methylation is strongly related to the immune responses in GBM. The immune gene-based signature we identified may have potential implications in predicting the prognosis of GBM patients and mechanisms underlying the role of MGMT methylation.
Mosaic trisomy of chromosome 1q in human brain tissue associates with unilateral polymicrogyria, very early-onset focal epilepsy, and severe developmental delay
Authors: Kobow Katja , Jabari Samir , Pieper Tom , Kudernatsch Manfred , Polster Tilman , Woermann Friedrich G , Kalbhenn Thilo , Hamer Hajo , Rössler Karl , Mühlebner Angelika , Spliet Wim GM , Feucht Martha , Hou Yanghao , Stichel Damian , Korshunov Andrey , Sahm Felix , Coras Roland , Blümcke Ingmar , von Deimling Andreas
Published: July 2020

Polymicrogyria (PMG) is a developmental cortical malformation characterized by an excess of small and frustrane gyration and abnormal cortical lamination. PMG frequently associates with seizures. The molecular pathomechanisms underlying PMG development are not yet understood. About 40 genes have been associated with PMG, and small copy number variations have also been described in selected patients. We recently provided evidence that epilepsy-associated structural brain lesions can be classified based on genomic DNA methylation patterns. Here we analyzed 26 PMG patients employing array-based DNA-methylation profiling on formalin-fixed paraffin-embedded material. A series of 62 well-characterized non-PMG cortical malformations (focal cortical dysplasia type 2a/b and hemimegalencephaly), temporal lobe epilepsy, and non-epilepsy autopsy controls was used as reference cohort. Unsupervised dimensionality reduction and hierarchical cluster analysis of DNA methylation profiles showed that PMG formed a distinct DNA methylation class. Copy number profiling from DNA methylation data identified a uniform duplication spanning the entire long arm of chromosome 1 in 7 out of 26 PMG patients, which was verified by additional fluorescence in situ hybridization analysis. In respective cases about 50% of nuclei in the center of the PMG lesion were 1q triploid. No chromosomal imbalance was seen in adjacent, architecturally normal-appearing tissue indicating mosaicism. Clinically, PMG 1q patients presented with a unilateral frontal or hemispheric PMG without hemimegalencephaly, a severe form of intractable epilepsy with seizure onset in the first months of life, and severe developmental delay. Our results show that PMG can be classified among other structural brain lesions according to their DNA methylation profile. One subset of PMG with distinct clinical features exhibits a duplication of chromosomal arm 1q.
Behavioral effects of developmental exposure to JWH-018 in wild type and disrupted in schizophrenia 1 (disc1) mutant zebrafish
Authors: García-González Judit , de Quadros Bruno , Brock Alistair J. , Brennan Caroline H.
Published: July 2020

Synthetic cannabinoids can cause acute adverse psychological effects, but the potential impact when exposure happens before birth is unknown. Use of synthetic cannabinoids during pregnancy may affect fetal brain development, and such effects could be moderated by the genetic makeup of an individual. Disrupted in schizophrenia 1 (DISC1) is a gene with important roles in neurodevelopment which has been associated with psychiatric disorders in pedigree analyses. Using zebrafish as a model, we investigated (1) the behavioral impact of developmental exposure to JWH-018 (a common psychoactive synthetic cannabinoid) and (2) whetherdisc1moderates the effects of JWH-018. As altered anxiety responses are seen in a several psychiatric disorders, we focused on zebrafish anxiety-like behavior. Zebrafish embryos were exposed to JWH-018 from one to six days post-fertilization. Anxiety-like behavior was assessed using forced light/dark and acoustic startle assays in larvae, and novel tank diving in adults. Compared to controls, developmentally exposed zebrafish larvae had impaired locomotion during the forced light/dark test, but anxiety levels and response to startle stimuli was unaltered. Adult zebrafish developmentally exposed to JWH-018 spent less time on the bottom of the tank, suggesting decreased anxiety. Loss-of-function indisc1increased anxiety but did not alter sensitivity to JWH-018. Results suggest developmental exposure to JWH-018 has behavioral impact in zebrafish, which is not moderated bydisc1.
CRISPR-Cas9-mediated editing ofmyb28impairs glucoraphanin accumulation ofBrassica oleraceain the field
Authors: Neequaye Mikhaela , Stavnstrup Sophia , Lawrenson Tom , Hundleby Penny , Troncoso-Rey Perla , Saha Shikha , Harwood Wendy , Traka Maria H , Mithen Richard , Østergaard Lars
Published: July 2020

We sought to quantify the role ofMYB28in the regulation of aliphatic glucosinolate biosynthesis and associated sulphur metabolism in field-grownB. oleraceawith the use of CRISPR-Cas9-mediated gene editing technology. We describe the first characterisedmyb28knockout mutant inB. oleracea, and the first UK field trial of CRISPR-Cas9-mediated gene edited plants under the European Court of Justice interpretation of the 2001/18 EU GMO directive. We report that knocking-outmyb28results in downregulation of aliphatic glucosinolate biosynthesis genes and reduction in accumulation of the methionine-derived glucosinolate, glucoraphanin, in leaves and florets of field-grownmyb28mutant broccoli plants. There were no significant changes to the accumulation of sulphate, S-methyl cysteine sulfoxide and indole glucosinolate in leaf and floret tissues.
Lack of redundancy between electrophysiological measures of long-range neuronal communication
Authors: Strahnen Daniel , Kapanaiah Sampath K.T. , Bygrave Alexei M. , Kätzel Dennis
Published: July 2020

Communication between brain areas has been implicated in a wide range of cognitive and emotive functions and is impaired in numerous mental disorders. In rodent models, various functional connectivity metrics have been used to quantify inter-regional neuronal communication. However, in individual studies, typically only very few measures of coupling are reported and, hence, redundancy across such indicators is implicitly assumed. In order to test this assumption, we here comparatively assessed a broad range of directional and non-directional metrics like coherence, weighted Phase-Lag-Index (wPLI), Granger causality (GC), spike-phase coupling (SPC), cross-regional phase-amplitude coupling, amplitude cross-correlations, and others. We applied these analyses to simultaneous field recordings from the prefrontal cortex and the ventral and dorsal hippocampus in the schizophrenia-relatedGria1-knockout mouse model which displays a robust novelty-induced hyperconnectivity phenotype. We find that across such measures there is a considerable lack of functional redundancy. While coherence and GC yielded similar results, other measures, especially wPLI and SPC, often produced deviating conclusions. Bivariate correlations within animals revealed that virtually none of the metrics consistently co-varied with any of the other measures across the three connections and two genotypes analysed. Parametric GC showed the qualitatively highest degree of redundancy with other metrics and would be most suitable for connectivity analysis. We conclude that analysis of multiple metrics is necessary to characterise functional connectivity.
BPIFB3 interacts with ARFGAP1 and TMED9 to regulate non-canonical autophagy and RNA virus infection
Authors: Evans Azia S. , Lennemann Nicholas J. , Coyne Carolyn B.
Published: July 2020

Autophagy is a degradative cellular pathway that targets cytoplasmic contents and organelles for turnover by the lysosome. Various autophagy pathways play key roles in the clearance of viral infections, and many families of viruses have developed unique methods for avoiding degradation. Some positive stranded RNA viruses, such as enteroviruses and flaviviruses, usurp the autophagic pathway to promote their own replication. We previously identified the endoplasmic reticulum-localized protein BPIFB3 as an important regulator of non-canonical autophagy that uniquely impacts the replication of enteroviruses and flaviviruses. Here, we find that many components of the canonical autophagy machinery are not required for BPIFB3-regulated autophagy and identify the host factors that facilitate its role in the replication of enteroviruses and flaviviruses. Using proximity-dependent biotinylation (BioID) followed by mass spectrometry, we identify ARFGAP1 and TMED9 as two cellular components that interact with BPIFB3 to regulate autophagy and viral replication. Importantly, our data demonstrate that non-canonical autophagy in mammalian cells can be controlled outside of the traditional pathway regulators and define the role of two proteins in BPIFB3-mediated non-canonical autophagy.

Summary Statement

BPIFB3 is a regulator of a non-canonical cellular autophagy pathway that impacts the replication of enteroviruses and flaviviruses. Here we define ARFGAP1 and TMED9 as essential components of this pathway.
Pathogen-driven coevolution across CBP60 plant immune regulator subfamilies confers resilience on the regulator module
Authors: Zheng Qi , Majsec Kristina , Katagiri Fumiaki
Published: July 2020

Among eight Arabidopsis CaM-Binding Protein (CBP) 60 family members, AtCBP60g and AtSARD1 are partially functionally redundant, major positive immune regulators while AtCBP60a is a negative immune regulator. Phylogenetic analysis of CBP60 protein sequences of 247 diverse land plant species indicated that the CBP60a, CBP60g, and SARD1 immune regulator subfamilies diversified around the time of Angiosperm divergence. The immune regulator subfamilies, especially the CBP60g subfamily, have been evolving very fast, suggesting strong selection pressure from CBP60-targeting pathogen effectors. We closely examined this fast evolution of the immune regulator subfamilies using the subfamily protein sequences from 12 diverse Core Eudicot species. The fast evolution was caused by both high proportions of polymorphic sites and high evolution rates per polymorphic site, compared to the genomic norm. We developed an analytical platform for physical-chemical characteristics of amino acids, called Protein Evolution Analysis in Euclidean Space (PEAES). Using the pairwise distance rank on PEAES (PEAES-PDR), we detected signatures of significant coevolutionary interactions across the immune regulator subfamilies within the CBP60-conserved domain. The patterns of detected coevolutionary interactions were consistent with hypothetical coevolutionary mechanisms that protect the positive immune regulator function from targeting by pathogen effectors. The coevolutionary interactions across the subfamilies were largely specific to each species lineage, suggesting that the coevolution occurred through species lineage-specific histories of variable pathogen pressure. Thus, fast coevolution of the subfamilies with overlapping or opposing functions appears crucial to maintain resilience of the CBP60 immune regulator module against fast-evolving pathogen effectors.
Human-specific GAPDH RT-qPCR is an accurate and sensitive method of xenograft metastasis quantification
Authors: Dahn Margaret L , Dean Cheryl A , Jo Diana B , Coyle Krysta M , Marcato Paola
Published: July 2020

Metastasis is the primary cause of cancer-related mortality. Having experimental models that accurately reflect changes in the metastatic burden is imperative for developing improved treatments and a better understanding of the disease. The murine xenograft tumor model mimics the human scenario and provides a platform forin vivoandex vivometastasis quantification analyses. Histological analysis of hematoxylin and eosin (H&E) stained thin sections has been the gold standard for quantifying metastasisex vivobut gaining favor for its ease and accuracy is reverse transcription-qualitative polymerase chain reaction (RT-qPCR). Herein we directly compare histological and RT-qPCR-based methods for quantifying lung metastasis in a murine xenograft tumor model. Furthermore, we have introduced a variation of the RT-qPCR method; human-specific glyceraldehyde 3-phosphate dehydrogenase (GAPDH) RT-qPCR, which allows quantification of metastasis in xenograft models, without the requirement of overexpression of exogenous genes. Human-specific GAPDH RT-qPCR detected increased lung metastasis resulting from aldehyde dehydrogenase 1A3 (ALDH1A3) expression in MDA-MB-231 breast cancer cells orthotopically implanted in NOD/SCID mice. Further, in the xenograft tumor model, human-specific GAPDH RT-qPCR was more sensitive and cost-effective than quantification of lung metastasis by histological analysis of H&E stained fixed thin sections. The two assays were highly correlative in terms of determining relative metastatic burden, suggesting that the human-specific GAPDH RT-qPCR method could be used as a standard method for quantification of disseminated human cells in murine xenograft models.
Intrauterine growth restriction causes cellular, molecular, and behavioral deficits consistent with abnormal dentate gyrus neurogenesis in mice
Authors: Brown Ashley S. , Wieben Matthew , Murdock Shelby , Chang Jill , Dizon Maria , Dorsky Richard I. , Fung Camille M.
Published: July 2020

Background

Children born with intrauterine growth restriction (IUGR) are at increased risk for cognitive impairment including learning and memory deficits. Dentate gyrus (DG) granule neurons relay cortical information into the hippocampus proper for memory formation, and their production is highly dependent on environmental signals. However, it is unknown whether IUGR affects DG neurogenesis, and thus provides a potential mechanism underlying abnormal learning and memory function.

Methods

Using a hypertensive disease of pregnancy mouse model of IUGR, we assessed multiple behaviors, quantified neural stem and progenitor cells (NSPCs) and developing neurons in the DG, and characterized transcriptional effects on molecular pathways in the hippocampus.

Results

We found that the predominant behavioral phenotype in IUGR offspring, short-term implicit learning and memory deficits, was associated with accelerated DG neurogenesis and NSPC depletion. Consistent with known molecular regulators of DG neurogenesis, we also found strong evidence for decreased Wnt pathway activity following IUGR.

Conclusion

We have discovered that postnatal memory deficits are associated with accelerated NSPC differentiation following IUGR, a phenotype that could be explained by decreased Wnt signaling.
Diel Oxygen Changes in Closed Ecological Systems; Predictive of Lake Metabolism?
Authors: Taub Frieda B. , Bridges David J.
Published: July 2020

The net oxygen change over a 24-hour day/night cycle in a laboratory study showed strong consistent patterns of (1)gain, when nutrients and light were available; (2)maintain, with daytime gains being matched by nighttime losses; and (3)loss, over brief periods of time during intense zooplankton grazing on previously grown phytoplankton or over long durations without an external source of nutrients. These were simplified aquatic communities closed to the atmosphere, Closed Ecological Systems (CES). Natural lakes are much more complex. While temperate lakes, having a winter accumulation of nutrients followed by sequential algal and zooplankton blooms, may show similar patterns, tropical and flood lakes may exhibit different patterns. Examination of archived lake metabolic studies could yield new insights while looking for these patterns by examining net ecosystem production (NEP), often measured as changes in oxygen concentrations.
Heritable associations with microbial communities are essential for necrotrophic pathogen resistance
Authors: Pogoda Cloe S. , Reinert Stephan , Talukder Zahirul I. , Attia Ziv , Corwin Jason A. , Money Kennedy L. , Collier-zans Erin C.E. , Underwood William , Gulya Thomas J. , Quandt C. Alisha , Kane Nolan C. , Hulke Brent S.
Published: July 2020

Host-microbe interactions are increasingly recognized as important drivers of organismal health, growth, longevity, and community-scale ecological processes. However, less is known about how genetic variation affects hosts’ associated microbiomes and downstream phenotypes. We demonstrate that sunflower (Helianthus annuus) harbors substantial, heritable variation in microbial communities under field conditions. We show that microbial communities explain up to 77.5% of the heritable variation in resistance to root infection caused by the necrotrophic pathogenSclerotinia sclerotiorum, and that plants grown in sterilized soil showed almost complete elimination of pathogen resistance. Association mapping revealed 69 genetic locations related to microbial abundance andSclerotiniaresistance. Although the genetic architecture is complex and quantitative, we have, in large part, elucidated previously unexplained genetic variation for resistance to this pathogen. This suggests new targets for plant breeding and demonstrates the potential for heritable microbial associations to play important roles in defense in natural and human-altered environments.
CITEseq analysis of non-small-cell lung cancer lesions reveals an axis of immune cell activation associated with tumor antigen load andTP53mutations
Authors: Leader Andrew M. , Grout John A. , Chang Christie , Maier Barbara , Tabachnikova Alexandra , Walker Laura , Lansky Alona , LeBerichel Jessica , Malissen Naussica , Davila Melanie , Martin Jerome , Magri Giuliana , Tuballes Kevin , Zhao Zhen , Petralia Francesca , Samstein Robert , D’Amore Natalie Roy , Thurston Gavin , Kamphorst Alice , Wolf Andrea , Flores Raja , Wang Pei , Beasley Mary Beth , Salmon Helene , Rahman Adeeb H. , Marron Thomas U. , Kenigsberg Ephraim , Merad Miriam
Published: July 2020

Immunotherapy is becoming a mainstay in the treatment of NSCLC. While tumor mutational burden (TMB) has been shown to correlate with response to immunotherapy, little is known about the relation of the baseline immune response with the tumor genotype. Here, we profiled 35 early stage NSCLC lesions using multiscale single cell sequencing. Unsupervised clustering identified in a subset of patients a key cellular module consisting ofPDCD1+ CXCL13+ activated T cells, IgG+ plasma cells, andSPP1+ macrophages, referred to as the lung cancer activation module (LCAMhi). Transcriptional data from two NSCLC cohorts confirmed a subset of patients with LCAMhienrichment, which was independent of overall immune cell content. The LCAMhimodule strongly correlated with TMB, expression of cancer testis antigens, and withTP53mutations in smokers and non-smokers. These data establish LCAM as a key mode of immune cell activation associated with high tumor antigen load and driver mutations.
Bibliome Variant Database: Automated Identification and Annotation of Genetic Variants in Primary Literature
Authors: Baker Samuel W. , Ganguly Arupa
Published: July 2020

The Bibliome Variant Database (BVdb) is a freely available reference database containing over 1 million human genetic variants mapped to the human genome that have been mined from primary literature. The BVdb is designed to facilitate variant interpretation in clinical and research contexts by reducing or eliminating the time required to search for literature describing a given variant. Users can search the database using gene symbols, HGVS variant nomenclature, genomic positions, or rsIDs. Each variant page lists references in the database that describe the variant, as well as the exact gene symbol and variant text description identified in each reference.

AVAILABILITY AND IMPLEMENTATION

The BVdb is freely available athttp://bibliome.ai
A novel high-content phenotypic screen to identify inhibitors of mitochondrial DNA maintenance in trypanosomes
Authors: Miskinyte Migla , Dawson John C. , Makda Ashraff , Doughty-Shenton Dahlia , Carragher Neil O. , Schnaufer Achim
Published: July 2020

Kinetoplastid parasites cause diverse neglected diseases in humans and livestock, with an urgent need for new treatments. Survival of kinetoplastids depends on their uniquely structured mitochondrial genome (kDNA), the eponymous kinetoplast. Here we report development of a high-content screen for pharmacologically induced kDNA loss, based on specific staining of parasites and automated image analysis. As proof-of-concept we screened a diverse set of ∼14,000 small molecules and exemplify a validated hit as a novel kDNA-targeting compound.
Artificial intelligence based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease
Authors: Tsuji Shingo , Hase Takeshi , Yachie Ayako , Nishino Taiko , Ghosh Samik , Kikuchi Masataka , Shimokawa Kazuro , Aburatani Hiroyuki , Kitano Hiroaki , Tanaka Hiroshi
Published: July 2020

Background

Identification of novel therapeutic targets is a key for successful drug development. However, the cost to experimentally identify therapeutic targets is huge and only 400 genes are targets for FDA-approved drugs. Therefore, it is inevitable to develop powerful computational tools to identify potential novel therapeutic targets. Because proteins make their functions together with their interacting partners, a protein-protein interaction network (PIN) in human could be a useful resource to build computational tools to investigate potential targets for therapeutic drugs. Network embedding methods, especially deep-learning based methods would be useful tools to extract an informative low-dimensional latent space that contains enough information required to fully represent original high-dimensional non-linear data of PINs.

Results

In this study, we developed a deep learning based computational framework that extracts low-dimensional latent space embedded in high-dimensional data of the human PIN and uses the features in the latent space (latent features) to infer potential novel targets for therapeutic drugs. We examined the relationships between the latent features and the representative network metrics and found that the network metrics can explain a large number of the latent features, while several latent features do not correlate with all the network metrics. The results indicate that the features are likely to capture information that the representative network metrics can not capture, while the latent features also can capture information obtained from the network metrics. Our computational framework uses the latent features together with state-of-the-art machine learning techniques to infer potential drug target genes. We applied our computational framework to prioritized novel putative target genes for Alzheimer’s disease and successfully identified key genes for potential novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we inferred repositionable candidate-compounds for the disease (e.g., Tamoxifen, Bosutinib, and Dasatinib)

Discussions

Our computational framework could be powerful computational tools to efficiently prioritize new therapeutic targets and drug repositioning. It is pertinent to note here that our computational platform is easily applicable to investigate novel potential targets and repositionable compounds for any diseases, especially for rare diseases.
Digital Cell Sorter (DCS): a cell type identification, anomaly detection, and Hopfield landscapes toolkit for single-cell transcriptomics
Authors: Domanskyi Sergii , Hakansson Alex , Bertus Thomas , Paternostro Giovanni , Piermarocchi Carlo
Published: July 2020

Motivation

Analysis of singe cell RNA sequencing (scRNA-seq) typically consists of different steps including quality control, batch correction, clustering, cell identification and characterization, and visualization. The amount of scRNA-seq data is growing extremely fast, and novel algorithmic approaches improving these steps are key to extract more biological information. Here, we introduce: (i) two methods for automatic cell type identification (i.e. without expert curator) based on a voting algorithm and a Hopfield classifier, (ii) a method for cell anomaly quantification based on isolation forest, and (iii) a tool for the visualization of cell phenotypic landscapes based on Hopfield energy-like functions. These new approaches are integrated in a software platform that includes many other state-of-the-art methodologies and provides a self-contained toolkit for scRNA-seq analysis.

Results

We present a suite of software elements for the analysis of scRNA-seq data. This Python-based open source software, Digital Cell Sorter (DCS), consists in an extensive toolkit of methods for scRNA-seq analysis. We illustrate the capability of the software using data from large datasets of peripheral blood mononuclear cells (PBMC), as well as plasma cells of bone marrow samples from healthy donors and multiple myeloma patients. We test the novel algorithms by evaluating their ability to deconvolve cell mixtures and detect small numbers of anomalous cells in PBMC data.

Availability

The DCS toolkit is available for download and installation through the Python Package Index (PyPI). The software can be deployed using the Python import function following installation. Source code is also available for download on Zenodo: doi.org/10.5281/zenodo.2533377

Contact

domansk6@msu.edu
Spin-density studies of the multiferroic metal-organic compound [NH2(CH3)2][FeIIIFeII(HCOO)6]
Authors: Cañadillas-Delgado Laura , Fabelo Oscar , Rodríguez-Velamazán J. Alberto , Stunault Anne , Zhao Jiong-Peng , Bu Xian-He , Rodríguez-Carvajal Juan
Published: July 2020

Polarized neutron diffraction is used to study in depth the magnetic properties of the heterometallic compound [NH2(CH3)2][FeIIIFeII(HCOO)6] and give insight into its magnetic behaviour, addressing open questions that will contribute to a better understanding of this attention-grabbing material and other related ones. Previous results revealed that upon cooling, the magnetic moments of the FeII and FeIII sites do not order simultaneously: the magnetization of the FeII site increases faster than that of the FeIII sites. Unpolarized neutron diffraction measurements at 2 K with no external field revealed some discrepancies in the saturation value of the magnetic signal on the FeIII sites and in the ferromagnetic moment along the c axis. These discrepancies could be related to the actual distribution of magnetic moment, since unpolarized neutron diffraction gives information on the magnetic moment localized only on the magnetic ions. Polarized neutron diffraction allows an analysis of the magnitude of the spin density over magnetic and non-magnetic ions (the organic ligand and the counterion), which can give a clue to explain the low saturation on the FeIII sites and the correlation with the physical measurements. The present study also contributes to the understanding of the magneto-electric behaviour of this compound, giving insight into the role of metal disorder in the origin of the structural phase transition, which is responsible for its antiferrolelectric order, and into the influence of spin-density delocalization on its magneto-electric properties, allowing a discussion of the alternative explanations given so far for its electric properties at low temperature.
[(Z)-N-(3-Fluorophenyl)-O-methylthiocarbamato-κS](triphenylphosphane-κP)gold(I): crystal structure, Hirshfeld surface analysis and computational study
Authors: Yeo Chien Ing , Tan Sang Loon , Kwong Huey Chong , Tiekink Edward R. T.
Published: July 2020

The title phosphanegold(I) thiolate, C26H22AuFNOPS or [Au(C8H7FNOS)(C18H15P)], has the AuI centre coordinated by phosphane-P [2.2494 (8) Å] and thiolate-S [2.3007 (8) Å] atoms to define a close to linear geometry [P—Au—S = 176.10 (3)°]. The thiolate ligand is orientated so that the methoxy-O atom is directed towards the Au atom, forming an Au...O close contact of 2.986 (2) Å. In the crystal, a variety of intermolecular contacts are discerned with fluorobenzene-C—H...O(methoxy) and phenyl-C—H...F interactions leading to dimeric aggregates. These are assembled into a three-dimensional architecture by phenyl-C—H...S(thiolate) and phenyl-C—H...π(fluorobenzene, phenyl) interactions. Accordingly, the analysis of the calculated Hirshfeld surface shows 30.8% of all contacts are of the type C...H/H...C but this is less than the H...H contacts, at 44.9%. Other significant contributions to the surface come from H...F/F...H [8.1%], H...S/S...H [6.9%] and H...O/O...H [3.2%] contacts. Two major stabilization energies have contributions from the phenyl-C—H...π(fluorobenzene) and fluorobenzene-C—H...C(imine) interactions (−37.2 kcal mol−1), and from the fluorobenzene-C—H...F and phenyl-C—H...O interactions (−34.9 kcal mol−1), the latter leading to the dimeric aggregate.
Synthesis, crystal structure at 219 K and Hirshfeld surface analyses of 1,4,6-trimethylquinoxaline-2,3(1H,4H)-dione monohydrate
Authors: Zouitini Ayman , Faizi Md. Serajul Haque , Ouzidan Younes , Ouazzani Chahdi Fouad , Marrot Jérôme , Prim Damien , Dege Necmi , Mashrai Ashraf
Published: July 2020

The asymmetric unit of the title compound, C11H12N2O2·H2O, contains a molecule of 1,4,6-trimethyl-1,4-dihydroquinoxaline-2,3-dione and a solvent water molecule. Four atoms of the benzene ring are disordered over two sets of sites in a 0.706 (7):0.294 (7) ratio while the N-bound methyl groups are rotationally disordered with occupancy ratios of 0.78 (4):0.22 (4) and 0.76 (5):0.24 (5). In the crystal, molecules are linked by O—H...O and C—H...O hydrogen bonds into layers lying parallel to (10\overline{1}). The Hirshfeld surface analysis indicates that the most important contributions to the packing arrangement are due to H...H (51.3%) and O...H/H...O (28.6%) interactions. The molecular structure calculated by density functional theory is compared with the experimentally determined molecular structure, and the HOMO–LUMO energy gap has been calculated.