bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stratified tissue biofabrication by rotational internal flow layer engineering
Authors: Holland Ian , Shu Wenmiao , Davies Jamie A. 
Published: December 2022

AbstractThe bioassembly of layered tissue that closely mimics human histology presents challenges for tissue engineering. Existing bioprinting technologies lack the resolution and cell densities necessary to form the microscale cell-width layers commonly observed in stratified tissue, particularly when using low-viscosity hydrogels, such as collagen. Here we present rotational internal flow layer engineering (RIFLE), a novel biofabrication technology for assembling tuneable, multi-layered tissue-like structures. Using high-speed rotating tubular moulds, small volumes of cell-laden liquids added to the inner surface were transitioned into thin layers and gelled, progressively building macroscale tubes composed of discrete microscale strata with thicknesses a function of rotational speed. Cell encapsulation enabled the patterning of high-density layers (108cells/ml) into heterogenous constructs. RIFLE versatility was demonstrated through tunica media assembly, encapsulating human smooth muscle cells in cell-width (12.5μm) collagen layers. This enabling technology has the potential to allow researchers to economically create a range of representative stratified tissue.
Competitive, connective and allosteric Nanobodies that modulate the SOS1•RAS protein-protein interactions and tune the nucleotide exchange rate as a starting point for drug design
Authors: Fischer Baptiste , Uchański Tomasz , Sheryazdanova Aidana , Gonzalez Simon , Volkov Alexander N. , Brosens Elke , Zögg Thomas , Kalichuk Valentina , Ballet Steven , Versées Wim , Sablina Anna A. , Pardon Els , Wohlkönig Alexandre , Steyaert Jan 
Published: December 2022

AbstractProtein-protein interactions (PPIs) are central in cell metabolism but research tools for the structural and functional characterization of these PPIs are often missing. Here we introduce novel and broadly applicable immunization (Cross-link PPIs andimmunizellamas, ChILL) and selection strategies (Display andco-selection, DisCO) for the discovery of diverse Nanobodies that either stabilize or disrupt PPIs in a single experiment. We applied ChILL and DisCO to identify competitive, connective or fully allosteric Nanobodies that inhibit or facilitate the formation of the SOS1•RAS complex and modulate the nucleotide exchange rate on this pivotal GTPasein vitroand RAS signallingin cellulo. One of these connective Nanobodies fills a cavity that was previously identified as the binding pocket for a series of therapeutic lead compounds. The long complementarity-determining region (CDR3) that penetrates this binding pocket serves as an innovative pharmacophore for extending the repertoire of potential leads.
Learning the differences: a transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity
Authors: Bravi Barbara , Di Gioacchino Andrea , Fernandez-de-Cossio-Diaz Jorge , Walczak Aleksandra M. , Mora Thierry , Cocco Simona , Monasson Rémi 
Published: December 2022

AbstractAntigen immunogenicity and the specificity of binding of T-cell receptors to antigens are key properties underlying effective immune responses. Here we propose diffRBM, an approach based on transfer learning and Restricted Boltzmann Machines, to build sequence-based predictive models of these properties. DiffRBM is designed to learn the distinctive patterns in amino acid composition that, one the one hand, underlie the antigen’s probability of triggering a response, and on the other hand the T-cell receptor’s ability to bind to a given antigen. We show that the patterns learnt by diffRBM allow us to predict putative contact sites of the antigen-receptor complex. We also discriminate immunogenic and non-immunogenic antigens, antigen-specific and generic receptors, reaching performances that compare favorably to existing sequence-based predictors of antigen immunogenicity and T-cell receptor specificity. More broadly, diffRBM provides a general framework to detect, interpret and leverage selected features in biological data.
First biodegradable bioactive glass-based humidity sensor
Authors: Gharbi Amina , Kallel Ahmed Yahia , Kanoun Olfa , Cheikhrouhou-Koubaa Wissem , Contag Christopher H. , Antoniac Iulian , Derbel Nabil , Ashammakhi Nureddin 
Published: December 2022

AbstractMonitoring changes in edema-associated intracranial pressure that complicates trauma or surgery would lead to improved outcomes. Implantable pressure sensors have been explored, but, these sensors require post-surgical removal leading to risks of injury to brain tissue. Biodegradable implantable sensors would eliminate the risks while providing sensing when needed. Here, we demonstrate a bioactive glass (BaG)-based hydration sensor. A fluorine (CaF2) containing BaG (BaG-F) was produced using a melting manufacturing technique. The structure and electrical properties of the resulting constructs were evaluated to understand the electrical behaviors of this BaG-based sensor. The synthetic process of producing the BaG-F-based sensor was validated by assessing the electrical properties. We demonstrated that this BaG-F chemical composition is highly sensitive to hydration, and that electrical activity (resistive-capacitive) is induced by hydration and reversed by dehydration. These properties make BaG-F suitable for use as a humidity sensor to monitor brain edema and consequently provide an alert for increasing intracranial pressure.
Matrix Gla Protein acts as a driver of stemness and tumor initiation in ovarian cancer
Authors: Nieddu V. , Melocchi V. , Battistini C. , Franciosa G. , Lupia M. , Stellato C. , Bertalot G. , Olsen J.V. , Colombo N. , Bianchi F. , Cavallaro U. 
Published: December 2022

AbstractOvarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential.We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings.Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.
Exploring the intricacies and pitfalls of the ATN framework: An assessment across cohorts and thresholding methodologies
Authors: Salimi Yasamin , Domingo-Fernández Daniel , Hofmann-Apitius Martin , Birkenbihl Colin ,   the Alzheimer’s Disease Neuroimaging Initiative,   the Japanese Alzheimer’s Disease Neuroimaging Initiative,   the Alzheimer’s Disease Repository Without Borders Investigators,   the European Prevention of Alzheimer’s Disease (EPAD) Consortium
Published: December 2022

AbstractThe amyloid/tau/neurodegeneration (ATN) framework has redefined Alzheimer’s disease (AD) toward a primarily biological entity. While it has found wide application in AD research, it was so far typically applied to single cohort studies using distinct data-driven thresholding methods. This poses the question of how concordant thresholds obtained using distinct methods are within the same dataset as well as whether thresholds derived by the same technique are interchangeable across cohorts. Given potential differences in cohort data-derived thresholds, it remains unclear whether individuals of one cohort are actually comparable with regard to their exhibited disease patterns to individuals of another cohort, even when they are assigned to the same ATN profile. If such comparability is not evident, the generalizability of results obtained using the ATN framework is at question. In this work, we evaluated the impact of selecting specific thresholding methods on ATN profiles by applying five commonly-used methodologies across eleven AD cohort studies. Our findings revealed high variability among the obtained thresholds, both across methods and datasets, linking the choice of thresholding method directly to the type I and type II error rate of ATN profiling. Moreover, we assessed the generalizability of primarily Magnetic Resonance Imaging (MRI) derived biological patterns discovered within ATN profiles by simultaneously clustering participants of different cohorts who were assigned to the same ATN profile. In only two out of seven investigated ATN profiles, we observed a significant association between individuals’ assigned clusters and cohort origin for thresholds defined using Gaussian Mixture Models, while no significant associations were found for K-means-derived thresholds. Consequently, in the majority of profiles, biological signals governed the clustering rather than systematic cohort differences resulting from distinct biomarker thresholds. Our work revealed that: 1) the thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling, 2) obtained thresholds are most likely not directly interchangeably across two independent cohorts, and 3) MRI-based biological patterns derived from distinctly thresholded ATN profiles can generalize across cohort datasets. Conclusively, in order to appropriately apply the ATN framework as an actionable and robust biological profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and the validation of achieved results is crucial.
DRAGin situbarcoding reveals an increased number of HSPCs contributing to myelopoiesis with age
Authors: Urbanus Jos , Cosgrove Jason , Beltman Joost , Elhanati Yuval , de Andrade Moral Rafael , Conrad Cecile , van Heijst Jeroen W , Tubeuf Emilie , Velds Arno , Kok Lianne , Merle Candice , Magnusson Jens P , Frisén Jonas , Fre Silvia , Walczak Aleksandra M , Mora Thierry , Jacobs Heinz , Schumacher Ton N. , Perié Leïla 
Published: December 2022

SummaryAgeing is associated with changes in the cellular composition of the immune system. During ageing, hematopoietic stem and progenitor cells (HSPCs) that produce immune cells are thought to decline in their regenerative capacity. However, HSPC function has been mostly assessed using transplantation assays, and it remains unclear how HSPCs age in the native bone marrow niche. To address this issue, we developed a novel in situ single cell lineage tracing technology to quantify the clonal composition and cell production of single cells in their native niche. Our results demonstrate that a pool of HSPCs with unequal output maintains myelopoiesis through overlapping waves of cell production throughout adult life. During ageing, the increased frequency of myeloid cells is explained by greater numbers of HSPCs contributing to myelopoiesis, rather than increased myeloid output of individual HSPCs. Strikingly, the myeloid output of HSPCs remained constant over time despite accumulating significant transcriptomic changes throughout adulthood. Together, these results show that, unlike emergency myelopoiesis post-transplantation, aged HSPCs in their native microenvironment do not functionally decline in their regenerative capacity.
PDX3 is important for carbon/nitrogen balance in Arabidopsis associated with distinct environmental conditions
Authors: Steensma Priscille , Eisenhut Marion , Colinas Maite , Rosado-Souza Laise , Fernie Alisdair R. , Weber Andreas P. M. , Fitzpatrick Teresa B. 
Published: December 2022

ABSTRACTTo survive and proliferate in diverse environments with varying climate and nutrient availability, plants modulate their metabolism. Achieving a balance between carbon (C) and nitrogen (N) use such that growth and defense mechanisms can be appropriately controlled is critical for plant fitness. The identification of factors that regulate C/N utilization in plants can make a significant contribution to optimization of plant health. Here we show that pyridox(am)ine 5’-phosphate oxidase (PDX3), which regulates vitamin B6homeostasis, influences C/N balance. The B6vitamer imbalance resulting from loss of PDX3 leads to over-accumulation of nitrogenous compounds. A combination of increased glutamate dehydrogenase activity, impairment in the photorespiratory cycle and inappropriate use of endogenous ammonium fuel the metabolic imbalance. Growth at elevated CO2levels further exacerbates thepdx3phenotypes. Interestingly, serine supplementation rescues growth under high CO2likely bypassing the phosphorylated pathway of biosynthesis suggesting that this amino acid is an important commodity. We show that PDX3 function appears dispensable upon thermomorphogenesis, a condition that favors C metabolism. Furthermore, while a low ammonium to nitrate ratio likely accounts for overstimulation of salicylic acid (SA) defense responses inpdx3lines that compromises growth, a basal level of SA protects against loss of PDX3 biochemical function. Overall, the study highlights environmental scenarios where vitamin B6homeostasis, as managed by the salvage pathway enzyme PDX3, is critical and provides insight into how plants reprogram their metabolism under such conditions.
Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis
Authors: Rädecker Nils , Escrig Stéphane , Spangenberg Jorge E. , Voolstra Christian R. , Meibom Anders 
Published: December 2022

AbstractEfficient nutrient recycling underpins the ecological success of the cnidarian-algal symbiosis in oligotrophic waters. In a stable symbiosis, nitrogen limitation restricts the growth of algal endosymbionts and stimulates their release of photosynthates to the cnidarian animal host. However, the detailed mechanisms controlling nitrogen availabilityin hospiteand their role in symbiosis regulation remain poorly understood. Here, we studied the metabolic regulation of symbiotic nitrogen cycling in the sea anemone Aiptasia by experimentally altering labile carbon availability in a series of experiments. Combining13C and15N stable isotope labeling experiments with physiological analyses and NanoSIMS imaging, we show that the competition for environmental ammonium between the host and its algal symbionts is regulated by labile carbon availability. Light regimes optimal for algal photosynthesis increased carbon availability in the holobiont and stimulated nitrogen assimilation in the host metabolism. Consequently, algal symbiont densities were lowest under optimal environmental conditions and increased toward the symbiosis’s lower and upper light tolerance limits. This metabolic regulation promotes efficient carbon recycling in a stable symbiosis across a wide range of environmental conditions. At the same time, the dependence on resource competition may favor parasitic interactions explaining the instability of the symbiosis as the environmental conditions in the Anthropocene shift towards its tolerance limits.
No supergene despite social polymorphism in the big-headed antPheidole pallidula
Authors: Favreau Emeline , Lebas Claude , Stolle Eckart , Priyam Anurag , Pracana Rodrigo , Aron Serge , Wurm Yannick 
Published: December 2022

AbstractAnt colonies ancestrally contained one queen and her non-reproductive workers. This is also the case for many but not all colonies of the Mediterranean big-headed antPheidole pallidula. Indeed, this species also has a derived form of social organization with multiple reproductive queens in the colony. The co-existence of two social forms also independently evolved in three other lineages of ants. In each of those lineages, variants of a supergene region of suppressed recombination determine social form. This is likely because supergene regions can link advantageous combinations of alleles from multiple loci. We thus hypothesized that a supergene region also determines colony queen number in the big-headed ant. To test this, we performed extensive population genetic analyses and genomic comparisons. We find no evidence of a supergene-like region with differentiation between single- and multiple-queen colonies. Our results show that a complex social polymorphism can evolve and be maintained without supergenes.
Improvement of protein tertiary and quaternary structure predictions using the ReFOLD4 refinement method and the AlphaFold2 recycling process
Authors: Adiyaman Recep , Edmunds Nicholas S. , Genc Ahmet G. , Alharbi Shuaa M. A. , McGuffin Liam J. 
Published: December 2022

ABSTRACTMotivationThe accuracy gap between predicted and experimental structures has been significantly reduced following the development of AlphaFold2. However, for further studies, such as drug discovery and protein design, AlphaFold2 structures need to be representative of proteins in solution, yet AlphaFold2 was trained to generate only a few structural conformations rather than a conformational landscape. In previous CASP experiments, MD simulation-based methods have been widely used to improve the accuracy of single 3D models. However, these methods are highly computationally intensive and less applicable for practical use in large-scale applications. Despite this, the refinement concept can still provide a better understanding of conformational dynamics and improve the quality of 3D models at a modest computational cost. Here, our ReFOLD4 pipeline was adopted to provide the conformational landscape of AlphaFold2 predictions while maintaining high model accuracy. In addition, the AlphaFold2 recycling process was utilised to improve 3D models by using them as custom template inputs for tertiary and quaternary structure predictions.ResultsAccording to the Molprobity score, 94% of the generated 3D models by ReFOLD4 were improved. As measured by average change in lDDT, AlphaFold2 recycling showed an improvement rate of 87.5% (using MSAs) and 81.25% (using single sequences) for monomeric AF2 models and 100% (MSA) and 97.8% (single sequence) for monomeric non-AF2 models. By the same measure, the recycling of multimeric models showed an improvement rate of as much as 80% for AF2 models and 94% for non-AF2 models. The AlphaFold2 recycling processes and ReFOLD4 method can be combined very efficiently to provide conformational landscapes at the AlphaFold2-accuracy level, while also significantly improving the global quality of 3D models for both tertiary and quaternary structures, with much less computational complexity than traditional refinement methods.
A bioelectrical phase transition patterns the first beats of a vertebrate heart
Authors: Jia Bill Z. , Qi Yitong , Wong-Campos J. David , Megason Sean G. , Cohen Adam E. 
Published: December 2022

AbstractThe heart is among the first organs to function in vertebrate development, but its transition from silent to beating has not been directly characterized. Using all-optical electrophysiology, we captured the very first zebrafish heartbeat and analyzed the development of cardiac excitability around this singular event. The first beats appeared suddenly and propagated coherently across the primordial heart. Targeted optogenetic perturbations mapped the development of excitability and conduction before and after the first heartbeats. Measured bioelectrical dynamics support a noisy saddle-node on invariant circle (SNIC) bifurcation as the critical phase transition that starts the heart. Simple models of this bifurcation quantitatively capture cardiac dynamics in space and time through early development, including coherent beating before transcriptional specification of pacemakers. Our work shows how gradual and largely asynchronous development of single-cell bioelectrical properties produces a stereotyped and robust tissue-scale transition from quiescence to coordinated beating.
Towards a framework to unify the relationship between numerical abundance, biomass, and quantitative eDNA
Authors: Yates M.C , Wilcox T. M. , Kay S. , Heath D.D. 
Published: December 2022

AbstractDoes environmental DNA (eDNA) correlate more closely with numerical abundance (N) or biomass in aquatic organisms? We hypothesize that the answer is ‘neither’: eDNA production likely scales allometrically, reflecting key physiological rates and surface area-to-body mass relationships. Building on individual-level frameworks developed from the Metabolic Theory of Ecology, we derive a framework through which quantitative eDNA data can be transformed to simultaneously reflect both population-level N and biomass. We then validated our framework using data from two previously published studies: (i) a marine eDNA metabarcoding dataset; and (ii) a freshwater single-species qPCR dataset. Using a Bayesian modeling approach, we estimated the value of the allometric scaling coefficient that jointly optimized the relationship between N, biomass, and ‘corrected’ eDNA data to be 0.82 and 0.77 in Case Studies (i) and (ii), respectively. These estimates closely match expected scaling coefficients estimated in previous work on Teleost fish metabolic rates. We also demonstrate that correcting quantitative eDNA can significantly improve correspondence between eDNA- and traditionally-derived quantitative community biodiversity metrics (e.g., Shannon index and Bray-Curtis dissimilarity) under some circumstances. Collectively, we show that quantitative eDNA data is unlikely to correspond exactly to either N or biomass, but can be ‘corrected’ to reflect both through our unifying joint modelling framework. This framework can also be further expanded to include other variables that might impact eDNA pseudo-steady-state concentrations in natural ecosystems (e.g., temperature, pH, and phenology), and is flexible enough to model these relationships across trophic levels.Significance StatementAquatic animals release DNA (from shed cells, mucous, faeces, etc.) into water, which can be detected via environmental DNA (eDNA) sampling. What is less clear is whether we can estimate numerical abundance (N) or biomass from eDNA concentrations. We hypothesize that eDNA production scales allometrically; that is, large animals release less DNA per unit mass than smaller animals. Building from the Metabolic Theory of Ecology, we derived a framework through which eDNA data can be transformed to simultaneously reflect bothNand biomass. We then validated the framework using two case studies in marine and freshwater systems. This framework unifies discrepancies between eDNA,N, and biomass data, unlocking the potential of eDNA to monitor population abundance/biomass and quantify biodiversity.