bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular epidemiology and antimicrobial resistance phenotype of paediatric bloodstream infections caused by Gram-negative bacteria in Oxfordshire, UK
Authors: Lipworth Sam , Vihta Karina-Doris , Davies Tim , Wright Sarah , Tabirao Merline , Chau Kevin , Vaughan Alison , Kavanagh James , Barker Leanne , George Sophie , Segal Shelley , Paulus Stephane , Barrett Lucinda , Oakley Sarah , Jeffery Katie , Butcher Lisa , Peto Tim , Crook Derrick , Walker Sarah , Kadambari Seilesh , Stoesser Nicole
Published: June 2021

Objectives

Gram-negative organisms are common causes of bloodstream infection (BSI) during the neonatal period and early childhood. Whilst several large studies have characterised these isolates in adults, equivalent data (particularly incorporating whole genome sequencing) is lacking in the paediatric population.

Methods

We performed an epidemiological and sequencing based analysis of Gram-negative bloodstream infections in children <18 years old between 2008 and 2018 in Oxfordshire, UK.

Results

327 isolates (296 successfully sequenced) from 287 patients were included. The burden of infection was predominantly in neonates (124/327[38%]). Most infections were caused byEscherichia coli (149/327[46%])/Klebsiellaspp. (69/327[21%]) andEnterobacter hormaechei (34/327[10%]). There was no evidence of an increasing incidence ofE. coliBSIs (IRRy 0.96, 95%CI 0.90-1.30, p=0.30) and forKlebsiellaspp. there was some evidence that the incidence decreased slightly (IRRy 0.91, 95%CI 0.83-1.00, p=0.06). Similarly the proportion of antimicrobial resistant (across all antimicrobial classes evaluated) isolates did not change over time, though we did identify some evidence of sub-breakpoint increases in gentamicin resistance IRRy 1.86, 95%CI 1.33-2.58, pheterogeneity=0.002. The population structure ofE. coliBSI isolates in neonates and children mirrors that in adults with a predominance of STs 131/95/73/69 and the same proportion of O-antigen serotypes covered by the ExPEC-4V vaccine. In most cases there was no evidence of transmission/point-source acquisition and whole genome sequencing was able to refute a previously suspectedSerratia marcescensoutbreak.

Conclusion

Our findings support continued use of current empirical treatment guidelines and suggest that O-antigen targeted vaccines may have a role in reducing the incidence of neonatal sepsis.
Determination of IgG1 and IgG3 SARS-CoV-2 spike protein and nucleocapsid binding – Who is binding who and why?
Authors: IIes Jason K , Zmuidinaite Raminta , Sadée Christoph , Gardiner Anna , Lacey Jonathan , Harding Stephen , Wallis Gregg , Patel Roshani , Roblett Debra , Heeney Jonathan , Baxendale Helen , Iles Ray K
Published: June 2021

The involvement of IgG3 in the humoral immune response to SARS-CoV2 infection has been implicated in the pathogenesis of ARDS in COVID-19. The exact molecular mechanism is unknown but may be due to the differential ability of IgG3 Fc region to fix complement and stimulate cytokine release. We examined convalescent patients’ antibodies binding to immobilised nucleocapsid and spike protein by MALDI-ToF mass spectrometry. IgG3 was a major immunoglobulin found in all samples. Differential analysis of the spectral signatures found for nucleocapsid versus spike protein demonstrated that the predominant humoral immune response to nucleocapsid was IgG3, whilst against spike it was IgG1. However, the spike protein displayed a strong affinity for IgG3 itself which it would bind from control plasma samples as well as from those previously infected with SARS-CoV2, much in the way Protein-G binds IgG1. Furthermore, detailed spectral analysis indicated a mass shift consistent with hyper-glycosylation or glycation was a characteristic of the IgG3 captured by the spike protein.
NATURAL HISTORY OF LAFORA DISEASE A Prognostic Systematic Review and Individual Participant Data Meta-Analysis
Authors: Pondrelli Federica , Muccioli Lorenzo , Licchetta Laura , Mostacci Barbara , Zenesini Corrado , Tinuper Paolo , Vignatelli Luca , Bisulli Francesca
Published: June 2021

Objective

To describe the clinical course of Lafora Disease (LD) and identify predictors of outcome by means of a prognostic systematic review with individual participant data meta-analysis.

Methods

A search was conducted on MEDLINE and Embase with no restrictions on publication date. Only studies reporting genetically confirmed LD cases were included. Kaplan-Meier estimate was used to assess probability of death and of loss of autonomy. Univariable and multivariable Cox regression models with mixed effects (clustered survival data) were performed to evaluate prognostic factors.

Results

Seventy-three papers describing 298 genetically confirmed LD cases were selected. Mean age at disease onset was 13.4 years (SD 3.7), with 9.1% aged≥ 18 years. Overall survival rates in 272 cases were 93% [95% CI 89-96] at 5 years, 62% [95% CI 54-69] at 10 years and 57% [95% CI 49-65] at 15 years. Median survival time was 11 years. The probability of loss of autonomy in 110 cases was 45% [95% CI 36-55] at 5 years, 75% [95% CI 66-84] at 10 years, and 83% [95% CI 74-90] at 15 years. Median loss of autonomy time was 6 years. Asian origin and age at onset <18 years emerged as negative prognostic factors, while type of mutated gene and symptoms at onset were not related to survival or disability.

Conclusions

This study documented that half of patients survived at least 11 years. The notion of actual survival rate and prognostic factors is crucial to design studies on the effectiveness of upcoming new disease-modifying therapies.
COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya
Authors: Brand Samuel P. C. , Ojal John , Aziza Rabia , Were Vincent , Okiro Emelda A , Kombe Ivy K , Mburu Caroline , Ogero Morris , Agweyu Ambrose , Warimwe George M , Nyagwange James , Karanja Henry , Gitonga John N , Mugo Daisy , Uyoga Sophie , Adetifa Ifedayo M O , Scott J Anthony G , Otieno Edward , Murunga Nickson , Otiende Mark , Ochola-Oyier Lynette I , Agoti Charles N , Githinji George , Kasera Kadondi , Amoth Patrick , Mwangangi Mercy , Aman Rashid , Ng’ang’a Wangari , Tsofa Benjamin , Bejon Philip , Keeling Matt. J. , Nokes D. James. , Barasa Edwine
Published: June 2021

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies.

One Sentence Summary

COVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure
Clinician views on best practice community care for people with complex emotional needs and how it can be achieved: a qualitative study
Authors: Foye Una , Stuart Ruth , Trevillion Kylee , Oram Sian , Allen Dawn , Broeckelmann Eva , Jefferies Stephen , Jeynes Tamar , Crawford Mike J , Moran Paul , McNicholas Shirley , Billings Jo , Dale Oliver , Simpson Alan , Johnson Sonia
Published: June 2021

Background

Service provision for people with complex emotional needs (CEN) is recurrently identified as needing to be transformed: there are serious concerns about quality, accessibility, fragmentation of the service system and the stigma and therapeutic pessimism service users say they encounter. We use the term CEN as a working description to refer to the needs experienced by people who may have been diagnosed with a ‘personality disorder’. Understanding clinician perspectives is vital for service transformation, as their views and experiences shed light on potential barriers to achieving good care, and how these might be overcome. In this study, we aimed to explore these views.

Methods

We used a qualitative interview design. A total of fifty participants from a range of professions across specialist and generic community mental health services across England who provide care to people with CEN took part in six focus groups and sixteen one-to-one interviews. We analysed the data using a thematic approach.

Findings

Main themes were: 1) Defining Best Practice, 2) Facilitators of Best Care, 3) Barriers to Best Care, 4) Systemic Challenges. Across these themes, staff highlighted in particular the need for care that was person-centred, relational, empathic, and trauma informed. However, major barriers to achieving this are stigmatising attitudes and behaviour towards people with CEN, especially in generic mental health services, lack of development of coherent service systems offering clear long-term pathways and ready access to high quality treatment, and lack of well-developed structures for staff training and support.

Discussion

Overall, the findings point towards clinician views as generally congruent with those of service users, reinforcing the need for priorities towards systemwide change to ensure that we can provide the best practice care for these individuals. Particularly prominent is the need to put in place system-wide training and support for clinicians working with CEN, encompassing generic as well as specialist services, and to challenge the stigma still experienced throughout the system.

Conclusions

Staff working with this service user group report that delivering best practice care services to be flexible, integrated, and sustainably funded, and for staff to be supported through ongoing training and supervision.
Evaluation of the Access Bio CareStart™ rapid SARS-CoV-2 antigen test in asymptomatic individuals tested at a community mass-testing program in Western Massachusetts
Authors: Suliman Sara , Matias Wilfredo R. , Fulcher Isabel R , Molano Francisco J. , Collins Shannon , Uceta Elizabeth , Zhu Jack , Paxton Ryan M. , Gonsalves Sean F. , Harden Maegan V. , Fisher Marissa , Meldrim Jim , Gabriel Stacey , Franke Molly F. , Hung Deborah T. , Smole Sandra C. , Madoff Lawrence C. , Ivers Louise C.
Published: June 2021

Background

Point-of-care antigen-detecting rapid diagnostic tests (RDTs) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represent a scalable tool for SARS-CoV-2 infections surveillance. Data on their performance in real-world community settings is paramount for their implementation.

Method

We evaluated the accuracy of CareStart™ COVID-19 Antigen test (CareStart) in a testing site in Holyoke, Massachusetts. We compared CareStart to a SARS-CoV-2 reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) reference, using anterior nasal swab samples. We calculated the sensitivity, specificity, and expected positive and negative predictive values at different SARS-CoV-2 prevalence estimates.

Results

We performed 666 tests on 591 unique individuals. 573 (86%) were asymptomatic. There were 52 positive tests by RT-qPCR. The sensitivity of CareStart was 49.0% (95% Confidence Interval (CI): 34.8 – 63.4) and specificity was 99.5% (95% CI: 98.5 – 99.9). Among positive RT-qPCR tests, the median cycle threshold (Ct) was significantly lower in samples that tested positive on CareStart. Using a Ct ≤ 30 as a benchmark for positivity increased the sensitivity to 64.9% (95% CI: 47.5 – 79.8).

Conclusions

CareStart has a high specificity and moderate sensitivity. The utility of RDTs, such as CareStart, in mass implementation should prioritize use cases in which a higher specificity is more important.
Structural basis for the interaction of SARS-CoV-2 virulence factor nsp1 with Pol α - Primase
Authors: Kilkenny Mairi L. , Veale Charlotte E. , Guppy Amir , Hardwick Steven W. , Chirgadze Dimitri Y. , Rzechorzek Neil J. , Maman Joseph D. , Pellegrini Luca
Published: June 2021

The molecular mechanisms that drive the infection by the SARS-CoV-2 coronavirus – the causative agent of the COVID-19 (Coronavirus disease-2019) pandemic – are under intense current scrutiny, to understand how the virus operates and to uncover ways in which the disease can be prevented or alleviated.

Recent cell-based analyses of SARS-CoV-2 protein - protein interactions have mapped the human proteins targeted by the virus. The DNA polymerase α - primase complex or primosome – responsible for initiating DNA synthesis in genomic duplication – was identified as a target of nsp1 (non structural protein 1), a major virulence factor in the SARS-CoV-2 infection.

Here, we report the biochemical characterisation of the interaction between nsp1 and the primosome and the cryoEM structure of the primosome - nsp1 complex. Our data provide a structural basis for the reported interaction between the primosome and nsp1. They suggest that Pol α - primase plays a part in the immune response to the viral infection, and that its targeting by SARS-CoV-2 aims to interfere with such function.
Discovery of SARS-CoV-2 MproPeptide Inhibitors from Modelling Substrate and Ligand Binding
Authors: Chan H. T. Henry , Moesser Marc A. , Walters Rebecca K. , Malla Tika R. , Twidale Rebecca M. , John Tobias , Deeks Helen M. , Johnston-Wood Tristan , Mikhailov Victor , Sessions Richard B. , Dawson William , Salah Eidarus , Lukacik Petra , Strain-Damerell Claire , Owen C. David , Nakajima Takahito , Świderek Katarzyna , Lodola Alessio , Moliner Vicent , Glowacki David R. , Walsh Martin A. , Schofield Christopher J. , Genovese Luigi , Shoemark Deborah K. , Mulholland Adrian J. , Duarte Fernanda , Morris Garrett M.
Published: June 2021

The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mprosubstrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mprosubstrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mprocompetitively. The combined results provide new insight useful for the development of Mproinhibitors.
WWP1 deficiency protects from cardiac remodeling induced by simulated microgravity
Authors: Zhong Guohui , Zhao Dingsheng , Li Jianwei , Liu Zifan , Pan Junjie , Yuan Xinxin , Xing Wenjuan , Zhao Yinglong , Ling Shukuan , Li Yingxian
Published: June 2021

Cardiac muscle is extremely sensitive to changes in loading conditions, the microgravity during space flight can cause cardiac remodeling and function decline. At present, the mechanism of microgravity-induced cardiac remodeling remains to be revealed. WW domain-containing E3 ubiquitin protein ligase 1 (WWP1) is an important activator of pressure-overload induced cardiac remodeling by stabilizing disheveled segment polarity proteins 2 (DVL2) and activating CaMKII/HDAC4/MEF2C axis. However, the role of WWP1 in the cardiac remodeling induced by microgravity is unknown. The purpose of this study was to determine whether WWP1 was also involved in the regulation of cardiac remodeling caused by microgravity. Firstly, we detected the expression of WWP1 and DVL2 in the heart from mice and monkeys after simulated microgravity using western blotting and Immunohistochemistry. Secondly, WWP1 knockout (KO) and wild type mice were subjected to hindlimb unloading (HU) to simulate microgravity effect. We assessed the cardiac remodeling in morphology and function through histological analysis and echocardiography. Finally, we detected the phosphorylation level of CaMKII and HDAC4 in the heart from WT and WWP1 KO mice after HU. The results revealed the increased expression of WWP1 and DVL2 in the heart both from mice and monkey after simulated microgravity. WWP1 deficiency protected against simulated microgravity-induced cardiac atrophy and function decline. Histological analysis demonstrated WWP1 KO inhibited the decreases in the size of individual cardiomyocytes of mice after hindlimb unloading. WWP1 KO can inhibit the activation of DVL2/CaMKII/HDAC4 pathway in heart of mice induced by simulated microgravity. These results demonstrated WWP1 as a potential therapeutic target for cardiac remodeling and function decline induced by simulated microgravity.
A method to study extracellular vesicles secretedin vitroby cultured cells with minimum sample processing and extracellular vesicle loss
Authors: Viveiros A , Kadam V , Monyror J , Morales LC , Pink D , Rieger A M , Sipione S , Posse de Chaves E
Published: June 2021

Extracellular vesicles (EVs) are involved in a multitude of physiological functions and play important roles in health and disease. The study of EV secretion and EV characterization remains challenging due to the small size of these particles, a lack of universal EV markers, and sample loss or technical artifacts that are often associated with EV separation techniques. We developed a method for in-cell EV labeling with fluorescent lipids (DiI), followed by DiI-labelled EV characterization in the conditioned medium by imaging flow cytometry (IFC). Direct IFC analysis of EVs in the conditioned medium, after removal of apoptotic bodies and cellular debris, significantly reduces sample processing and loss compared to established methods for EV separation, resulting in improved detection of quantitative changes in EV secretion and subpopulations compared to protocols that rely on EV separation by ultracentrifugation. In conclusion, our optimized protocol for EV labeling and analysis reduces EV sample processing and loss, and is well suited for cell biology studies that focus on modulation of EV secretion by cells in culture.
Supervised Capacity Preserving Mapping: A Clustering Guided Visualization Method for scRNAseq data
Authors: Zhai Zhiqian , Lei Yu L. , Wang Rongrong , Xie Yuying
Published: June 2021

The rapid development of scRNA-seq technologies enables us to explore the transcriptome at the cell level in a large scale. Recently, various computational methods have been developed to analyze the scR-NAseq data such as clustering and visualization. However, current visualization methods including t-SNE and UMAP are challenged by the limited accuracy of rendering the geometic relationship of populations with distinct functional states. Most visualization methods are unsupervised, leaving out information from the clustering results or given labels. This leads to the inaccurate depiction of the distances between the bona fide functional states and the variance of clusters. We present supCPM, a robust supervised visualization method, which separates different clusters, preserves global structure, and tracks the cluster variance. Compared with six visualization methods using synthetic and real data sets, supCPM shows improved performance than other methods in preserving the global geometric structure and data variance. Overall, supCPM provides an enhanced visualization pipeline to assist the interpretation of functional transition and accurately depict population segregation.
Dynamical differential covariance recovers directional network structure in multiscale neural systems
Authors: Chen Yusi , Rosen Burke Q. , Sejnowski Terrence J.
Published: June 2021

Investigating neural interactions is essential to understanding the neural basis of behavior. Many statistical methods have been used for analyzing neural activity, but estimating the direction of network interactions correctly and efficiently remains a difficult problem (1). Here, we derive dynamical differential covariance (DDC), a new method based on dynamical network models that detects directional interactions with low bias and high noise tolerance under nonstationarity conditions. The method was first validated and compared with other methods on networks with false positive motifs and multiscale neural simulations where the ground truth connectivity was known. When applied to recordings of resting-state functional magnetic resonance imaging (rs-fMRI) recordings, DDC consistently detected regional interactions with strong structural connectivity in over 1,000 individual subjects obtained by diffusion MRI (dMRI). DDC is a promising new family of methods for estimating functional connectivity that can be generalized to a wide range of dynamical models and recording techniques and to other applications where system identification from sparse data is needed.

Significance Statement

Through dynamical interactions with each other, neurons make it possible for us to sense, move and think. It is now possible to simultaneously record from many individual neurons and brain regions. Methods for analyzing these large-scale recordings are needed that can reveal how the patterns of activity give rise to behavior. We developed an efficient, intuitive and robust way to analyze these recordings and validated it on simulations of model neural networks where the ground truth was known. We called this method dynamical differential covariance (DDC) because it can estimate not only the presence of a connection but also which direction the information is flowing in a network between neurons or cortical areas. We also successfully applied DDC to brain imaging data from functional Magnetic Resonance Imaging.
PTT-quant - a new method for direct identification and absolute quantification of premature transcription termination events, following the example of bacterial riboswitches
Authors: Machtel Piotr , Wasilewska-Burczyk Anna , Zacharjasz Julian , Bąkowska-Żywicka Kamilla
Published: June 2021

Regulation of gene expression by premature termination of transcription has been well described in all domains of life, including metazoans, yeast, plants and bacteria. Although methods for identification of such regulatory events by sequencing are available, the focused biochemical studies of the mechanism is hampered by lack of highly sensitive and accurate experimental methods. Here we propose a new method for absolute quantification of premature transcription termination events, PTT-quant. It is based on highly sensitive two-step digital droplet PCR protocol, coupled with normalized cDNA synthesis attained by site-specific pre-cleavage of investigated transcripts with RNase H. As a consequence, our method enables the reliable and sensitive quantification of both, prematurely terminated and full-length transcripts. By application of our method to investigation of transcriptional riboswitches in Bacillus subtilis, we were able to precisely measure the dynamics of SAM riboswitch induction, which turned to be ∼23% higher in comparison the results obtained without cDNA synthesis normalization.
On electrical spiking of Ganoderma resinaceum
Authors: Adamatzky Andrew , Gandia Antoni
Published: June 2021

Fungi exhibit action-potential like spiking activity. Up to date most electrical activity of oyster fungi has been characterised in sufficient detail. It remains unclear if there are any patterns of electrical activity specific only for a certain set of species or if all fungi share the same ‘language’ of electrical signalling. We use pairs of differential electrodes to record extracellular electrical activity of the antler-like sporocarps of the polypore fungus Ganoderma resinaceum. The patterns of the electrical activity are analysed in terms of frequency of spiking and parameters of the spikes. The indicators of the propagation of electrical activity are also highlighted.
Impact of genomic preselection on subsequent genetic evaluations with ssGBLUP - using real data from pigs
Authors: Jibrila Ibrahim , Vandenplas Jeremie , ten Napel Jan , Bergsma Rob , Veerkamp Roel F , Calus Mario P.L
Published: June 2021

Background

Empirically assessing the impact of preselection on subsequent genetic evaluations of preselected animals requires comparison of scenarios taking into account different approaches, including scenarios without preselection. However, preselection almost always takes place in animal breeding programs, so it is difficult to have a dataset without preselection. Hence most studies on preselection used simulated datasets, concluding that genomic estimated breeding values (GEBV) from subsequent single-step genomic best linear unbiased prediction (ssGBLUP) evaluations are unbiased. The aim of this study was to investigate the impact of genomic preselection (GPS) on accuracy and bias in subsequent ssGBLUP evaluations, using data from a commercial pig breeding program.

Methods

We used data on four pig production traits from one sire line and one dam line. The traits are average daily gain during performance testing, average daily gain throughout life, backfat thickness, and loin depth. As these traits had different weights in the breeding goals of the two lines, we analyzed the two lines separately. Per line, we had a reference GPS scenario which kept all available data, against which the next two scenarios were compared. We then implemented two other scenarios with additional layers of GPS by removing all animals without progeny either i) only in the validation generation, or ii) in all generations. We conducted subsequent ssGBLUP evaluations per GPS scenario, utilizing all the data remaining after implementing the GPS scenario. In computing accuracy and bias, we compared GEBV against progeny yield deviations of validation animals.

Results

Results for all traits in both lines showed marginal loss in accuracy due to the additional layers of GPS. Average accuracy across all GPS scenarios in both lines was 0.39, 0.47, 0.56, and 0.60 respectively for the four traits considered in this study. Bias was largely absent, and when present did not differ greatly among corresponding GPS scenarios.

Conclusion

As preselection generally has the same effect in animal breeding programs, we concluded that impact of preselection is generally minimal on accuracy and bias in subsequent ssGBLUP evaluations of selection candidates in pigs and in other animal breeding programs.
Do we really understand the role of the prefrontal cortex in placebo analgesia?
Authors: Frangos Eleni , Madian Nicholas , Wang Binquan , Bradson Megan L. , Gracely John L. , Richards Emily A. , Colloca Luana , Schweinhardt Petra , Bushnell M. Catherine , Ceko Marta
Published: June 2021

Several reviews have strongly implicated prefrontal cortical engagement in expectation-based placebo analgesia. We recently found a robust placebo analgesic response and associated decreases in pain-related cortical activations, without observable prefrontal engagement. We hypothesized our substantial conditioning and weak verbal instructions diminished expectation-related prefrontal activation. To test this, we examined the same subjects during a conditioning procedure, in which expectancy of pain relief was high. In two conditioning sessions, noxious heat was applied to a leg region treated with an “analgesic” cream and another treated with a “moisturizing” cream. In reality, both creams were inert, but the temperature applied to the moisturizing-cream area was 2°C higher than that applied to the analgesic-cream area.

Functional MRI was acquired during the second conditioning session. Pain ratings were lower for the low heat than the high heat, with corresponding reduced activations in pain-related regions. Similar to previous studies with strong expectation for pain relief, we observed more prefrontal activations during the “analgesic” than the control condition. Nevertheless, contrary to the idea of active prefrontal engagement, the relative activation was based on differences in negative BOLD signals. A literature review revealed that only a few studies conclusively showed active engagement of prefrontal cortex, i.e. increased positive BOLD signal during high expectation compared to a control, with variable timing and spatial-specificity. We suggest that this variability is due to the heterogeneous influence of cognitive, emotional and motivational factors. Future studies should attempt to unravel the multiple contributions to placebo responsiveness in the prefrontal cortex.
EcoEvoApps: Interactive Apps for Theoretical Models in Ecology and Evolutionary Biology
Authors: McGuire Rosa M. , Hayashi Kenji T. , Yan Xinyi , Caritá Vaz Marcel , Cinoğlu Damla , Cowen Madeline C. , Martínez-Blancas Alejandra , Sullivan Lauren L. , Vazquez-Morales Sheila , Kandlikar Gaurav S.
Published: June 2021

The integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology (EEB) is that theory is often developed and expressed in the form of mathematical models that can feel daunting and inaccessible for students and empiricists with variable quantitative training and attitudes towards math.

A promising way to make mathematical models more approachable is to embed them into interactive tools with which one can visually evaluate model structures and directly explore model outcomes through simulation.

To promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open-source (R/Shiny) apps that include model overviews, interactive model simulations, and code to implement these models directly in R. The package currently focuses on canonical models of population dynamics, species interaction, and landscape ecology. We also outline a vision and approach for growing the collection to include more models from across EEB.

These apps help illustrate fundamental results from theoretical ecology and can serve as valuable teaching tools in classroom settings. We present data from student surveys which show that students rate these apps as useful learning tools, and that using interactive apps leads to substantial gains in students’ interest and confidence in mathematical models. This points to the potential for interactive activities to make theoretical models more accessible to a wider audience, and thus facilitate the feedback between theory and data across ecology and evolutionary biology.
Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models
Authors: Patel Neel , Bush William S.
Published: June 2021

Background

Transcription factor(TF) interactions are known to regulate target gene(TG) expression in eukaryotes via TF regulatory modules(TRMs). Such interactions can be formed due to co-localizing TFs binding proximally to each other in the DNA sequence or over long distances between distally binding TFs via chromatin looping. While the former type of interaction has been characterized extensively, long distance TF interactions are still largely understudied. Furthermore, most prior approaches have focused on characterizing physical TF interactions without accounting for their effects on TG expression regulation. Understanding TRM based TG expression regulation could aid in understanding diseases caused by disruptions to these mechanisms. In this paper, we present a novel neural network based TRM detection approach that consists of using multi-omics TF based regulatory mechanism information to generate features for building non-linear multilayer perceptron TG expression prediction models in the GM12878 immortalized lymphoblastoid cells.

Results

We estimated main effects of 149 individual TFs and interaction effects of 48 distinct combinations of TFs forming TRMs based on their influence on TG expression. We identified several well-known and discovered multiple previously uncharacterized TF interactions within our detected set of TRMs. We further characterized the pairwise TRMs using long distance chromatin looping and motif co-occurrence data. We found that nearly all the TFs constituting TRMs detected by our approach interacted via chromatin looping, and that these TFs further interacted with promoters to influence TG expression through one of four possible regulatory configurations.

Conclusion

Here, we have provided a framework for detecting TRMs using neural network models containing multi-omics TF based regulatory features. We have also described these TRMs based on their regulatory potential along with presenting evidence for the possibility of TF interactions forming the TRMs occurring via chromatin looping.
Communication between the mediodorsal thalamus and prelimbic cortex regulates timing performance in rats
Authors: De Corte Benjamin J. , Heslin Kelsey A. , Cremers Nathan S. , Freeman John H. , Parker Krystal L.
Published: June 2021

Predicting when future events will occur and adjusting behavior accordingly is critical to adaptive behavior. Despite this, little is known about the brain networks that encode time and how this ultimately impacts decision-making. One established finding is that the prefrontal cortex (PFC) and its non-human analogues (e.g., the rodent prelimbic cortex; PL) mediate timing. This provides a starting point for exploring the networks that support temporal processing by identifying areas that interact with the PFC during timing tasks. For example, substantial work has explored the role of frontostriatal circuits in timing. However, other areas are undoubtedly involved. The mediodorsal nucleus of the thalamus (MD) is an excellent candidate region. It shares dense, reciprocal connections with PFC-areas in both humans and non-human species and is implicated in cognition. However, causal data implicating MD-PFC interactions in cognition broadly is still sparse, and their role in timing specifically is currently unknown. To address this, we trained male rats on a time-based, decision-making task referred to as the ‘peak-inter- val’ procedure. During the task, presentation of a cue instructed the rats to respond after a specific interval of time elapsed (e.g., tone-8 seconds). We incorporated two cues; each requiring a response after a distinct time-interval (e.g., tone-8 seconds / light-16 seconds). We tested the effects of either reversibly inactivating the MD or PL individually or functionally disconnecting them on performance. All manipulations caused a comparable timing deficit. Specifically, responses showed little organization in time, as if primarily guided by motivational systems. These data expand our understanding of the networks that support timing and suggest that MD-PL interactions specifically are a core component. More broadly, our results suggest that timing tasks provide a reliable assay for characterizing the role of MD-PL interactions in cognition using rodents, which has been difficult to establish in the past.
Economic Choices under Simultaneous or Sequential Offers Rely on the Same Neural Circuit
Authors: Shi Weikang , Ballesta Sébastien , Padoa-Schioppa Camillo
Published: June 2021

A series of studies in which monkeys chose between two juices offered in variable amounts identified in the orbitofrontal cortex (OFC) different groups of neurons encoding the value of individual options (offer value), the binary choice outcome (chosen juice) and thechosen value. These variables capture both the input and the output of the choice process, suggesting that the cell groups identified in OFC constitute the building blocks of a decision circuit. Several lines of evidence support this hypothesis. However, in previous experiments offers were presented simultaneously, raising the question of whether current notions generalize to when goods are presented or are examined in sequence. Recently, Ballesta and Padoa-Schioppa (2019) examined OFC activity under sequential offers. An analysis of neuronal responses across time windows revealed that a small number of cell groups encoded specific sequences of variables. These sequences appeared analogous to the variables identified under simultaneous offers, but the correspondence remained tentative. Thus in the present study we examined the relation between cell groups found under sequential versus simultaneous offers. We recorded from the OFC while monkeys chose between different juices. Trials with simultaneous and sequential offers were randomly interleaved in each session. We classified cells in each choice modality and we examined the relation between the two classifications. We found a strong correspondence – in other words, the cell groups measured under simultaneous offers and under sequential offers were one and the same. This result indicates that economic choices under simultaneous or sequential offers rely on the same neural circuit.

Significance Statement

Research in the past 20 years has shed light on the neuronal underpinnings of economic choices. A large number of results indicates that decisions between goods are formed in a neural circuit within the orbitofrontal cortex (OFC). In most previous studies, subjects chose between two goods offered simultaneously. Yet, in daily situations, goods available for choice are often presented or examined in sequence. Here we recorded neuronal activity in the primate OFC alternating trials under simultaneous and under sequential offers. Our analyses demonstrate that the same neural circuit supports choices in the two modalities. Hence current notions on the neuronal mechanisms underlying economic decisions generalize to choices under sequential offers.
A compendium of novel genomics technologies provides a chromosome-scale assembly and insights into the sex determining system of the Greenland Halibut
Authors: Ferchaud A-L , Mérot C , Normandeau E , Ragoussis I , Babin C , Djambazian H , Bérubé P , Audet C , Treble M , Walkusz W , Bernatchez L
Published: June 2021

Despite the commercial importance of Greenland Halibut (Reinhardtius hippoglossoides), important gaps still persist in our knowledge of this species, including its reproductive biology and sex determination mechanism. In this study, we combined single molecule sequencing of long reads (Pacific Sciences) with Chromatin Conformation Capture sequencing (Hi-C) data to provide the first chromosome-level genome reference for this species. The high-quality assembly encompassed more than 598 Megabases (Mb) assigned to 1 594 scaffolds (scaffold N50 = 25 Mb) with 96 % of its total length distributed among 24 chromosomes. The investigation of its syntenic relationships with other economically important flatfish species revealed a high conservation of synteny blocks among members of this phylogenetic clade. Sex determination analysis revealed that flatfishes do not escape the rule applied to other teleost fish and exhibit a high level of plasticity and turnover in sex-determination mechanisms. A whole-genome sequence analysis of 198 individuals allowed us to draw a full picture of the molecular sex determination (SD) system for Greenland Halibut, revealing that this species possesses a very nascent male heterogametic XY system, with a putative major effect of the sox2 gene, also described as the main SD driver in two other flatfishes. Interestingly, our study also suggested for the first time in flatfishes that a putative Y-autosomal fusion could be associated with a reduction of recombination typical of early steps of sex chromosome evolution.
The percentage of Monocytes CD39+ is higher in Pregnant COVID-19 than in Non-Pregnant COVID-19 patients
Authors: Cérbulo-Vázquez A. , García-Espinosa M. , Briones-Garduño J.C. , Arriaga-Pizano L. , Ferat-Osorio E. , Zavala-Barrios B. , Cabrera-Rivera G.L. , Miranda-Cruz P. , García de la Rosa M.T. , Prieto-Chávez J.L. , Rivero-Arredondo V. , Madera-Sandoval R.L. , Cruz-Cruz A. , Salazar-Rios E. , Salazar-Rios ME , Serrano-Molina D , De Lira-Barraza R. C. , Villanueva-Compean A. H. , Esquivel-Pineda A. , Ramirez-Montes de Oca R. , Caldiño-Soto F. , Ramírez-García L.A. , Flores-Padilla G. , Moreno-Álvarez O. , Guerrero-Avendaño GML , López-Macías C.
Published: June 2021

Current medical guidelines consider COVID-19 pregnant women a high-risk group. Physiological gestation down regulates the immunological response to maintain “maternal-fetal tolerance”; hence, a SARS-CoV-2 infection constitutes a potentially threatening condition to both the mother and the fetus. To establish the immune profile in pregnant COVID-19+ patients a cross-sectional study was conducted. Leukocyte immunophenotype, mononuclear leukocyte response to polyclonal stimulus and cytokine/chemokine serum concentration were analyzed in pregnant fifteen COVID-19+ and control groups (fifteen non-pregnant COVID-19+, and thirteen pregnant COVID-19-women). Pregnant COVID-19+ patients exhibit lower percentages of monocytes HLA-DR+ compared with control groups. Nevertheless, pregnant COVID-19+ women show a higher percentage of monocytes CD39+ than controls. Furthermore, a higher concentration of TNF-α, IL-6, MIP1b and IL-4 was observed within the pregnant COVID-19+ group. Our result shows that pregnant women express immunological characteristics that potentially mediate the immune response in COVID-19.
Phylogenetic study of thermophilic genera Anoxybacillus, Geobacillus, Parageobacillus, and proposal of a new classification Quasigeobacillus gen. nov
Authors: Talamantes-Becerra Berenice , Carling Jason , Blom Jochen , Georges Arthur
Published: June 2021

A phylogenetic study of Anoxybacillus, Geobacillus and Parageobacillus was performed using publicly available whole genome sequences. A total of 113 genomes were selected for phylogenomic metrics including calculation of Average Nucleotide Identity (ANI) and Average Amino acid Identity (AAI), and a maximum likelihood tree was built from alignment of a set of 662 orthologous core genes. The combined results from the core gene tree and ANI and AAI dendrograms show that the genomes split into two main clades, clade I containing all Geobacillus, all Parageobacillus and some species of Anoxybacillus, and clade II, containing the majority of Anoxybacillus species. Clade I is further partitioned into three clades, consisting separately of Geobacillus, Parageobacillus, and a third clade which we suggest should be elevated to a new genus Quasigeobacillus gen. nov. Two species of Anoxybacillus showed inconsistent positioning among the trees produced by differing methods and could not be clearly resolved into any of the three existing genera or the new genus. This research shows the importance of considering closely related genera together when studying phylogeny or assigning genomic affinities.
Robust Brain State Decoding using Bidirectional Long Short Term Memory Networks in functional MRI
Authors: Mittal Anant , Aggarwal Priya , Pessoa Luis , Gupta Anubha
Published: June 2021

Decoding brain states of the underlying cognitive processes via learning discriminative feature representations has recently gained a lot of interest in brain imaging studies. Particularly, there has been an impetus to encode the dynamics of brain functioning by analyzing temporal information available in the fMRI data. Long-short term memory (LSTM), a class of machine learning model possessing a “memory” component, is increasingly being observed to perform well in various applications with dynamic temporal behavior, including brain state decoding. Because of the dynamics and inherent latency in fMRI BOLD responses, future temporal context is crucial. However, it is neither encoded nor captured by the conventional LSTM model. This paper performs robust brain state decoding via information encapsulation from both the past and future instances of fMRI data via bi-directional LSTM. This allows for explicitly modeling the dynamics of BOLD response without any delay adjustment. The two hidden activations of forward and reverse directions in bi-LSTM are collated to build the “memory” of the model and are used to robustly predict the brain states at every time instance. Working memory data from the Human Connectome Project (HCP) is utilized for validation and was observed to perform 18% better than it’s unidirectional counterpart in terms of accuracy in predicting the brain states.
Flexible seed size enables ultra-fast and accurate read alignment
Authors: Sahlin Kristoffer
Published: June 2021

Read alignment to genomes is a fundamental computational step used in many bioinformatic analyses, and often, it is the computational bottleneck. Therefore, it is desirable to perform the alignment step as fast as possible without compromising accuracy. Most alignment algorithms consider a seed-and-extend approach, where the time-consuming seeding step identifies and decides on candidate mapping locations. Recently, several advances have been made on seeding methods for fast sequence comparison.

We combine two such methods, syncmers and strobemers, in a novel seeding approach for constructing dynamic-sized fuzzy seeds and implement the method in a short-read aligner, strobealign. Firstly, we show that our seeding is fast to construct and effectively reduces repetitiveness in the seeding step using a novel metric E-hits. Secondly, we benchmark strobealign to traditional and recently proposed aligners on simulated and biological data and show that strobealign is several times faster than traditional aligners such as BWA and Bowtie2 at similar and sometimes higher accuracy while being both faster and more accurate than more recently proposed aligners. Our aligner can free up substantial time and computing resources needed for read alignment in many pipelines.

Availability

https://github.com/ksahlin/strobealign.
Requirement for an Otopetrin-Like protein for acid taste in Drosophila
Authors: Ganguly Anindya , Chandel Avinash , Turner Heather , Wang Shan , Liman Emily R. , Montell Craig
Published: June 2021

Many of the Drosophila receptors required for bitter, sugar and other tastes have been identified. However, the receptor required for the taste of acid has been elusive. In Drosophila, the major families of taste receptors, such as “Gustatory Receptors” and “Ionotropic Receptors” are unrelated to taste receptors in mammals. Previous work indicated that members of these major families do not appear to be broadly required acid sensors. Here, to identify the enigmatic acid taste receptor, we interrogated three genes encoding proteins distantly related the mammalian Otopertrin1 proton channel. We found that RNAi knockdown or mutation of Otopetrin-Like A (OtopLA) by CRISPR/Cas9, severely impairs the behavioral rejection of sugary foods laced with HCl or carboxylic acids. Mutation of OtopLA also greatly reduces acid-induced action potentials. We identified an isoform of OtopLA that was expressed in the proboscis and was sufficient to restore acid sensitivity to OtopLA mutant flies. OtopLA functioned in acid taste in a subset of bitter-activated gustatory receptor neurons that senses protons. This work highlights an unusual functional conservation of a receptor required for a taste modality in flies and mammals.