bluuebunny/crossref_metadata_2025_split huggingface dataset:
The ratio versus difference optimization and its implications for optimality theory
Authors: Shinde Sonali , Patwardhan Ankur , Watve Milind 
Published: December 2020

AbstractAmong the classical models of optimization, some models maximize the ratio of returns per investment, others maximize the difference between returns and investment. However, the question under what conditions use of the ratio model is appropriate and under what conditions a difference model should be used remained unaddressed until recently. The question is important because the strategies indicated by ratio optimum can be substantially different than the ones suggested by difference optimum. We make a general case here for the set of conditions for appropriate use of ratio versus difference optimum. When the investable amount is perceived as limiting but not the investment opportunities a ratio optimum is appropriate and when the investment opportunities are perceived to be limiting but not the investable amount, difference optimum is appropriate. Taking examples of Concorde fallacy, parental investment, r and K selection, nectar production, pollinator behavior, protein synthesis and stability, viral burst size and human economic behavior we show that the ratiodifference distinction in optimization models resolves many long standing debates and conundrums in evolution, behavior and economics.
ICM cells can be partitioned robustly through transient synchronization using secreted FGF4
Authors: Xu Xiaochan , Trusina Ala , Sneppen Kim 
Published: December 2020

AbstractThe differentiation of ICM cells into epiblast (EPI) and primitive endoderm (PE) is central in embryonic development. It is known that FGF4 signaling is important in this process, but it remains unclear how cells can be correctly partitioned. Here we model the NANOG-GATA6-FGF4 network, and test all 64 logical regulatory combinations for their ability to partition a group of cells. We found that nearly all the logic combinations allowed for correct partitioning, including a minimal network where self-activation of NANOG and GATA6 was inactivated. However such self-activation increased the robustness of the system. Furthermore, the model also captured the reported changes in cell proportions in response to FGF perturbations. This constrains the possible regulatory logic and predicts the presence of an “OR” gate in cell-cell communication. We repeatedly found that FGF4 coordinated the decision in two phases: A convergence and a bifurcation phase. First FGF4 negative feedback drives the cells to a balanced “battle” state where most cells have intermediate levels of both regulators, thus being double positive. Subsequent bifurcation happens at constant FGF4 level. Together our results suggest that the frequently observed state of multipotency during differentiation may be an emergent phenomenon resulting from inter-cellular negative feedbacks.
Large-scale simulations of biological cell sorting driven by differential adhesion follow diffusion-limited domain coalescence regime
Authors: Durand Marc 
Published: December 2020

AbstractCell sorting, whereby a heterogeneous cell mixture segregates and forms distinct homogeneous tissues, is one of the main collective cell behaviors at work during development. Although differences in interfacial energies are recognized to be a possible driving source for cell sorting, no clear consensus has emerged on the kinetic law of cell sorting driven by differential adhesion. Using a modified Cellular Potts Model algorithm that allows for efficient simulations while preserving the connectivity of cells, we numerically explore cell-sorting dynamics over unprecedentedly large scales in space and time. For a binary mixture of cells surrounded by a medium, increase of domain size follows a power-law with exponentn= 1/4 independently of the mixture ratio, revealing that the kinetics is dominated by the diffusion and coalescence of rounded domains. We compare these results with recent numerical and experimental studies on cell sorting, and discuss the importance of boundary conditions, space dimension, initial cluster geometry, and finite size effects on the observed scaling.Author summaryCell sorting describes the spontaneous segregation of identical cells in biological tissues. This phenomenon is observed during development or organ regeneration in a variety of biological systems. Minimization of the total surface energy of a tissue, in which adhesion strengh between homotypic and heterotypic cells are different, is one of the mechanisms that explain cell sorting. This mechanism is then similar to the one that drives demixing of two immiscible fluids. Because of the high sensibility of this process to finite-size and finite-time effects, no clear consensus has emerged on the scaling law of cell sorting driven by differential adhesion. Using an efficient numerical code, we were able to investigate this scaling law on very large binary mixtures of cells. We show that on long times, cell sorting obeys a universal power law, which is independent of the mixture ratio.
From random to predictive: a context-specific interaction framework improves selection of drug protein-protein interactions for unknown drug pathways
Authors: Wilson Jennifer L. , Gravina Alessio , Grimes Kevin 
Published: December 2020

AbstractWith high drug attrition, interaction network methods are increasingly attractive as quick and inexpensive methods for prediction of drug safety and efficacy effects when a drug pathway is unknown. However, these methods suffer from high false positive rates for selecting drug phenotypic effects, their performance is often no better than random (AUROC ~0.5), and this limits the use of network methods in regulatory and industrial decision making. In contrast to many network engineering approaches that apply mathematical thresholds to discover phenotype associations, we hypothesized that interaction networks associated with true positive drug phenotypes are context specific. We tested this hypothesis on 16 designated medical event (DMEs) phenotypes which are a subset of adverse events that are of upmost concern to FDA review using a novel data set extracted from drug labels. We demonstrated that context-specific interactions (CSIs) distinguished true from false positive DMEs with an 50% improvement over non-context-specific approaches (AUROC 0.77 compared to 0.51). By reducing false positives, CSI analysis has the potential to advance network techniques to influence decision making in regulatory and industry settings.Author summaryDrugs bind proteins that interact with multiple downstream proteins and these protein networks are responsible for drug efficacy and safety. Protein interaction network methods predict drug effects aggregating information about proteins around drug-binding protein targets. However, many frameworks exist for identifying proteins relevant to a drug’s effect. We consider three frameworks for selecting these proteins and show increased performance from a context-specific approach on selecting proteins relevant to severe drug side effects. The context-specific approach leverages the idea that the proteins responsible for a drug side effect are specific to each side-effect. By discovering the relevant proteins, we can better understand downstream effects of drugs and better anticipate drug side effects for new drugs in development. Further, we focus on designated medical events, a subset of the most severe drug side-effects that are high priority for regulatory review.
ChameleonmicroRNAs in breast cancer: their elusive role as regulatory factors in cancer progression
Authors: Miglioli Cesare , Bakalli Gaetan , Orso Samuel , Karemera Mucyo , Molinari Roberto , Guerrier Stéphane , Mili Nabil 
Published: December 2020

AbstractBreast cancer is one of the most frequent cancers affecting women. Non-coding micro RNAs (miRNAs) seem to play an important role in the regulation of pathways involved in tumor occurrence and progression. Extending on the research in Haakensenet al., where significant miRNAs were selected as being associated with the progression from normal breast tissue to breast cancer, in this work we put forward 112 sets of miRNA combinations, each including at most 5 expressions with high accuracy in discriminating healthy breast tissue from breast carcinoma. Our results are based on a recently developed machine learning technique which, instead of selecting a single model (or combination of features), delivers a set of models with equivalent predictive capabilities that allow to interpret and visualize the interaction of these features. These results shed new light on the biological action of the selected miRNAs which can behave in different ways according to the miRNA network with which they interact.Indeed, these revealed connections may contribute to explain why, in some cases, different studies attribute opposite functions to the same miRNA. It is therefore possible to understand how the role of a genomic variable may change when considered in interaction with other sets of variables, as opposed to only considering its effect when it is evaluated within a unique combination of features. The approach proposed in this work provides a statistical basis for the notion ofchameleonmiRNAs and is inspired by the emerging field of systems biology.Author SummaryThe notion of a single predictive genomic (statistical) model is replaced by that of a set of models that can be considered as exchangeable due to their indistinguishable (optimal) predictive abilities;Our results indicate that the role of miRNAs cannot be interpreted independently from the combination of features with which they interact and can therefore vary considerably when considered in a network of different combinations. Some miRNAs may act aschameleonsand behave in opposite manners thereby showing some kind of antagonistic duality;Some miRNAs are exchangeable inside models with equivalent predictive ability and seem to point to latent biological functions.
Structural and functional insights into the mechanism of action of plant boron transporters
Authors: Saouros Savvas , Mohan Thotegowdanapalya C. , Cecchetti Cristina , Lehmann Silke , Barritt Joseph D. , Scull Nicola J. , Simpson Paul , Alguel Yilmaz , Cameron Alexander D. , Jones Alexandra M. E. , Byrne Bernadette 
Published: December 2020

AbstractBoron has essential roles in plant growth and development. BOR proteins are key in the active uptake and distribution of boron, and regulation of intracellular boron concentrations. However, their mechanism of action remains poorly studied. BOR proteins are members of the SLC4 family of transporters and thus homologues of well studied mammalian transporters including the human Anion Exchanger 1 (hAE1). Here we generatedArabidopsis thalianaBOR1 (AtBOR1) variants based i) on known disease causing mutations of hAE1 (S466R, A500R) and ii) a loss of function mutation (D311A) identified in the yeast BOR protein, ScBOR1p. The AtBOR1 variants express in yeast and localise to the plasma membrane, although both S466R and A500R exhibit lower expression than the WT AtBOR1 and D311A. The D311A, S466R and A500R mutations result in a loss of boron efflux activity in a yeastbor1pknockout strain.A. thalianaplants containing these three individual mutations exhibit substantially decreased growth phenotypes in soil under conditions of low boron. These data confirm an important role for D311 in the function of the protein and show that mutations equivalent to disease causing mutations in hAE1 have major effects in AtBOR1. We also obtained a low resolution cryo-EM structure of a BOR protein fromOryza sativa, OsBOR3 lacking the 30 C-terminal amino acids. This structure confirms the gate and core domain organisation previously observed for related proteins, and is strongly suggestive of an inward facing conformation.
Alpha-tubulin acetylation inTrypanosoma cruzi: a dynamic instability of microtubules is required for replication and cell cycle progression
Authors: Alonso Victoria Lucia , Carloni Mara Emilia , Gonçalves Camila Silva , Peralta Gonzalo Martinez , Chesta Maria Eugenia , Pezza Alejandro , Tavernelli Luis Emilio , Motta Maria Cristina M. , Serra Esteban 
Published: December 2020

AbstractTrypanosomatids have a cytoskeleton arrangement that is simpler than what is found in most eukaryotic cells. However, it is precisely organized and constituted by stable microtubules. Such microtubules compose the mitotic spindle during mitosis, the basal body, the flagellar axoneme and the subpellicular microtubules, which are connected to each other and also to the plasma membrane forming a helical arrangement along the central axis of the parasite cell body. Subpellicular, mitotic and axonemal microtubules are extensively acetylated inTrypanosoma cruzi. Acetylation on lysine (K) 40 of α-tubulin is conserved from lower eukaryotes to mammals and is associated with microtubule stability. It is also known that K40 acetylation occurs significantly on flagella, centrioles, cilia, basal body and the mitotic spindle in eukaryotes. Several tubulin posttranslational modifications, including acetylation of K40, have been catalogued in trypanosomatids, but the functional importance of these modifications for microtubule dynamics and parasite biology remains largely undefined. The primary tubulin acetyltransferase that delivers this modification was recently identified in several eukaryotes as Mec-17/ATAT, a Gcn5-related N-acetyltransferase. Here, we report thatT. cruziATAT acetylates α-tubulinin vivoand is capable of auto-acetylation.TcATAT is located in the cytoskeleton and flagella of epimastigotes and colocalizes with acetylated α-tubulin in these structures. We have expressedTcATAT with an HA tag using the inducible vector pTcINDEX-GW inT. cruzi. Over-expression ofTcATAT causes increased levels of the acetylated isoform, induces morphological and ultrastructural defects, especially in the mitochondrion, and causes a halt in the cell cycle progression of epimastigotes, which is related to an impairment of the kinetoplast division. Finally, as a result ofTcATAT over-expression we observed that parasites became more resistant to microtubule depolymerizing drugs. These results support the idea that α-tubulin acetylation levels are finely regulated for the normal progression ofT. cruzicell cycle.
Characterization of highly proliferative decidual precursor cells during the window of implantation in human endometrium
Authors: Diniz-da-Costa Maria , Kong Chow-Seng , Fishwick Katherine J. , Rawlings Thomas , Brighton Paul J. , Hawkes Amelia , Odendaal Joshua , Quenby Siobhan , Ott Sascha , Lucas Emma S , Vrljicak Pavle , Brosens Jan J 
Published: December 2020

AbstractPregnancy depends on the wholesale transformation of the endometrium, a process driven by differentiation of endometrial stromal cells (EnSC) into specialist decidual cells. Upon embryo implantation, decidual cells impart the tissue plasticity needed to accommodate a rapidly growing conceptus and invading placenta, although the underlying mechanisms are unclear. Here we characterize a discrete population of highly proliferative mesenchymal cells (hPMC) in midluteal human endometrium, coinciding with the window of embryo implantation. Single-cell transcriptomics demonstrated that hPMC express genes involved in chemotaxis and vascular transmigration. Although distinct from resident EnSC, hPMC also express genes encoding pivotal decidual transcription factors and markers, most prominently prolactin. We further show that hPMC are enriched around spiral arterioles, scattered throughout the stroma, and occasionally present in glandular and luminal epithelium. The abundance of hPMC correlated with thein vitrocolony-forming unit activity of midluteal endometrium and, conversely, clonogenic cells in culture express a gene signature partially conserved in hPMC. Cross-referencing of single-cell RNA-sequencing data sets indicated that hPMC differentiate into a recently discovered decidual subpopulation in early pregnancy. Finally, we demonstrate that recurrent pregnancy loss is associated with hPMC depletion. Collectively, our findings characterize midluteal hPMC as novel decidual precursors that are likely derived from circulating bone marrow-derived mesenchymal stem/stromal cells and integral to decidual plasticity in pregnancy.Significance statementTransformation of cycling endometrium into the decidua of pregnancy requires extensive tissue remodeling. Perturbations in this process lead to breakdown of the maternal-fetal interface and miscarriage. Here we report the characterization of decidual precursor cells during the window of implantation. We demonstrate that decidual precursors are clonogenic and primed for exponential growth. They likely originate from bone marrow-derived MSC and give rise to a distinct decidual subpopulation in pregnancy. Recurrent pregnancy loss is associated with loss of decidual precursor cells prior to conception, raising the possibility that they can be harnessed for the prevention of pregnancy disorders, including miscarriages and preterm labor.
Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines
Authors: Kegel Barbara De , Quinn Niall , Thompson Nicola A. , Adams David J. , Ryan Colm J. 
Published: December 2020

AbstractPairs of paralogs may share common functionality and hence display synthetic lethal interactions. As the majority of human genes have an identifiable paralog, exploiting synthetic lethality between paralogs may be a broadly applicable approach for targeting gene loss in cancer. However only a biased subset of human paralog pairs has been tested for synthetic lethality to date. Here, by analysing genome-wide CRISPR screens and molecular profiles of over 700 cancer cell lines, we identify features predictive of synthetic lethality between paralogs, including shared protein-protein interactions and evolutionary conservation. We develop a machine-learning classifier based on these features to predict which paralog pairs are most likely to be synthetic lethal and to explain why. We show that our classifier accurately predicts the results of combinatorial CRISPR screens in cancer cell lines and furthermore can distinguish pairs that are synthetic lethal in multiple cell lines from those that are cell-line specific.
ICT infrastructure, innovation development and economic growth: a comparative evidence between two decades in OECD countries
Authors: Kurniawati Meta Ayu 
Published: December 2020

PurposeThe objective of this study is to examine the causal relationship between economic growth, information and communication technology (ICT) penetration and innovation development in OECD countries.Design/methodology/approachThis study incorporates data for 24 OECD countries from 2000 to 2018, which is divided into the earliest (2000–2009) and the latest (2010–2018) periods. The econometric methodologies of this study employ panel cointegration, estimation procedures and vector error-correction modelling to investigate the potential interconnections between ICT, innovation development and economic growth.FindingsThe results from the latest period illustrate that OECD countries have achieved positive and significant economic development from high ICT penetration, while results from the earliest period show that OECD countries were just beginning to enjoy the benefits of ICT penetration. Moreover, findings show that innovation development is highly significant in the latest period when promoting economic growth.Practical implicationsThe policy implications suggest that promoting ICT infrastructure establishment and expanding the innovation development may drive the process of economic development in OECD countries.Originality/valueThis study employs mobile and Internet penetration as the development of telecommunication which is in line with the enlargement of innovation to foster economic growth in OECD countries. Comparing the evidence from two decades provides significant value for policymakers and decision-makers regarding the advantages of technology expansion and innovation development to promote economic growth in recent conditions.
Identification of the piston machine combustion chamber tightness
Authors: Bielawski Piotr Jan 
Published: December 2020

PurposeThe lack of integrity of the piston machine combustion chamber manifests itself in leakages of the working fluid between the piston and the cylinder liner, at valves mounted in the cylinder head and between the head and the liner. An untight combustion chamber leads to decreased power output or efficiency of the engine, while leaks of a fluid may cause damage to many components of the chamber. The actual value of working chamber leak is a desired and essential piece of information for planning operations of a given machine.Design/methodology/approachThis research paper describes causes and mechanisms of leakage from the working chamber of internal combustion engines. Besides, the paper outlines presently used methods and means of leak identification and states that their further development and improvements are needed. New methods and their applicability are presented.FindingsThe methods of leak identification have been divided into diagnostic and non-working machine leak identification methods. The need has been justified for the identification of leakage from the combustion chamber of a non-working machine and for using the leakage measure as the value of the cross-sectional area of the equivalent leak, defined as the sum of cross-section areas of all leaking paths. The analysis of possible developments of tightness assessment methods referring to the combustion chamber of a non-working machine consisted in modelling subsequent combustion chamber leaks as gas-filled tank leak, leak from another element of gas-filled tank and as a regulator of gas flow through a nozzle.Originality/valueA measurement system was built allowing the measurement of pressure drop in a tank with the connected engine combustion chamber, which indicated the usefulness of the system for leakage measurement in units as defined in applicable standards. A pneumatic sensor was built for measuring the cross-sectional area of the equivalent leak of the combustion chamber connected to the sensor where the chamber functioned as a regulator of gas flow through the sensor nozzle. It has been shown that the sensor can be calibrated by means of reference leaks implemented as nozzles of specific diameters and lengths. The schematic diagram of a system for measuring the combustion chamber leakage and a diagram of a sensor for measuring the cross-sectional area of the equivalent leak of the combustion chamber leakage are presented. The results are given of tightness tests of a small one-cylinder combustion engine conducted by means of the set up measurement system and a pre-prototype pneumatic sensor. The two solutions proved to be practically useful.