bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-omic rejuvenation of human cells by maturation phase transient reprogramming
Authors: Gill Diljeet , Parry Aled , Santos Fátima , Hernando-Herraez Irene , Stubbs Thomas M. , Milagre Inês , Reik Wolf 
Published: January 2021

AbstractAgeing is the gradual decline in organismal fitness that occurs over time leading to tissue dysfunction and disease. At the cellular level, ageing is associated with reduced function, altered gene expression and a perturbed epigenome. Somatic cell reprogramming, the process of converting somatic cells to induced pluripotent stem cells (iPSCs), can reverse these age-associated changes. However, during iPSC reprogramming somatic cell identity is lost, and can be difficult to reacquire as re-differentiated iPSCs often resemble foetal rather than mature adult cells. Recent work has demonstrated that the epigenome is already rejuvenated by the maturation phase of reprogramming, which suggests full iPSC reprogramming is not required to reverse ageing of somatic cells. Here we have developed the first “maturation phase transient reprogramming” (MPTR) method, where reprogramming factors are expressed until this rejuvenation point followed by withdrawal of their induction. Using dermal fibroblasts from middle age donors, we found that cells reacquire their fibroblast identity following MPTR, possibly as a result of persisting epigenetic memory at enhancers. Excitingly, our method substantially rejuvenated multiple cellular attributes including the transcriptome, which was rejuvenated by around 30 years as measured by a novel transcriptome clock. The epigenome, including H3K9me3 histone methylation levels and the DNA methylation ageing clock, was rejuvenated to a similar extent. The magnitude of rejuvenation instigated by MTPR is substantially greater than that achieved in previous transient reprogramming protocols. MPTR fibroblasts produced youthful levels of collagen proteins, suggesting functional rejuvenation. Overall, our work demonstrates that it is possible to separate rejuvenation from pluripotency reprogramming, which should facilitate the discovery of novel anti-ageing genes and therapies.HighlightsWe developed a novel method by which human fibroblasts are reprogrammed until the maturation phase of iPSCs and are then returned to fibroblast identityDNA methylation memory in fibroblast enhancers may allow recovery of cell identity when fibroblast gene expression programmes are already extinctMolecular measures of ageing including transcriptome and DNA methylation clocks and H3K9me3 levels reveal robust and substantial rejuvenationFunctional rejuvenation of fibroblasts by MPTR is suggested by reacquisition of youthful levels of collagen proteins
Chitinase 3-like-1 Stimulates PD-L1 and Other Immune Checkpoint Inhibitors
Authors: Ma Bing , Akosman Bedia , Kamle Suchitra , Lee Chang-Min , Koo Ja Seok , Lee Chun Geun , Elias Jack A. 
Published: January 2021

ABSTRACTPD-1 and its ligand PD-L1 are major mediators of tumor-induced immunosuppression. Chitinase 3-like-1 (Chi3l1) is induced in many cancers where it portends a poor prognosis and contributes to tumor metastasis. Here we demonstrate that Chi3l1 regulates the expression of PD-L1, PD-L2, PD-1 and LAG3 in melanoma lung metastasis. Chi3l1 stimulates macrophage PD-L1 expression and mediates optimal IFN-γ-stimulated PD-L1 expression via IL-13Rα2. We also demonstrate that RIG-like helicase innate immune activation suppresses Chi3l1, PD-L1, LAG3 and pulmonary metastasis. At least additive antitumor responses were seen in metastasis models treated simultaneously with individual antibodies against PD-1 and Chi3l1. At least additive cytotoxic T cell-induced tumor cell death was also seen in co-cultures of T and tumor cells treated with antibodies that target Chi3l1 and PD-1. Thus, Chi3l1 contributes to pulmonary metastasis by stimulating the PD1-PD-L1 axis and other checkpoint molecules. The simultaneous targeting of Chi3l1 and the PD-1-PD-L1 axis, represents a promising therapeutic strategy for pulmonary metastasis.
RIPK3 promoter hypermethylation in hepatocytes protects from bile acid induced inflammation and necroptosis
Authors: Hoff Jessica , Xiong Ling , Kammann Tobias , Neugebauer Sophie , Micheel Julia M. , Ghait Mohamed , Deshmukh Sachin , Gaßler Nikolaus , Bauer Michael , Press Adrian T. 
Published: January 2021

AbstractBackground & AimsNecroptosis facilitates cell death in a controlled manner and is employed by many cell types following injury. It plays a major role in various liver diseases, albeit the cell type-specific regulation of necroptosis in the liver and especially hepatocytes has not yet been conceptualized.Approaches & ResultsHere, we demonstrate that DNA methylation suppresses RIPK3 expression in human hepatocytes and HepG2 cells. In diseases leading to cholestasis the RIPK3 expression is induced in mice and humans in a cell-type specific manner. Over-expression of RIPK3 in HepG2 cells leads immediately to RIPK3 activation by phosphorylation that is further modulated by different bile acids.ConclusionBile acids mediated RIPK3 activation facilitates the secretion and expression of IL-8 via the JNK-pathway, suggesting hepatocytes suppress RIPK3 expression to protect themselves from bile acid induced necroptosis and inflammation but in chronical liver diseases associated with cholestasis induction of RIPK3 expression may be an early event signaling danger and repair through release of IL-8.Graphical abstract
Refinement ofα-synuclein ensembles against SAXS data: Comparison of force fields and methods
Authors: Ahmed Mustapha Carab , Skaanning Line K. , Jussupow Alexander , Newcombe Estella A. , Kragelund Birthe B. , Camilloni Carlo , Langkilde Annette E. , Lindorff-Larsen Kresten 
Published: January 2021

AbstractThe inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulations times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the proteinα-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.
Topological Sholl Descriptors For Neuronal Clustering and Classification
Authors: Khalil Reem , Kallel Sadok , Farhat Ahmad , Dłotko Paweł 
Published: January 2021

MotivationGiven that neuronal morphology can widely vary among cell classes, brain regions, and animal species, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. However, robust and unbiased computational methods currently used to characterize groups of neurons are scarce.ResultsIn this work, we introduce a novel and powerful technique to study neuronal morphologies. We develop mathematical descriptors that quantitatively characterize structural differences among neuronal cell types and thus allow for their accurate classification. Each Sholl descriptor that is assigned to a neuron is a function of a distance from the soma with values in real numbers or more general metric spaces. To illustrate the use of Sholl descriptors, six datasets were retrieved from the large public repositoryhttp://neuromorpho.org/comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional techniques and thus provide a practical and effective approach to the classification of diverse neuronal cell types, with the potential for discovery of subclasses of neurons.
Selective metal extraction by biologically produced siderophores during bioleaching from low-grade primary and secondary mineral resources
Authors: Williamson Adam J. , Folens Karel , Matthijs Sandra , Cortez Yensy Paz , Varia Jeet , Laing Gijs Du , Boon Nico , Hennebel Tom 
Published: January 2021

AbstractSiderophores are a class of biogenic macromolecules that have high affinities for metals in the environment, thus could be exploited for alternate sustainable metal recovery technologies. Here, we assess the role of siderophores in the extraction and complexation of metals from an iron oxide-rich metallurgical processing residue and a low-grade primary Ni ore. Evaluation of the biological siderophore bioproduction by three pseudomonads,P. fluorescens, P. azotoformansandP. putidaidentified thatP. putidacould generate the highest siderophore yield, which was characterized as a hydroxamate and catecholate mixed-type pyoverdine PyoPpC-3B. Key physiochemical parameters involved in raw siderophore mediated metal extraction were identified using a fractional factorial design of experiments (DOE) and subsequently employed in purified PyoPpC-3B leaching experiments. Further targeted experiments with hydroxamate and catecholate functional analogues of PyoPpC-3B confirmed their marked ability to competitively or selectively leach and chelate hard metal ions, including Al(OH)4-, Mn2+and Zn2+. Interestingly, complexation of Mn and Zn ions exceeded the natural affinity of pyoverdine for Fe3+, thus despite the low metal recoveries from the materials tested in this study, this work provides important new insights in siderophore-metal interactions.
Collective action or individual choice: Spontaneity and individuality contribute to decision-making inDrosophila
Authors: Steymans Isabelle , Pujol-Lereis Luciana M. , Brembs Björn , Gorostiza E. Axel 
Published: January 2021

AbstractOur own unique character traits make our behavior consistent and define our individuality. Yet, this consistency does not entail that we behave repetitively like machines. Like humans, animals also combine personality traits with spontaneity to produce adaptive behavior: consistent, but not fully predictable. Here, we study an iconically rigid behavioral trait – insect phototaxis – that that nevertheless also contains both components of individuality and spontaneity. In a light/dark T-maze, approximately 70% of a group ofDrosophilafruit flies choose the bright arm of the T-Maze, while the remaining 30% walk into the dark. Taking the photopositive and the photonegative subgroups and re-testing them reveals the spontaneous component: a similar 70-30 distribution emerges in each of the two subgroups. Increasing the number of choices to ten choices, reveals the individuality component: flies with extremely negative first choices were more likely to show photonegative behavior in subsequent choices andvice versa. General behavioral traits, independent of light/dark preference, contributed to the development of this individuality. The interaction of individuality and spontaneity together explains why group averages, even for such seemingly stereotypical behaviors, are poor predictors of individual choices.
Ultrasound-mediated blood-brain barrier disruption improves anti-pyroglutamate3 Aβ antibody efficacy and enhances phagocyte infiltration into brain in aged Alzheimer’s disease-like mice
Authors: Shi Qiaoqiao , Sun Tao , Zhang Yongzhi , Power Chanikarn , Hoesch Camilla , Antonelli Shawna , Schroeder Maren K. , Caldarone Barbara J. , Taudte Nadine , Schenk Mathias , Hettmann Thore , Schilling Stephan , McDannold Nathan J. , Lemere Cynthia A. 
Published: January 2021

AbstractPyroglutamate-3 amyloid-β (pGlu3 Aβ) is an N-terminally modified, toxic form of amyloid-β that is present in cerebral amyloid plaques and vascular deposits. Using the Fc-competent murine anti-pGlu3 Aβ monoclonal antibody (mAb), 07/2a, we present here a nonpharmacological approach using focused ultrasound (FUS) with intravenous (i.v.) injection of microbubbles (MB) to facilitate i.v. delivery of the 07/2a mAb across the blood brain barrier (BBB) in order to improve Aβ removal and restore memory in aged APP/PS1 mice, an Alzheimer’s disease (AD)-like model of amyloidogenesis.Compared to sham-treated controls, aged APP/PS1 mice treated with 07/2a immediately prior to FUS-mediated BBB disruption (mAb + FUS-BBBD combination treatment) showed significantly better spatial learning and memory in the Water T Maze. FUS-BBBD treatment alone improved contextual fear learning and memory in aged WT and APP/PS1 mice, respectively. APP/PS1 mice given the combination treatment had reduced Aβ42 and pGlu3 Aβ hippocampal plaque burden compared to PBS-treated APP/PS1 mice.Hippocampal synaptic puncta density and synaptosomal synaptic protein levels were also higher in APP/PS1 mice treated with 07/2a just prior to BBB disruption. Increased Iba-1+microglia were observed in the hippocampi of AD mice treated with 07/2a with and without FUS-BBBD, and APP/PS1 mice that received hippocampal BBB disruption and 07/2a showed increased Ly6G+monocytes in hippocampal CA3. FUS-induced BBB disruption did not increase the incidence of microhemorrhage in mice with or without 07/2a mAb treatment.Our findings suggest that FUS is useful tool that may enhance delivery of an anti-pGlu3 Aβ mAb for immunotherapy. FUS-mediated BBB disruption in combination with the 07/2a mAb also appears to facilitate monocyte infiltration in this AD model. Overall, these effects resulted in greater sparing of synapses and improved cognitive function without causing overt damage, suggesting the possibility of FUS as a noninvasive method to increase the therapeutic efficacy in AD patients.
Functional differences drive the selection of NRAS mutants in melanoma
Authors: Murphy Brandon M. , Weiss Tirzah J. , Holderbaum Andrea M. , Dhakal Aastha , Fort Marie , Bodnar Michael S. , Chen Min , Burd Craig J. , Coppola Vincenzo , Burd Christin E. 
Published: January 2021

ABSTRACTDistinct NRAS mutants are enriched in various tumor types. Here, we generated a suite of fully congenic, conditional,Nrasknock-in mouse models (LSL-Nras Q61R, -K, -L, -H, -P, -Q; G12DandG13D, -R) to test the hypothesis that melanocyte transformation requires functions specific to the NRAS mutants enriched in human melanoma (Q61R and Q61K). Consistent with the rarity of NRAS codon 12 and 13 mutants in human melanoma, spontaneous melanomas were rare or absent in mice expressing NRAS G12D, G13D or G13R. Mice expressing less common codon 61 alleles (Q61H, Q61P) also developed few or no tumors. NRAS Q61R, Q61K, or Q61L expression, by contrast, induced rapid melanoma onset with high penetrance. Cohorts of heterozygous mice containing oneLSL-Nras Q61Rand oneLSL-Nras Q61K, -L, -H, -P, or-Qallele were generated to assess potential interactions between NRAS mutants. The ability of eachNrasvariant to substitute for anNras Q61Rallele was consistent with its own ability to drive spontaneous melanoma formation. However,LSL-Nras Q61Q/Q61Rmice rarely developed tumors.In vitroexperiments in mouse embryonic fibroblasts (MEFs) highlighted activation of the MAPK pathway as a defining difference between tumorigenic and non-tumorigenic NRAS mutants. Enhanced MAPK activation was associated with the promotion of BRAF-BRAF and BRAF-CRAF dimers. These results support the development of cancer preventative strategies specific to the properties of the commonly observed RAS mutants in each tumor type.
LocalZProjectorandDeProj: A toolbox for local 2D projection and accurate morphometrics of large 3D microscopy images
Authors: Herbert Sébastien , Valon Léo , Mancini Laure , Dray Nicolas , Caldarelli Paolo , Gros Jérôme , Esposito Elric , Shorte Spencer L. , Bally-Cuif Laure , Levayer Romain , Aulner Nathalie , Tinevez Jean-Yves 
Published: January 2021

BackgroundQuantitative imaging of epithelial tissues prompts for bioimage analysis tools that are widely applicable and accurate. In the case of imaging 3D tissues, a common pre-processing step consists in projecting the acquired 3D volume on a 2D plane mapping the tissue surface. Indeed, while segmenting the tissue cells is amenable on 2D projections, it is still very difficult and cumbersome in 3D. However, for many specimen and models used in Developmental and Cell Biology, the complex content of the image volume surrounding the epithelium in a tissue often reduces the visibility of the biological object in the projection, compromising its subsequent analysis. In addition, the projection may distort the geometry of the tissue and can lead to strong artifacts in the morphology measurement.ResultsHere we introduce a user-friendly toolbox built to robustly project epithelia on their 2D surface from 3D volumes, and to produce accurate morphology measurement corrected for the projection distortion, even for very curved tissues. Our toolbox is built upon two components.LocalZProjectoris a user-friendly and configurable Fiji plugin that generates 2D projections and height-maps from potentially large 3D stacks (larger than 40 GB per time-point) by only incorporating signal of the planes with local highest variance/mean intensity, despite a possibly complex image content.DeProjis a MATLAB tool that generates correct morphology measurements by combining the height-map output (such as the one offered byLocalZProjector) and the results of a cell segmentation on the 2D projection, hence effectively deprojecting the 2D segmentation in 3D. In this paper we demonstrate their effectiveness over a wide range of different biological samples. We then compare its performance and accuracy against similar existing tools.ConclusionsWe find thatLocalZProjectorperforms well even in situations where the volume to project also contains un-wanted signal in other layers. We show that it can process large images without a pre-processing step. We study the impact of geometrical distortions on morphological measurements induced by the projection. We measured very large distortions which are then corrected byDeProj, providing accurate outputs.
Stable thalamocortical learning between medial-dorsal thalamus and cortical attractor networks captures cognitive flexibility
Authors: Qiu Siwei 
Published: January 2021

AbstractPrimates and rodents are able to continually acquire, adapt, and transfer knowledge and skill, and lead to goal-directed behavior during their lifespan. For the case when context switches slowly, animals learn via slow processes. For the case when context switches rapidly, animals learn via fast processes. We build a biologically realistic model with modules similar to a distributed computing system. Specifically, we are emphasizing the role of thalamocortical learning on a slow time scale between the prefrontal cortex (PFC) and medial dorsal thalamus (MD). Previous work [1] has already shown experimental evidence supporting classification of cell ensembles in the medial dorsal thalamus, where each class encodes a different context. However, the mechanism by which such classification is learned is not clear. In this work, we show that such learning can be self-organizing in the manner of an automaton (a distributed computing system), via a combination of Hebbian learning and homeostatic synaptic scaling. We show that in the simple case of two contexts, the network with hierarchical structure can do context-based decision making and smooth switching between different contexts. Our learning rule creates synaptic competition [2] between the thalamic cells to create winner-take-all activity. Our theory shows that the capacity of such a learning process depends on the total number of task-related hidden variables, and such a capacity is limited by system size N. We also theoretically derived the effective functional connectivity as a function of an order parameter dependent on the thalamo-cortical coupling structure.Significance StatementAnimals need to adapt to dynamically changing environments and make decisions based on changing contexts. Here we propose a combination of neural circuit structure with learning mechanisms to account for such behaviors. Specifically, we built a reservoir computing network improved by a Hebbian learning rule together with a synaptic scaling learning mechanism between the prefrontal cortex and the medial-dorsal (MD) thalamus. This model shows that MD thalamus is crucial in such context-based decision making. I also make use of dynamical mean field theory to predict the effective neural circuit. Furthermore, theoretical analysis provides a prediction that the capacity of such a network increases with the network size and the total number of tasks-related latent variables.
Ancient sedimentary DNA shows rapid post-glacial colonisation of Iceland followed by relatively stable vegetation until Landnám
Authors: Alsos Inger Greve , Lammers Youri , Kjellman Sofia E. , Føreid Merkel Marie Kristine , Bender Emma M. , Rouillard Alexandra , Erlendsson Egill , Guðmundsdóttir Esther Ruth , Benediktsson Ívar Örn , Farnsworth Wesley R. , Brynjólfsson Skafti , Gísladóttir Guðrún , Eddudóttir Sigrún Dögg , Schomacker Anders 
Published: January 2021

AbstractUnderstanding patterns of colonisation is important for explaining both the distribution of single species and anticipating how ecosystems may respond to global warming. Insular flora may be especially vulnerable because oceans represent severe dispersal barriers. Here we analyse two lake sediment cores from Iceland for ancient sedimentary DNA to infer patterns of colonisation and Holocene vegetation development. Our cores from lakes Torfdalsvatn and Nykurvatn span the lastc. 12,000 cal. yr BP andc. 8600 cal. yr BP, respectively. With near-centennial resolution, we identified a total of 191 plant taxa, with 152 taxa identified in the sedimentary record of Torfdalsvatn and 172 plant taxa in the sedimentary record of Nykurvatn. The terrestrial vegetation at Torfdalsvatn was first dominated by bryophytes, arctic herbs such asSaxifragaspp. and grasses. Around 10,100 cal. yr BP, a massive immigration of new taxa was observed, and shrubs and dwarf shrubs became common whereas aquatic macrophytes became dominant. At Nykurvatn, all dominant taxa occurred already in the earliest samples; shrubs and dwarf shrubs were more abundant at this site than at Torfdalsvatn. There was an overall steep increase both in the local and regional species pool until 8000 cal. yr BP, by which time ¾ of all taxa identified had arrived. In the period 4500-1000 cal. yr BP, a few new taxa of bryophytes, graminoids and forbs are identified. The last millennium, after human settlement of the island (Landnám), is characterised by a sudden disappearance ofJuniperus communis, but also reappearance of some high arctic forbs and dwarf shrubs. Notable immigration during the Holocene coincides with periods of dense sea-ice cover, and we hypothesise that this may have acted as a dispersal vector. Thus, although ongoing climate change might provide a suitable habitat in Iceland for a large range of species only found in the neighbouring regions today, the reduction of sea ice may in fact limit the natural colonisation of new plant species.