bluuebunny/crossref_metadata_2025_split huggingface dataset:
Valine and Inflammation Drive Epilepsy in a Mouse Model of ECHS1 Deficiency
Authors: Eller Meghan M. , Zuberi Aamir R. , Fu Xiaorong , Burgess Shawn C. , Lutz Cathleen M. , Bailey Rachel M. 
Published: June 2024

AbstractECHS1 Deficiency (ECHS1D) is a rare and devastating pediatric disease that currently has no defined treatments. This disorder results from missense loss-of-function mutations in theECHS1gene that result in severe developmental delays, encephalopathy, hypotonia, and early death. ECHS1 enzymatic activity is necessary for the beta-oxidation of fatty acids and the oxidation of branched-chain amino acids within the inner mitochondrial matrix. The pathogenesis of disease remains unknown, however it is hypothesized that disease is driven by an accumulation of toxic metabolites from impaired valine oxidation.To expand our knowledge on disease mechanisms, a novel mouse model of ECHS1D was generated that possesses a disease-associated knock-in (KI) allele and a knock-out (KO) allele. To investigate the behavioral phenotype, a battery of testing was performed at multiple time points, which included assessments of learning, motor function, endurance, sensory responses, and anxiety. Neurological abnormalities were assessed using wireless telemetry EEG recordings, pentylenetetrazol (PTZ) seizure induction, and immunohistochemistry. Metabolic perturbations were measured within the liver, serum, and brain using mass spectrometry and magnetic resonance spectroscopy. To test disease mechanisms, mice were subjected to disease pathway stressors and then survival, body weight gain, and epilepsy were assessed.Mice containing KI/KI or KI/KO alleles were viable with normal development and survival, and the presence of KI and KO alleles resulted in a significant reduction in ECHS1 protein. ECHS1D mice displayed reduced exercise capacity and pain sensation. EEG analysis revealed increased slow wave power that was associated with perturbations in sleep. ECHS1D mice had significantly increased epileptiform EEG discharges, and were sensitive to seizure induction, which resulted in death of 60% of ECHS1D mice. Under basal conditions, brain structure was grossly normal, although histological analysis revealed increased microglial activation in aged ECHS1D mice. Increased dietary valine only affected ECHS1D mice, which significantly exacerbated seizure susceptibility and resulted in death. Lastly, acute inflammatory challenge drove regression and early lethality in ECHS1D mice.In conclusion, we developed a novel model of ECHS1D that may be used to further knowledge on disease mechanisms and to develop therapeutics. Our data suggests altered metabolic signaling and inflammation may contribute to epilepsy in ECHS1D, and these alterations may be attributed to impaired valine metabolism.
Counterexample to the Lévy flight foraging hypothesis in the narrow capture framework
Authors: Tzou Justin C. , Tzou Leo 
Published: June 2024

The Lévy flight foraging hypothesis asserts that biological organisms have evolved to employ (truncated) Lévy flight searches due to such strategies being more efficient than those based on Brownian motion. However, we provide here a concrete two-dimensional counterexample in which Brownian search is more efficient. In fact, we show that the efficiency of Lévy searches worsens the farther the Lévy flight tail index deviates from the Brownian limit. Our counterexample is based on the framework of the classic narrow capture problem in which a random search is performed for a small target within a confined search domain. Our results are obtained via three avenues: Monte Carlo simulations of the discrete search processes, finite-difference solutions, and a matched asymptotic analysis of the elliptic (pseudo)differential equations of the corresponding continuum limits. Asymptotic analysis of the Lévy search yields an expression for the average search time accurate to O(1), providing insights into how the latter is impacted by various features of the target and search domain.

Published by the American Physical Society
2024
Multi-feature fusion stock prediction based on knowledge graph
Authors: Liu Zhenghao , Qian Yuxing , Lv Wenlong , Fang Yanbin , Liu Shenglan 
Published: June 2024

Purpose
Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.

Design/methodology/approach
This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.

Findings
Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.

Originality/value
The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.
Do learners exhibit a willingness to use ChatGPT? An advanced two-stage SEM-neural network approach for forecasting factors influencing ChatGPT adoption
Authors: Thongsri Nattaporn , Tripak Orawan , Bao Yukun 
Published: June 2024

Purpose
This study aims to examine the variables that influence learners’ acceptance of chat generative pre-trained transformer (ChatGPT) through the theoretical synthesis of variables in the field of behavioral science. It uses the use and gratifications theory in conjunction with variables related to the information system (IS), as proposed by the Delone and McLean IS success model.

Design/methodology/approach
This quantitative research collected data from 679 undergraduate students using stratified random sampling. A two-staged structural equation modeling (SEM)-neural network approach was used to analyze the data, with SEM used to study the factors influencing the intention to use ChatGPT. Additionally, an artificial neural network approach was used to confirm the results obtained through SEM.

Findings
The two-staged SEM-neural network approach yielded robust and consistent analysis results, indicating that the variable “System quality (SYQ)” has the highest influence, followed by “Cognitive need (CN),” “Information Quality (INQ),” “Social need (SN)” and “Affective need (AN)” in descending order of importance.

Practical implications
The results obtained from integrating the behavioral variables with IS variables will provide guidance to various organizations, such as the Ministry of Education, universities and educators, in the application of artificial intelligence technology in learning. They should prioritize the quality aspect of the system and the technological infrastructure that supports the use of ChatGPT for learning. Additionally, they should prepare learners to be ready in various dimensions, including knowledge, emotions and social aspects.

Originality/value
This study presents challenges in implementing artificial intelligence technology in learning, which educational institutions must embrace to keep up with the global technological trends. The educational sector should integrate artificial intelligence into the curriculum planning, teaching methods and learner assessment processes from the outset.
Development of a population pharmacokinetic model for the novel long‐acting injectable antipsychotic risperidone ISM®
Authors: Laveille Christian , Snoeck Eric , Ochoa Díaz de Monasterioguren Lourdes , Martínez‐González Javier , Llaudó Jordi , Anta Lourdes , Gutierro Ibon 
Published: June 2024

AbstractAimsThe aims of this study were to develop a population pharmacokinetic (PK) model for risperidone ISM® and to investigate the relationships between active moiety exposure, as described by apparent clearance (CL40), and several covariates using all data from five clinical studies.MethodsA population PK model was developed using active moiety concentrations from a study in healthy volunteers and two studies in patients with schizophrenia. Data from a comparative bioavailability study in medically stable patients and a Phase III study in patients with acute exacerbation of schizophrenia were then incorporated, using empirical Bayesian feedback and model refinement in NONMEM. Finally, covariate analysis was performed on CL40.ResultsThe final model adequately described the pharmacokinetics of 6288 active moiety concentrations in 17 healthy volunteers and 430 patients with schizophrenia. This one‐compartment disposition model had a complex absorption process, combining a small amount immediately entering the central active moiety compartment, two first‐order absorption processes and a combined zero‐order and first order process, with first‐order elimination from the central compartment. Significant covariates on CL40 were BMI and sex. Goodness‐of‐fit (GOF) plots and visual predictive checks (VPC) confirmed acceptable description of the data.ConclusionsThe population PK model adequately described active moiety concentrations from five clinical studies after risperidone ISM® administration. Relationships between active moiety exposure and covariates were defined in order to facilitate simulations for future studies. The model showed that risperidone ISM® rapidly achieves therapeutic plasma levels within the first hours after the first injection that are maintained sustainedly throughout the whole dosing interval following once‐monthly gluteal injections of 100 mg and 75 mg.
Immunogenicity of COVID‐19 vaccines in patients with follicular lymphoma receiving frontline chemoimmunotherapy
Authors: Lim Yeong Jer , Ward Victoria , Brown Anthony , Phillips Eloise , Kronsteiner Barbara , Malone Tom , Jennings Daisy , Healy Saoirse , Longet Stephanie , James Timothy , Thomson Paul , Farrell Liam , Oates Melanie , Jackson Richard , Morrison Andrew , Burns Matthew , Carroll Miles , Klenerman Paul , Turtle Lance , Naisbitt Dean , Rhodes Malcolm , Robinson Kate , Gatto Simona , Young Moya , Linton Kim , Eyre Toby A. , Eyre David W. , Dunachie Susanna , Barnes Eleanor , Pettitt Andrew 
Published: June 2024

SummaryImmune responses to primary COVID‐19 vaccination were investigated in 58 patients with follicular lymphoma (FL) as part of the PETReA trial of frontline therapy (EudraCT 2016–004010‐10). COVID‐19 vaccines (BNT162b2 or ChAdOx1) were administered before, during or after cytoreductive treatment comprising rituximab (depletes B cells) and either bendamustine (depletes CD4+ T cells) or cyclophosphamide‐based chemotherapy. Blood samples obtained after vaccine doses 1 and 2 (V1, V2) were analysed for antibodies and T cells reactive to the SARS‐CoV‐2 spike protein using the Abbott Architect and interferon‐gamma ELISpot assays respectively. Compared to 149 healthy controls, patients with FL exhibited lower antibody but preserved T‐cell responses. Within the FL cohort, multivariable analysis identified low pre‐treatment serum IgA levels and V2 administration during induction or maintenance treatment as independent determinants of lower antibody and higher T‐cell responses, and bendamustine and high/intermediate FLIPI‐2 score as additional determinants of a lower antibody response. Several clinical scenarios were identified where dichotomous immune responses were estimated with >95% confidence based on combinations of predictive variables. In conclusion, the immunogenicity of COVID‐19 vaccines in FL patients is influenced by multiple disease‐ and treatment‐related factors, among which B‐cell depletion showed differential effects on antibody and T‐cell responses.
Controversies in the pathophysiology of leg ulcers in sickle cell disease
Authors: Catella Judith , Guillot Nicolas , Nader Elie , Skinner Sarah , Poutrel Solène , Hot Arnaud , Connes Philippe , Fromy Berengère 
Published: June 2024

SummaryPatients with sickle cell disease (SCD) often experience painful vaso‐occlusive crises and chronic haemolytic anaemia, as well as various acute and chronic complications, such as leg ulcers. Leg ulcers are characterized by their unpredictability, debilitating pain and prolonged healing process. The pathophysiology of SCD leg ulcers is not well defined. Known risk factors include male gender, poor social conditions, malnutrition and a lack of compression therapy when oedema occurs. Leg ulcers typically start with spontaneous pain, followed by induration, hyperpigmentation, blister formation and destruction of the epidermis. SCD is characterized by chronic haemolysis, increased oxidative stress and decreased nitric oxide bioavailability, which promote ischaemia and inflammation and consequently impair vascular function in the skin. This cutaneous vasculopathy, coupled with venostasis around the ankle, creates an ideal environment for local vaso‐occlusive crises, which can result in the development of leg ulcers that resemble arterial ulcers. Following the development of the ulcer, healing is hindered as a result of factors commonly observed in venous ulceration, including venous insufficiency, oedema and impaired angiogenesis. All of these factors are modulated by genetic factors. However, our current understanding of these genetic factors remains limited and does not yet enable us to accurately predict ulceration susceptibility.
Spatiotemporal cell landscape of human embryonic tooth development
Authors: Shi Yueqi , Yu Yejia , Li Jutang , Sun Shoufu , Han Li , Wang Shaoyi , Guo Ke , Yang Jingang , Qiu Jin , Wei Wenjia 
Published: June 2024

AbstractUnderstanding the cellular composition and trajectory of human tooth development is valuable for dentistry and stem cell engineering research. Previous single‐cell studies have focused on mature human teeth and developing mouse teeth, but the cell landscape of human embryonic dental development is still unknown. In this study, tooth germ tissues were collected from aborted foetus (17–24 weeks) for single‐cell RNA sequence and spatial transcriptome analysis. The cells were classified into seven subclusters of epithelium, and seven clusters of mesenchyme, as well as other cell types such as Schwann cell precursor and pericyte. For epithelium, the stratum intermedium branch and the ameloblast branch diverged from the same set of outer enamel‐inner enamel‐ALCAM+ epithelial cell lineage, but their spatial distribution of two branches was not clearly distinct. This trajectory received spatially adjacent regulation signals from mesenchyme and pericyte, including JAG1 and APP. The differentiation of pulp cell and pre‐odontoblast showed four waves of temporally distinct gene expression, which involved regulation networks of LHX9, DLX5 and SP7, and these genes were regulated by upstream ligands such as the BMP family. This provides a reference landscape for the research on early human tooth development, covering different spatial structures and developmental periods.
From the little divergence to the little divide: Real wages in the Kingdom of Sicily (1540‒1850)
Authors: Buscemi Tancredi 
Published: June 2024

AbstractThis paper challenges the commonly held belief that Southern Italy was a homogeneous, backwards region by reconstructing real wages in the kingdom of Sicily over three centuries. The findings suggest more than one divide in pre‐unitarian regions, with Sicilian living standards being structurally higher than the Italian average. This study has important implications for traditional debates in European and Italian economic history, such as the timing of the little divergence and the Italian economic downturn. Additionally, it raises new questions regarding the origins of the regional divide, highlighting a heterogeneous picture of regional trends and the need for broader spatial coverage in wage studies to avoid the potential bias of single‐city analysis.
Fabrication, microstructure, and properties of Dy‐doped (Y1−xDyx)3Si2C2 ceramics fabricated by in situ reactive spark plasma sintering
Authors: Chen Lianghao , Cui Pengxing , Yang Guangyong , Tatarko Peter , Dai Jian‐Qing , Wang Canglong , Zhou Xiaobing 
Published: June 2024

AbstractDysprosium (Dy)‐doped (Y1−xDyx)3Si2C2 (x = 0, 0.1, 0.3, 0.5) solid solution ceramics were successfully fabricated using an in situ reaction spark plasma sintering technology, for the first time. The effect of various Dy doping contents (x) on the microstructure, mechanical, and thermal properties of (Y1−xDyx)3Si2C2 ceramics was investigated. The (0 2 0) crystal plane spacing of (Y0.5Dy0.5)3Si2C2 was 7.813 Å, which was smaller than that of Y3Si2C2, due to the fact that the atomic radius of Dy is smaller than that of Y. The Dy doping facilitated the consolidation of (Y1−xDyx)3Si2C2, thus a highly dense (Y0.5Dy0.5)3Si2C2 ceramic material with a low open porosity of 0.14% was successfully obtained at a relatively low temperature of 1 200°C. As the content of Dy doping (x) increased from 0 to 0.5, the purity of (Y1−xDyx)3Si2C2 ceramics increased from 88.3 to 90.7 wt.%, while the grain size of (Y1−xDyx)3Si2C2 ceramics decreased from 0.59 to 0.46 µm. As a result, the Vickers hardness and thermal conductivity of the (Y0.5Dy0.5)3Si2C2 material was 7.1 GPa and 9.8 W·m−1·K−1, respectively.
Synergetic engineering of ZnS/In2Te3 heterostructure for efficient oxygen evolution reaction
Authors: Alothman Asma A. , Kumar Ome Parkash , Madni Muhammad , Ahmad Imran , Mohammad Saikh , Saleem Shahroz , Abid Abdul Ghafoor 
Published: June 2024

AbstractThe potential of electrochemical water splitting to tackle energy and environmental issues has garnered substantial interest. In the present work, an effective ZnS/In2Te3 has been constructed by hydrothermal support on a stainless‐steel strip and explored for oxygen evolution. The addition of ZnS modifies the band structure of In2Te3 and enhances its specific conductivity and capacitance on an intrinsic level, making rapid ion transportation. The optimized ZnS/In2Te3 displayed efficient oxygen evolution reaction (OER) performance with an overpotential of 228 mV and a Tafel slope of 111 mV dec−1 with cyclic activity up to 1000 cycles in 1 M KOH solution. ZnS/In2Te3 has a large surface area (28 m3g−1) and a charge capacitance of (.037 mF), according to studies using Brunauer–Emmett–Teller and double‐layer capacitance. Combining several strategies improves overall electrochemical performance of ZnS/In2Te3, making it a promising option for use in state‐of‐the‐art OER.
Unemployment volatility: When workers pay costs upon accepting jobs
Authors: Ryan Rich 
Published: June 2024

AbstractHiring workers is costly. Firms' costs reduce resources that can go to recruitment and amplify how unemployment responds to changes in productivity. Workers also incur up‐front costs. Examples include moving expenses and regulatory fees. Workers' costs lessen unemployment volatility and leave resources available for recruitment unchanged. Their influence is bounded by the properties of a matching function. Using adjusted data on job finding, I estimate a bound that ascribes limited influence. The results demonstrate that workers' costs affect outcomes (firms threaten workers with paying the fixed costs again if negotiations fail), but their influence on volatility is less than firms' costs.
Effect of sheeting pressure on the viability of Escherichia coli during noodle processing
Authors: Xu Yingying , Lv Na , Yang Xudong , He Xiaohua , Li Ke , Liu Bin 
Published: June 2024

SummaryEscherichia coli is known to easily contaminate noodles and form biofilms during noodle processing. Sheeting was a key step in the processing. The objective of our study was to investigate the influence of sheeting pressure on the viability of E. coli. Our findings revealed a significant reduction in the E. coli count (by 1.46 log CFU g−1), as well as their swimming diameter (by 46.7%) and biofilm formation (by 25.7%) following an additional 20 sheeting treatments. The expression of genes (flhC, flhD, rpoS, csgD and adrA) validated the weakening of E. coli survival due to sheeting pressure. Moreover, the alterations in dough texture properties had adverse effects on the survival of E. coli. These results highlight that sheeting pressure can effectively reduce E. coli viability in dough. The implications of our findings provide valuable insights for minimising microbial contamination in noodle production.
Do cash transfer programs have different effects on children based on household disability status? Evidence from Malawi and Zambia
Authors: Silverstein Hannah , Angeles Gustavo , Handa Sudhanshu , Singh Kavita , Shanahan Meghan , Thissen David 
Published: June 2024

AbstractGlobally, about 1 billion people have disabilities. Cash transfers (CTs) are social protection programs often explicitly including people with disabilities. There is little research differentiating CT impacts by disability status. We used a triple difference estimation strategy with three‐way interaction terms to estimate disability‐differential impacts of CTs in Malawi and Zambia on material needs, physical health, and nutritional status among children. Results show CTs reduced the prevalence of illness more among children in households of members experiencing the greatest functional difficulties compared to those in households without disability. The CTs similarly improved access to material needs for all children. This research suggests CTs in Malawi and Zambia affected children in households with disabilities more in terms of health outcomes, despite experiencing similar impacts on material inputs.