bluuebunny/crossref_metadata_2025_split huggingface dataset:
Post-transcriptional regulation of aromatic amino acid metabolism by GcvB small RNA in
Escherichia coli
Authors: Kanda Takeshi , Sekijima Toshiko , Miyakoshi Masatoshi 
Published: January 2025

ABSTRACT

Escherichia coli
synthesizes aromatic amino acids (AAAs) through the common pathway to produce the precursor, chorismate, and the three terminal pathways to convert chorismate into Phe, Tyr, and Trp.
E. coli
also imports exogenous AAAs through five transporters. GcvB small RNA post-transcriptionally regulates more than 50 genes involved in amino acid uptake and biosynthesis in
E. coli
, but the full extent of GcvB regulon is still underestimated. This study examined all genes involved in AAA biosynthesis and transport using translation reporter assay and qRT-PCR analysis. In addition to previously verified targets,
aroC
,
aroP
, and
trpE
, we identified new target genes that were significantly repressed by GcvB primarily via the R1 seed region. Exceptionally, GcvB strongly inhibits the expression of
aroG
, which encodes the major isozyme of the first reaction in the common pathway, through direct base pairing between the
aroG
translation initiation region and the GcvB R3 seed sequence. RNase E mediates the degradation of target mRNAs except
aroC
and
aroP
via its C-terminal domain. GcvB overexpression prolongs the lag phase and reduces the growth rate in minimal media supplemented with AAAs and confers resistance to an antibiotic compound, azaserine, by repressing AAA transporters.

IMPORTANCE

E. coli
strains have been genetically modified in relevant transcription factors and biosynthetic enzymes for industrial use in the fermentative production of aromatic amino acids (AAAs) and their derivative compounds. This study focuses on GcvB small RNA, a global regulator of amino acid metabolism in
E. coli
, and identifies new GcvB targets involved in AAA biosynthesis and uptake. GcvB represses the expression of the first and last enzymes of the common pathway and the first enzymes of Trp and Phe terminal pathways. GcvB also limits import of AAAs. This paper documents the impact of RNA-mediated regulation on AAA metabolism in
E. coli
.
Synthesis of Functionalized Spiro[1-benzofuran-2,5'-pyrimidine] Derivatives of 5-Arylidenebarbituric Acids
Authors: Andin A. N. , Engelgardt M. A. 
Published: January 2025

Abstract
Adducts of dimedone and 5-arylidenebarbituric acids react with N-bromosuccinimide in aqueous ethanol to give functionalized spiro[1-benzofuran-2,5'-pyrimidine] derivatives with moderate yields. The reaction of 5-benzylidenebarbituric acid with ethyl acetoacetate in the presence of N-bromosuccinimide provides spiro[pyrimidine-5,6'-furo[2,3-d]pyrimidine].
Vortical waves in a quantum fluid with vector, axial and helical charges. II. Dissipative effects
Authors: Morales-Tejera Sergio , Ambruş Victor E. , Chernodub Maxim N. 
Published: January 2025

Abstract
In this paper, we consider the effect of interactions on the local, average polarization of a quantum plasma of massless fermion particles characterized by vector, axial, and helical quantum numbers. Due to the helical and axial vortical effects, perturbations in the vector charge in a rotating plasma can lead to chiral and helical charge transfer along the direction of the vorticity vector. At the same time, interactions between the plasma constituents lead to the dissipation of the helical charge through helicity-violating pair annihilation (HVPA) processes and of the axial charge through the axial anomaly. We will discuss separately a QED-like plasma, in which we ignore background electromagnetic fields and thus the axial charge is approximately conserved, as well as a QCD-like plasma, where instanton effects lead to the violation of the axial charge conservation, even in the absence of background chromomagnetic fields. The non-conservation of helicity and chirality leads to a gapping of the Helical, Axial, and mixed Axial-Helical vortical waves that prevents their infrared modes from propagating. On the other hand, usual dissipative effects, such as charge diffusion, lead to significant damping of ultraviolet modes. We end this paper with a discussion of the regimes where these vortical waves may propagate.
Metric-affine cosmological models and the inverse problem of the calculus of variations. Part II: Variational bootstrapping of the $$\Lambda $$CDM model
Authors: Ducobu Ludovic , Voicu Nicoleta 
Published: January 2025

Abstract
The method of variational bootstrapping, based on canonical variational completion, allows one to construct a Lagrangian for a physical theory depending on two sets of field variables, starting from a guess of the field equations for only one such set. This setup is particularly appealing for the construction of modified theories of gravity, since one can take lessons from GR for an “educated guess” of the metric field equations; the field equations for the other fields are then fixed by the obtained Lagrangian (up to terms that are completely independent from the metric tensor). In the present paper, we apply variational bootstrapping to determine metric-affine models which are, in a variational sense, closest to the

$$\Lambda $$

Λ

CDM model of cosmology. Starting from an “educated guess” that formally resembles the Einstein field equations with a cosmological “constant” (actually, a scalar function built from the metric and the connection) and a dark matter term, the method then allows to find “corrected” metric equations and to “bootstrap” the connection field equations. Lagrangians obtained via this method, though imposing some restricting criteria, still encompass a wide variety of metric-affine models. In particular, they allow for a subclass of quadratic metric-affine theories restricted to linear terms in the curvature tensor.
QScratch: introduction to quantum mechanics concepts through block-based programming
Authors: Escanez-Exposito Daniel , Rodriguez-Vega Marcos , Rosa-Remedios Carlos , Caballero-Gil Pino 
Published: January 2025

Abstract
This article introduces QScratch, a novel educational tool designed to introduce fundamental quantum concepts and principles. It is an extension of the high-level block-based visual programming language Scratch, developed by the MIT Media Lab. The quantum concepts taught are presented in a simple and illustrative, yet rigorous way. The selection of topics and their adaptation for this project has been made taking into account the huge complexity of the subject, developing specific intuitive blocks to model the quantum behaviours of superposition, entanglement and measurement. A pilot study carried out with a group of 68 students has demonstrated the validity of the software developed as a tool for introducing complex quantum physics concepts. Thus, the proposed tool complements the original Scratch tool, advancing in the construction of Science, Technology, Engineering and Mathematics (STEM) tools that facilitate the introduction of quantum concepts to everyone.
Automated Recommendation of Extracting Local Variable Refactorings
Authors: Jiang Yanjie , Chi Xiaye , Zhang Yuxia , Ji Weixing , Li Guangjie , Wang Weixiao , Xia Yunni , Zhang Lu , Liu Hui 
Published: January 2025

Extracting local variable refactoring is frequently employed to replace one or more occurrences of a complex expression with simple accesses to a newly introduced variable. To facilitate the refactoring, most IDEs can automate the extract local variable refactorings when the to-be-extracted expressions are selected by developers. However, refactoring tools usually replace all expressions that are lexically identical to the selected one without a comprehensive analysis of the safety of the refactoring. The automatically conducted refactorings may lead to serious software defects. Besides that, existing refactoring tools rely heavily on software developers to spot to-be-extracted expressions although it is often challenging for inexperienced developers and maintainers to make the selection. To this end, in this paper, we propose an automated approach, called
ValExtractor+
, to recommending extract local variable refactoring opportunities and to automatically and safely conduct the refactorings.
ValExtractor+
is composed of two parts, i.e., solutionAdvisor and opportunityAdvisor. Given a to-be-extracted expression, solutionAdvisor leverages lightweight static source code analysis to validate potential side effects of the expression, and to identify expressions that could be extracted together with the selected expression as a single variable without changing the semantics of the program or introducing any new exceptions. The static code analysis significantly improves the safety in automated extraction of local variables. To free programmers from manually selecting to-be-extracted expressions, opportunityAdvisor leverages solutionAdvisor to automatically retrieve all expressions that could be extracted safely as well as their refactoring solutions. It then leverages a learning-based classifier to predict which of the retrieved expressions should be extracted. Evaluations on open-source applications suggest that
solutionAdvisor
successfully avoided all defects (more than two hundred) caused by extracting local variable refactorings conducted by
Eclipse
(243 defects) or
IntelliJ IDEA
(263 defects). Additionally,
opportunityAdvisor
was able to effectively recommend expressions for extraction, achieving 307 true positives (TP) and 21,121 true negatives (TN). Four pull requests from our work (PR IDs:
66
,
333
,
439
, and
360
) were successfully merged into the Eclipse community repository, showcasing the practical impact and robustness of our approach as recognized by the wider developer community.
Impact of Race/Ethnicity on Clinical and Genomic Characteristics, Trial Participation, and Genotype-Matched Therapy among Patients with Metastatic Breast Cancer
Authors: Sood Rupali , Niemierko Andrzej , Ryan Lianne , Spring Laura , Moy Beverly , Bardia Aditya , Vidula Neelima 
Published: January 2025

Abstract
Background: Race/ethnicity may affect outcomes in metastatic breast cancer (MBC) due to biological and social determinants. We evaluated the impact of race/ethnicity on clinical, socioeconomic, and genomic characteristics, clinical trial participation, and receipt of genotype-matched therapy among patients with MBC. Methods: A retrospective study of patients with MBC who underwent cell-free DNA testing (cfDNA, Guardant360â, 74 gene panel) between 11/2016 and 11/2020 was conducted. Receipt of genotype-matched therapy targeted at a cfDNA actionable mutation was determined. Pearson's chi-squared and Wilcoxon rank-sum tests were used to compare categorical and continuous variables between groups. Multivariable logistic regression was used to assess the association of race and receiving matched therapy. Results: 425 patients with MBC and cfDNA results were identified (White: 369, Black: 27, Hispanic 15, and Asian 14). White patients traveled further for cancer care than other groups (p&lt;0.001). White patients had the highest rates of commercial insurance, Black patients had the highest rates of state-supported insurance, and Asian patients had the highest uninsured rates (p&lt;0.001). Clinical trial enrollment did not differ by race/ethnicity (p=0.34). The proportion of patients with ≥1 actionable mutation in cfDNA did not vary by race/ethnicity (p=0.18). The highest rates of matched therapy were observed in White patients (p&lt;0.001). After multivariable logistic regression adjusting for subtype, commercial vs. other insurance, Charlson comorbidity index, and distance to center, White patients remained more likely to receive matched therapy (p=0.024). Conclusions: Racial/ethnic minority patients were less likely to receive matched therapy. Further research is needed to identify barriers to precision medicine.
Neural Associations between Inhibitory Control and Counterintuitive Reasoning in Science and Maths in Primary School Children
Authors: Palmer Lucy R. J. , Sumanapala Dilini K. , Mareschal Denis , Dumontheil Iroise ,   the UnLocke Team
Published: January 2025

Abstract
Emerging evidence suggests that inhibitory control (IC) plays a pivotal role in science and maths counterintuitive reasoning by suppressing incorrect intuitive concepts, allowing correct counterintuitive concepts to come to mind. Neuroimaging studies have shown greater activation in the ventrolateral and dorsolateral pFCs when adults and adolescents reason about counterintuitive concepts, which has been interpreted as reflecting IC recruitment. However, the extent to which neural systems underlying IC support science and maths reasoning remains unexplored in children. This developmental stage is of particular importance, as many crucial counterintuitive concepts are learned in formal education in middle childhood. To address this gap, fMRI data were collected while fifty-six 7- to 10-year-olds completed counterintuitive science and math problems, plus IC tasks of interference control (Animal Size Stroop) and response inhibition (go/no-go). Univariate analysis showed large regional overlap in activation between counterintuitive reasoning and interference control, with more limited activation observed in the response inhibition task. Multivariate similarity analysis, which explores fine-scale patterns of activation across voxels, revealed neural activation similarities between (i) science and maths counterintuitive reasoning and interference control tasks in frontal, parietal, and temporal regions, and (ii) maths reasoning and response inhibition tasks in the precuneus/superior parietal lobule. Extending previous research in adults and adolescents, this evidence is consistent with the proposal that IC, specifically interference control, supports children's science and maths counterintuitive reasoning, although further research will be needed to demonstrate the similarities observed do not reflect more general multidemand processes.
Bilingualism Is Associated with Significant Structural and Connectivity Alterations in the Thalamus in Adulthood
Authors: Ayyildiz Behcet , Sayman Dila , Ayyildiz Sevilay , Oktem Ece Ozdemir , Arslan Ruhat , Colak Tuncay , Bamac Belgin , Yulug Burak 
Published: January 2025

Abstract
Language is a sophisticated cognitive skill that relies on the coordinated activity of cerebral cortex. Acquiring a second language creates intricate modifications in brain connectivity. Although considerable studies have evaluated the impact of second language acquisition on brain networks in adulthood, the results regarding the ultimate form of adaptive plasticity remain inconsistent within the adult population. Furthermore, due to the assumption that subcortical regions are not significantly involved in language-related tasks, the thalamus has rarely been analyzed in relation to other language-relevant cortical regions. Given these limitations, we aimed to evaluate the functional connectivity and volume modifications of thalamic subfields using magnetic resonance imaging (MRI) modalities following the acquisition of a second language. Structural MRI and fMRI data from 51 participants were collected from the OpenNeuro database. The participants were divided into three groups: monolingual (ML), early bilingual (EB), and late bilingual (LB). The EB group consisted of individuals proficient in both English and Spanish, with exposure to these languages before the age of 10 years. The LB group consisted of individuals proficient in both English and Spanish, but with exposure to these languages after the age of 14 years. The ML group included participants proficient only in English. Our results revealed that the ML group exhibited increased functional connectivity in all thalamic subfields (anterior, intralaminar-medial, lateral, ventral, and pulvinar) compared with the EB and LB groups. In addition, a significantly decreased volume of the left suprageniculate nucleus was found in the bilingual groups compared with the ML group. This study provides valuable evidence suggesting that acquiring a second language may be protective against dementia, due to its high plasticity potential, which acts synergistically with cognitive functions to slow the degenerative process.
Formononetin ameliorates polycystic ovary syndrome through suppressing NLRP3 inflammasome
Authors: Liu Zhuo , Wang Rui-Han , Wang Ke-Hua 
Published: January 2025

Abstract

Background
Polycystic ovary syndrome (PCOS) is a common gynecological disease accompanied by multiple clinical features, including anovulation, hyperandrogenism, and polycystic ovarian morphology, leading to infertility. Formononetin (FMN), which is a major bioactive isoflavone compound in Astragalus membranaceus, exerts anti-inflammatory effects. However, whether FMN is effective in the treatment of PCOS remains unknown. This study aims to explore the effects and the possible mechanisms of FMN in PCOS.

Methods
Dehydroepiandrosterone (DHEA)-induced PCOS rats and dihydrotestosterone (DHT)-induced PCOS cell models were established. Fifty rats were randomly assigned into five groups of 10 rats each: Control, PCOS, PCOS + FMN (15 mg/kg), PCOS + FMN (30 mg/kg), and PCOS + FMN (60 mg/kg). Fasting blood glucose, insulin, luteinizing hormone, follicle-stimulating hormone, testosterone, and estradiol were detected in DHEA-induced PCOS rats. Ovarian histological changes and apoptosis were evaluated utilizing H&E and TUNEL staining. Subsequently, the effects of FMN on oxidative stress and inflammatory responses in the DHEA-induced PCOS rat model and DHT-induced PCOS cell model were explored. Besides, the function of FMN on cell viability and apoptosis in DHT-induced PCOS cell model were explored by using CCK-8 assay and flow cytometry. Protein expression was detected via western blot and immunofluorescence staining in the DHEA-induced PCOS rat model and DHT-induced PCOS cell model.

Results
FMN alleviated PCOS symptoms and reduced inflammation, cell apoptosis, and oxidative stress in DHEA-induced PCOS rats and DHT-induced KGN cells. Additionally, FMN suppressed NLRP3 inflammasome activation in both models. In the DHT-induced PCOS cell model, nigericin (a activator of NLRP3) reversed the functions of FMN on inflammation, apoptosis, and oxidative stress.

Conclusion
These findings demonstrated that FMN could alleviate PCOS by repressing inflammation, apoptosis, as well as oxidative stress in vivo and in vitro via inhibition of the NLRP3 inflammasome.

Highlights

FMN improved PCOS symptoms.

FMN alleviated cell apoptosis, inflammation and oxidative stress in PCOS.

FMN inhibited the activation of NLRP3 inflammasome in PCOS.
Hybrid generative adversarial network based on frequency and spatial domain for histopathological image synthesis
Authors: Liu Qifeng , Zhou Tao , Cheng Chi , Ma Jin , Hoque Tania Marzia 
Published: January 2025

Abstract

Background
Due to the complexity and cost of preparing histopathological slides, deep learning-based methods have been developed to generate high-quality histological images. However, existing approaches primarily focus on spatial domain information, neglecting the periodic information in the frequency domain and the complementary relationship between the two domains. In this paper, we proposed a generative adversarial network that employs a cross-attention mechanism to extract and fuse features across spatial and frequency domains. The method optimizes frequency domain features using spatial domain guidance and refines spatial features with frequency domain information, preserving key details while eliminating redundancy to generate high-quality histological images.

Results
Our model incorporates a variable-window mixed attention module to dynamically adjust attention window sizes, capturing both local details and global context. A spectral filtering module enhances the extraction of repetitive textures and periodic structures, while a cross-attention fusion module dynamically weights features from both domains, focusing on the most critical information to produce realistic and detailed images.

Conclusions
The proposed method achieves efficient spatial-frequency domain fusion, significantly improving image generation quality. Experiments on the Patch Camelyon dataset show superior performance over eight state-of-the-art models across five metrics. This approach advances automated histopathological image generation with potential for clinical applications.
Predicting microRNA target genes using pan-cancer correlation patterns
Authors: Lin Shuting , Qiu Peng 
Published: January 2025

Abstract
The interaction relationship between miRNAs and genes is important as miRNAs play a crucial role in regulating gene expression. In the literature, several databases have been constructed to curate known miRNA target genes, which are valuable resources but likely only represent a small fraction of all miRNA-gene interactions. In this study, we constructed machine learning models to predict miRNA target genes that have not been previously reported. Using the miRNA and gene expression data from TCGA, we performed a correlation analysis between all miRNAs and all genes across multiple cancer types. The correlations served as features to describe each miRNA-gene pair. Using the existing databases of curated miRNA targets, we labeled the miRNA-gene pairs, and trained machine learning models to predict novel miRNA-gene interactions. For the miRNA-gene pairs that were consistently predicted across the models, we called them significant miRNA-gene pairs. Using held-out miRNA target databases and a literature survey, we validated 5.5% of the predicted significant miRNA-gene pairs. The remaining predicted miRNA-gene pairs could serve as hypotheses for experimental validation. Additionally, we explored several additional datasets that provided gene expression data before and after a specific miRNA perturbation and observed consistency between the correlation direction of predicted miRNA-gene pairs and their regulatory patterns. Together, this analysis revealed a novel framework for uncovering previously unidentified miRNA-gene relationships, enhancing the collective comprehension of miRNA-mediated gene regulation.