bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trophic Dynamics and Metabolic Pathways in Host-Parasite Interactions: A Nitrogen Isotope Analysis of Amino Acids in Multiple Tissues
Authors: Khaliq Shaista , Nachev Milen , Riekenberg Philip M. , Jochmann Maik A. , Vosough Maryam , Franke Frederik , Scharsack Jörn P. , Kurtz Joachim , Sures Bernd , Meer Marcel T.J. van der , Schmidt Torsten C. 
Published: December 2024

Abstract

Trophic interactions are crucial for understanding food web complexity and energy flow in ecosystems. Including parasites in these analyses can alter dynamics and challenge ecological assumptions. Compound-specific isotope analysis (CSIA) offers greater precision than bulk SIA by analyzing individual amino acids, providing deeper insights into nutrient exchange and metabolism in host-parasite systems. In this study, we conducted a 120-day controlled feeding experiment to investigate parasite metabolic pathways, host-parasite trophic dynamics, and trophic fractionation between infected and uninfected sticklebacks. Nitrogen isotope composition (δ15N) was measured in host (Gasterosteus aculeatus) liver and muscle tissues, and its parasite (Schistocephalus solidus). Parasite serine δ15N values were higher by 4.4 ± 2.4‰ compared to host liver, indicating a strong metabolic link. Lower proline concentrations and increased alanine δ15N values (5‰) indicate support of parasite growth through conversion to hydroxyproline and increased gluconeogenesis. The trophic position difference between parasite and host tissues was < 0.5, suggesting direct assimilation of host-derived products. Infected host tissues exhibited ~ 5‰ increase in glycine δ15N over time compared to control tissues, likely reflecting the host’s increased metabolic demand for immune support during infection. This study highlights the complex metabolic interactions in host-parasite systems.
AI as a Research Proxy: Navigating the New Frontier of Social Science Inquiry through Language Models
Authors: Rafikova Antonina , Voronin Anatoly 
Published: December 2024

Abstract

As artificial intelligence transforms the landscape of social science research, large language models (LLMs) like ChatGPT present both unprecedented opportunities and unprecedented challenges. This study explores the application of ChatGPT as "surrogates" or computational substitutes for human participants in sociological and socio-psychological research. By simulating responses to complex socio-cultural issues, we investigate how well ChatGPT can replicate human attitudes toward immigration, gender stereotypes, and LGB parenting attitudes. We utilized a general simulation model employing detailed demographic prompts to generate synthetic participant responses, assessing their accuracy and political biases. Our findings reveal a consistent liberal bias in ChatGPT outputs. The results demonstrate ChatGPT’s potential to simulate diverse human behaviors while highlighting their limitations in explanatory power and susceptibility to existing societal biases. This research underscores the necessity for critical evaluation of AI-generated data in social science contexts and calls for further refinement of LLM methodologies.
Gradient boosting for generalised additive mixed models
Authors: Knieper Lars , Hothorn Torsten , Bergherr Elisabeth , Griesbach Colin 
Published: December 2024

Abstract

Generalised additive mixed models are a common tool for modelling of grouped or longitudinal data where random effects are incorporated into the model in order to account for within-group or inter-individual correlations. As an alternative to established penalised maximum likelihood approaches, several different types of boosting routines have been developed to make more demanding data situations manageable. However, when estimating mixed models with component-wise gradient boosting, random and fixed effects compete within the variable selection mechanism. This can result in irregular selection properties and biased parameter estimates, particularly when covariates are constant within clusters. Moreover, while researchers typically are more interested in the covariance structure of random effects than in the effects themselves, current gradient boosting implementations focus solely on estimating the random effects. To overcome these drawbacks we propose a novel gradient boosting scheme for generalized additive mixed models. This novel approach is implemented as an R-package mermboost, seamlessly wrapped around the established mboost framework, maintaining its flexibility while enhancing functionality. The improved performance of the new framework is shown via an extensive simulation study and real world applications.
An Analytical Study on Computed Tomography-based Volumetric Additive Manufacturing: Resin Properties and Part Size Interrelationship- Part I
Authors: Behravesh Amir H. , Tariq Asra , Buni John , Rizvi Ghaus 
Published: December 2024

Abstract

This study presents an analytical description of the computed tomography-based volumetric additive manufacturing (VAM) process with an emphasis on the impact of resin properties on product dimensions. The main issue addressed in this study is the assessment of the dimensional limitation of the objects produced using the VAM process, which is usually reported to be of the order of one centimeter. An analytical model is introduced to predict the product size based on the resin property (penetration depth -Dp), vial size (radius), and the duration of part formation; and the results indicate significant correlations among these parameters. A method of Dp measurement and analysis is also introduced that is appropriate for the VAM process. Mathematical justification is provided along with experimental verification, for the effects of the main governing factor, Dp, on the maximum possible product size. Multiple criteria are also introduced for selecting the appropriate size of resin container (vial) based on the desired object size and the value of Dp. It was found that the Dp is a crucial factor in analysis and experimentation in the VAM process and its value is fundamentally different from the one obtained in the conventional polymerization AM methods. The product dimension based on resin property, vial size and time for the formation of part is introduced by analytical model. This model provides valuable insights into the complex interplay of factors influencing VAM outcomes and can facilitate informed decision-making in material selection and process design.
Statins and minimal/mild Traumatic Brain Injury, over 60 years: a prospective cohort study
Authors: Blanca Mª Angustias Ibañez Perez de la 
Published: December 2024

Abstract

Objective: To investigate whether mortality and complication rates after minimal/mild traumatic brain injury (m/mTBI) differ between elderly patients who are chronically treated with statins and those who are not.
Design: Prospective cohort study.
Methods Over-60-year-olds (n=5067) admitted to our Emergency Department within 24 hours of m/mTBI between 29 October 2010 and 5 May 2013 and between 17 November 2017 and 30 June 2020, and patients referred for brain CT scan from other centres who met study eligibility criteria. Study inclusion criteria were age >60 years; m/mTBI <24 h before admission and GCS score of 14 or 15 with or without transient loss of consciousness or amnesia. Quantitative variables were expressed as medians with interquartile range (IQR) and categorical variables as frequencies and percentages. In bivariate analyses, haemorrhagic complication and mortality rates were compared between statin and non-statin groups and a predictive multivariate logistic regression model was constructed for mortality.
Results: The mean age was 80 years and 2982 (58%) were female. A significantly higher percentage of the statin group had GCS score of 15 (p<0.032), injury mechanism other than fall (p<0.003), craniofacial injury (p<0.004), comorbidity (p<0.001) (kidney failure, hypertension, liver disease, neurological disease, and diabetes), and chronic intake of benzodiazepines (0.002), antiplatelets (<0.001), direct anticoagulants (p<0.001), and haemorrhagic complication (0.023),. No between-group difference was observed in haemorrhagic progression (0.066), hospitalization (0.716) or mortality (0.625) rates.
Conclusions: Chronic statin consumption did not protect patients over 60 years of age from the negative cerebral effects of m/mTBI..
Explainable Attention-Enhanced Heuristic Paradigm for Multi-View Prognostic Risk Sore Development in Hepatocellular Carcinoma
Authors: Liu Anran , Zhang Jiang , Li Tong , Zheng Danyang , Ling Yihong , Lu Lianghe , Zhang Yuanpeng , Cai Jing 
Published: December 2024

Abstract

Purpose
Existing prognostic staging systems depend on expensive manual extraction by pathologists, potentially overlooking hidden information, or use black-box deep learning models, which limits their clinical acceptance.This study introduces a novel deep learning-assisted paradigm for creating interpretable, multi-view risk scores to stratify prognostic risk in hepatocellular carcinoma (HCC) patients.
Methods
510 HCC patients were enrolled in an internal dataset (SYSUCC) as training and validation cohorts to develop the Hybrid Deep Score (HDS): The Attention Activator (ATAT) was designed to heuristically identify tissues associated with high prognostic risk, and a multi-view risk scoring system based on ATAT established HDS from microscopic to macroscopic levels. The HDS was also validated on an external testing cohort (TCGA-LIHC) with 341 HCC patients. We assessed the prognostic significance using Cox regression and the concordance index (c-index).
Results
The ATAT first heuristically identified regions where necrosis, lymphocytes, and tumor tissues converge, particularly focusing on their junctions in high-risk patients. From this, this study developed three independent risk factors: microscopic morphological, co-localization, and deep global indicators, ultimately predicting HDS for each patient. The HDS outperformed existing clinical prognostic staging systems, showing higher hazard ratios (HR 3.24, 95% CI 1.91-5.43 in SYSUCC; HR 2.34, 95% CI 1.58-3.47 in TCGA-LIHC) and c-index (0.751 in SYSUCC; 0.729 in TCGA-LIHC) for Disease-Free Survival (DFS).
Conclusion
This novel paradigm, from identifying high-risk tissues to constructing prognostic risk scores, offers fresh insights into HCC research. It more precisely stratifies HCC patients into high- and low-risk groups for DFS and Overall Survival (OS) compared to existing clinical risk staging systems.
Identifying Worker and Workplace Predictors of Life Satisfaction in Age-Sex Sub- Populations: An “Emelometrics” Approach
Authors: Haley M. Ryan 
Published: December 2024

Abstract

The paper applies a blend of econometric and machine learning techniques to individual-level data from the 2008 National Study of the Changing Workforce to identify covariates that appear to predict life satisfaction across four age-sex sub-populations; specifically, females age < 49; females age 49+; males age < 49; and males age 49+. Covariates such as logged absolute earnings, stress, sleep troubles, job satisfaction, marital status, depression, health status, job physicality, and some types of workplace flexibilities and are among the strongest predictors of life satisfaction across the sub-populations. The findings largely prevail though a wide array of sensitivity analyses, including alternative specifications and alternative estimation strategies, among them exhaustive-search algorithms and variable importance results from random forest algorithms. Prediction results from confusion matrices are reported for all binary-response models alongside coefficient estimates (where possible); the logit models delivered the best prediction accuracy.
JEL Classifications: J28, J30, J32, J,63, J81
Differences in the perception of drivers and barriers to the adoption of decentralised renewable energy technologies: a comparison between Spain and Colombia
Authors: Aparisi-Cerdá I. , Ribó-Pérez D. , García-Melón M. , Gonzalez-Urango H. , Ligardo-Herrera I. 
Published: December 2024

Abstract

This research examines the drivers and barriers influencing the adoption of decentralised renewable energy technologies such as rooftop solar PV and consumer battery energy storage systems. While these technologies offer economic viability and decentralized energy infrastructure, socioeconomic disparities between countries like Spain and Colombia necessitate a nuanced understanding of their drivers and barriers. Utilizing the Analytic Network Process, we assess the perceptions of DBs in both countries. Our study aims to identify and rank factors influencing renewable energy technology adoption, compare perceptions between Spain and Colombia, and provide insights for policy design. Key contributions include systematic comparisons across diverse contexts, yielding valuable inputs for effective policy mechanisms to promote the adoption of renewable energy technologies. Tailored policy interventions that address context-specific challenges and opportunities are imperative for advancing renewable energy adoption in Colombia and Spain. By embracing a holistic approach, both countries can harness the full potential of renewable energy resources.
Research on Cross-Breed Arbitrage between Five-Year and Ten-Year Treasury Bond Futures Based on AR-GARCH Model.
Authors: Cai Yanbing , Hou Liping 
Published: December 2024

Abstract

This paper delves into the realm of cross-species arbitrage, specifically examining the relationship between the 5-year treasury bond futures contract TF2309 and the 10-year treasury bond futures contract T2309, along with the corresponding resource management strategy. Utilizing the AR-GARCH model as a foundation, the study employs 1-minute closing price data spanning from May 18, 2023, to July 4, 2023, to conduct a thorough analysis. Initially, the prices of the two futures contracts are subjected to cointegration testing to ascertain their long-term equilibrium relationship, which serves as a crucial step in establishing an arbitrage ratio. Furthermore, the study goes beyond simply establishing the ratio by designing sophisticated trading signal strategies, incorporating both symmetric and asymmetric approaches. These strategies leverage the residual series and conditional variance equations derived from the AR-GARCH model. Throughout the research, a significant emphasis is placed on resource management aspects, such as fund allocation, risk control, and return optimization. The backtesting results reveal that the implemented strategy not only delivers consistent and stable returns but also enhances the efficiency of fund allocation and mitigates trading risks. In essence, this paper contributes novel insights and tangible evidence that can be utilized for optimizing resource management and arbitrage trading strategies in the futures market.
Ablation of Cbl-b and c-Cbl in macrophages causes severe spontaneous lung inflammation via enhancing the M-CSFR signaling pathway
Authors: Zhang Jinping , Xu Fei , Tan Chensheng , Tang Kun , Qiao Guodong , Shao Yu , Li Xiaoping , Zhou Ji , Zhu Peijie , Wu Mengyun , Chen Zhengrong , Gao Xiu , Wang Yufeng , Huang Beibei , Yang Yi , Hao Chuangli 
Published: December 2024

Abstract

The Casitas B-lineage lymphoma (Cbl) family proteins are E3 ubiquitin ligases implicated in the regulation of various immune cells. However, their function in macrophages remains unclear. We show that macrophage-specific deficiency of Cbl-b and c-Cbl (Cbls) causes mice to die prematurely from spontaneous macrophage massive invasive lung inflammation. Mechanically, we identify that Cbls functions upstream of AKT and Erk to mediate the ubiquitination and degradation of M-CSFR. upon M-CSF stimulation, M-CSF binds to M-CSFR to activates downstream PI3K-AKT and Erk signaling pathways. At the same time, autophosphorylation of tyrosine at position 559 on M-CSFR receptor can promote receptor recruitment and phosphorylation of Cbls, and phosphorylated activated Cbls can target lysine at position 791 of M-CSFR for K63 linked-polyubiquitination modification. Eventually, the receptor is internalized and degraded through the lysosomal pathway, preventing the signaling pathway from being over-activated. Thus, Cbls deficiency in macrophages promotes M-CSF-induced activation of M-CSFR, AKT and Erk, which causes the accumulation of systemic macrophages due to increased cell proliferation and decreased apoptosis. Together, these data demonstrate that Cbl-b and c-Cbl play critical roles in the regulation of macrophage homeostasis by inhibiting M-CSFR-mediated AKT and Erk activation.
The immune response modulated by inoculation of commensal bacteria at birth impacts the intestinal microbiota and prevents Salmonella colonization
Authors: Florent KEMPF , Rosanna DRUMO , Anne-Marie CHAUSSE , PIerrette MENANTEAU , Tereza KUBASOVA , Sylvie ROCHE , Anne-Christine LALMANACH , Rodrigo GUABIRABA , Thierry CHAUMEIL , Guillaume LARIVIERE-GAUTHIER , Ignacio CABALLERO-POSADAS , Béatrice LAROCHE , Ivan RYCHLIK , Isabelle VIRLOGEUX-PAYANT , Philippe VELGE 
Published: December 2024

Abstract

Super- and low-shedding phenomena have been observed in genetically homogeneous hosts infected by a single bacterial strain. To decipher the mechanisms underlying these phenotypes, we examined the impact of four commensal bacteria (Mix4), inoculated at hatching, on chicken systemic immune response and intestinal microbiota composition and functions, before and after Salmonellainfection. These phenotypes were not linked to changes in cell invasion capacity of bacteria during infection. Mix4 inoculation had both short- and long-term effects on immune response and microbiota and promoted the low-shedder phenotype. Kinetic analysis revealed that Mix4 activated immune response from day 4, which modified the microbiota on day 6. This change promotes a more fermentative microbiota, which inhibited Salmonella colonization by day 11 and beyond. In contrast, control animals exhibited a delayed immune response and developed an anaerobically respiring microbiota due to local inflammation, facilitating Salmonella growth. This strategy offers promising opportunities to strengthen the barrier effect against pathogens.
Modeling Soil Moisture, Growth, and Yield in Common Beans: Calibration and Validation of AquaCrop in Northeast Brazil
Authors: Teodoro Iêdo Peroba de Oliveira de Oliveira , Magalhães Ivomberg Dourado , Santos Jose Wanderson Silva dos , Lyra Guilherme Bastos , Lyra Gustavo Bastos , Rocha Adolpho Emanuel Quintela da , Teodoro Iedo , Silva Julianna Catonio da , Amaral Tiago , Junior Ricardo Araújo Ferreira , Medeiros Aldair de Souza , Azevedo Angelo Tiago , Barros Timóteo Herculino da Silva , Mendonça Fernando Campos 
Published: December 2024

Abstract

Agricultural models based on calibration and validation processes that consider meteorological conditions, soil and crop parameters and management practices are promising tools to support decision-making in agriculture. Thus, the objective of this study was to calibrate and validate the FAO AquaCrop model for common bean crop in the region of Rio Largo, Alagoas, Brazil, simulating soil moisture, total dry biomass (TDB), grain yield (GY), and canopy cover (CC). The model was calibrated with data from an experiment conducted from 11-17-2015 to 02-01-2016, changing the non-conservative parameters until obtaining the lowest percentage deviations between measured and simulated values of final TDB and GY. The model was validated using meteorological and soil data from another experiment, conducted from 12-16-2004 to 03-08-2005, and a previously calibrated crop file. The model performance in calibration and validation were evaluated based on the root mean square error (RMSE), Willmott’s index of agreement (d), Pearson’s correlation coefficient (r), standard deviation, and the confidence index (c). The model calibration model showed RMSE of 0.25 t ha-1 (TDB) and 15.58% (CC), and a very good confidence index (c > 0.76) for these variables. The validation was very good for TDB (c = 0,81) and poor for CC (c ≤ 0.40). The crop yield simulations showed percentage deviations of 0.09% (calibration) and 11.06% (validation). AquaCrop model satisfactorily simulates soil moisture and canopy cover, with better performance for TDB and GY.
Efficient systems for groundwater defluoridation: a pilot study for rural schools in southern Brazil
Authors: Castro Bender Luana Bertolo Y , Schneider Vinícius Kasper , Teixeira Luciana Costa , da Rosa Guterres Mateus , de Cassia de Souza Schneider Rosana , Lobo Eduardo A. , da Costa Adilson Ben 
Published: December 2024

ABSTRACT

Water is vital for human life, socioeconomic development, and environmental conservation. Access to safe drinking water and sanitation is a human right recognized by the United Nations’ 2030 Agenda in its Sustainable Development Goal No. 6. In this context, fluoride in groundwater at concentrations of 0.6–0.9 mg L−1 is essential for dental health. However, at higher levels (&gt;1.5 mg L−1), it is harmful to health. Thus, this study evaluated the removal of excess fluoride from groundwater in defluoridation systems installed in rural schools using activated bone charcoal as an adsorbent. The performance results of the campus defluoridation system indicate that the system can meet the consumption needs of a school with up to 39 people consuming 2 L day−1, with a minimum flow rate of 3.3 L h−1, for a minimum period of 90 days. Regarding the efficiency of fluoride removal from water in rural schools A, B, and C, the results indicated a value higher than 97%, meeting potability standards. The technology is sustainable, improves sanitation conditions, and ensures safe and accessible drinking water for all.
The Importance of Stem Cells in the Treatment of Neuropathic Pain
Authors: Kiabi Farshad Hassanzadeh , Khosravi Tayebeh , Ahangar Saeed Gharooee , Beiranvand Siavash 
Published: December 2024

Abstract:
Many disorders, including heart, bone, cancer, liver, and brain disease, have been treated
using stem cell therapy as a viable alternative. The somatosensory system is affected by a lesion,
which leads to neuropathic pain (NP), and just a relatively tiny fraction of patients now receive
effective care from existing pharmacological medications. There have been studies to show
the effectiveness of various stem cells in reducing or treating experimental neurological pain, although
these studies are uncommon in number. In this narrative review, we will summarize the
preclinical and clinical research that has been conducted on the effectiveness of several stem cell
types, such as mesenchymal stem cells, bone-derived stem cells, and neural stem cells, in reducing
neurological pain in this study.