bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combined deletion of MEN1, ATRX and PTEN triggers development of high-grade pancreatic neuroendocrine tumors in mice
Authors: Fuentes Mary Esmeralda , Lu Xiaoyin , Flores Natasha M. , Hausmann Simone , Mazur Pawel K. 
Published: April 2024

AbstractPancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of tumors that exhibit an unpredictable and broad spectrum of clinical presentations and biological aggressiveness. Surgical resection is still the only curative therapeutic option for localized PanNET, but the majority of patients are diagnosed at an advanced and metastatic stage with limited therapeutic options. Key factors limiting the development of new therapeutics are the extensive heterogeneity of PanNETs and the lack of appropriate clinically relevant models. In that context, genomic sequencing of human PanNETs revealed recurrent mutations and structural alterations in several tumor suppressors. Here, we demonstrated that combined loss of MEN1, ATRX, and PTEN, tumor suppressors commonly mutated in human PanNETs, triggers the development of high-grade pancreatic neuroendocrine tumors in mice. Histopathological evaluation and gene expression analyses of the developed tumors confirm the presence of PanNET hallmarks and significant overlap in gene expression patterns found in human disease. Thus, we postulate that the presented novel genetically defined mouse model is the first clinically relevant immunocompetent high-grade PanNET mouse model.
Evaluating the agronomic efficiency of alternative phosphorus sources applied in Brazilian tropical soils
Authors: da Silva Lucas Jónatan Rodrigues , da Silva Sandim Aline , da Silva Ana Paula Rodrigues , Deus Angélica Cristina Fernandes , Antonangelo João Arthur , Büll Leonardo Theodoro 
Published: April 2024

AbstractUnderstanding the efficacy of alternative phosphorus (P) sources in tropical soils is crucial for sustainable farming, addressing resource constraints, mitigating environmental impact, improving crop productivity, and optimizing soil-specific solutions. While the topic holds great importance, current literature falls short in providing thorough, region-specific studies on the effectiveness of alternative P sources in Brazilian tropical soils for maize cultivation. Our aim was to assess the agronomic efficiency of alternative P sources concerning maize crop (Zea mays L.) attributes, including height, shoot dry weight, stem diameter, and nutrient accumulation, across five Brazilian tropical soils. In greenhouse conditions, we carried out a randomized complete block design, investigating two factors (soil type and P sources), evaluating five tropical soils with varying clay contents and three alternative sources of P, as well as a commercial source and a control group. We evaluated maize crop attributes such as height, dry weight biomass, and nutrient accumulation, P availability and agronomic efficiency. Our results showed that, although triple superphosphate (TSP) exhibited greater values than alternative P sources (precipitated phosphorus 1, precipitated phosphorus 2 and reactive phosphate) for maize crop attributes (e.g., height, stem diameter, shoot dry weight and phosphorus, nitrogen, sulfur, calcium and magnesium accumulation). For instance, PP1 source increased nutrient accumulation for phosphorus (P), nitrogen (N), and sulfur (S) by 37.05% and 75.98% (P), 34.39% and 72.07% (N), and 41.94% and 72.69% (S) in comparison to PP2 and RP, respectively. Additionally, PP1 substantially increased P availability in soils with high clay contents 15 days after planting (DAP), showing increases of 61.90%, 99.04%, and 38.09% greater than PP2, RP, and TSP. For Ca and Mg accumulation, the highest values were found in the COxisol2 soil when PP2 was applied, Ca = 44.31% and 69.48%; and Mg = 46.23 and 75.79%, greater than PP1 and RP, respectively. Finally, the highest values for relative agronomic efficiency were observed in COxisol2 when PP1 was applied. The precipitated phosphate sources (PP1 and PP2) exhibited a similar behavior to that of the commercial source (TSP), suggesting their potential use to reduce reliance on TSP fertilization, especially in soils with low clay contents. This study emphasized strategies for soil P management, aimed at assisting farmers in enhancing maize crop productivity while simultaneously addressing the effectiveness of alternative P sources of reduced costs.
LVING reveals the intracellular structure of cell growth
Authors: Pradeep Soorya , Zangle Thomas A. 
Published: April 2024

AbstractThe continuous balance of growth and degradation inside cells maintains homeostasis. Disturbance of this balance by internal or external factors cause state of disease, while effective disease treatments seek to restore this balance. Here, we present a method based on quantitative phase imaging (QPI) based measurements of cell mass and the velocity of mass transport to quantify the balance of growth and degradation within intracellular control volumes. The result, which we call Lagrangian velocimetry for intracellular net growth (LVING), provides high resolution maps of intracellular biomass production and degradation. We use LVING to quantify the growth in different regions of the cell during phases of the cell cycle. LVING can also be used to quantitatively compare the effect of range of chemotherapy drug doses on subcellular growth processes. Finally, we applied LVING to characterize the effect of autophagy on the growth machinery inside cells. Overall, LVING reveals both the structure and distribution of basal growth within cells, as well as the disruptions to this structure that occur during alterations in cell state.
Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions
Authors: Abe Takeshi , Asai Yoshiyuki , Lintas Alessandra , Villa Alessandro E. P. 
Published: April 2024

AbstractQuadratic Phase Coupling (QPC) serves as an essential statistical instrument for evaluating nonlinear synchronization within multivariate time series data, especially in signal processing and neuroscience fields. This study explores the precision of QPC detection using numerical estimates derived from cross-bicoherence and bivariate Granger causality within a straightforward, yet noisy, instantaneous multiplier model. It further assesses the impact of accidental statistically significant bifrequency interactions, introducing new metrics such as the ratio of bispectral quadratic phase coupling and the ratio of bivariate Granger causality quadratic phase coupling. Ratios nearing 1 signify a high degree of accuracy in detecting QPC. The coupling strength between interacting channels is identified as a key element that introduces nonlinearities, influencing the signal-to-noise ratio in the output channel. The model is tested across 59 experimental conditions of simulated recordings, with each condition evaluated against six coupling strength values, covering a wide range of carrier frequencies to examine a broad spectrum of scenarios. The findings demonstrate that the bispectral method outperforms bivariate Granger causality, particularly in identifying specific QPC under conditions of very weak couplings and in the presence of noise. The detection of specific QPC is crucial for neuroscience applications aimed at better understanding the temporal and spatial coordination between different brain regions.
Coping and emotions of global higher education students to the Ukraine war worldwide
Authors: Raccanello Daniela , Burro Roberto , Aristovnik Aleksander , Ravšelj Dejan , Umek Lan , Vicentini Giada , Hall Rob , Buizza Chiara , Buzdar Muhammad Ayub , Chatterjee Surobhi , Cucari Nicola , Dobrowolska Beata , Ferreira-Oliveira Ana Teresa , França Thais , Ghilardi Alberto , Inasius Fany , Kar Sujita Kumar , Karampelas Konstantinos , Kuzyshyn Andrii , Lazăr Florin , Machin-Mastromatteo Juan D. , Malliarou Maria , Marques Bertil P. , Méndez-Prado Silvia Mariela , Mollica Cristina , Obadić Alka , Olaniyan Olawale Festus , Rodrigues Ana Sofia , Sbravati Giulio , Vasić Aleksandra , Zamfir Ana-Maria , Tomaževič Nina 
Published: April 2024

AbstractTrauma scientists have raised the alarm about the devastating consequences of the Ukraine war on mental health. We examined how higher education students—as indirect victims—coped with this conflict and how they emotionally reacted during 2022. We involved 2314 students from 16 countries through an online survey. A structural equation model indicated significant relations between war-related worry about military and macroeconomics domains and two coping strategies (opposition, support giving), in turn significantly linked with six emotions. The model was strongly invariant across gender, study field, and geographic area. The most frequent emotions were anger and anxiety, followed by two future-centred emotions (hopelessness and hope). Emotions were more frequent for females and students of the countries geographically close to the war region. Our findings call for evidence-based policy recommendations to be implemented by institutions to combat the negative short and long-term psychological sequelae of being witnesses of armed conflicts.
Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT
Authors: Kim Hojin , Yoo Sang Kyun , Kim Jin Sung , Kim Yong Tae , Lee Jai Wo , Kim Changhwan , Hong Chae-Seon , Lee Ho , Han Min Cheol , Kim Dong Wook , Kim Se Young , Kim Tae Min , Kim Woo Hyoung , Kong Jayoung , Kim Yong Bae 
Published: April 2024

AbstractThis work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT). Patient cohort with 50 pairs of T2-weighted MR and CT images from cervical cancer patients was split into 40 for training and 10 for testing phases. We conducted deformable image registration and Nyul intensity normalization for MR images to maximize the similarity between MR and CT images as a preprocessing step. The processed images were plugged into a deep learning model, generative adversarial network. To prove clinical feasibility, we assessed the accuracy of synthetic CT images in image similarity using structural similarity (SSIM) and mean-absolute-error (MAE) and dosimetry similarity using gamma passing rate (GPR). Dose calculation was performed on the true and synthetic CT images with a commercial Monte Carlo algorithm. Synthetic CT images generated by deep learning outperformed MRCAT images in image similarity by 1.5% in SSIM, and 18.5 HU in MAE. In dosimetry, the DL-based synthetic CT images achieved 98.71% and 96.39% in the GPR at 1% and 1 mm criterion with 10% and 60% cut-off values of the prescription dose, which were 0.9% and 5.1% greater GPRs over MRCAT images.
Randomness impacts the building of specific priors, visual exploration, and perception in object recognition
Authors: Gal Cécile , Țincaș Ioana , Moca Vasile V. , Ciuparu Andrei , Dan Emanuela L. , Smith Marie L. , Gliga Teodora , Mureșan Raul C. 
Published: April 2024

AbstractRecognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack a full understanding of the role visual information sampling plays in this process, and its relation to the individual’s priors. To bridge this gap, the eye-movements of 18 adult participants were recorded during a free-viewing object-recognition task usingDotsstimuli1. Participants viewed the stimuli in one of three orders: from most visible to least (Descending), least visible to most (Ascending), or in a randomised order (Random). This dictated the strength of their priors along the experiment. Visibility order influenced the participants’ recognition performance and visual exploration. In addition, we found that while orders allowing for stronger priors generally led participants to visually sample more informative locations, this was not the case ofRandomparticipants. Indeed, they appeared to behave naïvely, and their use of specific object-related priors was fully impaired, while they maintained the ability to use general, task-related priors to guide their exploration. These findings have important implications for our understanding of perception, which appears to be influenced by complex cognitive processes, even at the basic level of visual sampling during object recognition.
Online evolution of a phased array for ultrasonic imaging by a novel adaptive data acquisition method
Authors: Lukacs Peter , Stratoudaki Theodosia , Davis Geo , Gachagan Anthony 
Published: April 2024

AbstractUltrasonic imaging, using ultrasonic phased arrays, has an enormous impact in science, medicine and society and is a widely used modality in many application fields. The maximum amount of information which can be captured by an array is provided by the data acquisition method capturing the complete data set of signals from all possible combinations of ultrasonic generation and detection elements of a dense array. However, capturing this complete data set requires long data acquisition time, large number of array elements and transmit channels and produces a large volume of data. All these reasons make such data acquisition unfeasible due to the existing phased array technology or non-applicable to cases requiring fast measurement time. This paper introduces the concept of an adaptive data acquisition process, the Selective Matrix Capture (SMC), which can adapt, dynamically, to specific imaging requirements for efficient ultrasonic imaging. SMC is realised experimentally using Laser Induced Phased Arrays (LIPAs), that use lasers to generate and detect ultrasound. The flexibility and reconfigurability of LIPAs enable the evolution of the array configuration, on-the-fly. The SMC methodology consists of two stages: a stage for detecting and localising regions of interest, by means of iteratively synthesising a sparse array, and a second stage for array optimisation to the region of interest. The delay-and-sum is used as the imaging algorithm and the experimental results are compared to images produced using the complete generation-detection data set. It is shown that SMC, without a priori knowledge of the test sample, is able to achieve comparable results, while preforming $$\sim$$
∼
10 times faster data acquisition and achieving $$\sim$$
∼
10 times reduction in data size.
The development of lateral flow devices for urinary biomarkers to assess kidney health
Authors: D Souza Serena , Obeid Wassim , Hernandez Jeanine , Hu David , Wen Yumeng , Moledina Dennis G. , Albert Andre , Gregg Anya , Wheeler Andrew , Philbrook Heather Thiessen , Parikh Chirag R. 
Published: April 2024

AbstractSerum creatinine levels are insensitive to real-time changes in kidney function or injury. There is a growing interest in assessing kidney injury by measuring biomarkers in body fluid. From our previous studies, we identified and reported three urinary biomarkers namely Uromodulin (UMOD), Osteopontin (OPN), and Interleukin-9 (IL-9) to be associated with kidney health. The availability of a rapid point-of-care test for these urinary biomarkers will potentially accelerate its applicability and accessibility. In this study, we aimed to develop novel lateral flow device (LFD) for UMOD, OPN and IL-9. We tested paired antibodies using Enzyme Linked Immunosorbent Assay wherein we observed functionality only for UMOD and OPN and not for IL-9. A conjugation buffer pH of 7.8 and 8.5 was found suitable at a detection antibody concentration of 15 µg/mL for LFD development. The developed LFDs were found to quantitatively measure UMOD standard (LLOD of 80,000 pg/mL) and OPN standard (LLOD of 8600 pg/mL) respectively. The LFD was also able to measure human urinary UMOD and OPN with a percent CV of 12.12 and 5.23 respectively.
Bioactive and biodegradable cotton fabrics produced via synergic effect of plant extracts and essential oils in chitosan coating system
Authors: Szadkowski Bolesław , Śliwka-Kaszyńska Magdalena , Marzec Anna 
Published: April 2024

AbstractFunctional antibacterial textile materials are in great demand in the medical sector. In this paper, we propose a facile, eco-friendly approach to the design of antibacterial biodegradable cotton fabrics. Cotton fiber fabrics were enhanced with a chitosan coating loaded with plant extracts and essential oils. We employed Fourier-transform infrared (FTIR) and X-ray photoelectron spectroscopy (XPS), UV–Vis spectrophotometry, optical microscopy, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) to characterize the color, structure, and thermal properties of the modified fabrics. The fabrics were found to effectively induce growth inhibition of Gram-positive and Gram-negative bacteria, especially when a synergic system of aloe vera extract and cinnamon essential oil was applied in the coating formulation. Additionally, we observed significant color and weight changes after 5, 10, and 20 days in soil biodegradability tests. Given the straightforward modification process and the use of non-toxic natural materials, these innovative bio-based and biodegradable cotton fabrics show great promise as protective antimicrobial textiles for healthcare applications.
The complete Chloroplast genome of Stachys geobombycis and comparative analysis with related Stachys species
Authors: Wang Ru , Lan Zheng , Luo Yongjian , Deng Zhijun 
Published: April 2024

AbstractHerb genomics, at the forefront of traditional Chinese medicine research, combines genomics with traditional practices, facilitating the scientific validation of ancient remedies. This integration enhances public understanding of traditional Chinese medicine’s efficacy and broadens its scope in modern healthcare. Stachys species encompass annual or perennial herbs or small shrubs, exhibiting simple petiolate or sessile leaves. Despite their wide-ranging applications across various fields, molecular data have been lacking, hindering the precise identification and taxonomic elucidation of Stachys species. To address this gap, we assembled the complete chloroplast (CP) genome of Stachys geobombycis and conducted reannotation and comparative analysis of seven additional species within the Stachys genus. The findings demonstrate that the CP genomes of these species exhibit quadripartite structures, with lengths ranging from 14,523 to 150,599 bp. Overall, the genome structure remains relatively conserved, hosting 131 annotated genes, including 87 protein coding genes, 36 tRNA genes, and 8 rRNA genes. Additionally, 78 to 98 SSRs and long repeat sequences were detected , and notably, 6 highly variable regions were identified as potential molecular markers in the CP genome through sequence alignment. Phylogenetic analysis based on Bayesian inference and maximum likelihood methods strongly supported the phylogenetic position of the genus Stachys as a member of Stachydeae tribe. Overall, this comprehensive bioinformatics study of Stachys CP genomes lays the groundwork for phylogenetic classification, plant identification, genetic engineering, evolutionary studies, and breeding research concerning medicinal plants within the Stachys genus.
Lifestyle factors, glycemic traits, and lipoprotein traits and risk of liver cancer: a Mendelian randomization analysis
Authors: Zhang Honglu , Liu Jiyong 
Published: April 2024

AbstractThe current state of knowledge on the relationship between lifestyle factors, glycemic traits, lipoprotein traits with liver cancer risk is still uncertain despite some attempts made by observational studies. This study aims to investigate the causal genetic relationship between factors highly associated with liver cancer incidence by using Mendelian randomization (MR) analysis. Employing MR analysis, this study utilized previously published GWAS datasets to investigate whether lifestyle factors, glycemic traits, and lipoprotein traits would affect the risk of liver cancer. The study utilized three MR methods, including inverse variance-weighted model (IVW), MR Egger, and weighted median. Furthermore, MR-Egger analyses were performed to detect heterogeneity in the MR results. The study also conducted a leave-one-out analysis to assess the potential influence of individual SNPs on the MR analysis results. MR-PRESSO was used to identify and remove SNP outliers associated with liver cancer. MR analyses revealed that 2-h glucose (odds ratio, OR 2.33, 95% confidence interval, CI 1.28–4.21), type 2 diabetes mellitus (T2DM, OR 1.67, 95% CI 1.18–2.37), body mass index (BMI, OR 1.67, 95% CI 1.18–2.37), waist circumference (OR 1.78, 95% CI 1.18–2.37) were associated with increased risk of liver cancer. On the contrary, apolipoproteins B (APOB, OR 0.67, 95% CI 0.47–0.97), and low-density lipoprotein (LDL, OR 0.62, 95% CI 0.42–0.92) were negatively related to liver cancer risk. Additionally, after adjusting for BMI, apolipoproteins A-I (APOA-I, OR 0.56, 95% CI, 0.38–0.81), total cholesterol (TC, OR 0.72, 95% CI, 0.54–0.94), and total triglycerides (TG, OR 0.57, 95% CI, 0.40–0.78) exhibited a significant inverse correlation with the risk of liver cancer. This study supports a causal relationship between 2-h glucose, T2DM, BMI, and waist circumference with the increased risk of liver cancer. Conversely, the study reveals a cause-effect relationship between TC, TG, LDL, APOA-I, and APOB with a decreased risk of liver cancer.
Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment
Authors: Poquita-Du Rosa Celia , Huang Danwei , Todd Peter A. 
Published: April 2024

AbstractCharacterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.