bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence of phylosymbiosis inFormicaants
Authors: Jackson Raphaella , Patapiou Patapios A. , Golding Gemma , Helanterä Heikki , Economou Chloe K. , Chapuisat Michel , Henry Lee M. 
Published: January 2023

AbstractInsects share intimate relationships with microbes that play important roles in their biology. Yet our understanding of how host-bound microbial communities assemble and perpetuate over evolutionary time is limited. Ants host a wide range of microbes with diverse functions and are an emerging model for studying the evolution of insect microbiomes. Here, we ask whether phylogenetically related ant species have formed distinct and stable microbiomes. To answer this question, we investigated the microbial communities associated with queens of 14Formicaspecies from five clades, using deep coverage 16S rRNA amplicon sequencing. We reveal thatFormicaspecies and clades harbour highly defined microbial communities that are dominated by four bacteria genera:Wolbachia, Lactobacillus,Liliensternia,andSpiroplasma. Our analysis reveals that the composition ofFormicamicrobiomes mirrors the phylogeny of the host, i.e. phylosymbiosis, in that related hosts harbour more similar microbial communities. Our analysis also revealed significant correlations between microbe co-occurrences, which suggests that synergistic and antagonistic interactions may contribute to the phylosymbiotic signal. Additional factors potentially contributing to the phylosymbiotic signal are discussed, including host phylogenetic relatedness, host-microbe genetic compatibility, modes of transmission, and similarities in host ecologies (e.g., diets). Overall, our results support the growing body of evidence that microbial community composition closely depends on the phylogeny of their hosts, despite bacteria having diverse modes of transmission and localisation within the host.
Mapping cortical excitability in the human dorsolateral prefrontal cortex
Authors: Gogulski Juha , Cline Christopher C. , Ross Jessica M. , Truong Jade , Sarkar Manjima , Parmigiani Sara , Keller Corey J. 
Published: January 2023

ABSTRACTObjectiveTo characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and that EL-TEP amplitude is inversely related to muscle artifact. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach.MethodsIn 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.ResultsStimulation location significantly influenced EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%.SignificanceEarly local TMS-evoked potentials (EL-TEPs) can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.HighlightsEarly local TMS-evoked potentials (EL-TEPs) varied significantly across the dlPFC as a function of TMS target.TMS targets with less muscle artifact had significantly larger EL-TEPs.Selection of a postero-medial target increased EL-TEPs by 102% compared to anterior targets.
FGF2-induced Redox Signaling: A Mechanism Regulating Pyruvate Dehydrogenase Driven Histone Acetylation and NANOG Upregulation
Authors: Fojtík Petr , Senfluk Martin , Holomkova Katerina , Salykin Anton , Gregorova Jana , Smak Pavel , Pes Ondrej , Raska Jan , Stetkova Monika , Skladal Petr , Sedlackova Miroslava , Hampl Ales , Bohaciakova Dasa , Uldrijan Stjepan , Rotrekl Vladimir 
Published: January 2023

AbstractPrecise control of pluripotency is a requirement for the safe and effective use of hPSCs in research and therapies. Here we report that pyruvate dehydrogenase upregulates histone H3 pan acetylation and levels of pluripotency marker NANOG in 5% O2. Pyruvate dehydrogenase (PDH) is an essential metabolic switch and a bottleneck for the glycolytic production of acetyl-CoA. Silencing of gene expression showed that PDH is regulated by the activity of its phosphatase PDP1. We show that PDP1 is sensitive to reactive oxygen species-mediated inactivation, leading to the downregulation of H3 pan acetylation and NANOG levels. Furthermore, we show that FGF2, a cytokine commonly used to maintain pluripotency activates pyruvate dehydrogenase through MEK1/2-ERK1/2 signaling pathway-mediated downregulation of ROS in 5% O2, thus promoting histone acetylation. Our results show the importance of pyruvate dehydrogenase in regulating energy metabolism and its connection to pluripotency. Furthermore, our data highlight the role of reactive oxygen species and redox homeostasis in pluripotency maintenance and differentiation.Highlights- PDP1-induced activation of PDH leads to increased histone H3 pan acetylation and NANOG levels in hPSCs- Reactive oxygen species (ROS) inactivate PDP1 and decrease histone H3 pan acetylation and NANOG levels in hPSCs- MEK1/2-ERK1/2 signaling-mediated downregulation of ROS in 5% O2activates PDH in hPSCsGraphical abstract
WITHDRAWN: Immunological parameters ofProteus mirabilisisolates in Rheumatoid Arthritis patients with urinary tract infections
Authors: Abdul Fatima Rammadan , Raheem Ihsan Ali , Subhi Hanan Tariq , Fatah Hiwa Ramadhan , Muhammad Hanaa Ali 
Published: January 2023

Withdrawal statementThe authors have withdrawn this manuscript because [A conflict of interest exists and needs to correct the data that needs to be re-experimented and rewritten]. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA-sequencing datasets
Authors: Hazra Rasmani , Utama Raditya , Naik Payal , Dobin Alexander , Spector David L. 
Published: January 2023

AbstractGlioblastoma multiforme (GBM) is an aggressive, heterogeneous grade IV brain tumor. Glioblastoma stem cells (GSCs) initiate the tumor and are known culprits of therapy resistance. Mounting evidence has demonstrated a regulatory role of long non-coding RNAs (lncRNAs) in various biological processes, including pluripotency, differentiation, and tumorigenesis. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA-sequencing datasets of adult human GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brains to identify lncRNAs highly expressed in GBM. To categorize GSC populations in the GBM tumors, we used the GSC marker genes SOX2, PROM1, FUT4, and L1CAM. We found three major GSC population clusters: radial glia, oligodendrocyte progenitor cells, and neurons. We found 10–100 lncRNAs significantly enriched in different GSC populations. We also validated the level of expression and localization of several GSC-enriched lncRNAs using qRT-PCR, single-molecule RNA FISH, and sub-cellular fractionation. We found that the radial glia GSC-enriched lncRNAPANTR1is highly expressed in GSC lines and is localized to both the cytoplasmic and nuclear fractions. In contrast, the neuronal GSC-enriched lncRNAsLINC01563andMALAT1are highly enriched in the nuclear fraction of GSCs. Together, this study identified a panel of uncharacterized GSC-specific lncRNAs. These findings set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.
Archaeal type IV pili stabilizeHaloferax volcaniibiofilms in flow
Authors: Odermatt Pascal D. , Nussbaum Phillip , Monnappa Sourabh , Talà Lorenzo , Li Zhengqun , Sivabalasarma Shamphavi , Albers Sonja-Verena , Persat Alex 
Published: January 2023

AbstractBiofilms represent a prevalent lifestyle of unicellular organism that confers protection to external challenges. The mechanisms by which archaea form biofilms are however not entirely clear.H. volcaniiis an extremely halophilic euryarchaeon that commonly colonizes salt crust surfaces.H. volcaniiproduces long and thin appendages called type IV pili that are known to play a function in surface attachment and biofilm formation in archaea and bacteria. Here, we used biophysical experiments to identify critical function of type IV pili in the mechanical integrity ofH. volcaniibiofilms. Using interferometric scattering microscopy (iSCAT) to non-invasively visualize T4P in live cells, we find that piliation varies across mutants expressing single pilin isoforms. Using microfluidic experiments, we found that the adhesive strength of these mutants correlates with their extent of piliation. We found that in flow,H. volcaniiforms clonal biofilms that extend in three dimensions. Expression of PilA2, a single pilin isoform, is sufficient to maintain normal levels of piliation and form biofilms with a structure indistinguishable from WT. Furthermore, we found that fluid flow is a crucial determinant of biofilm integrity: in the absence of flow, biofilms lose cohesion and tend to disperse in a density-dependent manner. Overall, our results demonstrate that T4P-surface and possibly T4P-T4P interactions promote biofilm formation and integrity, and that flow is a crucial ingredient regulating archaeal biofilm formation.
A highly discriminatory RNA strand-specific assay to facilitate analysis of the role ofcis-acting elements in foot-and-mouth disease virus replication
Authors: Dobson Samuel J. , Ward Joseph C. , Herod Morgan R. , Rowlands David J. , Stonehouse Nicola J. 
Published: January 2023

AbstractFoot-and-mouth-disease virus (FMDV), the etiological agent responsible for foot-and-mouth disease (FMD), is a member of the genusAphthoviruswithin thePicornavirusfamily. In common with all picornaviruses, replication of the single-stranded positive-sense RNA genome involves synthesis of a negative-sense complementary strand that serves as a template for the synthesis of multiple positive-sense progeny strands. We have previously employed FMDV replicons to examine viral RNA and protein elements essential to replication, however, the factors affecting differential strand production remain unknown. Replicon-based systems require transfection of high levels of RNA, which can overload sensitive techniques such as qPCR preventing discrimination of specific strands. Here, we describe a method in which replicating RNA is labelledin vivowith 5-ethynyl uridine. The modified base is then linked to a biotin tag using click chemistry, facilitating purification of newly synthesised viral genomes or anti-genomes from input RNA. This selected RNA can then be amplified by strand-specific qPCR, thus enabling investigation of the consequences of defined mutations on the relative synthesis of negative-sense intermediate and positive-strand progeny RNAs. We apply this new approach to investigate the consequence of mutation of viralcis-acting replication elements and provide direct evidence for their roles in negative-strand synthesis.
Progeny counter mechanism in malaria parasites is linked to extracellular resources
Authors: Stürmer Vanessa S. , Stopper Sophie , Binder Patrick , Klemmer Anja , Becker Nils B. , Guizetti Julien 
Published: January 2023

AbstractMalaria is caused by the rapid proliferation ofPlasmodiumparasites in patients and disease severity correlates with the number of infected red blood cells in circulation. Parasite multiplication within red blood cells is called schizogony and occurs through an atypical multinucleated cell division mode. The mechanisms regulating the number of daughter cells produced by a single progenitor are poorly understood. We investigated underlying regulatory principles by quantifying nuclear multiplication dynamics inPlasmodium falciparumandknowlesiusing super-resolution time-lapse microscopy. This revealed that the number of daughter cells was statistically independent of the duration of the nuclear division phase, which confirms that a counter mechanism, rather than a timer, regulates multiplication.P. falciparumcell volume at the start of nuclear division correlated with the final number of daughter cells. As schizogony progressed, the nucleocytoplasmic volume ratio, which has been found to be constant in all eukaryotes characterized so far, increased significantly, possibly to accommodate the exponentially multiplying nuclei. Depleting nutrients by dilution of culture medium caused parasites to produce less merozoites and reduced proliferation but did not affect cell volume or total nuclear volume at the end of schizogony. Our findings suggest that the counter mechanism implicated in malaria parasite proliferation integrates extracellular resource status to modify progeny number during blood stage infection.
Source Localization Using Recursively Applied and Projected MUSIC with Flexible Extent Estimation
Authors: Hecker Lukas , Tebartz van Elst Ludger , Kornmeier Jürgen 
Published: January 2023

1AbstractMagneto- and electroencephalography (M/EEG) are widespread techniques to measure neural activityin-vivoat a high temporal resolution but low spatial resolution. Locating the neural sources underlying the M/EEG poses an inverse problem, which is ill-posed. We developed a new method based on Recursive Application of Multiple Signal Classification (MUSIC). Our proposed method is able to recover not only the locations but, in contrast to other inverse solutions, also the extent of active brain regions flexibly (FLEX-MUSIC). This is achieved by allowing it to search not only for single dipoles but also dipole clusters of increasing extent to find the best fit during each recursion. FLEX-MUSIC achieved the highest accuracy for both single dipole and extended sources compared to all other methods tested. Remarkably, FLEX-MUSIC was capable to accurately estimate the level of sparsity in the source space (r= 0.82), whereas all other approaches tested failed to do so (r≤ 0.18). The average computation time of FLEX-MUSIC was considerably lower compared to a popular Bayesian approach and comparable to that of another recursive MUSIC approach and eLORETA. FLEX-MUSIC produces only few errors and was capable to reliably estimate the extent of sources. The accuracy and low computation time of FLEX-MUSIC renders it an improved technique to solve M/EEG inverse problems both in neuroscience research and potentially in pre-surgery diagnostic in epilepsy.
Whole transcriptome profiling of placental pathobiology in SARS-CoV-2 pregnancies identifies placental dysfunction signatures
Authors: Stylianou Nataly , Sebina Ismail , Matigian Nicholas , Monkman James , Doehler Hadeel , Röhl Joan , Allenby Mark , Nam Andy , Pan Liuliu , Rockstroh Anja , Sadeghirad Habib , Chung Kimberly , Sobanski Thais , O’Byrne Ken , Ana Clara Simoes Florido Almeida , Rebutini Patricia Zadorosnei , Machado-Souza Cleber , Stonoga Emanuele Therezinha Schueda , Warkiani Majid E , Salomon Carlos , Short Kirsty , McClements Lana , de Noronha Lucia , Huang Ruby , Belz Gabrielle T. , Souza-Fonseca-Guimaraes Fernando , Clifton Vicki , Kulasinghe Arutha 
Published: January 2023

ABSTRACTObjectivesSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a “preeclampsia-like syndrome”. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection.MethodsWe utilized whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n=7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n=9).ResultsThrough comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified signatures associated with hypoxia and placental dysfunction during SARS-CoV-2 infection in pregnancy. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15,CRH), and preeclampsia (FLT1, EGFR, KISS1, PAPPA2),were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension, and inflammation, were also enriched in SARS-CoV-2 samples compared to uninfected controls.ConclusionsOur findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.Graphical abstractIn this study, using spatial digital profiling transcriptomic approaches, we demonstrate that SARS-CoV-2 infection in pregnancy disrupts optimal placental function by altering the genomic architecture of trophoblasts and villous core stromal cells.
Dopamine neurons encode trial-by-trial subjective reward value in an auction-like task
Authors: Hill Daniel F. , Hickman Robert W. , Al-Mohammad Alaa , Stasiak Arkadiusz , Schultz Wolfram 
Published: January 2023

ABSTRACTThe dopamine reward prediction error signal is known to be subjective but has so far only been assessed in aggregate choices. However, personal choices fluctuate across trials and thus reflect the instantaneous subjective reward value. In the well-established Becker-DeGroot-Marschak (BDM) auction-like mechanism, participants are encouraged to place bids that accurately reveal their instantaneous subjective reward value; inaccurate bidding results in suboptimal reward (‘incentive compatibility’). In our experiment, male rhesus monkeys became experienced over several years to place accurate BDM bids for juice rewards without specific external constraints. Their bids for physically identical rewards varied trial by trial and increased overall for larger rewards. In these highly experienced animals, responses of midbrain dopamine neurons followed the trial-by-trial variations of bids despite constant, explicitly predicted reward amounts. Inversely, dopamine responses were similar with similar bids for different physical reward amounts. Support Vector Regression demonstrated accurate prediction of the animals’ bids by as few as twenty dopamine neurons. Thus, the phasic dopamine reward signal reflects instantaneous subjective reward value.
DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience
Authors: Gil Ávila Cristina , Bott Felix S. , Tiemann Laura , Hohn Vanessa D. , May Elisabeth S. , Nickel Moritz M. , Zebhauser Paul Theo , Gross Joachim , Ploner Markus 
Published: January 2023

ABSTRACTBiomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher- dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets, the LEMON dataset, containing 213 EEG recordings of healthy participants, and the TDBRAIN dataset, containing 1274 EEG recordings, mainly from patients with a psychiatric condition. Additionally, we performed an exploratory analysis of the LEMON dataset that could inspire biomarkers of healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function.
Prediction Analysis of Preterm Neonates Mortality using Machine Learning Algorithms via Python Programming
Authors: Monfared Vahid , Hashemi Afkham 
Published: January 2023

AbstractPrediction analysis of preterm neonate mortality is necessary and significant for benchmarking and evaluating healthcare services in Hospitals and other medical centers. Application of artificial intelligence and machine learning models, which is a hot topic in medicine/healthcare and engineering, may improve physicians’ skill to predict the preterm neonatal deaths. The main purpose of this research article is to introduce a preterm neonatal mortality risk prediction by means of machine learning/ML predictive models to survive infants using supervised ML models if possible. Moreover, this paper presents some effective parameters and features which affect to survive the infants directly. It means, the obtained model has an accuracy of about 91.5% to predict the status of infant after delivery. After recognizing the critical status for an infant, physicians and other healthcare personnel can help to infant for possible surviving using special medical NICU cares. It has been tried to get some suitable models with high accuracy and comparing the results. In a word, a survival prediction analysis of preterm neonate mortality has been carried out using machine learning methods via Python programming (possible surviving infants after delivery in the hospital).