bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plasmacytoid dendritic cells mediate CpG-ODN induced increase in survival in a mouse model of lymphangioleiomyomatosis
Authors: Amosu Mayowa M , Jankowski Ashleigh M , McCright Jacob C , Yang Bennett E , Fernandez Juan Grano de Oro , Moore Kaitlyn A , Gadde Havish S , Donthi Mehul , Kaluzienski Michele L , Sriram Vedanth , Maisel Katharina 
Published: February 2023

ABSTRACTLymphangioleiomyomatosis (LAM) is a devastating disease primarily found in women of reproductive age that leads to cystic destruction of the lungs. Recent work has shown that LAM causes immunosuppression and that checkpoint inhibitors can be used as LAM treatment. Toll-like receptor (TLR) agonists can also re-activate immunity and the TLR9 agonist, CpG-ODN, has been effective in treating lung cancer in animal models. Here we investigate the use of TLR9 agonist CpG-ODN as LAM immunotherapy in combination with checkpoint inhibitor, anti-PD1, standard of care rapamycin and determine the immune mechanisms underlying therapeutic efficacy. We used survival studies, flow cytometry, ELISA, and histology to assess immune response and survival after intranasal treatment with CpG-ODN in combination with rapamycin or anti-PD1 therapy in a mouse model of metastatic LAM. We found that local administration of CpG-ODN enhances survival in a mouse model of LAM. We found that a lower dose led to longer survival likely due to fewer local side effects but increased LAM nodule count and size compared to the higher dose. CpG-ODN treatment also reduced regulatory T cells and increased the number of Th17 helper T cells as well as cytotoxic T cells. These effects appear to be mediated in part by plasmacytoid dendritic cells (pDCs), as depletion of pDCs reduces survival and abrogates Th17 T cell response. Finally, we found that CpG-ODN treatment is effective in early stage and progressive disease and is additive with anti-PD1 therapy and rapamycin. In summary, we have found that TLR9 agonist CpG-ODN can be used as LAM immunotherapy and effectively synergizes with rapamycin and anti-PD1 therapy in LAM.
Transcriptional profile of ribosome-associated quality control components and their associated phenotypes in mammalian cells
Authors: Leitão Dos Santos Otávio Augusto , Carneiro Rodolfo L. , Requião Rodrigo D. , Ribeiro-Alves Marcelo , Domitrovic Tatiana , Palhano Fernando L. 
Published: February 2023

AbstractDuring protein synthesis, organisms detect translation defects that induce ribosome stalling and result in protein aggregation. The Ribosome-associated Quality Control (RQC) complex, comprising TCF25, LTN1, and NEMF, is responsible for identifying incomplete protein products from unproductive translation events, targeting them for degradation. Though RQC disruption causes adverse effects on vertebrate neurons, data regarding mRNA/protein expression and regulation across tissues are lacking. Employing high-throughput methods, we analyzed public datasets to explore RQC gene expression and phenotypes. Our findings revealed a widespread expression of RQC components in human tissues; however, silencing of RQC yielded only mild negative effects on cell growth. Notably, TCF25 exhibited elevated mRNA levels that were not reflected in protein content. We experimentally demonstrated that this disparity arises from post-translational protein degradation by the proteasome. Additionally, we observed that cellular aging marginally influences RQC expression, leading to reduced mRNA levels in specific tissues. Our results suggest the necessity of RQC expression in all mammalian tissues. Nevertheless, when RQC falters, alternative mechanisms seem to compensate, ensuring cell survival under non-stress conditions.
Coupling Flux Balance Analysis with Reactive Transport Modeling through Machine Learning for Rapid and Stable Simulation of Microbial Metabolic Switching
Authors: Song Hyun-Seob , Ahamed Firnaaz , Lee Joon-Yong , Henry Christopher C. , Edirisinghe Janaka N. , Nelson William C. , Chen Xingyuan , Moulton J. David , Scheibe Timothy D. 
Published: February 2023

AbstractIntegration of genome-scale metabolic networks with reactive transport models (RTMs) is an advanced simulation technique that enables predicting the changes of microbial growth and metabolism in space and time. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated implementation of linear programming (LP) to get flux balance analysis (FBA) solutions in every time step and every spatial grid. To address this challenge, we propose a new simulation method where we train/validate artificial neural networks (ANNs) using FBA solutions randomly sampled and incorporate the resulting reduced-order FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study ofShewanella oneidensisMR-1 strain. During the aerobic growth on lactate,S. oneidensisproduces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred ones are depleted. Simulating such intricate dynamics posed a considerable challenge, which we overcame by adopting the cybernetic approach that describes metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based reduced-order models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Importantly, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.
IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods
Authors: Yan Aimin , Baricordi Cristina , Nguyen Quoc , Barbarossa Luigi , Loperfido Mariana , Biasco Luca 
Published: February 2023

AbstractIntegration site (IS) analysis is a fundamental analytical platform for evaluating the safety and efficacy of viral vector based preclinical and clinical Gene Therapy (GT). A handful of groups have developed standardized bioinformatics pipelines to process IS sequencing data, to generate reports, and/or to perform comparative studies across different GT trials. Keeping up with the technological advances in the field of IS analysis, different computational pipelines have been published over the past decade. These pipelines focus on identifying integration sites (IS) from single-read sequencing or paired-end sequencing data either using read-based or using sonication fragment-based methods, but there is a lack of a bioinformatics tool that automatically includes unique molecular identifiers (UMI) for IS abundance estimations and allows comparing multiple quantification methods in one integrated pipeline. Here we present IS-seq a bioinformatics pipeline that can process data from paired-end sequencing of both old restriction sites-based IS collection methods and new sonication-based IS retrieval systems while allowing the selection of different abundance estimation methods, including read-based, Fragment-based and UMI-based systems. We validated the performance of IS-Seq testing it against the most widely used analytical workflow available in the literature (INSPIIRED) and using different scenarios. Lastly, by performing a comprehensive wet-lab assessment of our IS-Seq pipeline we could show that in clinically relevant scenarios, UMI quantification provides better accuracy than the currently most widely used sonication fragment counts as a method for IS abundance estimation.
ABI5-FLZ13 Module Transcriptionally Represses Growth-related Genes to Delay Seed Germination in Response to ABA
Authors: Yang Chao , Li Xibao , Chen Shunquan , Liu Chuanliang , Yang Lianming , Li Kailin , Liao Jun , Zheng Xuanang , Li Hongbo , Li Yongqing , Zeng Shaohua , Zhuang Xiaohong , Rodriguez Pedro L. , Luo Ming , Wang Ying , Gao Caiji 
Published: February 2023

AbstractThe bZIP transcription factor ABSCISIC ACID INSENSITIVE5 (ABI5) is a master regulator determining seed germination and postgerminative growth in response to abscisic acid (ABA), but the detailed molecular mechanism underlying the repression function of ABI5 in plant growth remains to be characterized. In this study, we used proximity labeling (PL) to map the neighboring proteome of ABI5 and identified FCS-LIKE ZINC FINGER PROTEIN 13 (FLZ13) as an up-to-now unknown ABI5-interacting partner. Phenotypic analysis offlz13mutants andFLZ13-overexpressing lines demonstrated that FLZ13 acts as a positive regulator of ABA signaling. Interestingly, transcriptomic analysis showed that ABI5 and FLZ13 co-downregulate the expression of ABA-repressed and growth-related genes involved in chlorophyll biosynthesis, photosynthesis and cell wall organization, thereby repressing seed germination and seedling establishment in response to ABA. Further genetic analysis proved that FLZ13 works synergistically with ABI5 to regulate seed germination. Collectively, our study reveals a previously uncharacterized transcriptional regulatory mechanism regarding ABA-inhibited seed germination and seedling establishment.
The hierarchical structure of canine cognition: two domains and a general cognitive factor
Authors: Bognár Zsófia , Turcsán Borbála , Faragó Tamás , Szabó Dóra , Iotchev Ivaylo Borislavov , Kubinyi Enikő 
Published: February 2023

AbstractThe complex human environment results in a hard-to-bridge gap between human and animal studies on general cognitive abilities (g; colloquially often referred to as “intelligence”). Pet dogs are adapted to our environment, but a convincing demonstration ofgis missing. Exploratory and confirmatory factor analyses on seven tasks revealed a hierarchical structure with two cognitive domains (problem solving, learning) and an overarchingcanine g. Age did not affect the structure.Canine gwas negatively linked to age, height, and the owner’s emotional attitude but positively to training level, activity/excitability trait, experienced trauma and normal body condition. The longitudinal analyses over three years differentiated three main trajectory clusters: declining, stable, improving. The diversity of ageing phenotypes supports dogs’ translational value ingfactor and ageing research.One-Sentence SummaryThecanine gfactor is linked to age, height, training level, personality, body condition, and owner’s attitude.
ADP-ribose-acceptor hydrolase 2(Arh2) deficiency results in cardiac dysfunction, tumorigenesis, inflammation, and decreased survival
Authors: Kato Jiro , Yamashita Sachiko , Ishiwata-Endo Hiroko , Oka Shunya , Yu Zu-Xi , Liu Chengyu , Springer Danielle A. , Noguchi Audrey , Peiravi Morteza , Hoffmann Victoria , Lizak Martin J. , Medearis Matthew , Kim In-Kwon , Moss Joel 
Published: February 2023

AbstractADP-ribosylation is a reversible reaction with ADP-ribosyltransferases catalyzing the forward reaction and ADP-ribose-acceptor hydrolases (ARHs) hydrolyzing the ADP-ribose acceptor bond. ARH2 is a member of the 39-kDa ARH family (ARH1-3), which is expressed in heart and skeletal muscle. ARH2 failed to exhibit any in vitro enzymatic activity. To determine its possible in vivo activities,Arh2-knockout (KO) and - heterozygous (Het) mice were generated using CRISPR-Cas9.Arh2-KO mice exhibited decreased cardiac contractility by MRI, echocardiography and dobutamine stress with cardiomegaly and abnormal motor function.Arh2-Het mice showed results similar to those seen inArh2-KO mice except for cardiomegaly.Arh2-KO and -Het mice and mouse embryonic fibroblasts (MEFs) developed spontaneous tumors and subcutaneous tumors in nude mice. We identified 13 mutations inArh2-Het MEFs and heterozygous tumors, corresponding to humanARH2mutations in cancers obtained from COSMIC. Of interest, the L116R mutation inArh2gene plays a critical role in aggressive tumorigenesis in nude mice, corresponding to humanARH2mutations in stomach adenocarcinoma. Both genders ofArh2-KO and -Het mice showed increased unexpectedly deaths and decreased survival rate during a 24-month observation, caused by tumor, inflammation, non-inflammation (e.g., cardiomegaly, dental dysplasia), and congenital diseases. Thus,Arh2plays a pivotal role in cardiac function, tumorigenesis, inflammation, and overall survival.
Application of G-N high-order boundary condition on time harmonic analysis of concrete gravity dam-reservoir systems
Authors: Dehghanmarvasty Solmaz , Lotfi Vahid 
Published: February 2023

PurposeThe response of an idealized triangular concrete gravity dam is studied due to horizontal and vertical ground motions for both fully reflective and absorptive reservoir bottom conditions. For each combination, in this paper different orders of Givoli-Neta (G-N) high-order truncation condition are aimed to be evaluated from accuracy point of view by comparing the results against corresponding exact solutions which relies on utilizing a two-dimensional fluid hyper-element.Design/methodology/approachIn present study, the dynamic analysis of concrete gravity dam-reservoir systems is formulated by Finite Element (FE)-(FE-TE) approach. In this technique, dam and reservoir are discretized by plane solid and fluid finite elements. Moreover, the G-N high-order condition imposed at the reservoir truncation boundary. This task is formulated by employing a truncation element at that boundary. It is emphasized that reservoir far-field is excluded from the discretized model.FindingsIt was observed that trend in gaining accuracy with increase in the order of G-N condition were basically the same for both horizontal and vertical ground motions under full reflective reservoir bottom condition. Moreover, convergence rate increases for absorptive reservoir bottom condition cases in comparison with fully reflective cases. It is also noticed that in certain cases, the responses are hardly distinguishable from corresponding exact responses. This reveals that proposed FE-(FE-TE) analysis technique based on G-N condition is quite successful, and one may fully rely on that for accurate and efficient analysis of concrete gravity dam-reservoir systems.Originality/valueDynamic analysis of concrete gravity dam-reservoir systems are formulated by a new method. The salient aspect of the technique is that it utilizes G-N high-order condition at the truncation boundary. This is achieved by developing a special truncation element which its generalized matrices are derived for Finite Element Method (FEM) programmers. The method is discussed for all types of excitation and reservoir bottom conditions. It must be emphasized that although time harmonic analysis is considered in the present study, the main part of formulation is explained in the context of time domain. Therefore, the approach can easily be extended for transient type of analysis.
Knowledge graph embedding for experimental uncertainty estimation
Authors: Ramalli Edoardo , Pernici Barbara 
Published: February 2023

Purpose
Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

Design/methodology/approach
This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

Findings
The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

Originality/value
The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.
Resilient SMEs and entrepreneurs: evidence from the UK craft brewing sector
Authors: Waehning Nadine , Bosworth Gary , Cabras Ignazio , Shakina Ekatarina , Sohns Franziska 
Published: February 2023

PurposeThe paper examines the sudden changes and challenges experienced by British craft breweries because of COVID-19. The purpose is twofold; firstly, to evaluate the overall growth trajectory of the craft brewing sector prior to the pandemic crisis and, secondly, to identify features of resilience and adaptability that aided business survival.Design/methodology/approachThe authors conducted 24 interviews with a sample of craft brewers during 2020, supplemented with a focus group later in 2021, to understand the impacts of COVID-19 on their businesses. Inductive thematic analysis followed a flexible six-stage approach to generating codes. Qualitative findings were set in the context of the pre-COVID-19 industry trends which were analysed using panel data from the Society of Independent Brewers' (SIBA) Annual Surveys between 2015 and 2018.FindingsFindings from the analysis reveal a range of factors influencing growth in the UK craft beer sector before the pandemic crisis, such as levels of investment and local network ties, and identify a range of strategies implemented by brewers in response to the crisis, including new packaging and supply channels, more intensive marketing and greater online engagement with customers. Analysis of the intersection between aspects of individual and organisational resilience also revealed that dynamic responses to an external crisis depend on individual resilience characteristics before organisational strategies can be developed.Originality/valueThe study provides fresh empirical evidence to practitioners and policymakers to help forecast and future-proof the UK craft beer sector, as well as elucidating aspects of resilience that apply to SMEs in the global industry who face similar challenges. Moving towards a post-COVID-19 economy, the paper offers important theoretical insights into how the resilience of breweries, and other SMEs, is shaped by complex interdependencies and networks and how their adaptive responses might strengthen future business models.
Students between science and society: why students’ learning experiences in transformative spaces are vital to higher education institutions
Authors: Trechsel Lilian Julia , Diebold Clara Léonie , Zimmermann Anne Barbara , Fischer Manuel 
Published: February 2023

Purpose
This study aims to explore how the boundary between science and society can be addressed to support the transformation of higher education towards sustainable development (HESD) in the sense of the whole institution approach. It analyses students’ learning experiences in self-led sustainability projects conducted outside formal curricula to highlight their potential contribution to HESD. The students’ projects are conceived as learning spaces in “sustainability-oriented ecologies of learning” (Wals, 2020) in which five learning dimensions can be examined.

Design/methodology/approach
Using an iterative, grounded-theory-inspired qualitative approach and sensitising concepts, 13 in-depth semi-structured interviews were conducted exploring students’ learning experiences. Interviews were categorised in MAXQDA and analysed against a literature review.

Findings
Results revealed that students’ experiences of non-formal learning in self-led projects triggered deep learning and change agency. Trust, social cohesion, empowerment and self-efficacy were both results and conditions of learning. Students’ learnings are classified according to higher education institutions’ (HEIs) sustainability agendas, providing systematised insights for HEIs regarding their accommodative, reformative or transformative (Sterling, 2021) path to sustainable development.

Originality/value
The education for sustainable development (ESD) debate focuses mainly on ESD competences in formal settings. Few studies explore students’ learnings where formal and non-formal learning meet. This article investigates a space where students interact with different actors from society while remaining rooted in their HEIs. When acting as “change agents” in this hybrid context, students can also become “boundary agents” helping their HEIs move the sustainability agenda forward towards a whole institution approach. Learning from students’ learnings is thus proposed as a lever for transformation.
To automate or not to automate? A contingency approach to service automation
Authors: Hottat Eline , Leroi-Werelds Sara , Streukens Sandra 
Published: February 2023

PurposeFollowing a contingency approach, this paper aims to understand when service automation can enhance or destroy value for customers in the frontline by (1) providing a comprehensive overview of factors that influence the value co-creation/co-destruction potential of service automation and (2) zooming in on the combination of service contexts and service tasks to develop research propositions.Design/methodology/approachThis paper uses a grounded theory approach based on qualitative data from multiple methods (i.e. a diary study with follow-up interviews, a consultation of academic experts and a storyboard study) as well as a systematic literature review to develop (1) a Framework of Automated Service Interactions (FASI) and (2) a contingency model for service tasks/contexts.FindingsThis paper presents a framework which gives an overview of factors influencing the value co-creation/co-destruction potential of service automation. The framework discerns between three types of factors: service design (i.e. controllable and manageable by the organization), static contingency (i.e. uncontrollable and fixed) and dynamic contingency (i.e. uncontrollable and flexible). Furthermore, the paper presents a contingency model based on the combination of service contexts and service tasks which results in seven research propositions.Originality/valueThis paper brings structure in the fragmented field of service automation. It integrates and summarizes insights regarding service automation and sheds more light on when service automation has the potential to create or destroy value in the organizational frontline.