bluuebunny/crossref_metadata_2025_split huggingface dataset:
Induction of senescence renders cancer cells highly immunogenic
Authors: Marín Inés , Boix Olga , García Andrea , Sirois Isabelle , Caballe Adrià , Zarzuela Eduardo , Ruano Irene , Stephan-Otto Attolini Camille , Prats Neus , López-Domínguez José Alberto , Kovatcheva Marta , Garralda Elena , Muñoz Javier , Caron Etienne , Abad María , Gros Alena , Pietrocola Federico , Serrano Manuel 
Published: June 2022

ABSTRACTCellular senescence is a stress response that activates innate immunity. However, the interplay between senescent cells and the adaptive immune system remains largely unexplored. Here, we show that senescent cells display enhanced MHC class I (MHC-I) antigen processing and presentation. Immunization of mice with senescent syngeneic fibroblasts generates CD8 T cells reactive against both normal and senescent fibroblasts, some of them targeting senescence-associated MHC-I-peptides. In the context of cancer, we demonstrate that senescent cancer cells trigger strong anti-tumor protection mediated by antigen-presenting cells and CD8 T cells. This response is superior to the protection elicited by cells undergoing immunogenic cell death. Finally, induction of senescence in patient-derived cancer cells exacerbates the activation of autologous tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs) with no effect on non-reactive TILs. Our study indicates that immunization with senescent cancer cells strongly activates anti-tumor immunity, and this can be exploited for cancer therapy.STATEMENT OF SIGNIFICANCEOur study shows that senescent cells are endowed with a high immunogenic potential, superior to the gold standard of immunogenic cell death. The induction of senescence in cancer cells can be exploited to develop efficient and protective CD8-dependent anti-tumor immune responses.
The role of inflammation in the prospective associations between early childhood sleep problems and ADHD at 10 years: Findings from a UK birth cohort study
Authors: Muñoz Isabel Morales , Upthegrove Rachel , Lawrence Kate , Kooij Sandra , Gregory Alice M , Marwaha Steven 
Published: June 2022

AbstractBackgroundSeveral underlying mechanisms potentially account for the link between sleep and attention deficit and hyperactivity disorder (ADHD), including inflammation. However, studies so far have been cross-sectional. We investigate (i) the association between early childhood sleep and probable ADHD diagnosis in childhood; and (ii) whether childhood circulating inflammatory markers mediate any associations.Methods and FindingsData from the Avon Longitudinal Study of Parents and Children (ALSPAC) were available for 7658 10-years-old children. Parent-reported sleep duration, night awakening frequency, and regular sleep routines were collected at 3.5 years. The Development and Wellbeing Assessment (DAWBA) was administered to capture children with clinically relevant ADHD symptoms, or probable ADHD diagnosis. Further, blood samples were collected at 9 years, from which two inflammatory markers were obtained [i.e. interleukin-6 (IL-6) and C-reactive protein (CRP)]. Logistic regressions were applied to investigate the associations between sleep variables at 3.5 years and probable ADHD diagnosis at 10 years. Further, path analysis was applied to examine the mediating role of inflammation at 9 years (i.e. as measured by CRP and IL-6) in the associations between early sleep and ADHD at 10 years. We found that less regular sleep routines (OR=0.51, 95%CI=0.28-0.93, p=0.029), shorter nighttime sleep (OR=0.70, 95%CI=0.56-0.89, p=0.004), and higher night awakening (OR=1.27, 95I%CI=1.06-1.52, p=0.009) at 3.5 years were associated with higher odds of probable ADHD at 10 years. Further, IL-6 at 9 years mediated the association between irregular sleep routines and ADHD (bias-corrected estimate, -0.002; p=0.005); and between night awakening and ADHD (bias-corrected estimate, 0.002; p=0.003).ConclusionsSeveral sleep problems in early childhood constitute a risk factor for probable ADHD diagnosis at 10 years. These associations may be mediated by inflammation, as measured by IL-6. These results open a new research vista to the pathophysiology of ADHD and highlight sleep and inflammation as potential preventative targets for ADHD.
A fast non-parametric test of association for multiple traits
Authors: Garrido-Martín Diego , Calvo Miquel , Reverter Ferran , Guigó Roderic 
Published: June 2022

AbstractThe increasing availability of multidimensional phenotypic data in large cohorts of genotyped individuals requires efficient methods to identify genetic effects on multiple traits. Permutational multivariate analysis of variance (PERMANOVA) offers a powerful non-parametric approach. However, it relies on permutations to assess significance, which hinders the analysis of large datasets. Here, we derive the limiting null distribution of the PERMANOVA test statistic, providing a framework for the fast computation of asymptotic p values. We show that the asymptotic test presents controlled type I error and high power, comparable to or higher than parametric approaches. We illustrate the applicability of our method in a number of use-cases. Using the GTEx cohort, we perform the first population-biased splicing QTL mapping study across multiple tissues. We identify thousands of genetic variants that affect alternative splicing differently depending on ethnicity, including potential disease markers. Using the UK Biobank cohort, we perform the largest GWAS to date of MRI-derived volumes of hippocampal subfields. Most of the identified loci have not been previously related to the hippocampus, but many are associated to cognition or brain disorders, thus contributing to understand the intermediate traits through which genetic variants impact complex organismal phenotypes.
Optimisation of the core subset for the APY approximation of genomic relationships
Authors: Pocrnic Ivan , Lindgren Finn , Tolhurst Daniel , Herring William O. , Gorjanc Gregor 
Published: June 2022

AbstractBackgroundBy entering the era of mega-scale genomics, we are facing many computational issues with standard genomic evaluation models due to their dense data structure and cubic computational complexity. Several scalable approaches have have been proposed to address this challenge, like the Algorithm for Proven and Young (APY). In APY, genotyped animals are partitioned into core and non-core subsets, which induces a sparser inverse of genomic relationship matrix. The partitioning into subsets is often done at random. While APY is a good approximation of the full model, the random partitioning can make results unstable, possibly affecting accuracy or even reranking animals. Here we present a stable optimisation of the core subset by choosing animals with the most informative genotype data.MethodsWe derived a novel algorithm for optimising the core subset based on the conditional genomic relationship matrix or the conditional SNP genotype matrix. We compared accuracy of genomic predictions with different core subsets on simulated and real pig data. The core subsets were constructed (1) at random, (2) based on the diagonal of genomic relationship matrix, (3) at random with weights from (2), or (4) based on the novel conditional algorithm. To understand the different core subset constructions, we have visualised population structure of genotyped animals with the linear Principal Component Analysis and the non-linear Uniform Manifold Approximation and Projection.ResultsAll core subset constructions performed equally well when the number of core animals captured most of variation in genomic relationships, both in simulated and real data. When the number of core animals was not optimal, there was substantial variability in results with the random construction and no variability with the conditional construction. Visualisation of population structure and chosen core animals showed that the conditional construction spreads core animals across the whole domain of genotyped animals in a repeatable manner.ConclusionsOur results confirm that the size of the core subset in APY is critical. The results further show that the core subset can be optimised with the conditional algorithm that achieves a good and repeatable spread of core animals across the domain of genotyped animals.
Reshaping the dynamics of follicle-stimulant hormone receptor models in polyunsaturated lipid bilayers. Calculation of conformational free energy landscapes of α-helical domains from all-atom MD simulations
Authors: Jardón-Valadez Eduardo , Ulloa-Aguirre Alfredo , Portillo-Bobadilla Tobías , Villavicencio-Pulido Geiser 
Published: June 2022

AbstractG-coupled-protein receptors (GPCR) are conspicuous target molecules for novel therapeutic drugs due to their role as mediators of cellular responses. Structural biology of GPCR revealed that intracellular signaling stimulated by extracellular ligands involves subtle conformational changes of the receptor during activation. Nonetheless, transitions among intermediates evolve in an intricate and rough free energy landscape of the conformational space. Experimental evidence suggests that the membrane environment is an active modulator of the receptor dynamics; therefore, the lipid composition may facilitate conformational transitions towards productive signaling states. In this study, we setup molecular dynamics simulations to examine the conformational dynamics of the transmembrane domains, in the context of a membrane of polyunsaturated phospholipid molecules, for a homology model of the human follicle-stimulating-hormone receptor (FSHR) and the crystal structure of the Lumi intermediate of the squid rhodopsin (LSRh). The conformational dynamics of the α−helical domains of LSRh was consistent with interactions stabilizing the crystal structure, which remained well preserved in the membrane environment. In contrast, conformations in the FSHR model evolved towards stable states in the membrane environment. To assess the relevance of the conformational dynamics in the FSHR model, dihedral restraints were imposed for the helical domains on top of the force field. This strategy was implemented to reoptimize the interhelical interactions probably overlooked in the modeling process. The conformational dynamics in the helical domains was evaluated by the TM-score, contact maps, principal components analysis of Cα atoms at the helical domains, and projections of the conformational free energy on principal components. The roughness of the conformational landscape in the FSHR model without dihedral restraints, suggested that alternative interhelical conformational states were populated, whereas imposing restraints led to a dominant conformational state. Template-based models of GPCR, with reoptimized interhelical interactions using dihedral restraints, may enhance the identification of binding sites for potential therapeutic drugs.
Predicting supply chain risks through big data analytics: role of risk alert tool in mitigating business disruption
Authors: Park Minseok , Singh Nitya Prasad 
Published: June 2022

PurposeAs organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how to effectively manage the increasing risks to their supply chain. Therefore, the purpose of this paper is to bring these two issues on a single platform to understand how firms can effectively predict supply chain risk by developing and using BDA capabilities, through an automated risk alert tool.Design/methodology/approachThe authors used a questionnaire-based survey methodology supported by secondary data to collect information related to managerial perceptions on how firms can develop a risk alert tool by improving BDA capabilities. A database of 213 senior and middle-level managers was developed and used to test the proposed hypothesis. Using econometric techniques, the authors identify the conditions necessary for such an automated risk management tool to be effective.FindingsThe results suggest that if organizations focus on developing an effective IT infrastructure supported by a strong BDA capability, they will be able to leverage these capabilities to develop an effective risk management tool. Moderating influences of Upstream and Downstream Supply Chain IT Infrastructure capabilities were also observed on different types of BDA capabilities within a firm. In conclusion, it was argued that the effectiveness of a risk alert tool is dependent on how well firms harness big data analytics capability.Originality/valueThe value of the research stems from the fact that it uses managerial surveys to identify specific BDA capabilities that can enable firms to develop risk resilience capabilities. In addition, the article is one of the few empirical studies that aims to identify how firms can use BDA capabilities within a supply chain context to develop an automated risk alert tool. The article, therefore, contributes to the literature that identifies the value of BDA capabilities within the context of supply chain risk management.
Dependence and resource commitment as antecedents of supply chain integration
Authors: Tarifa Fernández Jorge 
Published: June 2022

PurposeThe purpose of this paper is to explore and further the existing knowledge on supply chain integration (SCI). This study proposes a model and several hypotheses to better understand some SCI antecedents, dependence and resource commitment and their relationships with performance.Design/methodology/approachBased on diverse theoretical approaches, the author develops and tests an integrated model in which dependence and resource commitment are proposed to enhance external integration, leading to an increase in economic performance. This study's empirical validity is reinforced by collecting data from 142 manufacturing firms in Spain and Germany and testing the model using structural equation model (SEM).FindingsThe results support dependence and resource commitment as antecedents of SCI, both with a positive effect. Also, discrepancies in the effect of external integration on performance are found where supplier integration seems not to have any effect on performance.Originality/valueThis study helps to better understand SCI antecedents. It makes both theoretical and managerial contributions by empirically analyzing both antecedents. This furthers extant knowledge regarding the joined impact of resource commitment and dependence on SCI. In particular, it incorporates resource commitment by considering it as the sacrifice firms need to implement to get involved in a long-term relationship.
Obtaining the most exact Jacobian of the time modelling of power electronics structures for gradient-based optimisations
Authors: Gerbaud Laurent , Diarra Zié Drissa , Chazal Herve , Garbuio Lauric 
Published: June 2022

Purpose
The paper aims to deal with the exact computation of the Jacobian of a time criteria from a numerical simulation of power electronics structures, for the sizing by gradient-based optimization algorithm.

Design/methodology/approach
Runge Kutta 44 is used to solve the state equations. The generic approach combines numerical and symbolic approaches. The modelling of the static converter is based on ideal switches.

Findings
The paper extends the state equations to derivate any state variable according a sizing parameter. The integral expressions used for some sizing performances (e.g. average or RMS values) mix symbolic and numerical approaches. Choices are made for the derivatives of the extrema of which the search is not a continuous process. The use of an object-oriented implementation allows to have generic formulation of some design performances.

Research limitations/implications
The paper aims to propose and to test formulations of sizing criteria and their gradients; so, the modelling of the study case is carried out manually. Due to generic modelling approach used for the power electronics, the model is not completely continuous. So, the derivatives according some parameters (e.g. switch controls) must be carried out by finite differences. However, as the global behaviour is continuous, it is not critical.

Practical implications
The proposed formulations can be easily applied on simple static converter applications. For applications with large state equations, it should be possible to use the basic model of switches used in simulation tools of power electronics. The solving process and the sizing criteria formulation (with their derivatives) are generic and can be instantiate for any study.

Originality/value
The approach proposes formulations giving a numerical sizing dynamic model with a Jacobian computed, if possible, by an exact derivation useful for optimization studies. The approach gives fast simulation and fast computation of the derivatives by combining numerical and analytical approaches.
Influence of social media adoption on the performance of construction small and medium-sized enterprises (SMEs) in Abuja – Nigeria
Authors: Oyewobi Luqman , Adedayo Olatunde Folaranmi , Olorunyomi Seth O. , Jimoh Richard Ajayi 
Published: June 2022

PurposeThe purpose of this paper is to examine the influence of social media adoption on the performance of construction small and medium-sized enterprises (SMEs).Design/methodology/approachConstruction SMEs owners and managers in Nigeria were surveyed using questionnaires to gather data. Partial least square structural equation modeling (PLS-SEM) was employed to assess measurement reliability and validity, as well as the hypothesized paths provided in the conceptual model that formed part of the final conclusions.FindingsThe empirical finding showed that social media usage increased knowledge accessibility, reduced costs and improved customer relations and service for organizations. Overall, social media adoption was significantly and positively related to SMEs business performance. Also, the paper revealed that learning capability mediates the relationship between social media and SMEs performance.Research limitations/implicationsData for the study came from only one industry and one related line of business; thus, including more companies from different sectors or industries could be more interesting. The study's findings contributed to the growing body of knowledge about the impact of social media on the efficiency of businesses. Small and medium-sized businesses also need to understand and recognize the impact of social media on the organization's performance in order to achieve a long-term competitive edge from the adoption of social media.Practical implicationsAccording to the findings, small construction firms can benefit from marketing the brands through social media channels and improved learning capability. In terms of accessibility, cost savings and improved relationships with customers, research shows that social media promotion can be beneficial to businesses. A study like this has the potential to show how social media can help striving small businesses interact cost-effectively with customers all over the world, opening new doors for sales and continuous improvement.Originality/valueThe relationship between SME performance in Nigeria and the use of social media has received very little attention despite social media's promising potentials, particularly for small businesses. The authors hoped that this study will fill a gap in the authors' understanding of how social media affects the performance of small and medium-sized businesses (SMEs) in the construction industry.
When does export customer responsiveness strategy contribute to export market competitive advantage?
Authors: Miocevic Dario , Gnizy Itzhak , Cadogan John W. 
Published: June 2022

PurposeThe purpose of this study is to explore the nature of the relationship between export customer responsiveness and export growth.Design/methodology/approachThe study uses primary data obtained by questioning over 200 exporting firms. The model constructed predicts the export growth of those firms with export customer responsiveness data, together with a variety of moderator and control variables. The model is assessed using multiple regression.FindingsExporters with higher levels of export customer responsiveness often have higher export sales growth rates than those with lower levels of export customer responsiveness, but not always. For some firms, the opposite is true, such that those with lower levels of export customer responsiveness outperform those with higher levels.Originality/valueThe study is the first to provide export decision-makers with empirically grounded recommendations regarding (1) when it is advisable to have high export customer responsiveness levels and (2) those situations when firms may benefit from having lower export customer responsiveness levels.
Reliability centered maintenance (RCM): literature review of current industry state of practice
Authors: Geisbush James , Ariaratnam Samuel T. 
Published: June 2022

PurposeReliability centered maintenance (RCM) is a process used to determine activities to be taken to ensure an asset continues to perform asset's function in asset's present operating context by identifying asset's function, failure modes that could preclude performing asset's intended function, prioritizing failure modes and determining effective preventative maintenance tasks that can be cost effectively and efficiently implemented to reduce the likelihood of a failure.Design/methodology/approachA comprehensive survey of literature was undertaken to examine the current industry state of practice. Various industries were examined to better understand applications of RCM within the various industry sectors and determine those industries that RCM has not historically been readily adopted. A case study example of RCM applied to radial gates for water control in open channel canals for water conveyance is presented to demonstrate a civil infrastructure application.FindingsThe results found that RCM has been used since RCM's inception in the airline industry during the 1960s to reduce the cost of maintaining aircrafts. Over the past 40 years, an assortment of industries has begun implementing cost effective preventative maintenance tasks identified during RCM analysis. However, there is a noticeable lack of civil assets being analyzed by RCM, such as water conveyance systems and other civil infrastructure systems vital to the health and well-being of today's societies.Originality/valueThe comprehensive literature review of the current state of practice will provide a better understanding of the various applications of RCM to facilitate RCM's application to other industries, thereby reducing failure due to early identification of maintenance tasks. An example RCM demonstrates the application to a radial gate, used in water conveyance for the drinking water and irrigation sectors, which have not historically used RCM for developing maintenance strategies.