bluuebunny/crossref_metadata_2025_split huggingface dataset:
Midbrain dopamine neurons provide teaching signals for goal-directed navigation
Authors: Farrell Karolina , Lak Armin , Saleem Aman B 
Published: February 2021

SummaryIn naturalistic environments, animals navigate in order to harvest rewards. Successful goal-directed navigation requires learning to accurately estimate location and select optimal state-dependent actions. Midbrain dopamine neurons are known to be involved in reward value learning1–13. They have also been linked to reward location learning, as they play causal roles in place preference14,15and enhance spatial memory16–21. Dopamine neurons are therefore ideally placed to provide teaching signals for goal-directed navigation. To test this, we imaged dopamine neural activity as mice learned to navigate in a closed-loop virtual reality corridor and lick to report the reward location. Across learning, phasic dopamine responses developed to visual cues and trial outcome that resembled reward prediction errors and indicated the animal’s estimate of the reward location. We also observed the development of pre-reward ramping activity, the slope of which was modulated by both learning stage and task engagement. The slope of the dopamine ramp was correlated with the accuracy of licks in the next trial, suggesting that the ramp sculpted accurate location-specific action during navigation. Our results indicate that midbrain dopamine neurons, through both their phasic and ramping activity, provide teaching signals for improving goal-directed navigation.HighlightsWe investigated midbrain dopamine activity in mice learning a goal-directed navigation task in virtual realityPhasic dopamine signals reflected prediction errors with respect to subjective estimate of reward locationA slow ramp in dopamine activity leading up to reward location developed over learning and was enhanced with task engagementPositive ramp slopes were followed by improved performance on subsequent trials, suggesting a teaching role during goal-directed navigation
The IL-10GFP(VeRT-X) mouse strain is not suitable for the detection of IL-10 production by granulocytes during lung inflammation
Authors: Özkan Müge , Eskiocak Yusuf Cem , Wingender Gerhard 
Published: February 2021

AbstractThe clear and unequivocal identification of immune effector functions is essential to understand immune responses. The cytokine IL-10 is a critical immune regulator and was shown, for example, to limit pathology during various lung diseases. However, the clear identification of IL-10-producing cells is challenging and, therefore, reporter mouse lines were developed to facilitate their detection. Several such reporter lines utilize GFP, including the IL-10GFP(VeRT-X) reporter strain studied here. In line with previous reports, we found that this IL-10GFPline faithfully reports on the IL-10 production of lymphoid cells. However, we show that the IL-10GFPreporter is not suitable to analyse IL-10 production of myeloid cells during inflammations. During inflammation, the autofluorescence of myeloid cells increased to an extent that entirely masked the IL-10-specific GFP-signal. Our data illustrate a general and important technical caveat using GFP-reporter lines for the analysis of myeloid cells and suggest that previous reports on effector functions of myeloid cells using such GFP-based reporters might require re-evaluation.
Measuring the unknown: an estimator and simulation study for assessing case reporting during epidemics
Authors: Jarvis Christopher I , Gimma Amy , Finger Flavio , Morris Tim P , Thompson Jennifer A , Waroux Olivier le Polain de , Edmunds W John , Funk Sebastian , Jombart Thibaut 
Published: February 2021

AbstractThe fraction of cases reported, known as ‘reporting’, is a key performance indicator in an outbreak response, and an essential factor to consider when modelling epidemics and assessing their impact on populations. Unfortunately, its estimation is inherently difficult, as it relates to the part of an epidemic which is, by definition, not observed.We introduce a simple statistical method for estimating reporting, initially developed for the response to Ebola in Eastern Democratic Republic of the Congo (DRC), 2018-2020. This approach uses transmission chain data typically gathered through case investigation and contact tracing, and uses the proportion of investigated cases with a known, reported infector as a proxy for reporting. Using simulated epidemics, we study how this method performs for different outbreak sizes and reporting levels. Results suggest that our method has low bias, reasonable precision, and despite sub-optimal coverage, usually provides estimates within close range (5-10%) of the true value.Being fast and simple, this method could be useful for estimating reporting in real-time in settings where person-to-person transmission is the main driver of the epidemic, and where case investigation is routinely performed as part of surveillance and contact tracing activities.Author summaryWhen responding to epidemics of infectious diseases, it is essential to estimate how many cases are not being reported. Unfortunately reporting, the proportion of cases actually observed, is difficult to estimate during an outbreak, as it typically requires large surveys to be conducted on the affected populations. Here, we introduce a method for estimating reporting from case investigation data, using the proportion of cases with a known, reported infector. We used simulations to test the performance of our approach by mimicking features of a recent Ebola epidemic in the Democratic Republic of the Congo. We found that despite some uncertainty in smaller outbreaks, our approach can be used to obtain informative ballpark estimates of reporting under most settings. This method is simple and computationally inexpensive, and can be used to inform the response to any epidemic in which transmission events can be uncovered by case investigation.
Invariant Differential Expression Analysis Reveals Mechanism of Cancer Resistance to Cell Cycle Inhibitors
Authors: Chatterjee Amit , Pandey Sonalisa , Danda Ravikanth , Ranjith Kumar R , Maheswari S , Khetan Vikas , Rishi Pukhraj , Ramaprabhu S , Elchuri Sailaja V , Sahoo Debashis 
Published: February 2021

AbstractRetinoblastoma (RB) is a good model to study drug resistance to cell-cycle inhibitors because it is driven by mutations in the core components of cell-cycle, i.e, Rb gene. However, there is limited gene expression dataset in RB which has major reproducibility issues. We have developed invariant differential expression analysis (iDEA) that improves the state of the art in differential expression analysis (DEA). iDEA uses strong Boolean implication relationships in a large diverse human dataset GSE119087 (n = 25,955) to filter the noisy differentially expressed genes (DEGs). iDEA was applied to RB datasets and a gene signature was computed that led to prediction and mechanism of drug sensitivity. The prediction was confirmed using drugs-sensitive/resistant RB cell-lines and mouse xenograft models using CDC25 inhibitor NSC663284. iDEA improved reproducibility of differential expression across diverse retina/RB cohorts and RB cell-lines with different drug sensitivity (Y79/Weri vs NCC). Pathway analysis revealed WNT/β-catenin involved in distinguishing drug sensitivity to CDC25 inhibitor NSC663284. NSC663284 inhibited tumour cell proliferation in mouse xenograft model containing Y79 cells indicating novel therapeutic option in RB. Invariant differentially expressed genes (iDEGs) are robustly associated with outcome in diverse cancer datasets and supports for a fundamental mechanism of drug resistance.
Chromatin accessibility determines intron retention in a cell type-specific manner
Authors: Petrova Veronika , Song Renhua ,   DEEP Consortium, Nordström Karl J.V. , Walter Jörn , Wong Justin J.-L. , Armstrong Nicola J. , Rasko John E.J. , Schmitz Ulf 
Published: February 2021

SummaryDynamic intron retention (IR) in vertebrate cells is of widespread biological importance. Aberrant IR is associated with numerous human diseases including cancer. Despite consistent reports demonstrating intrinsic sequence features that predispose introns to become retained, conflicting findings about cell type-specific IR regulation demand a systematic analysis in a controlled experimental setting. We integrated matched transcriptomics and epigenetics data (including DNA methylation, nucleosome occupancy, histone modifications) from primary human myeloid and lymphoid cells. Using machine learning we trained two complementary models to determine the role of epigenetic factors in the regulation of IR. We show that increased chromatin accessibility contributes substantially to the retention of introns in a cell-specific manner. We also confirm that intrinsic characteristics of introns are key for them to evade splicing. With mounting reports linking pathogenic alterations to RNA processing, our findings may have profound implications for the design of therapeutic approaches targeting aberrant splicing.
Harmonised segmentation of neonatal brain MRI
Authors: Grigorescu Irina , Vanes Lucy , Uus Alena , Batalle Dafnis , Cordero-Grande Lucilio , Nosarti Chiara , David Edwards A. , Hajnal Joseph V. , Modat Marc , Deprez Maria 
Published: February 2021

ABSTRACTDeep learning based medical image segmentation has shown great potential in becoming a key part of the clinical analysis pipeline. However, many of these models rely on the assumption that the train and test data come from the same distribution. This means that such methods cannot guarantee high quality predictions when the source and target domains are dissimilar due to different acquisition protocols, or biases in patient cohorts. Recently, unsupervised domain adaptation (DA) techniques have shown great potential in alleviating this problem by minimizing the shift between the source and target distributions, without requiring the use of labelled data in the target domain. In this work, we aim to predict tissue segmentation maps onT2-weighted (T2w) magnetic resonance imaging (MRI) data of an unseen preterm-born neonatal population, which has both different acquisition parameters and population bias when compared to our training data. We achieve this by investigating two unsupervised DA techniques with the objective of finding the best solution for our problem. We compare the two methods with a baseline fully-supervised segmentation network and report our results in terms of Dice scores obtained on our ground truth test dataset. Moreover, we analyse tissue volumes and cortical thickness (CT) measures of the harmonised data on a subset of the population matched for gestational age (GA) at birth and postmenstrual age (PMA) at scan. Finally, we demonstrate the applicability of the harmonised cortical gray matter maps with an analysis comparing term and preterm-born neonates and a proof-of-principle investigation of the association between CT and a language outcome measure.
Heterogeneous interactions and polymer entropy decide organization and dynamics of chromatin domains
Authors: Kumari Kiran , Prakash J. Ravi , Padinhateeri Ranjith 
Published: February 2021

AbstractChromatin is known to be organized into multiple domains of varying sizes and compaction. While these domains are often imagined as static structures, they are highly dynamic and show cell-to-cell variability. Since processes such as gene regulation and DNA replication occur in the context of these domains, it is important to understand their organization, fluctuation and dynamics. To simulate chromatin domains, one requires knowledge of interaction strengths among chromatin segments. Here, we derive interaction strength parameters from experimentally known contact maps and use them to predict chromatin organization and dynamics. Taking two domains on the human chromosome as examples, we investigate its 3D organization, size/shape fluctuations, and dynamics of different segments within a domain, accounting for hydrodynamic effects. Considering different cell types, we quantify changes in interaction strengths and chromatin shape fluctuations in different epigenetic states. Perturbing the interaction strengths systematically, we further investigate how epigenetic-like changes can alter the spatio-temporal nature of the domains. Our results show that heterogeneous weak interactions are crucial in determining the organization of the domains. Computing effective stiffness and relaxation times, we investigate how perturbations in interactions affect the solid-like and liquid-like nature of chromatin domains. Quantifying dynamics of chromatin segments within a domain, we show how the competition between polymer entropy and interaction energy influence the timescales of loop formation and maintenance of stable loops.
Potent neutralization antibodies induced by a recombinant trimeric Spike protein vaccine candidate containing PIKA adjuvant for COVID-19
Authors: Tong Jiao , Zhu Chenxi , Lai Hanyu , Feng Chunchao , Zhou Dapeng 
Published: February 2021

AbstractNeutralizing antibodies are critical to prevent corona virus infection. The structures of immunogens to elicit most potent neutralization antibodies are still under investigation. Here we tested the immunogenicity of the trimeric, full length Spike protein with 2 proline mutations to preserve its prefusion conformation. Recombinant trimeric Spike protein expressed by CHO cells was used with polyI:C (PIKA) adjuvant to immunize mice by 0-7-14 day schedule. The results showed that Spike-specific antibody was induced at day 21 with titer of more than 50,000 in average as measured by direct binding to Spike protein. The titer of neutralization reached more than 1000 in average when tested by a pseudo-virus system, using monoclonal antibodies (40592-MM57 and 40591-MM43) with neutralizing IC50 at 1 μg/ml as standards. Protein/peptide array showed that the antibodies induced by trimeric S protein vaccine bind similarly to natural infection with the receptor binding domain (RBD) as major immunodominant region. No linear epitopes were found in RBD, although several linear epitopes were found in C-terminal domain right after RBD, and heptad repeat regions. Our study supports the efficacy of recombinant trimeric Spike protein vaccine candidate for COVID-19, with excellent safety and readiness for storage and distribution in developing countries.
The Need for Sustainable Leadership in Academia – a German Case Study
Authors: Haage Verena , Voss Linn , Nguyen Daniela , Eggert Friderike 
Published: February 2021

AbstractAcademic leaders are selected based on their publication record, citation index and acquisition of third party funding. However, heading a successful research team, also requires leadership skills. Despite the clear need, leadership development has been systematically neglected in the present academic system. At the same time, growing evidence suggests that leadership styles of academic supervisors can dramatically affect the mental health of academic employees as well as drive highly skilled researchers out of academia. Here, we assessed the current state of academic leadership in the German academic system by surveying 368 participants currently employed in academia in Germany. We report that 64% of current academic leaders did not feel prepared for their current position while 86% of participants expressed their interest in leadership development programs offered by their research institutions. Our results highlight the demand for leadership development programs in German academic institutions to ensure a more efficient academic system.
Broadly reactive human monoclonal antibodies targeting the pneumococcal histidine triad protein protect against fatal pneumococcal infection
Authors: Huang Jiachen , Gingerich Aaron D. , Royer Fredejah , Paschall Amy V. , Pena-Briseno Alma , Avci Fikri Y. , Mousa Jarrod J. 
Published: February 2021

AbstractStreptococcus pneumoniaeremains a leading cause of bacterial pneumonia despite the widespread use of vaccines. While vaccines are effective at reducing the incidence of most vaccine-included serotypes, a rise in infection due to non-vaccine serotypes, and moderate efficacy against some vaccine included serotypes have contributed to high disease incidence. Additionally, numerous isolates ofS. pneumoniaeare antibiotic or multi-drug resistant. Several conserved pneumococcal proteins prevalent in the majority of serotypes have been examined as vaccines in preclinical and clinical trials. An additional, yet unexplored tool for disease prevention and treatment is the use of human monoclonal antibodies (mAbs) targeting conserved pneumococcal proteins. Here, we isolate the first human mAbs (PhtD3, PhtD6, PhtD7, PhtD8, PspA16) against the pneumococcal histidine triad protein (PhtD), and the pneumococcal surface protein A (PspA), two conserved and protective antigens. mAbs to PhtD target diverse epitopes on PhtD, and mAb PspA16 targets the N-terminal segment of PspA. The PhtD-specific mAbs bind to multiple serotypes, while mAb PspA16 serotype breadth is limited. mAbs PhtD3 and PhtD8 prolong the survival of mice infected with pneumococcal serotype 3. Furthermore, mAb PhtD3 prolongs the survival of mice in intranasal and intravenous infection models with pneumococcal serotype 4, and in mice infected with pneumococcal serotype 3 when administered 24 hours after pneumococcal infection. All PhtD and PspA mAbs demonstrate opsonophagocytic activity, suggesting a potential mechanism of protection. Our results provide new human mAbs for pneumococcal disease prevention and treatment, and identify epitopes on PhtD and PspA recognized by human B cells.
How the replication and transcription complex functions in jumping transcription of SARS-CoV-2
Authors: Liang Jianguang , Shi Jinsong , Chen Shunmei , Duan Guangyou , Yang Fan , Cheng Zhi , Li Xin , Ruan Jishou , Mi Dong , Gao Shan 
Published: February 2021

AbstractBackgroundCoronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC) and 16 non-structural proteins, named NSP1-16.ResultsIn the present study, we proposed a two-route model to answer how the RTC functions in the jumping transcription of CoVs. The key step leading to this model was that the motif AAACH for METTL3 recognition flanking the transcription regulatory sequence (TRS) motif was discovered to determine the m6A methylation of SARS-CoV-2 RNAs, by reanalyzing public Nanopore RNA-seq data. As the most important finding, TRS hairpins were reported for the first time to interpret NSP15 cleavage, RNA methylation of CoVs and their association at the molecular level. In addition, we reported canonical TRS motifs of all CoVs to prove the importance of our findings.ConclusionsThe main conclusions are: (1) TRS hairpins can be used to identify recombination regions in CoV genomes; (2) RNA methylation of CoVs participates in the determination of the RNA secondary structures by affecting the formation of base pairing; and (3) The eventual determination of the CoV RTC global structure needs to consider METTL3 in the experimental design. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, providing a crucial basis for future studies.
The role of genus and life span in predicting seed and vegetative trait variation and correlation inLathyrus,Phaseolus, andVicia(Fabaceae)
Authors: Herron Sterling A. , Rubin Matthew J. , Albrecht Matthew A. , Long Quinn G. , Sandoval Marissa C. , Miller Allison J. 
Published: February 2021

ABSTRACTPREMISE OF THE STUDYAnnual and perennial life history transitions are abundant among angiosperms, and understanding the phenotypic variation underlying life span shifts is a key endeavor of plant evolutionary biology. Comparative analyses of trait variation and correlation networks among annual and perennial plants is increasingly important as new perennial crops are being developed in a predominately annual-based agricultural setting. However, it remains unclear how seed to vegetative growth trait relationships may correlate with life span.METHODSWe measured 29 annual and perennial congeneric species of three herbaceous legume genera (Lathyrus,Phaseolus, andVicia) for seed size and shape, germination proportion, and early vegetative height and leaf growth over three months in order to assess relative roles of genus and life span in predicting phenotypic variation and correlation.KEY RESULTSGenus was the greatest predictor of seed size and shape variation, while life span consistently predicted static vegetative growth traits. Correlation networks revealed that annual species had significant associations between seed traits and vegetative traits, while perennials had no significant seed-vegetative associations. Each genus also differed in the extent of integration between seed and vegetative traits, as well as within-vegetative trait correlation patterns.CONCLUSIONSGenus and life span were important for predicting aspects of early life stage phenotypic variation and trait relationships. Differences in phenotypic correlation may indicate selection on seed size traits will impact vegetative growth differently depending on life span, which has important implications for nascent perennial breeding programs.
Eliciting a potent antitumor immune response by expressing tumor antigens in a skin commensal
Authors: Chen Y. Erin , Atabakhsh Katayoon , Dimas Alex , Nagashima Kazuki , Fischbach Michael A. 
Published: February 2021

ABSTRACTImmune modulation has become central to treating cancer. However, global immune stimulation is only effective in a subset of patients and can lead to serious complications, including colitis and type I diabetes. Newer modalities like engineered T cells and tumor vaccines are more specific, but they have shown limited efficacy in solid tumors and are difficult to scale. Bacterial strains from the human microbiome can induce antigen-specific T cells to help maintain barrier function. Here, we redirect CD8+ and CD4+ T cells elicited by the skin commensalStaphylococcus epidermidisto recognize tumor cells by expressing tumor-derived antigens in the bacterial cell.S. epidermidisexpressing the model antigen ovalbumin (S. epidermidis-OVA) stimulates antigen-specific CD8+ and CD4+ T cells in vitro. The subcellular localization of the antigen skews the response: cell wall-attached OVA preferentially stimulates CD8+ T cells whereas secreted OVA predominantly induces CD4+ T cells. In a syngeneic tumor model (OVA-expressing B16 melanoma), mice colonized topically withS. epidermidis-OVA exhibit a marked reduction in subcutaneous tumor volume compared to mice colonized withS. epidermidisexpressing mCherry; this effect is dependent on live bacteria and a combination of CD8+ and CD4+ T cells.S. epidermidis-OVA also reduces tumor burden when tumor cells are injected intravenously (a model of metastasis), demonstrating that the antitumor effect operates in tissues distant from the site of bacterial colonization.S. epidermidisstrains expressing neoantigen peptides from the B16 tumor cell line exhibit potent antitumor efficacy without inducing an autoimmune response against melanocytes in healthy tissue. Antigen-expressing colonists are a simple but powerful strategy to elicit a targeted T cell response in the context of cancer and other diseases.