bluuebunny/crossref_metadata_2025 huggingface dataset:
SARS-CoV-2 infection in households with and without young children: Nationwide cohort study
Authors: Husby Anders , Corn Giulia , Krause Tyra Grove
Published: March 2021

Background

Infections with seasonally spreading human coronaviruses (HCoVs) are common among young children during winter months in the northern hemisphere, with immunological response lasting around a year. However, it is not clear whether recent household exposure to HCoVs reduces the risk of SARS-CoV-2 infection.

Methods

In a nationwide cohort study we followed all adults in Denmark aged 18 to 60 years from February 27 to November 15, 2020. Hazard ratios of SARS-CoV-2 infection by number of young children aged ten months to five years living in the household were estimated using Cox regression adjusted for adult age, gender, and other potential confounders. In sensitivity analyses we investigated the effect of age of children in the household, number of children living outside of the household, and number of other adult household-members.

Results

Among 449,915 adults in Denmark living in households with young children, 5,761 were tested positive for SARS-CoV-2, while among 2,629,821 adults without young children in their household, 33,788 were tested positive for SARS-CoV-2 (adjusted hazard ratio, 1.05; 95% confidence interval, 1.02 to 1.09). Sensitivity analyses of age of children in the household, number of children living outside of the household, and number of additional adult household members found increasing number of children, and especially increasing number of older children, to substantially increase the risk of SARS-CoV-2 infection.

Conclusions

Living in a household with young children was not associated with decreased risk of SARS-CoV-2 infection, thereby suggesting no strong preventive effect of recent exposure to HCoVs against SARS-CoV-2 infection.
Trajectories of Clinical and Laboratory Characteristics Associated with COVID-19 in Hemodialysis Patients by Survival
Authors: Chaudhuri Sheetal , Lasky Rachel , Jiao Yue , Larkin John , Monaghan Caitlin , Winter Anke , Neri Luca , Kotanko Peter , Hymes Jeffrey , Lee Sangho , Wang Yuedong , Kooman Jeroen P. , Maddux Franklin , Usvyat Len
Published: March 2021

Introduction

The clinical impact of COVID-19 has not been established in the dialysis population. We evaluated the trajectories of clinical and laboratory parameters in hemodialysis (HD) patients.

Methods

We used data from adult HD patients treated at an integrated kidney disease company who received a RT-PCR test to investigate suspicion of a SARS-CoV-2 infection between 01 May and 01 Sep 2020. Nonparametric smoothing splines were used to fit data for individual trajectories and estimate the mean change over time in patients testing positive or negative for SARS-CoV-2 and those who survived or died within 30 days of first suspicion or positive test date. For each clinical parameter of interest, the difference in average daily changes between COVID-19 positive versus negative group and COVID-19 survivor versus non-survivor group was estimated by fitting a linear mixed effects model based on measurements in the 14 days before (i.e., day-14 to day 0) day 0.

Results

There were 12,836 HD patients with a suspicion of COVID-19 who received RT-PCR testing (8,895 SARS-CoV-2 positive). We observed significantly different trends (p<0.05) in pre-HD systolic blood pressure (SBP), pre-HD pulse rate, body temperature, ferritin, lymphocytes, albumin, and interdialytic weight gain (IDWG) between COVID-19 positive and negative patient. For COVID-19 positive group, we observed significantly different clinical trends (p<0.05) in pre-HD pulse rate, lymphocytes, albumin and neutrophil-lymphocyte ratio (NLR) between survivors and non-survivors. We also observed that, in the group of survivors, most clinical parameters returned to pre-COVID-19 levels within 60-90 days.

Conclusion

We observed unique temporal trends in various clinical and laboratory parameters among HD patients who tested positive versus negative for SARS-CoV-2 infection and those who survived the infection versus those who died. These trends can help to define the physiological disturbances that characterize the onset and course of COVID-19 in HD patients
The Efficacy of Isoniazid Prophylaxis in Renal Transplant Recipients in a High TB Burden Country
Authors: Dodani Sunil , Nasim Asma , Aziz Tahir , Naqvi Anwar
Published: March 2021

Introduction

Renal transplant recipients are at high risk of tuberculosis (TB). We have started Isoniazid (INH) prophylaxis of 1 year duration in all renal transplant recipients from April 2009. Our aim is to assess the incidence of TB on INH prophylaxis and its tolerability.

Methods

This was a retrospective observational study. The files of renal transplant recipients from April 2009 to December 2011 were reviewed till June 2015. We noted the incidence of TB, INH tolerability and development of resistance. We compared the incidence of TB with the historical controls who never received the prophylaxis.

Results

A total of 910 patients were reviewed and followed for 4.8 years. INH prophylaxis was completed by 825 (91%) patients. A total of 46 patients (5%) developed active TB as compared to 15% in the historical controls. The median time of TB diagnosis from transplantation was 2.8 years. In the first-year post transplant, out of total TB cases, 52% occurred in the historical controls whereas 13% occurred in study cohort. Around 67% had TB > 2 years after transplant. Overall 1.43% had hepatotoxicity. There was a significant reduction in TB among those who completed prophylaxis to those who did not (p=0.02). Out of 14 cultures one isolate was INH resistant (7%).

Conclusion

INH prophylaxis is well tolerated. The incidence of TB has decreased during the first 2 years. However there was a surge in TB cases 1 year after stopping INH therapy. We should consider prolonging the duration of INH prophylaxis in high TB burden countries in renal transplant recipients.
Comparable seasonal pattern for COVID-19 and Flu-Like Illnesses
Authors: Hoogeveen Martijn J. , Hoogeveen Ellen K.
Published: March 2021

Background

During the first wave of COVID-19 it was hypothesized that COVID-19 is subject to multi-wave seasonality, similar to Influenza-Like Illnesses since time immemorial. One year into the pandemic, we aimed to test the seasonality hypothesis for COVID-19.

Methods

We calculated the average annual time-series for Influenza-Like Illnesses based on incidence data from 2016 till 2019 in the Netherlands, and compared these with two COVID-19 time-series during 2020/2021 for the Netherlands. We plotted the time-series on a standardized logarithmic infection scale. Finally, we calculated correlation coefficients and used univariate regression analysis to estimate the strength of the association between the time-series of COVID-19 and Influenza-Like Illnesses.

Results

The time-series for COVID-19 and Influenza-Like Illnesses were strongly and highly significantly correlated. The COVID-19 peaks were all during flu season, and lows were all in the opposing period. Finally, COVID-19 meets the multi-wave characteristics of earlier flu-like pandemics, namely a short first wave at the tail-end of a flu season, and a longer and more intense second wave during the subsequent flu season.

Conclusions

We conclude that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands. Further, the COVID-19 pandemic satisfies the criteria of earlier respiratory pandemics, namely a first wave that is short-lived at the tail-end of flu season, and a second wave that is longer and more severe.

This seems to imply that the same factors that are driving the seasonality of Influenza-Like Illnesses are causing COVID-19 seasonality as well, such as solar radiation (UV), temperature, relative humidity, and subsequently seasonal allergens and allergies.

HIGHLIGHTS

Time-series analysis shows that COVID-19 and historic of Influenza-Like illnesses have highly similar seasonal patterns in the Netherlands.

COVID-19 satisfies the criteria of earlier flu-like pandemics, namely a short cycle at the end of flu season, and a longer, more intense cycle during the subsequent flu season.

The implication is that the seasonal factors driving flu season, are also responsible for COVID-19 seasonality.

We developed and applied a new method to determine seasonality, encompassing comparative time-series analysis, a standardized logarithmic infection scale, and qualitative seasonality criteria.
Association of Streptococcus mutans harboring bona-fide collagen binding proteins and Candida albicans with early childhood caries recurrence
Authors: Garcia B.A. , Acosta N.C. , Tomar S.L. , Roesch L.F.W. , Lemos J.A. , Mugayar L.C.F. , Abranches J.
Published: March 2021

Early childhood caries (ECC) recurrence occurs in approximately 40% of treated cases within one year. The association of Streptococcus mutans and Candida albicans with the onset of ECC is well known. Also, S. mutans strains harboring collagen-binding proteins (Cbps) avidly bind to collagen-rich dentin and are linked to increased caries incidence. Here, we investigated the presence of Cbp+S. mutans and C. albicans in saliva and dental plaque of children with varying caries statuses, as well as the salivary microbiome of these children. In this cross-sectional study, 143 children who were caries-free, treated for ECC with no signs of recurrence after 6 months, or treated for ECC and experiencing recurrence within 6 months following treatment were enrolled. Co-infection with C. albicans and S. mutans, especially Cbp+S. mutans, was strongly associated with caries recurrence. Subjects of the recurrence group infected with Cbp+S. mutans showed a greater burden of C. albicans and of Mutans streptococci in dentin than those infected with Cbp−S. mutans. Microbiome analysis revealed that Streptococcus parasanguinis was overrepresented in the caries recurrence group. Our findings indicate that Cbp+S. mutans and C. albicans are intimately associated with caries recurrence, contributing to the establishment of recalcitrant biofilms.
Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation
Authors: Milardi Demetrio , Basile Gianpaolo Antonio , Faskowitz Joshua , Bertino Salvatore , Quartarone Angelo , Anastasi Giuseppe , Bramanti Alessia , Cacciola Alberto
Published: March 2021

The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson’s Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories.

We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. Higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. All the pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.
Day-night and seasonal variation of human gene expression across tissues
Authors: Wucher Valentin , Sodaei Reza , Amador Raziel , Irimia Manuel , Guigó Roderic
Published: March 2021

Circadian and circannual cycles trigger physiological changes whose reflection on human transcriptomes remains largely uncharted. We used the time and season of death of 932 individuals from GTEx to jointly investigate transcriptomic changes associated with those cycles across multiple tissues. Overall, most variation across tissues during day-night and among seasons was unique to each cycle. Although all tissues remodeled their transcriptomes, brain and gonadal tissues exhibited the highest seasonality, whereas those in the thoracic cavity showed stronger day-night regulation. Core clock genes displayed marked day-night differences across multiple tissues, which were largely conserved in baboon and mouse, but adapted to their nocturnal or diurnal habits. Seasonal variation of expression affected multiple pathways and it was enriched among genes associated with the immune response, consistent with the seasonality of viral infections. Furthermore, they unveiled cytoarchitectural changes in brain regions. Altogether, our results provide the first combined atlas of how transcriptomes from human tissues adapt to major cycling environmental conditions.
Detecting Selection in Low-Coverage High-Throughput Sequencing Data using Principal Component Analysis
Authors: Meisner Jonas , Albrechtsen Anders , Hanghøj Kristian
Published: March 2021

1

Identification of selection signatures between populations is often an important part of a population genetic study. Leveraging high-throughput DNA sequencing larger sample sizes of populations with similar ancestries has become increasingly common. This has led to the need of methods capable of identifying signals of selection in populations with a continuous cline of genetic differentiation. Individuals from continuous populations are inherently challenging to group into meaningful units which is why existing methods rely on principal components analysis for inference of the selection signals. These existing methods require called genotypes as input which is problematic for studies based on low-coverage sequencing data. Here, we present two selections statistics which we have implemented in thePCAngsdframework. These methods account for genotype uncertainty, opening for the opportunity to conduct selection scans in continuous populations from low and/or variable coverage sequencing data. To illustrate their use, we applied the methods to low-coverage sequencing data from human populations of East Asian and European ancestries and show that the implemented selection statistics can control the false positive rate and that they identify the same signatures of selection from low-coverage sequencing data as state-of-the-art software using high quality called genotypes. Moreover, we show thatPCAngsdoutperform selection statistics obtained from called genotypes from low-coverage sequencing data.
Using empirical datasets to quantify uncertainty in inferences of landscape genetic resistance due to variation of individual-based genetic distance metrics
Authors: Beninde Joscha , Frantz Alain C.
Published: March 2021

Estimates of gene flow are commonly based on inferences of landscape resistance in ecological and evolutionary research and they frequently inform decision-making processes in conservation management. It is therefore imperative that inferences of a landscape factors relevance and its resistance are robust across approaches and reflect real-world gene flow instead of methodological artefacts. Here, we tested the impact of 160 different individual-based pairwise genetic metrics on consistency of landscape genetic inferences.

We used three empirical datasets that adopted individual-based sampling schemes and varied in scale (35-25,000 km2) and total number of samples (184-790) and comprise the wild boar,Sus scrofa,the red fox,Vulpes vulpesand the common wall lizard,Podarcis muralis. We made use of a machine-learning algorithm implemented in ResistanceGA to optimally fit resistances of landscape factors to genetic distance metrics and ranked their importance. Employed for nine landscape factors this resulted in 4,320 unique combinations of dataset, landscape factor and genetic distance metric, which provides the basis for quantifying uncertainty in inferences of landscape resistance.

Our results demonstrate that there are clear differences in Akaike information criteria (AICc)-based model support and marginal R2-based model fit between different genetic distance metrics. Metrics based on between 1-10 axes of eigenvector-based multivariate analyses (Factorial correspondence analysis, FCA; Principal component analysis, PCA) outperformed more widely used metrics, including the proportion of shared alleles (DPS), with AICc and marginal R2values often an order of magnitude greater in the former. Across datasets, inferences of the directionality of a landscape factors influence on gene flow, e.g. facilitating or impeding it, changed across different genetic distance metrics. The directionality of the inferred resistance was largely consistent when considering metrics based on between 1-10 FCA/PCA axes.

Inferences of landscape genetic resistance need to be corroborated using calculations of multiple individual-based pairwise genetic distance metrics. Our results call for the adoption of eigenvector-based quantifications of pairwise genetic distances. Specifically, a preliminary step of analysis should be incorporated, which explores model ranks across genetic distance metrics derived from FCA and PCA, and, contrary to findings of a simulation study, we demonstrate that it suffices to quantify these distances spanning the first ten axes only.
Characterization of induction methods forDrosophilaseizure mutations
Authors: Mituzaite Jurga , Petersen Rasmus , Claridge-Chang Adam , Baines Richard A.
Published: March 2021

Epilepsy is one of the most common neurological disorders. Around one third of patients do not respond to current medications. This lack of treatment indicates a need for better understanding of the underlying mechanisms and, importantly, the identification of novel targets for drug manipulation. The fruitflyDrosophila melanogasterhas a fast reproduction time, powerful genetics, and facilitates large sample sizes, making it a strong model of seizure mechanisms. However, there has not yet been a systematic analysis of the wide range of behavioral and physiological phenotypes observed across major fly seizure genotypes. To understand this, we systematically measured seizure severity and secondary behavioral phenotypes at both the larval and adult stage. Comparison of several seizure-induction methods; specifically electrical, mechanical and heat-induction, show that larval electroshock is the most effective at inducing seizures across a wide range of seizure-prone mutants. Locomotion in adults and larvae was found to be non-predictive of seizure susceptibility. Recording activity in identified larval motor neurons revealed variations in action potential patterns, across different genotypes, but these patterns did not correlate with seizure susceptibility. To conclude, while there is wide variation in mechanical induction, heat induction, and secondary phenotypes, electroshock is the most consistent method of seizure induction across known major seizure genotypes inDrosophila.

Significance Statement

Epilepsy is a neurological disorder affecting 1 in 130 people globally, with a significant impact on patients, families, and society. Approximately one third of epileptics do not respond to currently available medication. Thus, better insights into underlying disease mechanisms and identification of new drugs are needed. Fruit flies (Drosophila melanogaster) are a powerful genetic model: a number of single gene mutant flies exhibit seizures, phenotypes that have been shown to respond to established antiepileptic drugs. We compare methods of seizure induction and their utility, to establish which induction method is the most consistent across a range of different seizure-inducing genetic backgrounds. Adopting a common method for seizure analysis in this model will, we predict, speed identification of novel anti-convulsive treatments.
Interpretable Drug Target Predictions using Self-Expressiveness
Authors: Galeano Diego , Noto Santiago , Jimenez Ruben , Paccanaro Alberto
Published: March 2021

The identification of missing drug targets is critical for the development of treatments and for the molecular elucidation of drug side effects. Drug targets have been predicted by exploiting molecular, biological or pharmacological features of drugs and protein targets. Yet, developing integrative and interpretable machine learning models for predicting drug targets remains a challenging task. We present Inception, an integrative and interpretable matrix completion model for predicting drug targets. Inception is a self-expressive model that learns two similarity matrices: one for drugs and another for protein targets. These learned similarity matrices are key for our models’ interpretability: they can explain how a predicted drug-target interaction can be explain in terms of a linear combination of chemical, biological and pharmacological similarities. We develop a novel objective function with efficient closed-form solution. To demonstrate the ability of Inception at recovering missing drug-target interactions (DTIs), we perform cross-validation experiments with stringent controls of data imbalance, chemical similarities between drugs and sequence similarities between targets. We also assess the performance of our model using a simulated prospective approach. Having trained our model with DTIs from a snapshot 2011 of the DrugBank database, we test whether we could predict DTIs from a 2020 snapshot of DrugBank. Inception outperforms two state-of-the-art drug target prediction models in all the scenarios. This suggests that Inception could be useful for predicting missing drug target interactions while providing interpretable predictions.
Comparison of cerebrospinal fluid biomarkers relevant to neurodegenerative diseases in healthy cynomolgus and rhesus macaque monkeys
Authors: Robertson Emma L. , Boehnke Susan E. , Lyra e Silva Natalia M. , Armitage-Brown Brittney , Winterborn Andrew , Cook D.J. , De Felice Fernanda G. , Munoz Douglas P.
Published: March 2021

Structured Abstract

INTRODUCTION

Non-human primates are important translational models of neurodegenerative disease. We characterized how species, sex, age, and site of sampling affected concentrations of key biomarkers of neurodegeneration.

METHODS

Amyloid-beta (Aβ40, Aβ42), tau (tTau, pTau), and neurofilament light (NFL) in CSF were measured in 82 laboratory-housed naïve cynomolgus and rhesus macaques of both sexes.

RESULTS

Aβ40, Aβ42, and NFL were significantly higher in rhesus compared with cynomolgus macaques. tTau and NFL were higher in males. pTau was not affected by species or sex. Site of acquisition only affected NFL, with NFL being higher in CSF acquired from lumbar compared with cisterna magna puncture.

DISCUSSION

Normative values for key neurodegeneration biomarkers were established for laboratory housed cynomolgus and rhesus macaque monkeys. Differences were observed as a function of species, sex and site of CSF acquisition that should be considered when employing primate models.

Research In Context

Systematic review: We reviewed reports characterizing CSF biomarkers of neurodegenerative diseases in non-human primates – an increasingly important model of disease - revealing that studies with laboratory housed macaque monkeys were of small sample size, with a paucity of data about how biomarkers varied as a function of species, sex, age, and site of acquisition.

Interpretation: To address this gap, we collected CSF from 82 naïve laboratory housed male and female macaques of two species and measured Aβ40, Aβ42, tTau, pTau, and NFL. In addition to providing normative statistics for concentrations of these biomarkers, we revealed various species and sex differences.

Future directions: Establishing normative values of biomarkers is an important step to the efficient development of cynomolgus and rhesus macaques as models of neurodegenerative disorders such as Alzheimer’s disease. Reference values reduce the need for large control groups by which to compare with disease model animals.
Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images
Authors: Pécot Thierry , Cuitiño Maria C. , Johnson Roger H. , Timmers Cynthia , Leone Gustavo
Published: March 2021

Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep learning-based approach that couples remarkably precise nuclear segmentation with quantitation of fluorescent labeling intensity within segmented nuclei, and then apply it to the analysis of cell cycle dependent protein concentration in mouse tissues using 2D fluorescent still images. First, several existing deep learning-based methods were evaluated to accurately segment nuclei using different imaging modalities with a small training dataset. Next, we developed a deep learning-based approach to identify and measure fluorescent labels within segmented nuclei, and created an ImageJ plugin to allow for efficient manual correction of nuclear segmentation and label identification. Lastly, using fluorescence intensity as a readout for protein concentration, a three-step global estimation method was applied to the characterization of the cell cycle dependent expression of E2F proteins in the developing mouse intestine.
Mako: a graph-based pattern growth approach to detect complex structural variants
Authors: Lin Jiadong , Yang Xiaofei , Kosters Walter , Xu Tun , Jia Yanyan , Wang Songbo , Zhu Qihui , Ryan Mallory , Guo Li , Zhang Chengsheng ,   The Human Genome Structural Variation Consortium, Lee Charles , Devine Scott E. , Eichler Evan E. , Ye Kai
Published: March 2021

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. We systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections and pattern growth enables CSV detection without predefined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSV on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13bp and 26bp, respectively. Moreover, Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segments swap and tandem dispersed duplication. Further analysis of these CSVs also revealed impact of sequence homology in the formation of CSVs. Mako is publicly available at https://github.com/jiadong324/Mako.
Imaging-based evaluation of pathogenicity by novelDNM2 variantsassociated with centronuclear myopathy
Authors: Fujise Kenshiro , Okubo Mariko , Abe Tadashi , Yamada Hiroshi , Takei Kohji , Nishino Ichizo , Takeda Tetsuya , Noguchi Satoru
Published: March 2021

Centronuclear myopathy (CNM) is characterized clinically by muscle weakness and pathologically by the presence of centralized nuclei and disarrangement of T-tubules in muscle fibers.DNM2which encodes a large GTPase dynamin 2 have been identified as a causative gene for CNM. Nevertheless, the identification ofDNM2variants may not always lead to the definitive diagnosis as their pathogenicity is often unknown.

In this study, by imaging T-tubule-like structures reconstitutedin cellulo, we demonstrated that aberrant membrane remodeling by mutant dynamin 2 is tightly associated with gain-of-function features ofDNM2variants. This simplein celluloassay provided quantitative data required for accurately evaluating pathogenicity of reported and novelDNM2variants identified from CNM patients in our cohort. Our approaches combining thein celluloassay with clinical information of the patients enabled to explain the course of a disease progression by pathogenesis of each variant inDNM2-associated CNM.
Copy number evolution in simple and complex tandem repeats across the C57BL/6 and C57BL/10 inbred mouse lines
Authors: Flynn Jullien M. , Brown Emily J. , Clark Andrew G.
Published: March 2021

Simple sequence tandem repeats are among the most rapidly evolving compartments of the genome. Some repeat expansions are associated with mammalian disease or meiotic segregation distortion, yet the rates of copy number change across generations are not well known. Here, we use 14 distinct sub-lineages of the C57BL/6 and C57BL/10 inbred mouse strains, which have been evolving independently over about 300 generations, to estimate the rates of copy number changes in genome-wide tandem repeats. Rates of change varied across simple repeats and across lines. Notably, CAG, whose expansions in coding regions are associated with many neurological and other genetic disorders, was highly stable in copy number, likely indicating purifying selection. Rates of change were generally positively correlated with copy number, but the direction and magnitude of changes varied across lines. Some mouse lines experienced consistent losses or gains across most genome-wide simple repeats, but this did not correlate with copy number changes in complex repeats. Rates of copy number change were similar between simple repeats and the much more abundant complex repeats once they were normalized by copy number. Finally, the Y-specific centromeric repeat had a 4-fold higher rate of change than the homologous centromeric repeat on other chromosomes. Structural differences in satellite complexity, or restriction to the Y chromosome and the elevated mutation rate of the male germline, may explain the higher rate of change. Overall, our work underscores the mutational fluidity of long tandem arrays of repeats, and the correlations and constraints between genome-wide tandem repeats which suggest that turnover is not a completely neutral process.
The dynamic interactive network of long non-coding RNAs and chromatin accessibility facilitates erythroid differentiation
Authors: Ren Yunxiao , Zhu Junwei , Han Yuanyuan , Li Pin , Qu Hongzhu , Zhang Zhaojun , Fang Xiangdong
Published: March 2021

Erythroid differentiation is a dynamic process regulated by multiple factors, while the interaction between long non-coding RNAs and chromatin accessibility and its influence on erythroid differentiation remains unclear. To elucidate this interaction, we employed hematopoietic stem cells, multipotent progenitor cells, common myeloid progenitor cells, megakaryocyte-erythroid progenitor cells, and erythroblasts from human cord blood as an erythroid differentiation model to explore the coordinated regulatory functions of lncRNAs and chromatin accessibility in erythropoiesis by integrating RNA-Seq and ATAC-Seq data. We revealed that the integrated network of chromatin accessibility and LncRNAs exhibits stage-specific changes throughout the erythroid differentiation process, and that the changes at the EB stage of maturation are dramatic. We identified a subset of stage-specific lncRNAs and transcription factors (TFs) that coordinate with chromatin accessibility during erythroid differentiation, in which lncRNAs are key regulators of terminal erythroid differentiation via a lncRNA-TF-gene network. LncRNAPCED1B-AS1was revealed to regulate terminal erythroid differentiation by coordinating GATA1 dynamically binding to the chromatin during erythroid differentiation.DANCR, another lncRNA that is highly expressed at the MEP stage, was verified to promote erythroid differentiation by compromising megakaryocyte differentiation and coordinating with chromatin accessibility and TFs, such as RUNX1. Overall, our results identified the interactive network of lncRNAs and chromatin accessibility in erythropoiesis and provide novel insights into erythroid differentiation and abundant resources for further study.

Key Points

LncRNAs regulate erythroid differentiation through coordinating with chromatin accessibility.

The integrative multi-omics analysis reveals stage-specific interaction network of LncRNAs and chromatin accessibility in erythropoiesis.
Selecting an appropriate learning management system in open and distance learning: a strategic approach
Authors: Kant Nikhil , Prasad K.D. , Anjali Kumari
Published: March 2021

Purpose

This paper aims to derive criteria for a strategic selection of learning management system (LMS) after making an analysis of the feedback data collected from learners and academic counselors in open and distance learning (ODL) to evaluate their perceptions. This analysis hints at the need to implement a learning management system (LMS) in ODL. Selecting an appropriate LMS can prove to be a strategic approach for ODL in achieving self-reliance and competitiveness.

Design/methodology/approach

Research design includes qualitative design intended to discuss the features, advantages and attributes of different popular LMSs and compare them. In addition, the quantitative design (a questionnaire-based online feedback) to analyze the perceptions of the learners and academic counselors in order to know their e-learning needs has also been used. Results have been exhibited in tabular/graphical formats for easy comprehension and enhanced understanding.

Findings

Findings of the study suggest that availability of plethora of LMSs in the market, which also include open source (OS) LMSs, makes the decision- making as regards selection of an appropriate LMS strategically crucial requiring adequate consideration of every aspect such as cost, quality, usage, capacity, budget and most importantly priorities and objectives.

Research limitations/implications

This study will help educational administrators and decision-makers in ODL for building a quality civilized life and empowered society by removing the constraints related to financial problems, disabilities, time, geographical conditions and many others in bringing education to the doorstep of every willing learner. The technical details of LMS, however, were intentionally kept simplified to achieve the objective and provide easy comprehensibility for the reader with little technical background, which might be a limitation of this study.

Originality/value

This study highlights that ODL has tasted success with optimum exploitation of different technological advancements in its transformational expedition from conventional learning to innovative e-learning and to the newest adaptive e-learning system. The huge potential of LMS, in providing learners and educators in ODL with an effective web-based learning system incorporating almost all the academic activities, has attracted organizations for using it not only for imparting education to learners but also for providing appropriate trainings to their human resources.
An evaluation of faculty development programme on the design and development of self-learning materials for open distance learning
Authors: Asgar Ali , Satyanarayana Rampelli
Published: March 2021

Purpose

This paper seeks to ascertain the effectiveness of a two-week-long faculty development programme (FDP), organized by Indira Gandhi National Open University (IGNOU), for teachers of the open and distance learning (ODL) system, with the aim of upgrading their knowledge and skills for developing print self-learning materials (SLMs). The specific aim of this study is to ascertain whether the objectives of the FDP have been achieved, to examine the effectiveness of the training programme and to suggest measures for improvement in future FDPs regarding the design and development of print SLMs.

Design/methodology/approach

The study was conducted using a descriptive survey research method, through semi-structured questionnaires and adopted purposive sampling. The first survey was conducted immediately after the completion of the programme, in order to collect feedback from the trainees, while the second survey was conducted after six months of the FDP, using the follow-up approach, so that more reliable and authentic results could be obtained.

Findings

The outcomes of the study revealed that the training had been effective in imparting appropriate knowledge and skills to the trainees, with respect to designing print SLMs. However, certain gaps were also identified and have been reported in this paper. Key suggestions have been made to address the shortcomings and improve forthcoming FDPs.

Research limitations/implications

The present research focused on a specific training programme regarding the design and development of SLMs. Therefore, only the teachers and academics who participated in this specialized training activity were considered for the collection of feedback.

Practical implications

The recommendations of this work may be useful for the trainers, FDP coordinators, training institutions and ODL policymakers for planning and designing effective staff development activities for teachers and academics working in ODL institutions. These would be especially useful in the design of FDPs, aimed at orienting teachers who are involved in curriculum planning, design and development of learning resources.

Originality/value

This study is an original research based on the empirical primary data obtained by the researchers. As the largest open university in the world, IGNOU has been playing a key role in staff development for and in ODL in developing countries. This evaluative study of a specialized FDP in the area of SLM design and development is a significant work that may be valuable for planning the staff development strategies and building a training evaluation mechanism.
The economic consequences of Covid in Spain and how to deal with them
Authors: de la Fuente Angel
Published: March 2021

Purpose

This paper aims to review the economic impact of Covid in Spain and propose policies to deal with them.

Design/methodology/approach

Not relevant.

Findings

The pandemic is having a very severe effect, which varies across sectors and regions. Given the severity of the problem, a comprehensive policy strategy is needed. Specific proposals about such a strategy are made, distinguishing between the short and the long run.

Originality/value

It provides a discussion about the main measures that have been taken to mitigate the economic consequences of Covid in Spain and about what else should be done.
Measuring the gender pay gap: the complexity of HR metrics
Authors: Coron Clotilde
Published: March 2021

Purpose

The literature on HR metrics does not address the political issues that surround the definition and interpretation of these metrics. However, the need for agreement about HR metrics between different stakeholders is underlined by the framework of the sociology of quantification. This research aims to complement the literature on HR metrics by studying the process of defining and interpreting appropriate HR metrics, focusing on the example of the gender pay gap.

Design/methodology/approach

A case study with interviews and participant observation is conducted on a French company.

Findings

The results show that HR metrics are essential to prove the existence of inequalities. However, there are disagreements between management, unions and gender equality referents concerning appropriate HR metrics and their use.

Originality/value

Contrary to the literature on the subject, which remains predominantly positivist and normative, this article sheds light on the political issues surrounding the definition and use of HR metrics and shows the importance of involving a range of actors (managers, unions and employees) in the entire process.
Interpersonal conflict and counterproductive work behavior: the moderating roles of emotional intelligence and gender
Authors: Kundi Yasir Mansoor , Badar Kamal
Published: March 2021

Purpose

This paper aims to examine how interpersonal conflict at work might enhance employees’ propensity to engage in counterproductive work behavior (CWB), as well as how this relationship might be attenuated by emotional intelligence. It also considers how the attenuating role of emotional intelligence might depend on employees’ gender.

Design/methodology/approach

Survey data were collected from 193 employees working in different organizations in Pakistan.

Findings

Interpersonal conflict relates positively to CWB, but this relationship is weaker at higher levels of emotional intelligence. The negative buffering role of emotional intelligence is particularly strong among women as compared to men.

Practical implications

Given that individuals high in emotional intelligence are better at regulating their negative emotions, emotional intelligence training may be a powerful tool for reducing the hostility elicited among organizational members in response to interpersonal conflict and, consequently, their engagement in CWB.

Originality/value

This study uncovered the emotional mechanism that underlies the interpersonal conflict–CWB relationship by gender and makes suggestions to managers on minimizing the harmful effects of interpersonal conflict.
An analysis of the distribution and price determinants of Airbnb rentals in Malta
Authors: Fearne Rafael
Published: March 2021

Purpose

The purpose of this paper is twofold: to explore the distribution and pricing characteristics of Airbnb listings in Malta as at May 2019; and to develop a pricing model to determine the factors which have a statistically significant impact on price per night of listings.

Design/methodology/approach

A descriptive analysis of location and pricing of listings was undertaken via heat mapping techniques. A cross-sectional ordinary least squares (OLS) regression was run to determine the statistically significant variables.

Findings

Listings tend to cluster around not only in traditional tourist towns but also in rural areas which opens up new opportunities for tourist lodging. The Southern Harbour region was found to be the most expensive with the Gozo and Comino region being the least expensive. The coefficients of the pricing regression model were in line with a priori expectations.

Research limitations/implications

The study is based on a cross-sectional data set and thus fails to account for seasonal changes in prices. Likewise, the use of an OLS regression without incorporating quantile regression methods or spatial autocorrelation econometric techniques is another limitation of this study.

Originality/value

The paper is one of the few related to sharing economy rental platforms, particularly in Malta. It is also the first study in Malta to develop a comprehensive pricing model to determine what affects a listing’s price per night and the extent to which certain factors do so.
Performance evaluation: a comparative study between public and private sectors
Authors: Ensslin Sandra Rolim , Welter Larissa Marx , Pedersini Daiana Rafaela
Published: March 2021

Purpose

This study analysed international publications related to the performance evaluation (PE) theme to compare the public and private sectors with a focus on the metrics and a reflection on the consideration of each sector's characteristics.

Design/methodology/approach

In total, two bibliographic portfolios (BPs) were selected with the aid of the Knowledge Development Process-Constructivist (ProKnow-C) instrument, and the literature was systematically and critically reviewed to construct a theme literature map; the metrics analysed the performance evaluation systems (PESs) used in the studies and identified each sector's characteristics and PES behaviour based on these characteristics.

Findings

The two sectors stand out because of the low incidence of articles with cardinal scales, which enable the measurement and identification of the consequences of performance that are below or above the target. The behaviour of the sector characteristics was unusual, especially regarding the user and the organisational structure; it was found that the presence or absence of critical factors, such as communication, may prove to be a differential of success or failure. An absence of the organisation's particularities when designing and using a PES was noted.

Originality/value

The contributions relate to (1) identification of the public and private sector characteristics based on the selected literature, which helps in understanding the critical success and failure factors of an organisation's PES, especially with regard to metrics adequacy for each context; and (2) verification of the paths taken by the literature in both sectors.
The meaning of work for people with severe mental illness: a systematic review
Authors: Axiotidou Maria , Papakonstantinou Doxa
Published: March 2021

Purpose

Mental illness is associated with high unemployment rates, limited working opportunities, work-related discrimination, stigma and prejudices. For people with severe mental illness, the work reality is even more burdensome. This paper aims to explore in-depth and presents research results in the past decade on the meaning of work for people with severe mental illness.

Design/methodology/approach

The authors conducted a systematic literature search in Medline, Science Direct, PsycINFO databases between 2000 and 2019. The review concluded in 13 studies.

Findings

This research showed actual results regarding the meaning of work for individuals with severe mental illness from a medical, social, psychological and financial perspective. Work is of great importance for people with severe mental illness, influencing their lives on many levels.

Practical implications

The present research results can contribute to the information and further awareness of experts in mental health and vocational rehabilitation services. This review lightens the meaning of work and challenges the state's priorities in creating active and not marginalised citizens.

Originality/value

This review is original and adds to the existing knowledge that employment may benefit people with severe mental illness, especially the youngest adults, despite their labor market obstacles. It is for communities' benefit, employers, but mostly for people with severe mental illness themselves, to work.