bluuebunny/crossref_metadata_2025_split huggingface dataset:
C/EBPα acts as an RNA binding protein essential for its chromatin recruitment and promotes Macrophage differentiation
Authors: Zhang Yanzhou , Bassal Mahmoud , Friedrich Daniel , Ummarino Simone , Verbiest Tom , Zhang Junyan , Tenen Danielle , Haribabu Arthanari , Tenen Daniel G 
Published: October 2021

AbstractC/EBPα has known to be a transcription factor that involved in Neutrophil differentiation for decades. However, exploring the Chromatin RNA Immunoprecipitation Sequencing (RIP), we discover that C/EBPα is a RNA binding protein mainly interacts with RNA introns. Structure study and RNA electrophoretic mobility shift assay (REMSA) show that C/EBPα interacts with RNA through two novel RNA binding domains distinct from its DNA binding domain. Mouse bone marrow transplantation and in vitro cytokine assay reveal that C/EBPα RNA binding is critical for Macrophage differentiation but not Neutrophil differentiation. Mechanically, RNA binding domains control specific gene transcription. In particular, PU.1 intron 4 RNA interacts with C/EBPα and recruit C/EBPα to its enhancer site, which facilitate PU.1 expression. Taken together, C/EBPα is demonstrated to be a RNA binding protein with unique function distinct from its DNA binding activity. Our finding transforms our knowledge of transcriptional regulation by transcription factor.One-Sentence SummaryC/EBPα interacts with RNA through novel RNA binding domains and regulates PU.1 expression during Macrophage differentiation.
Genome-wide distribution of Rad26 and Rad1-Rad10 reveals their relationship with Mediator and RNA polymerase II
Authors: Gopaul Diyavarshini , Wilkes Cyril Denby , Goldar Arach , Aiach Nathalie Giordanengo , Barrault Marie-Bénédicte , Novikova Elizaveta , Soutourina Julie 
Published: October 2021

AbstractTranscription is coupled with DNA repair, especially within nucleotide excision repair (NER). Mediator is a conserved coregulator playing a key role in RNA polymerase (Pol) II transcription. Mediator also links transcription and NER via a direct contact with Rad2/XPG endonuclease. In this work, we analyzed the genome-wide distribution of Rad26/CSB and that of Rad1-Rad10/XPF-ERCC1, addressing the question on a potential interplay of these proteins with Mediator and Pol II in yeast Saccharomyces cerevisiae. Our genome-wide analyses show that Rad1-Rad10 and Rad26 are present on the yeast genome in the absence of genotoxic stress, especially on highly transcribed regions, with Rad26 binding strongly correlating with that of Pol II. Moreover, we revealed that Rad1-Rad10 and Rad26 colocalize with Mediator on intergenic regions and physically interact with this complex. Using kin28 TFIIH mutant, we showed that Mediator stabilization on core promoters lead to an increase in Rad1-Rad10 chromatin binding, whereas Rad26 occupancy is less impacted by Mediator and follows mainly a decrease in Pol II transcription. Combined with multivariate analyses, our results reveal the interplay between Rad1-Rad10, Rad26, Mediator and Pol II, modulated by the binding dynamics of Mediator and Pol II transcription. In conclusion, we extend the Mediator link to Rad1-Rad10 and Rad26 NER proteins and reveal important differences in Mediator relationships with Rad2, Rad1-Rad10 and Rad26. Our work thus contributes to new concepts of the functional interplay between transcription and DNA repair, relevant for human diseases including cancer and XP/CS syndromes.
Abstract representations emerge naturally in neural networks trained to perform multiple tasks
Authors: Johnston W. Jeffrey , Fusi Stefano 
Published: October 2021

AbstractHumans and other animals demonstrate a remarkable ability to generalize knowledge across distinct contexts and objects during natural behavior. We posit that this ability to generalize arises from a specific representational geometry, that we call abstract and that is referred to as disentangled in machine learning. These abstract representations have been observed in recent neurophysiological studies. However, it is unknown how they emerge. Here, using feedforward neural networks, we demonstrate that the learning of multiple tasks causes abstract representations to emerge, using both supervised and reinforcement learning. We show that these abstract representations enable few-sample learning and reliable generalization on novel tasks. We conclude that abstract representations of sensory and cognitive variables may emerge from the multiple behaviors that animals exhibit in the natural world, and, as a consequence, could be pervasive in high-level brain regions. We also make several specific predictions about which variables will be represented abstractly.
MS2 RNA aptamer enhances prime editing in rice
Authors: Chai Yiping , Jiang Yuanyuan , Wang Junya , Qiao Dexin , Zhang Yu , Xin Cuiping , Zhou Yun , Wang Xue-Chen , Chen Qi-Jun 
Published: October 2021

AbstractPrime editing is a universal and very promising precise genome editing technology. However, optimization of prime editor (PE) from different aspects remains vital for its use as a routine tool in plant basic research and crop molecular breeding. In this report, we tested MS2-based prime editor (MS2PE). We fused the M-MLV reverse transcriptase (RT) gene variant to the MS2 RNA binding protein gene, MCP, and allowed the MCP-RT fusion gene to co-express with the SpCas9 nickase gene, SpCas9H840A, and various engineered pegRNAs harboring MS2 RNA (MS2pegR). Compared with control PEs, MS2PEs significantly enhanced editing efficiency at four of six targets in rice protoplasts, and achieved 1.2∼10.1-fold increase in editing efficiency at five of six targets in transgenic rice lines. Furthermore, we tested total 22 different MS2pegR scaffolds, 3 RT variants or genes, 2 MCP variants, and various combinations of the Cas9 nickase, RT, and MCP modules. Our results demonstrated an alternative strategy for enhancing prime editing.
The Resting-State Causal Human Connectome is Characterized by Hub Connectivity of Executive and Attentional Networks
Authors: Rawls Eric , Kummerfeld Erich , Mueller Bryon A. , Ma Sisi , Zilverstand Anna 
Published: October 2021

AbstractWe demonstrate a data-driven approach for calculating a “causal connectome” of directed connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non-Gaussian edge orientations. We used this approach to construct n=442 causal connectomes. These connectomes were very sparse in comparison to typical Pearson correlation-based graphs (roughly 2.25% edge density) yet were fully connected in nearly all cases. Prominent highly connected hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles: attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hub networks are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal connectivity analysis in psychiatry.
Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts
Authors: Nakayama Jun , Matsunaga Hiroko , Arikawa Koji , Yoda Takuya , Hosokawa Masahito , Takeyama Haruko , Yamamoto Yusuke , Semba Kentaro 
Published: October 2021

AbstractGene expression analysis at the single-cell level by next generation sequencing has revealed the existence of clonal dissemination and microheterogeneity in cancer metastasis. The current spatial analysis technologies can elucidate the heterogeneity of cell–cell interactions in situ. To reveal the regional and expressional heterogeneity in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model with our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed three cancer cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell (CSC)-like clusters (CD44/MYC-high, HMGA1-high). Reanalysis of public single-cell RNA-seq (scRNA-seq) datasets confirmed that the two CSC-like populations existed both in TNBC xenograft models and TNBC patients. In addition, the gene signature of the HMGA1-high CSC-like cluster has the potential to serve as a novel biomarker for diagnosis. The diversity of these multiple CSC-like populations may cause differential anticancer drug resistance, increasing the difficulty of curing this cancer.
Massively parallel identification of zipcodes in primary cortical neurons
Authors: von Kügelgen Nicolai , Mendonsa Samantha , Dantsuji Sayaka , Ron Maya , Kirchner Marieluise , Zerna Nadja , Bujanic Lucija , Mertins Philipp , Ulitsky Igor , Chekulaeva Marina 
Published: October 2021

SUMMARYCells adopt highly polarized shapes and form distinct subcellular compartments largely due to the localization of many mRNAs to specific areas, where they are translated into proteins with local functions. This mRNA localization is mediated by specific cis-regulatory elements in mRNAs, commonly called “zipcodes.” Their recognition by RNA-binding proteins (RBPs) leads to the integration of the mRNAs into macromolecular complexes and their localization. While there are hundreds of localized mRNAs, only a few zipcodes have been characterized. Here, we describe a novel neuronal zipcode identification protocol (N-zip) that can identify zipcodes across hundreds of 3’UTRs. This approach combines a method of separating the principal subcellular compartments of neurons – cell bodies and neurites - with a massively parallel reporter assay. Our analysis identifies the let-7 binding site and (AU)n motif as de novo zipcodes in mouse primary cortical neurons and suggests a strategy for detecting many more.
Is the Success of Adaptive Therapy in Metastatic Castrate-Resistant Prostate Cancer Influenced by Cell-Type-Dependent Production of Prostate-Specific Antigen?
Authors: Salvioli Monica , Vandelaer Len , Schneider Katharina , Cavill Rachel , Staňková Kateřina 
Published: October 2021

AbstractProstate-specific antigen (PSA) is the most common serum marker for prostate cancer. It is used to detect prostate cancer, to assess responses to treatment and recently even to determine when to switch treatment on and off in adaptive therapy protocols. However, the correlation between PSA and tumor volume is poorly understood. There is empirical evidence that some cancer cell types produce more PSA than others. Still, recent mathematical cancer models assume either that all cell types contribute equally to PSA levels, or that only specific subpopulations produce PSA at a fixed rate.Here, we compare time to competitive release of the PSA-based adaptive therapy protocol by Zhang et al. with that of the standard of care based on continuous maximum tolerable dose under different assumptions on PSA production. In particular, we assume that androgen dependent, androgen producing, and androgen independent cells may contribute to the PSA production to different extents.Our results show that, regardless the assumption on how much each type contributes to PSA production, the time to competitive release is always longer under adaptive therapy than under the standard of care. However, in some cases, e.g., if the androgen-independent cells are the only PSA producers, adaptive therapy protocol by Zhang et al. cannot be applied, because the PSA value never reaches half of its initial size and therefore therapy is never discontinued.Furthermore, we observe that in the adaptive therapy protocol, the number of treatment cycles and their length strongly depend on the assumptions about the PSA contribution of the three types. Our results support the belief that a better understanding of patient-specific PSA dynamics will lead to more successful adaptive therapies.
Shape optimization in acoustic–structure interaction
Authors: Kliewe Philipp , Laurain Antoine , Schmidt Kersten 
Published: October 2021

PurposeMotivated by the acoustics of motor vehicles, a coupled fluid–solid system is considered. The air pressure is modeled by the Helmholtz equation, and the structure displacement is described by elastodynamic equations. The acoustic–structure interaction is modeled by coupling conditions on the common interface. First, the existence and uniqueness of solutions are investigated, and then, after recalling fundamental notions of shape optimization, the tensor form of the distributed shape derivative is obtained for the coupled problem. It is then applied to the minimization of the sound pressure by variation of the structure shape through the positioning of beads.Design/methodology/approachThe existence and uniqueness of solutions up to eigenfrequencies are shown by the Fredholm–Riesz–Schauder theory using a novel decomposition into an isomorphism and a compact operator. For the design optimization, the distributed shape derivative is obtained using the averaged adjoint method. It is then used in a closed 3D optimization process of the position of a bead for noise reduction. In this process, the C++ library concepts are used to solve the differential equations on hexahedral meshes with the finite element method of higher order.FindingsThe existence and uniqueness of solutions have been shown for the case without absorption, where the given proof allows for extension to the case with absorption in the domain or via boundary conditions. The theoretical results show that the averaged adjoint can be applied to compute distributed shape derivatives in the context of acoustic–structure interaction. The numerical results show that the distributed shape derivative can be used to reduce the sound pressure at a chosen frequency via rigid motions of a nonsmooth shape.Originality/valueThe proof of shape differentiability and the calculation of the distributed shape derivative in tensor form allows to consider nonsmooth shapes for the optimization, which is particularly relevant for the optimal placement of beads or stampings in a structural-acoustic system.
An empirical investigation of the role of lean six sigma practices on quality performance in medical device manufacturing industry
Authors: Sim Choon Ling , Li Zeyun , Chuah Francis , Lim Yi Jin , Sin Kit Yeng 
Published: October 2021

Purpose
With the growing pressure to gain optimum level of quality and speed, Lean Six Sigma (LSS) practices have drawn considerable attention as a viable alternative for process improvement. However, previous studies revealed that there is very little systematic and rigorous research to validate the claims. In this regard, this paper aims to empirically examine the effect of LSS practices on quality performance in the medical device manufacturing industry.

Design/methodology/approach
For this study, partial least square–based structural equation modeling (PLS-SEM) was used to empirically examine the effect of LSS practices on quality performance in Malaysian medical device manufacturing industry.

Findings
The findings of this paper revealed that LSS practices have a significant and positive effect on quality performance in the medical device manufacturing industry.

Practical implications
This paper will serve as a valuable implication for industry practitioners in providing them with a clearer managerial direction to exploit the strength of LSS practices to achieve company’s quality goals. Moreover, this study will serve as a basis for future LSS scholars, providing them with valuable insights and directions for future research.

Originality/value
This paper develops a conceptual LSS framework that captures the integrated nature of two methodologies and provides empirical evidence that supports the positive influence of LSS practices on quality performance; hence, it contributes to the growing body of LSS literature in both theoretical and empirical sense.
Useful paths for identifying Lean Six Sigma improvement opportunities
Authors: Kane Victor E. 
Published: October 2021

PurposeThe goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects.Design/methodology/approachUsing a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis.FindingsSeven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification.Research limitations/implicationsAny starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list.Practical implicationsLearners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities.Originality/valueAny successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.
Territorial efficiency of social spending in Spain
Authors: García-Luque Olga , Lafuente-Lechuga Matilde , Faura-Martínez Úrsula 
Published: October 2021

PurposeRegional disparities in social risk levels threaten social cohesion in Spain, which cannot be justified by the territorial differences in social spending per capita. These divergences may encourage and spread nationalist positions and populist discourses. The objective of this paper is to examine the efficiency of social policies (health, education and social protection) aimed at reducing the risk of exclusion across Spanish autonomous communities.Design/methodology/approachThe authors use data envelopment analysis (DEA) to compare each autonomous community. The analysis will determine whether the autonomies' resources (inputs or social spending in this case) are appropriately translated into goods and/or services (outputs or social cohesion), and which regions are more efficient in doing so.FindingsThis work contributes to sustaining DEA analysis in the study of social policy efficiency, as it reveals the regions that have better adjustments between social investment and social results from a global perspective, as well as from the different intervention areas. The authors also provide a ranking of regions based on their relative efficiency, estimating a possible margin of improvement in the results.Originality/valueIt is unusual to include the disaggregated analysis of social spending in efficiency studies using DEA at regional level. Therefore, this is an innovative analysis compared to most extended models that are mainly concerned with health or education expenditure, which are also considered in this study.
Exploring environmental sustainability of academia as a working space
Authors: Stavrianakis Kostas , Ramos William 
Published: October 2021

PurposeThis study aims to examine the organizational citizenship behaviors toward the environment among US-based faculty members, in social sciences, natural sciences, the humanities and engineering. Potential barriers that may stop academia from being more sustainable are examined but also the opportunities for academics to be involved in environmental sustainability are explored.Design/methodology/approachThe authors followed a sequential explanatory mixed methods approach using online surveys (n = 633) followed by open-ended phone interviews (n = 28).FindingsResults suggest that there are certain power dynamics that force young faculty members in anti-environmental behaviors, although they are cognizant of the negative impacts on the environment. Many faculty members engage in environmental-related actions outside their service requirements, but this is mostly the case for tenured faculty members.Originality/valueThe originality of this study lies in the fact that it explores environmental behaviors from an academic ranking perspective and expands on pertinent barriers to promote sustainable behaviors in academia.
Analyzing TripAdvisor reviews of wine tours: an approach based on text mining and sentiment analysis
Authors: Barbierato Elena , Bernetti Iacopo , Capecchi Irene 
Published: October 2021

Purpose
Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.

Design/methodology/approach
The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.

Findings
The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.

Research limitations/implications
The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.

Practical implications
The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.

Social implications
The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.

Originality/value
The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.