bluuebunny/crossref_metadata_2025 huggingface dataset:
Prolonged Withdrawal from Escalated Oxycodone is Associated with Increased Expression of Glutamate Receptors in the Rat Hippocampus
Authors: Salisbury Aaron J. , Blackwood Christopher A. , Cadet Jean Lud
Published: December 2020

People suffering from opioid use disorder (OUD) exhibit cognitive dysfunctions. Here, we investigated potential changes in the expression of glutamate receptors in rat hippocampi at 2 hours and 31 days after the last session of oxycodone self-administration (SA). RNA extracted from the hippocampus was used in quantitative polymerase chain reaction (qPCR) analyses. Rats, given long-access (9 hours per day) to oxycodone (LgA), took significantly more drug than rats exposed to short-access (3 hours per day) (ShA). In addition, LgA rats could be further divided into higher oxycodone taking (LgA-H) or lower oxycodone taking (LgA-L) groups, based on a cut-off of 50 infusions per day. LgA rats, but not ShA, rats exhibited incubation of oxycodone craving. In addition, LgA rats showed increased mRNA expression ofGluA1-3 and GluN2a-csubunits as well asGrm3,Grm5,Grm6andGrm8subtypes of glutamate receptors after 31 days but not after 2 hours of stopping the SA experiment. Changes inGluA1-3, Grm6, and Grm8mRNA levels also correlated with increased lever pressing (incubation) after long periods of withdrawal from oxycodone. More studies are needed to elucidate the molecular mechanisms involved in altering the expression of these receptors during withdrawal from oxycodone and/or incubation of drug seeking.
Information Retrieval using Machine Learning for Biomarker Curation in the Exposome-Explorer
Authors: Lamurias Andre , Jesus Sofia , Neveu Vanessa , Salek Reza M , Couto Francisco M
Published: December 2020

In 2016, the International Agency for Research on Cancer, part of the World Health Organization, released the Exposome-Explorer, the first database dedicated to biomarkers of exposure for environmental risk factors for diseases. The database contents resulted from a manual literature search that yielded over 8500 citations, but only a small fraction of these publications were used in the final database. Manually curating a database is time-consuming and requires domain expertise to gather relevant data scattered throughout millions of articles. This work proposes a supervised machine learning approach to assist the previous manual literature retrieval process.

The manually retrieved corpus of scientific publications used in the Exposome-Explorer was used as training and testing sets for the machine learning models (classifiers). Several parameters and algorithms were evaluated to predict an article’s relevance based on different datasets made of titles, abstracts and metadata.

The top performance classifier was built with the Logistic Regression algorithm using the title and abstract set, achieving an F2-score of 70.1%. Furthermore, from 705 articles classified as relevant, we extracted 545 biomarkers, including 460 new candidate entries to the Exposome-Explorer database.

Our methodology reduced the number of articles to be manually screened by the database curators by nearly 90%, while only misclassifying 22.1% of the relevant articles. We expect that this methodology can also be applied to similar biomarkers datasets or be adapted to assist the manual curation process of similar chemical or disease databases.
Structures of the human mitochondrial ribosome recycling complexes reveal distinct mechanisms of recycling and antibiotic resistance
Authors: Koripella Ravi Kiran , Deep Ayush , Agrawal Ekansh K. , Keshavan Pooja , Banavali Nilesh K. , Agrawal Rajendra K.
Published: December 2020

Ribosomes are recycled for a new round of translation initiation by dissociation of ribosomal subunits, messenger RNA and transfer RNA from their translational post-termination complex. Mitochondrial ribosome recycling factor (RRFmt) and a recycling-specific homolog of elongation factor G (EF-G2mt) are two proteins with mitochondria-specific additional sequences that catalyze the recycling step in human mitochondria. We have determined high-resolution cryo-EM structures of the human 55S mitochondrial ribosome (mitoribosome) in complex with RRFmt, and the mitoribosomal large 39S subunit in complex with both RRFmtand EF-G2mt. In addition, we have captured the structure of a short-lived intermediate state of the 55S•RRFmt•EF-G2mtcomplex. These structures clarify the role of a mitochondria-specific segment of RRFmtin mitoribosome recycling, identify the structural distinctions between the two isoforms of EF-Gmtthat confer their functional specificity, capture recycling-specific conformational changes in the L7/L12 stalk-base region, and suggest a distinct mechanistic sequence of events in mitoribosome recycling. Furthermore, biochemical and structural assessments of the sensitivity of EF-G2mtto the antibiotic fusidic acid reveals that the molecular mechanism of antibiotic resistance for EF-G2mtis markedly different from that exhibited by mitochondrial elongation factor EF-G1mt, suggesting that these two homologous mitochondrial proteins have evolved diversely to negate the effect of a bacterial antibiotics.
Dissecting the midlife crisis: Disentangling social, personality and demographic determinants in social brain anatomy
Authors: Kiesow Hannah , Uddin Lucina Q. , Bernhardt Boris C. , Kable Joseph , Bzdok Danilo
Published: December 2020

In any stage of life, humans crave social connection with other people. In midlife, transitions in social networks can be related to new leadership roles at work or becoming a caregiver for aging parents. Previous neuroimaging studies have reported that during midlife, especially the medial prefrontal cortex (mPFC) undergoes structural remodeling changes. Social behavior, personality predisposition, and demographic profile all bear intimate relation with the mPFC according to separate literature streams. To integrate these three areas commonly studied in isolation, we explicitly modeled their unique links with brain structure using a fully probabilistic framework. We weighed against each other a rich collection of 40 traits with their interindividual variation in social brain morphology in ~10,000 middle-aged UK Biobank participants (40-69 years at recruitment). Across conducted analyses, household size and daily routine schedules showed several of the largest effects in explaining variation in social brain regions. We revealed male-biased effects in the dorsal mPFC and amygdala for job income, and a female-biased effect in the ventral mPFC for health satisfaction. Our population investigation offers a more complete perspective into how adults at the midlife milestone may navigate life depending on their identity and status.
High-resolution Cell Atlas of Domestic Pig Lung and Online Platform Exploring for Lung Single Cell
Authors: Zhang Lijing , Zhu Jiacheng , Wang Haoyu , Xia Jun , Liu Ping , Chen Fang , Jiang Hui , Wu Weiying , Luo Lihua , Chen Dongsheng , Zhang Xingliang
Published: December 2020

Due to the comparable organ sizes and physiology to human beings, genetically engineered pig is gradually regarded as an optimal source of human for transplantation and an excellent model for human diseases research. The major barrier between pig and human is mainly cellular heterogeneity and immune incompatibilities. Myriad scRNA-seq data of human has been reported, but the counterpart in pig is scarce. Here, we applied scRNA-seq technology to study the cellular heterogeneity of 3 months old pig lungs, generating the single-cell atlas of 13,580 cells covering 16 major cell types. Based on this data, we systematically characterized transcription factor regulatory networks, cell-cell communications in each cell type, and comparison of them and those in human lung. We first presented a comprehensive and openly accessible online platform, ScdbLung, which was composed of three functional modules (Marker, Cluster, and Download) and dedicated to exploiting the valuable resources of lung scRNA-seq data across four mammalian species. Overall, our scRNA-seq atlas of domestic pig lung, conserved transcription factor regulatory networks and cell-cell communications between domestic pig and human, and ScdbLung could provide guidance for porcine lung research and clinical applicability.
Sexual conflict drives micro- and macroevolution of sexual dimorphism in immunity
Authors: Bagchi Basabi , Corbel Quentin , Khan Imroze , Payne Ellen , Banerji Devshuvam , Liljestrand-Rönn Johanna , Martinossi-Allibert Ivain , Baur Julian , Sayadi Ahmed , Immonen Elina , Arnqvist Göran , Söderhäll Irene , Berger David
Published: December 2020

Background

Sexual selection can have major effects on mating rates and sex-specific costs of mating and may thereby influence sex-differences in immunity as well as associated host-pathogen dynamics. Yet, experimental evidence linking the mating system to evolved sexual dimorphism in immunity are scarce and the direct effects of mating rate on immunity are not well established. Here, we use transcriptomic analyses, experimental evolution and phylogenetic comparative methods to study the association between the mating system and sexual dimorphism in immunity in seed beetles, where mating causes internal injuries in females.

Results

We demonstrate that female phenoloxidase (PO) activity, involved in wound healing and defence against parasitic infections, is elevated relative to males. This difference is accompanied by concomitant sex-differences in the expression of genes in the pro-phenoloxidase activating cascade. We document substantial phenotypic plasticity in female PO activity in response to mating and show that experimental evolution under enforced monogamy (resulting in low remating rates and sexual conflict relative to natural polygamy) rapidly decreases female (but not male) PO activity. Moreover, monogamous females have evolved increased tolerance to bacterial infection unrelated to mating, implying that female responses to costly mating may trade off with other aspects of immune defence, an hypothesis which broadly accords with the documented sex differences in gene expression. Finally, female (but not male) PO activity shows correlated evolution with the perceived harmfulness of male genitalia across 12 species of seed beetles, suggesting that sexual conflict has a significant influence on sexual dimorphisms in immunity in this group of insects.

Conclusions

Our study provides insights into the links between sexual conflict and sexual dimorphism in immunity at the molecular and phenotypic level and suggests that selection pressures moulded by mating interactions can lead to a sex-specific mosaic of immune responses with important implications for host-pathogen dynamics in sexually reproducing organisms.
Large variation in the association between seasonal antibiotic use and resistance across multiple bacterial species and antibiotic classes
Authors: Sun Daphne S. , Kissler Stephen M. , Kanjilal Sanjat , Olesen Scott W. , Lipsitch Marc , Grad Yonatan H.
Published: December 2020

Understanding how antibiotic use drives resistance is crucial for guiding effective strategies to limit the spread of resistance, but the use-resistance relationship across pathogens and antibiotics remains unclear. We applied sinusoidal models to evaluate the seasonal use-resistance relationship across 3 species (Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae) and 5 antibiotic classes (penicillins, macrolides, quinolones, tetracyclines, and nitrofurans) in Boston, Massachusetts. Use of all 5 classes and resistance in 9 of 15 species-antibiotic combinations showed statistically significant amplitudes of seasonality (false discovery rate < 0.05). While seasonal peaks in use varied by class, resistance in all 9 species-antibiotic combinations peaked in the winter and spring. The correlations between seasonal use and resistance thus varied widely, with resistance to all antibiotic classes being most positively correlated with use of the winter-peaking classes (penicillins and macrolides). These findings challenge the simple model of antibiotic use independently selecting for resistance and suggest that stewardship strategies will not be equally effective across all species and antibiotics. Rather, seasonal selection for resistance across multiple antibiotic classes may be dominated by use of the most highly prescribed antibiotic classes, penicillins and macrolides.
pH and Receptor Induced Conformational Changes-Implications Towards S1 Dissociation of SARS-CoV2 Spike Glycoprotein
Authors: Castin Jesu E. , Gideon Daniel A. , Sudarsha Karthik S. , Rosita Sherlin A.
Published: December 2020

Viruses, being obligate intracellular parasites, must first attach themselves and gain entry into host cells. Viral fusion machinery is the central player in the viral attachment process in almost every viral disease. Viruses have incorporated an array of efficient fusion proteins on their surfaces to bind efficiently to host cell receptors. They make use of the host proteolytic enzymes to rearrange their surface protein(s) into the form which facilitates their binding to host-cell membrane proteins and subsequently, fusion. This stage of viral entry is very critical and has many therapeutic implications. The current global pandemic of COVID-19 has sparked severe health crisis and economic shutdowns. SARS-CoV2, the etiological agent of the disease has led to millions of deaths and brought the scientific community together in an attempt to understand the mechanisms of SARS-CoV2 pathogenesis and mortality. Like other viral fusion machinery, CoV2 spike (S) glycoprotein- ‘The Demogorgon’ poses the same questions about viral-host cell fusion. The intermediate stages of S protein-mediated viral fusion are unclear owing to the lack of structural insights and concrete biochemical evidence. The mechanism of conformational transition is still unclear. S protein binding and fusion with host cell receptors, Eg., angiotensin-converting enzyme-2 (ACE2) is accompanied by cleavage of S1/S2 subunits. To track the key events of viral-host cell fusion, we have identified (in silico) that low pH-induced conformational change and ACE-2 binding events promote S1 dissociation. Deciphering key mechanistic insights of SARS-CoV2 fusion will further our understanding of other class-I fusion proteins
The impacts of biofuel crops on local biodiversity: a global synthesis
Authors: Tudge Sophie Jane , Purvis Andy , De Palma Adriana
Published: December 2020

Concerns about the environmental impacts of climate change have led to increased targets for biofuel in the global energy market. First-generation biofuel crops contain oil, sugar or starch and are usually also grown for food, whereas second-generation biofuel is derived from non-food sources, including lignocellulosic crops, fast-growing trees, crop residues and waste. Increasing biofuel production drives land-use change, a major cause of biodiversity loss, but there is limited knowledge of how different first- and second-generation biofuel crops affect local biodiversity. A more detailed understanding could support better decisions about the net environmental impacts of biofuels. We synthesised data from 116 sources where a potential biofuel crop was grown and estimated how two measures of local biodiversity, species richness and total abundance, responded to different crops. Local species richness and abundance were 37% and 49% lower at sites planted with first-generation biofuel crops than in sites with primary vegetation. Soybean, wheat, maize and oil palm had the worst effects; the worst affected regions were Asia and Central and South America; and plant species richness and vertebrate abundance were the worst affected biodiversity measures. Second-generation biofuels had significantly smaller effects: species richness and abundance were 19% and 25%, respectively, lower in such sites than in primary vegetation. Our models suggest that land clearance to generate biofuel results in negative impacts on local biodiversity. However, the geographic and taxonomic variation in effects, and the variation in yields among different crops, are all relevant for making the most sustainable land-use decisions.
Pastures and Climate Extremes: Impacts of cool season warming and drought on the productivity of key pasture species in a field experiment
Authors: Churchill Amber C. , Zhang Haiyang , Fuller Kathryn J. , Amiji Burhan , Anderson Ian C. , Barton Craig V. M. , Carrillo Yolima , Catunda Karen L. M. , Chandregowda Manjunatha H. , Igwenagu Chioma , Jacob Vinod , Kim Gil Won , Macdonald Catriona A. , Medlyn Belinda E. , Moore Ben D. , Pendall Elise , Plett Jonathan M. , Post Alison K. , Powell Jeff R. , Tissue David T. , Tjoelker Mark G. , Power Sally A.
Published: December 2020

Shifts in the timing, intensity and/or frequency of climate extremes, such as severe drought and heatwaves, can generate sustained shifts in ecosystem function with important ecological and economic impacts for rangelands and managed pastures. The Pastures and Climate Extremes experiment (PACE) in Southeast Australia was designed to investigate the impacts of a severe winter/spring drought (60% rainfall reduction) and, for a subset of species, a factorial combination of drought and elevated temperature (ambient +3 °C) on pasture productivity. The experiment included nine common pasture and Australian rangeland species from three plant functional groups (C3grasses, C4grasses and legumes) planted in monoculture. Winter/spring drought resulted in productivity declines of 45% on average and up to 74% for the most affected species (Digitaria eriantha) during the 6-month treatment period, with eight of the nine species exhibiting significant yield reductions. Despite considerable variation in species’ sensitivity to drought, C4grasses were more strongly affected by this treatment than C3grasses or legumes. Warming also had negative effects on cool-season productivity, associated at least partially with exceedance of optimum growth temperatures in spring and indirect effects on soil water content. The combination of winter/spring drought and year-round warming resulted in the greatest yield reductions. We identified responses that were either additive such that there was only as significant warming effect under drought (Festuca), or less-than-additive, where there was no drought effect under warming (Medicago), compared to ambient plots. Results from this study highlight the sensitivity of diverse pasture species to increases in winter and spring drought severity similar to those predicted for this region, and that anticipated benefits of cool-season warming are unlikely to be realised. Overall, the substantial negative impacts on productivity suggest that future, warmer, drier climates will result in shortfalls in cool-season forage availability, with profound implications for the livestock industry and natural grazer communities.
The 3D architecture and molecular foundations of de novo centriole assembly via bicentrioles
Authors: Gomes Pereira Sónia , Sousa Ana Laura , Nabais Catarina , Paixão Tiago , Holmes Alexander J. , Schorb Martin , Goshima Gohta , Tranfield Erin M. , Becker Jörg D. , Bettencourt-Dias Mónica
Published: December 2020

Centrioles are structurally conserved organelles, composing both centrosomes and cilia. In animal cycling cells, centrioles often form through a highly characterized process termed canonical duplication. However, a large diversity of eukaryotes form centrioles de novo through uncharacterized pathways. This unexplored diversity is key to understanding centriole assembly mechanisms and how they evolved to assist specific cellular functions. Here, combining electron microscopy and tomography, we show that during spermatogenesis of the moss Physcomitrium patens, centrioles are born as a co-axially oriented centriole pair united by a cartwheel. We observe that microtubules emanate from those bicentrioles, which localize to the spindle poles during cell division. Thereafter, each bicentriole breaks apart, and the two resulting sister centrioles mature asymmetrically, elongating specific microtubule triplets and a naked cartwheel. Subsequently, two cilia are assembled which are capable of beating asynchronously. We further show that conserved cartwheel and centriole wall components, SAS6, BLD10 and POC1 are expressed during spermatogenesis and are required for this de novo biogenesis pathway. Our work supports a scenario where centriole biogenesis is more diverse than previously thought and that conserved molecular modules underlie diversification of this essential pathway.
VirStrain: a strain identification tool for RNA viruses
Authors: Liao Herui , Cai Dehan , Sun Yanni
Published: December 2020

Genome epidemiology, which uses genomic data to analyze the source and spread of infectious diseases, provides important information beyond interview-based methods. Given fast accumulation of sequenced viral genomes, a basic need in genome epidemiology is to identify which reference genomes are identical or closest to the ones in a sequenced sample. Then the associated metadata such as the geographical locations can be utilized to infer the transmission network. In this work, we deliver VirStrain, a fast and accurate tool for conducting strain-level analysis from short reads. By using a greedy covering algorithm, we are able to derive unique k-mer combinations for highly similar reference genomes. VirStrain is able to
detect the most possible strain and also multiple strains that may simultaneously infect the same host. We tested VirStrain on three types of RNA viruses whose reference genomes have different similarity distributions. For each types of virus, we assessed VirStrain across multiple benchmark datasets of different properties and complexity. The experimental results on both simulated and real sequencing data show that VirStrain outperforms other strain identification tools.
Identification of potential and novel target genes in pituitary prolactinoma by bioinformatics analysis
Authors: Ghatnatti Vikrant , Vastrad Basavaraj , Patil Swetha , Vastrad Chanabasayya , Kotturshetti Iranna
Published: December 2020

Pituitary prolactinoma is one of the most complicated and fatally pathogenic pituitary adenomas. Therefore, there is an urgent need to improve our understanding of the underlying molecular mechanism that drives the initiation, progression, and metastasis of pituitary prolactinoma. The aim of the present study was to identify the key genes and signaling pathways associated with pituitary prolactinoma using bioinformatics analysis. Transcriptome microarray dataset GSE119063 was acquired from Gene Expression Omnibus datasets, which included 5 pituitary prolactinoma samples and 4 normal pituitaries samples. We screened differentially expressed genes (DEGs) with limma and investigated their biological function by pathway and Gene Ontology (GO) enrichment analysis. A protein-protein interaction (PPI) network of the up and down DEGs were constructed and analyzed by HIPPIE and Cytoscape software. Module analyses were performed. In addition, a target gene - miRNA network and target gene - TF network of the up and down DEGs were constructed by NetworkAnalyst and Cytoscape software. The set of DEGs exhibited an intersection consisting of 989 genes (461 up-regulated and 528 down-regulated), which may be associated with pituitary prolactinoma. Pathway enrichment analysis showed that the 989 DEGs were significantly enriched in the retinoate biosynthesis II, signaling pathways regulating pluripotency of stem cells, ALK2 signaling events, vitamin D3 biosynthesis, cell cycle and aurora B signaling. Gene Ontology (GO) enrichment analysis also showed that sensory organ morphogenesis, extracellular matrix, hormone activity, nuclear division, condensed chromosome and microtubule binding. In the PPI network and modules, SOX2, PRSS45, CLTC, PLK1, B4GALT6, RUNX1 and GTSE1 were considered as hub genes. In the target gene miRNA network and target gene - TF network, LINC00598, SOX4, IRX1 and UNC13A were considered as hub genes. Using integrated bioinformatics analysis, we identified candidate genes in pituitary prolactinoma, which may improve our understanding of the mechanisms of the pathogenesis and integration; genes may be therapeutic targets and prognostic markers for pituitary prolactinoma.
Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches
Authors: Onisiforou Anna , Spyrou George M.
Published: December 2020

During the course of a viral infection, virus-host protein-protein interactions (PPIs) play a critical role in allowing viruses to evade host immune responses, replicate and hence survive within the host. These interspecies molecular interactions can lead to viral-mediated perturbations of the human interactome causing the generation of various complex diseases, from cancer to neurodegenerative diseases (NDs). There are evidences suggesting that viral-mediated perturbations are a possible pathogenic aetiology in several NDs such as Amyloid Later Sclerosis, Parkinson’s disease, Alzheimer’s disease and Multiple Sclerosis (MS), as they can cause degeneration of neurons via both direct and/or indirect actions. These diseases share several common pathological mechanisms, as well as unique disease mechanisms that reflect disease phenotype. NDs are chronic degenerative diseases of the central nervous system and current therapeutic approaches provide only mild symptomatic relief rather than treating the disease at heart, therefore there is unmet need for the discovery of novel therapeutic targets and pharmacotherapies. In this paper we initially review databases and tools that can be utilized to investigate viral-mediated perturbations in complex NDs using network-based analysis by examining the interaction between the ND-related PPI disease networks and the virus-host PPI network. Afterwards we present our integrative network-based bioinformatics approach that accounts for pathogen-genes-disease related PPIs with the aim to identify viral-mediated pathogenic mechanisms focusing in MS disease. We identified 7 high centrality nodes that can act as disease communicator nodes and exert systemic effects in the MS enriched KEGG pathways network. In addition, we identified 12 KEGG pathways targeted by 67 viral proteins from 8 viral species that might exert viral-mediated pathogenic mechanisms in MS by interacting with the disease communicator nodes. Finally, our analysis highlighted the Th17 differentiation pathway, a hub-bottleneck disease communicator node and part of the 12 underlined KEGG pathways, as a key viral-mediated pathogenic mechanism and a possible therapeutic target for MS disease.
Interpreting coronary artery disease GWAS results: A functional genomics approach assessing biological significance
Authors: Hartmann Katherine , Seweryn Michał , Sadee Wolfgang
Published: December 2020

Genome-wide association studies (GWAS) have implicated 58 loci in coronary artery disease (CAD). However, the biological basis for these associations, the relevant genes, and causative variants often remain uncertain. Since the vast majority of GWAS loci reside outside coding regions, most exert regulatory functions. Here we explore the complexity of each of these loci, using tissue specific RNA sequencing data from GTEx to identify genes that exhibit altered expression patterns in the context of GWAS-significant loci, expanding the list of candidate genes from the 75 currently annotated by GWAS to 245, with almost half of these transcripts being non-coding. Tissue specific allelic expression imbalance data, also from GTEx, allows us to uncover GWAS variants that mark functional variation in a locus,e.g., rs7528419 residing in theSORT1locus, in liver specifically, and rs72689147 in theGUYC1A1locus, across a variety of tissues. We consider the GWAS variant rs1412444 in the LIPA locus in more detail as an example, probing tissue and transcript specific effects of genetic variation in the region. By evaluating linkage disequilibrium (LD) between tissue specific eQTLs, we reveal evidence for multiple functional variants within loci. We identify 3 variants (rs1412444, rs1051338, rs2250781) that when considered together, each improve the ability to account for LIPA gene expression, suggesting multiple interacting factors. These results refine the assignment of 58 GWAS loci to likely causative variants in a handful of cases and for the remainder help to re-prioritize associated genes and RNA isoforms, suggesting that ncRNAs maybe a relevant transcript in almost half of CAD GWAS results. Our findings support a multifactorial system where a single variant can influence multiple genes and each genes is regulated by multiple variants.
Functional Aspects of the Eustachian Tube by Means of 3D-Modeling
Authors: Robert Schuon , Schwarzensteiner Josef , Paasche Gerrit , Thomas Lenarz , John Samuel
Published: December 2020

The extent of dysfunction of the Eustachian tube (ET) is relevant in understanding the pathogenesis of secondary otological diseases such as acute or chronic otitis media. The underlying mechanism of ET dysfunction remains poorly understood except for an apparent genesis such as a nasopharyngeal tumor or cleft palate. To better describe the ET, its functional anatomy, and the biomechanical valve mechanism and subsequent development of diagnostic and interventional tools, a three-dimensional model based on thin-layer histology was created from an ET in this study. Blackface sheep was chosen as a donor. The 3-D model was generated by the coherent alignment of the sections. It was then compared with the cone-beam computed tomography dataset of the complete embedded specimen taken before slicing. The model shows the topographic relation of the individual components, such as the bone and cartilage, the muscles and connective tissue, as well as the lining epithelium with the lumen. It indicates a limited spiraling rotation of the cartilaginous tube over its length and relevant positional relationships of the tensor and levator veli palatine muscles.
ISSRseq: an extensible method for reduced representation sequencing
Authors: Sinn Brandon T. , Simon Sandra J. , Santee Mathilda V. , DiFazio Stephen P. , Fama Nicole M. , Barrett Craig F.
Published: December 2020

The capability to generate densely sampled single nucleotide polymorphism (SNP) data is essential in diverse subdisciplines of biology, including crop breeding, pathology, forensics, forestry, ecology, evolution, and conservation. However, the wet-lab expertise and bioinformatics training required to conduct genome-scale variant discovery remain limiting factors for investigators with limited resources.

Here we present ISSRseq, a PCR-based method for reduced representation of genomic variation using simple sequence repeats as priming sites to sequence inter simple sequence repeat (ISSR) regions. Briefly, ISSR regions are amplified with single primers, pooled, used to construct sequencing libraries with a commercially-available kit, and sequenced on the Illumina platform. We also present a flexible bioinformatic pipeline that assembles ISSR loci, calls and hard filters variants, outputs data matrices in common formats, and conducts population analyses using R.

Using three angiosperm species as case studies, we demonstrate that ISSRseq is highly repeatable, necessitates only simple wet-lab skills and commonplace instrumentation, is flexible in terms of the number of single primers used, and can generate genomic-scale variant discovery on par with existing RRS methods which require more complex wet lab procedures.

ISSRseq represents a straightforward approach to SNP genotyping in any organism, and we predict that this method will be particularly useful for those studying population genomics and phylogeography of non-model organisms. Furthermore, the ease of ISSRseq relative to other RRS methods should prove useful to those lacking advanced expertise in wet lab methods or bioinformatics.
Label2label: Training a neural network to selectively restore cellular structures in fluorescence microscopy
Authors: Kölln Lisa Sophie , Salem Omar , Valli Jessica , Hansen Carsten Gram , McConnell Gail
Published: December 2020

Fluorescence microscopy is an essential tool in cell biology to visualise the spatial distribution of proteins that dictates their role in cellular homeostasis, dynamic cellular processes, and dysfunction during disease. However, unspecific binding of the antibodies that are used to label a cellular target often leads to high background signals in the images, decreasing the contrast of a cellular structure of interest. Recently, convolutional neural networks (CNNs) have been successfully employed for denoising and upsampling in fluorescence microscopy, but current image restoration methods cannot correct for background signals originating from the label. Here, we report a new method to train a CNN as content filter for non-specific signals in fluorescence images that does not require a clean benchmark, using dual-labelling to generate the training data. We name this methodlabel2label(L2L). In L2L, a CNN is trained with image pairs of two non-identical labels that target the same cellular structure of interest. We show that after L2L training a network restores images not only with reduced image noise but also label-induced unspecific fluorescence signal in images of a variety of cellular structures, resulting in images with enhanced structural contrast. By implementing a multi-scale structural similarity loss function, the performance of the CNN as a content filter is further enhanced, for example, in STED images of caveolae. We show evidence that, for this loss function, sample differences in the training data significantly decrease so-called hallucination effects in the restorations that we otherwise observe when training the CNN with images of the same label. We also assess the performance of a cycle generative adversarial network as a content filter after L2L training with unpaired image data. Lastly, we show that a CNN can be trained to separate structures in superposed fluorescence images of two different cellular targets, allowing multiplex imaging with microscopy setups where the number of excitation sources or detectors is limited.
Restoration ecologists might not get what they want: Global change shifts trade-offs among ecosystem functions
Authors: Fiedler Sebastian , Monteiro José A.F. , Hulvey Kristin B. , Standish Rachel J. , Perring Michael P. , Tietjen Britta
Published: December 2020

Ecological restoration increasingly aims at improving ecosystem multifunctionality and making landscapes resilient to future threats, especially in biodiversity hotspots such as Mediterranean-type ecosystems. Successful realisation of such a strategy requires a fundamental mechanistic understanding of the link between ecosystem plant composition, plant traits and related ecosystem functions and services, as well as how climate change affects these relationships. An integrated approach of empirical research and simulation modelling with focus on plant traits can allow this understanding.

Based on empirical data from a large-scale restoration project in a Mediterranean-type climate in Western Australia, we developed and validated the spatially explicit simulation model ModEST, which calculates coupled dynamics of nutrients, water and individual plants characterised by traits. We then simulated all possible combinations of eight plant species with different levels of diversity to assess the role of plant diversity and traits on multifunctionality, the provision of six ecosystem functions (covering three ecosystem services), as well as trade-offs and synergies among the functions under current and future climatic conditions.

Our results show that multifunctionality cannot fully be achieved because of trade-offs among functions that are attributable to sets of traits that affect functions differently. Our measure of multifunctionality was increased by higher levels of planted species richness under current, but not future climatic conditions. In contrast, single functions were differently impacted by increased plant diversity. In addition, we found that trade-offs and synergies among functions shifted with climate change.

Synthesis and application. Our results imply that restoration ecologists will face a clear challenge to achieve their targets with respect to multifunctionality not only under current conditions, but also in the long-term. However, once ModEST is parameterized and validated for a specific restoration site, managers can assess which target goals can be achieved given the set of available plant species and site-specific conditions. It can also highlight which species combinations can best achieve long-term improved multifunctionality due to their trait diversity.
Repurposing Nintedanib for Pathological Cardiac Remodeling and Dysfunction
Authors: Umbarkar Prachi , Singh Anand P. , Tousif Sultan , Zhang Qinkun , Sethu Palaniappan , Lal Hind
Published: December 2020

Background

Heart Failure (HF) is the leading cause of death worldwide. Myocardial fibrosis, one of the clinical manifestations implicated in almost every form of heart disease, contributes significantly to HF development. However, there is no approved drug specifically designed to target cardiac fibrosis. Nintedanib (NTB) is an FDA approved tyrosine kinase inhibitor for idiopathic pulmonary fibrosis (IPF) and chronic fibrosing interstitial lung diseases (ILD). The favorable clinical outcome of NTB in IPF patients is well established. Furthermore, NTB is well tolerated in IPF patients irrespective of cardiovascular comorbidities. However, there is a lack of direct evidence to support the therapeutic efficacy and safety of NTB in cardiac diseases.

Methods and Results

We examined the effects of NTB treatment on cardiac fibrosis and dysfunction using a murine model of HF. Specifically, 10 weeks old C57BL/6J male mice were subjected to Transverse Aortic Constriction (TAC) surgery. NTB was administered once daily by oral gavage (50mg/kg) till 16 weeks post-TAC. Cardiac function was monitored by serial echocardiography. Histological analysis and morphometric studies were performed at 16 weeks post-TAC. In the control group, systolic dysfunction started developing from 4 weeks post-surgery and progressed till 16 weeks. However, NTB treatment prevented TAC-induced cardiac functional decline. In another experiment, NTB treatment was stopped at 8 weeks, and animals were followed till 16 weeks post-TAC. Surprisingly, NTB’s beneficial effect on cardiac function was maintained even after treatment interruption. NTB treatment remarkably reduced cardiac fibrosis as confirmed by Masson’s trichome staining and decreased expression of collagen genes (COL1A1, COL3A1). Compared to TAC group, NTB treated mice showed lower HW/TL ratio and cardiomyocyte cross-sectional area. Ourin vitrostudies demonstrated that NTB prevents myofibroblast transformation, TGFβ1-induced SMAD3 phosphorylation, and production of fibrogenic proteins (Fibronectin-1). However, NTB significantly altered vital signaling pathways in both, isolated fibroblast and cardiomyocytes, suggesting that its biological effect and underlying cardiac protection mechanisms are not limited to fibroblast and fibrosis alone.

Conclusion

Our findings provide a proof of concept for repurposing NTB to combat adverse myocardial fibrosis and encourage the need for further validation in large animal models and subsequent clinical development for HF patients.
Fast and memory-efficient mapping of short bisulfite sequencing reads using a two-letter alphabet
Authors: de Sena Brandine Guilherme , Smith Andrew D.
Published: December 2020

DNA cytosine methylation is an important epigenomic mark with a wide range of functions across many organisms. Whole genome bisulfite sequencing (WGBS) is the gold standard to interrogate cyto-sine methylation genome-wide. Algorithms used to map WGBS reads often encode the four-base DNA alphabet with three letters by reducing two bases to a common letter. This encoding substantially reduces the entropy of nucleotide frequencies in the resulting reference genome. Within the paradigm of read mapping by first filtering possible candidate alignments, reduced entropy of the reference can increase the required computing effort. We introduce another bisulfite mapping algorithm (abismal), based on the idea of encoding a four-letter DNA sequence as only two letters, one for purines and one for pyrimidines. We show that this encoding has greater specificity when subsequences are selected from reads for filtration. Through the two-letter encoding, the abismal software tool maps reads in less time and using less memory than most WGBS read mapping software tools, while attaining similar accuracy. This allowsin silicomethylation analysis to be performed in a wider range of computing machines with limited hardware settings.
Combinatorial approach of binary colloidal crystals (BCCs) and CRISPR activation to improve induced pluripotent stem cell differentiation into neurons
Authors: Urrutia-Cabrera Daniel , Liou Roxanne Hsiang-Chi , Lin Jiao , Liu Kun , Hung Sandy S.C. , Hewitt Alex W. , Wang Peng-Yuan , Wong Raymond Ching-Bong
Published: December 2020

Conventional methods of neuronal differentiation for human induced pluripotent stem cells (iPSCs) are tedious and complicated, involving multi-stage protocols with complex cocktails of growth factors and small molecules. Artificial extracellular matrix with defined surface topography and chemistry represents a promising venue to improve the neuronal differentiationin vitro. In the present study, we test the impact of a type of colloidal self-assembled patterns called binary colloidal crystals (BCCs) in neuronal differentiation. We developed a CRISPR activation (CRISPRa) iPSC platform that constitutively expresses the dCas9-VPR system, which allows robust activation of the proneural transcription factorNEUROD1to rapidly induce neuronal differentiation within seven days. We showed that the combinatorial use of BCCs can further improve this neuronal differentiation system. In particular, our results indicate that fine tuning of silica and polystyrene size is critical to generate specific topographies to improve neuronal differentiation and branching. BCCs with 5 μm silica and 100 nm carboxylated polystyrene has the most prominent effect on increasing neurite outgrowth and more complex ramification, while BCCs with 2μm silica and 65nm carboxylated polystyrene is better in promoting neuronal enrichment. These results indicate that biophysical cues can support rapid differentiation and improve neuronal maturation. In summary, our combinatorial approach of CRISPRa and BCCs provides a robust and rapid pipeline forin vitroproduction of human neurons. Specific BCCs can be adapted to late stages of neuronal differentiation protocols to improve neuronal maturation, which have important implications in tissue engineering,in vitrobiological studies and disease modeling.
Genome-wide reversal of glial and neurovascular cell transcriptomic aging signatures by GLP-1R agonism
Authors: Li Zhongqi , Chen Xinyi , Vong Joaquim S. L. , Zhao Lei , Huang Junzhe , Yan Leo Y. C. , Ip Bonaventure , Wing Yun Kwok , Lai Hei-Ming , Mok Vincent C. T. , Ko Ho
Published: December 2020

Pharmacological reversal of brain aging is a long-sought yet challenging strategy for the prevention and treatment of age-related neurodegeneration, due to the diverse cell types and complex cellular pathways impacted by the aging process. Here, we report the genome-wide reversal of transcriptomic aging signatures in multiple major brain cell types, including glial and mural cells, by glucagon-like peptide-1 receptor (GLP-1R) agonist (GLP-1RA) treatment. The age-related expression changes reversed by GLP-1RA encompass both shared and cell type-specific functional pathways that are implicated in aging and neurodegeneration. Concomitantly, Alzheimer’s disease (AD)-associated transcriptomic signature in microglia that arises from aging is reduced. These results show the feasibility of reversing brain aging by pharmacological means, provide mechanistic insights into the neurological benefits of GLP-1RAs in diabetic patients, and imply that GLP-1R agonism may be a generally applicable pharmacological intervention for patients at risk of age-related neurodegeneration.
Social disparities in the first wave of COVID-19 infections in Germany: A county-scale explainable machine learning approach
Authors: Doblhammer Gabriele , Reinke Constantin , Kreft Daniel
Published: December 2020

Background

Little is known about factors correlated with this geographic spread of the first wave of COVID-19 infections in Germany. Given the lack of individual-level socioeconomic information on COVID-19 cases, we resorted to an ecological study design, exploring regional correlates of COVID-19 diagnoses.

Data and Method

We used data from the Robert-Koch-Institute on COVID-19 diagnoses by sex, age (age groups: 0-4, 5-14, 15-34, 35-59, 60-79, 80+), county (NUTS3 region) differentiating five periods (initial phase: through 15 March; 1st lockdown period: 16 March to 31 March; 2nd lockdown period: from 1 April to 15 April; easing period: 16 April to 30 April; post-lockdown period: 1 May through 23 July). For each period we calculated age-standardized incidence of COVID-19 diagnoses on the county level, using the German age distribution from the year 2018. We characterized the regions by macro variables in nine domains: “Demography”, “Employment”, “Politics, religion, and education”, “Income”, “Settlement structure and environment”, “Health care”, “(structural) Poverty”, “Interrelationship with other regions”, and “Geography”. We trained gradient boosting models to predict the age-standardized incidence rates with the macro structures of the counties, and used SHAP values to characterize the 20 most prominent features in terms of negative/positive correlations with the outcome variable.

Results

The change in the age-standardized incidence rates over time is reflected in the changing importance of features as indicated by the mean SHAP values for the five periods. The first COVID-19 wave started as a disease in wealthy rural counties in southern Germany, and ventured into poorer urban and agricultural counties during the course of the first wave. The negative social gradient became more pronounced from the 2ndlockdown period onwards, when wealthy counties appeared to be better protected. Population density per se does not appear to be a risk factor, and only in the post-lockdown period did connectedness become an important regional characteristic correlated with higher infections. Features related to economic and educational characteristics of the young population in a county played an important role at the beginning of the pandemic up to the 2ndlockdown phase, as did features related to the population living in nursing homes; those related to international migration and a large proportion of foreigners living in a county became important in the post-lockdown period.

Discussion

In the absence of individual level data, explainable machine learning methods based on regional data may help to better understand the changing nature of the drivers of the pandemic. High mobility of high SES groups may drive the pandemic at the beginning of waves, while mitigation measures and beliefs about the seriousness of the pandemic as well as the compliance with mitigation measures put lower SES groups at higher risks later on.