bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psycholinguistic and emotion analysis of cryptocurrency discourse on X platform
Authors: Tash Moein Shahiki , Kolesnikova Olga , Ahani Zahra , Sidorov Grigori 
Published: April 2024

AbstractThis paper provides an extensive examination of a sizable dataset of English tweets focusing on nine widely recognized cryptocurrencies, specifically Cardano, Binance, Bitcoin, Dogecoin, Ethereum, Fantom, Matic, Shiba, and Ripple. Our goal was to conduct a psycholinguistic and emotional analysis of social media content associated with these cryptocurrencies. Such analysis can enable researchers and experts dealing with cryptocurrencies to make more informed decisions. Our work involved comparing linguistic characteristics across the diverse digital coins, shedding light on the distinctive linguistic patterns emerging in each coin’s community. To achieve this, we utilized advanced text analysis techniques. Additionally, this work unveiled an understanding of the interplay between these digital assets. By examining which coin pairs are mentioned together most frequently in the dataset, we established co-mentions among different cryptocurrencies. To ensure the reliability of our findings, we initially gathered a total of 832,559 tweets from X. These tweets underwent a rigorous preprocessing stage, resulting in a refined dataset of 115,899 tweets that were used for our analysis. Overall, our research offers valuable perception into the linguistic nuances of various digital coins’ online communities and provides a deeper understanding of their interactions in the cryptocurrency space.
Using a flashlight-contingent window paradigm to investigate visual search and object memory in virtual reality and on computer screens
Authors: Beitner Julia , Helbing Jason , David Erwan Joël , Võ Melissa Lê-Hoa 
Published: April 2024

AbstractA popular technique to modulate visual input during search is to use gaze-contingent windows. However, these are often rather discomforting, providing the impression of visual impairment. To counteract this, we asked participants in this study to search through illuminated as well as dark three-dimensional scenes using a more naturalistic flashlight with which they could illuminate the rooms. In a surprise incidental memory task, we tested the identities and locations of objects encountered during search. Importantly, we tested this study design in both immersive virtual reality (VR; Experiment 1) and on a desktop-computer screen (Experiment 2). As hypothesized, searching with a flashlight increased search difficulty and memory usage during search. We found a memory benefit for identities of distractors in the flashlight condition in VR but not in the computer screen experiment. Surprisingly, location memory was comparable across search conditions despite the enormous difference in visual input. Subtle differences across experiments only appeared in VR after accounting for previous recognition performance, hinting at a benefit of flashlight search in VR. Our findings highlight that removing visual information does not necessarily impair location memory, and that screen experiments using virtual environments can elicit the same major effects as VR setups.
Advancing forensic-based investigation incorporating slime mould search for gene selection of high-dimensional genetic data
Authors: Qiu Feng , Heidari Ali Asghar , Chen Yi , Chen Huiling , Liang Guoxi 
Published: April 2024

AbstractModern medicine has produced large genetic datasets of high dimensions through advanced gene sequencing technology, and processing these data is of great significance for clinical decision-making. Gene selection (GS) is an important data preprocessing technique that aims to select a subset of feature information to improve performance and reduce data dimensionality. This study proposes an improved wrapper GS method based on forensic-based investigation (FBI). The method introduces the search mechanism of the slime mould algorithm in the FBI to improve the original FBI; the newly proposed algorithm is named SMA_FBI; then GS is performed by converting the continuous optimizer to a binary version of the optimizer through a transfer function. In order to verify the superiority of SMA_FBI, experiments are first executed on the 30-function test set of CEC2017 and compared with 10 original algorithms and 10 state-of-the-art algorithms. The experimental results show that SMA_FBI is better than other algorithms in terms of finding the optimal solution, convergence speed, and robustness. In addition, BSMA_FBI (binary version of SMA_FBI) is compared with 8 binary algorithms on 18 high-dimensional genetic data from the UCI repository. The results indicate that BSMA_FBI is able to obtain high classification accuracy with fewer features selected in GS applications. Therefore, SMA_FBI is considered an optimization tool with great potential for dealing with global optimization problems, and its binary version, BSMA_FBI, can be used for GS tasks.
Plasminogen degrades α-synuclein, Tau and TDP-43 and decreases dopaminergic neurodegeneration in mouse models of Parkinson’s disease
Authors: Guo Chunying , Wang Ting , Huang Haiyan , Wang Xiaolu , Jiang Yugui , Li Jinan 
Published: April 2024

AbstractParkinson's disease (PD) is the second most frequently diagnosed neurodegenerative disease, and it is characterized by the intracellular and extracellular accumulation of α-synuclein (α-syn) and Tau, which are major components of cytosolic protein inclusions called Lewy bodies, in the brain. Currently, there is a lack of effective methods that preventing PD progression. It has been suggested that the plasminogen activation system, which is a major extracellular proteolysis system, is involved in PD pathogenesis. We investigated the functional roles of plasminogen in vitro in an okadaic acid-induced Tau hyperphosphorylation NSC34 cell model, ex vivo using brains from normal controls and methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated mice, and in vivo in a widely used MPTP-induced PD mouse model and an α-syn overexpression mouse model. The in vitro, ex vivo and in vivo results showed that the administered plasminogen crossed the blood‒brain barrier (BBB), entered cells, and migrated to the nucleus, increased plasmin activity intracellularly, bound to α-syn through lysine binding sites, significantly promoted α-syn, Tau and TDP-43 clearance intracellularly and even intranuclearly in the brain, decreased dopaminergic neurodegeneration and increased the tyrosine hydroxylase levels in the substantia nigra and striatum, and improved motor function in PD mouse models. These findings indicate that plasminogen plays a wide range of pivotal protective roles in PD and therefore may be a promising drug candidate for PD treatment.
Prediction error in implicit adaptation during visually- and memory-guided reaching tasks
Authors: Numasawa Kosuke , Miyamoto Takeshi , Kizuka Tomohiro , Ono Seiji 
Published: April 2024

AbstractHuman movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.
A reassessment of trends and rural–urban/regional differences in the total fertility rate in China, 2000–2020: analyses of the 2020 national census data
Authors: Li Long , Jin Guangzhao , Lai Xiaozhen , Jing Rize , Zhu He 
Published: April 2024

AbstractThe decline in the total fertility rate (TFR) is a key driver of population change and has important implications for population health and social development. However, China’s TFR has been a considerable controversy due to a lack of high-quality data. Therefore, this study used the 2020 national population census of China (NPCC) data and reverse survival method to reassess temporal trends in the TFRs and to reexamine rural–urban differences and regional variations in TFRs from 2000 to 2020 in China. Overall, there were significant gaps between the estimated and reported TFRs before 2020, and the estimated TFRs based on the 2020 NPCC data remained higher than the reported TFRs from government statistics. Although TFRs rebounded shortly in the years after the two-child policy, they have shown a wavelike decline since 2010. Additionally, the estimated TFRs fluctuated below 1.5 children per woman in urban areas compared to above 1.8 in rural areas, but the rural–urban differences continued to decrease. Regarding geographic regional variations, the estimated TFRs in all regions displayed a declining trend during 2010–2020, especially in rural areas. Large decreases of over 25% in TFRs occurred in the north, east, central, and northwest regions. In addition to changing the birth policy, the government and society should adopt comprehensive strategies, including reducing the costs of marriage, childbearing, and child education, as well as promoting work-family balance, to encourage and increase fertility levels.
Simulation of daily soft multifocal contact lenses using SimVis Gekko: from in-vitro and computational characterization to clinical validation
Authors: Esteban-Ibañez Eduardo , Montagud-Martínez Diego , Sawides Lucie , Zaytouny Amal , de Castro Alberto , Sisó-Fuertes Irene , Barcala Xoana , Piñero David P. , Furlan Walter D. , Dorronsoro Carlos , Gambra Enrique 
Published: April 2024

AbstractMultifocal contact lenses (MCLs) are one of the solutions to correct presbyopia, but their adoption is not widespread. To address this situation, visual simulators can be used to refine the adaptation process. This study aims to obtain accurate simulations for a visual simulator (SimVis Gekko; 2EyesVision) of daily soft MCL designs from four manufacturers. In-vitro characterization of these MCLs—several powers and additions- was obtained using NIMO TR-1504. From the averaged relative power profiles across powers, phase maps were reconstructed and the Through-Focus Visual Strehl metric was calculated for each MCL design. The SimVis Gekko simulation corresponding to each MCL design was obtained computationally and bench-validated. Finally, the MCL simulations were clinically validated involving presbyopic patients. The clinical validation results show a good agreement between the SimVis Gekko simulations and the real MCLs for through-focus visual acuity (TF-VA) curves and VA at three real distances. All MCL designs showed a partial correlation higher than 0.90 and a Root Mean Square Error below 0.07 logMAR between the TF-VA of simulations and Real MCLs across subjects. The validity of the simulation approach using SimVis Gekko and in-vitro measurements was confirmed in this study, opening the possibility to accelerate the adaptation of MCLs.
An explainable machine learning model for prediction of high-risk nonalcoholic steatohepatitis
Authors: Njei Basile , Osta Eri , Njei Nelvis , Al-Ajlouni Yazan A. , Lim Joseph K. 
Published: April 2024

AbstractEarly identification of high-risk metabolic dysfunction-associated steatohepatitis (MASH) can offer patients access to novel therapeutic options and potentially decrease the risk of progression to cirrhosis. This study aimed to develop an explainable machine learning model for high-risk MASH prediction and compare its performance with well-established biomarkers. Data were derived from the National Health and Nutrition Examination Surveys (NHANES) 2017-March 2020, which included a total of 5281 adults with valid elastography measurements. We used a FAST score ≥ 0.35, calculated using liver stiffness measurement and controlled attenuation parameter values and aspartate aminotransferase levels, to identify individuals with high-risk MASH. We developed an ensemble-based machine learning XGBoost model to detect high-risk MASH and explored the model’s interpretability using an explainable artificial intelligence SHAP method. The prevalence of high-risk MASH was 6.9%. Our XGBoost model achieved a high level of sensitivity (0.82), specificity (0.91), accuracy (0.90), and AUC (0.95) for identifying high-risk MASH. Our model demonstrated a superior ability to predict high-risk MASH vs. FIB-4, APRI, BARD, and MASLD fibrosis scores (AUC of 0.95 vs. 0.50, 0.50, 0.49 and 0.50, respectively). To explain the high performance of our model, we found that the top 5 predictors of high-risk MASH were ALT, GGT, platelet count, waist circumference, and age. We used an explainable ML approach to develop a clinically applicable model that outperforms commonly used clinical risk indices and could increase the identification of high-risk MASH patients in resource-limited settings.
Phenotypic analysis of ataxia in spinocerebellar ataxia type 6 mice using DeepLabCut
Authors: Piotrowski Dennis , Clemensson Erik K. H. , Nguyen Huu Phuc , Mark Melanie D. 
Published: April 2024

AbstractThis study emphasizes the benefits of open-source software such as DeepLabCut (DLC) and R to automate, customize and enhance data analysis of motor behavior. We recorded 2 different spinocerebellar ataxia type 6 mouse models while performing the classic beamwalk test, tracked multiple body parts using the markerless pose-estimation software DLC and analyzed the tracked data using self-written scripts in the programming language R. The beamwalk analysis script (BAS) counts and classifies minor and major hindpaw slips with an 83% accuracy compared to manual scoring. Nose, belly and tail positions relative to the beam, as well as the angle at the tail base relative to the nose and tail tip were determined to characterize motor deficits in greater detail. Our results found distinct ataxic abnormalities such as an increase in major left hindpaw slips and a lower belly and tail position in both SCA6 ataxic mouse models compared to control mice at 18 months of age. Furthermore, a more detailed analysis of various body parts relative to the beam revealed an overall lower body position in the SCA684Q compared to the CT-longQ27PC mouse line at 18 months of age, indicating a more severe ataxic deficit in the SCA684Q group.
A cross-sectional analysis of the PURE study on minerals intake among Malaysian adult population with hypertension
Authors: Mat Nasir Nafiza , Md Isa Zaleha , Ismail Noor Hassim , Ismail Rosnah , Mohd Tamil Azmi , Jaafar Mohd Hasni , Mohamed Yassin Mohamed Syarif , Zainol Abidin Najihah , Ab Razak Nurul Hafiza , Zulkifli Aziemah , Yusof Khairul Hazdi 
Published: April 2024

AbstractHypertension (HPT) is the leading modifiable risk factor for cardiovascular diseases and premature death worldwide. Currently, attention is given to various dietary approaches with a special focus on the role of micronutrient intake in the regulation of blood pressure. This study aims to measure the dietary intake of selected minerals among Malaysian adults and its association with HPT. This cross-sectional study involved 10,031 participants from the Prospective Urban and Rural Epidemiological study conducted in Malaysia. Participants were grouped into HPT if they reported having been diagnosed with high blood pressure [average systolic blood pressure (SBP)/average diastolic blood pressure (DBP) ≥ 140/90 mm Hg]. A validated food frequency questionnaire (FFQ) was used to measure participants' habitual dietary intake. The dietary mineral intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, sodium, and zinc was measured. The chi-square test was used to assess differences in socio-demographic factors between HPT and non-HPT groups, while the Mann–Whitney U test was used to assess differences in dietary mineral intake between the groups. The participants’ average dietary intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, selenium, sodium, and zinc was 591.0 mg/day, 3.8 mg/day, 27.1 mg/day, 32.4 mg/day, 0.4 mg/day, 1431.1 mg/day, 2.3 g/day, 27.1 µg/day, 4526.7 mg/day and 1.5 mg/day, respectively. The intake was significantly lower among those with HPT than those without HPT except for calcium and manganese. Continuous education and intervention should be focused on decreasing sodium intake and increasing potassium, magnesium, manganese, zinc, and calcium intake for the general Malaysian population, particularly for the HPT patients.
Impact of species composition on fire-induced stand damage in Spanish forests
Authors: Peris-Llopis Marina , Mola-Yudego Blas , Berninger Frank , Garcia-Gonzalo Jordi , González-Olabarria José Ramón 
Published: April 2024

AbstractMixed forests play a fundamental ecological role increasing biodiversity and providing ecosystem services; it has been suggested they have higher resilience and resistance against disturbances, particularly fire. Here, we compare tree mortality in post-fire mixed and pure stands in Spain, on 2,782 plots and 30,239 trees during the period 1986 to 2007. We show evidence that mixed stands can have higher post-fire mortality than pure stands, and specific mixtures of species with different fire-related strategies increase the stand's vulnerability to fire damage versus pure stands of either species, such is the case of Pinus halepensis—Pinus nigra mixtures. Mixtures of two species often had higher mortality than species growing in pure stands. Combinations of species with different fire-related strategies can both enhance or reduce forest resistance. The role and management of mixed forests should be reconsidered after these findings, in order to enhance forest resilience to fires.
Probing the expression and adhesion of glycans involved in Helicobacter pylori infection
Authors: Sijmons Daniel , Collett Simon , Soliman Caroline , Guy Andrew J. , Scott Andrew M. , Durrant Lindy G. , Elbourne Aaron , Walduck Anna K. , Ramsland Paul A. 
Published: April 2024

AbstractHelicobacter pylori infects approximately half the human population and has an unusual infective niche of the human stomach. Helicobacter pylori is a major cause of gastritis and has been classified as a group 1 carcinogen by the WHO. Treatment involves triple or quadruple antibiotic therapy, but antibiotic resistance is becoming increasingly prevalent. Helicobacter pylori expresses certain blood group related antigens (Lewis system) as a part of its lipopolysaccharide (LPS), which is thought to assist in immune evasion. Additionally, H. pylori LPS participates in adhesion to host cells alongside several adhesion proteins. This study profiled the carbohydrates of H. pylori reference strains (SS1 and 26695) using monoclonal antibodies (mAbs) and lectins, identifying interactions between two carbohydrate-targeting mAbs and multiple lectins. Atomic force microscopy (AFM) scans were used to probe lectin and antibody interactions with the bacterial surfaces. The selected mAb and lectins displayed an increased adhesive force over the surface of the curved H. pylori rods. Furthermore, this study demonstrates the ability of anti-carbohydrate antibodies to reduce the adhesion of H. pylori 26695 to human gastric adenocarcinoma cells via AFM. Targeting bacterial carbohydrates to disrupt crucial adhesion and immune evasion mechanisms represents a promising strategy for combating H. pylori infection.
Cullin-3 proteins be a novel biomarkers and therapeutic targets for hyperchloremia induced by oral poisoning
Authors: Duan Hui , Li Na , Qi Jia , Li Xi , Zhou Kun 
Published: April 2024

AbstractOral poisoning can trigger diverse physiological reactions, determined by the toxic substance involved. One such consequence is hyperchloremia, characterized by an elevated level of chloride in the blood and leads to kidney damage and impairing chloride ion regulation. Here, we conducted a comprehensive genome-wide analysis to investigate genes or proteins linked to hyperchloremia. Our analysis included functional enrichment, protein–protein interactions, gene expression, exploration of molecular pathways, and the identification of potential shared genetic factors contributing to the development of hyperchloremia. Functional enrichment analysis revealed that oral poisoning owing hyperchloremia is associated with 4 proteins e.g. Kelch-like protein 3, Serine/threonine-protein kinase WNK4, Serine/threonine-protein kinase WNK1 and Cullin-3. The protein–protein interaction network revealed Cullin-3 as an exceptional protein, displaying a maximum connection of 18 nodes. Insufficient data from transcriptomic analysis indicates that there are lack of information having direct associations between these proteins and human-related functions to oral poisoning, hyperchloremia, or metabolic acidosis. The metabolic pathway of Cullin-3 protein revealed that the derivative is Sulfonamide which play role in, increasing urine output, and metabolic acidosis resulted in hypertension. Based on molecular docking results analysis it found that Cullin-3 proteins has the lowest binding energies score and being suitable proteins. Moreover, no major variations were observed in unbound Cullin-3 and all three peptide bound complexes shows that all systems remain compact during 50 ns simulations. The results of our study revealed Cullin-3 proteins be a strong foundation for the development of potential drug targets or biomarker for future studies.
Practical application of quantum neural network to materials informatics
Authors: Hirai Hirotoshi 
Published: April 2024

AbstractQuantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for materials informatics (MI) problems. However, there are only a few examples of the application of QNN to multivariate regression models, and little is known about how these models are constructed. This study aims to construct a QNN model to predict the melting points of metal oxides as an example of a multivariate regression task for the MI problem. Different architectures (encoding methods and entangler arrangements) are explored to create an effective QNN model. Shallow-depth ansatzs could achieve sufficient expressibility using sufficiently entangled circuits. The “linear” entangler was adequate for providing the necessary entanglement. The expressibility of the QNN model could be further improved by increasing the circuit width. The generalization performance could also be improved, outperforming the classical NN model. No overfitting was observed in the QNN models with a well-designed encoder. These findings suggest that QNN can be a useful tool for MI.