bluuebunny/crossref_metadata_2025 huggingface dataset:
The Value of 3 Tesla Field Strength for Musculoskeletal Magnetic Resonance Imaging
Authors: Khodarahmi Iman , Fritz Jan
Published: July 2021

Musculoskeletal magnetic resonance imaging (MRI) is a careful negotiation between spatial, temporal, and contrast resolution, which builds the foundation for diagnostic performance and value. Many aspects of musculoskeletal MRI can improve the image quality and increase the acquisition speed; however, 3.0-T field strength has the highest impact within the current diagnostic range. In addition to the favorable attributes of 3.0-T field strength translating into high temporal, spatial, and contrast resolution, many 3.0-T MRI systems yield additional gains through high-performance gradients systems and radiofrequency pulse transmission technology, advanced multichannel receiver technology, and high-end surface coils. Compared with 1.5 T, 3.0-T MRI systems yield approximately 2-fold higher signal-to-noise ratios, enabling 4 times faster data acquisition or double the matrix size. Clinically, 3.0-T field strength translates into markedly higher scan efficiency, better image quality, more accurate visualization of small anatomic structures and abnormalities, and the ability to offer high-end applications, such as quantitative MRI and magnetic resonance neurography. Challenges of 3.0-T MRI include higher magnetic susceptibility, chemical shift, dielectric effects, and higher radiofrequency energy deposition, which can be managed successfully. The higher total cost of ownership of 3.0-T MRI systems can be offset by shorter musculoskeletal MRI examinations, higher-quality examinations, and utilization of advanced MRI techniques, which then can achieve higher gains and value than lower field systems. We provide a practice-focused review of the value of 3.0-T field strength for musculoskeletal MRI, practical solutions to challenges, and illustrations of a wide spectrum of gainful clinical applications.
Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2 infection
Authors: Swadling Leo , Diniz Mariana O. , Schmidt Nathalie M. , Amin Oliver E. , Chandran Aneesh , Shaw Emily , Pade Corinna , Gibbons Joseph M. , Bert Nina Le , Tan Anthony T. , Jeffery-Smith Anna , Tan Cedric , Tham Christine Y. L. , Kucyowicz Stephanie , Aidoo-Micah Gloryanne , Rosenheim Joshua , Davies Jessica , Jensen Melanie P. , Joy George , McCoy Laura E , Valdes Ana M , van Dorp Lucy , Altmann Daniel M. , Boyton Rosemary J. , Manisty Charlotte , Treibel Thomas A. , Moon James C. ,   COVIDsortium investigators, Balloux Francois , McKnight Áine , Noursadeghi Mahdad , Bertoletti Antonio , Maini Mala K.
Published: July 2021

Individuals with likely exposure to the highly infectious SARS-CoV-2 do not necessarily develop PCR or antibody positivity, suggesting some may clear sub-clinical infection before seroconversion. T cells can contribute to the rapid clearance of SARS-CoV-2 and other coronavirus infections1–5. We hypothesised that pre-existing memory T cell responses, with cross-protective potential against SARS-CoV-26–12, would expand in vivo to mediate rapid viral control, potentially aborting infection. We studied T cells against the replication transcription complex (RTC) of SARS-CoV-2 since this is transcribed first in the viral life cycle13–15and should be highly conserved. We measured SARS-CoV-2-reactive T cells in a cohort of intensively monitored healthcare workers (HCW) who remained repeatedly negative by PCR, antibody binding, and neutralisation for SARS-CoV-2 (exposed seronegative, ES). 16-weeks post-recruitment, ES had memory T cells that were stronger and more multispecific than an unexposed pre-pandemic cohort, and more frequently directed against the RTC than the structural protein-dominated responses seen post-detectable infection (matched concurrent cohort). The postulate that HCW with the strongest RTC-specific T cells had an abortive infection was supported by a low-level increase in IFI27 transcript, a robust early innate signature of SARS-CoV-2 infection16. We showed that the RNA-polymerase within RTC was the largest region of high sequence conservation across human seasonal coronaviruses (HCoV) and was preferentially targeted by T cells from UK and Singapore pre-pandemic cohorts and from ES. RTC epitope-specific T cells capable of cross-recognising HCoV variants were identified in ES. Longitudinal samples from ES and an additional validation cohort, showed pre-existing RNA-polymerase-specific T cells expanded in vivo following SARS-CoV-2 exposure, becoming enriched in the memory response of those with abortive compared to overt infection. In summary, we provide evidence of abortive seronegative SARS-CoV-2 infection with expansion of cross-reactive RTC-specific T cells, highlighting these highly conserved proteins as targets for future vaccines against endemic and emerging Coronaviridae.
Reliability and Validity of Bifactor Models of Dimensional Psychopathology in Youth from three Continents
Authors: Hoffmann Maurício Scopel , Moore Tyler Maxwell , Axelrud Luiza Kvitko , Tottenham Nim , Zuo Xi-Nian , Rohde Luis Augusto , Milham Michael Peter , Satterthwaite Theodore Daniel , Abrahão Salum Giovanni
Published: July 2021

Bifactor models are a promising strategy to parse general from specific aspects of psychopathology in youth. Currently, there are multiple configurations of bifactor models originating from different theoretical and empirical perspectives. Our aim is to identify and test the reliability, validity, measurement invariance, and the correlation of different bifactor models of psychopathology using the Child Behavior Checklist (CBCL). We used data from the Reproducible Brain Charts (RBC) initiative (N=7,011, ages 5 to 22 years, 40.2% females). Factor models were tested using the baseline data. To address our aim, we a) mapped the published bifactor models using the CBCL; b) tested their global model fit; c) calculated model-based reliability indices. d) tested associations with symptoms’ impact in everyday life; e) tested measurement invariance across many characteristics and f) analyzed the observed factor correlation across the models. We found 11 bifactor models ranging from 39 to 116 items. Their global model fit was broadly similar. Factor determinacy and H index were acceptable for the p-factors, internalizing, externalizing and somatic specific factors in most models. However, only p- and attention factors were predictors of symptoms’ impact in all models. Models were broadly invariant across different characteristics. P-factors were highly correlated across models (r = 0.88 to 0.99). Homotypic specific factors were also highly correlated. Regardless of item selection and strategy to compose CBCL bifactor models, results suggest that they all assess very similar constructs. Our results provide support for the robustness of the bifactor of psychopathology and distinct study characteristics.

General Scientific Summaries

This study supports the notion that models of psychopathology that separate what is general from what is specific in mental health problems have little impact from item selection and types of specific dimensions. The general dimensions are highly correlated among different models, valid to predict symptom impact in daily life and are not influenced by demographic and clinical characteristics, time and information.
Multi-Sequence Average Templates for Aging and Neurodegenerative Disease Populations
Authors: Dadar Mahsa , Camicioli Richard , Duchesne Simon ,   For the CCNA Group
Published: July 2021

Magnetic resonance image (MRI) processing pipelines use average templates to enable standardization of individual MRIs in a common space. MNI-ICBM152 is currently used as the standard template by most MRI processing tools. However, MNI-ICBM152 represents an average of 152 healthy young adult brains and is vastly different from brains of patients with neurodegenerative diseases. In those populations, extensive atrophy might cause inevitable registration errors when using an average template of young healthy individuals for standardization. Disease-specific templates that represent the anatomical characteristics of the populations can reduce such errors and improve downstream driven estimates.

We present multi-sequence average templates for Alzheimer’s Dementia (AD), Fronto-temporal Dementia (FTD), Lewy Body Dementia (LBD), Mild Cognitive Impairment (MCI), cognitively intact and impaired Parkinson’s Disease patients (PD-CIE and PD-CI, respectively), individuals with Subjective Cognitive Impairment (SCI), AD with vascular contribution (V-AD), Vascular Mild Cognitive Impairment (V-MCI), Cognitively Intact Elderly (CIE) individuals, and a human phantom. We also provide separate templates for males and females to allow better representation of the diseases in each sex group.
Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity
Authors: Arvanitis Marios , Tayeb Karl , Strober Benjamin J. , Battle Alexis
Published: July 2021

Understanding the mechanisms that underlie genetic regulation of gene expression is crucial to explaining the diversity that governs complex traits. Large scale expression quantitative trait locus (eQTL) studies have been instrumental in identifying genetic variants that influence the expression of target genes. However, a large fraction of disease-associated genetic variants have not been clearly explained by current eQTL data, frustrating attempts to use these data to comprehensively characterize disease loci. One notable observation from recent studies is that cis-eQTL effects are often shared across different cell types and tissues. This would suggest that common genetic variants impacting steady-state, adult gene expression are largely tolerated, shared across tissues, and less relevant to disease. However, allelic heterogeneity and complex patterns of linkage disequilibrium (LD) within each locus may skew the quantification of sharing of genetic effects between tissues, impede our ability to identify causal variants, and hinder the identification of regulatory effects for disease-associated genetic variants. Indeed, recent research suggests that multiple causal variants are often present in many eQTL and complex trait associated loci. Here, we re-analyze tissue-specificity of genetic effects in the presence of LD and allelic heterogeneity, proposing a novel method, CAFEH, that improves the identification of causal regulatory variants across tissues and their relationship to disease loci.
Rotation-based schedules in elementary schools to prevent COVID-19 spread: A simulation study
Authors: Brom Cyril , Diviák Tomáš , Drbohlav Jakub , Korbel Václav , Levínský René , Neruda Roman , Suchopárová Gabriela , Šlerka Josef , Šmíd Martin , Trnka Jan , Vidnerová Petra
Published: July 2021

Background

Rotations of schoolchildren on a weekly basis is one of the nonpharmaceutical interventions often considered in the covid-19 pandemic. This study aims to investigate the impact of different types of rotations in various testing contexts.

Methods

We built an agent-based model of interactions among pupils and teachers based on an online survey in an elementary school in Prague, Czechia. This model contains 624 schoolchildren and 55 teachers (679 nodes) and about 27 thousands social contacts (edges) in 10 layers. The layers reflect different types of contacts (in classroom, cafeteria etc.) as described in the survey. On this multi-graph structure we run a modified SEIR model of the covid-19 dynamics. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in the period March to June 2020.

Findings

There are three main findings in our paper.

Weekly rotations of in-class and distance learning reduce the spread of covid-19 by 75–81% and thus represent an effective preventative measure in school setting.

Regular antigen testing twice a week, or weekly PCR testing, significantly reduces infections even when using tests with a lower sensitivity: tests with a 40% sensitivity reduce infections by more than 50 percent.

The density of revealed contact graphs for older pupils is 1.5 times higher than the younger pupils graph, the teachers network is yet an order of magnitude denser. Consequently, the infection transmission between teachers is highly overproportional in our school. Moreover, teachers act as bridges connecting clusters of classes, especially in the secondary grade where they are responsible for 14–18% of infections, in comparison to 8–11% in primary grade.

Interpretation

Weekly rotations with regular testing are a highly effective non-pharmaceutical intervention for the prevention of covid-19 spread in schools and a way to keep schools open during an epidemic or to reopen them as the epidemiological situation improves.
Correlation between the environmental parameters with outbreak pattern of COVID-19: A district level investigation based on yearlong period in India
Authors: Gupta Amitesh , Saha Laboni
Published: July 2021

The present study has investigated the role of regional meteorology and air quality parameters in the outbreak pattern of COVID-19 pandemic in India. Using the remote sensing based dataset of 12 environmental variables we correlated infective case counts at a district level in India. Our investigation carried out on the circumstantial data from more than 300 major affected districts in India and found that air quality parameters are playing very crucial role in this outbreak. Among the air pollutants, O3 was better correlating with infection counts followed by AOD, CO, NO2, BC and SO2. We also observed that among the weather parameters air temperature, incoming shortwave radiation, wind speed are positively and significantly associate with outbreak pattern and precipitation and humidity are negatively correlated with confirmed cases; only cloud cover has no significant relation. We noted that coastal districts in the both coast of India and districts located in the plain and low-lying areas have experienced bitter situation during this pandemic. Our study suggests that improving air quality with proper strict regulations and complete lockdown during the peak of pandemic could reduce the misfortune in all over India.
The Gendered Implications of Energy Gaps in Health Care: A Comparative Analysis of Haiti, Senegal, and the Democratic Republic of Congo
Authors: Shastry Vivek , Morse Sophie M.
Published: July 2021

The World Health Organization recently articulated a number of challenges faced by health systems due to unreliable access to energy services. Reliable energy availability at rural health facilities is understood to be an enabler of access to quality healthcare, owing to its potential impacts on medical services, health and safety, disease prevention and treatment, staff recruitment and retention, and administration and logistics. However, little is known empirically about the intersections of energy and healthcare, often due to the lack of availability of facility level data. Moreover, the gender implications of energy access (or lack thereof) for women as providers and seekers of primary healthcare have not been investigated. In this study, using a gender lens, we explore the linkages between energy and healthcare in three Francophone countries in the Caribbean and sub-Saharan Africa: Democratic Republic of the Congo (DRC), Haiti and Senegal. All three countries have faced serious challenges to the provision of quality health services, including infrastructure problems and specifically unreliable access to electricity. We use Demographic Health Survey data from all three countries to present detailed descriptions of the association between (a) the availability and reliability of electricity sources, and (b) availability of health services, equipment and medical personnel at different levels of the respective health systems. We find that the unavailability and unreliability of electricity is associated with lower availability of medical equipment and basic health services, especially among facilities at the primary care level in DRC and Haiti. Our findings highlight the opportunity to create more dependable and sustainable health systems by integrating decentralized clean energy technologies into health infrastructure, which can facilitate providers in female-dominated cadres such as nursing the ability to provide the care they are tasked with.
Infectivity and immune escape of the new SARS-CoV-2 variant of interest Lambda
Authors: Acevedo Mónica L. , Alonso-Palomares Luis , Bustamante Andrés , Gaggero Aldo , Paredes Fabio , Cortés Claudia P. , Valiente-Echeverría Fernando , Soto-Rifo Ricardo
Published: July 2021

Background

The newly described SARS-CoV-2 lineage C.37 was recently classified as a variant of interest by the WHO (Lambda variant) based on its high circulation rates in South American countries and the presence of critical mutations in the spike protein. The impact of such mutations in infectivity and immune escape from neutralizing antibodies are entirely unknown.

Methods

We performed a pseudotyped virus neutralization assay and determined the impact of the Lambda variant on infectivity and immune escape using plasma samples from healthcare workers (HCW) from two centers in Santiago, Chile who received the two-doses scheme of the inactivated virus vaccine CoronaVac.

Results

We observed an increased infectivity mediated by the Lambda spike protein that was even higher than that of the D614G (lineage B) or the Alpha and Gamma variants. Compared to the Wild type (lineage A), neutralization was decreased by 3.05-fold for the Lambda variant while it was 2.33-fold for the Gamma variant and 2.03-fold for the Alpha variant.

Conclusions

Our results indicate that mutations present in the spike protein of the Lambda variant of interest confer increased infectivity and immune escape from neutralizing antibodies elicited by CoronaVac. These data reinforce the idea that massive vaccination campaigns in countries with high SARS-CoV-2 circulation must be accompanied by strict genomic surveillance allowing the identification of new isolates carrying spike mutations and immunology studies aimed to determine the impact of these mutations in immune escape and vaccines breakthrough.
Characterization of DNA extrusion scenarios underlying aggregate Hi-C patterns by a new computational framework
Authors: Zhang Xizhe , Gogoshin Grigoriy , Branciamore Sergio
Published: July 2021

1

Aggregate Hi-C maps centered on several genetic elements show significant DNA extrusion features. However, these features are missing from the component Hi-C images. To resolve this discrepancy, we present a new computational framework that reconstructs DNA extrusion scenarios (DESs) and explains the enhancement of DNA extrusion features by aggregation. We showed that the reconstructed DES is essential to understand the site interactions of the relevant genetic elements. For example, CCCTC-binding factor (CTCF) binding elements (CBE) with a specific motif direction are only affected by DNA extrusion activities initiated from one side, manifested as a directional bias. About half of promoters search for enhancers in a specific direction, as indicated by the corresponding DES. Moreover, since DNA extrusion does not pause at promoter or enhancer elements, direct promoter-enhancer contacts are not long-lasting; rather, promoters and enhancers are brought in proximity by continuous, dynamic DNA extrusion.
The recent range expansion of Great Cormorants (Phalacrocorax carbo hanedae) in Hokkaido, Japan
Authors: Squires Theodore E. , Aoki Daisuke , Hasegawa Osamu
Published: July 2021

Though the Japanese subspecies of Great Cormorant (Phalacrocorax carbo hanedae) has increased its population in recent decades, information on its spread to the northern island of Hokkaido has not been reported outside of Japan. The purpose of this paper is to update the scientific community about the breeding and range ecology of P. carbo, and to provide comparative information on the abundant and similar looking resident Japanese Cormorant (P. capillatus). Several ornithological groups and researchers were contacted in order to gather information about the current distribution and breeding activities of P. carbo in the region. Here the findings of Japanese research groups, translated publications, and direct observations are made available.
Specialization of chromatin-bound nuclear pore complexes promotes yeast aging
Authors: Meinema Anne C. , Aspert Theo , Lee Sung Sik , Charvin Gilles , Barral Yves
Published: July 2021

The nuclear pore complex (NPC) mediates nearly all exchanges between nucleus and cytoplasm, and changes composition in many species as the organism ages. However, how these changes arise and whether they contribute themselves to aging is poorly understood. We show that in replicatively aging yeast cells attachment of DNA circles to NPCs drives the displacement of the NPCs’ nuclear basket and cytoplasmic complexes. Remodeling of the NPC resulted from the regulation of basket components by SAGA, rather than from damages. These changes affected NPC interaction with mRNA export factors, without affecting the residence of import factors or engaging the NPC quality control machinery. Mutations preventing NPC remodeling extended the replicative lifespan of the cells. Thus, our data indicate that DNA circles accumulating in the mother cell drive aging at least in part by triggering NPC specialization. We suggest that antagonistic pleiotropic effects of NPC specialization are key drivers of aging.
Logical modeling: Combining manual curation and automated parameterization to predict drug synergies
Authors: Flobak Åsmund , Zobolas John , Vazquez Miguel , Steigedal Tonje S. , Thommesen Liv , Grislingås Asle , Niederdorfer Barbara , Folkesson Evelina , Kuiper Martin
Published: July 2021

Treatment with drug combinations carries great promise for personalized therapy. We have previously shown that drug synergies targeting cancer can manually be identified based on a logical framework. We now demonstrate how automated adjustments of model topology and logic equations can greatly reduce the workload traditionally associated with logical model optimization. Our methodology allows the exploration of larger model ensembles that all obey a set of observations. We benchmark synergy predictions against a dataset of 153 targeted drug combinations. We show that well-performing manual models faithfully represent measured biomarker data and that their performance can be outmatched by automated parameterization using a genetic algorithm. The predictive performance of a curated model is strongly affected by simulated curation errors, while data-guided deletion of a small subset of edges can improve prediction quality. With correct topology we find some tolerance to simulated errors in the biomarker calibration data. With our framework we predict the synergy of joint inhibition of PI3K and TAK1, and further substantiate this prediction with observation in cancer cell cultures and in xenograft experiments.
First Report of Lactoria cornuta from Karnataka, West coast of India–Role of tropical cyclones in Range Extension
Authors: Muhammed Zafar Iqbal A.N. , Mali Gurudev , Dollin Raghavendra
Published: July 2021

India is known for its rich biodiversity and is fortunate to have several endemic species from different classes of vertebrates. India is home to 7.5% of the global fish diversity, with 91 endemic species of ray finned fishes, the actinopterygians. Some fish species have never been reported until recently, one such example is the long-horned Cowfish (Ostracidae), best known for inhabiting only certain areas of the Indo-Pacific oceans. However, this fish has been reported from Bay of Bengal, Costs of Goa and Lakshadweep. This is the first time this fish has been found on the Coasts of Karnataka, west coast of India. Given its morphology, the migration seems highly improbable since it can only endure lethargic swimming. In this article, we have explored the role of other external forces that could have contributed to its range extension in the east and west coast of India. In this paper we are exploring the role of Super Cyclones as a vital force in determining the expansion of its range. The fact of collection longhorn cowfish for the first time from the coast of Karwar coincides with the passage of Cyclone Ockhi on the west coast of India this suggests the possible role of super cyclone in its range extension. A year later, another specimen was recovered from a location very close to the first, which indicates the successful establishment of Lacturia cornuta in its new environment. Related morphometric and meristic studies of our specimens are consistent with previous studies reported in the Bay of Bengal.
PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts
Authors: Li Ruidong , Zhu Jianguo , Zhong Wei-De , Jia Zhenyu
Published: July 2021

Prostate cancer (PCa) is a heterogeneous disease with highly variable clinical outcomes which presents enormous challenges in the clinical management. A vast amount of transcriptomics data from large PCa cohorts have been generated, providing extraordinary opportunities for the molecular characterization of the PCa disease and the development of diagnostic and prognostic signatures. The lack of an inclusive collection and harmonization of the scattered public datasets constrains the extensive use of the valuable resources. In this study, we present a user-friendly database, PCaDB, for a comprehensive and interactive analysis and visualization of gene expression profiles from 77 transcriptomics datasets with 9,068 patient samples. PCaDB also includes a single-cell RNA-sequencing (scRNAseq) dataset for normal human prostates and 30 published PCa prognostic signatures. The comprehensive data resources and advanced analytical methods equipped in PCaDB would greatly facilitate data mining to understand the heterogeneity of PCa and to develop machine learning models for accurate PCa diagnosis and prognosis to assist on clinical decision-making. PCaDB is publicly available at http://bioinfo.jialab-ucr.org/PCaDB/.
The Genome Sequence Archive Family: Towards Explosive Data Growth and Diverse Data Types
Authors: Chen Tingting , Chen Xu , Zhang Sisi , Zhu Junwei , Tang Bixia , Wang Anke , Dong Lili , Zhang Zhewen , Yu Caixia , Sun Yanling , Chi Lianjiang , Chen Huanxin , Zhai Shuang , Sun Yubin , Lan Li , Zhang Xin , Xiao Jingfa , Bao Yiming , Wang Yanqing , Zhang Zhang , Zhao Wenming
Published: July 2021

The Genome Sequence Archive (GSA) is a data repository for archiving raw sequence data, which provides data storing and sharing services for worldwide scientific communities. Considering explosive data growth with diverse data types, here we present the GSA family by expanding into a set of resources for raw data archive with different purposes, namely, GSA (https://ngdc.cncb.ac.cn/gsa/), GSA for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human/), and Open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix/). Compared with the 2017 version, GSA has been significantly updated in data model, online functionalities, and web interfaces. GSA-Human, as a new partner of GSA, is a data repository specialized in human genetics-related data with controlled access and security. OMIX, as a critical complement to the two resources mentioned above, is an open archive for miscellaneous data. Together, all these resources form a family of resources dedicated to archiving explosive data with diverse types, accept data submissions from all over the world and provide free open access to all publicly available data in support of worldwide research activities.
Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research
Authors: Kastally Chedly , Niskanen Alina K. , Perry Annika , Kujala Sonja T. , Avia Komlan , Cervantes Sandra , Haapanen Matti , Kesälahti Robert , Kumpula Timo A. , Mattila Tiina M. , Ojeda Dario I. , Tyrmi Jaakko S. , Wachowiak Witold , Cavers Stephen , Kärkkäinen Katri , Savolainen Outi , Pyhäjärvi Tanja
Published: July 2021

Scots pine (Pinus sylvestris) is the most widespread coniferous tree in the boreal forests of Eurasia and has major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies and genomic selection. We present a new 50K SNP genotyping array for Scots pine research, breeding programs, and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array, and identified 47 712 high-quality SNPs for the final array (called ‘PiSy50k’). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns, and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from breeding populations from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.92%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the amount of Mendelian error was negligible. In addition, array genotypes successfully discriminate Scots pine populations from different geographic origins. The PiSy50k array will be a valuable tool for future genetic studies and forestry applications.

Significance statement

Scots pine is an evolutionary, economically and ecologically impressive coniferous species but its gigantic genome has limited studying e.g. the genetic basis of its functional trait variation. We have developed a genotyping array that facilitates Scots pine genetic research and linking its trait variation to genetic polymorphisms and gene expression levels across the genome.
SLOW5: a new file format enables massive acceleration of nanopore sequencing data analysis
Authors: Gamaarachchi Hasindu , Samarakoon Hiruna , Jenner Sasha P. , Ferguson James M. , Amos Timothy G. , Hammond Jillian M. , Saadat Hassaan , Smith Martin A. , Parameswaran Sri , Deveson Ira W.
Published: July 2021

Nanopore sequencing is an emerging genomic technology with great potential. However, the storage and analysis of nanopore sequencing data have become major bottlenecks preventing more widespread adoption in research and clinical genomics. Here, we elucidate an inherent limitation in the file format used to store raw nanopore data – known as FAST5 – that prevents efficient analysis on high-performance computing (HPC) systems. To overcome this, we have developed SLOW5, an alternative file format that permits efficient parallelisation and, thereby, acceleration of nanopore data analysis. For example, we show that using SLOW5 format, instead of FAST5, reduces the time and cost of genome-wide DNA methylation profiling by an order of magnitude on common HPC systems, and delivers consistent improvements on a wide range of different architectures. With a simple, accessible file structure and a ~25% reduction in size compared to FAST5, SLOW5 format will deliver substantial benefits to all areas of the nanopore community.
A dinucleotide tag-based parallel reporter gene assay method
Authors: Ren Naixia , Li Bo , Liu Qingqing , Yang Lele , Liu Xiaodan , Huang Qilai
Published: July 2021

The causal SNPs leading to increased cancer predisposition mainly function as gene regulatory elements, the evaluation of which largely rely on the parallel reporter gene assay system. However, the common DNA barcode-based parallel reporter gene assay systems are troubled with tag bias, mainly due to the tag nucleotide composition. Here we describe a versatile dinucleotide-tag reporter system (DiR) that enables parallel analysis of regulatory elements with minimized bias based on the next-generation sequencing. The DiR system is also more robust than the classical luciferase assay method, especially in the investigation of moderate-level regulatory elements. We applied DiR-seq assay in the functional evaluation of the prostate cancer risk SNPs in prostate cancer cell lines and disclosed 2, and 6 regulatory SNPs in PC-3 and LNCaP cells. The DiR system has great potential to advance the functional study of risk SNPs that have associations with polygenic diseases.
Quercetin ameliorates mitochondrial dysfunction and mitigates methamphetamine-induced anxiety-like behavior
Authors: Chen Fengrong , Sun Jiaxue , Zhang Yongjin , Dai Yicong , Zhang Zherui , Chen Cheng , Zou Lei , Zhang Zunyue , Wu Hongjin , Tian Weiwei , Xu Yu , Luo Huayou , Yu Juehua , Wang Kunhua
Published: July 2021

Methamphetamine (MA) abuse results in neurotoxic outcomes, including increased anxiety and depression, during both MA use and withdrawal. Although numerous studies have reported an association between MA exposure and anxiety, the underlying mechanism remains elusive. In this study, escalating dose of MA was used to establish an MA-treated mouse model presenting anxiety behavior. RNA seq was then performed to profile the gene expression patterns in the hippocampus (HIPP). Differentially expressed genes (DEGs) were identified and function enrichment analysis was conducted to explore the underlying mechanisms. Quercetin as an mitochondria protector was usedin vivoandin vitro. The C57BL/6J mice were co-treated with 50 mg/kg Quercetin and escalating MA. Anxiety behavior was evaluated by utilizing the elevated plus maze and the open field test. Transmission electron microscopy and immunohistochemistry were conducted to study the pathology of MA-inducced anxiety. The effects of MA and Quercetin on astrocytes were investigated by fluorescence staining, transmission electron microscopy, flow cytometry, and oxygen consumption rate. Western blot and qPCR were performed to analyze altered protein and gene levels of HIPP in mice and astrtocytes. The results demonstrated that forteen upregulated differentially expressed genes were identified and significantly enriched in signaling pathways related to psychiatric disorders and mitochondrial function. Interestingly, we found that quercetin was able to alleviate MA-induced anxiety-like behavior by improving neuron number and mitochondria injury. Mechanistically, quercetin can mitigate aberrant mitochondrial morphology and mitochondrial dysfunction not only by decreasing the levels of total cytoplasmic reactive oxygen species (ROS), mitochondria-derived ROS (mtROS), and mitochondrial membrane potential (MMP), but also increasing the oxygen consumption rate (OCR) and mitochondrial ATP productionin vitro, indicating Quercetin ameliorated MA-induced anxiety-like behavior by modifying mitochondrial morphology and function. Furthermore, quercetin reversed OPA1 and DRP1 expression in astrocytes, and mitigated astrocyte activation and the release of inflammatory factors, which can trigger neuronal apoptosis and synaptic loss. Taken together, we provided evidence showing that MA can induce anxiety-like behavior via the induction of oxidative stress and mitochondrial dysfunction. Quercetin exerted antipsychotic activity through mitochondrial modulation, suggesting its potential for further therapeutic development in MA-induced anxiety.
A neuromorphic model of olfactory processing and sparse coding in the Drosophila larva brain
Authors: Jürgensen Anna-Maria , Khalili Afshin , Chicca Elisabetta , Indiveri Giacomo , Nawrot Martin Paul
Published: July 2021

Animal nervous systems are highly efficient in processing sensory input. The neuromorphic computing paradigm aims at the hardware implementation of neural network computations to support novel solutions for building brain-inspired computing systems. Here, we take inspiration from sensory processing in the nervous system of the fruit fly larva. With its strongly limited computational resources of <200 neurons and <1.000 synapses the larval olfactory pathway employs fundamental computations to transform broadly tuned receptor input at the periphery into an energy efficient sparse code in the central brain. We show how this approach allows us to achieve sparse coding and increased separability of stimulus patterns in a spiking neural network, validated with both software simulation and hardware emulation on mixed-signal real-time neuromorphic hardware. We verify that feedback inhibition is the central motif to support sparseness in the spatial domain, across the neuron population, while the combination of spike frequency adaptation and feedback inhibition determines sparseness in the temporal domain. Our experiments demonstrate that such small-sized, biologically realistic neural networks, efficiently implemented on neuromorphic hardware, can achieve parallel processing and efficient encoding of sensory input at full temporal resolution.
Transcriptional profiling of sequentially generated septal neuron fates
Authors: García Miguel Turrero , Stegmann Sarah K , Lacey Tiara E , Reid Christopher M , Hrvatin Sinisa , Weinreb Caleb , Adam Manal A , Aurel Nagy M , Harwell Corey C
Published: July 2021

The septum is a ventral forebrain structure known to regulate innate behaviors. During embryonic development, septal neurons are produced in multiple proliferative areas from neural progenitors following transcriptional programs that are still largely unknown. Here, we use a combination of single cell RNA sequencing, histology and genetic models to address how septal neuron diversity is established during neurogenesis. We find that the transcriptional profiles of septal progenitors change along neurogenesis, coinciding with the generation of distinct neuron types. We characterize the septal eminence, a spatially distinct and transient proliferative zone composed of progenitors with distinctive molecular profiles, proliferative capacity and fate potential compared to the rostral septal progenitor zone. We show that Nkx2.1-expressing septal eminence progenitors give rise to neurons belonging to at least three morphological classes, born in temporal cohorts that are distributed across different septal nuclei in a sequential fountain-like pattern. Our study provides insight into the molecular programs that control the sequential production of different neuronal types in the septum, a structure with important roles in regulating mood and motivation.
Atrazine induced In vivo immunotoxicity in Bivalves
Authors: Muhammed Zafar Iqbal A.N , Iqbal Navalgund M. Azhar
Published: July 2021

Atrazine is ubiquitously used broad-spectrum herbicide to control the weeds in agriculture. The present study aimed to evaluate the acute toxicity and immunotoxicity of Atrazine in two ecologically and economically important bivalves. Acute toxicity of atrazine evaluated in triplicates by taking control and six experimental groups each comprising of 30 animals and treated with a range of atrazine from 2 PPM to 12 PPM for 96 hours. Mortalities were recorded for every 24 hours until 96 hours and data analyzed by one-way ANOVA and Dunnett T-test. The results indicated a significant increase in mortalities with increase in dose and time of exposure in both species. The values of LC50 were determined as 6.10 PPM and 4.90 PPM respectively for Perna viridis and Paphia malabarica. Furthermore, the immunotoxic potential of atrazine assessed by treating mussels and clams with the five sub-lethal doses of atrazine for 14 days and quantifying the viability of hemocytes by using simple yet reliable Tryphan blue exclusion assay. The results of the present study suggest atrazine-induced immunotoxicity by decreasing the number of viable hemocytes in bivalves. Hemocytes with phagocytic function are indispensable to confer innate immunity in bivalves, decreased viability of these cells leads to compromised immunity. This study is first of its kind to implicate atrazine with the immunotoxicity in bivalves.
HMMploidy: inference of ploidy levels from short-read sequencing data
Authors: Soraggi Samuele , Rhodes Johanna , Altinkaya Isin , Tarrant Oliver , Balloux François , Fisher Matthew C. , Fumagalli Matteo
Published: July 2021

The inference of ploidy levels from genomic data is important to understand molecular mechanisms underpinning genome evolution. However, current methods based on allele frequency and sequencing depth variation do not have power to infer ploidy levels at low-and mid-depth sequencing data, as they do not account for data uncertainty. Here we introduce HMMploidy, a novel tool that leverages the information from multiple samples and combines the information from sequencing depth and genotype likelihoods. We demonstrate that HMMploidy outperforms existing methods in most tested scenarios, especially at low-depth with large sample size. We apply HMMploidy to sequencing data from the pathogenic fungus Cryptococcus neoformans and retrieve pervasive patterns of aneuploidy, even when artificially downsampling the sequencing data. We envisage that HMMploidy will have wide applicability to low-depth sequencing data from polyploid and aneuploid species.
Discovering cancer driver genes and pathways using stochastic block model graph neural networks
Authors: Fanfani Viola , Vinas Torne Ramon , Lio' Pietro , Stracquadanio Giovanni
Published: July 2021

The identification of genes and pathways responsible for the transformation of normal cellsinto malignant ones represents a pivotal step to understand the aetiology of cancer, to characterise progression and relapse, and to ultimately design targeted therapies. The advent of high-throughput omic technologies has enabled the discovery of a significant number of cancer driver genes, but recent genomic studies have shown these to be only necessary but not sufficient to trigger tumorigenesis. Since most biological processes are the results of the interaction of multiple genes, it is then conceivable that tumorigenesis is likely the result of the action of networks of cancer driver and non-driver genes. Here we take advantage of recent advances in graph neural networks, combined with well established statistical models of network structure, to build a new model, called Stochastic Block Model Graph Neural Network (SBM-GNN), which predicts cancer driver genes and cancer mediating pathways directly from high-throughput omic experiments. Experimental analysis of synthetic datasets showed that our model can correctly predict genes associated with cancer and recover relevant pathways, while outperforming other state-of-the-art methods. Finally, we used SBM-GNN to perform a pan-cancer analysis, where we found genes and pathways directly involved with the hallmarks of cancer controlling genome stability, apoptosis, immune response, and metabolism.
Children are full of optimism, but those rose-tinted glasses are fading – reduced learning from negative outcomes drives hyperoptimism in children
Authors: Habicht Johanna , Bowler Aislinn , Moses-Payne Madeleine E , Hauser Tobias U
Published: July 2021

Believing that good things will happen in life is essential to maintain motivation and achieve highly ambitious goals. This optimism bias, the overestimation of positive outcomes, may be particularly important during childhood when motivation must be maintained in the face of negative outcomes. In a learning task, we have thus studied the mechanisms underlying the development of optimism bias. Investigating children (8-9 year-olds), early (12-13 year-olds) and late adolescents (16-17 year-olds), we find a consistent optimism bias across age groups. However, children were particularly hyperoptimistic, with the optimism bias decreasing with age. Using computational modelling, we show that this was driven by a reduced learning from worse-than-expected outcomes, and this reduced learning explains why children are hyperoptimistic. Our findings thus show that insensitivity to bad outcomes in childhood helps to prevent taking on an overly realistic perspective and maintain motivation.
Single-cell analyses of immune thrombocytopenic patients reveal multiorgan dissemination of high-affinity autoreactive plasma cells
Authors: Canales-Herrerias Pablo , Crickx Etienne , Broketa Matteo , Sokal Aurélien , Chenon Guilhem , Azzaoui Imane , Vandenberghe Alexis , Perima Angga , Iannascoli Bruno , Goff Odile Richard-Le , Castrillon Carlos , Mottet Guillaume , Sterlin Delphine , Robbins Ailsa , Michel Marc , England Patrick , Millot Gael A. , Eyer Klaus , Baudry Jean , Mahevas Matthieu , Bruhns Pierre
Published: July 2021

The major therapeutic goal for immune thrombocytopenia (ITP) is to restore normal platelet counts using drugs to promote platelet production or by interfering with mechanisms responsible for platelet destruction. 80% of patients possess anti-integrin αIIbβ3 (GPIIbIIIa) IgG autoantibodies causing platelet opsonization and phagocytosis. The spleen is considered the primary site of autoantibody production by autoreactive B cells and platelet destruction. The immediate failure in ~50% of patients to recover a normal platelet count after anti-CD20 Rituximab-mediated B cell depletion and splenectomy suggest that autoreactive, rituximab-resistant, IgG-secreting B cells (IgG-SC) reside in other anatomical compartments. We analyzed >3,300 single IgG-SC from spleen, bone marrow and/or blood of 27 patients with ITP revealing high inter-individual variability in affinity for GPIIbIIIa with variations over 3 logs. IgG-SC dissemination and range of affinities were however similar per patient. Longitudinal analysis of autoreactive IgG-SC upon treatment with anti-CD38 mAb daratumumab demonstrated variable outcomes, from complete remission to failure with persistence of high-affinity anti-GPIIbIIIa IgG-SC in the bone marrow. This study demonstrates the existence and dissemination of high-affinity autoreactive plasma cells in multiple anatomical compartments of patients with ITP that may cause the failure of current therapies.
Using wearable biosensors and ecological momentary assessments for the detection of prolonged stress in real life
Authors: Tutunji Rayyan , Kogias Nikos , Kapteijns Bob , Krentz Martin , Krause Florian , Vassena Eliana , Hermans Erno J.
Published: July 2021

Background

Increasing efforts toward prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated.

Methods

Using ecological momentary assessments (EMA) combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (i.e., an exam week) on physiological arousal and affect. With this paradigm we investigated whether we could use wearable devices to detect stress states using machine learning models.

Results

During stressful high-stake exam (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal was decreased on average during the exam week. Time-resolved analyses revealed peaks in physiological arousal associated with both self-reported stress and self-reported positive affect, while the overall decrease in physiological arousal was mediated by lower positive affect during the stress period. We then used machine learning to show that a combination of EMA and physiology yields optimal identification of stress states.

Conclusions

Our findings highlight the potential of wearable biosensors in stress-related mental-health monitoring, but critically show that psychological context is essential for interpreting physiological arousal detected using these devices.