bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Upregulation of TLR4/MyD88 pathway in alcohol-induced Wernicke’s encephalopathy: findings in preclinical models and in a postmortem human case”
Authors: Moya Marta , Escudero Berta , Gómez-Blázquez Elena , Rebolledo-Poves Ana Belen , López-Gallardo Meritxell , Guerrero Carmen , María Marco Eva , Orio Laura 
Published: July 2022

AbstractWernicke’s encephalopathy (WE) is a neurologic disease caused by vitamin B1 or thiamine deficiency (TD), being the alcohol use disorder (AUD) its main risk factor. WE patients present limiting motor, cognitive and emotional alterations related to a selective cerebral vulnerability. Neuroinflammation has been proposed as one of the phenomena contributing to brain damage. Our previous studies provide evidence for the involvement of the innate immune receptor Toll-like (TLR) 4 in the inflammatory response induced in the frontal cortex and cerebellum in TD animal models (animals fed with TD diet and receiving pyrithiamine). However, the effects of the combination of chronic alcohol consumption and TD on TLR4 and their specific contribution to the pathogenesis of WE are currently unknown. Additionally, no studies on TLR4 have been conducted on WE patients since brains from these patients are difficult to achieve. Here, we used rat models of chronic alcohol (CA; 9 months of forced consumption of 20% (w/v) alcohol), TD hit (TDD; TD diet + daily 0.25 mg/kg i.p. pyrithiamine during 12 days), or a combined treatment (CA+TDD) to check the activation of the proinflammatory TLR4/MyD88 pathway and related markers in the frontal cortex and the cerebellum. In addition, we characterized for the first time the TLR4 and its co-receptor MyD88 signature, along with other markers of this proinflammatory signaling such as phospo-NFκB p65 and IκBα, in the post-mortem human frontal cortex and cerebellum (gray and white matter) of an alcohol-induced WE patient, comparing it with negative (no disease) and positive (aged brain with Alzheimer’s disease) control subjects for neuroinflammation. We found an increase in the cortical TLR4 and its adaptor molecule MyD88, together with an upregulation of the proinflammatory signaling molecules p-NF-ĸB and IĸBα in the CA+TDD animal model. In the patient diagnosed with alcohol-induced WE we observed cortical and cerebellar upregulation of the TLR4/MyD88 pathway. Thus, our findings provide evidence, both in the animal model and the human postmortem brain, of the upregulation of the TLR4/MyD88 proinflammatory pathway in WE related to alcohol consumption.
Regulation of oxidative phosphorylation by Nuclear myosin 1 protects cells from metabolic reprogramming and tumorigenesis in mice
Authors: Venit Tomas , Sapkota Oscar , Abdrabou Wael Said , Loganathan Palanikumar , Pasricha Renu , Mahmood Syed Raza , El Said Nadine Hosny , Thomas Sneha , Idaghdour Youssef , Magzoub Mazin , Percipalle Piergiorgio 
Published: July 2022

SummaryMetabolic reprogramming is one of the hallmarks of tumorigenesis. Using a combination of multi-omics, here we show that nuclear myosin 1 (NM1) serves as a key regulator of cellular metabolism. As part of the nutrient-sensing PI3K/Akt/mTOR pathway, NM1 forms a positive feedback loop with mTOR and directly affects mitochondrial oxidative phosphorylation (OXPHOS) via transcriptional regulation of mitochondrial transcription factors TFAM and PGC1α. NM1 depletion leads to suppression of PI3K/Akt/mTOR pathway, underdevelopment of mitochondria inner cristae, and redistribution of mitochondria within the cell, which is associated with reduced expression of OXPHOS genes, decreased mitochondrial DNA copy number and deregulated mitochondrial dynamics. This leads to metabolic reprogramming of NM1 KO cells from OXPHOS to aerobic glycolysis and with a metabolomic profile typical for cancer cells, namely, increased amino acid-, fatty acid-, and sugar metabolism, and increased glucose uptake, lactate production, and intracellular acidity. We show that NM1 KO cells form solid tumors in a nude mouse model even though they have suppressed the PI3K/Akt/mTOR signaling pathway suggesting that the metabolic switch towards aerobic glycolysis provides a sufficient signal for carcinogenesis. We suggest that NM1 plays a key role as a tumor suppressor and that NM1 depletion may contribute to the Warburg effect at the early onset of tumorigenesis.
Null models for the Opportunity for Selection
Authors: Waples R. S. , Reed Thomas E. 
Published: July 2022

AbstractCrow’s ‘Opportunity for Selection’ (I=variance in relative fitness) is an important albeit controversial eco-evolutionary concept, particularly regarding the most appropriate null model(s). Here we treat this topic in a comprehensive way by considering opportunities for both fertility selection (If) and viability selection (Im) for discrete generations, both seasonal and lifetime reproductive success in age-structured species, and for experimental designs that include either a full or partial life cycle, with complete enumeration or random subsampling. For each scenario, a null model that includes random demographic stochasticity can be constructed that follows Crow’s initial formulation that I=If+Im. The two components of I are qualitatively different. Whereas an adjusted If (ΔIf) can be computed that accounts for random demographic stochasticity in offspring number, Im cannot be similarly adjusted in the absence of data on phenotypic traits under viability selection. Including as potential parents some individuals that die before reproductive age produces an overall, zero-inflated-Poisson null model. It is always important to remember that (1) Crow’s I represents only the opportunity for selection and not selection itself, and (2) the species’ biology can lead to random stochasticity in offspring number that is either overdispersed or underdispersed compared to the Poisson (Wright-Fisher) expectation.
Predicting the causative pathogen among children with pneumonia using a causal Bayesian network
Authors: Wu Yue , Mascaro Steven , Bhuiyan Mejbah , Fathima Parveen , Mace Ariel O. , Nicol Mark P. , Richmond Peter , Kirkham Lea-Ann , Dymock Michael , Foley David A. , McLeod Charlie , Borland Meredith L. , Martin Andrew , Williams Phoebe C.M. , Marsh Julie A. , Snelling Tom , Blyth Christopher C. 
Published: July 2022

AbstractBackgroundPneumonia remains a leading cause of hospitalization and death among young children worldwide, and the diagnostic challenge of differentiating bacterial from non-bacterial pneumonia is the main driver of antibiotic use for treating pneumonia in children. Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provide clear maps of probabilistic relationships between variables and produce results in an explainable way by incoporating both domain expert knowledge and numerical data.MethodsWe used domain expert knowledge and data in combination and iteratively, to construct, parameterise and validate a causal BN to predict causative pathogens for childhood pneumonia. Expert knowledge elicitation occurred through a series of group workshops, surveys and one-on-one meetings involving 6-8 experts from diverse domain areas. The model performance was evaluated based on both quantitative metrics (area under the receiver-operator curve (AUROC) and log loss) and qualitative expert validation. Sensitivity analyses were conducted to investigate how the target output is influenced by varying key assumptions of particular high degree of uncertainty around data or domain expert knowledge.ResultsDesigned to apply to a cohort of children with X-ray confirmed pneumonia who presented to a tertiary paediatric hospital in Australia, the resulting BN offers explainable and quantitative predictions on a range of variables of interest, including the diagnosis of bacterial pneumonia, detection of respiratory pathogens in the nasopharynx, and the clinical phenotype of a pneumonia episode. Satisfactory numeric performance has been achieved including an AUROC of 0.8 in predicting the clinical diagnosis of bacterial pneumonia. Three commonly encountered scenarios were presented to demonstrate the potential usefulness of the BN outputs in various clinical pictures.ConclusionsTo our knowledge, this is the first causal model developed to help determine the causative pathogen for paediatric pneumonia. It can be utilized to derive recommendations to support more directed and judicious use of antimicrobials for relevant cohorts. The BN needs further validation before it can be clinically implemented. Our model framework and the methodological approach can be adapted beyond our context to broad respiratory infections and geographical and healthcare settings.
A Multivariate Comparison of EEG and fMRI to ECoG Using Visual Object Representations in Humans
Authors: Ebrahiminia Fatemeh , Cichy Radoslaw Martin , Khaligh-Razavi Seyed-Mahdi 
Published: July 2022

1.AbstractToday most neurocognitive studies in humans employ the non-invasive neuroimaging techniques fMRI and EEG. However, how the data provided by fMRI and EEG relate exactly to the underlying neural activity remains incompletely understood. Here, we pursued this open question by relating EEG and fMRI data at the level of neural population codes using multivariate pattern analysis. For this, we recorded EEG and fMRI data while participants viewed everyday objects in different viewing conditions, and then related the data to ECoG data recorded for the same stimulus set. The comparison of EEG and ECoG data showed that object category signals emerge swiftly in the visual system and can be detected by both EEG and ECoG at similar temporal delays after stimulus onset. The correlation between EEG and ECoG reduces and onset latencies increase when object representations tolerant to changes in scale and orientation are considered. The comparison of fMRI and ECoG overall revealed a tighter relationship in occipital than in temporal regions, related to differences in fMRI signal-to-noise ratio. Together, our results reveal a complex relationship between fMRI, EEG and ECoG signals at the level of population codes that critically depends on the time point after stimulus onset, the region investigated, and the visual contents used.
HT-SIP: A semi-automated Stable Isotope Probing pipeline identifies interactions in the hyphosphere of arbuscular mycorrhizal fungi
Authors: Nuccio Erin E. , Blazewicz Steven J. , Lafler Marissa , Campbell Ashley N. , Kakouridis Anne , Kimbrel Jeffrey A. , Wollard Jessica , Vyshenska Dariia , Riley Robert , Tomatsu Andy , Hestrin Rachel , Malmstrom Rex R. , Firestone Mary , Pett-Ridge Jennifer 
Published: July 2022

ABSTRACTBackgroundLinking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive to meet this goal, Stable Isotope Probing—SIP—remains the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, active microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated DNA-SIP pipeline to support well-replicated, temporally-resolved amplicon or metagenomics experiments that enable studies of dynamic microbial communities over space and time. To test this pipeline, we assembled SIP-metagenome assembled genomes (MAGs) from the hyphosphere zone surrounding arbuscular mycorrhizal fungi (AMF), in combination with a 13CO2 plant labelling study.ResultsOur semi-automated pipeline for DNA fractionation, cleanup, and nucleic acid quantification of SIP density gradients requires six times less hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients and reduced variation compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We then tested this pipeline on samples from a highly-constrained soil microhabitat with significant ecological importance, the AMF fungal hyphosphere. Processing via our quantitative SIP pipeline confirmed the AMF Rhizophagus intraradices and its associated microbiome were highly 13C enriched, even though the soils’ overall enrichment was only 1.8 atom% 13C. We assembled 212 13C-enriched hyphosphere MAGs, and the hyphosphere taxa that assimilated the most AMF-derived 13C (range 10-33 atom%) were from the phlya Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia oxidizing archaeon genus Nitrososphaeara.ConclusionsOur semi-automated SIP approach decreases operator time and errors and improves reproducibility by targeting the most labor-intensive steps of SIP—fraction collection and cleanup. Here, we illustrate this approach in a unique and understudied soil microhabitat—generating MAGs of active microbes living in the AMF hyphosphere (without plant roots). Their phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling.
Goat PRP14 (gPRP14) has xeno-antigenic properties and works as a vaccine in preclinical models of cancer
Authors: Minucci Saverio , Bussolati Benedetta , Massa Paul E. , Brossa Alessia , Ravasio Roberto , Saadeldin Mona , Degani Genny , Papadimitriou Elli , Saadeldin Amal , Salvaggio Antonio , Visintin Cristina , Rizzi Giulia , Ricagno Stefano , Popolo Laura , Vanoni Maria Antonietta , Pelicci Pier Giuseppe 
Published: July 2022

AbstractWe studied the activity of recombinant goat PRP14 (gPRP14), a member of the RID protein family, as a xeno-antigen in preclinical models of cancer. Antisera from rabbits and mice immunized with gPRP14 showed strong reactivity against several tumor cell types, which was absent towards normal cells: the tumor selectivity was related to surface and intra-cellular expression in tumor cells, and to an exclusively intra-cellular localization in normal cells. In vitro, binding to tumor cells was followed by cytotoxicity which could be rescued by the addition of excess soluble antigen. In vivo, an anti-tumor activity of immunization with gPRP14 was observed in murine syngeneic models of breast cancer and melanoma: the anti-tumor response was present when gPRP14 was administered in a preventive setting, and persisted upon repeated challenges with tumor cells in long-term survivor mice. Finally, we showed that both the humoral and T-cell mediated responses are needed for the optimal anti-tumor effect in the murine melanoma model. Thus, we have performed an initial characterization of gPRP14 as a cancer vaccine, which -given the potential wide range of tumor cells positive for the antigen-appears as a promising, novel immunotherapy.
Identification and characterisation of variable rhythms using CosinorPy
Authors: Moškon Miha 
Published: July 2022

AbstractBackground and objectiveAnalysis of rhythmic data has become an important aspect in biological and medical science, as well as other fields of science. Parametric methods based on trigonometric regression reflect several advantages in comparison to their alternatives. Software packages for parametric analysis of rhythmic data are mostly based on a single-component cosinor model, which is not able to describe asymmetric rhythms that might reflect multiple peaks per period. Moreover, a basic cosinor model is unable to describe rhythmicity that is changed with time. Here, we present some important extensions of the recently developed CosinorPy Python package to address these gaps.MethodsThe extended package CosinorPy provides the functionalities to perform a detailed individual or comparative analysis of rhythms reflecting (1) multiple asymmetric peaks per period, (2) forced, damped, or sustained rhythms, and (3) shift of the midline statistics of rhythm over time. In all these cases the package is able to assess the (differential) rhythmicity parameters, evaluate their significance and confidence intervals, and provide a set of publication-ready figures.ResultsWe demonstrate the package in some typical scenarios that incorporate different types of rhythmic dynamics, such as asymmetric, damped, and forced rhythms. We show that the proposed implementation of a generalised cosinor model is capable of reducing the error of estimated rhythmicity parameters in cases that tend to be problematic for alternative models. The implementation of the presented package is available together with scripts to reproduce the reported results athttps://github.com/mmoskon/CosinorPy.ConclusionAccording to our knowledge, CosinorPy currently presents the only implementation that is able to cover all the above scenarios using a parametric model with vast applications in biology and medicine as well as in other scientific domains.
Global quantitative understanding of nonequilibrium cell fate decision making in response to pheromone
Authors: Li Sheng , Liu Qiong , Wang Erkang , Wang Jin 
Published: July 2022

AbstractCell cycle arrest and polarized cell growth are commonly used to qualitatively characterize the fate of yeast in response to pheromone. However, the quantitative decision-making process underlying the time-dependent changes in cell fate remains unclear. Here, by observing the multi-dimensional responses at the single-cell level experimentally, we find that yeast cells have various fates. Multiple states are revealed, along with the kinetic switching rates and pathways among them, giving rise to a quantitative landscape of mating response. We developed a theoretical framework using a nonequilibrium landscape and flux theory to account for the cell morphology observed experimentally and performed a stochastic simulation of biochemical reactions to explain the signal transduction and cell growth. Our experimental results established the first global quantitative demonstration of the real-time synchronization of intracellular signaling with their physiological growth and morphological functions which reveals the underlying physical mechanism. This study provides an emerging mechanistic approach for understanding the nonequilibrium global pheromone-regulated cell fate decision-making in growth and morphology.
Novel class of yellow emitting carbon dots stimulate collective cell migration and 3D uptake in vivo
Authors: Singh Udisha , Shah Krupa , Kansara Krupa , Kumar Ashutosh , Bhatia Dhiraj 
Published: July 2022

AbstractWe present a new class of nitrogen-doped yellow fluorescent carbon dots, synthesized using a one-step hydrothermal method. These bright fluorescent nanoparticles have excitation and emission spectra near the red region of the visible light spectrum that are quite useful for bioimaging applications. Using organic molecules like ortho- phenylenediamine (OPDA), L-ascorbic acid and urea, yellow fluorescent carbon dots (CDs) were synthesized. We obtained a scalable number of CDs having an average size of 3 nm. The CDs show significant emission spectra in the yellow fluorescence region (λem= 557 nm). The CDs show remarkable stability in their fluorescence in different pH conditions, ionic stability, photostability as well as thermal stability. These CDs are efficiently uptaken by mammalian cells through clathrin-mediated pathway. Apart from in vitro studies we have also used zebrafish larvae as a 3D in vivo model, and showed that CDs were uptaken efficiently by larvae showing maximum accumulation and fluorescence in the yolk sac region and the notochord region. The CDs also offer enhancement in cell proliferation, hence showing the application in wound healing. The fluorescence of CDs is quite robust and is not affected by most external stimuli, hence can be explored as a promising bioimaging tool for targeted bioimaging and biomedical applications.
Modeling the carbon-dioxide response function in fMRI under task and resting-state conditions
Authors: Shams Seyedmohammad , Prokopiou Prokopis , Esmaelbeigi Azin , Mitsis Georgios D. , Chen J. Jean 
Published: July 2022

AbstractConventionally, cerebrovascular reactivity (CVR) is estimated as the amplitude of the hemodynamic response to vascular stimuli. While the CVR amplitude has established clinical utility, the temporal characteristics of CVR have been increasingly explored and may yield even more pathology-sensitive parameters. This work is motivated by the current need to evaluate the feasibility of dCVR modeling in various noise conditions. In this work, we present a comparison of several recently published model-based deconvolution approaches for estimating h(t), including maximum a posterior likelihood (MAP), inverse logit (IL), canonical correlation analysis (CCA), and basis expansion (using Gamma and Laguerre basis sets). To aid the comparison, we devised a novel simulation framework that allowed us to target a wide range of SNRs, ranging from 10 to −7 dB, representative of both task and resting-state CO2 changes. In addition, we built ground-truth h(t) into our simulation framework, overcoming the practical limitation that the true h(t) is unknown in methodological evaluations. Moreover, to best represent realistic noise found in fMRI scans, we extracted it from in-vivo resting-state scans. Furthermore, we introduce a simple optimization of the CCA method (CCAopt) and compare its performance to these existing methods. Our findings suggest that model-based methods can reasonably estimate dCVR even amidst high noise, and in a manner that is largely independent of the underlying model assumptions for each method. We also provide a quantitative basis for making methodological choices, based on the desired dCVR parameters, the estimation accuracy and computation time. The BEL method provided the highest accuracy and robustness, followed by the CCAopt and IL methods. Of the three, the CCAopt method required the lowest computational time. These findings lay the foundation for wider adoption of dCVR estimation in CVR mapping.
The effect of combined dexmedetomidine and isoflurane anaesthesia on visually evoked responses in rats – an electrophysiological study
Authors: Østergaard Freja Gam , Skoven Christian Stald , Laursen Bettina , Dyrby Tim B. , Wade Alex 
Published: July 2022

AbstractThe purpose of this study was to pilot an anaesthetic regime with the potential to be used for blood oxygenation level dependent functional magnetic resonance imaging (BOLD fMRI) of the visual system. We used electrophysiology to explore the effect of an anaesthesia regime, combining dexmedetomidine and isoflurane, on the visual system of female Sprague-Dawley rats. This paradigm is hypothesised to affect neural signalling less than other paradigms, and thus may be suitable for studies using BOLD fMRI. Electrodes were implanted bilaterally in the visual cortex (VC) and superior colliculus (SC) of 16 rats. Visual evoked potentials (VEPs) and steady-state VEPs (SSVEPs) were recorded during 1 Hz and 14 Hz light stimulation, respectively. As a control experiment an exploration of the wash-out of isoflurane was performed. The combined anaesthetic regime showed, that the visually evoked responses were almost completely abolished at the initiation of anaesthesia, but gradually recovered to baseline levels over time in the SC. In contrast, the evoked response in the VC only partially recovered, staying significantly below baseline condition. BOLD fMRI results from a previously published study supports this finding.