bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomic profiling of intracranial atherosclerotic plaque in the human brain
Authors: Hao Qing , Wang Erming , Wang Ju , Wu Zhiping , Crary John F. , Sharma Shivangi , Thorn Emma L. , Elahi Fanny , Zhang Bin , Peng Junmin 
Published: February 2024

AbstractBackgroundIntracranial atherosclerotic disease (ICAD) is one of the major causes of ischemic stroke and associated with high risk of stroke recurrence. There are no reliable and specific fluid biomarkers for ICAD, and little is known about the proteomic profiling of ICAD. In this study we aimed to explore the feasibility of applying proteomics technology to profile intracranial atherosclerotic plaques extracted from postmortem human brain arteries.MethodsEighteen segments (5-10mm in length) of major arteries from 10 postmortem brains were collected from the Mount Sinai Neuropathology Brain Bank. Among these segments, 5 had no evidence of atherosclerotic disease, and 13 had wall thickening or visible plaques with various degree of stenosis. Proteins were extracted from the vessel segments, quantified, and digested into peptides. Subsequently, the peptides underwent tandem mass tag (TMT) labeling, pooling, and analysis using two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS). Protein identification and quantification were performed using the JUMP software. Differentially expressed proteins (DEPs) were defined as proteins with p.adj < 0.05 and absolute log2 (fold change) > log2 (1.2).ResultsA total of 7,492 unique proteins were detected, and 6,726 quantifiable proteins were retained for further analysis. Among these, 265 DEPs, spanning on 252 unique gene, were found to be associated with ICAD by comparing the arterial segments with vs those without atherosclerotic disease. The top 4 most significant DEPs include LONP1, RPS19, MRPL12 and SNU13. Among the top 50 DEPs, FADD, AIFM1 and PGK1 were associated with atherosclerotic disease or cardiovascular events in previous studies. Moreover, the previously reported proteins associated with atherosclerosis such as APCS, MMP12, CTSD were elevated in arterial segments with atherosclerotic changes. Furthermore, the up-regulation of APOE and LPL, the ICAD GWAS risk genes, was shown to be associated with the plaque severity. Finally, gene set enrichment analysis revealed the DEP signature is enriched for biological pathways such as chromatin structure, plasma lipoprotein, nucleosome, and protein-DNA complex, peroxide catabolic and metabolic processes, critical in ICAD pathology.ConclusionsDirect proteomic profiling of fresh-frozen intracranial artery samples by MS-based proteomic technology is a feasible approach to identify ICAD-associated proteins, which can be potential biomarker candidates for ICAD. Further plaque proteomic study in a larger sample size is warranted to uncover mechanistic insights into ICAD and discover novel biomarkers that may help to improve diagnosis and risk stratification in ICAD.
TTF1 control of LncRNA synthesis and cell growth delineates a tumour suppressor pathway acting directly on the ribosomal RNA Genes
Authors: Sibai Dany S. , Tremblay Michel G. , Lessard Frédéric , Tav Christophe , Sabourin-Félix Marianne , Robinson Mark D. , Moss Tom 
Published: February 2024

ABSTRACTThe tumour suppressor p14/19ARF regulates ribosomal RNA (rRNA) synthesis by controlling the nucleolar localization of Transcription Termination Factor 1 (TTF1). However, the role played by TTF1 in regulating the rRNA genes and in potentially controlling growth has remained unclear. We now show that TTF1 expression regulates cell growth by determining the cellular complement of ribosomes. Unexpectedly, it achieves this by acting as a “roadblock” to synthesis of the non-coding LncRNA and pRNA that we show are generated from the “Spacer Promoter” duplications present upstream of the 47S pre-rRNA promoter on the mouse and human ribosomal RNA genes. Unexpectedly, the endogenous generation of these non-coding RNAs does not induce CpG methylation or gene silencing. Rather, it actsin cisto suppress 47S preinitiation complex formation and hencede novopre-rRNA synthesis by a mechanism reminiscent of promoter interference or occlusion. Taken together, our data delineate a pathway from p19ARF to cell growth suppression via the regulation of ribosome biogenesis by non-coding RNAs and validate a key cellular growth law in mammalian cells.
Predicting gene sequences with AI to study codon usage patterns
Authors: Sidi Tomer , Bahiri-Elitzur Shir , Tuller Tamir , Kolodny Rachel 
Published: February 2024

AbstractSelective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained artificial intelligence (AI) models to predict the codons given their amino acid sequence in the eukaryotesSaccharomyces cerevisiaeandSchizosaccharomyces pombeand the bacteriaEscherichia coliandBacillus subtilis, to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins, and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels. Our models significantly outperformed naïve frequency-based approaches, demonstrating that there are dependencies between codons that can be learned to better predict evolutionary-selected codon usage. The prediction accuracy advantage of our models is greater for highly expressed genes and it is greater in bacteria than eukaryotes, supporting the hypothesis that there is a monotonic relationship between selective pressure for complex codon patterns and effective population size. Also, inS.cerevisiaeand bacteria, our models were more accurate for longer proteins, suggesting that the AI system may have learned patterns related to co-translational folding. Gene functionality and conservation were also important determinants that affect the performance of our models. Finally, we showed that using information encoded in homologous proteins has only a minor effect on prediction accuracy, perhaps due to complex codon-usage codes in genes undergoing rapid evolution. In summary, our study employing contemporary AI methods offers a new perspective on codon usage patterns and a novel tool to optimize codon usage in endogenous and heterologous proteins.Significance statementCan one predict codon sequences used by an organism to encode a given amino acid sequence? This is difficult, because there are exponentially many codon sequences that can encode the same amino acid sequence and evolution is stochastic. Indeed, codons frequencies vary, a phenomenon known as codon-bias, yet we improve upon frequency-based predictions using contemporary AI tools that learn complex patterns and capture interactions between codons. Because our predictions are tested fairly, on cases not seen during the training process, accurate predictions suggest that these learned patterns are not random, and may be related to the evolutionary process. Thus, studying where our predictions are more accurate, is expected to reveal novel insights related to the way evolution shapes coding regions.
Breakthrough in Dicot Prime Editing: Enabling Heritable Desired Edits in Tomato andArabidopsis
Authors: Vu Tien Van , Nguyen Ngan Thi , Kim Jihae , Song Young Jong , Nguyen Thu Hoai , Kim Jae-Yean 
Published: February 2024

AbstractPrime editing (PE) enables almost all types of precise genome editing in animals and plants. It has been successfully adapted to edit several plants at variable efficiency and versatility. However, this technique is inefficient for dicots for unknown reasons. Here, by employing novel combinations of PE components, including an RNA chaperone and modified epegRNAs driven by a PolII-PolIII composite promoter and a viral replicon system, we obtained up to 9.7% of the desired PE efficiency at the callus stage assessed by targeted deep sequencing. Subsequently, we identified that up to 38.2% of transformants contained desired PE alleles in tomatoes andArabidopsis, marking the first successful heritable PE transmission in dicots. Our PE tools also showed high accuracy, specificity, and multiplexing capability, which unlocked the potential for practical PE applications in dicots, paving the way for transformative advancements in plant sciences.
Bats of a feather: Range characteristics and wing morphology predict phylogeographic breaks in volant vertebrates
Authors: Decker Sydney K. , Provost Kaiya L. , Carstens Bryan C. 
Published: February 2024

AbstractIntraspecific genetic variation and phylogeographic structure can be influenced by factors such as landscape features, environmental gradients, historical biogeography, and organismal traits such as dispersal ability. Since deep genetic structure is often considered a precursor to speciation, identifying the factors that are associated with genetic structure can contribute to a greater understanding about diversification. Here, we use repurposed data to perform a global analysis of volant vertebrates (i.e., bats and birds) to estimate where intraspecific phylogeographic breaks occur and identify the factors that are important predictors of these breaks. We estimate phylogeographic breaks using Monmonier’s maximum difference barrier algorithm and conduct a Random Forests analysis using the presence of a phylogeographic break as a response variable. In bats, phylogeographic breaks are concentrated in biodiversity hotspots while breaks estimated in bird species are more widespread across temperate and tropical zones. However, for both clades geographical features such as maximum latitude, measures of wing morphology, and organismal traits associated with feeding ecology were found to be important predictors of phylogeographic breaks. Our analysis identifies geographical areas as wells as suites of organismal traits that could serve as a starting point for more detailed studies of biodiversity processes.
Mind the blank: behavioral, experiential, and physiological signatures of absent-mindedness
Authors: Musat Esteban Munoz , Corcoran Andrew W. , Belloli Laouen , Naccache Lionel , Andrillon Thomas 
Published: February 2024

ABSTRACTDoes being awake mean being conscious? This study investigates Mind Blanking (MB), characterized by an "emptiness of mind", comparing it with Mind Wandering (MW) and On-task (ON) states. Using a sustained attention task and electroencephalogram monitoring on 26 participants, behavioral and neurophysiological signatures of MB were examined. MB exhibited a specific pattern of behavioral lapses, as well as decreased fast oscillatory activity and complexity over posterior electrodes compared to MW. Functional connectivity analyses also revealed decreased frontal-posterior connectivity during MB and event-related potentials indicated a disruption in late-stage visual processing, suggesting a lack of conscious access to sensory information during MB. EEG-based neural features enabled trial-level prediction of mental states, furnishing estimates of the fine-grained dynamics of consciousness beyond subjective reports. Overall, these findings challenge the notion of continuous wake consciousness, suggesting that MB represents genuine gaps in our stream of thoughts.SIGNIFICANCE STATEMENTEmploying cutting-edge neurophysiological techniques on high-density EEG recordings, our study unveils unique neurophysiological markers of mind blanking—a phenomenon characterized by lapses in conscious content amidst the flow of consciousness. Distinguished from task-oriented states and mind wandering, this signature sheds light on the elusive nature of mind blanking. Furthermore, we demonstrate the feasibility of decoding consciousness dynamics solely from EEG features, transcending the limitations of intermittent subjective reports. Our findings not only provide a novel framework for investigating the stream of consciousness but also challenge the conventional notion that wakefulness invariably signifies consciousness.
traits.build: a data model, workflow and R package for building harmonised ecological trait databases
Authors: Wenk Elizabeth , Bal Payal , Coleman David , Gallagher Rachael , Yang Sophie , Falster Daniel 
Published: February 2024

AbstractTrait databases have proliferated over the past decades, facilitating research on the ecology, evolution, and conservation of taxa across the Tree of Life. Typically, teams of independent researchers build these databases, and each must develop their own workflow and output structure. This divests research hours from downstream tasks such as trait-based analysis and interpretation and the resultant datasets are often difficult to integrate due to disparate database structures. Here we introduce the {traits.build} package, which offers a generalised workflow for building trait databases. {traits.build} contains bespoke functions for propagating metadata files, extensive tutorials, and sample configuration files, allowing researchers to efficiently build a new trait database using open source tools. In addition, the {traits.build} output structure is fully documented by a data model, ensuring the meaning of each variable and sematic relationship between variables is transparent and consistent. The data standard links to terms in previously published data standards, drawing strongly on DarwinCore and the Ecological Trait-data Standard, but also includes the ability to fully map location and context properties absent from these vocabularies., It is the first published database-building workflow that adheres to the Extensible Observation Ontology. Simultaneously developing a generalised workflow and publishing a data standard for the workflow provides {traits.build} users a straightforward pathway to build a new trait database that achieves the FAIR principles. The meaning of all variables in a {traits.build} database are already documented, allowing further integration with either other {traits.build} databases or indeed any other database with a documented data model. This follows the vision of the Open Traits Network to build trait databases whose data can be easily integrated for further analysis.
Two distinct mechanisms for Nav1.7 null analgesia
Authors: Kanellopoulos Alexandros H. , Tian Naxi , Cox James J. , Zhao Jing , Woods Christopher G. , Wood John N 
Published: February 2024

AbstractGenetic deletion and pharmacological inhibition are distinct approaches to unravelling pain mechanisms, identifying targets and developing new analgesics. Both approaches have been applied to the voltage-gated sodium channels Nav1.7 and Nav1.8. Genetic deletion of Nav1.8 in mice leads to a loss of pain, and antagonists are effective analgesics. Complete embryonic loss of Nav1.7 in humans or in mouse sensory neurons leads to profound analgesia substantially mediated by endogenous opioid signaling, and anosmia that is opioid independent. Autonomic function appears to be normal. Adult deletion of Nav1.7 in sensory neurons also leads to analgesia with diminished sensory neuron excitability but there is no opioid component of analgesia. Pharmacological inhibition of Nav1.7 leads to dramatic side-effects on the autonomic nervous system. Here we compare and contrast the distinct embryonic and adult null mechanisms of Nav1.7 loss-of-function analgesia. We describe an endogenous opioid mechanism of analgesia that provides new opportunities for therapeutic intervention and pain relief.SummaryIn contrast to Nav1.8, Nav1.7, a genetically validated human pain target is unsuitable for small molecule drug development because of its wide spread expression both centrally and peripherally.
Leveraging information communication technology (ICT) and artificial intelligence (AI) to enhance auditing practices
Authors: Thottoli Mohammed Muneerali 
Published: February 2024

Purpose
In the fourth industrial revolution, where business accounting integrates with automation through artificial intelligence (AI) and information communication technology (ICT), auditors must be able to access and analyze vast data and information to identify potential risks and issues. Using data analytics and AI to study significant amounts of data linked to audits, this study aims to investigate auditing practices by leveraging ICT and AI to enhance the audit process.

Design/methodology/approach
Bibliometric and quantitative research techniques have been used in the study’s mixed-method process. The theoretical underpinnings of AI have been investigated using the bibliometric research method, and the challenge of implementing ICT-enabled auditing practices among auditing professionals has been studied using the quantitative research method. Surveys, interviews and bibliometric analysis have all been used as data-gathering techniques.

Findings
Research in AI and auditing has a broad worldwide scope, involving developed and developing nations. ICT perceived benefits have no direct effect on auditing practices. However, ICT training has a mediating effect on the relationship between ICT perceived benefits and auditing practices. ICT adoption has no moderating effect on the relationship between ICT training and auditing practices.

Research limitations/implications
Findings have significance for lead auditors, policymakers and the Institute of Chartered Accountants of India (ICAI), who are keenly interested in upgrading the auditing practice of accounting professionals in India by incorporating AI and ICT determinants.

Practical implications
This research makes a significant contribution by offering a thorough framework for improving the knowledge management of practising auditors regarding ICT adoption, training and perceived benefits, a crucial component of auditing practices in the digital age. In addition, it provides insightful information about how AI affects accounting practices, which may point the way for further study in this area.

Originality/value
This research has significant implications for auditing firms in India. It can inform ICAI, policymakers and regulators in their attempts to foster the incorporation of AI and ICTs in auditing practice.
Librarians’ views of the readiness of university libraries in Indonesia to adopt virtual and augmented reality
Authors: Mayesti Nina , Huang Chen Hao , Azmir Aviazka Firdhaussi , Adzani Diah Melati 
Published: February 2024

Purpose
This study aims to determine the extent of virtual reality (VR)/augmented reality (AR) adoption in university libraries in Indonesia and identify librarians’ views of library readiness. The assessment centers on two crucial dimensions: library readiness, gauged by commitment and efficacy, and librarian readiness, appraised through cognitive and affective aspects.

Design/methodology/approach
The research features a survey-based quantitative method. A sample of 259 librarians from university libraries, all members of the Indonesian Higher Education Library Forum, responded to the online survey.

Findings
Indonesian university libraries, especially in Central Java, express strong interest in VR/AR despite low current adoption. Librarians believe in their commitment and efficacy for adoption, with improvements needed in budget procurement and human resources. Librarians are optimistic about innovating academic activities with VR/AR, despite concerns about collaboration, data governance and human resource insecurity. The research underscores the simultaneous influence of librarians’ and libraries’ readiness on VR/AR adoption, emphasizing their interconnectedness and mutual support within library management.

Practical implications
There are practical implications for library institutions in Indonesia in terms of understanding the attendant opportunities and challenges when preparing organizational ecosystems. These findings provide a broad overview of VR/AR adoption in university libraries in Indonesia and contribute to understanding the specific needs and interests of universities in Indonesia considering adopting VR/AR. In addition to preparing adequate infrastructure, libraries should ensure the availability of adequate human resources.

Originality/value
In the Indonesian context, this study, to the best of the authors’ knowledge, makes the first attempt to examine the librarian’s view as part of library management to face the dilemmas that may arise during the adoption of VR/AR despite university libraries’ commitment and efficacy to enable this technology. This research also identifies librarians’ cognitive and affective readiness as individual characteristics and resources able to influence adequate adoption.
The impact of biomass power plants on Brazilian workers’ income: a synthetic difference-in-differences approach
Authors: Uhr Daniel de Abreu Pereira , Cordeiro Mikael Jhordan Lacerda , Uhr Júlia Gallego Ziero 
Published: February 2024

PurposeThis research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.Design/methodology/approachMunicipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.FindingsThe findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.Originality/valueThis article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.
“Weaving tales of resilience”: cyborg composing with AI
Authors: Li Ruth 
Published: February 2024

Purpose
This paper aims to offer an approach to cyborg composing with artificial intelligence (AI). The author posits that the hybridity of the cyborg, which amalgamates human and artificial elements, invites a cascade of creative and emancipatory possibilities. The author critically examines the biases embedded in AI systems while gesturing toward the generative potential of AI–human entanglements. Drawing on Bakhtinian theories of dialogism, the author contends that crafting found poetry with AI could inspire writers to problematize the ideologies embedded into the corpus while teasing apart its elisions or contradictions, sparking new forms of expression at the interface of the organic and the artificial.

Design/methodology/approach
To illustrate this approach to human–AI composing, the author shares a found poem that she wrote using ChatGPT alongside her reflection on the poem. The author reflects on her positionality as well as the positionality of her artificial interlocutor, interrogating the notion of subjectivity in relation to Bakhtinian dialogism and multivocality.

Findings
Weaving tales of resilience in harmony or tension with AI could unravel threads of possibility as human writers enrich, deepen or complicate AI-generated texts. By composing with AI, writers can resist closure, infiltrate illusions of objectivity and “speak back” to AI and the dominant voices replicated in its systems.

Originality/value
By encouraging students to critically engage with, question and complicate AI-generated texts, one can open avenues for alternative ways of thinking and writing, inspiring students to imagine and compose speculative futures. Ultimately, in animating assemblages of the organic and the artificial, one can invite transformative possibilities of being and becoming.