bluuebunny/crossref_metadata_2025_split huggingface dataset:
The total mRNA concentration buffering system in yeast is global rather than gene-specific
Authors: García-Martínez José , Medina Daniel A. , Bellvís Pablo , Sun Mai , Cramer Patrick , Chávez Sebastián , Pérez-Ortín José E. 
Published: January 2021

AbstractGene expression in eukaryotes does not follow a linear process from transcription to translation and mRNA degradation. Instead it follows a circular process in which cytoplasmic mRNA decay crosstalks with nuclear transcription. In many instances this crosstalk contributes to buffer mRNA at a roughly constant concentration. Whether the mRNA buffering concept operates on the total mRNA concentration or at the gene-specific level, and if the mechanism to do so is a global or a specific one, remain unknown. Here we assessed changes in mRNA concentrations and their synthesis rates along the transcriptome of aneuploid strains of the yeastSaccharomyces cerevisiae. We also assessed mRNA concentrations and their synthesis rates in non sense-mediated decay (NMD) targets in euploid strains. We found that the altered synthesis rates in the genes from the aneuploid chromosome and the changes in their mRNA stabilities were not counterbalanced. In addition, the stability of NMD targets was not specifically compensated by the changes in synthesis rate. We conclude that there is no genetic compensation of NMD mRNA targets in yeast, and total mRNA buffering uses mostly a global system rather than a gene-specific one.
Minimal genetically encoded tags for fluorescent protein labeling in living neurons
Authors: Arsić Aleksandra , Hagemann Cathleen , Stajković Nevena , Schubert Timm , Nikić-Spiegel Ivana 
Published: January 2021

AbstractModern light microscopy, including super-resolution techniques, brought about a demand for small labeling tags that bring the fluorophore closer to the target. This challenge can be addressed by labeling unnatural amino acids (UAAs) with click chemistry. UAAs are site-specifically incorporated into a protein of interest by genetic code expansion. If the UAA carries a strained alkene or alkyne moiety it can be conjugated to a tetrazine-bearing fluorophore via a strain-promoted inverse-electron-demand Diels–Alder cycloaddition (SPIEDAC), a variant of bioorthogonal click chemistry. The minimal size of the incorporated tag and the possibility to couple the fluorophores directly to the protein of interest with single-residue precision make SPIEDAC live-cell labeling unique. However, until now, this type of labeling has not been used in complex, non-dividing cells, such as neurons. Using neurofilament light chain as a target protein, we established SPIEDAC labeling in living primary neurons and applied it for fixed-cell, live-cell, dual-color pulse—chase and super-resolution microscopy. We also show that SPIEDAC labeling can be combined with CRISPR/Cas9 genome engineering for tagging endogenous NFL. Due to its versatile nature and compatibility with advanced microscopy techniques, we anticipate that SPIEDAC labeling will contribute to novel discoveries in neurobiology.
A triple-negative matrix-producing breast carcinoma is arrested by tumor-targetingSalmonella typhimuriumA1-R in a PDOX model
Authors: Hamada Kazuyuki , Yamamoto Jun , Hozumi Chihiro , Zhao Ming , Murata Takuya , Sugisawa Norihiko , Sun Yu , Aoki Yusuke , Nishino Hiroto , Bouvet Michael , Tsunoda Takuya , Hoffman Robert M. 
Published: January 2021

ABSTRACTBackground/AimMatrix-producing breast carcinoma (MPBC), is a rare, recalcitrant and highly aggressive. The present study aimed to determine the efficacy of tumor-targetingSalmonella typhimurium(S. typhimurium) A1-R on a triple-negative MPBC in a patient-derived orthotopic xenograft (PDOX) model.MethodsThe PDOX model was established in the left second mammary gland of a nude mouse by surgical orthotopic implantation (SOI) of the patient triple-negative MPBC PDOX models were randomized into two groups: G1, control group (n=6); G2, tumor-targetingS. typhimuriumA1-R group (n=7, intravenous (i.v.) injection via tail vein, weekly, for two weeks). All mice were sacrificed on day 15. Tumor volume and body weight were measured one time per week.ResultsS. typhimuriumA1-R arrested tumor growth compared to the control group (P = 0.016).ConclusionThe results of the present study suggest thatS. typhimuriumA1-R has future clinical potential in triple-negative MPBC patients.
Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data
Authors: Hu Guoqiang , Li Huanjie , Zhao Wei , Hao Yuxing , Bai Zonglei , Nickerson Lisa D. , Cong Fengyu 
Published: January 2021

AbstractThe study of brain network interactions during naturalistic stimuli facilitates a deeper understanding of human brain function. Intersubject correlation (ISC) analysis of functional magnetic resonance imaging (fMRI) data is a widely used method that can measure neural responses to naturalistic stimuli that are consistent across subjects. However, interdependent correlation values in ISC artificially inflated the degrees of freedom, which hinders the investigation of individual differences. Besides, the existing ISC model mainly focus on similarities between subjects but fails to distinguish neural responses to different stimuli features. To estimate large-scale brain networks evoked with naturalistic stimuli, we propose a novel analytic framework to characterize shared spatio-temporal patterns across subjects in a purely data-driven manner. In the framework, a third-order tensor is constructed from the timeseries extracted from all brain regions from a given parcellation, for all participants, with modes of the tensor corresponding to spatial distribution, time series and participants. Tensor component analysis (TCA) will then reveal spatially and temporally shared components, i.e., naturalistic stimuli evoked networks, their temporal courses of activity and subject loadings of each component. To enhance the reproducibility of the estimation with TCA, a novel spectral clustering method, tensor spectral clustering, was proposed and applied to evaluate the stability of TCA algorithm. We demonstrate the effectiveness of the proposed framework via simulations and real fMRI data collected during a motor task with a traditional fMRI study design. We also apply the proposed framework to fMRI data collected during passive movie watching to illustrate how reproducible brain networks are identified evoked by naturalistic movie viewing.
Cladistic hypotheses as degree of equivalence relational structures: implications for three-item statements
Authors: Rineau Valentin , Prin Stéphane 
Published: January 2021

AbstractThree-item statements, as minimal informative rooted binary phylogenetic trees on three items, are the minimal units of cladistic information. Their importance for phylogenetic reconstruction, consensus and supertree methods relies on both (i) the fact that any cladistic tree can always be decomposed into a set of three-item statements, and (ii) the possibility, at least under some conditions, to build a new cladistic tree by combining all or part of the three-item statements deduced from several prior cladistic trees. In order to formalise such procedures, severalk-adic rules of inference, i.e., rules that allow us to deduce at least one new three-item statement from exactlykother ones, have been identified. However, no axiomatic background has been proposed, and it remains unknown if a particulark-adic rule of inference can be reduced to more basic rules. In order to solve this problem, we propose here to define three-item statements in terms of degree of equivalence relations. Given both the axiomatic definition of the latter and their strong connection to hierarchical classifications, we establish a list of the most basic properties for three-item statements. With such an approach, we show that it is possible to combine five three-item statements from basic rules although they are not combinable only from dyadic rules. Such a result suggests that all higherk-adic rules are well reducible to a finite set of simpler rules.
A Paradoxical Screening Serological Assay for the Diagnosis of Whipple’s Disease (infection with Tropheryma whipplei)
Authors: Liew K.C. , Nguyen Chelsea , Waidyatillake Nilakshi T , Stenos John , Walton Aaron , Athan Eugene , Harris Owen , Graves Stephen 
Published: January 2021

ABSTRACTWhipple’s disease (WD) is a rare infection due to Tropheryma whipplei. Following in-vitro cultivation of T. whipplei, an indirect-immunofluorescence serological assay (IFA) was developed. We tested the hypothesis that this assay could be used to either identify WD patients, or rule out WD, in patients in whom the diagnosis is being considered, based on the antibody titers of their IgM and IgG antibody responses. In this small study fourteen WD patients and 22 healthy volunteers’ sera were obtained from across Australia. All specimens were coded and de-identified before testing. A patient with an IgG antibody titer of ≤1:16 may have WD [sensitivity 57% (8/14) and specificity close to 100% (22/22)]. High IgM antibody titers (≥1:256) were more common in WD patients [sensitivity 50% (7/14) and specificity 86% (19/22)] than in controls. The area under Receiver-Operator-Characteristic curve for IgG in the IFA assay was 0.84 (95% CI 0.69-1.00). At an IgG antibody titer of ≤1:16 the Youden’s index was 0.57. WD patients’ under-produce IgG antibody to T.whipplei but are more likely to over-produce IgM antibodies. This screening IFA serological assay may be clinically useful in detecting those with a possible diagnosis of WD. Patients with an IgG antibody titer of ≤1:16 and an IgM antibody titer of ≥1:256 may have WD and should proceed to a tissue biopsy and PCR for confirmation. Further validation of this assay, by increasing the sample size, by testing it in patients with non-WD disease and trialing in other countries should be undertaken.
SARS-CoV-2 seropositivity and seroconversion in patients undergoing active cancer-directed therapy
Authors: Sun Lova , Surya Sanjna , Goodman Noah G. , Le Anh N. , Kelly Gregory , Owoyemi Olutosin , Desai Heena , Zheng Cathy , DeLuca Shannon , Good Madeline L. , Hussain Jasmin , Jeffries Seth D. , Kry Yolanda R. , Kugler Emily M. , Mansour Maikel , Ndicu John , Osei-Akoto AnnaClaire , Prior Timothy , Pundock Stacy L. , Varughese Lisa A. , Weaver JoEllen , Doucette Abigail , Dudek Scott , Verma Shefali Setia , Gouma Sigrid , Weirick Madison E. , McAllister Christopher M. , Bange Erin , Gabriel Peter , Ritchie Marylyn , Rader Daniel J. , Vonderheide Robert H. , Schuchter Lynn M , Verma Anurag , Maillard Ivan , Mamtani Ronac , Hensley Scott E. , Gross Robert , Wileyto E. Paul , Huang Alexander C. , Maxwell Kara N. , DeMichele Angela 
Published: January 2021

AbstractMultiple studies have demonstrated the negative impact of cancer care delays during the COVID-19 pandemic, and transmission mitigation techniques are imperative for continued cancer care delivery. To gauge the effectiveness of these measures at the University of Pennsylvania, we conducted a longitudinal study of SARS-CoV-2 antibody seropositivity and seroconversion in patients presenting to infusion centers for cancer-directed therapy between 5/21/2020 and 10/8/2020. Participants completed questionnaires and had up to five serial blood collections. Of 124 enrolled patients, only two (1.6%) had detectable SARS-CoV-2 antibodies on initial blood draw, and no initially seronegative patients developed newly detectable antibodies on subsequent blood draw(s), corresponding to a seroconversion rate of 0% (95%CI 0.0-4.1%) over 14.8 person-years of follow up, with a median of 13 healthcare visits per patient. These results suggest that cancer patients receiving in-person care at a facility with aggressive mitigation efforts have an extremely low likelihood of COVID-19 infection.
EmptyNN: A neural network based on positive-unlabeled learning to remove cell-free droplets and recover lost cells in single-cell RNA sequencing data
Authors: Yan Fangfang , Zhao Zhongming , Simon Lukas M. 
Published: January 2021

ABSTRACTDroplet-based single-cell RNA sequencing (scRNA-seq) has significantly increased the number of cells profiled per experiment and revolutionized the study of individual transcriptomes. However, to maximize the biological signal robust computational methods are needed to distinguish cell-free from cell-containing droplets. Here, we introduce a novel cell-calling algorithm called EmptyNN, which trains a neural network based on positive-unlabeled learning for improved filtering of barcodes. We leveraged cell hashing and genetic variation to provide ground-truth. EmptyNN accurately removed cell-free droplets while recovering lost cell clusters, and achieved an Area Under the Receiver Operating Characteristics (AUROC) of 94.73% and 96.30%, respectively. The comparisons to current state-of-the-art cell-calling algorithms demonstrated the superior performance of EmptyNN, as measured by the number of recovered cell-containing droplets and cell types. EmptyNN was further applied to two additional datasets and showed good performance. Therefore, EmptyNN represents a powerful tool to enhance scRNA-seq quality control analyses.
Repurposing of an Antifungal Drug against Gastrointestinal Stromal Tumors
Authors: Arulanandam Charli Deepak , Prathiviraj R , Kaveriyappan Govindarajan Rasiravathanahalli 
Published: January 2021

ABSTRACTDrug discovery is an important research area to improve human health. Currently, treatment of gastrointestinal stromal tumors (GISTs) is unsuccessful due to drug-resistance, hence, there is a demand for alternatives. Often, there is limited time available for toxicological assessments and a lack of safer drugs. It is possible to identify new drugs from existing approved drugs possessing another purpose in the clinical lines. In this study, virtual screening of some Food and Drug Administration (FDA-USA) approved and available antifungal and antineoplastic drugs were performed against GISTs based on docking affinity of human platelet-derived growth factor receptor alpha (PDGFRA) with these drugs to identify a suitable PDGFRA inhibitor for saving the time required for toxicity screening. The protein and ligand-binding affinity were investigated for five FDA approved antineoplastic and thirty-six antifungal drugs against PDGFRA using the AutoDock (AD) and AutoDock Vina (ADV) software. Based on docking score and inhibition constant (Ki), Itraconazole was predicted as a better PDGFRA inhibitor among all the computationally tested drugs.
Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference
Authors: Deserno Lorenz , Moran Rani , Michely Jochen , Lee Ying , Dayan Peter , Dolan Raymond J. 
Published: January 2021

AbstractDopamine is implicated in signalling model-free (MF) reward prediction errors and various aspects of model-based (MB) credit assignment and choice. Recently, we showed that cooperative interactions between MB and MF systems include guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test the hypothesis that enhancing dopamine levels, using levodopa, boosts the guidance of MF credit assignment by MB inference. We found that levodopa enhanced retrospective guidance of MF credit assignment by MB inference, without impacting on MF and MB influences per se. This drug effect positively correlated with working memory, but only in a context where reward needed to be recalled for MF credit assignment. The dopaminergic enhancement in MB-MF interactions correlated negatively with a dopamine-dependent change in MB credit assignment, possibly reflecting a potential trade-off between these two components of behavioural control. Thus, our findings demonstrate that dopamine boosts MB inference during guidance of MF learning, supported in part by working memory, but trading-off with a dopaminergic enhancement of MB credit assignment. The findings highlight a novel role for a DA influence on MB-MF interactions.
High-resolution model of Arabidopsis Photosystem II reveals the consequences of digitonin-extraction
Authors: Graça André T. , Hall Michael , Persson Karina , Schröder Wolfgang P. 
Published: January 2021

AbstractIn higher plants, the photosynthetic process is performed and regulated by Photosystem II (PSII).Arabidopsis thalianawas the first higher plant with a fully sequenced genome, conferring it the status of a model organism; nonetheless, a high-resolution structure of its Photosystem II is missing. We present the first Cryo-EM high-resolution structure of Arabidopsis PSII supercomplex with average resolution of 2.79 Å, an important model for future PSII studies. The digitonin extracted PSII complexes demonstrate the importance of: the LHG2630-lipid-headgroup in the trimerization of the light-harvesting complex II; the stabilization of the PsbJ subunit and the CP43-loop E by DGD520-lipid; the choice of detergent for the integrity of membrane protein complexes. Furthermore, our data shows at the anticipated Mn4CaO5-site a single metal ion density as a reminiscent early stage of Photosystem II photoactivation.
How the healthy ageing brain supports semantic binding during language comprehension
Authors: Markiewicz Roksana , Segaert Katrien , Mazaheri Ali 
Published: January 2021

AbstractSemantic binding refers to constructing complex meaning based on elementary building blocks. Using EEG, we investigated the age-related changes in modulations of oscillatory brain activity supporting lexical retrieval and semantic binding. Young and older adult participants were visually presented two-word phrases, which for the first word revealed a lexical retrieval signature (e.g.swiftvs.swrfeq) and for the second word revealed a semantic binding signature (e.g.horsein a semantic binding “swifthorse” vs. no binding “swrfeqhorse” context). The oscillatory brain activity associated with lexical retrieval as well as semantic binding significantly differed between healthy older and young adults. Specifically for lexical retrieval, we found that different age groups exhibited opposite patterns of theta and alpha modulation, which as a combined picture suggest that lexical retrieval is associated with different and delayed signatures in older compared to young adults. For semantic binding, in young adults we found a signature in the low-beta range centred around the target word onset (i.e. a smaller low-betaincrease for binding relative to no binding), while in healthy older adults we found an opposite binding signature about ~500ms later in the low- and high-beta range (i.e. a smaller low- and high-betadecrease for binding relative to no binding). The novel finding of a different and delayed oscillatory signature for semantic binding in healthy older adults reflects that the integration of word meaning into the semantic context takes longer and relies on different mechanisms in healthy older compared to young adults.
A temporal parcellation of the sensory-evoked responses during the rubber hand illusion reveals manipulation- and illusion-specific correlates
Authors: Sciortino Placido , Kayser Christoph 
Published: January 2021

AbstractThe neurophysiological processes reflecting body illusions such as the rubber hand remain debated. In particular, previous studies investigating neural responses evoked by the illusion-inducing stimuli provide diverging reports as to when these responses reflect the illusory state. To resolve these controversies in previous work we applied multivariate (cross-) classification to EEG responses obtained during the rubber hand illusion and multiple control conditions in human participants. These controls were designed to test for markers of the illusory state that generalize across the spatial arrangements of limbs or the specific nature of the control condition (rubber hand or participant’s real hand) - hence which are independent of the precise experimental conditions used as contrast for the illusion. This revealed a parcellation of evoked responses into a temporal sequence of events that each differentiate the illusion and control conditions along distinct dimensions. Importantly, around 130-150 ms following stimulus onset the neurophysiological signals reliably differentiated the illusory-state from all non-illusion epochs. This neurophysiological signature was not correlated with changes in skin conductance accompanying the illusion, suggesting that neurophysiological and bodily signals reflect distinct illusion-related processes.
The Pentose Phosphate Pathway constitutes a major metabolic hub in pathogenicFrancisella
Authors: Rytter Héloise , Jamet Anne , Ziveri Jason , Ramond Elodie , Coureuil Mathieu , Lagouge-Roussey Pauline , Euphrasie Daniel , Tros Fabiola , Goudin Nicolas , Chhuon Cerina , Nemazanyy Ivan , de Moraes Fabricio Edgar , Labate Carlos , Guerrera Ida Chiara , Charbit Alain 
Published: January 2021

AbstractMetabolic pathways are now considered as intrinsic virulence attributes of pathogenic bacteria and hence represent potential targets for anti-bacterial strategies. Here, we addressed the role of the pentose phosphate pathway (PPP) and its connections with other metabolic pathways in the pathophysiology ofFrancisella novicida. The involvement of the PPP inFrancisellaintracellular life cycle was first demonstrated with the study of PPP inactivation mutants. Indeed, inactivation oftktA, rpiAorrpegenes, severely impaired intramacrophagic multiplication during the first 24 hours. Time-lapse video microscopy demonstrated thatrpiAandrpemutants were able to resume late intracellular bacterial multiplication. To get further insight into the links between the PPP and other metabolic networks of the bacterium, we next performed a thorough proteo-metabolomic analysis of these mutants. We show that the PPP constitutes a major bacterial metabolic hub with multiple connections with glycolysis, tricarboxylic acid cycle and other pathways, such as fatty acid degradation and sulfur metabolism. Hence, our study highlights how the PPP is instrumental toFrancisellapathogenesis and growth in its intracellular niche.