bluuebunny/crossref_metadata_2025_split huggingface dataset:
Autophagy is impaired in fetal hypoplastic lungs and rescued by administration of amniotic fluid stem cell extracellular vesicles
Authors: Khalaj Kasra , Antounians Lina , Figueira Rebeca Lopes , Post Martin , Zani Augusto 
Published: January 2022

ABSTRACTRationalePulmonary hypoplasia secondary to congenital diaphragmatic hernia (CDH) is characterized by reduced branching morphogenesis, which is responsible for poor clinical outcomes. Administration of amniotic fluid stem cell extracellular vesicles (AFSC-EVs) rescues branching morphogenesis in rodent fetal models of pulmonary hypoplasia. Herein, we hypothesized that AFSC-EVs exert their regenerative potential by affecting autophagy, a process required for normal lung development.ObjectivesTo evaluate autophagy in hypoplastic lungs throughout gestation and establish whether AFSC-EV administration improves branching morphogenesis through autophagy-mediated mechanisms.MethodsEVs were isolated from c-kit+ AFSC conditioned medium by ultracentrifugation and characterized for size, morphology, and EV markers. Branching morphogenesis was inhibited in rat fetuses by nitrofen administration to dams and in human fetal lung explants by blocking RAC1 activity with NSC23766. Expression of autophagy activators (BECN1 and ATG5) and adaptor (SQSTM1/p62) was analyzed in vitro (rat and human fetal lung explants) and in vivo (rat fetal lungs). Mechanistic studies on rat fetal primary lung epithelial cells were conducted using inhibitors for microRNA-17 and -20a contained in the AFSC-EV cargo and known to regulate autophagy.Measurements and Main ResultsRat and human models of fetal pulmonary hypoplasia showed reduced autophagy mainly at pseudoglandular and canalicular stages. AFSC-EV administration restored autophagy in both pulmonary hypoplasia models by transferring miR-17∼92 cluster members contained in the EV cargo.ConclusionsAFSC-EV treatment rescues branching morphogenesis partly by restoring autophagy through miRNA cargo transfer. This study enhances our understanding of pulmonary hypoplasia pathogenesis and creates new opportunities for fetal therapeutic intervention in CDH babies.
A split ribozyme that links detection of a native RNA to orthogonal protein outputs
Authors: Gambill Lauren , Staubus August , Ameruoso Andrea , Chappell James 
Published: January 2022

ABSTRACTIndividual RNA remains a challenging signal to synthetically transduce into different types of cellular information. Here, we describe Ribozyme-ENabled Detection of RNA (RENDR), a plug-and-play strategy that uses cellular transcripts to template the assembly of split ribozymes, triggering splicing reactions that generate orthogonal protein outputs. To identify split ribozymes that require templating for splicing, we used laboratory evolution to evaluate the activities of different split variants of the Tetrahymena thermophila ribozyme. The best design delivered a 93-fold dynamic range of splicing with RENDR controlling fluorescent protein production in response to an RNA input. We resolved a thermodynamic model to guide RENDR design, showed how input signals can be transduced into diverse visual, chemical, and regulatory outputs, and used RENDR to detect an antibiotic resistance phenotype in bacteria. This work shows how transcriptional signals can be monitored in situ using RNA synthetic biology and converted into different types of biochemical information.
Explainable t-SNE for single-cell RNA-seq data analysis
Authors: Han Henry , Zhang Tianyu , Li Chun , Benton Mary Lauren , Wang Juan , Li Junyi 
Published: January 2022

AbstractBackgroundSingle-cell RNA (scRNA-seq) sequencing technologies trigger the study of individual cell gene expression and reveal the diversity within cell populations. To measure cell-to-cell similarity based on their transcription and gene expression, many dimension reduction methods are employed to retrieve corresponding low-dimensional embeddings of input scRNA-seq data to conduct clustering. However, the methods lack explainability and may not perform well with scRNA-seq data because they are not customized for high-dimensional sparse scRNA-seq data.ResultsIn this study, we propose an explainable t-SNE: cell-driven t-SNE (c-TSNE) that fuses cell differences reflected from biologically meaningful distance metrics for input data. Our study shows that the proposed method not only enhances the interpretation of the original t-SNE visualization but also demonstrates favorable single cell segregation performance on benchmark datasets compared to state-of-the-art peers. The robustness analysis shows that the proposed cell-driven t-SNE demonstrates robustness to dropout and noise in clustering. It provides a novel and practical way to investigate the interpretability of t-SNE in scRNA-seq data analysis. Unlike the general assumption that the explainability of a machine learning method may need to compromise with learning efficiency, the proposed explainable t-SNE improves both clustering efficiency and explainability. More importantly, our work suggests that widely used t-SNE can be easily misused in existing scRNA-seq analysis, because its default Euclidean distance can bring biases or meaningless results in cell difference evaluation for high-dimensional sparse scRNA-seq data. To the best of our knowledge, it is the first explainable t-SNE proposed in scRNA-seq analysis and will inspire other explainable machine learning method development in the field.ConclusionThe proposed explainable t-SNE outperforms classic t-SNE and its peers in meaningful visualization and segregation. The poor performance of the classic t-SNE highlights the importance of developing explainable machine learning methods in scRNA-seq analysis. The explainable t-SNE is a data-centric customized ML enhance efficiency in data analysis through bringing more biological insights and interpretations.
Myeloid-biased HSC require Semaphorin 4A from the bone marrow niche for self-renewal under stress and life-long persistence
Authors: Toghani Dorsa , Zeng Sharon , Mahammadov Elmir , Crosse Edie I. , Seyedhassantehrani Negar , Burns Christian , Gravano David , Radtke Stefan , Kiem Hans-Peter , Rodriguez Sonia , Carlesso Nadia , Pradeep Amogh , Wilson Nicola K. , Kinston Sarah J. , Göttgens Berthold , Nerlov Claus , Pietras Eric , Mesnieres Marion , Maes Christa , Kumanogoh Atsushi , Worzfeld Thomas , Kharchenko Peter , Scadden David T. , Scialdone Antonio , Spencer Joel A , Silberstein Lev 
Published: January 2022

SUMMARYTissue stem cells are hierarchically organized. Those that are most primitive serve as key drivers of regenerative response but the signals that selectively preserve their functional integrity are largely unknown. Here, we identify a secreted factor, Semaphorin 4A (Sema4A), as a specific regulator of myeloid-biased hematopoietic stem cells (myHSC), which are positioned at the top of the HSC hierarchy. Lack of Sema4A leads to exaggerated myHSC (but not downstream “balanced” HSC) proliferation after acute inflammatory stress, indicating that Sema4A enforces myHSC quiescence. Strikingly, aged Sema4A knock-out myHSC expand but almost completely lose reconstitution capacity. The effect of Sema4A is non cell-autonomous, since upon transplantation into Sema4A-deficient environment, wild-type myHSC excessively proliferate but fail to engraft long-term. Sema4A constrains inflammatory signaling in myHSC and acts via a surface receptor Plexin-D1. Our data support a model whereby the most primitive tissue stem cells critically rely on a dedicated signal from the niche for self-renewal and life-long persistence.
Cell- and non-cell-autonomous ARF3 coordinates meristem proliferation and organ patterning in Arabidopsis
Authors: Zhang Ke , Zhang Hao , Pan Yanyun , Guo Lin , Tian Shijun , Wei Jiarong , Fu Yunze , Wang Cong , Qu Ping , Liu Liantao , Zhang Yongjiang , Sun Hongchun , Bai Zhiying , Dong Jingao , Li Cundong , Liu Xigang 
Published: January 2022

ABSTRACTIn cell–cell communication, non-cell-autonomous transcription factors play vital roles in controlling plant stem cell fate. We previously reported that AUXIN RESPONSE FACTOR 3 (ARF3), a member of the ARF family with critical roles in floral meristem maintenance and determinacy, has a distinct accumulation pattern that differs from the expression domain of its encoding gene in the shoot apical meristem (SAM). However, the biological meaning of this difference is obscure. Here, we demonstrate that ARF3 expression is mainly activated at the periphery of the SAM by auxin, where ARF3 cell-autonomously regulates the expression of meristem–organ boundary-specific genes, such as CUP-SHAPED COTYLEDON1-3 (CUC1-3), BLADE ON PETIOLE1-2 (BOP1-2) and TARGETS UNDER ETTIN CONTROL3 (TEC3) to determine organ patterning. We also show that ARF3 is translocated into the organizing center, where it represses cytokinin activity and WUSCHEL expression to regulate meristem activity non-cell-autonomously. Therefore, ARF3 acts as a molecular link that mediates the interaction of auxin and cytokinin signaling in the SAM while coordinating the balance between meristem maintenance and organogenesis. Our findings reveal an ARF3-mediated coordination mechanism through cell–cell communication in dynamic SAM maintenance.
Sequence Coverage Visualizer: A web application for protein sequence coverage 3D visualization
Authors: Shao Xinhao , Grams Christopher , Gao Yu 
Published: January 2022

AbstractProtein structure is connected with its function and interaction and plays an extremely important role in protein characterization. As one of the most important analytical methods for protein characterization, Proteomics is widely used to determine protein composition, quantitation, interaction, and even structures. However, due to the gap between identified proteins by proteomics and available 3D structures, it was very challenging, if not impossible, to visualize proteomics results in 3D and further explore the structural aspects of proteomics experiments. Recently, two groups of researchers from DeepMind and Baker lab have independently published protein structure prediction tools that can help us obtain predicted protein structures for the whole human proteome. Although there is still debate on the validity of some of the predicted structures, it is no doubt that these represent the most accurate predictions to date. More importantly, this enabled us to visualize the majority of human proteins for the first time. To help other researchers best utilize these protein structure predictions, we present the Sequence Coverage Visualizer (SCV), http://scv.lab.gy, a web application for protein sequence coverage 3D visualization. Here we showed a few possible usages of the SCV, including the labeling of post-translational modifications and isotope labeling experiments. These results highlight the usefulness of such 3D visualization for proteomics experiments and how SCV can turn a regular result list into structural insights. Furthermore, when used together with limited proteolysis, we demonstrated that SCV can help validate and compare different protein structures, including predicted ones and existing PDB entries. By performing limited proteolysis on native proteins at various time points, SCV can visualize the progress of the digestion. This time-series data further allowed us to compare the predicted structure and existing PDB entries. Although not deterministic, these comparisons could be used to refine current predictions further and represent an important step towards a complete and correct protein structure database. Overall, SCV is a convenient and powerful tool for visualizing proteomics results.
Antigenic evolution of SARS-CoV-2 in immunocompromised hosts
Authors: Smith Cameron A. , Ashby Ben 
Published: January 2022

AbstractProlonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution. Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis. We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.Lay SummaryWe study the role that immunocompromised individuals may play in the evolution of novel variants of the coronavirus responsible for the COVID-19 pandemic. We show that immunocompromised hosts can be crucial for the evolution of immune escape variants. Targeted treatment and surveillance may therefore prevent the emergence of new variants.
Fuel flow rate modeling for descent using cuckoo search algorithm: a case study for point merge system procedure at Istanbul airport
Authors: Oruc Ridvan , Sahin Ozlem , Baklacioglu Tolga 
Published: January 2022

Purpose
The purpose of this paper is to create a new fuel flow rate model using cuckoo search algorithm (CSA) for the descending stage of the flight.

Design/methodology/approach
Using the actual flight data record data of the B737-800 aircraft, a new fuel flow rate model has been developed for this aircraft type. The created model is to predict the fuel flow rate with high accuracy depending on the altitude and true airspeed. In addition, the CSA fuel flow rate model was used to calculate the fuel consumption for the point merge system, which is used for combining the initial approach to the final approach at Istanbul Airport, the largest airport of Turkey.

Findings
As a result of the analysis, the correlation coefficient value is found as 0.996858 for Flight 1, 0.998548 for Flight 2, 0.995363 and 0.997351 for Flight 3 and Flight 4, respectively. The values that are so close to 1 indicate that the model predicts the real fuel flow rate data with high accuracy.

Practical implications
This model is considered to be useful in air traffic management decision support systems, aircraft performance models, models used for trajectory prediction and strategies used by the aviation community to reduce fuel consumption and related emissions.

Originality/value
The importance of this study lies in the fact that to the best of the authors’ knowledge, it is the first fuel flow rate model developed using CSA for the descent stage in the existing literature; the data set used is real values.
Fake or real news? Understanding the gratifications and personality traits of individuals sharing fake news on social media platforms
Authors: Sampat Brinda , Raj Sahil 
Published: January 2022

Purpose“Fake news” or misinformation sharing using social media sites into public discourse or politics has increased dramatically, over the last few years, especially in the current COVID-19 pandemic causing concern. However, this phenomenon is inadequately researched. This study examines fake news sharing with the lens of stimulus-organism-response (SOR) theory, uses and gratification theory (UGT) and big five personality traits (BFPT) theory to understand the motivations for sharing fake news and the personality traits that do so. The stimuli in the model comprise gratifications (pass time, entertainment, socialization, information sharing and information seeking) and personality traits (agreeableness, conscientiousness, extraversion, openness and neuroticism). The feeling of authenticating or instantly sharing news is the organism leading to sharing fake news, which forms the response in the study.Design/methodology/approachThe conceptual model was tested by the data collected from a sample of 221 social media users in India. The data were analyzed with partial least squares structural equation modeling to determine the effects of UGT and personality traits on fake news sharing. The moderating role of the platform WhatsApp or Facebook was studied.Findings The results suggest that pass time, information sharing and socialization gratifications lead to instant sharing news on social media platforms. Individuals who exhibit extraversion, neuroticism and openness share news on social media platforms instantly. In contrast, agreeableness and conscientiousness personality traits lead to authentication news before sharing on the social media platform.Originality/value This study contributes to social media literature by identifying the user gratifications and personality traits that lead to sharing fake news on social media platforms. Furthermore, the study also sheds light on the moderating influence of the choice of the social media platform for fake news sharing.
Fostering sustainable logistics businesses: the role of innovation ecosystems and institutional contexts for logistics firms in China
Authors: Liu Yulong , Chung Henry F.L. , Mi Lili 
Published: January 2022

PurposeDrawing on institution embeddedness and the resource-based view, the authors develop a theoretical framework and empirically examine how intra-national innovation ecosystems and environmental institutions impact logistics service providers' (LSPs) technological innovation (TI) and green practices.Design/methodology/approachThe authors test the theoretical framework based on survey data of 328 Chinese LSPs. Archival datasets complement the survey data.FindingsThe research reveals that intra-national institutional forces of formal and informal environment-related institutions can mitigate LSPs' reliance on their firm-specific advantages when engaging in TI and green practices. Results from a three-way interaction indicate that intra-national innovation ecosystems positively moderate the effects of environmental institutions.Research limitations/implicationsThe research has three critical implications. First, the study reveals the contingency role of intra-national environment-related institutions and innovation ecosystems in shaping green logistics. Second, the study finds new results about the roles of informal environmental institutions. Finally, intra-national innovation ecosystems can override environmental institutions in influencing the green practices of LSPs.Originality/valueTaking a unique angle of institution embeddedness coupled with the resource-based view, the authors examined how intra-national ecosystems and environmental institutions impact LSPs' TI and green practices.
Corporate governance reform in Nigeria: upstream and downstream interventions
Authors: Nakpodia Franklin , Olan Femi 
Published: January 2022

Purpose
Internal (e.g. firm performance, internal stakeholders) and external pressures (e.g. globalisation, technology, corporate scandals) have intensified calls for corporate governance reforms across varieties of capitalism. Yet, corporate governance practices among developing economies remain problematic. Drawing insights from Africa’s largest economy (Nigeria) and relying on the resource dependence theorisation, this study aims to address two questions – what are the prerequisites for effective reforms; and what reforms yield robust corporate governance?

Design/methodology/approach
This study adopts a qualitative methodology comprising semi-structured interviews with 21 executives in publicly listed Nigerian firms. The interviews were analysed using the content analysis technique.

Findings
This study proposes two sequential reforms (i.e. the upstream and downstream). The upstream factors highlight the preconditions that support corporate governance reforms, i.e. government commitment and enabling environment, while the downstream reforms combine elements of awareness and regulation to proffer robust corporate governance interventions.

Originality/value
This research further stresses the need to consider a bottom-up approach to corporate governance in place of the dominant top-down strategy. This strategy allows agents to participate actively in corporate governance policy-making rather than a top-down model, which imposes corporate governance on agents.
Tribological behavior of UHMWPE in water lubrication: the effect of molding temperature
Authors: Zhou Xincong , Yang Chaozhen , Huang Jian , Liu Xueshen , Zhong Da , Wang Peng , Wan Gao 
Published: January 2022

Purpose
Ultra-high molecular weight polyethylene (UHMWPE) is adopted in water-lubricated bearings for its excellent performance. This paper aims to investigate the tribological properties of UHMWPE with a molecular weight of 10.2 million (g mol‐1) under different molding temperatures.

Design/methodology/approach
The UHMWPE samples were prepared by mold pressing under constant pressure and different molding temperatures (140°C, 160°C, 180°C, 200°C, 220°C). The friction and wear tests in water were conducted at the RTEC tribo-tester.

Findings
The friction coefficient and wear loss decreased first and rose later with the increasing molding temperature. The minimums of the friction coefficient and wear loss were found at the molding temperatures of 200°C. At low melting temperatures, the UHMWPE molecular chains could not unwrap thoroughly, leading to greater abrasive wear. On the other hand, high melting temperatures will cause the UHMWPE molecular chains to break up and decompose. The optimal molding temperatures for UHMWPE were found to be 200°C.

Originality/value
Findings are of great significance for the design of water-lubricated UHMWPE bearings.
Genetic nutrition programmes – disappointment or empowered health? Exploring consumer engagement to understand social health change
Authors: Conroy Denise Maria , Errmann Amy , Young Jenny , Fifita Ilaisaane M.E. 
Published: January 2022

PurposeThis research aims to gain insight into how consumers interact with a commercially available genetic nutrition programme, DNAfit, to explore health change via an intervention.Design/methodology/approachFocus groups were conducted between June and October 2019, pre-, during- and post-intervention, with a total sample of 14 younger (aged 25–44 years) and 14 mature (aged 45–65 years) cohorts from New Zealand. Qualitative thematic analysis was completed with the help of NVivo software.FindingsYounger participants in this study engaged less overall with DNAfit, felt the service did not match their lifestyles and did not encourage their believability of genetic personalised nutrition (GPN). In contrast, mature participants had positive engagement with GPN, as their motivation to use the service fit with their motivation for longevity. Overall, social uptake in health changes based on GPN is likely to depend on life stage.Originality/valueThis paper adds to limited social marketing research, which seeks novel avenues to explore how consumers engage with GPN technologies to drive social change, assisting social marketers on how to more effectively deliver health programmes that allow consumer-driven interaction to build health capabilities.