bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early-life family meal participation and anthropometric measures at 4 years of age
Authors: Hillesund Elisabet Rudjord , Sagedal Linda Reme , Øverby Nina Cecilie 
Published: September 2024

Abstract
Early-life family meal participation has been associated with several aspects of nutritional health, but longitudinal associations with linear growth have not yet been investigated. The aim of this study was to investigate whether family meal participation at 12 months of age associates with anthropometric measures 3 years later. We used follow-up data from children born to mothers in the Norwegian Fit for Delivery trial (NFFD) and included 368 first-borns with dietary and anthropometric data at 12 months and 4 years of age. We treated the sample as a cohort and conducted subgroup analyses by randomization status. A family meal participation score was used as exposure, and weight, height, and body mass index (BMI) as outcomes in crude and multivariable linear regression models adjusted for maternal education, randomization status, and child sex.
Higher family meal participation score at 12 months was positively associated with length at 12 months (B = 0.198, 95% CI 0.028, 0.367, p = 0.022) and 4 years (B = 0.283, 95% CI 0.011, 0.555, p = 0.042) in multivariable models. After additional adjustment for maternal height the associations attenuated and were no longer significant. An inverse association with BMI at 4 years of age was observed in children born to mothers that had been exposed to the NFFD intervention (B = −0.144, 95% CI −0.275, −0.014, p = 0.030), but attenuated after adjustment for maternal BMI.
The longitudinal association observed between early family meal participation and child height was largely explained by maternal height. The relationship with BMI differed according to maternal participation in a lifestyle intervention trial during pregnancy.
Quantum Calculation of the Vibrational Excitation of Nitrogen Molecules by Fast Ions: Can It Contribute to STEVE Formation?
Authors: Liang Jun , Donovan Eric 
Published: September 2024

AbstractThe vibrational‐translational (VT) excitation of nitrogen molecules led by collisions with fast ions in subauroral ion drifts (SAID) has been conceived as a potential underlying mechanism contributing to the formation of the Strong Thermal Emission Velocity Enhancement (STEVE) phenomenon (Harding et al., 2020, https://doi.org/10.1029/2020gl087102). In this study, we perform quantum calculations of the VT excitation rates of N2 led by fast‐drifting ions, and evaluate the resulting vibrational distribution of N2 with ionospheric/thermospheric parameters expected under intense SAID condition. We conclude that, while the VT energy transfer led by SAID plays a distinguishable role in the vibrational excitation of N2, it is incapable of populating the high vibrational levels to the required concentration (Harding et al., 2020, https://doi.org/10.1029/2020gl087102) to produce adequate nitric oxide density, and in turn the nitrogen‐dioxide continuum intensity, to account for the STEVE brightness.
Reconciling Global Terrestrial Evapotranspiration Estimates From Multi‐Product Intercomparison and Evaluation
Authors: Cai Yaoting , Xu Qingchen , Bai Fan , Cao Xueqi , Wei Zhongwang , Lu Xingjie , Wei Nan , Yuan Hua , Zhang Shupeng , Liu Shaofeng , Zhang Yonggen , Li Xueyan , Dai Yongjiu 
Published: September 2024

AbstractTerrestrial evapotranspiration (ET) is a vital process regulating the terrestrial water balance. However, significant uncertainties persist in global ET estimates. Focusing on the area between 60°, we performed an intercomparison of 90 state‐of‐the‐art ET products from 1980 to 2014. These products were obtained from various sources or methods and were grouped into six categories: remote sensing, reanalysis, land surface models, climate models, machine learning methods, and ensemble estimates. It is shown that global ET magnitudes of categories differ considerably, with averages ranging from 518.4 to 706.3 mm yr−1. Spatial patterns are generally consistent but with significant divergence in tropical rainforests. Global trends are mildly positive or negative (−0.10 to 0.37 mm yr−2) depending on categories but with distinct spatial variability. Evaluation against site measurements reveals various performances across land cover types; the ideal point error values range from 0.45 to 0.83, with wetlands performing the worst and open shrublands the best. Using the three‐cornered hat method, there are spatial differences in ET uncertainty, with lower uncertainty for ensemble estimates, showing less than 15% relative uncertainty in most areas. The best global ET data set varies depending on the intended use and study region. Distinct spatial patterns of controlling factors across categories have been identified, with precipitation driving arid and semi‐arid regions and leaf area index dominating tropical regions. It is suggested to include advancing precipitation inputs, incorporate vegetation dynamics, and employ hybrid modeling in future ET estimates. Constraining estimates using complementary data and robust theoretical frameworks can enhance credibility in ET estimation.
A review of geospatial exposure models and approaches for health data integration
Authors: Clark Lara P. , Zilber Daniel , Schmitt Charles , Fargo David C. , Reif David M. , Motsinger-Reif Alison A. , Messier Kyle P. 
Published: September 2024

Abstract
Background
Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health.

Objective
Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications.

Methods
We conduct a literature review and synthesis.

Results
First, we discuss key concepts and terminology for geospatial exposure data and models. Second, we provide an overview of workflows in geospatial exposure model development and health data integration. Third, we review modeling approaches, including proximity-based, statistical, and mechanistic approaches, across diverse exposure types, such as air quality, water quality, climate, and socioeconomic factors. For each model type, we provide descriptions, general equations, and example applications for environmental exposure assessment. Fourth, we discuss the approaches used to integrate geospatial exposure data and health data, such as methods to link data sources with disparate spatial and temporal scales. Fifth, we describe the landscape of open-source tools supporting these workflows.
Implications of obesity and insulin resistance for the treatment of oestrogen receptor-positive breast cancer
Authors: Javed Sohail Rooman , Skolariki Aglaia , Zameer Mohammed Zeeshan , Lord Simon R. 
Published: September 2024

AbstractBreast cancer is the most common cancer in women, and incidence rates are rising, it is thought in part, due to increasing levels of obesity. Endocrine therapy (ET) remains the cornerstone of systemic therapy for early and advanced oestrogen receptor-positive (ER + ) breast cancer, but despite treatment advances, it is becoming more evident that obesity and insulin resistance are associated with worse outcomes. Here, we describe the current understanding of the relationship between both obesity and diabetes and the prevalence and outcomes for ER+ breast cancer. We also discuss the mechanisms associated with resistance to ET and the relationship to treatment toxicity.
Mesenchymal stromal cells restrain the Th17 cell response via L-amino-acid oxidase within lymph nodes
Authors: Ni Qi , Zhen Le , Zeng Zhu , Yang Jingwen , Wang Yukai , Xu Huanke , Zhang Qixiang , Zhu Yongcheng , Tao Yu , Wang Jing , Liu Qing , Yi Kezheng , Chen Yang , Chen Qian , Wang Guangji , Zhou Fang , Shan Yunlong 
Published: September 2024

AbstractMesenchymal stromal/stem cells (MSC) have emerged as a promising therapeutic avenue for treating autoimmune diseases, eliciting considerable interest and discussion regarding their underlying mechanisms. This study revealed the distinctive ability of human umbilical cord MSC to aggregate within the lymph nodes of mice afflicted with autoimmune diseases, but this phenomenon was not observed in healthy mice. The specific distribution is driven by the heightened expression of the CCL21-CCR7 axis in mice with autoimmune diseases, facilitating the targeted homing of MSC to the lymph nodes. Within the lymph nodes, MSC exhibit a remarkable capacity to modulate Th17 cell function, exerting a pronounced anti-inflammatory effect. Transplanted MSC stimulates the secretion of L-amino-acid oxidase (LAAO), a response triggered by elevated levels of tumor necrosis factor-α (TNF-α) in mice with autoimmune diseases through the NF-κB pathway. The presence of LAAO is indispensable for the efficacy of MSC, as it significantly contributes to the inhibition of Th17 cells. Furthermore, LAAO-derived indole-3-pyruvic acid (I3P) serves as a potent suppressor of Th17 cells by activating the aryl hydrocarbon receptor (AHR) pathway. These findings advance our understanding of the global immunomodulatory effects exerted by MSC, providing valuable information for optimizing therapeutic outcomes.
Distributed representations of behaviour-derived object dimensions in the human visual system
Authors: Contier Oliver , Baker Chris I. , Hebart Martin N. 
Published: September 2024

AbstractObject vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioural goals, suggesting basic limitations of this category-centric framework. To address these limitations, we mapped a series of dimensions derived from a large-scale analysis of human similarity judgements directly onto the brain. Our results reveal broadly distributed representations of behaviourally relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behaviour-derived dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, suggesting a more expansive view on visual processing in the human brain.
The protective effects of chitosan and curcumin nanoparticles against the hydroxyapatite nanoparticles-induced neurotoxicity in rats
Authors: Eldeeb Gihan Mahmoud , Yousef Mokhtar Ibrahim , Helmy Yasser Mohamed , Aboudeya Hebatallah Mohammed , Mahmoud Shimaa A. , Kamel Maher A. 
Published: September 2024

AbstractHydroxyapatite nanoparticles (HANPs) have extensive applications in biomedicine and tissue engineering. However, little information is known about their toxicity. Here, we aim to investigate the possible neurotoxicity of HANPs and the possible protective role of chitosan nanoparticles (CNPs) and curcumin nanoparticles (CUNPs) against this toxicity. In our study, HANPs significantly reduced the levels of neurotransmitters, including acetylcholine (Ach), dopamine (DA), serotonin (SER), epinephrine (EPI), and norepinephrine (NOR). HANPs significantly suppressed cortical expression of the genes controlling mitochondrial biogenesis such as peroxisome proliferator activator receptor gamma coactivator 1α (PGC-1α) and mitochondrial transcription factor A (mTFA). Our findings revealed significant neuroinflammation associated with elevated apoptosis, lipid peroxidation, oxidative DNA damage and nitric oxide levels with significant decline in the antioxidant enzymes activities and glutathione (GSH) levels in HANPs-exposed rats. Meanwhile, co-supplementation of HANP-rats with CNPs and/or CUNPs significantly showed improvement in levels of neurotransmitters, mitochondrial biogenesis, oxidative stress, DNA damage, and neuroinflammation. The co-supplementation with both CNPs and CUNPs was more effective to ameliorate HANPs-induced neurotoxicity than each one alone. So, CNPs and CUNPs could be promising protective agents for prevention of HANPs-induced neurotoxicity.
The relationship of the source of punishment and personality traits with investment and punishment in a public goods game
Authors: Rodrigues Johannes , Leipold Natasha , Hewig Johannes , Hein Grit 
Published: September 2024

AbstractIn this study, we investigated the motivations behind punishing individuals who exploit common resources, a phenomenon crucial for resource preservation. While some researchers suggest punishment stems from concern for the common good, others propose it is driven by anger toward free riders. To probe these motivations, we developed a modified public goods game in which participants had the option to use their own money or the money from the common pool to punish free riders. The analysis included choice behavior, mouse trajectories, and personality traits like anger, empathy, and altruism. According to our results, investments were highest, and punishment was strongest if participants could punish using credits from the common pool, indicating that this is the preferred option to diminish free riding and maintain cooperation in public goods and common good contexts. Also, punishment was highest if the punisher’s own investment was high, and the investment of others was low. Concerning traits, highly altruistic individuals tended to invest more and punish less in general but gave harsher punishments when they did choose to use the common pool punitively. Conversely, trait anger and trait empathy were linked to low investment while trait empathy also tended to be related to lower punishment. Taken together, these findings underscore the role of situational factors and personality traits in fostering cooperative behavior and shaping societal norms around costly punishment.
Seminal plasma inhibits Chlamydia trachomatis infection in vitro, and may have consequences on mucosal immunity
Authors: Reot Louis , Adapen Cindy , Cannou Claude , Nunez Natalia , Lakoum Sabrine , Pimienta Camille , Lacroix Laetitia , Binois Olivier , Frydman Nelly , Nugeyre Marie-Thérèse , Le Grand Roger , Menu Elisabeth 
Published: September 2024

AbstractSeminal plasma (SP) is the main vector of C. trachomatis (CT) during heterosexual transmission from male to female. It has immunomodulatory properties and impacts the susceptibility to HIV-1 infection, but its role has not been explored during CT infection. In the female reproductive tract (FRT), CT infection induces cytokine production and neutrophil recruitment. The role of neutrophils during CT infection is partially described, they could be at the origin of the pathology observed during CT infection. During this study, we developed an experimental in vitro model to characterize the impact of CT infection and SP on endocervical epithelial cell immune response in the FRT. We also studied the impact of the epithelial cell response on neutrophil phenotype and functions. We showed that the production by epithelial cells of pro-inflammatory cytokines increased during CT infection. Moreover, the pool of SP as well as individuals SP inhibited CT infection in a dose-dependent manner. The pool of SP inhibited cytokine production in a dose-dependent manner. The pool of SP altered gene expression profiles of infected cells. The culture supernatants of cells infected or not with CT, in presence or not of the pool of SP, had an impact on neutrophil phenotype and functions: they affected markers of neutrophil maturation, activation and adhesion capacity, as well as the survival, ROS production and phagocytosis ability. This study proposes a novel approach to study the impact of the environment on the phenotype and functions of neutrophils in the FRT. It highlights the impact of the factors of the FRT environment, in particular SP and CT infection, on the mucosal inflammation and the need to take into account the SP component while studying sexually transmitted infections during heterosexual transmission from male to female.
Jagged-1+ skin Tregs modulate cutaneous wound healing
Authors: Lui Prudence PokWai , Xu Jessie Z. , Aziz Hafsah , Sen Monica , Ali Niwa 
Published: September 2024

AbstractSkin-resident regulatory T cells (Tregs) play an irreplaceable role in orchestrating cutaneous immune homeostasis and repair, including the promotion of hair regeneration via the Notch signaling ligand Jagged-1 (Jag1). While skin Tregs are indispensable for facilitating tissue repair post-wounding, it remains unknown if Jag1-expressing skin Tregs impact wound healing. Using a tamoxifen inducible Foxp3creERT2Jag1fl/fl model, we show that loss of functional Jag1 in Tregs significantly delays the rate of full-thickness wound closure. Unlike in hair regeneration, skin Tregs do not utilize Jag1 to impact epithelial stem cells during wound healing. Instead, mice with Treg-specific Jag1 ablation exhibit a significant reduction in Ly6G + neutrophil accumulation at the wound site. However, during both homeostasis and wound healing, the loss of Jag1 in Tregs does not impact the overall abundance or activation profile of immune cell targets in the skin, such as CD4+ and CD8+ T cells, or pro-inflammatory macrophages. This collectively suggests that skin Tregs may utilize Jag1-Notch signalling to co-ordinate innate cell recruitment under conditions of injury but not homeostasis. Overall, our study demonstrates the importance of Jag1 expression in Tregs to facilitate adequate wound repair in the skin.
Serum neurofilament light chain as a sensitive biomarker for neuromonitoring during extracorporeal membrane oxygenation
Authors: Fischer Stefanie , Heubner Lars , May Stephanie , Amirkhiz Puya Shalchi , Kuhle Jens , Benkert Pascal , Ziemssen Tjalf , Spieth Peter , Akgün Katja 
Published: September 2024

AbstractThe use of extracorporeal membrane oxygenation (ECMO) has grown rapidly, driven by the COVID-19 pandemic. Despite its widespread adoption, neurological complications pose a significant risk, impacting both mortality and survivors’ quality of life. Detecting these complications is challenging due to sedation and the heterogeneous nature of ECMO-associated neurological injury. Still, consensus of neurologic monitoring during ECMO is lacking since utilization and effectiveness of current neuromonitoring methods are limited. Especially in view of the heterogeneous nature of neurological injury during ECMO support an easily acquirable biomarker tracing neuronal damage independently from the underlying pathomechanism would be favorable. In a single-center prospective study on 34 severe acute respiratory distress syndrome (ARDS) patients undergoing ECMO, we explored the potential of serum neurofilament light chain levels (NfL) as a biomarker for neurological complications and its predictive power towards the overall outcome of ECMO patients. Individuals experiencing neurological complications (41%) demonstrated a notable rise in NfL levels (Tbaseline median 92.95 pg/ml; T24h median 132 pg/ml (IQR 88.6–924 pg/ml), p = 0.008; T7d median 248 pg/ml (IQR 157–1090 pg/ml), p = 0.001). Moreover, under ECMO therapy, these patients exhibited markedly elevated concentrations compared to those without neurological complications (T24h median 70.75 pg/ml (IQR 22.2–290 pg/ml), p = 0.023; T7d median 128 pg/ml (IQR 51.8–244 pg/ml), p = 0.002). There was no significant difference in the NfL dynamics between surviving patients and those who died during or shortly after ECMO therapy. While NfL indicates neuro-axonal damage during intensive care with ECMO therapy, we could not identify any correlation between survival outcome and the levels of NfL, indicating that NfL may not serve as a prognostic marker for survival. Nevertheless, additional studies involving a larger patient cohort are required.
Sewage sludge fertilization affects microbial community structure and its resistome in agricultural soils
Authors: Serwecińska Liliana , Font-Nájera Arnoldo , Strapagiel Dominik , Lach Jakub , Tołoczko Wojciech , Bołdak Małgorzata , Urbaniak Magdalena 
Published: September 2024

AbstractGlobal sewage sludge production is rapidly increasing, and its safe disposal is becoming an increasingly serious issue. One of the main methods of municipal sewage sludge management is based on its agricultural use. The wastewater and sewage sludge contain numerous antibiotic resistance genes (ARGs), and its microbiome differs significantly from the soil microbial community. The aim of the study was to assess the changes occurring in the soil microbial community and resistome after the addition of sewage sludge from municipal wastewater treatment plant (WWTP) in central Poland, from which the sludge is used for fertilizing agricultural soils on a regular basis. This study used a high-throughput shotgun metagenomics approach to compare the microbial communities and ARGs present in two soils fertilized with sewage sludge. The two soils represented different land uses and different physicochemical and granulometric properties. Both soils were characterized by a similar taxonomic composition of the bacterial community, despite dissimilarities between soils properties. Five phyla predominated, viz. Planctomycetes, Actinobacteria, Proteobacteria, Chloroflexi and Firmicutes, and they were present in comparable proportions in both soils. Network analysis revealed that the application of sewage sludge resulted in substantial qualitative and quantitative changes in bacterial taxonomic profile, with most abundant phyla being considerably depleted and replaced by Proteobacteria and Spirochaetes. In addition, the ratio of oligotrophic to copiotrophic bacteria substantially decreased in both amended soils. Furthermore, fertilized soils demonstrated greater diversity and richness of ARGs compared to control soils. The increased abundance concerned mainly genes of resistance to antibiotics most commonly used in human and animal medicine. The level of heavy metals in sewage sludge was low and did not exceed the standards permitted in Poland for sludge used in agriculture, and their level in fertilized soils was still inconsiderable.
Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies
Authors: Patel Nihil , Celaya Adrian , Eltaher Mohamed , Glenn Rachel , Savannah Kari Brewer , Brock Kristy K. , Sanchez Jessica I. , Calderone Tiffany L. , Cleere Darrel , Elsaiey Ahmed , Cagley Matthew , Gupta Nakul , Victor David , Beretta Laura , Koay Eugene J. , Netherton Tucker J. , Fuentes David T. 
Published: September 2024

AbstractImage segmentation of the liver is an important step in treatment planning for liver cancer. However, manual segmentation at a large scale is not practical, leading to increasing reliance on deep learning models to automatically segment the liver. This manuscript develops a generalizable deep learning model to segment the liver on T1-weighted MR images. In particular, three distinct deep learning architectures (nnUNet, PocketNet, Swin UNETR) were considered using data gathered from six geographically different institutions. A total of 819 T1-weighted MR images were gathered from both public and internal sources. Our experiments compared each architecture’s testing performance when trained both intra-institutionally and inter-institutionally. Models trained using nnUNet and its PocketNet variant achieved mean Dice-Sorensen similarity coefficients>0.9 on both intra- and inter-institutional test set data. The performance of these models suggests that nnUNet and PocketNet liver segmentation models trained on a large and diverse collection of T1-weighted MR images would on average achieve good intra-institutional segmentation performance.