bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychosocial Factors Affecting Parental Report of Symptoms in Children: A Systematic Review
Authors: Smith Louise E. , Weinman John , Yiend Jenny , Rubin James
Published: November 2019

Objective

Parents make important treatment decisions for their children based on symptoms they perceive their child to be experiencing. Multiple psychological factors are associated with subjective symptom perception, but factors affecting perception of symptoms in others have been explored less. We systematically reviewed the literature to identify parent and child psychological factors associated with parental report of physical symptoms in their child.

Methods

We searched Embase, Ovid, PsycINFO, and Scopus for studies that investigated associations between psychological factors and parental report of symptoms in their child.

Results

Thirty-six citations reporting on 34 studies that assessed the association between parent or child psychological factors and parental report of physical symptoms in the child were included in the review. Three main factors were identified as being associated with parental symptom report. First, there was evidence for an association between parental symptom report and affect, in particular parent and child anxiety. Second, child behavioral and conduct problems, and temperament-related challenges (problems with feeding and sleeping) were associated with parental symptom report. Third, parental expectations and beliefs that symptoms would occur were associated with parental symptom report, although few studies investigated these associations.

Conclusions

Parent and child affect, and parental expectations and beliefs may influence parents’ cognition, causing them to pay more attention to their child, interpret their child’s behavior as symptomatic, and recall symptoms in the child. Given the importance of parental perception of symptoms in driving decisions around care, additional research in this field is needed.
Exploring the cerebral substrate of voice perception in primate brains
Authors: Bodin Clémentine , Belin Pascal
Published: November 2019

One can consider human language to be the Swiss army knife of the vast domain of animal communication. There is now growing evidence suggesting that this technology may have emerged from already operational material instead of being a sudden innovation. Sharing ideas and thoughts with conspecifics via language constitutes an amazing ability, but what value would it hold if our conspecifics were not first detected and recognized? Conspecific voice (CV) perception is fundamental to communication and widely shared across the animal kingdom. Two questions that arise then are: is this apparently shared ability reflected in common cerebral substrate? And, how has this substrate evolved? The paper addresses these questions by examining studies on the cerebral basis of CV perception in humans' closest relatives, non-human primates. Neuroimaging studies, in particular, suggest the existence of a ‘voice patch system’, a network of interconnected cortical areas that can provide a common template for the cerebral processing of CV in primates.

This article is part of the theme issue ‘What can animal communication teach us about human language?’
Animal cognition and the evolution of human language: why we cannot focus solely on communication
Authors: Fitch W. Tecumseh
Published: November 2019

Studies of animal communication are often assumed to provide the ‘royal road’ to understanding the evolution of human language. After all, language is the pre-eminent system of human communication: doesn't it make sense to search for its precursors in animal communication systems? From this viewpoint, if some characteristic feature of human language is lacking in systems of animal communication, it represents a crucial gap in evolution, and evidence for an evolutionary discontinuity. Here I argue that we should reverse this logic: because a defining feature of human language is its ability to flexibly represent and recombine concepts, precursors for many important components of language should be sought in animalcognitionrather than animal communication. Animal communication systems typically only permit expression of a small subset of the concepts that can be represented and manipulated by that species. Thus, if a particular concept is not expressed in a species' communication system this is not evidence that it lacks that concept. I conclude that if we focus exclusively on communicative signals, we sell the comparative analysis of language evolution short. Therefore, animal cognition provides a crucial (and often neglected) source of evidence regarding the biology and evolution of human language.

This article is part of the theme issue ‘What can animal communication teach us about human language?’
Factors associated with risk of developmental delay in preschool children in a setting with high rates of malnutrition: a cross-sectional analysis of data from the IHOPE study, Madagascar
Authors: Miller Ann C. , Garchitorena Andres , Rabemananjara Faramalala , Cordier Laura , Randriamanambintsoa Marius , Rabeza Victor , Razanadrakoto Hery-Tiana Rahaniraka , Ramakasoa Ranaivozafindary Rakoto , RamahefarisonTiana Olivier , Ratsimbazafy Baolova Nathaline , Ouenzar Mohammed Ali , Bonds Matthew H. , Ratsifandrihamanana Lisy
Published: November 2019

Background

Nearly two hundred eighty million children in low and middle income countries are at risk for not achieving their full developmental potential(1). Poor development can lead to reduced scholastic ability(2) or opportunity (promoting and entrenching inequity), and has been associated with lower adult earning potential(3), and poorer health(4), thus potentially contributing to intergenerational poverty traps.

While the entire period of childhood is important for development, the first 1000 days (conception to age 2) are critically important for brain development; with the most rapid and prolific development of neural pathways, first in sensory development, then language skills and then higher cognitive functioning(5). Experiences during this period – positive or negative – can substantially impact the architecture of the developing brain. Adverse events such as exposure to familial or societal violence, toxins such as lead or arsenic, illness (anemia, diarrhea, HIV, chronic malnutrition, maternal depression), or lack of a developmentally stimulating and nurturing environment can all act as toxic stressors on young children that negatively impact cognitive development throughout the life-course(6). Infants and young children in settings of poverty are often faced with many of these stressors(7).
Methylenetetrahydrofolate reductase (MTHFR) A1298C polymorphism and risk of lung cancer
Authors: Rai Vandana
Published: November 2019

Recent epidemiological studies have reported association between methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms and lung cancer. The aim of the present study to perform a meta-analysis of published studies to validate the association between MTHFR A1298C polymorphism and risk of lung cancer.PubMed, Springer Link, Science Direct and Google Scholar databases were searched for eligible studies. Of the 78 initially identified studies, 11 case–control studies with 5,996 patients and 7,404 healthy controls were finally included in the present meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association, and all statistical analyses were performed using MIX software (version 1.7).

No statistically significant associations were found between the MTHFR A1298C polymorphism and lung cancer risk in the additive/ allele contrast, co-dominant/heterozygote, homozygote, dominant and recessive genetic models (C vs. A: OR= 0.95, 95% CI= 0.83-1.08; CC vs. AA: OR= 1.13, 95% CI= 0.83-1.5; AC vs. AA: OR= 0.86, 95% CI= 0.70-1.02; AC+CC vs. AA: OR= 0.89, 95% CI= 0.75-1.05; CC vs. AA+AC: OR= 1.20, 95% CI= 0.89-1.40). Significant heterogeneity between individual studies was evident in all five models. In conclusion, present meta-analysis results indicated that there is no significant association between MTHFR A1298C polymorphism and risk of lung cancer.
IE-Map: A novel in-vivo atlas template of the human inner ear
Authors: Ahmadi Seyed-Ahmad , Raiser Theresa , Rühl Ria Maxine , Flanagin Virginia L. , Eulenburg Peter zu
Published: November 2019

Brain atlases and templates are core tools in scientific research with increasing importance also in clinical applications. Advances in neuroimaging now allowed us to expand the atlas domain to the vestibular and auditory organ, the inner ear. In this study, we present IE-Map, an in-vivo template and atlas of all known substructures of the human labyrinth derived from multi-modal high-resolution magnetic resonance imaging data in a non-invasive manner (no contrast agent or radiation). We reconstructed a common template from 126 inner ears (63 normal subjects) and annotated it with 94 established landmarks and semi-automatic segmentations. Quantitative substructure analysis revealed a correlation of labyrinth parameters with total intracranial volume. No effects of gender or laterality were found. We provide the validated templates, atlas segmentations, surface meshes and landmark annotations as open-access material, to provide neuroscience researchers and clinicians in neurology, neurosurgery, and otorhinolaryngology with a widely applicable tool for computational neurootology.
Mutation prevalence tables for hereditary cancer derived from multi-gene panel testing
Authors: Hart Steven N. , Polley Eric C. , Yussuf Amal , Yadav Siddhartha , Goldgar David E. , Hu Chunling , LaDuca Holly , Smith Laura P. , Fujimoto June , Li Shuwei , Couch Fergus J. , Dolinsky Jill S.
Published: November 2019

Purpose

Multi-gene panel testing for cancer predisposition mutations is becoming routine in clinical care. However, the gene content of panels offered by testing laboratories vary significantly, and data on mutation detection rates by gene and by panel is limited, causing confusion among clinicians on which test would be the most appropriate to order. Moreover, screening guidelines are not described in sufficient granularity to explain how differences in family, personal history, age, and other factors would affect the prevalence of finding a mutation in similar populations. The tool herein quantifies prevalence of mutations in hereditary cancer genes based on personalized clinical and demographic characteristics.

Methods

Using results from approximately 150,000 multi-gene panel tests conducted at Ambry Genetics, we built an interactive prevalence tool to explore how differences in ethnicity, age of onset, and personal and family history of different cancers affect the prevalence of pathogenic mutations in 31 cancer predisposition genes, across various clinically available hereditary cancer gene panels.

Results

Over 13,000 mutation carriers were identified in this high-risk population. Most of the cases were Non-Hispanic White (74%, n=109,537), but also provide an appreciable dataset for those identifying as Black (n=10,875), Ashkenazi Jewish (n=10,464), Hispanic (n=10,028), and Asian (n=7,090). The most prevalent cancer types were breast (50%), ovarian (6.6%), and colorectal (4.7%), which is expected based on genetic testing guidelines and clinician referral for testing.

Conclusion

The Hereditary Cancer Multi-Gene Panel Prevalence Tool presented here can be used to provide insight into the prevalence of mutations on a per-gene and per-multigene panel basis, while conditioning on multiple custom phenotypic variables to include race and cancer type. The tool can be found at https://www.ambrygen.com/prevalence-tool.
The efficacy of DNA MMR enzyme immunohistochemistry as a screening test for hypermutated gliomas
Authors: McCord Matthew , Steffens Alicia , Javier Rodrigo , Kam Kwok-Ling , McCortney Kathleen , Horbinski Craig
Published: November 2019

A subset of gliomas has DNA repair defects that lead to hypermutated genomes. While such tumors are resistant to alkylating chemotherapies, they may also express more mutant neoantigens on their cell surfaces, and thus be more responsive to immunotherapies. A fast, inexpensive method of screening for hypermutated gliomas would therefore be of great clinical value. Since immunohistochemistry (IHC) for the DNA mismatch repair (MMR) proteins Msh2, Msh6, Mlh1, and Pms2 is already used to screen for hypermutated colorectal cancers, we sought to determine whether that panel might have similar utility in gliomas. MMR IHC was scored in 100 WHO grade I-IV gliomas with known tumor mutation burdens (TMB), while blinded to TMB data. Eight of 100 cases showed loss of one or more MMR proteins by IHC, and all 8 were hypermutated. Among the remaining 94 gliomas with intact MMR IHC, only one was hypermutated; that tumor had an inactivating mutation in another DNA repair gene, ATM. Overall accuracy, sensitivity, and specificity were 99%, 89%, and 100%, respectively. The strongest correlates with hypermutation were prior TMZ treatment, MGMT promoter methylation, and IDH1 mutation. Among MMR-deficient hypermutated gliomas, 50% contained both MMR-lost and MMR-retained tumor cells. Together, these data suggest that MMR IHC could be a viable front-line screening test for gliomas in which immunotherapy is being considered. They also suggest that not all cells in a hypermutated glioma may actually be MMR-deficient, a finding that might need to be considered when treating such tumors with immunotherapies.
Pre-season screening currently has no value for injury prediction: The development and internal validation of a multivariable prognostic model to predict indirect muscle injury risk in elite football (soccer) players
Authors: Hughes Tom , Riley Richard D. , Callaghan Michael J. , Sergeant Jamie C.
Published: November 2019

Background

In elite football (soccer), periodic health examination (PHE) could provide prognostic factors to predict injury risk.

Objective

To develop and internally validate a prognostic model to predict individual indirect (non-contact) muscle injury (IMI) risk during a season in elite footballers, only using PHE-derived candidate prognostic factors.

Methods

Routinely collected preseason PHE and injury data were used from 119 players over 5 seasons (1stJuly 2013 to 19thMay 2018). Ten candidate prognostic factors (12 parameters) were included in model development. Multiple imputation was used to handle missing values. The outcome was any time-loss, index indirect muscle injury (I-IMI) affecting the lower extremity. A full logistic regression model was fitted, and a parsimonious model developed using backward-selection to remove non-significant factors. Predictive performance was assessed through calibration, discrimination and decision-curve analysis, averaged across all imputed datasets. The model was internally validated using bootstrapping and adjusted for overfitting.

Results

During 317 participant-seasons, 138 I-IMIs were recorded. The parsimonious model included only age and frequency of previous IMIs; apparent calibration was perfect but discrimination was modest (C-index = 0.641, 95% confidence interval (CI): 0.580 to 0.703), with clinical utility evident between risk thresholds of 37-71%. After validation and overfitting adjustment, performance deteriorated (C-index = 0.580; calibration-in-the-large =-0.031, calibration slope =0.663).

Conclusion

The selected PHE data were insufficient prognostic factors from which to develop a useful model for predicting IMI risk in elite footballers. Further research should prioritise identifying novel prognostic factors to improve future risk prediction models in this field.

Trial registration number

NCT03782389

KEY POINTS

Factors measured through preseason screening generally have weak prognostic strength for future indirect muscle injuries and further research is needed to identify novel, robust prognostic factors.

Because of sample size restrictions, and until the evidence base improves, it is likely that any further attempts at creating a prognostic model at individual club level would also suffer from poor performance.

The value of using preseason screening data to make injury predictions or to select bespoke injury prevention strategies remains to be demonstrated, so screening should only be considered as useful for detection of salient pathology or for rehabilitation/ performance monitoring purposes at this time.
Digitising point of care HIV test results to accurately measure, and improve performance towards, the UNAIDS 90-90-90 targets
Authors: Jacob Nisha , Rice Brian , Kalk Emma , Heekes Alexa , Morgan Jennie , Hargreaves James , Boulle Andrew
Published: November 2019

Introduction

High rates of pre-treatment loss to care among persons diagnosed with HIV persist. Linkage to care can be improved through active digitally-based surveillance. Currently, record-keeping for HIV diagnoses in South Africa is paper-based. Aggregated testing data are reported routinely, and only discordant findings result in a specimen being tested at a laboratory and digitised.

Methods

The Western Cape Province in South Africa has a Provincial Health Data Centre (PHDC) where person-level routine data are consolidated in a single database, leveraging the existence of a unique patient identifier. To facilitate improved surveillance, a pre-carbonated point-of-care test (PoCT) form was piloted, where one copy was routed to the centralised laboratory and digitised for PHDC inclusion. We evaluated the utility of the intervention using cross-sectional and retrospective cohort analyses, as well as comparisons with reported aggregate data.

Results

From May 2017 to June 2018, 11337 digitised point-of-care HIV testing records were linked to the PHDC. Overall, 96% of records in the aggregate dataset were digitised, with 97% linked to the PHDC. Of those tested, 79% were female (median age 27 years). Linkage demonstrated that 51.3% of patients testing HIV-positive were retesting. Of those truly newly diagnosed, 81% were linked to HIV care and 25% were initiated on antiretroviral therapy immediately.

Conclusion

Digitisation of PoCT results is feasible and provides individuated HIV testing data to assist in linkage to care and in differentiating newly diagnosed patients from positive patients retesting. Actionable and accurate data can improve the measurement of performance towards the UNAIDS 90-90-90 targets.
EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease
Authors: Tait Luke , Tamagnini Francesco , Stothart George , Barvas Edoardo , Monaldini Chiara , Frusciante Roberto , Volpini Mirco , Guttmann Susanna , Coulthard Elizabeth , Brown Jon T , Kazanina Nina , Goodfellow Marc
Published: November 2019

Introduction

Electroencephalogram (EEG) is a potentially useful clinical tool for aiding diagnosis of Alzheimer’s disease (AD). We hypothesized we can increase the accuracy of EEG for aiding diagnosis of AD using microstates, which are epochs of quasi-stability at the millisecond scale.

Methods

EEG was collected from two independent cohorts of AD and control participants and a cohort of mild cognitive impairment (MCI) patients with four-year clinical follow-up. Microstates were analysed, including a novel measure of complexity.

Results

Microstate complexity significantly decreased in AD, and when combined with a spectral EEG measure, could classify AD with sensitivity and specificity >80%. These results were validated on an independent cohort and were also found to be generalizable to predict progression from MCI to AD. Additionally, microstates associated with the frontoparietal network were altered in AD.

Discussion

EEG has the potential to be a non-invasive functional biomarker that predicts progression from MCI to AD.
MeSHHeading2vec: A new method for representing MeSH headings as feature vectors based on graph embedding algorithm
Authors: Guo Zhen-Hao , You Zhu-Hong , Yi Hai-Cheng , Zheng Kai , Wang Yan-Bin
Published: November 2019

Motivation

Effectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify.

Results

In this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective.

Contact

zhuhongyou@ms.xjb.ac.cn
Local intracerebral Inhibition of IRE1 by MKC8866 sensitizes glioblastoma to irradiation/chemotherapy in vivo
Authors: Le Reste Pierre Jean , Pineau Raphael , Voutetakis Konstantinos , Samal Juhi , Jégou Gwénaële , Lhomond Stéphanie , Gorman Adrienne M. , Samali Afshin , Patterson John B , Zeng Qingping , Pandit Abhay , Aubry Marc , Soriano Nicolas , Etcheverry Amandine , Chatziioannou Aristotelis , Mosser Jean , Avril Tony , Chevet Eric
Published: November 2019

Glioblastoma multiforme (GBM) is the most severe primary brain cancer. Despite an aggressive treatment comprising surgical resection and radio/chemotherapy patient’s survival post diagnosis remains short. A limitation for success in finding novel improved therapeutic options for such dismal disease partly lies in the lack of a relevant animal model that accurately recapitulates patient disease and standard of care. In the present study, we have developed a novel immunocompetent GBM model that includes tumor surgery and a radio/chemotherapy regimen resembling the Stupp protocol and we have used this model to test the impact of the pharmacological inhibition of the endoplasmic reticulum (ER) stress sensor IRE1, on treatment efficacy.
Arbitration between insula and temporoparietal junction subserves framing-induced boosts in generosity during social discounting
Authors: Sellitto Manuela , Neufang Susanne , Schweda Adam , Weber Bernd , Kalenscher Tobias
Published: November 2019

Generosity toward others declines across the perceived social distance to them. Here, participants chose between selfish and costly generous options in two conditions: in the gain frame, a generous choice yielded a gain to the other; in the loss frame, it entailed preventing the loss of a previous endowment to the other. Social discounting was reduced in the loss compared to the gain frame, implying increased generosity toward strangers. Using neuroimaging tools, we found that while the temporoparietal junction (TPJ) and the ventromedial prefrontal cortex (VMPFC) subserved generosity in the gain frame, the insular cortex was selectively recruited during generous choices in the loss frame. We provide support for a network-model according to which TPJ and insula differentially promote generosity by modulating value signals in the VMPFC in a frame-dependent fashion. These results extend our understanding of the insula role in nudging prosocial behavior in humans.
Efficient toolkit implementing best practices for principal component analysis of population genetic data
Authors: Privé Florian , Luu Keurcien , Blum Michael G.B. , McGrath John J. , Vilhjálmsson Bjarni J.
Published: November 2019

Principal Component Analysis (PCA) of genetic data is routinely used to infer ancestry and control for population structure in various genetic analyses. However, conducting PCA analyses can be complicated and has several potential pitfalls. These pitfalls include (1) capturing Linkage Disequilibrium (LD) structure instead of population structure, (2) projected PCs that suffer from shrinkage bias, (3) detecting sample outliers, and (4) uneven population sizes. In this work, we explore these potential issues when using PCA, and present efficient solutions to these. Following applications to the UK Biobank and the 1000 Genomes project datasets, we make recommendations for best practices and provide efficient and user-friendly implementations of the proposed solutions in R packages bigsnpr and bigutilsr.

For example, we find that PC19 to PC40 in the UK Biobank capture complex LD structure rather than population structure. Using our automatic algorithm for removing long-range LD regions, we recover 16 PCs that capture population structure only. Therefore, we recommend using only 16-18 PCs from the UK Biobank to account for population structure confounding. We also show how to use PCA to restrict analyses to individuals of homogeneous ancestry. Finally, when projecting individual genotypes onto the PCA computed from the 1000 Genomes project data, we find a shrinkage bias that becomes large for PC5 and beyond. We then demonstrate how to obtain unbiased projections efficiently using bigsnpr.

Overall, we believe this work would be of interest for anyone using PCA in their analyses of genetic data, as well as for other omics data.
A cooperative network of molecular “hot spots” highlights the complexity of LH3 collagen glycosyltransferase activities
Authors: Chiapparino Antonella , De Giorgi Francesca , Scietti Luigi , Faravelli Silvia , Roscioli Tony , Forneris Federico
Published: November 2019

Hydroxylysine glycosylations are collagen-specific post-translational modifications essential for maturation and homeostasis of fibrillar as well as non-fibrillar collagen molecules. Lysyl hydroxylase 3 (LH3) is the only human enzyme capable of performing two chemically-distinct collagen glycosyltransferase reactions using the same catalytic site: inverting beta-1,O-galactosylation of hydroxylysines and retaining alpha-1,2-glycosylation of galactosyl hydroxylysines.

Here, we used structure-based mutagenesis to show that both glycosyltransferase activities are strongly dependent on a broad cooperative network of amino acid side chains which includes the first-shell environment of the glycosyltransferase catalytic site and shares features with both retaining and inverting enzymes. We identified critical “hot spots” leading to selective loss of inverting activity without affecting the retaining reaction. Finally, we present molecular structures of LH3 in complex with UDP-sugar analogs which provide the first structural templates for LH3 glycosyltransferase inhibitor development.

Collectively, our data provide a comprehensive overview of the complex network of shapes, charges and interactions that enable LH3 glycosyltransferase activities, expanding the molecular framework for the manipulation of glycosyltransferase functions in biomedical and biotechnological applications.
LMSM: a modular approach for identifying lncRNA related miRNA sponge modules in breast cancer
Authors: Zhang Junpeng , Xu Taosheng , Liu Lin , Zhang Wu , Zhao Chunwen , Li Sijing , Li Jiuyong , Rao Nini , Le Thuc Duy
Published: November 2019

Until now, existing methods for identifying lncRNA related miRNA sponge modules mainly rely on lncRNA related miRNA sponge interaction networks, which may not provide a full picture of miRNA sponging activities in biological conditions. Hence there is a strong need of new computational methods to identify lncRNA related miRNA sponge modules. In this work, we propose a framework, LMSM, to identify LncRNA related MiRNA Sponge Modules from heterogeneous data. To understand the miRNA sponging activities in biological conditions, LMSM uses gene expression data to evaluate the influence of the shared miRNAs on the clustered sponge lncRNAs and mRNAs. We have applied LMSM to the human breast cancer (BRCA) dataset from The Cancer Genome Atlas (TCGA). As a result, we have found that the majority of LMSM modules are significantly implicated in BRCA and most of them are BRCA subtype-specific. Most of the mediating miRNAs act as crosslinks across different LMSM modules, and all of LMSM modules are statistically significant. Multi-label classification analysis shows that the performance of LMSM modules is significantly higher than baseline’s performance, indicating the biological meanings of LMSM modules in classifying BRCA subtypes. The consistent results suggest that LMSM is robust in identifying lncRNA related miRNA sponge modules. Moreover, LMSM can be used to predict miRNA targets. Finally, LMSM outperforms a graph clustering-based strategy in identifying BRCA-related modules. Altogether, our study shows that LMSM is a promising method to investigate modular regulatory mechanism of sponge lncRNAs from heterogeneous data.

Author summary

Previous studies have revealed that long non-coding RNAs (lncRNAs), as microRNA (miRNA) sponges or competing endogenous RNAs (ceRNAs), can regulate the expression levels of messenger RNAs (mRNAs) by decreasing the amount of miRNAs interacting with mRNAs. In this work, we hypothesize that the “tug-of-war” between RNA transcripts for attracting miRNAs is across groups or modules. Based on the hypothesis, we propose a framework called LMSM, to identify LncRNA related MiRNA Sponge Modules. Based on the two miRNA sponge modular competition principles, significant sharing of miRNAs and high canonical correlation between the sponge lncRNAs and mRNAs, LMSM is also capable of predicting miRNA targets. LMSM not only extends the ceRNA hypothesis, but also provides a novel way to investigate the biological functions and modular mechanism of lncRNAs in breast cancer.
Investigating higher order interactions in single cell data with scHOT
Authors: Ghazanfar Shila , Lin Yingxin , Su Xianbin , Lin David M. , Patrick Ellis , Han Ze Guang , Marioni John C. , Yang Jean Yee Hwa
Published: November 2019

Single-cell RNA-sequencing has transformed our ability to examine cell fate choice. For example, in the context of development and differentiation, computational ordering of cells along ‘pseudotime’ enables the expression profiles of individual genes, including key transcription factors, to be examined at fine scale temporal resolution. However, while cell fate decisions are typically marked by profound changes in expression, many such changes are observed in genes downstream of the initial cell fate decision. By contrast, the genes directly involved in the cell fate decision process are likely to interact in subtle ways, potentially resulting in observed changes in patterns of correlation and variation rather than mean expression prior to cell fate commitment. Herein, we describe a novel approach, scHOT – single cell Higher Order Testing - which provides a flexible and statistically robust framework for identifying changes in higher order interactions among genes. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. We demonstrate the utility of scHOT by studying embryonic development of the liver, where we find coordinated changes in higher order interactions of programs related to differentiation and liver function. We also demonstrate its ability to find subtle changes in gene-gene correlation patterns across space using spatially-resolved expression data from the mouse olfactory bulb. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.
Assessing the shared variation among high-dimensional data matrices: a modified version of the Procrustean correlation coefficient
Authors: Coissac E. , Gonindard-Melodelima C.
Published: November 2019

Motivation

Molecular biology and ecology studies can produce high dimension data. Estimating correlations and shared variation between such data sets are an important step in disentangling the relationships between different elements of a biological system. Unfortunately, classical approaches are susceptible to producing falsely inferred correlations.

Results

Here we propose a corrected version of the Procrustean correlation coefficient that is robust to high dimensional data. This allows for a correct estimation of the shared variation between two data sets and the partial correlation coefficients between a set of matrix data.

Availability

The proposed corrected coefficients are implemented in the ProcMod R package available on CRAN. The git repository is hosted at https://git.metabarcoding.org/lecasofts/ProcMod

Contact

eric.coissac@metabarcoding.org
Estradiol promotes and progesterone reduces anxiety-like behavior produced by nicotine withdrawal in rats
Authors: Flores Rodolfo J. , Cruz Bryan , Uribe Kevin P. , Correa Victor L. , Arreguin Montserrat C. , Carcoba Luis M. , Mendez Ian A. , O’Dell Laura E.
Published: November 2019

The present study assessed sex differences and the role of ovarian hormones in the behavioral effects of nicotine withdrawal. Study 1 compared physical signs, anxiety-like behavior, and corticosterone levels in male, intact female, and ovariectomized (OVX) female rats during nicotine withdrawal. Estradiol (E2) and progesterone levels were also assessed in intact females that were tested during different phases of the 4-day estrous cycle. Study 2 assessed the role of ovarian hormones in withdrawal by comparing the same measures in OVX rats that received vehicle, E2, or E2+progesterone prior to testing. Briefly, rats received a sham surgery or an ovariectomy procedure. Fifteen days later, rats were prepared with a pump that delivered nicotine for 14 days. On the test day, rats received saline or the nicotinic receptor antagonist, mecamylamine to precipitate withdrawal. Physical signs and anxiety-like behavior were assessed on the elevated plus maze (EPM) and light-dark transfer (LDT) tests. During withdrawal, intact females displayed greater anxiety-like behavior and corticosterone levels as compared to male and OVX rats. Females tested in estrus (when E2 is relatively low) displayed less anxiety-like behavior and corticosterone versus all other phases. Anxiety-like behavior and corticosterone were positively correlated with E2 and negatively correlated with progesterone. Intact females displaying high E2/low progesterone displayed greater anxiety-like behavior and corticosterone as compared to females displaying low E2/high progesterone. Lastly, OVX-E2 rats displayed greater anxiety-like behavior than OVX-E2+progesterone rat. These data suggest that E2 promotes and progesterone reduces anxiety-like behavior produced by withdrawal.
Spiking Recurrent Networks as a Model to Probe Neuronal Timescales Specific to Working Memory
Authors: Kim Robert , Sejnowski Terrence J.
Published: November 2019

Cortical neurons process and integrate information on multiple timescales. In addition, these timescales or temporal receptive fields display functional and hierarchical organization. For instance, areas important for working memory (WM), such as prefrontal cortex, utilize neurons with stable temporal receptive fields and long timescales to support reliable representations of stimuli. Despite of the recent advances in experimental techniques, the underlying mechanisms for the emergence of neuronal timescales long enough to support WM are unclear and challenging to investigate experimentally. Here, we demonstrate that spiking recurrent neural networks (RNNs) designed to perform a WM task reproduce previously observed experimental findings and that these models could be utilized in the future to study how neuronal timescales specific to WM emerge.
A literature mining method to judge whether there are uncertainties in empirical-dependent antineoplastic drug distribution in specific clinical scenarios
Authors: Ji Xiaoyang , Feng Zhendong , Zhang Qiangzu , Zhang Zhonghai , Fan Yanhui , Na Renhua , Niu Gang
Published: November 2019

Cancer clinical practice guidelines recommend different treatment options for different cancer types and are mainly developed by clinicians. In theory, those recommendation schemes that are supported by scientific research should provide better efficacy for patients. However, in actual clinical practice: “Is the choice of a specific antineoplastic drug for a specific cancer supported by the results of molecular biology mechanisms or based on the subjective experience of the clinician?” Answering this question is of significant importance for guiding clinical practice, but there is currently no operational method to provide objective judgment in specific cases. This paper describes a literature mining method that collates information from specific antineoplastic drug-related literature to establish an antineoplastic drug-gene association matrix for global or specific cancer scenarios, and further establishes a standard model and scenario models. Based on the parameters of these models, we constructed a linear regression analysis method to evaluate whether the models in different scenarios deviated from a random distribution. Finally, we determined the possible efficacy of an antineoplastic drug in different cancer types, which was validated by the Genomics of Drug Sensitivity in Cancer (GDSC) database. Using our mining method, we tested 18 antineoplastic drugs in 16 cancer types. We found that cisplatin used in ovarian cancer was more efficacious and may benefit patients more than when used in breast cancer, which provides a new paradigm for rational knowledge-driven drug distribution patterns in clinical practice.
Transcription closed and open complex formation coordinate expression of genes with a shared promoter region
Authors: Häkkinen Antti , Oliveira Samuel M. D. , Neeli-Venkata Ramakanth , Ribeiro Andre S.
Published: November 2019

Many genes are spaced closely, allowing coordination without explicit control through shared regulatory elements and molecular interactions. We study the dynamics of a stochastic model of a gene-pair in a head-to-head configuration, sharing promoter elements, which accounts for the rate-limiting steps in transcription initiation. We find that only in specific regions of the parameter space of the rate-limiting steps is orderly co-expression exhibited, suggesting that successful cooperation between closely spaced genes requires the co-evolution of compatible rate-limiting step configuration. The model predictions are validated by in vivo single-cell, single-RNA measurements of the dynamics of pairs of genes sharing promoter elements. Our results suggest that, in E. coli, the kinetics of the rate-limiting steps in active transcription can play a central role in the dynamics of pairs of genes sharing promoter elements.
The Absence of Universally-Conserved Protein-coding Genes
Authors: Tan Change Laura
Published: November 2019

Public access to thousands of completely sequenced and annotated genomes provides a great opportunity to address the relationships of different organisms, at the molecular level and on a genome-wide scale. Via comparing the phylogenetic profiles of all protein-coding genes in 317 model species described in the OrthoInspector3.0 database, we found that approximately 29.8% of the total protein-coding genes were orphan genes (genes unique to a specific species) while < 0.01% were universal genes (genes with homologs in each of the 317 species analyzed). When weighted by potential birth event, the orphan genes comprised 82% of the total, while the universal genes accounted for less than 0.00008%. Strikingly, as the analyzed genomes increased, the sum total of universal and nearly-universal genes plateaued while that of orphan and nearly-orphan genes grew continuously. When the compared species increased to the inclusion of 3863 bacteria, 711 eukaryotes, and 179 archaea, not one of the universal genes remained. The results speak to a previously unappreciated degree of genetic biodiversity, which we propose to quantify using the birth-event-weighted gene count method.
Genome reconstruction of the non-culturable spinach downy mildew Peronospora effusa by metagenome filtering
Authors: Klein Joël , Neilen Manon , van Verk Marcel , Van den Ackerveken Guido , Dutilh Bas E.
Published: November 2019

Peronospora effusa (previously known as  P. farinosa f. sp. spinaciae, and here referred to as Pfs) is an obligate biotrophic oomycete that causes downy mildew on spinach (Spinacia oleracea). To combat this destructive disease resistant cultivars are continually bred. However, new Pfs races rapidly break the employed resistance genes. To get insight into the gene repertoire of Pfs and identify infection-related genes, the genome of the first reference race, Pfs1, was sequenced, assembled, and annotated. Due to the obligate biotrophic nature of this pathogen, material for DNA isolation can only be collected from infected spinach leaves that, however, also contain many other microorganisms. The obtained sequences are, therefore, considered a metagenome. To filter and obtain Pfs sequences we utilized the CAT tool to taxonomically annotate ORFs residing on long sequences of a genome pre-assembly. This study is the first to show that CAT filtering performs well on eukaryotic contigs. Based on the taxonomy, determined on multiple ORFs, contaminating long sequences and corresponding reads were removed. Filtered reads were re-assembled to provide a clean and improved Pfs genome sequence of 32.40 Mbp consisting of 8,635 scaffolds. Transcript sequencing of a range of infection time points aided the prediction of a total of 13,277 gene models, including 99 RXLR(-like) effector, and 14 putative Crinkler genes. Comparative analysis identified common features in the secretomes of different obligate biotrophic oomycetes, regardless of their phylogenetic distance. Their secretomes are generally smaller, compared to hemibiotrophic and necrotrophic oomycete species. We observe a reduction in proteins involved cell wall degradation, in Nep1-like proteins (NLPs), proteins with PAN/apple domains, and host translocated effectors. The genome of Pfs1 will be instrumental in studying downy mildew virulence and for understanding the molecular adaptations by which new isolates break spinach resistance.
Strong information-limiting correlations in early visual areas
Authors: Montijn Jorrit S , Liu Rex G , Aschner Amir , Kohn Adam , Latham Peter E , Pouget Alexandre
Published: November 2019

If the brain processes incoming data efficiently, information should degrade little between early and later neural processing stages, and so information in early stages should match behavioral performance. For instance, if there is enough information in a visual cortical area to determine the orientation of a grating to within 1 degree, and the code is simple enough to be read out by downstream circuits, then animals should be able to achieve that performance behaviourally. Despite over 30 years of research, it is still not known how efficient the brain is. For tasks involving a large number of neurons, the amount of information encoded by neural circuits is limited by differential correlations. Therefore, determining how much information is encoded requires quantifying the strength of differential correlations. Detecting them, however, is difficult. We report here a new method, which requires on the order of 100s of neurons and trials. This method relies on computing the alignment of the neural stimulus encoding direction, f′, with the eigenvectors of the noise covariance matrix, Σ. In the presence of strong differential correlations, f′ must be spanned by a small number of the eigenvectors with largest eigenvalues. Using simulations with a leaky-integrate-and-fire neuron model of the LGN-V1 circuit, we confirmed that this method can indeed detect differential correlations consistent with those that would limit orientation discrimination thresholds to 0.5-3 degrees. We applied this technique to V1 recordings in awake monkeys and found signatures of differential correlations, consistent with a discrimination threshold of 0.47-1.20 degrees, which is not far from typical discrimination thresholds (1-2 deg). These results suggest that, at least in macaque monkeys, V1 contains about as much information as is seen in behaviour, implying that downstream circuits are efficient at extracting the information available in V1.
Specificity in auxin responses is not explained by the promoter preferences of activator ARFs
Authors: Lanctot Amy , Taylor-Teeples Mallorie , Oki Erika A. , Nemhauser Jennifer L.
Published: November 2019

Auxin is essential for almost every developmental process within plants. How a single small molecule can lead to a plethora of downstream responses has puzzled researchers for decades. It has been hypothesized that one source for such diversity is distinct promoter-binding and activation preferences for different members of the AUXIN RESPONSE FACTOR (ARF) family of transcription factors. We systematically tested this hypothesis by engineering varied promoter sequences in a heterologous yeast system and quantifying transcriptional activation by ARFs from two species, Arabidopsis thaliana and Zea mays. By harnessing the user-defined and scalable nature of our synthetic system, we elucidated promoter design rules for optimal ARF function, discovered novel ARF-responsive promoters, and characterized the impact of ARF dimerization on their activation potential. We found no evidence for specificity in ARF-promoter interactions, suggesting that the diverse auxin responses observed in plants may be driven by factors outside the core auxin response machinery.
Encoding of social exploration by neural ensembles in the insular cortex
Authors: Miura Isamu , Sato Masaaki , Kunori Nobuo , Overton Eric T.N. , Nakai Junichi , Kawamata Takakazu , Nakai Nobuhiro , Takumi Toru
Published: November 2019

The insular cortex participates in diverse complex brain functions including sociality, yet little is known about their cellular bases. Using microendoscopic calcium imaging of the agranular insular cortex (AI) in mice interacting with freely-moving and restrained social targets, we identified two subsets of AI neurons –a larger fraction of Social-ON cells and a smaller fraction of Social-OFF cells– that change their activity in opposite directions during social exploration. Social-ON cells included those that represented social investigation independent of location and consisted of multiple subsets, each of which were preferentially active during exploration under particular behavioral state or with a particular target of physical contact. These results uncover a previously unknown function of AI neurons in encoding conjunctive information on social behavior and suggest that AI may act to monitor the ongoing status of social exploration while an animal interacts with unfamiliar conspecifics.