bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multimodal nonlinear correlates of behavioural symptoms in frontotemporal dementia
Authors: Zamboni Giovanna , Mattioli Irene , Arya Zobair , Tondelli Manuela , Vinceti Giulia , Chiari Annalisa , Jenkinson Mark , Huey Edward D. , Grafman Jordan 
Published: August 2023

Abstract

Background
Studies exploring the brain correlates of behavioural symptoms in the frontotemporal dementia spectrum (FTD) have mainly searched for linear correlations with single modality neuroimaging data, either structural magnetic resonance imaging (MRI) or fluoro-deoxy-D-glucose positron emission tomography (FDG-PET). We aimed at studying the two imaging modalities in combination to identify nonlinear co-occurring patterns of atrophy and hypometabolism related to behavioural symptoms.
Methods
We analysed data from 93 FTD patients who underwent T1-weighted MRI, FDG-PET imaging, and neuropsychological assessment including the Neuropsychiatric Inventory, Frontal Systems Behaviour Scale, and Neurobehavioral Rating Scale. We used a data-driven approach to identify the principal components underlying behavioural variability, then related the identified components to brain variability using a newly developed method fusing maps of grey matter volume and FDG metabolism.
Results
A component representing apathy, executive dysfunction, and emotional withdrawal was associated with atrophy in bilateral anterior insula and putamen, and with hypometabolism in the right prefrontal cortex. Another component representing the disinhibition versus depression/mutism continuum was associated with atrophy in the right striatum and ventromedial prefrontal cortex for disinhibition, and hypometabolism in the left fronto-opercular region and sensorimotor cortices for depression/mutism. A component representing psychosis was associated with hypometabolism in the prefrontal cortex and hypermetabolism in auditory and visual cortices.
Discussion
Behavioural symptoms in FTD are associated with atrophy and altered metabolism of specific brain regions, especially located in the frontal lobes, in a hierarchical way: apathy and disinhibition are mostly associated with grey matter atrophy, whereas psychotic symptoms are mostly associated with hyper-/hypo-metabolism.
Šolar, the developmental corpus of Slovene
Authors: Holdt Špela Arhar , Kosem Iztok 
Published: August 2023

Abstract

The paper presents the Šolar developmental corpus of Slovene, comprising the written language production of students in Slovene elementary and secondary schools, along with teacher feedback. The corpus consists of 5,485 texts (1,635,407 words) and features linguistically categorized teacher corrections. Notably, the annotation of language problems is based on actual teacher corrections, making the corpus unique in reflecting authentic classroom correction practices. The paper addresses the corpus compilation, content and format, annotation, availability, and its applicative value. While learner corpora are abundant, developmental corpora are less common. The paper bridges the gap by introducing the evolution from Šolar 1.0 to 3.0, emphasizing improvements in text collection, error and correction annotation, and categorization methodology. It also underlines the challenges and unresolved issues of compiling developmental corpora, most notably the lack of openly available tools and standards for different steps of the compilation process. Overall, the Šolar corpus offers valuable insights into language learning and teaching, contributing to teacher training, empirical studies in applied linguistics, and natural language processing tasks.
Ιn vitro RNA delivery in breast cancer cells using polysaccharide functionalized SPIONs
Authors: Tsave Olga , Psarrou Maria , Kastrinaki Georgia , Papachristou Eleni , Papi Rigini , Zaspalis Vassilios , Nalbandian Lori , Sarafidis Charalampos , Ouranidis Andreas , Choli-Papadopoulou Theodora , Vamvakaki Maria , Chatzidoukas Christos 
Published: August 2023

Abstract
RNA-based pharmaceuticals have recently emerged as a novel platform for the prevention and treatment of numerous pathological conditions, including cancer, diabetes, and heart disease among others, because they demonstrate great potential towards effectiveness and specificity and significantly lower toxicity compared to already established treatments. However, the effective delivery of the nucleic acid to the cells remains a major challenge. The present study focuses on the use of superparamagnetic iron oxide nanoparticles (SPIONs) coated with natural polysaccharide derivatives to improve the efficiency of mRNA delivery in breast cancer cells. Two polysaccharide derivatives, namely oxidized dextran and quaternized chitosan, bearing aldehyde and cationic quaternary ammonium groups, respectively, were prepared and coated onto the SPIONs. The hybrid nanoparticles were characterized in terms of their size, surface charge, magnetization and polymer content, and were next used to bind Green Fluorescent Protein-mRNA constructs to create mRNA delivery vehicles. Biological assessments were conducted to evaluate the cellular uptake, cell proliferation, viability, migration and binding efficiency, and protein expression of the nanoparticle treated cells, aiming to develop a suitable nanocarrier for future pre-clinical in vivo application.
Longitudinal changes of brain metabolites following pediatric concussion: An Advancing Concussion Assessment in Pediatrics (A-CAP) study
Authors: La Parker L , Walker Robyn , Bell Tiffany K , Craig William , Doan Quynh , Beauchamp Miriam H. , Zemek Roger , Yeates Keith Owen , Harris Ashley D 
Published: August 2023

Abstract
Concussion is commonly characterized by a cascade of neurometabolic changes following injury. Magnetic Resonance Spectroscopy (MRS) can be used to quantify neurometabolites non-invasively. Longitudinal changes in neurometabolites have rarely been studied in pediatric concussion, and fewer studies consider symptoms. This study examines longitudinal changes of neurometabolites in pediatric concussion and associations between neurometabolites and symptom burden. Participants who presented with concussion or orthopedic injury (OI, comparison group) were recruited. The first timepoint for MRS data collection was at a mean of 12-days post-injury (n = 545). Participants were then randomized to 3- (n = 243) or 6- (n = 215) months for MRS follow-up. Parents completed symptom questionnaires to quantify somatic and cognitive symptoms at multiple timepoints following injury. There were no significant changes in neurometabolites over time in the concussion group and neurometabolite trajectories did not differ between asymptomatic concussion, symptomatic concussion, and OI groups. Cross-sectionally, Choline was significantly lower in those with persistent somatic symptoms compared to OI controls at 3-months post-injury. Lower Choline was also significantly associated with higher somatic symptoms. Although overall neurometabolites do not change over time, choline differences that appear at 3-months and is related to somatic symptoms.
Predictions of Land Use and Land Cover (LULC) and Runoff of the Teesta River Basin under Different Emission and Socioeconomic Scenarios
Authors: Rahman Syadur , Islam AKM Saiful 
Published: August 2023

Abstract
The Teesta basin, shared by Bangladesh and India, undergoes profound changes due to land use and land cover (LULC) dynamics combined with climate change, significantly impacting its water balance. This comprehensive study aims to analyze the combined effects of future LULC changes and climate change on basin runoff. Employing a cellular-automata model, we accurately predicted LULC for 2020 and projected scenarios for 2050 and 2080. We utilized the semi-distributed Soil Water Assessment Tool (SWAT) hydrological model for the base period (1995–2014) and two future periods: 2050s (2035–2064) and 2080s (2071–2100). SWAT model is forced by 8 General Circulation Models (GCMs) under two Socioeconomic Pathways (SSPs): SSP245 and SSP585. The study reveals notable LULC changes, with substantial increases in agricultural (0.49%) and settlement areas (1.67%) from 2000 to 2010, followed by changes from 2010 to 2020. The CA-Markov prediction indicates significant future increases in settlements and agricultural land by 2050 and 2080, coupled with reductions in forest, water, and snow cover. The calibrated and validated SWAT model effectively simulated discharge, yielding satisfactory results. Projected changes in discharge during the monsoon and winter periods were examined under different scenarios. Monsoon discharge is predicted to increase by 26–38% in the 2050s and 30–45% in the 2080s. Conversely, the winter/dry period may experience a decrease of 46–49% in the 2050s and 38% in the 2080s for SSP245 and SSP585 scenarios, respectively. Considering LULC changes to account, additional discharge increases during the monsoon are projected, with slight increases in the dry period during the 2050s and decreases during the 2080s. This study anticipates an increasing trend in peak flow during the monsoon and a declining trend in mean flow during winter without further upstream water control. Understanding and managing the combined effects of LULC changes and climate change on the hydrological dynamics of the basin is of utmost importance for sustainable water resource management in the region.
Variations in the cystic duct: frequency and the relationship among insertion sides and heights on the bile duct
Authors: Fujiwara Kenji , Hiraka Kiyohisa , Shindo Koji , Abe Atsushi , Masatsugu Toshihiro , Hirano Tatsuya , Sada Masayuki 
Published: August 2023

Abstract
Background
Evaluation of the cystic duct anatomy prior to cholecystectomy is important, to decrease the risk of bile duct injury. This study aimed to clarify the frequency of cystic duct variations and the relationship between them.
Methods
Data of 205 patients who underwent cholecystectomy after imaging at Sada Hospital, Japan, were analyzed. The Chi-square test was used to analyze the relationships among variations.
Results
The lateral and posterior sides of the bile duct were the two most common insertion points (92 patients, 44.9%), and the middle height was the most common insertion height (135 patients, 65.9%). Clinically important variations (spiral courses, parallel courses, low insertions, and right hepatic duct draining) relating to the risk of bile duct injury were observed in 24 patients (11.7%). Regarding the relationship between the insertion sides and heights, we noticed that the posterior insertion frequently existed in low insertions (75.0%, P < 0.001) and did not exist in high insertions. In contrast, the anterior insertion coexisted with high and never low insertions. Spiral courses have two courses: anterior and posterior, and anterior ones were only found in high insertion cases.
Conclusions
The insertion point of the cystic duct and the spiral courses tended to be anterior or lateral superiorly and posterior inferiorly. Clinically significant variations in cystic duct insertions are common and surgeons should be cautious about these variations to avoid complications.
Comparative study of binding affinity of short chain fatty acids on free fatty acid receptors-A computational approach
Authors: Sundaram Subhiksha , S Sumathi 
Published: August 2023

Abstract
Free fatty acid receptors are a class of G-protein coupled receptors, that are mainly involved in binding of free fatty acids obtained by breakdown of dietary sources. Short chain fatty acids are a class of free fatty acids that are saturated aliphatic organic compounds consisting of 1-6 carbon atoms. The most known SCFAs are acetate, butyrate and propionate. To understand the binding affinity of short chain fatty acid to the free fatty acid receptors, molecular docking was performed.Upon performing docking it was found that butyrate had the lowest binding energy for all the four free fatty acid receptors (FFAR1, FFAR2, FFAR3, FFAR4). This shows that butyrate is the best ligand for the four fatty acid receptors than acetate and propionate.
The Power of Tentative Truth: The Impacts of Enhanced Science Instruction on Student Paranormal Beliefs
Authors: Basir Mo 
Published: August 2023

Abstract
This research explores the impact of epistemic-focused science instruction on college students' paranormal beliefs and conceptual physics understanding. Despite lacking a scientific foundation, paranormal beliefs are common. Grounded on previous studies, a theoretical model was conceived to tackle this challenge. The model indicates that these beliefs, much like common science alternative ideas, are likely derived from inherent biases in intuitive thinking. Accordingly, an intervention was designed and put into practices in three consecutive semesters. The intervention incorporated epistemic and ontological training. It challenged students' intuitive idea formation and confirmation, and encouraged model-based hypothesis formation backed by empirical evidence. A three-level, mixed-methods study tested the effectiveness of the intervention. Quantitative data at the whole-class level displayed a reduction in paranormal beliefs with a small effect size. Concurrently, a large effect size was observed in enhancing students' conceptual physics understanding. Moving to the subgroup level, a k-means clustering analysis revealed distinct student clusters characterized by different shifts in paranormal beliefs and conceptual physics learning, indicating differential responses to the intervention. At the individual layer of analysis, qualitative data underscored instances where students creatively misconstrued scientific concepts to reinforce their paranormal beliefs, highlighting the situated and contextual nature of epistemic practices. This work reinforces the critical role of science as a way of knowing for transforming student epistemic practices. It highlights the transition from forming definitive truth based on intuitive idea formation and confirmation, towards model-based hypothesis formation, backed by empirical evidence, to construct a tentative truth until the better one emerges.
Safety and Efficacy of Favipiravir in COVID-19 Patients with Pneumonia. A randomized, double-blind, placebo-controlled study (FAVID)
Authors: Horcajada Juan P. , Aldonza Rebeca , Real Mónica , Espinosa Silvia Castañeda , Sendra Elena , Gomez-Junyent Joan , López-Montesinos Inmaculada , Gómez-Zorrilla Silvia , Briansó Silvia , Taberna Montserrat Duran , Fernández Andrés , Tarragó Cristina , Quintillá Teresa Auguet 
Published: August 2023

Abstract
Purpose: To design a randomized clinical trial to assess the efficacy and safety of favipiravir in patients with COVID-19 disease with pneumonia.
Methods: A randomized, double blind, placebo-controlled clinical trial of favipiravir in patients with COVID-19 pneumonia was conducted in 3 Spanish sites. Randomization 1:1 to favipiravir or placebo (in both groups added to the Standard of Care) was performed to treat the patients with COVID-19 pneumonia. The primary endpoint was “time to clinical improvement,” measured as an improvement for ≥ two categories on a 7-point WHO ordinal scale in an up to 28 days' time frame.
Results: 44 patients were randomized (23 in the favipiravir group and 21 in the placebo group). The median time to clinical improvement was not different between the favipiravir and the placebo arms (10 days for both groups) and none of the secondary endpoints showed significant differences between arms.
The proportion of adverse events (both serious and non-serious) was statistically different between the favipiravir group (68.29%) and the placebo group (31.7%) (p = 0.019), but there was insufficient statistical evidence to correlate the degree of severity of the events with the treatment groups.
Conclusions: Favipiravir administered for ten days to patients with COVID-19 and pneumonia did not improve outcomes compared with placebo. Although this is an underpowered negative study, efficacy results align with other randomized trials. However, in the present study, the non-serious adverse events were more frequent in the favipiravir group.
Synergistic Integration of Blockchain and Machine Learning: A Path to a Decentralized Intelligent Future
Authors: Neyigapula Bheema Shanker 
Published: August 2023

Abstract
The integration of blockchain and machine learning has emerged as a promising paradigm that can revolutionize various industries and applications. Blockchain’s decentralized and immutable nature, coupled with the analytical capabilities of machine learning, presents new opportunities for secure and transparent data sharing, collaborative model training, and intelligent decision-making. This research paper explores the concept of synergistic integration of blockchain and machine learning, providing an overview of the underlying technologies, related work, and existing frameworks. It proposes a novel Decentralized Intelli- gent Learning Network (DILN) framework that combines the strengths of both technologies to create a decentralized and efficient ecosystem for collaborative machine learning applications. The paper presents case studies in healthcare, finance, supply chain management, IoT, and academic research to showcase the potential impact of this integration. Furthermore, it discusses technical approaches, challenges, and ethical considerations to address in the deployment of decentralized intelligent systems. The research paper concludes by encourag- ing further research and development in the field to unlock the full potential of this transformative technology.
DFMFMA: Design of an efficient Deep learning model for age estimation from frontal Faces via Multimodal Feature representation &amp; Multicomponent Augmented analysis
Authors: Jumbadkar Rupali 
Published: August 2023

Abstract
Age estimation from facial images has various applications, including security, healthcare, and entertainment. Accurate age estimation is essential for age- dependent services such as age-restricted content filtering, targeted advertising, and personalized health care. However, age estimation from facial images is a challenging task due to various factors such as variations in pose, illumination, occlusion, and aging patterns. Conventional approaches for age estimation from facial images are typically based on handcrafted features, such as texture, shape, and appearance features. These approaches often suffer from limited discriminative power and robustness to variations in the images. With the advent of deep learning, there has been a surge of interest in using deep neural networks for age estimation from facial images. Deep neural networks can learn complex and discriminative features from the images, enhancing the accuracy and robustness of the age estimation models. The proposed approach in this paper utilizes a deep learning-based approach for age estimation from frontal face images. The approach involves the analysis of facial components, including eyes, nose, and mouth, to capture age-related changes in different regions of the face images. The components are augmented using various operations such as rotation and shifting to improve the robustness of the model against variations in pose, illumination, and occlusions. The augmented components are then converted into multimodal features and individually classified using an efficient & novel Binary Cascaded CNN that employs binary weights and activations, reducing the model’s complexity and improving its efficiency levels. The use of multimodal features allows the model to capture the age-related changes in multiple domains, improving the dis- criminative efficiency of the model under multiple class scenarios. The + model’s accuracy is evaluated on augmented FGNET datasets and samples, achieving an accuracy of 99.5% with an MAE of 1.26 across all age groups. The high accuracy achieved by the proposed model highlights its effectiveness and potential for real-world age estimation scenarios.
Environmentally Friendly Binders from Calcium Carbide Residue and Silica Fume and Feasibility for Soft Clay Stabilization
Authors: Joyklad Panuwat , Suriwong Tawat , Inyai Thunthanut , Chomphurat Thanakorn , Julphunthong Phongthorn 
Published: August 2023

Abstract
This study demonstrates the use of calcium carbide residue (CCR) and silica fume (SF), both of industrial waste, as green binders instead of ordinary Portland cement (OPC). A series of raw material fractions was designed based on the molar ratio derived from the pozzolanic reaction and the chemical composition of the raw materials. The Ca/SiO2 molar ratio (C/S ratio) ranged from 1.85 to 0.65. The chemical composition, phase evolution and microstructure of the raw materials and hydrated pastes were characterized by energy dispersive X-ray fluorescence, X-ray diffraction, thermogravimetric analysis and scanning electron microscopy/energy dispersive X-ray spectroscopy. The results show that the fraction of raw materials significantly influences the cementitious formation and compressive strength of specimens. The sample with the highest compressive strength over a long period had a C/S ratio of 1.55, which is related to the C-S-H content in the pastes. The CCR-SF mixture demonstrates promising potential as a stabilizer for enhancing the strength of soft Bangkok clay, particularly in the context of long-term observation. The addition of 30 wt.% of this mixture results in a substantial improvement, with the stabilized clay achieving an unconfined compressive strength that is 84% higher compared to the use of a 10 wt.% OPC stabilizer.
Identification and functional analysis of circulating extrachromosomal circular DNA in schizophrenia implicate its negative effect on the disorder
Authors: Xiang Xi , Pan Xiaoguang , Lv Wei , Chen Shanshan , Zhang Haoran , Li Jinguang , Liao Yanhui , Yu Jiaying , Li Jing , Dang Yonghui , You Zifan , Wang Liangliang , Chen Wei , Han Peng , Tang Jinsong 
Published: August 2023

Abstract
Background: Extrachromosomal circular DNA (eccDNA) is a circular DNA molecule derived and free from linear chromosome, its characteristics and potential function in SCZ remain unclear.
Methods: Here, we explored the presence of circulating eccDNA in the plasma of chronic SCZ and healthy control using Circle-seq. Then the molecular role of SCZ over-represented eccDNAs was investigated by bioinformatical and experimental analysis.
Results: 211 over-represented eccDNAs carrying genic segments (eccGene), including eccTAOK2, eccDNMT3B, eccSIRT5, eccJAG1 and so on, were identified in 10 chronic SCZ patients, whereas only 26 over-represented eccGenes were found in 17 healthy people. Human phenotype ontology enrichment analysis upon the 211 SCZ over-represented eccGenes showed that six of them were enriched significantly in the phenotype of progressive intellectual disability. Functional assays of two artificial eccDNAs carrying TAOK2-intronic sequence showed that they attenuated the TAOK2 mRNA expression in both U-251MG and SH-SY5Y cell lines, which the function was further confirmed by dual-luciferase reporter gene assay. In addition, RNA-seq analysis showed that introduction of the artificial eccTAOK2 in U-251MG cells resulted in dysregulation of immune-related biological processes.
Conclusions: These findings delineate the circulating eccDNAs profile of SCZ and highlight the regulatory function of eccTAOK2 and its impact on cellular immune processes, underscoring the eccDNA biology and its potential role as a noninvasive biomarker for diagnosis and monitoring of schizophrenia.