bluuebunny/crossref_metadata_2025_split huggingface dataset:
ERNIE-RNA: An RNA Language Model with Structure-enhanced Representations
Authors: Yin Weijie , Zhang Zhaoyu , He Liang , Jiang Rui , Zhang Shuo , Liu Gan , Zhang Xuegong , Qin Tao , Xie Zhen 
Published: March 2024

AbstractWith large amounts of unlabeled RNA sequences data produced by high-throughput sequencing technologies, pre-trained RNA language models have been developed to estimate semantic space of RNA molecules, which facilities the understanding of grammar of RNA language. However, existing RNA language models overlook the impact of structure when modeling the RNA semantic space, resulting in incomplete feature extraction and suboptimal performance across various downstream tasks. In this study, we developed a RNA pre-trained language model named ERNIE-RNA (EnhancedRepresentations with base-pairing restriction forRNAmodeling) based on a modified BERT (Bidirectional Encoder Representations from Transformers) by incorporating base-pairing restriction with no MSA (Multiple Sequence Alignment) information. We found that the attention maps from ERNIE-RNA with no fine-tuning are able to capture RNA structure in the zero-shot experiment more precisely than conventional methods such as fine-tuned RNAfold and RNAstructure, suggesting that the ERNIE-RNA can provide comprehensive RNA structural representations. Furthermore, ERNIE-RNA achieved SOTA (state-of-the-art) performance after fine-tuning for various downstream tasks, including RNA structural and functional predictions. In summary, our ERNIE-RNA model provides general features which can be widely and effectively applied in various subsequent research tasks. Our results indicate that introducing key knowledge-based prior information in the BERT framework may be a useful strategy to enhance the performance of other language models.
Curcumin-mediated NRF2 induction limits inflammatory damage in preclinical models of cystic fibrosis
Authors: Leon-Icaza Stephen A , Fretaud Maxence , Cornélie Sarahdja , Bureau Charlotte , Yatime Laure , Floto R Andres , Renshaw Stephen A , Herrmann Jean-Louis , Langevin Christelle , Cougoule Céline , Bernut Audrey 
Published: March 2024

AbstractOveractive inflammation is directly correlated with airway damage and early death in individuals with cystic fibrosis (CF), a genetic disorder caused by mutation in theCFTRgene. Reducing the impact of inflammatory damage is therefore a major concern in CF. Several studies indicate that a decrease in the nuclear factor erythroid 2-related factor-2 (NRF2) signaling in people with CF may hamper their ability to alleviate oxidative stress and inflammation, although the role of NRF2 in CF inflammatory damage has not been determined. Therefore, we examined whether the phytochemical curcumin, an activator of NRF2, might provide a beneficial effect in the context of CF.Herein, combiningCftr-depleted zebrafish larvae as innovative biomedical model with CF patient-derived airway organoids (AOs), we sought to understand how NRF2 dysfunction leads to abnormal inflammatory status and impaired tissue remodeling, and determine the effects of curcumin in reducing inflammation and tissue damage in CF.We demonstrate that NFR2 is instrumental in efficiently regulating inflammatory and repair processesin vivo, thereby preventing acute neutrophilic inflammation and tissue damage. Importantly, curcumin treatment restores NRF2 activity in both CF zebrafish and AOs. Curcumin reduces neutrophilic inflammation in CF context, by rebalancing the production of epithelial ROS and pro-inflammatory cytokines. Furthermore, curcumin alleviates CF-associated tissue remodeling and allows tissue repair to occur. Our findings demonstrate that curcumin reduces inflammatory damage by restoring normal NRF2 activity, since disruption of Nrf2 pathway abrogated the effect of treatment in CF zebrafish.This work highlights the protective role of NRF2 in limiting inflammation and injury, and show that therapeutic strategies to normalize NRF2 activity using curcumin might simultaneously reduce inflammation and enhance tissue repair, and thus prevent infectious and inflammatory lung damage in CF.
Stalling of Transcription by Putative G-quadruplex Sequences and CRISPR-dCas9
Authors: Hoque Mohammed Enamul , Kabir Mohammad Lutful , Shiekh Sajad , Balci Hamza , Basu Soumitra 
Published: March 2024

ABSTRACTPutative G-quadruplex forming sequences (PQS) have been identified in promoter sequences of prominent genes that are implicated among others in cancer and neurological disorders. We explored mechanistic aspects of CRISPR-dCas9-mediated gene expression regulation, which is transient and sequence specific unlike alternative approaches that lack such specificity or create permanent mutations, using the PQS in tyrosine hydroxylase (TH) andc-Mycpromoters as model systems. We performedin vitroensemble and single molecule investigations to study whether G-quadruplex (GQ) structures or dCas9 impede T7 RNA polymerase (RNAP) elongation process and whether orientation of these factors is significant. Our results demonstrate that dCas9 is more likely to block RNAP progression when the non-template strand is targeted. While the GQ inTHpromoter was effectively destabilized when the dCas9 target site partially overlapped with the PQS, thec-MycGQ remained folded and stalled RNAP elongation. We also determined that a minimum separation between the transcription start site and the dCas9 target site is required for effective stalling of RNAP by dCas9. Our study provides significant insights about the factors that impact dCas9-mediated transcription regulation when dCas9 targets the vicinity of sequences that form secondary structures and provides practical guidelines for designing guide RNA sequences.
Retinoic acid, an essential component of the RP organizer, promotes the spatio-temporal segregation of dorsal neural fates
Authors: Rekler Dina , Ofek Shai , Kagan Sarah , Friedlander Gilgi , Kalcheim Chaya 
Published: March 2024

SummaryDorsal neural tube-derived retinoic acid promotes the end of neural crest production and transition into a definitive roof plate. Here we analyze how this impacts the segregation of central and peripheral lineages, a process essential for tissue patterning and function. Localized in-ovo inhibition of retinoic acid activity followed by single cell transcriptomics unraveled a comprehensive list of differentially expressed genes relevant to these processes. Importantly, progenitors co-expressed neural crest, roof plate and dI1 interneuron markers indicating a failure in proper lineage segregation. Furthermore, we found that separation between roof plate and dI1 interneurons is mediated by Notch activity downstream of retinoic acid, highlighting their critical role in establishing the roof plate-dI1 boundary.Within the peripheral branch, where absence of retinoic acid resulted in neural crest production and emigration extending into the roof plate stage, sensory progenitors failed to separate from melanocytes leading to formation of a common glia-melanocyte cell with aberrant migratory patterns. Together, we uncover and characterize a molecular mechanism responsible for segregation of dorsal neural fates during development.
Identification of novel prognostic targets in acute kidney injury using bioinformatics and next generation sequencing data analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: March 2024

AbstractAcute kidney injury (AKI) is a type of renal disease occurs frequently in hospitalized patients, which may cause abnormal renal function and structure with increase in serum creatinine level with or without reduced urine output. With the incidence of AKI is increasing. However, the molecular mechanisms of AKI have not been elucidated. It is significant to further explore the molecular mechanisms of AKI. We downloaded the GSE139061 next generation sequancing (NGS) dataset from the Gene Expression Omnibus (GEO) database. Limma R bioconductor package was used to screen the differentially expressed genes (DEGs). Then, the enrichment analysis of DEGs in Gene Ontology (GO) function and REACTOME pathways was analyzed by g:Profiler. Next, the protein-protein interaction (PPI) network and modules was constructed and analysed, and the hub genes were identified. Next, the miRNA-hub gene regulatory network and TF-hub gene regulatory network were built. We also validated the identified hub genes via receiver operating characteristic (ROC) curve analysis. Overall, 956 DEGs were identified, including 478 up regulated and 478 down regulated genes. The enrichment functions and pathways of DEGs involve primary metabolic process, small molecule metabolic process, striated muscle contraction and metabolism. Topological analysis of the PPI network and module revealed that hub genes, including PPP1CC, RPS2, MDFI, BMI1, RPL23A, VCAM1, ALB, SNCA, DPP4 and RPL26L1, might be involved in the development of AKI. miRNA-hub gene and TF-hub gene regulatory networks revealed that miRNAs and TFs including hsa-mir-510-3p, hsa-mir-6086 and mir-146a-5p, MAX and PAX2, might be involved in the development of AKI. Various known and newtherapeutic targets were obtained via network analysis. The results of the current investigation might be beneficial for the diagnosis and treatment of AKI.
Functional associations of evolutionarily recent human genes exhibit sensitivity to the 3D genome landscape and disease
Authors: Fleck Katherine , Luria Victor , Garag Nitanta , Karger Amir , Hunter Trevor , Marten Daniel , Phu William , Nam Kee-Myoung , Sestan Nenad , O’Donnell-Luria Anne H. , Erceg Jelena 
Published: March 2024

SummaryGenome organization is intricately tied to regulating genes and associated cell fate decisions. Here, we examine the positioning and functional significance of human genes, grouped by their lineage restriction level, within the 3D organization of the genome. We reveal that genes of different lineage restriction levels have distinct positioning relationships with both domains and loop anchors, and remarkably consistent relationships with boundaries across cell types. While the functional associations of each group of genes are primarily cell type-specific, associations of conserved genes maintain greater stability across 3D genomic features and disease than recently evolved genes. Furthermore, the expression of these genes across various tissues follows an evolutionary progression, such that RNA levels increase from young lineage restricted genes to ancient genes present in most species. Thus, the distinct relationships of gene evolutionary age, function, and positioning within 3D genomic features contribute to tissue-specific gene regulation in development and disease.
Do goldfish like to be informed?
Authors: Ajuwon Victor , Monteiro Tiago , Walton Mark , Kacelnik Alex 
Published: March 2024

AbstractMost mammalian and avian species tested so far, including humans, prefer foretold over unsignalled future events, even if the information is costly and confers no direct benefit, a phenomenon that has been called paradoxical, or suboptimal choice. It is unclear whether this is an epiphenomenon of taxonomically widespread mechanisms of reinforcement learning, or if information-seeking is a dedicated cognitive trait, perhaps a precursor of human curiosity. We investigate whether a teleost fish that shares basic reinforcement learning mechanisms with birds and mammals also presents such preference, with the aim of dissociating food-reinforced learning from information-seeking. Goldfish chose between two alternatives, both yielding a 50% chance of reward 5s after being chosen. The ‘informative’ alternative caused immediate onset of either of two stimuli (S+ or S-) correlated with the trial’s forthcoming outcome (reward/no reward). Choosing the ‘non-informative’ option, instead triggered either of two uncorrelated stimuli (N1 or N2). Goldfish learned to discriminate between the different contingencies, but did not develop preference for the informative option. This shows that conditioning learning is not always sufficient, and the difference with birds and mammals supports the hypothesis that information-seeking, rather than simple conditioning, causes the paradoxical preference for unusable information shown by the latter.
Spec2Class: Accurate Prediction of Plant Secondary Metabolite Class using Deep Learning
Authors: Poltorak Victoria , Shachaf Nir , Aharoni Asaph , Zeevi David 
Published: March 2024

AbstractMass spectrometry (MS)-based data is commonly used in studying metabolism and natural products, but typically requires domain-specific skill and experience to analyze. Existing computational tools for non-targeted metabolite analysis (i.e., metabolomics) mostly rely on comparison to reference MS spectral libraries for metabolite identification, limiting the annotation of metabolites for which reference spectra do not exist. This is the case in plant secondary metabolites, where most spectral features remain unidentified. Here, we developedSpec2Class, a deep-learning algorithm for the identification and classification of plant secondary metabolites from liquid chromatography (LC)-MS/MS spectra. We used the in-house spectral library of 7973 plant metabolite chemical standards, alongside publicly available data, to trainSpec2Classto classify LC-MS/MS spectra to 43 common plant secondary metabolite classes. Tested on held out sets, our algorithm achieved an overall accuracy of 73%, outperforming state-of-the-art classification. We further established a prediction certainty parameter to set a threshold for low-confidence results. Applying this threshold, we reached an accuracy of 93% on an unseen dataset. We show a high robustness of our prediction to noise and to the data acquisition method.Spec2Classis publicly available and is anticipated to facilitate metabolite identification and accelerate natural product discovery.Significance StatementUntargeted mass spectrometry (MS) is essential for natural product discovery but is limited by product identification, which is often manual and requires domain-specific skills.Spec2Classaddresses this limitation by accurately classifying plant secondary metabolites from LC-MS/MS spectra without reliance on reference spectral libraries. Trained on a substantial dataset and using a prediction certainty threshold, it outperforms state-of-the-art algorithms with 93% accuracy. This tool demonstrates high robustness against noise and different data acquisition methods, promising to streamline metabolite identification and expedite natural product research.Spec2Classis open-source, publicly available, and easy to integrate into natural product discovery pipelines.
Dynamic role of GlyT1 as glycine sink or source: pharmacological implications for the gain control of NMDA receptors
Authors: Supplisson Stéphane 
Published: March 2024

AbstractGlycine transporter 1 (GlyT1) mediates termination of inhibitory glycinergic receptors signaling in the spinal cord and brainstem, and is also diffusely present in the forebrain. Here, it regulates the ambient glycine concentration influencing the ‘glycine’-site occupancy ofN-methyl-d-aspartate (NMDARs). GlyT1 is a reversible transporter with a substantial, but not excessive, sodium-motive force for uphill transport. This study examines its potential role as a glycine source, either by reversed-uptake or by heteroexchange. I explored how glycine accumulation triggers its release, facilitating the activation of NMDARs by glutamate applied alone. Indeed, glutamate evokes no current in “naive” oocytes coexpressing GluN1/GluN2A and GlyT1, a previously characterized cellular model, but now using GlyT1 as the only potential source of coagonist for NMDAR activation. After glycine uptake, however, glutamate evokes large currents, blocked by ALX-5407 and potentiated by sarcosine, a specific inhibitor and substrate of GlyT1, respectively. These results suggest higher occupancy of the co-agonist site when GlyT1 functions as a glycine source either by reversed-uptake or by heteroexchange. A difference between these two glycine-release mechanisms occurs at hyperpolarized potentials, which induce an apparent voltage-dependent block of NMDAR currents, whereas heteroexchange preserves NMDAR activation at these potentials. Together, these results confirm GlyT1-mediated efflux as a positive regulator of NMDAR co-agonist site occupancy, and demonstrate sarcosine heteroexchange effectiveness in enhancing coagonist site occupancy. Depending on its actual mode of transport, GlyT1-inhibitors and sarcosine may have distinct effects on ambient glycine and NMDAR facilitation, and be a source of variation in reversing NMDAR hypofunction in schizophrenia.Graphical Abstract
Large-scale composite hypothesis testing for omics analyses
Authors: De Walsche Annaïg , Gauthier Franck , Boissot Nathalie , Charcosset Alain , Mary-Huard Tristan 
Published: March 2024

AbstractComposite hypothesis testing using summary statistics is a well-established approach for assessing the effect of a single marker or gene across multiple traits or omics levels. Numerous procedures have been developed for this task and have been successfully applied to identify complex patterns of association between traits, conditions, or phenotypes. However, existing methods often struggle with scalability in large datasets or fail to account for dependencies between traits or omics levels, limiting their ability to control false positives effectively. To overcome these challenges, we present the qch_copula approach, which integrates mixture models with a copula function to capture dependencies between traits or omics, and provides rigorously definedp-values for any composite hypothesis. Through a comprehensive benchmark against eight state-of-the-art methods, we demonstrate that qch_copula controls Type I error rates effectively while enhancing the detection of joint association patterns. Compared to other mixture model-based approaches, our method notably reduces memory usage during the EM algorithm, allowing the analysis of up to 20 traits and 105− 106markers. The effectiveness of qch_copula is further validated through two application cases in human and plant genetics. The method is available in the R package qch, accessible on CRAN.
Research on the matching effect between advertising appeal and product type on the purchase intention of organic food
Authors: Zhao Jiayuan , Huo Hong , Wei Sheng , Han Chunjia , Yang Mu , Gupta Brij B. , Arya Varsha 
Published: March 2024

PurposeThe study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.Design/methodology/approachThis paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.FindingsThe analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.Originality/valueThis research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.
Charting the progress of technology adoption in tourism and hospitality in the era of industry 4.0
Authors: Buhalis Dimitrios , Efthymiou Leonidas , Uzunboylu Naziyet , Thrassou Alkis 
Published: March 2024

PurposeAmidst ongoing digital transformation, the current paper provides a 360-degree overview of technology-adoption in Tourism and Hospitality. By combining and consolidating a wide range of sources, mainly in the tourism literature, the analysis depicts how the complex technological ecosystem often enhances or hinders the successful adoption, integration and interoperability of different technologies.Design/methodology/approachThe critical review method was used to assess, analyse and synthesise existing literature in the area of digitisation in tourism and hospitality. The critical review process included a thematic analysis of the literature, where recurring themes, patterns and trends were identified towards addressing the study’s research questions.FindingsThe analysis identifies current trends, opportunities, challenges and strategies for technology adoption in tourism and hospitality, the implications for theory, practicable executive directions and avenues for further research.Originality/valueThe paper’s main contribution lies in its comprehensive identification, consideration and incorporation of all primary contemporary technological elements, and the ensuing development of a corresponding conceptual charting framework, which illustrates a multifaceted process with practical implications for various stakeholders, including businesses, authorities, consumers and employees.
Career adaptability in the new normal world of work: exploring the post-pandemic research trends using bibliometric analysis
Authors: Parrey Aubid Hussain , Kour Gurleen 
Published: March 2024

PurposeCareer adaptability is emerging as an important research area in today's uncertain, volatile world of work created by the COVID-19 pandemic. The present study focuses on career adaptability research post-COVID-19 by scientifically capturing the literature evolution, hotspots and future trends using bibliometric analysis.Design/methodology/approachThe Scopus database, due to its vast and quality literature, was used to search the papers from the period 2020 to 2023. Bibliometric data were extracted and analyzed from the relevant literature. For further scientific mapping, VOSviewer and Biblioshiny software tools were used.FindingsFindings of the analysis suggest a positive research trend related to career adaptability research post-Covid. Keyword analysis revealed noteworthy clusters and important themes. Bibliometric visual networks regarding authors, sources, citations, future themes, etc. are also presented from the 441 analyzed publications with comprehensive interpretation.Research limitations/implicationsThe literature for carrying out the bibliometric analysis was confined to the Scopus database. Other databases in combination with different software can be used for future niche research. From the analysis, future research avenues and practical interventions are presented which have significant implications for future researchers, career counselors and managers.Originality/valueThe study summarizes the recent literature on career adaptability in the aftermath of the pandemic and makes a novel contribution to the existing literature. A reliable study has been provided by the authors using the scientific bibliometric technique. The study highlights emerging research trends post the pandemic. The results are concluded with further suggestions which can guide future research related to the topic.