bluuebunny/crossref_metadata_2025 huggingface dataset:
REACT-1 round 8 interim report: SARS-CoV-2 prevalence during the initial stages of the third national lockdown in England
Authors: Riley Steven , Wang Haowei , Eales Oliver , Walters Caroline E. , Ainslie Kylie E. C. , Atchison Christina , Fronterre Claudio , Diggle Peter J. , Ashby Deborah , Donnelly Christl A. , Cooke Graham , Barclay Wendy , Ward Helen , Darzi Ara , Elliott Paul
Published: January 2021

Background

High prevalence of SARS-CoV-2 virus in many northern hemisphere populations is causing extreme pressure on healthcare services and leading to high numbers of fatalities. Even though safe and effective vaccines are being deployed in many populations, the majority of those most at-risk of severe COVID-19 will not be protected until late spring, even in countries already at a more advanced stage of vaccine deployment.

Methods

The REal-time Assessment of Community Transmission study-1 (REACT-1) obtains throat and nose swabs from between 120,000 and 180,000 people in the community in England at approximately monthly intervals. Round 8a of REACT-1 mainly covers a period from 6th January 2021 to 15th January 2021. Swabs are tested for SARS-CoV-2 virus and patterns of swab-positivity are described over time, space and with respect to individual characteristics. We compare swab-positivity prevalence from REACT-1 with mobility data based on the GPS locations of individuals using the Facebook mobile phone app. We also compare results from round 8a with those from round 7 in which swabs were collected from 13th November to 24th November (round 7a) and 25th November to 3rd December 2020 (round 7b).

Results

In round 8a, we found 1,962 positives from 142,909 swabs giving a weighted prevalence of 1.58% (95% CI, 1.49%, 1.68%). Using a constant growth model, we found no strong evidence for either growth or decay averaged across the period; rather, based on data from a limited number of days, prevalence may have started to rise at the end of round 8a. Facebook mobility data showed a marked decrease in activity at the end of December 2020, followed by a rise at the start of the working year in January 2021. Between round 7b and round 8a, prevalence increased in all adult age groups, more than doubling to 0.94% (0.83%, 1.07%) in those aged 65 and over. Large household size, living in a deprived neighbourhood, and Black and Asian ethnicity were all associated with increased prevalence. Both healthcare and care home workers, and other key workers, had increased odds of swab-positivity compared to other workers.

Conclusion

During the initial 10 days of the third COVID-19 lockdown in England in January 2021, prevalence of SARS-CoV-2 was very high with no evidence of decline. Until prevalence in the community is reduced substantially, health services will remain under extreme pressure and the cumulative number of lives lost during this pandemic will continue to increase rapidly.
Correlates of Sleep and Arousal via Matrix Methods
Authors: Sorooshyari Siamak K. , Lecea Luis de
Published: January 2021

Conventional computational modeling of sleep and arousal are primarily brain-centric in restricting attention to data from the nervous system. While such a view is warranted, the importance of considering the coupling of peripheral systems in the causes and effects of sleep are being increasingly recognized. An analysis is presented that has the capability to incorporate neural recordings of different modalities as well as data from the metabolic and immune systems. We formulate a matrix-based approach for inference of the arousal state based on the activity level of cell types that will comprise the matrix components. While the presented computations are intended to predict sleep/arousal, it is anticipated that a scrutiny of the structure of the matrices will provide insight into the dynamics of the constituent systems. A model is also proposed to consider the interaction of the signals recorded across the neural, metabolic, and immune systems in leading to the arousal state.
Selection maintains protein interactome resilience in the long-term evolution experiment withEscherichia coli
Authors: Maddamsetti Rohan
Published: January 2021

Most cellular functions are carried out by a dynamic network of interacting proteins. An open question is whether the network properties of protein interactomes represent phenotypes under natural selection. One proposal is that protein interactomes have evolved to be resilient, such that they tend to maintain connectivity when proteins are removed from the network. This hypothesis predicts that interactome resilience should be maintained by natural selection during long-term experimental evolution. I tested this prediction by modeling the evolution of protein-protein interaction (PPI) networks in Lenski’s long-term evolution experiment withEscherichia coli(LTEE). In this test, I removed proteins affected by nonsense, insertion, deletion, and transposon mutations in evolved LTEE strains, and measured the resilience of the resulting networks. I compared the rate of change of network resilience in each LTEE population to the rate of change of network resilience for corresponding randomized networks. The evolved PPI networks are significantly more resilient than networks in which random proteins have been deleted.

Moreover, the evolved networks are generally more resilient than networks in which the random deletion of proteins was restricted to those disrupted in LTEE. These results suggest that evolution in the LTEE has favored PPI networks that are, on average, more resilient than expected from the genetic variation across the evolved strains. My findings therefore support the hypothesis that selection maintains protein interactome resilience over evolutionary time.

Significance Statement

Understanding how protein-protein interaction (PPI) networks evolve is a central goal of evolutionary systems biology. One property that has been hypothesized to be important for PPI network evolution is resilience, which means that networks tend to maintain connectivity even after many nodes (proteins in this case) have been removed. This hypothesis predicts that PPI network resilience should be maintained during long-term experimental evolution. Consistent with this prediction, I found that the PPI networks that evolved over 50,000 generations of Lenski’s long-term evolution experiment withE. coliare more resilient than expected by chance.
Freddie: Annotation-independent Detection and Discovery of Transcriptomic Alternative Splicing Isoforms
Authors: Orabi Baraa , McConeghy Brian , Chauve Cedric , Hach Faraz
Published: January 2021

Alternative splicing (AS) is an important mechanism in the development of many cancers, as novel or aberrant AS patterns play an important role as an independent onco-driver. In addition, cancer-specific AS is potentially an effective target of personalized cancer therapeutics. However, detecting AS events remains a challenging task, especially if these AS events are not pre-annotated. This is exacerbated by the fact that existing transcriptome annotation databases are far from being comprehensive, especially with regard to cancer-specific AS. Additionally, traditional sequencing technologies are severely limited by the short length of the generated reads, that rarely spans more than a single splice junction site. Given these challenges, transcriptomic long-read (LR) sequencing presents a promising potential for the detection and discovery of AS.

We present Freddie, a computational annotation-independent isoform discovery and detection tool. Freddie takes as input transcriptomic LR sequencing of a sample and computes a set of isoforms for the given sample. Freddie takes as input the genomic alignment of the transcriptomic LRs generated by a splice aligner. It then partitions the reads to sets that can be processed independently and in parallel. For each partition, Freddie segments the genomic alignment of the reads into canonical exon segments. The goal of this segmentation is to be able to represent any potential isoform as a subset of these canonical exons. This segmentation is formulated as an optimization problem and is solved with a Dynamic Programming algorithm. Then, Freddie reconstructs the isoforms by jointly clustering and error-correcting the reads using the canonical segmentation as a succinct representation. The clustering and error-correcting step is formulated as an optimization problem – the Minimum Error Clustering into Isoforms (MErCi) problem – and is solved using Integer Linear Programming (ILP).

We compare the performance of Freddie on simulated datasets with other isoform detection tools with varying dependence on annotation databases. We show that Freddie outperforms the other tools in its recall, including those given the complete ground truth annotation. In terms of false positive rate, Freddie performs comparably to the other tools. We also run Freddie on a transcriptomic LR dataset generated in-house from a prostate cancer cell line. Freddie detects a potentially novel Androgen Receptor isoform that includes novel intron retention. We cross-validate this novel intron retention using orthogonal publicly available short-read RNA-seq datasets.

Availability

Freddie is open source and available athttps://bitbucket.org/baraaorabi/freddie
Uncovering the Gene Regulatory Networks Underlying Macrophage Polarization Through Comparative Analysis of Bulk and Single-Cell Data
Authors: Carvalho Klebea , Rebboah Elisabeth , Jansen Camden , Williams Katherine , Dowey Andrew , McGill Cassandra , Mortazavi Ali
Published: January 2021

Gene regulatory networks (GRNs) provide a powerful framework for studying cellular differentiation. However, it is less clear how GRNs encode cellular responses to everyday microenvironmental cues. Macrophages can be polarized and potentially repolarized based on environmental signaling. In order to identify the GRNs that drive macrophage polarization and the heterogeneous single-cell subpopulations that are present in the process, we used a high-resolution time course of bulk and single-cell RNA-seq and ATAC-seq assays of HL-60-derived macrophages polarized towards M1 or M2 over 24 hours. We identified transient M1 and M2 markers, including the main transcription factors that underlie polarization, and subpopulations of naive, transitional, and terminally polarized macrophages. We built bulk and single-cell polarization GRNs to compare the recovered interactions and found that each technology recovered only a subset of known interactions. Our data provide a resource to study the GRN of cellular maturation in response to microenvironmental stimuli in a variety of contexts in homeostasis and disease.
RNAStructViz: Graphical base pairing analysis
Authors: Schmidt Maxie Dion , Kirkpatrick Anna , Heitsch Christine
Published: January 2021

We present a new graphical tool for RNA secondary structure analysis. The central feature is the ability to visually compare/contrast up to three base pairing configurations for a given sequence in a compact, standardized circular arc diagram layout. This is complemented by a built-in CT-style file viewer and radial layout substructure viewer which are directly linked to the arc diagram window via the zoom selection tool. Additional functionality includes the computation of some numerical information, and the ability to export images and data for later use. This tool should be of use to researchers seeking to better understand similarities and differences between structural alternatives for an RNA sequence.

Availability and implementation

https://github.com/gtDMMB/RNAStructViz/wiki

Author contacts

mschmidt34@gatech.edu,akirkpatrick3@gatech.edu, andheitsch@math.gatech.edu
Large-scale calcium imaging with a head-mounted axial scanning 3D fluorescence microscope
Authors: Hayashi Yuichiro , Kobayakawa Ko , Kobayakawa Reiko
Published: January 2021

Miniaturized fluorescence microscopes are becoming more important for deciphering the neural codes underlying various brain functions. With gradient index (GRIN) lenses, these devices enable recording neuronal activity in deep brain structures. However, to minimize any damage to brain tissues and local circuits, the diameter of the GRIN lens should be 0.5–1 mm, resulting in a small field of view. Volumetric imaging capability might increase the number of neurons imaged through the lenses considering the three-dimensional (3D) structure of neural circuits in the brain. To observe 3D calcium dynamics, we developed a miniaturized microscope with an electrically tunable lens and a novel CNMF-based neural signal extraction algorithm for wide-field 3D imaging data. By combining the hardware and software, approximately 1000 neurons were imaged from the cortices of freely behaving mice. Compared with the state-of-the-art 2D imaging technique, the proposed 3D method imaged 1.7–2.6 times more cells with a higher separation of cellular signals.
New insights on folliculogenesis and follicular placentation in marine viviparous fish black rockfish (Sebastes schlegelii)
Authors: Xu Xiaojie , Liu Qinghua , Wang Xueying , Qi Xin , Zhou Li , Liu Haoming , Li Jun
Published: January 2021

In viviparous fish, a considerable degree of variation in placental structures have been described. However, no distinct structures are reported in Scorpaenidae. In this study, we demonstrate a new type of folliculogenesis and follicular placentation inSebastes schlegelii. Before copulation, the germinal epithelium gradually surrounds the oocytes and develops to individually follicles with a stalk-like structure hanging on the ovigerous lamella, which ensures each follicle have access to spermatozoa after copulation. From stage V to early gestation, thecyp17-Ihighly expressed accompanied bycyp19a1asignals disappearance, and 11-ketotestosterone level keeps rising and peaks at blastula stage, while 17β-estradiol declines to the bottom. Meanwhile, the theca cells rapidly proliferate and invade outwards forming a highly hypertrophied and folded microvillous placenta. This unbalance of hormone might be an important factor driving the theca cells proliferation and invasion. Additionally, some conserved genes related to mammalian placentation are significantly high expression in follicular placenta suggesting the high convergence in vertebrate placenta evolution.
PrismExp: Predicting Human Gene Function by Partitioning Massive RNA-seq Co-expression Data
Authors: Lachmann Alexander , Rizzo Kaeli , Bartal Alon , Jeon Minji , Clarke Daniel J. B. , Ma’ayan Avi
Published: January 2021

Gene co-expression correlations from mRNA-sequencing (RNA-seq) can be used to predict gene function based on the covariance structure that exists within such data. In the past, we showed that RNA-seq co-expression data is highly predictive of gene function and protein-protein interactions. We demonstrated that the performance of such predictions is dependent on the source of the gene expression data. Furthermore, since genes function in different cellular contexts, predictions derived from tissue-specific gene co-expression data outperform predictions derived from cross-tissue gene co-expression data. However, the identification of the optimal tissue type to maximize gene function predictions for all mammalian genes is not trivial. Here we introduce and validate an approach we term Partitioning RNA-seq data Into Segments for Massive co-EXpression-based gene function Predictions (PrismExp), for improved gene function prediction based on RNA-seq co-expression data. With coexpression data from ARCHS4, we apply PrismExp to predict a wide variety of gene functions, including pathway membership, phenotypic associations, and protein-protein interactions. PrismExp outperforms the cross-tissue co-expression correlation matrix approach on all tested domains. Hence, PrismExp can enhance machine learning methods that utilize RNA-seq coexpression correlations to impute knowledge about understudied genes and proteins.
Improving Fabric Face Masks: Impact of Design Features on the Protection Offered by Fabric Face Masks
Authors: O’Kelly Eugenia , Arora Anmol , Pirog Sophia , Ward James , Clarkson P John
Published: January 2021

Objective

With much of the public around the world depending on fabric face masks to protect themselves and others, it is essential to understand how the protective ability of fabric masks can be enhanced. This study evaluated the protection offered by eighteen fabric masks designs. In addition, it assessed the benefit of including three design features: insert filters, surgical mask underlayers, and nose wires.

Methods

Quantitative fit tests were conducted on different masks and with some additional design features. An array of fabric masks were tested on a single participant to account for variability in face shapes. The effects of insert filters, surgical mask underlayers and nose wires were also assessed.

Results

As expected, the fabric masks offered low degrees of protection; however, alterations in design showed significant increase in their protective ability. The most effective designs were multi-layered masks that fit tightly to the face and lacked dead space between the user and mask. Also, low air-resistance insert filters and surgical mask underlays provided the greatest increase in protection.

Conclusions

Our findings indicate substantial heterogeneity in the protection offered by various fabric face masks. We also note some design features which may enhance the protection these masks offer.
Longitudinal trends and risk factors for depressed mood among Canadian adults during the first wave of COVID-19
Authors: Betini Gustavo S. , Hirdes John P. , Adekpedjou Rhéda , Perlman Christopher M. , Huculak Nathan , Hébert Paul
Published: January 2021

Abstract

Background

The COVID-19 pandemic has raised serious concerns about the mental health impact of people directed and indirectly affected by the virus. Because this is a rapidly evolving situation, our goal was to explore potential risk factors and trends in feelings of anxiety and depression among the general population in Canada over the first five months of the pandemic.

Methods

We completed on-line surveys of 3,127 unique individuals representative of the Canadian general population at 4 discreet periods every 6 weeks from April 15thto July 28th2020. We assessed feelings of anxiety, depression and loss of interest with the interRAI self-reported mood scale using a multivariable generalized estimating equation model to examine factors associated with having a 5+ score on the scale (indicating potentially depressed mood). We also investigated potential longitudinal trends to examine temporal changes in mood scores.

Results

More than 30% of participants felt highly anxious, depressed, and disinterested in everyday activities in the first survey (April), but this number decreased to about 20% over 4 months. Feeling lonely, younger age, feeling overwhelmed by one’s health needs, having financial concerns, and living outside of Québec were significantly associated with depressed mood.

Interpretation

The prevalence of depressed mood during the pandemic was between 2 and 3 times the pre-pandemic rate (especially among young people), but it can change rapidly in response to social changes. Thus, monitoring of psychological distress among vulnerable groups that may benefit from additional supports should be a priority.
Predicting Prognosis and IDH Mutation Status for Patients with Lower-Grade Gliomas Using Whole Slide Images
Authors: Jiang Shuai , Zanazzi George J. , Hassanpour Saeed
Published: January 2021

We developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the grade 3 gliomas TCGA dataset, which was not used for training, our models were able to predict survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas.
Using body temperature and variables commonly available in the EHR to predict acute infection: A proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients
Authors: Berdahl Carl T , Nguyen An T , Diniz Marcio A , Henreid Andrew J , Nuckols Teryl K , Libby Christopher P , Pevnick Joshua M
Published: January 2021

Objectives

Obtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, time of day.

Methods

For patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients’ COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: 1) body temperature alone; 2) body temperature and pretest probability; 3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3.

Results

Data from 117 patients were included. The models’ AUCs were: 1) 0.69 2) 0.72, and 3) 0.76, respectively. The absolute difference in AUC was 0.029 (95%CI −0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95%CI −0.021 to 0.097, p=0.10) between model 3 and 2.

Conclusions

By incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.
Single-cell deconvolution of 3,000 post-mortem brain samples for eQTL and GWAS dissection in mental disorders
Authors: Park Yongjin , He Liang , Davila-Velderrain Jose , Hou Lei , Mohammadi Shahin , Mathys Hansruedi , Peng Zhuyu , Bennett David , Tsai Li-Huei , Kellis Manolis
Published: January 2021

Thousands of genetic variants acting in multiple cell types underlie complex disorders, yet most gene expression studies profile only bulk tissues, making it hard to resolve where genetic and non-genetic contributors act. This is particularly important for psychiatric and neurodegenerative disorders that impact multiple brain cell types with highly-distinct gene expression patterns and proportions. To address this challenge, we develop a new framework, SPLITR, that integrates single-nucleus and bulk RNA-seq data, enabling phenotype-aware deconvolution and correcting for systematic discrepancies between bulk and single-cell data. We deconvolved 3,387 post-mortem brain samples across 1,127 individuals and in multiple brain regions. We find that cell proportion varies across brain regions, individuals, disease status, and genotype, including genetic variants in TMEM106B that impact inhibitory neuron fraction and 4,757 cell-type-specific eQTLs. Our results demonstrate the power of jointly analyzing bulk and single-cell RNA-seq to provide insights into cell-type-specific mechanisms for complex brain disorders.
Low adenovirus vaccine doses administered to skin using microneedle patches induce better functional antibody immunogenicity as compared to systemic injection
Authors: Flynn Olivia , Dillane Kate , Lanza Juliane Sousa , Marshall Jennifer M. , Jin Jing , Silk Sarah E. , Draper Simon J. , Moore Anne C.
Published: January 2021

Adenovirus-based vaccines are demonstrating promising clinical potential for multiple infectious diseases including COVID-19. However the immunogenicity of the vector itself decreases its effectiveness as a boosting vaccine due to the induction of strong anti-vector neutralising immunity. Here we determined how dissolvable microneedle patches (DMN) for skin immunization can overcome this issue, using a clinically-relevant adenovirus-basedPlasmodium falciparummalaria vaccine, AdHu5-PfRH5, in mice. Incorporation of vaccine into patches significantly enhanced its thermostability compared to the liquid form. Conventional high dose repeated immunization by the intramuscular (IM) route induced low antigen-specific IgG titres and high anti-vector immunity. A low priming dose of vaccine, by the IM route but more so using DMN patches, induced the most efficacious immune responses, assessed by parasite growth inhibitory activity (GIA) assays. Administration of low dose AdHu5-PfRH5 using patches to the skin, boosted by high dose IM, induced the highest antigen-specific serum IgG response after boosting, the greatest skewing of the antibody response towards the antigen and away from the vector and the highest efficacy. This study therefore demonstrates that repeated use of the same adenovirus vaccine can be highly immunogenic towards the transgene if a low dose is used to prime the response. It also provides a method of stabilising adenovirus vaccine, in easy-to-administer dissolvable microneedle patches, permitting storage and distribution out of cold chain.
Publication practices during the COVID-19 pandemic: Biomedical preprints and peer-reviewed literature
Authors: Sevryugina Yulia V. , Dicks Andrew J.
Published: January 2021

The coronavirus pandemic introduced many changes to our society, and deeply affected the established in biomedical sciences publication practices. In this article, we present a comprehensive study of the changes in scholarly publication landscape for biomedical sciences during the COVID-19 pandemic, with special emphasis on preprints posted on bioRxiv and medRxiv servers. We observe the emergence of a new category of preprint authors working in the fields ofimmunology, microbiology,infectious diseases, andepidemiology, who extensively used preprint platforms during the pandemic for sharing their immediate findings. The majority of these findings were works-in-progress unfitting for a prompt acceptance by refereed journals. The COVID-19 preprints that became peer-reviewed journal articles were often submitted to journals concurrently with the posting on a preprint server, and the entire publication cycle, from preprint to the online journal article, took on average 63 days. This included an expedited peer-review process of 43 days and journal’s production stage of 15 days, however there was a wide variation in publication delays between journals. Only one third of COVID-19 preprints posted during the first nine months of the pandemic appeared as peer-reviewed journal articles. These journal articles display high Altmetric Attention Scores further emphasizing a significance of COVID-19 research during 2020. This article will be relevant to editors, publishers, open science enthusiasts, and anyone interested in changes that the 2020 crisis transpired to publication practices and a culture of preprints in life sciences.
Activity in perirhinal and entorhinal cortex predicts perceived visual similarities among category exemplars with highest precision
Authors: Ferko Kayla M. , Blumenthal Anna , Martin Chris B. , Proklova Daria , Minos Alexander , Saksida Lisa M. , Bussey Timothy J. , Khan Ali R. , Köhler Stefan
Published: January 2021

Vision neuroscience has made great strides in understanding the hierarchical organization of object representations along the ventral visual stream (VVS). How VVS representations capture fine-grained visual similarities between objects that observers subjectively perceive has received limited examination so far. In the current study, we addressed this question by focusing on perceived visual similarities among subordinate exemplars of real world-categories. We hypothesized that these perceived similarities are reflected with highest fidelity in neural activity patterns downstream from inferotemporal regions, namely in perirhinal and anterolateral entorhinal cortex in the medial temporal-lobe. To address this issue with fMRI, we administered a modified 1-Back task that required discrimination between category exemplars as well as categorization. Further, we obtained observer-specific ratings of perceived visual similarities, which predicted behavioural performance during scanning. As anticipated, we found that activity patterns in perirhinal and anterolateral entorhinal cortex predicted the structure of perceived visual similarity relationships among category exemplars, including its observer-specific component, with higher precision than any other VVS region. Our findings provide new evidence that subjective aspects of object perception that rely on fine-grained visual differentiation are reflected with highest fidelity in the medial temporal lobe.
The Pif1 helicase is actively inhibited during meiotic recombination which restrains gene conversion tract length
Authors: Vernekar Dipti Vinayak , Reginato Giordano , Adam Céline , Ranjha Lepakshi , Dingli Florent , Marsolier Marie-Claude , Loew Damarys , Guérois Raphaël , Llorente Bertrand , Cejka Petr , Borde Valérie
Published: January 2021

Meiotic recombination ensures proper chromosome segregation to form viable gametes and results in gene conversions events between homologs. Conversion tracts are shorter in meiosis than in mitotically dividing cells. This results at least in part from the binding of a complex, containing the Mer3 helicase and the MutLβ heterodimer, to meiotic recombination intermediates. The molecular actors inhibited by this complex are elusive. The Pif1 DNA helicase is known to stimulate DNA polymerase delta (Pol δ) -mediated DNA synthesis from D-loops, allowing long synthesis required for break-induced replication. We show that Pif1 is also recruited genome wide to meiotic DNA double-strand break (DSB) sites. We further show that Pif1, through its interaction with PCNA, is required for the long gene conversions observed in the absence of MutLβ recruitment to recombination sites.In vivo, Mer3 interacts with the PCNA clamp loader RFC, andin vitro, Mer3-MutLβ ensemble inhibits Pif1-stimulated D-loop extension by Pol δ and RFC-PCNA. Mechanistically, our results suggest that Mer3-MutLβ may compete with Pif1 for binding to RFC-PCNA. Taken together, our data show that Pif1’s activity that promotes meiotic DNA repair synthesis is restrained by the Mer3-MutLβ ensemble which in turn prevents long gene conversion tracts and possibly associated mutagenesis.
Braiding Braak and Braak: Staging patterns and model selection in network neurodegeneration
Authors: Putra Prama , Thompson Travis B. , Chaggar Pavanjit , Goriely Alain ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2021

A hallmark of Alzheimer’s disease is the aggregation of insoluble amyloid-beta plaques and tau protein neurofibrillary tangles. A key histopathological observation is that tau protein aggregates follow a structured progression pattern through the brain. Mathematical network models of prion-like propagation have the ability to capture such patterns but a number of factors impact the observed staging result, thus introducing questions regarding model selection. Here, we introduce a novel approach, based on braid diagrams, for studying the structured progression of a marker evolving on a network. We apply this approach to a six-stage ‘Braak pattern’of tau proteins, in Alzheimer’s disease, motivated by a recent observation that seed-competent tau precedes tau aggregation. We show that the different modeling choices, from the model parameters to the connectome resolution, play a significant role in the landscape of observable staging patterns. Our approach provides a systematic way to approach model selection for network propagation of neurodegenerative diseases that ensures both reproducibility and optimal parameter fitting.

Author summary

Network diffusion models of neurodegenerative diseases are a class of dynamical systems that simulate the evolution of toxic proteins on the connectome. These models predict, from an initial seed, a pattern of invasion called staging. The generalized staging problem seeks to systematically study the effect of various model choices on staging. We introduce methods based on braid diagrams to test the possible staging landscape of a model and how it depends on the choice of connectome, as well as the model parameters. Our primary finding is that connectome construction, the choice of the graph Laplacian, and transport models all have an impact on staging that should be taken into account in any study.
A complex genetic architecture in zebrafish relativesDanio quaggaandD. kyathitunderlies development of stripes and spots
Authors: McCluskey Braedan M. , Uji Susumu , Mancusi Joseph L. , Postlethwait John H. , Parichy David M.
Published: January 2021

Vertebrate pigmentation is a fundamentally important, multifaceted phenotype. Zebrafish,Danio rerio, has been a valuable model for understanding genetics and development of pigment pattern formation due to its genetic and experimental tractability, advantages that are shared across severalDaniospecies having a striking array of pigment patterns. Here, we use the sister speciesD. quaggaandD. kyathit, with stripes and spots, respectively, to understand how natural genetic variation impacts phenotypes at cellular and organismal levels. We first show thatD. quaggaandD. kyathitphenotypes resemble those of wild-typeD. rerioand several single locus mutants ofD. rerio, respectively, in a morphospace defined by pattern variation along dorsoventral and anteroposterior axes. We then identify differences in patterning at the cellular level betweenD. quaggaandD. kyathitby repeated daily imaging during pattern development and quantitative comparisons of adult phenotypes, revealing that patterns are similar initially but diverge ontogenetically. To assess the genetic architecture of these differences, we employ reduced-representation sequencing of second-generation hybrids. Despite the similarity ofD. quaggatoD. rerio, andD. kyathitto someD. reriomutants, our analyses reveal a complex genetic basis for differences betweenD. quaggaandD. kyathit, with several quantitative trait loci contributing to variation in overall pattern and cellular phenotypes, epistatic interactions between loci, and abundant segregating variation within species. Our findings provide a window into the evolutionary genetics of pattern-forming mechanisms inDanioand highlight the complexity of differences that can arise even between sister species. Further studies of natural genetic diversity underlying pattern variation inD. quaggaandD. kyathitshould provide insights complementary to those from zebrafish mutant phenotypes and more distant species comparisons.

Author Summary

Pigment patterns of fishes are diverse and function in a wide range of behaviors. Common pattern themes include stripes and spots, exemplified by the closely related minnowsDanio quaggaandD. kyathit, respectively. We show that these patterns arise late in development owing to alterations in the development and arrangements of pigment cells. In the closely related model organism zebrafish (D. rerio) single genes can switch the pattern from stripes to spots. Yet, we show that pattern differences betweenD. quaggaandD. kyathithave a more complex genetic basis, depending on multiple genes and interactions between these genes. Our findings illustrate the importance of characterizing naturally occuring genetic variants, in addition to laboratory induced mutations, for a more complete understanding of pigment pattern development and evolution.
Conserved and divergent features of neuronal CaMKII holoenzyme structure, function, and high-order assembly
Authors: Buonarati Olivia R. , Miller Adam P. , Coultrap Steven J. , Bayer K. Ulrich , Reichow Steve L.
Published: January 2021

Neuronal CaMKII holoenzymes (α- and β-isoforms) enable molecular signal computation underlying learning and memory, but also mediate excitotoxic neuronal death. Here, we provide a comparative analysis of these signaling devices, using single particle EM in combination with biochemical and live-cell imaging studies. In the basal state, both isoforms assembled mainly as 12-mers (but also 14-mers, and even 16-mers for the β-isoform). CaMKIIα and β-isoforms adopted an ensemble of extended activatable states (with average radius of 12.6 versus 16.8 nm, respectively), characterized by multiple transient intra- and inter-holoenzyme interactions associated with distinct functional properties. The extended state of CaMKIIβ allowed EM analysis to directly resolve intra-holoenzyme kinase-domain dimers that could enable the cooperative activation mechanism by calmodulin, which was found for both isoforms. Surprisingly, high-order CaMKII clustering mediated by inter-holoenzyme kinase-domain dimerization was reduced for the β isoform for both basal and excitotoxicity-induced clusters, bothin vitroand in neurons.
DYNAMITE: a phylogenetic tool for identification of dynamic transmission epicenters
Authors: Magalis Brittany Rife , Marini Simone , Salemi Marco , Prosperi Mattia
Published: January 2021

Molecular data analysis is invaluable in understanding the overall behavior of a rapidly spreading virus population when epidemiological surveillance is problematic. It is also particularly beneficial in describing subgroups within the population, often identified as clades within a phylogenetic tree, that represent individuals connected via direct transmission or transmission via differing risk factors in viral spread. However, transmission patterns or viral dynamics within these smaller groups should not be expected to exhibit homogeneous behavior over time. As such, standard phylogenetic approaches that identify clusters based on summary statistics (e.g., median genetic distance over the clade) would not be expected to capture dynamic clusters of transmission. For this purpose, we have developed DYNAMITE (DYNAMic Identification of Transmission Epicenters), a cluster identification algorithm based on a branch-wise (rather than traditional clade-wise) search for cluster criteria, allowing partial clades to be recognized as clusters. Using simulated viral outbreaks with varying cluster types and dynamics, we show that DYNAMITE is consistently more sensitive than existing tools in detecting both static and dynamic transmission clusters. DYNAMITE has been implemented in R and released as open source at:github.com/ProsperiLab/DYNAMITE.
Proximity and Touch are associated with Neural but not Physiological Synchrony in Naturalistic Mother-Infant Interactions
Authors: Nguyen Trinh , Abney Drew H. , Salamander Dina , Bertenthal Bennett I. , Hoehl Stefanie
Published: January 2021

Caregiver touch plays a vital role in infants’ growth and development, but its role as a communicative signal in human parent-infant interactions is surprisingly poorly understood. Here, we assessed whether touch and proximity in caregiver-infant dyads are related to neural and physiological synchrony. We simultaneously measured brain activity and respiratory sinus arrhythmia of 4- to 6-month-old infants and their mothers (N=69 dyads) in distal and proximal joint watching conditions as well as in an interactive face-to-face condition. Neural synchrony was higher during the proximal than during the distal joint watching conditions, and even higher during the face-to-face interaction. Physiological synchrony was highest during the face-to-face interaction and lower in both joint watching conditions, irrespective of proximity. Maternal affectionate touch during the face-to-face interaction was positively related to neural but not physiological synchrony. This is the first evidence that touch mediates mutual attunement of brain activities, but not cardio-respiratory rhythms in caregiver-infant dyads during naturalistic interactions. Our results also suggest that neural synchrony serves as a biological pathway of how social touch plays into infant development and how this pathway could be utilized to support infant learning and social bonding.

Highlights

Mother-infant neural and physiological synchrony arise during mutual engagement.

Behavioral correlates of neural and physiological synchrony diverge.

Interpersonal neural synchrony is related to proximity and affective touch.

Interpersonal physiological synchrony is related to infant negative affect.
Dual expression of Atoh1 and Ikzf2 promotes transformation of adult cochlear supporting cells into outer hair cells
Authors: Sun Suhong , Li Shuting , Luo Zhengnan , Ren Minhui , He Shunji , Wang Guangqin , Liu Zhiyong
Published: January 2021

Mammalian cochlear outer hair cells (OHCs) are essential for hearing. OHC degeneration causes severe hearing impairment. Previous attempts of regenerating new OHCs from cochlear supporting cells (SCs) had yielded cells lacking Prestin, a key motor protein for OHC function. Thus, regeneration of Prestin+ OHCs remains a challenge for repairing OHC damagein vivo. Here, we reported that successfulin vivoconversion of adult cochlear SCs into Prestin+ OHC-like cells could be achieved by simultaneous expression of Atoh1 and Ikzf2, two key transcriptional factors necessary for OHC development. New OHC-like cells exhibited upregulation of hundreds of OHC genes and downregulation of SC genes. Single cell transcriptomic analysis demonstrated that the differentiation status of these OHC-like cells was much more advanced than previously achieved. Thus, we have established an efficient approach to promote regeneration of Prestin+ OHCs and paved the way for repairing damaged cochleain vivovia transdifferentiation of SCs.
Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia
Authors: Pazienti Antonio , Galluzzi Andrea , Dasilva Miguel , Sanchez-Vives Maria V. , Mattia Maurizio
Published: January 2021

During sleep and anesthesia, large groups of neurons throughout the entire cortex activate rhythmically producing wavefronts of activity referred to as slow-wave activity (SWA). In the arousal process, the brain restores its integrative and complex activity. The network mechanisms underlying this global state transition remain however to be elucidated. Here we investigated the network features shaping the SWA under fading anesthesia. Using electrocorticographical recordings of wide cortical areas of the mouse brain, we developed a quantitative measure of the anesthesia level based on slow-wave frequency and complexity. At deep anesthesia, we document a stringent alternation of posterior-anterior-posterior modes of propagation. With fading anesthesia, SWA evolves to produce a plethora of metastable spatiotemporal patterns. A network model of spiking neurons reproduced the data using short-range connectivity, subcortical input and a local activity-dependent adaptation. The emergence from deep anesthesia does not require modifying the connectivity, but small changes in the local excitability of cortical cell assemblies, further supporting the hypothesis of a tight bound between scales in the brain.
Functional brain network community structure in childhood: Unfinished territories and fuzzy boundaries
Authors: Tooley Ursula A. , Bassett Danielle S. , Mackey Allyson P.
Published: January 2021

Adult cortex is organized into distributed functional communities. Yet, little is known about community architecture of children’s brains. Here, we uncovered the community structure of cortex in childhood using fMRI data from 670 children aged 9-11 years from the Adolescent Brain and Cognitive Development study. Children showed similar community structure to adults in early-developing sensory and motor communities, but differences emerged in transmodal areas. Children have more cortical territory in the limbic community, which is involved in emotion processing, than adults. Regions of association cortex interact more flexibly across communities, creating uncertainty for the model-based assignment algorithm, and perhaps reflecting cortical boundaries that are not yet solidified. Uncertainty was highest for cingulo-opercular areas involved in flexible deployment of cognitive control. Collectively, our findings suggest that community boundaries are not solidified by middle childhood, an instability that provides important context for children’s thoughts and behaviors.
Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan
Authors: Kurita Junko , Sugawara Tamie , Sugishita Yoshiyuki , Ohkusa Yasushi
Published: January 2021

Background

Since the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.

Object

To evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.

Method

We applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.

Results

No excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.

Discussion and Conclusion

Significantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia.
Determining paracrystallinity in mixed-tacticity polyhydroxybutyrates
Authors: Van Opdenbosch Daniel , Haslböck Maria , Zollfrank Cordt
Published: January 2021

Recently, the authors reported on the development of crystallinity in mixed-tacticity polyhydroxybutyrates. Comparable values reported in the literature vary depending on the manner of determination, the discrepancies being partially attributable to scattering from paracrystalline portions of the material. These portions can be qualified by peak profile fitting or quantified by allocation of scattered X-ray intensities. However, the latter requires a good quality of the former, which in turn must additionally account for peak broadening inherent in the measurement setup, and due to limited crystallite sizes and the possible presence of microstrain. Since broadening due to microstrain and paracrystalline order both scale with scattering vector, they are easily confounded. In this work, a method to directionally discern these two influences on the peak shape in a Rietveld refinement is presented. Allocating intensities to amorphous, bulk and paracrystalline portions with changing tactic disturbance provided internal validations of the obtained directional numbers. In addition, the correlation between obtained thermal factors and Young's moduli, determined in earlier work, is discussed.