bluuebunny/crossref_metadata_2025_split huggingface dataset:
Independent and distinct patterns of abnormal lateral orbitofrontal cortex activity during compulsive grooming and reversal learning normalize after fluoxetine
Authors: Manning Elizabeth E , Geramita Matthew A , Piantadosi Sean C , Pierson Jamie L , Ahmari Susanne E 
Published: March 2021

AbstractBackgroundPatients with obsessive-compulsive disorder (OCD) display disrupted performance and abnormal lateral orbitofrontal cortex (LOFC) activity during reversal learning tasks, yet it is unknown whether compulsions and reversal learning deficits share a common neural substrate. To answer this question, we measured neural activity within vivocalcium imaging in LOFC during compulsive grooming and reversal learning before and after fluoxetine treatment.MethodsSapap3-knockout (KO) mice were used as a model for OCD-relevant behaviors.Sapap3-KOs and control littermates were injected with virus encoding GCaMP6f and implanted with gradient-index lenses to visualize LOFC activity using miniature microscopes. Grooming, reversal learning, and neural activity were measured pre- and post-fluoxetine treatment (18mg/kg, 4 weeks).ResultsBaseline compulsive grooming and reversal learning impairments in KOs improved after fluoxetine treatment. Additionally, KOs display distinct patterns of abnormal LOFC activity during grooming and reversal learning, both of which normalize after fluoxetine. Finally, modulation in response to reversal learning and compulsive behavior are independent, as reversal learning-associated neurons are distributed randomly amongst grooming-associated neurons (i.e. overlap is what would be expected by chance).ConclusionsIn OCD, the LOFC is disrupted during both compulsive behaviors and reversal learning, yet whether these behaviors share common neural underpinnings is unknown. We find that the LOFC plays distinct and independent roles in compulsive grooming and impaired reversal learning and their improvement with fluoxetine. These findings suggest that LOFC plays separate roles in pathophysiology and treatment of different perseverative behaviors in OCD.
Pneumococcal genetic variability influences age-dependent bacterial carriage
Authors: Kremer PHC , Ferwerda B , Bootsma HJ , Rots NY , Wijmega-Monsuur AJ , Sanders EAM , Trzciński K , Wyllie AL , Turner P , van der Ende A , Brouwer MC , Bentley SD , van de Beek D , Lees JA 
Published: March 2021

AbstractThe pneumococcal conjugate vaccine (PCV) primarily reduces disease burden in adults through a reduction in carriage prevalence of invasive serotypes in children. Current vaccine formulations are the same for both adults and children, but tailoring these formulations to age category could optimize vaccine efficacy. Identification of specific pneumococcal genetic factors associated with carriage in younger or older age groups may suggest alternative formulations and contribute to a better mechanistic understanding of immunity. Here, we used whole genome sequencing to dissect pneumococcal variation associated with age. We performed genome sequencing in a large carriage cohort, and conducted a meta-analysis with an existing carriage study. We compiled a dictionary of pathogen genetic variation including serotype, sequence cluster, sequence elements, SNPs, burden combined rare variants, and clusters of orthologous genes (COGs) for each cohort – all of which used in a genome-wide association with host age. Age-dependent colonization had some heritability, though this varied between cohorts (h2= 0.10, 0.00 – 0.69 95% CI in the first; h2= 0.46, 0.33 – 0.60 95% CI in the second cohort). We found that serotypes and genetic background (strain) explained most of the heritability in each cohort (h2serotype= 0.06 and h2GPSC= 0.04 in the first; h2serotype= 0.20 and h2GPSC= 0.23 in the second cohort). We found one candidate association (p = 1.2×10−9) upstream of an accessory Sec-dependent serine-rich glycoprotein adhesin. Overall, association with age was highly cohort and strain dependent, supporting proposals for a future vaccination strategy which is primarily targeted using serotypes rather than proteins, and is tailored towards specific pathogen populations.
Identification of gene products involved in plant colonization byPantoeasp. YR343 using a diguanylate cyclase expressed in the presence of plants
Authors: Bible Amber N. , Chang Mang , Morrell-Falvey Jennifer L. 
Published: March 2021

AbstractMicrobial colonization of plant roots is a highly complex process that requires the coordination and regulation of many gene networks, yet the functions of many of these gene products remain poorly understood.Pantoeasp. YR343, a gamma-proteobacterium isolated from the rhizosphere ofPopulus deltoides, forms robust biofilms along the root surfaces ofPopulusand possesses plant growth-promoting characteristics. The mechanisms governing biofilm formation along plant roots by bacteria, includingPantoeasp. YR343, are not fully understood and many genes involved in this process have yet to be discovered. In this work, we identified three diguanylate cyclases in the plant-associated microbePantoeasp. YR343 that are expressed in the presence of plant roots, One of these diguanylate cyclases, DGC2884 localizes to discrete sites in the cells and its overexpression results in reduced motility and increased EPS production and biofilm formation. We then performed a genetic screen by expressing this diguanylate cyclase from an inducible promoter in order to identify candidate downstream effectors of c-di-GMP signaling which may be involved in root colonization byPantoeasp. YR343. Further, we demonstrate the importance of other domains in DGC2884 to its activity, which in combination with the genes identified by transposon mutagenesis, may yield insights into activity and regulation of homologous enzymes in medically and agriculturally relevant microbes.
Site-specific phosphorylation of PSD-95 dynamically regulates the post-synaptic density as observed by phase separation
Authors: Vistrup-Parry Maria , Chen Xudong , Johansen Thea L. , Bach Sofie , Buch-Larsen Sara C. , Bartling Christian R. O. , Ma Chenxue , Clemmensen Louise S. , Nielsen Michael L. , Zhang Mingjie , Strømgaard Kristian 
Published: March 2021

SUMMARYPostsynaptic density protein 95 is a key scaffolding protein in the postsynaptic density of excitatory glutamatergic neurons, organizing signaling complexes primarily via its three PSD-95/Discs-large/Zona occludens domains. PSD-95 is regulated by phosphorylation, but technical challenges have limited studies of the molecular details. Here, we genetically introduced site-specific phosphorylations in single, tandem and full-length PSD-95 and generated a total of 11 phosphorylated protein variants. We examined how these phosphorylations affected binding to known interaction partners and the impact on phase separation of PSD-95 complexes, and identified two new phosphorylation sites with opposing effects. Phosphorylation of Ser78 inhibited phase separation with the glutamate receptor subunit GluN2B and the auxiliary protein stargazin, whereas phosphorylation of Ser116 induced phase separation with stargazin only. Thus, by genetically introducing phosphoserine site-specifically and exploring the impact on phase separation, we have provided new insights into the regulation of PSD-95 by phosphorylation and the dynamics of the PSD.Graphical Abstract: Phosphorylation of PSD-95.Illustration of the interaction between the PDZ domains of PSD-95 and the NMDA receptor (NMDAR) (PDB: 4PE5) at the plasma membrane. PSD-95 interacts with the AMPA receptor (AMPAR) (PDB: 3KG2) through Stargazin (PDB: 5KBU). Using the software Ranch, a model of FL PSD-95 was generated using known structural domains of PSD-95 connected via a fully-flexible linker (PDZ1-2, PDB: 3GSL; PDZ3, PDB: 5JXB; SH3-GK, PDB: 1KJW).Illustration of the effect of phosphorylation of PSD-95 on the formation of condensates at the PSD. PSD-95 can phase separate with receptors and intracellular proteins, and phosphorylation is can affect this interaction and lead to alterations, both negative and positive, in the formation of condensates.
Genome-wide analysis of focal DNA hypermethylation inIDH-mutant AML samples
Authors: Wilson Elisabeth R. , Helton Nichole M. , Heath Sharon E. , Fulton Robert S. , Payton Jacqueline E. , Welch John S. , Walter Matthew J. , Westervelt Peter , DiPersio John F. , Link Daniel C. , Miller Christopher A. , Ley Timothy J. , Spencer David H. 
Published: March 2021

AbstractRecurrent mutations inIDH1orIDH2in acute myeloid leukemia (AML) are associated with increased DNA methylation, but the genome-wide patterns of this hypermethylation phenotype have not been comprehensively studied in AML samples. We analyzed whole-genome bisulfite sequencing data from 15 primary AML samples withIDH1orIDH2mutations, which identified ~4,000 focal regions that were uniquely hypermethylated vs. normal CD34+ cells. These regions had modest, but significant, hypermethylation in AMLs with biallelicTET2mutations, and 5-hydroxymethylation levels that were dependent on functional TET2, indicating that hypermethylation in these regions is caused by inhibition of TET-mediated demethylation. Focal hypermethylation inIDHmutAMLs occurred in regions with low methylation in normal CD34+ cells, implying that DNA methylation and demethylation are active at these loci. AML samples containingIDHandDNMT3AR882mutations were significantly less hypermethylated, suggesting that methylation in these regions is mediated by DNMT3A.IDHmut-specific hypermethylation was highly enriched for enhancers that form direct interactions with genes involved in normal hematopoiesis and AML, includingMYCandETV6. These results suggest that focal hypermethylation inIDH-mutant AML occurs by altering the balance between DNA methylation and demethylation, and that disruption of these pathways at enhancers may contribute to AML pathogenesis.
High-frequency screening combined with diagnostic testing for control of SARS-CoV-2 in high-density settings: an economic evaluation of resources allocation for public health benefit
Authors: Rogers Will , Ruiz-Aravena Manuel , Hansen Dale , Madden Wyatt , Kessler Maureen , Fields Matthew W. , Ferrari Matthew J. , Chang Connie B. , Morrow Jayne , Hoegh Andrew , Plowright Raina K. 
Published: March 2021

AbstractSARS-CoV-2 spreads quickly in dense populations, with serious implications for universities, workplaces, and other settings where exposure reduction practices are difficult to implement. Rapid screening has been proposed as a tool to slow the spread of the virus; however, many commonly used diagnostic tests (e.g., RT-qPCR) are expensive, difficult to deploy (e.g., require a nasopharyngeal specimen), and have extended turn-around times. We evaluated testing regimes that combined diagnostic testing using qPCR with high-frequency screening using a novel reverse-transcription loop-mediated isothermal amplification (RT-LAMP, herein LAMP) assay. We used a compartmental susceptible-exposed-infectious-recovered (SEIR) model to simulate screening of a university population. We also developed a Shiny application to allow administrators and public health professionals to develop optimal testing strategies given site-specific assumptions about testing investment, target population, and cost. The frequency of screening, especially when pooling samples, was more important for minimizing epidemic size than test sensitivity, behavioral compliance, contact tracing capacity, and time between testing and results. Our results suggest that when testing budgets are limited, it is safer and more cost-effective to allocate the majority of funds to screening. Rapid, cost-effective, and scalable screening tests, like LAMP, should be viewed as critical components of SARS-CoV-2 testing in high-density populations.
High seroprevalence of anti-SARS-CoV-2 antibodies after the first wave of the COVID-19 pandemic in a vulnerable population in Perpignan, France
Authors: Beaumont Adeline , Durand Cécile , Ledrans Martine , Schwoebel Valérie , Noel Harold , Le Strat Yann , Diulius Donatien , Colombain Léa , Médus Marie , Gueudet Philippe , Mouly Damien , Aumaître Hugues 
Published: March 2021

ABSTRACTBackgroundIn March 2020, many cases of COVID-19 were reported in three socially deprived neighbourhoods of the city of Perpignan, in the south of France, where large sedentary gypsy communities live. A study to measure seroprevalence was conducted in July 2020 to assess the level of contamination in these neighbourhoods after the first wave of the pandemic, and to identify factors associated with seropositivity.MethodsSCoPe is a cross-sectional survey conducted in selected persons aged six years old and over living in three neighbourhoods in Perpignan. Households were selected by systematic sampling and participants by random sampling. Collected blood samples were tested for SARS-CoV-2 IgG and IgM antibodies using the EIecsys® immunoassay to target the coronavirus’s spike protein. Antibody seroprevalence was estimated from weighted data and associated factors were investigated using multivariate logistic regression.ResultsThe seroprevalence of anti-SARS-CoV-2 antibodies was 35.4% (95% CI: 30.2-41.0). Over a fifth of seropositive individuals (21.7% ([14.1-31.8]) did not report any COVID-19 symptom. People aged 15-64 years old were at greater risk of seropositivity than those aged 65 years or over. Obesity prevalence was 40.7% (35.8-45.8) and obese people were more likely to be seropositive (aOR=2.0 [1.1-3.8]). The risk of being seropositive was higher in households with clinical COVID-19 cases (One case: aOR=2.5 [1.3-5.0]). In the neighbourhood with the highest measured seroprevalence, people living in a dwelling with 1-2 rooms had a higher risk of being seropositive than those living in a 4-room house (aOR=2.8 [1.2-6.3]). Working during the lockdown was associated with a lower risk of seropositivity (aOR=0.2 [0.03-1.0]).ConclusionTransmission prevalence of the SARS-COV-2 virus in this vulnerable population was very high during the COVID-19 pandemic’s first wave. Our results highlight the need to strengthen and adapt preventive measures by taking into account all social determinants of health, especially housing conditions.
Predicting functional consequences of mutations using molecular interaction network features
Authors: Ozturk Kivilcim , Carter Hannah 
Published: March 2021

AbstractVariant interpretation remains a central challenge for precision medicine. Missense variants are particularly difficult to understand as they change only a single amino acid in protein sequence yet can have large and varied effects on protein activity. Numerous tools have been developed to identify missense variants with putative disease consequences from protein sequence and structure. However, biological function arises through higher order interactions among proteins and molecules within cells. We therefore sought to capture information about the potential of missense mutations to perturb protein interaction networks by integrating protein structure and interaction data. We developed 16 network-based annotations for missense mutations that provide orthogonal information to features classically used to prioritize variants. We then evaluated them in the context of a proven machine-learning framework for variant effect prediction across multiple benchmark datasets to demonstrate their potential to improve variant classification. Interestingly, network features resulted in larger performance gains for classifying somatic mutations than for germline variants, possibly due to different constraints on what mutations are tolerated at the cellular versus organismal level. Our results suggest that modeling variant potential to perturb context-specific interactome networks is a fruitful strategy to advancein silicovariant effect prediction.
Evotuning protocols for Transformer-based variant effect prediction on multi-domain proteins
Authors: Yamaguchi Hideki , Saito Yutaka 
Published: March 2021

AbstractAccurate variant effect prediction has broad impacts on protein engineering. Recent machine learning approaches toward this end are based on representation learning, by which feature vectors are learned and generated from unlabeled sequences. However, it is unclear how to effectively learn evolutionary properties of an engineering target protein from homologous sequences, taking into account the protein’s sequence-level structure called domain architecture (DA). Additionally, no optimal protocols are established for incorporating such properties into Transformer, the neural network well-known to perform the best in natural language processing research. This article proposes DA-aware evolutionary fine-tuning, or “evotuning”, protocols for Transformer-based variant effect prediction, considering various combinations of homology search, fine-tuning, and sequence vectorization strategies. We exhaustively evaluated our protocols on diverse proteins with different functions and DAs. The results indicated that our protocols achieved significantly better performances than previous DA-unaware ones. The visualizations of attention maps suggested that the structural information was incorporated by evotuning without direct supervision, possibly leading to better prediction accuracy.Availabilityhttps://github.com/dlnp2/evotuning_protocols_for_transformersSupplementary informationSupplementary data are available atBriefings in Bioinformaticsonline.
Sleep deprivation exacerbates seizures and diminishes GABAergic tonic inhibition
Authors: Konduru Sai Surthi , Pan Yuzhen , Wallace Eli , Pfammatter Jesse A , Jones Mathew V. , Maganti Rama K. 
Published: March 2021

AbstractPatients with epilepsy report that sleep deprivation is a common trigger for breakthrough seizures. The basic mechanism of this phenomenon is unknown. In the Kv1.1-/-mouse model of epilepsy, daily sleep deprivation indeed exacerbated seizures though these effects were lost after the 3rdday. Sleep deprivation also accelerated mortality in ~52% of Kv1.1-/-mice, not observed in controls. Voltage-clamp experiments on the day after recovery from sleep deprivation showed reductions in GABAergic tonic inhibition in dentate granule cells both in Kv1.1-/-and wild-type mice. Our results suggest that sleep deprivation is detrimental to seizures and survival, possibly due to reductions in GABAergic tonic inhibition.
Regulation of coordinated muscular relaxation by a pattern-generating intersegmental circuit
Authors: Hiramoto Atsuki , Jonaitis Julius , Niki Sawako , Kohsaka Hiroshi , Fetter Richard , Cardona Albert , Pulver Stefan , Nose Akinao 
Published: March 2021

AbstractTypical patterned movements in animals are achieved through combinations of contraction and delayed relaxation of groups of muscles. However, how intersegmentally coordinated patterns of muscular relaxation are regulated by the neural circuits remain poorly understood. Here, we identify Canon, a class of higher-order premotor interneurons, that regulates muscular relaxation during backward locomotion ofDrosophilalarvae. Canon neurons are cholinergic interneurons present in each abdominal neuromere and show wave-like activity during fictive backward locomotion. Optogenetic activation of Canon neurons induces relaxation of body wall muscles, whereas inhibition of these neurons disrupts timely muscle relaxation. Canon neurons provide excitatory outputs to inhibitory premotor interneurons. Canon neurons also connect with each other to form an intersegmental circuit and regulate their own wave-like activities. Thus, our results demonstrate how coordinated muscle relaxation can be realized by an intersegmental circuit that regulates its own patterned activity and sequentially terminates motor activities along the anterior-posterior axis.
Wearable sensing devices acceptance behavior in construction safety and health: assessing existing models and developing a hybrid conceptual model
Authors: Okpala Ifeanyi , Nnaji Chukwuma , Awolusi Ibukun 
Published: March 2021

Purpose
This study aims to examine relationships between several key technology acceptance variables that predict workers’ wearable sensing devices (WSDs) acceptance in the construction industry by using technology acceptance model, theory of planned behavior and unified theory of acceptance and use of technology (UTAUT) model. The study proposes a hybrid conceptual model to measure construction field workers’ intentions to use WSDs and their usage behaviors. The study introduces variables that are instrumental in understanding and improving WSD acceptance in construction.

Design/methodology/approach
The study was carried out using a structured literature review, online survey and structural equation modeling. A total of 195 field workers across the USA, with experience in using WSDs, participated in the study.

Findings
Results indicate that all three theories predict WSD acceptance with variables explaining at least 89% of the variance in actual use, with the UTAUT outperforming other models (91%). However, the differences between the predictive power of these models were not statistically significant. A hybrid conceptual model is proposed using findings from the present study.

Practical implications
The study contributes to knowledge and practice by highlighting key variables that influence WSD acceptance. Findings from this study should provide stakeholders with critical insights needed to successfully drive WSD acceptance in the construction industry.

Originality/value
To the best of the authors’ knowledge, this is the first study that evaluates the predictive strength of multiple technology acceptance theories and models within the construction worker safety technology domain. Additionally, the study proposes a hybrid conceptual model which could provide practitioners and researchers with information pertinent to enhancing WSD acceptance.
A deployment framework for BIM localization
Authors: Wang Jing , Lu Weisheng 
Published: March 2021

PurposeOver the past two decades, building information modeling (BIM) has been promoted as one of the most disruptive innovations across the global architecture, engineering and construction (AEC) community. Nevertheless, despite its widely propagated benefits, BIM adoption in various localities is not progressing excitingly. BIM as an innovation developed from a presumed, general context may not fit well with the specific regulatory, social and cultural settings of a locality. This study aims to tackle the lukewarm local BIM adoption by developing a deployment framework for BIM localization.Design/methodology/approachDrawing upon the diffusion of innovation (DoI) theory, a longitudinal case study is designed and conducted by engaging closely with a top cost consultancy company in Hong Kong for forty-one months.FindingsThe findings refuted the “one-size-fits-for-all” view to use a standardized BIM for international users. Rather, an organization needs to undergo a series of localization works to integrate global BIM in its specific local context. The deployment framework outlines the BIM dimensions (i.e. technology, process and protocol) and the mechanisms (i.e. configuration, coupling and reinterpretation) of BIM localization that go through the three “A”s (i.e. analysis, adaption and assimilation) process under a firm's network and contextual factors.Originality/valueThis study improves our understanding of sluggish BIM adoption by attributing it to the gap between general BIM development and the local, unique BIM use context. Proposing the deployment framework, the study also offers a handy tool for prospective executives to localize BIM and harness its power in their respective organizations and localities.