bluuebunny/crossref_metadata_2025 huggingface dataset:
SR Ca2+ handling in unbranched, immediately post-necrotic fast-twitch mdx fibres is similar to wt littermates
Authors: Chan Stephen , Kueh Sindy L. L. , Morley John W. , Head Stewart I.
Published: December 2021

There is a lack of consensus in the literature regarding the effects of dystrophin deficiency on the Ca2+-handling properties of the SR in mdx mice, an animal model of Duchenne muscular dystrophy. One possible reason for this is that only a few studies control for the presence of branched fibres. Fibre branching, a consequence of degenerative-regenerative processes such as muscular dystrophy, has in itself a significant influence on the function of the SR. In our present study we attempt to detect early effects of dystrophin deficiency on SR Ca2+ handling by using unbranched fibres from the immediate post-necrotic stage in mdx mice (just regenerated following massive necrosis). Using kinetically-corrected Fura-2 fluorescence signals measured during twitch and tetanus, we analysed the amplitude, rise time and decay time of Δ[Ca2+]i in unfatigued and fatigued fibres. Decay was also resolved into SR pump and SR leak components. Fibres from mdx mice were similar in all respects to fibres from wt littermates apart from: (i) a longer rise time and slower rate of rise of [Ca2+]i during a tetanus; and (ii) a mitigation of the fall in Δ[Ca2+]i amplitude during the course of fatigue. Our findings suggest that the early effects of a loss of dystrophin on SR Ca2+ handling are only slight, and differ from the widely held view that there is significant Ca2+ pathology in mdx mice. It may be that Ca2+ pathology is magnified by progressive branching and degeneration.

New findings

Central question: What are the early effects of dystrophin deficiency on SR Ca2+ handling in the mdx mouse?

Main finding: In the mdx mouse, Ca2+ handling by the SR is little affected by the absence of dystrophin when looking at fibres without branches that have just regenerated following massive myonecrosis. This has important implications for the traditional view that Ca2+ pathology is significant in the mdx mouse.
Proteomics Indicates Lactate Dehydrogenase is Prognostic in Acetaminophen-induced Acute Liver Failure Patients and Reveals a Role for LKB1-AMPK Signaling
Authors: Vazquez Joel H. , Kennon-McGill Stefanie , Byrum Stephanie D. , Mackintosh Samuel G. , Jaeschke Hartmut , Williams D. Keith , Lee William M. , Dranoff Jonathan A. , McGill Mitchell R. ,   Acute Liver Failure Study Group
Published: December 2021

Better biomarkers to predict death early in acute liver failure (ALF) are needed. To that end, we obtained early (study day 1) and later (day 3) serum samples from transplant-free survivors (n=28) and non-survivors (n=30) of acetaminophen (APAP)-induced ALF from the NIH-sponsored Acute Liver Failure Study Group, and from control volunteers (n=10). To identify proteins that increase early in serum during ALF, we selected individuals from this cohort for whom ALT was lower on day 1 than day 3, indicating a time point before the peak of injury (n=10/group). We then performed untargeted proteomics on their day 1 samples. Out of 1,682 quantifiable proteins, 79 were elevated ≥4-fold in ALF patients vs. controls and 23 of those were further elevated ≥4-fold in non-survivors vs. survivors, indicating potential to predict death. Interestingly, the biomarker with best performance was LDH. To confirm the prognostic potential of LDH, we measured activity in all day 1 and 3 samples from all 58 ALF patients. LDH was elevated in the non-survivors vs. survivors on both days. In addition, receiver operating characteristic (ROC) curve analyses revealed that LDH alone performed similarly to the model for end-stage liver disease (MELD), while a combination of MELD and LDH outperformed either alone. Finally, Upstream Analysis of our proteomics data indicated activation of LKB1-AMPK signaling in liver regeneration after APAP overdose and we confirmed that in mice. Overall, we conclude LDH can predict death in APAP-induced ALF and that LKB1-AMPK signaling may be a promising therapeutic target to improve survival.
Machine learning for prediction of immunotherapy efficacy in non-small cell lung cancer from simple clinical and biological data
Authors: Benzekry Sébastien , Grangeon Mathieu , Karlsen Mélanie , Alexa Maria , Bicalho-Frazeto Isabella , Chaleat Solène , Tomasini Pascale , Barbolosi Dominique , Barlesi Fabrice , Greillier Laurent
Published: December 2021

Background

Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.

Methods

Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.

Results

Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3 % and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p<0.0001; OR 1.8, p<0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophils-to-lymphocytes ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03.

Conclusion

Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

Highlights

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Machine learning applied to a large set of NSCLC patients could predict efficacy of immunotherapy with a 69% accuracy using simple routine data

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Hemoglobin levels and performance status were the strongest predictors and significantly associated with DCR, PFS and OS

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Neutrophils-to-lymphocyte ratio was also associated with outcome

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Benchmark of 8 machine learning models
Network Assisted Analysis ofDe NovoVariants Using Protein-Protein Interaction Information Identified 46 Candidate Genes for Congenital Heart Disease
Authors: Xie Yuhan , Jiang Wei , Dong Weilai , Li Hongyu , Jin Sheng Chih , Brueckner Martina , Zhao Hongyu
Published: December 2021

De novovariants (DNVs) with deleterious effects have proved informative in identifying risk genes for early-onset diseases such as congenital heart disease (CHD). A number of statistical methods have been proposed for family-based studies or case/control studies to identify risk genes by screening genes with more DNVs than expected by chance in Whole Exome Sequencing (WES) studies. However, the statistical power is still limited for cohorts with thousands of subjects. Under the hypothesis that connected genes in protein-protein interaction (PPI) networks are more likely to share similar disease association status, we develop a Markov Random Field model that can leverage information from publicly available PPI databases to increase power in identifying risk genes. We identified 46 candidate genes with at least 1 DNV in the CHD study cohort, including 18 known human CHD genes and 35 highly expressed genes in mouse developing heart. Our results may shed new insight on the shared protein functionality among risk genes for CHD.
Single-cell physical phenotyping of mechanically dissociated tissue biopsies for fast diagnostic assessment
Authors: Soteriou Despina , Kubánková Markéta , Schweitzer Christine , López-Posadas Rocío , Pradhan Rashmita , Thoma Oana-Maria , Györfi Andrea-Hermina , Matei Alexandru-Emil , Waldner Maximilian , Distler Jörg H. W. , Scheuermann Stefan , Langejürgen Jens , Schneider-Stock Regine , Atreya Raja , Neurath Markus F. , Hartmann Arndt , Guck Jochen
Published: December 2021

Rapid and accurate histopathological diagnosis during surgery is critical for clinical decision-making. The prevalent method of intraoperative consultation pathology is time, labour and cost intensive and requires the expertise of trained pathologists. Here, we present an alternative technique for the rapid, label-free analysis of biopsy samples by sequentially assessing the physical phenotype of singularized, suspended cells in high-throughput. This new diagnostic pipeline combines enzyme-free, mechanical dissociation of tissues with real-time deformability cytometry at measurement rates of 100 – 1,000 cells/sec, and machine learning-based analysis. We show that physical phenotype parameters extracted from brightfield images of single cells can be used to distinguish subpopulations of cells in various tissues, without prior knowledge or the need for molecular markers. Further, we demonstrate the potential of our method for inflammatory bowel disease diagnostics. Using unsupervised dimensionality reduction and logistic regression, we accurately differentiate between healthy and tumorous tissue in both mouse and human biopsy samples. The method delivers results within 30 minutes, laying the groundwork for a fast and marker-free diagnostic pipeline to detect pathological changes in solid biopsies.
Accessibility of Canadian COVID-19 Testing Locations for People with Disabilities During the Third Wave of the COVID-19 Pandemic
Authors: Rotenberg Sara , Cooper Jane , Downer Matthew B.
Published: December 2021

Background

Canadians with disabilities make up nearly a quarter of the population yet face barriers in accessing information about COVID-19 testing accessibility across the country.

Objective

No known studies evaluate the online information about the accessibility of COVID-19 testing locations. This study aimed to understand the accessibility of COVID-19 testing sites in Canada based on online information in March 2021.

Methods

Key accessibility features were identified to evaluate COVID-19 testing websites information on accessibility and data were extracted from the website to simulate the user experience of booking a COVID-19 test.

Results

All provinces and territories provided minimal accessibility information on their COVID-19 testing websites, except for Ontario. Out of 170 testing locations in Ontario, few had information about accessibility, with only 8.2% listing at least 3 of the 5 key accessibility features measured on their websites.

Conclusions

This paper demonstrates that more than a year into the pandemic, there existed a clear lack of accessibility information for Canadian testing locations for people with disabilities.
Cytolysin-positive Enterococcus faecalis is elevated in patients with chronic alcoholic pancreatitis
Authors: Perrin Clara , Rebours Vinciane , Trainel Nicolas , Voican Cosmin Sebastian , Perlemuter Gabriel , Cassard Anne-Marie , Ciocan Dragos
Published: December 2021

Introduction

Patients with alcoholic hepatitis have an increase in cytolysin-producing Enterococcus faecalis that correlates with disease severity and mortality.

Aim

To determine whether patients with chronic alcoholic pancreatitis have an elevated abundance of cytolysin-producing E. faecalis.

Methods

Quantification by qPCR of cytolysin-producing E. faecalis in controls and patients with alcoholic hepatitis or pancreatitis.

Results

Patients with alcoholic pancreatitis had a higher proportion of intestinal cytolysin-positive E. faecalis than healthy controls and patients with alcoholic hepatitis.

Conclusion

Cytolytic E. faecalis may also be involved in this other alcohol-related complication and benefit from targeted microbiota editing strategies.
AP2/ERF transcription factor NbERF-IX-33 is involved in the regulation of phytoalexin production for the resistance ofNicotiana benthamianatoPhytophthora infestans
Authors: Imano Sayaka , Fushimi Mayuka , Camagna Maurizio , Tsuyama-Koike Akiko , Mori Hitoshi , Ashida Akira , Tanaka Aiko , Sato Ikuo , Chiba Sotaro , Kawakita Kazuhito , Ojika Makoto , Takemoto Daigo
Published: December 2021

Plants recognize molecular patterns unique to a certain group of microbes to induce effective resistance mechanisms. Elicitins are secretory proteins produced by plant pathogenic oomycete genera includingPhytophthoraandPythium. Treatment of INF1 (an elicitin produced byP. infestans) induces a series of defense responses inNicotianaspecies, including reactive oxygen species (ROS) production, transient induction of ethylene production, hypersensitive cell death and accumulation of the sesquiterpenoid phytoalexin capsidiol. In this study, we analyzed the expression profiles ofN. benthamianagenes after INF1 treatment by RNAseq analysis. Based on their expression patterns,N. benthamianagenes were categorized into 20 clusters and 4,761 (8.3%) out of 57,140 genes were assigned to the clusters for INF1-induced genes. All genes encoding enzymes dedicated to capsidiol production, 5-epi-aristolochene (EA) synthase (NbEAS, 10 copies) and EA dehydrogenase (NbEAH, 6 copies), and some genes for ethylene production, such as 1-aminocyclopropane 1-carboxylate (ACC) synthase (NbACS) and ACC oxidase (NbACO), were significantly upregulated by INF1 treatment. Analysis ofNbEAS1andNbEAS4promoters revealed that AGACGCC (GCC box-like motif) is the essential cis-element required for INF1-induced expression ofNbEASgenes. Given that the GCC box is known to be targeted by ERF (ethylene-responsive factor) transcription factors, we created a complete list ofN. benthamianagenes encoding AP2/ERF family transcription factors, and identified 45 out of 337AP2/ERFgenes in the clusters for INF1-induced genes. Among INF1-inducedNbERFgenes, silencing ofNbERF-IX-33compromised resistance againstP. infestansand INF1-induced production of capsidiol. Recombinant NbERF-IX-33 protein can bind to the promoter sequence ofNbEAS4, suggesting that NbERF-IX-33 is a transcription factor directly regulating the expression of genes for phytoalexin production.
Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain
Authors: Hansen Justine Y. , Markello Ross D. , Tuominen Lauri , Nørgaard Martin , Kuzmin Elena , Palomero-Gallagher Nicola , Dagher Alain , Misic Bratislav
Published: December 2021

Neurotransmitter receptors modulate the signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression is often used as a proxy for receptor densities. In the present report, we comprehensively test the expression-density association for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT1A, D2, CB1, and MOR). These expression-density associations are related to population variance and change across different classes of laminar differentiation. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function.
A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution
Authors: Grau-Bové Xavier , Navarrete Cristina , Chivas Cristina , Pribasnig Thomas , Antó Meritxell , Torruella Guifré , Galindo Luis Javier , Lang Bernd Franz , Moreira David , López-Garcia Purificación , Ruiz-Trillo Iñaki , Schleper Christa , Sabidó Eduard , Sebé-Pedrós Arnau
Published: December 2021

Histones and associated chromatin proteins have essential functions in eukaryotic genome organization and regulation. Despite this fundamental role in eukaryotic cell biology, we lack a phylogenetically-comprehensive understanding of chromatin evolution. Here, we combine comparative proteomics and genomics analysis of chromatin in eukaryotes and archaea. Proteomics uncovers the existence of histone post-translational modifications in Archaea. However, archaeal histone modifications are scarce, in contrast with the highly conserved and abundant marks we identify across eukaryotes. Phylogenetic analysis reveals that chromatin-associated catalytic functions (e.g., methyltransferases) have pre-eukaryotic origins, whereas histone mark readers and chaperones are eukaryotic innovations. We show that further chromatin evolution is characterized by expansion of readers, including capture by transposable elements and viruses. Overall, our study infers detailed evolutionary history of eukaryotic chromatin: from its archaeal roots, through the emergence of nucleosome-based regulation in the eukaryotic ancestor, to the diversification of chromatin regulators and their hijacking by genomic parasites.
Stimulus dependence of theta rhythmic activity in primate V1 and its potential relevance for visual perception
Authors: Fanyiwi Prasakti Tenri , Agayby Beshoy , Kienitz Ricardo , Haag Marcus , Schmid Michael C.
Published: December 2021

A growing body of psychophysical research reports theta (3-8 Hz) rhythmic fluctuations in visual perception that are often attributed to an attentional sampling mechanism arising from theta rhythmic neural activity in mid- to high-level cortical association areas. However, it remains unclear to what extent such neuronal theta oscillations might already emerge at early sensory cortex like the primary visual cortex (V1), e.g. from the stimulus filter properties of neurons. To address this question, we recorded multi-unit neural activity from V1 of two macaque monkeys viewing a static visual stimulus with variable sizes, orientations and contrasts. We found that among the visually responsive electrode sites, more than 50 % showed a spectral peak at theta frequencies. Theta power varied with varying basic stimulus properties. Within each of these stimulus property domains (e.g. size), there was usually a single stimulus value that induced the strongest theta activity. In addition to these variations in theta power, the peak frequency of theta oscillations increased with increasing stimulus size and also changed depending on the stimulus position in the visual field. Further analysis confirmed that this neural theta rhythm was indeed stimulus-induced and did not arise from small fixational eye movements (microsaccades). When the monkeys performed a detection task of a target embedded in a theta-generating visual stimulus, reaction times also tended to fluctuate at the same theta frequency as the one observed in the neural activity. The present study shows that a highly stimulus-dependent neuronal theta oscillation can be elicited in V1 that appears to influence the temporal dynamics of visual perception.
Chronic adolescent exposure to cannabis in mice leads to sex-biased changes in gene expression networks across brain regions
Authors: Zuo Yanning , Iemolo Attilio , Montilla-Perez Patricia , Li Hai-Ri , Yang Xia , Telese Francesca
Published: December 2021

During adolescence, frequent and heavy cannabis use can lead to serious adverse health effects and cannabis use disorders (CUD). Rodent models of adolescent exposure to the main psychoactive component of cannabis, delta-9-tetrahydrocannabinol (THC), mimic the behavioral alterations observed in adolescent users. However, the underlying molecular mechanisms remain largely unknown. Here, we treated female and male mice with high doses of THC during early adolescence and assessed their memory and social behaviors in late adolescence. We then profiled the transcriptome of five brain regions involved in cognitive and addiction-related processes. We applied gene coexpression network analysis and identified gene coexpression modules, termed cognitive modules, that simultaneously correlated with THC treatment and memory traits reduced by THC. The cognitive modules were related to endocannabinoid signaling in the female dorsal medial striatum, inflammation in the female ventral tegmental area, and synaptic transmission in the male nucleus accumbens. Moreover, cross-brain region module-module interaction networks uncovered intra- and inter-region molecular circuitries influenced by THC. Lastly, we identified key driver genes of gene networks associated with THC in mice and genetic susceptibility to CUD in humans. This analysis revealed a common regulatory mechanism linked to CUD vulnerability in the nucleus accumbens of females and males, which shared four key drivers (Hapln4, Kcnc1, Elav12, Zcchc12). These genes regulate transcriptional subnetworks implicated in addiction processes, synaptic transmission, brain development, and lipid metabolism. Our study provides novel insights into disease mechanisms regulated by adolescent exposure to THC in a sex- and brain region-specific manner.
SARS-CoV-2 variants impact RBD conformational dynamics and ACE2 accessibility
Authors: Valério Mariana , Borges-Araújo Luís , Melo Manuel N. , Lousa Diana , Soares Cláudio M.
Published: December 2021

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed over 5 million people and is causing a devastating social and economic impact all over the world. The rise of new variants of concern (VOCs) represents a difficult challenge due to the loss vaccine and natural immunity, and increased transmissibility. All circulating VOCs contain mutations in the spike glycoprotein, which mediates fusion between the viral and host cell membranes, via its receptor binding domain (RBD) that binds to angiotensin-converting enzyme 2 (ACE2). In an attempt to understand the effect of RBD mutations in circulating VOCs, a lot of attention has been given to the RBD-ACE2 interaction. However, this type of analysis is limited, since it ignores more indirect effects, such as the conformational dynamics of the RBD itself. Observing that some VOCs mutations occur in residues that are not in direct contact with ACE2, we hypothesized that they could affect RBD conformational dynamics. To test this, we performed long atomistic (AA) molecular dynamics (MD) simulations to investigate the structural dynamics of wt RBD, and that of three circulating VOCs (alpha, beta, and delta). Our results show that in solution, wt RBD presents two distinct conformations: an “open” conformation where it is free to bind ACE2; and a “closed” conformation, where the RBM ridge blocks the binding surface. The alpha and beta variants significantly impact the open/closed equilibrium, shifting it towards the open conformation by roughly 20%. This shift likely increases ACE2 binding affinity. Simulations of the currently predominant delta variant RBD were extreme in this regard, in that a closed conformation was never observed. Instead, the system alternated between the before mentioned open conformation and an alternative “reversed” one, with a significantly changed orientation of the RBM ridge flanking the RBD. This alternate conformation could potentially provide a fitness advantage not only due to increased availability for ACE2 binding, but also by aiding antibody escape through epitope occlusion. These results support the hypothesis that VOCs, and particularly the delta variant, impact RBD conformational dynamics in a direction that simultaneously promotes efficient binding to ACE2 and antibody escape.
Temporally stable beta sensorimotor oscillations and cortico–muscular coupling underlie force steadiness
Authors: Mongold Scott J. , Piitulainen Harri , Legrand Thomas , Ghinst Marc Vander , Naeije Gilles , Jousmäki Veikko , Bourguignon Mathieu
Published: December 2021

As humans, we seamlessly hold objects in our hands, and may even lose consciousness of these objects. This phenomenon raises the unsettled question of the involvement of the cerebral cortex, the core area for voluntary motor control, in dynamically maintaining steady muscle force. To address this issue, we measured magnetoencephalographic brain activity from healthy adults who maintained a steady pinch grip. Using a novel analysis approach, we uncovered fine-grained temporal modulations in the ∼20-Hz sensorimotor brain rhythm and its coupling with muscle activity, with respect to several aspects of muscle force (rate of increase/decrease or plateauing high/low). These modulations preceded changes in force features by ∼40 ms and possessed behavioral relevance, as less salient or absent modulation predicted a more stable force output. These findings have consequences for the existing theories regarding the functional role of cortico-muscular coupling, and suggest that steady muscle contractions are characterized by a stable rather than fluttering involvement of the sensorimotor cortex.
Multiscale and extended retrieval of associative memory structures in a cortical model of local-global inhibition balance
Authors: Burns Thomas F , Haga Tatsuya , Fukai Tomoki
Published: December 2021

Inhibitory neurons take on many forms and functions. How this diversity contributes to memory function is not completely known. Previous formal studies indicate inhibition differentiated by local and global connectivity in associative memory networks functions to rescale the level of retrieval of excitatory assemblies. However, such studies lack biological details such as a distinction between types of neurons (excitatory and inhibitory), unrealistic connection schemas, and non-sparse assemblies. In this study, we present a rate-based cortical model where neurons are distinguished (as excitatory, local inhibitory, or global inhibitory), connected more realistically, and where memory items correspond to sparse excitatory assemblies. We use this model to study how local-global inhibition balance can alter memory retrieval in associative memory structures, including naturalistic and artificial structures. Experimental studies have reported inhibitory neurons and their sub-types uniquely respond to specific stimuli and can form sophisticated, joint excitatory-inhibitory assemblies. Our model suggests such joint assemblies, as well as a distribution and rebalancing of overall inhibition between two inhibitory sub-populations – one connected to excitatory assemblies locally and the other connected globally – can quadruple the range of retrieval across related memories. We identify a possible functional role for local-global inhibitory balance to, in the context of choice or preference of relationships, permit and maintain a broader range of memory items when local inhibition is dominant and conversely consolidate and strengthen a smaller range of memory items when global inhibition is dominant. This model therefore highlights a biologically-plausible and behaviourally-useful function of inhibitory diversity in memory.
An experimental test of chronic traffic noise exposure on parental behaviour and reproduction in zebra finches
Authors: Liu Quanxiao , Gelok Esther , Fontein Kiki , Slabbekoorn Hans , Riebel Katharina
Published: December 2021

Chronic traffic noise is increasingly recognised as a potential hazard to wildlife. Several songbird species have been shown to breed poorly in traffic noise exposed habitats. However, identifying whether noise is causal in this requires experimental approaches. We tested whether experimental exposure to chronic traffic noise affected parental behaviour and reproductive success in zebra finches (Taeniopygia guttata). In a counterbalanced repeated-measures design, breeding pairs were exposed to continuous playback of one of two types of highway noise previously shown to be either neutral (control) or aversive. Parental nest attendance positively correlated with feeding effort and was higher for the aversive than the control sound and this effect was more pronounced for parents attending larger broods. However, neither noise condition affected offspring number, growth or body mass. The absence of an effect held when we combined our data with data from two other comparable studies into a meta-analysis. We discuss whether the increased nest attendance could be a compensatory strategy that alleviated detrimental noise effects on the chicks, and whether it could be caused by impaired parent-offspring or within-pair communication. Future work should test these hypotheses and investigate potential long-term costs of increased parental engagement.
Broad human and animal coronavirus neutralisation by SARS-CoV-2 S2-targeted vaccination
Authors: Ng Kevin W. , Faulkner Nikhil , Finsterbusch Katja , Wu Mary , Harvey Ruth , Hussain Saira , Greco Maria , Liu Yafei , Kjaer Svend , Swanton Charles , Gandhi Sonia , Beale Rupert , Gamblin Steve J. , Cherepanov Peter , McCauley John , Daniels Rodney , Howell Michael , Arase Hisashi , Wack Andeas , Bauer David L.V. , Kassiotis George
Published: December 2021

Several common-cold coronaviruses (HCoVs) are endemic in humans and several variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged during the current Coronavirus disease 2019 (COVID-19) pandemic. Whilst antibody cross-reactivity with the Spike glycoproteins (S) of diverse coronaviruses has been documented, it remains unclear whether such antibody responses, typically targeting the conserved S2 subunit, contribute to or mediate protection, when induced naturally or through vaccination. Using a mouse model, we show that prior HCoV-OC43 S immunity primes neutralising antibody responses to otherwise subimmunogenic SARS-CoV-2 S exposure and promotes S2-targeting antibody responses. Moreover, mouse vaccination with SARS-CoV-2 S2 elicits antibodies that neutralise diverse animal and human alphacoronaviruses and betacoronaviruses in vitro, and protects against SARS-CoV-2 challenge in vivo. Lastly, in mice with a history of SARS-CoV-2 Wuhan-based S vaccination, further S2 vaccination induces stronger and broader neutralising antibody response than booster Wuhan S vaccination, suggesting it may prevent repertoire focusing caused by repeated homologous vaccination. The data presented here establish the protective value of an S2-targeting vaccine and support the notion that S2 vaccination may better prepare the immune system to respond to the changing nature of the S1 subunit in SARS-CoV-2 variants of concern (VOCs), as well as to unpredictable, yet inevitable future coronavirus zoonoses.
The effects of probabilistic context inference on motor adaptation
Authors: Dario Cuevas Rivera , Stefan Kiebel
Published: December 2021

Humans have been shown to adapt their movements when a sudden or gradual change to the dynamics of the environment are introduced, a phenomenon called motor adaptation. If the change is reverted, the adaptation is also quickly reverted. Humans are also able to adapt to multiple changes in dynamics presented separately, and to be able to switch between adapted movements on the fly. Such switching relies on contextual information which is often noisy or misleading, affecting the switch between known adaptations. Recently, computational models for motor adaptation and context inference have been introduced, which contain components for context inference and Bayesian motor adaptation. These models were used to show the effects of context inference on learning rates across different experiments. We expanded on these works by using a simplified version of the recently-introduced COIN model to show that the effects of context inference on motor adaptation and control go even further than previously shown. Here, we used this model to simulate classical motor adaptation experiments from previous works and showed that context inference, and how it is affected by the presence and reliability of feedback, effect a host of behavioral phenomena that had so far required multiple hypothesized mechanisms, lacking a unified explanation. Concretely, we show that the reliability of direct contextual information, as well as noisy sensory feedback, typical of many experiments, effect measurable changes in switching-task behavior, as well as in action selection, that stem directly from probabilistic context inference.
Dynamic Resting State Motor Network Connectivity of Neurotypical Children, the Groundwork for Network-Guided Therapy in Childhood Movement Disorders
Authors: Sussman Bethany L. , Wyckoff Sarah N. , Fine Justin M. , Heim Jennifer , Wilfong Angus A. , Adelson P. David , Kruer Michael C. , Boerwinkle Varina L.
Published: December 2021

Background

Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state network informed treatments in pediatric movement disorders.

Method

Cross-spectral dynamic causal modelling of resting-state fMRI was investigated in 19 neurotypically developing 5-7-year-old children. Fully connected six-node motor network models were created for each hemisphere including primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging were used to create a group model for each hemisphere; Purdue Pegboard Test (PPBT) scores for relevant hand motor behavior were also entered as a covariate at the group level to determine the brain-behavior relationship.

Results

Overall, the resting-state functional MRI effective connectivity of motor cortico-basal ganglia-cerebellar networks was similar across hemispheres, with greater connectivity in the left hemisphere. The motor network effective connectivity relationships between the nodes were consistent and robust across subjects. Additionally, the PPBT score for each hand was positively correlated with the thalamus to contralateral cerebellum connection.

Discussion

The normative effective connectivity from resting-state functional MRI in children largely reflect the direction of inter-nodal signal predicted by other prior modalities and was consistent and robust across subjects, with differences from these prior task-dependent modalities that likely reflect the motor rest-action state during acquisition. Effective connectivity of the motor network was correlated with motor behavior, indicating effective connectivity brain-behavior relationship has physiological meaning in the normally developing. Thus, it may be helpful for future studies in children with movement disorders, wherein comparison to normative effective connectivity will be critical for network-targeted intervention.

Impact Statement

This is the first study to use pediatric resting-state functional MRI to create a normative effective connectivity model of the motor network and to also show correlation with behavior, which may have therapeutic implications for children with movement disorders.
T cell receptor repertoire signatures associated with COVID-19 severity
Authors: Park Jonathan J. , Lee Kyoung A V. , Lam Stanley Z. , Chen Sidi
Published: December 2021

T cell receptor (TCR) repertoires are critical for antiviral immunity. Determining the TCR repertoires composition, diversity, and dynamics and how they change during viral infection can inform the molecular specificity of viral infection such as SARS-CoV-2. To determine signatures associated with COVID-19 disease severity, here we performed a large-scale analysis of over 4.7 billion sequences across 2,130 TCR repertoires from COVID-19 patients and healthy donors. TCR repertoire analyses from these data identified and characterized convergent COVID-19 associated CDR3 gene usages, specificity groups, and sequence patterns. T cell clonal expansion was found to be associated with upregulation of T cell effector function, TCR signaling, NF-kB signaling, and Interferon-gamma signaling pathways. Machine learning approaches accurately predicted disease severity for patients based on TCR sequence features, with certain high-power models reaching near-perfect AUROC scores across various predictor permutations. These analyses provided an integrative, systems immunology view of T cell adaptive immune responses to COVID-19.
Variance in Variants: Propagating Genome Sequence Uncertainty into Phylogenetic Lineage Assignment
Authors: Champredon David , Becker Devan , Chato Connor , Gugan Gopi , Poon Art
Published: December 2021

Genetic sequencing is subject to many different types of errors, but most analyses treat the resultant sequences as if they are known without error. Next generation sequencing methods rely on significantly larger numbers of reads than previous sequencing methods in exchange for a loss of accuracy in each individual read. Still, the coverage of such machines is imperfect and leaves uncertainty in many of the base calls. On top of this machine-level uncertainty, there is uncertainty induced by human error, such as errors in data entry or incorrect parameter settings. In this work, we demonstrate that the uncertainty in sequencing techniques will affect downstream analysis and propose a straightforward method to propagate the uncertainty.

Our method uses a probabilistic matrix representation of individual sequences which incorporates base quality scores as a measure of uncertainty that naturally lead to resampling and replication as a framework for uncertainty propagation. With the matrix representation, resampling possible base calls according to quality scores provides a bootstrap- or prior distribution-like first step towards genetic analysis. Analyses based on these re-sampled sequences will include a more complete evaluation of the error involved in such analyses.

We demonstrate our resampling method on SARS-CoV-2 data. The resampling procedures adds a linear computational cost to the analyses, but the large impact on the variance in downstream estimates makes it clear that ignoring this uncertainty may lead to overly confident conclusions. We show that SARS-CoV-2 lineage designations via Pangolin are much less certain than the bootstrap support reported by Pangolin would imply and the clock rate estimates for SARS-CoV-2 are much more variable than reported.
The enteric nervous system of C. elegans is specified by the Sine Oculis-like homeobox gene ceh-34
Authors: Vidal Berta , Gulez Burcu , Cao Wen Xi , Leyva-Diaz Eduardo , Tekieli Tessa , Hobert Oliver
Published: December 2021

Overarching themes in the terminal differentiation of the enteric nervous system, an autonomously acting unit of animal nervous systems, have so far eluded discovery. We describe here the overall regulatory logic of enteric nervous system differentiation of the nematode C. elegans that resides within the foregut (pharynx) of the worm. A Caenorhabditis elegans homolog of the Drosophila Sine Oculis homeobox gene, ceh-34, is expressed in all 14 classes of interconnected pharyngeal neurons from their birth throughout their life time, but in no other neuron type of the entire animal. Constitutive and temporally controlled ceh-34 removal shows that ceh-34 is required to initiate and maintain the neuron type-specific terminal differentiation program of all pharyngeal neuron classes, including their circuit assembly, without affecting panneuronal features. Through additional genetic loss of function analysis, we show that within each pharyngeal neuron class, ceh-34 cooperates with different homeodomain transcription factors to individuate distinct pharyngeal neuron classes. Our analysis underscores the critical role of homeobox genes in neuronal identity specification and links them to the control of neuronal circuit assembly of the enteric nervous system. Together with the pharyngeal nervous system simplicity as well as its specification by a Sine Oculis homolog, our findings invite speculations about the early evolution of nervous systems.
Effect of spatiotemporally changing environment on serial dependence in ensemble representations
Authors: Son Sangkyu , Lee Joonyeol , Kwon Oh-Sang , Kim Yee-Joon
Published: December 2021

The recent visual past has a strong impact on our current perception. Recent studies of serial dependence in perception show that low-level adaptation repels our current perception away from previous stimuli1–5 whereas post-perceptual decision attracts perceptual report toward the immediate past6–12. In their studies, these repulsive and attractive biases were observed with different task demands perturbing ongoing sequential process. Therefore, it is unclear whether the opposite biases arise naturally in navigating complex real-life environments. Here we only manipulated the environmental statistics to characterize how serially dependent perceptual decisions unfold in spatiotemporally changing visual environments. During sequential mean orientation adjustment task on the array of Gabor patches, we found that the repulsion effect dominated only when ensemble variance increased across consecutive trials whereas the attraction effect prevailed when ensemble variance decreased or remained the same. The observed attractive bias by high- to-low-variance stimuli and repulsive bias by low-to-high-variance stimuli were reinforced by the repeated exposure to the low and the high ensemble variance, respectively. Further, this variance-dependent differential pattern of serial dependence in ensemble representation remained the same regardless of whether observers had a prior knowledge of environmental statistics or not. We used a Bayesian observer model constrained by visual adaptation13,14 to provide a unifying account of both attractive and repulsive bias in perception. Our results establish that the temporal integration and segregation of visual information is flexibly adjusted through variance adaptation.
Chitin-induced systemic disease resistance in rice requires both OsCERK1 and OsCEBiP and is mediated via perturbation of cell-wall biogenesis in leaves
Authors: Takagi Momoko , Hotamori Kei , Naito Keigo , Matsukawa Sumire , Egusa Mayumi , Nishizawa Yoko , Kanno Yuri , Seo Mitsunori , Ifuku Shinsuke , Mine Akira , Kaminaka Hironori
Published: December 2021

Chitin is a well-known elicitor of disease resistance whose recognition by plants is crucial to perceive fungal infections. Chitin can induce both a local immune response and a systemic disease resistance when provided as a supplement in soils. Unlike local immune responses, how chitin-induced systemic disease resistance is deployed has not been studied in detail.

In this study, we evaluated systemic disease resistance against the fungal pathogen Bipolaris oryzae by performing a transcriptome analysis and monitoring cell-wall composition in rice plants grown in chitin-supplemented soils. We also examined the local immune response to chitin by measuring the production of reactive oxygen species in leaves.

Chitins induced both local immune response and systemic disease resistance with differing requirements for the receptors OsCERK1 and OsCEBiP. Transcriptome analysis suggested that a perturbation in cell-wall biogenesis is involved in the induction of systemic disease resistance, an idea which was supported by the induction of disease resistance by treatment with a cellulose biosynthesis inhibitor and alterations of cell-wall composition.

These findings suggest that chitin-induced systemic disease resistance in rice is caused by a perturbation of cell-wall biogenesis in leaves through long-distance signalling after recognition of chitins by OsCERK1 and OsCEBiP.
X-MyoNET: Biometric Identification using Deep Processing of Transient Surface Electromyography
Authors: Hu Qin , Sarmadi Alireza , Gulati Paras , Krishnamurthy Prashanth , Khorrami Farshad , Atashzar S. Farokh
Published: December 2021

The rapid development of the Internet and various applications such as the Internet of Medical Things (IoMT) has raised substantial concerns about personal information security. Conventional methods (e.g., passwords) and classic biological features (e.g., fingerprints) are security deficient because of potential information leakage and hacking. Biometrics that expressbehavioral featuressuggest a robust approach to achieving information security because of the corresponding uniqueness and complexity. In this paper, we consider identifying human subjects based on their transient neurophysiological signature captured using multichannel upper-limb surface electromyography (sEMG). An explainable artificial intelligence (XAI) approach is proposed to process the internal dynamics of temporal sEMG signals. We propose and prove the suitability of “transient sEMG” as a biomarker that can identify individuals. For this, we utilize the Gradient-weighted Class Activation Mapping (Grad-CAM) analysis to explain the network’s attention. The outcome not only decodes and makes the unique neurophysiological pattern (i.e., motor unit recruitment during the transient phase of contraction) associated with each individual visualizable but also generates an optimizing two-dimensional (2D) spectrotemporal mask used to significantly reduce the size of the model and the trainable parameters. The resulting mask selectively and systematically samples the spectrotemporal characteristics of the users’ neurophysiological responses, discarding 40% of the input space while securing the accuracy of about 74% with much shallower neural network architecture. In the systematic comparative study, we find that our proposed model outperforms several state-of-the-art algorithms. For broader impacts, we anticipate our design of a compact, practical, interpretable, and robust identification system that requires only a minimal number of gestures and sensors (only 7% of the entire data set) to be a starting point for small and portable identification hardware.
Linking gene expression patterns and brain morphometry to trauma and symptom severity in patients with functional seizures
Authors: Jungilligens Johannes , Popkirov Stoyan , Perez David L. , Diez Ibai
Published: December 2021

Objective

Adverse life experiences (ALEs) increase the susceptibility to functional (somatoform/dissociative) symptoms, likely through neurodevelopmental effects. This analysis aimed to illuminate potential genetic influences in neuroanatomical variation related to functional symptoms and ALEs in patients with functional seizures.

Methods

Questionnaires, structural brain MRIs and Allen Human Brain Atlas gene expression information were used to probe the intersection of functional symptom severity (Somatoform Dissociation Questionnaire, SDQ-20), ALE burden, and gray matter volumes in 20 patients with functional seizures.

Results

Functional symptom severity positively correlated with the extent of sexual trauma, emotional neglect, and threat to life experiences. In voxel-based morphometry analyses, increased SDQ-20 scores related to decreased bilateral insula, left orbitofrontal, right amygdala, and perigenual and posterior cingulate gray matter volumes. Left insula findings held adjusted for psychiatric comorbidities. Increased sexual trauma burden correlated with decreased right posterior insula and putamen volumes; increased emotional neglect related to decreased bilateral insula and right amygdala volumes. The sexual trauma–right insula/putamen and emotional neglect– right amygdala relationships held adjusting for individual differences in psychiatric comorbidities. When probing the intersection of symptom severity and sexual trauma volumetric findings, genes overrepresented in adrenergic, serotonergic, oxytocin, opioid, and GABA receptor signaling pathways were spatially correlated. This set of genes was over-expressed in cortical and amygdala development.

Conclusion

ALEs and functional symptom severity were associated with gray matter alterations in cingulo-insular and amygdala areas. Transcriptomic analysis of this anatomical variation revealed a potential involvement of several receptor signaling pathways.