bluuebunny/crossref_metadata_2025_split huggingface dataset:
A combination of Δ9-tetrahydrocannabinol and cannabidiol modulates glutamate dynamics in the hippocampus of an animal model of Alzheimer’s disease
Authors: Sánchez-Fernández Nuria , Gómez-Acero Laura , Castañé Anna , Adell Albert , Campa Leticia , Brito Verónica , Ginés Silvia , Queiroz Francisco , Silva Henrique , Lopes João Pedro , Lopes Cátia R. , Radošević Marija , Gasull Xavier , Cunha Rodrigo A , Köfalvi Attila , Ferreira Samira G , Ciruela Francisco , Aso Ester 
Published: March 2024

Abstract
Background: Dysregulation of glutamatergic activity has been shown to contribute to cognitive impairment and to the progression of the neurodegenerative process in Alzheimer’s disease (AD). Previous data revealed that chronic treatment with a combination of two natural cannabinoids, Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD), reduces cognitive decline in APP/PS1 mice. Since the endogenous cannabinoid system plays a key role in the control of neuronal excitability, we hypothesize that the chronic treatment with the combination of THC and CBD might alleviate cognitive decline in APP/PS1 mice by modulating glutamate dynamics in the hippocampus.
Methods: In vivo microdialysis was used to assess extracellular glutamate levels in the hippocampus of APP/PS1 and wild-type (WT) mice chronically treated with THC and CBD. The levels of glutamate transporters and of glutamate receptors and their associated signaling pathways were assessed by immunoblotting. Electrophysiological recordings were used to evaluate synaptic transmission and plasticity. Dendritic spine density and morphology was analyzed by DiI ballistic labeling.
Results: Chronic treatment with the combination of THC and CBD reduced the extracellular glutamate levels in the hippocampus of APP/PS1 and WT mice in response to the depolarizing drug veratridine or the glutamate transporter GLT-1 inhibitor dihydrokainic acid. No relevant effects were observed in the levels of the main glutamate receptor subunits or transporters and in their associated signaling mediators after chronic treatment. Similarly, no significant treatment effects were observed in dendritic spine density and morphology in the hippocampus or in the induction of long-term potentiation in CA1 area in treated animals. However, the input-output curve revealed that chronic THC and CBD treatment reduced the basal excitability of hippocampal CA1 synapses in both APP/PS1 and WT mice.
Conclusions: Our data suggest that the beneficial effects of these cannabinoids at the cognitive levels might be related to the modulation of glutamate dynamics in the hippocampus and support their potential therapeutic properties against AD.
Landsat greening trends in alpine ecosystems are inflated by multidecadal increases in summer observations
Authors: Bayle Arthur , Gascoin Simon , Berner Logan T. , Choler Philippe 
Published: March 2024

Abstract

Remote sensing is an invaluable tool for tracking decadal-scale changes in vegetation greenness in response to climate and land use changes. While the Landsat archive has been widely used to explore these trends and their spatial and temporal complexity, its inconsistent sampling frequency over time and space raises concerns about its ability to provide reliable estimates of annual vegetation indices such as the annual maximum NDVI, commonly used as a proxy of plant productivity. Here we demonstrate for seasonally snow-covered ecosystems, that greening trends derived from annual maximum NDVI can be significantly overestimated because the number of available Landsat observations increases over time, and mostly that the magnitude of the overestimation varies along environmental gradients. Typically, areas with a short growing season and few available observations experience the largest bias in greening trend estimation. We show these conditions are met in late snowmelting habitats in the European Alps, which are known to be particularly sensitive to temperature increases and present conservation challenges. In this critical context, almost 50% of the magnitude of estimated greening can be explained by this bias. Our study calls for greater caution when comparing greening trends magnitudes between habitats with different snow conditions and observations. At a minimum we recommend reporting information on the temporal sampling of the observations, including the number of observations per year, when long term studies with Landsat observations are undertaken.
Assessment of surface and groundwater quality in the Ctalamochita river basin, Argentina: Hydrogeochemical characteristics and exploratory data analysis.
Authors: Urseler Noelia , Biolé Fernanda , Bachetti Romina , Biolé Michelle , Bellotti Camila , Marín Graciela , Morgante Carolina 
Published: March 2024

Abstract

Surface and groundwater are important resources for the drinking water supply and the development of agricultural and livestock activities in the Córdoba province, Argentina. The objective of this study was to assess the physicochemical and microbiological quality of surface (n = 14) and groundwater (n = 17) sites in the middle-lower basin of the Ctalamochita river (Córdoba, Argentina) for human and animal consumption. A total of 18 physicochemical and five microbiological parameters were evaluated to determine the hydrogeological characteristics of both water resources and their suitability for human and animal consumption using the Water Quality Index (WQI). The results indicated that Na+and HCO3‒were the dominant cation and anion, respectively, both in surface water and groundwater. Physicochemical and microbiological parameters values were compared with limits recommended by national and international guidelines. The WQI showed that groundwater samples exhibited poor quality compared to surface waters for human consumption, due to high concentrations of major ions and the presence of total coliforms andPseudomonas aeruginosa. Meanwhile, the WQI for animal consumption indicated that both surface and groundwater samples were suitable for this purpose. Piper diagram showed that most of the surface and groundwater samples were classified as Na+-Cl‒-HCO3‒and Na+-HCO3‒, respectively, showing the hydrogeochemical difference between the two water resources. Gibbs diagram indicates the processes of rock-water interaction and evaporation control the chemical composition of surface and groundwater sources. The findings of this study would enable the development of a proactive plan aimed at preserving safe and sustainable water resources in the middle-lower basin of the Ctalamochita river. This could be achieved through the implementation of preventive strategies and the introduction of innovative policies.
Prognostic biomarkers for lung adenocarcinoma based on Mendelian randomization analysis
Authors: Yang Lirong , Li Tiantian , Teng Zhaowei , Peng Xinhao , Zhao Jian , Liu Yuan , Wu Jiafan , Fan Jia , Chen Li 
Published: March 2024

Abstract
Background
Lung adenocarcinoma (LUAD) is a multifaceted disease with diverse locations and timing of gene mutations, histology, and molecular pathogenesis. As a result, identifying target genes for the treatment of patients with LUAD has become a major challenge.
Method
We downloaded the gene expression profiles of 220 patients with LUAD from the Gene Expression Omnibus (GEO) database and found the differentially expressed genes (DEGs) between control and treatment groups. Mendelian randomization (MR) analysis was performed between the exposure gene eQTL ID and ieu-a-965 to obtain GWAS summary data. Sensitivity analysis was used to test for the presence of pleiotropy and heterogeneity in the instrumental variables. We further conducted MR analysis to explore the potential intersecting genes between DEGs and specific genes. Moreover, GESA and over survival analyses were performed on the intersection gene.
Result
We combined GEO and GWAS data to identify one upregulated and two downregulated genes associated with LUAD risk using IVW as the primary analytical method. And observed that the survival of the high-expression group of ANGPT1 and CD36 was significantly higher than that of the low-expression group. POU2AF1 were inconsistent with the results obtained in the Kaplan–Meier analysis and lacked statistical significance in the GSE70770 cohort
Conclusion
Our results confirmed two specific target genes CD36 and ANGPT1 based on MR analysis, providing new insights into the role of these target genes in mediating the development of LUAD.
Counterfactuals in Fuzzy Relational Models
Authors: Al-Hmouz Rami , Pedrycz Witold , Ammari Ahmed 
Published: March 2024

Abstract

Given rapidly growing requirements for explainability, counterfactual explanations have gained interest in Machine Learning systems. This study investigates this timely problem in fuzzy relational systems described by fuzzy relational equations and develops a detailed solution to the counterfactual problems encountered in this setting. An underlying optimization problem is formulated, and its gradient-based solution is constructed. It is also demonstrated that the non-uniqueness of the derived solution is conveniently formalized and quantified by admitting a result coming in the form of information granules of a higher type, namely type-2 or interval-valued fuzzy set. The construction of the solution in this format is realized by invoking the principle of justifiable granularity. We also discuss ways of designing fuzzy relations and elaborate on methods of carrying out counterfactual explanation in rule-based models. Illustrative examples are included to present the performance of the method and interpret the obtained results.
A piece-wise reconstruction of some mechanistic steps in Pickering emulsion polymerization: A semicontinuous styrene montmorilonite-supported process as a case example
Authors: Rodríguez Diego Saldaña , Fouconnier Benoit , López-Serrano Francisco 
Published: March 2024

Abstract

Building on traditional emulsion polymerization research, which continues to yield results up to the present day, techniques have emerged to produce hybrid materials. One such technique is Pickering emulsion polymerization, with numerous industrial applications. Despite a growing interest in Pickering emulsion polymerization, the intrinsic mechanisms involved have been based mainly on the findings of classical emulsion polymerization. In this work, by relying on a minimum of assumptions and using a simple model and experimental data on conversion and particle size, we obtain information about the prevailing mechanisms. More specifically, we present four main findings based on data reported previously in the literature. First, in contrast to the three rate-of-reaction intervals reported in classical emulsion polymerization, the integro-differential method yielded only two rate-of-reaction intervals against conversion. Second, a master curve is constructed by plotting the reaction rate against overall conversion, showing a maximum of approximately 55% conversion. Third, despite having a semi-continuous process, monomer concentration inside the particles is not constant. Finally, particle density is a strong function of the Pickering agent concentration, where two fitting parameters (nucleation and coagulation) allowed an accurate description for the particle number time-evolution. Both parameters showed a power-law dependence with clay concentration.
Ulcerative colitis and estrogen receptor-negative breast cancer risk: a Mendelian randomized study
Authors: liu xiaolin , Wang Shan , Lv Hongwei , Chen Enli , Yu Jing 
Published: March 2024

Abstract
BACKGROUND: Some studies have suggested a potential association between ulcerative colitis (UC) and estrogen receptor-negative breast cancer. However, whether there is a causal relationship between the two is currently unknown. In this study, we will investigate the relationship between UC and estrogen receptor-negative breast cancer risk from a genetic perspective.
OBJECTIVE: This study explored the causal relationship between UC and estrogen receptor-negative breast cancer risk.
METHODS: Patients with UC (n=27,432) and estrogen receptor-negative breast cancer (n=22,068) who met the same ethnicity and came from different regions were selected. The causal relationship between UC and estrogen receptor-negative breast cancer risk was evaluated by five methods, namely, Mendelian randomised Egger regression, median weighted, IVW random effects model, IVW radial method, and IVW fixed effects model, respectively, with OR. Sensitivity analyses were performed using Cochran's Q test, MR⁃Egger regression intercept term, MR⁃PRESSO, and leave-one-out method to assess the stability and reliability of the results.
RESULTS: European ethnicity was the basis of GWAS data on screened UC and estrogen receptor-negative breast cancers. In MR analysis, we found that genetically predicted UC was associated with an increased risk of estrogen receptor-negative breast cancer, and the results of Weighted median, Simple mode, Weighted mode, and MR Egger all showed similar trends (OR=1.07, 95% CI:1.03-1.11). The results of sensitivity analyses remained consistent, suggesting that UC is associated with a high prevalence of estrogen receptor-negative breast cancer.
CONCLUSION: Our findings suggest that patients with UC have an increased risk of developing estrogen receptor-negative breast cancer.
Material Property Prediction with Joint Reasoning based on Large Language Models and Knowledge Graphs for Lithium Batteries
Authors: Lei Gang , Yin Ziyu , Xiao Jianmao , Qiu Xinji , Cao Yuanlong , Zhang Qian , Wu Musheng 
Published: March 2024

Abstract
Lithium batteries, as a crucial part of modern energy storage, rely heavily on the properties of their materials, which affect energy density, cycle life, charge/dis-charge rates, and safety. Traditional experimental methods for predicting these properties are often costly and time-consuming. While data-driven machine learning approaches can predict performance by analyzing the impact of various factors, inconsistencies in data measurement and reporting, along with a lack of semantic integration of material information, hinder research on lithium battery materials. This paper introduces a lithium battery material property prediction method based on joint reasoning with large language models and knowledge graphs (JRLKG). Knowledge relationships are extracted from extensive literature to construct a knowledge graph encompassing material structure, properties, and research methods. By assessing material similarity within the graph, related information is fed into the GPT-4 model. Prompt learning techniques guide GPT-4 to leverage explicit knowledge from the external knowledge graph and its implicit knowledge for joint reasoning predictions, providing results and rationales. Experiments show that JRLKG improves the accuracy and inter-pretability of material property predictions, offering new avenues and methods for research and shortening the Research and development cycle for lithium-ion battery materials.
Could the systemic inflammatory response index be a marker for the non- dipper pattern in newly diagnosed hypertensive patients?
Authors: Kaplangoray Mustafa , Toprak Kenan , Caglayan Cuneyt , Deveci Edhem , Celik Enes , Uyan Umut , Aydın Cihan 
Published: March 2024

Abstract
Background
The Systemic Inflammatory Response Index (SIRI),has been shown to be associated with prognosis in coronary artery disease (CAD), heart failure (HF), and acute myocardial infarction.This study investigated the relationship between SIRI and non-dipper hypertension.
Methods
The study retrospectively included a total of 254 naive, newly diagnosed hypertensive individuals based on ambulatory blood pressure monitoring (ABPM),comprising 166 dippers (DHT) and 88 non-dippers (NDHT).The SIRI value of all patients was calculated based on neutrophil, monocyte, and lymphocyte counts.
Results
The study population's average age was 50.7 ± 9.4, and the male ratio was found to be 68.5%. Compared to DHT, patients in the NDHT group were found to have higher SIRI, neutrophil-lymphocyte Ratio (NLR), platelet-lymphocyte ratio (PLR), C-reactive protein (CRP), and neutrophil count, while high-density lipoprotein cholesterol (HDL-C) and lymphocyte count were lower (p < 0.05).The left ventricular mass index (LVMI) was found to be higher in the NDHT group (p < 0.05).Multivariate logistic regression analysis showed that SIRI, LVMI, and HDL-C were independent predictor factors for NDHT.ROC curve analysis determined the optimal SIRI cut-off value for predicting NDHT diagnosis to be 2.41 (sensitivity 69.3%, specificity 64.5%, area under the receiver operating characteristic curve, 0.743; p < 0.001).When the AUC values obtained for SIRI, NLR, PLR, HDL-C, and LVMI parameters in the ROC curve analysis were compared pairwise, it was shown that SIRI's discriminative capacity in predicting NDHT was superior to all other indices.
Conclusion
SIRI is an independent and significant predictor factor for NDHT and is superior in predicting NDHT diagnosis compared to HDL-C, LVMI, NLR, and PLR.
L-SHADE-MA: Enhancing L-SHADE with Momentum and Adaptive Decay Coefficient
Authors: Zhang Kai , Hu Songhua , Zhu Lianghong , Han Yu , Huang Qiujun 
Published: March 2024

Abstract

L-SHADE represents a modified form of the Differential Evolution (DE) algorithm, blending Linear Population Size Reduction (LPSR) with SHADE, the Success-History-Based Adaptation of DE. While acknowledged for its effectiveness, L-SHADE occasionally tends toward local optima and may converge too soon, especially during complex optimization challenges. Addressing these challenges, we introduce L-SHADE-MA, an advanced L-SHADE iteration employing a momentum-based mutation strategy. This approach minimizes oscillatory tendencies during searches, promoting quicker convergence and enhanced solution accuracy. Additionally, an adaptive decay coefficient, rooted in success-history, is integrated. It dynamically adjusts the balance of historical data and momentum in mutations, optimizing exploration and exploitation for each generation. This accelerates convergence and fosters population diversity. For a holistic assessment, L-SHADE-M is also presented, which adopts the momentum approach but omits the adaptive coefficient. To ascertain L-SHADE-MA’s effectiveness, it was tested on CEC2014 benchmark functions in two distinct dimensions. Performance comparisons spanned L-SHADE-M and seven other algorithms across 30 numerical functions in 50 and 100 dimensions. Empirical results unequivocally validate L-SHADE-MA’s enhancements over L-SHADE, confirming its dominance in most tested scenarios.
Amplified Microglial Dysfunction and Brain Lesions in Mouse Models for Comorbidity of Chronic Stress and Intracerebral Hypoperfusion
Authors: Zhang Yuan , Wang Shunying , Weng Jie , Zhu Yueyan , Li Jiaying , Sun Daijing , Gao Yanqin , Yu Bo , Jiang Yan 
Published: March 2024

Abstract
Both clinical and preclinical evidence demonstrates a robust association between mood disorders and cerebrovascular diseases, with the dysfunction of the neurovascular unit (NVU) recognized as a crucial factor. Despite existing research illustrating that chronic stress can induce mood-related behavioral deficits by disrupting the NVU, the underlying mechanisms remain elusive. In this study, we uncovered notable transcriptomic alterations within the NVU following chronic stress, with up-regulated genes highly enriched in microglia. Additionally, an increased interaction between microglia and cerebral microvessels was observed in the stressed brain. However, no notable evidence of blood-brain barrier (BBB) compromise was found in response to chronic stress alone. To mimic the comorbidity of depression and intracranial hypoperfusion, we combined chronic stress with bilateral common carotid artery stenosis (BCAS). Strikingly, the comorbidity model exhibited severe brain lesions across multiple regions, surpassing the effects observed in the control, stress-only, or BCAS-only groups. These lesions included pronounced microglial activation, disrupted neuronal formation, demyelination, BBB compromise, and neovascularization. Importantly, microglia emerged as central players in all observed cellular events. Our findings strongly suggest that chronic stress may compromise microglial functions, thereby increasing vulnerability to adverse cerebrovascular events. This study provides valuable insights into the intricate relationship between chronic stress and cerebrovascular diseases, underscoring the significance of considering mood management for patients with this complex comorbidity.
Causal relationship between selectins and endometriosis: a Mendelian randomization study
Authors: Chen Juan , Zhou Jie , Su LinJie , Hu Hongbo 
Published: March 2024

Abstract

Objective: Previous observational research has indicated an association between plasma selectin family members and endometriosis, and our objective was to investigate the causal association between selectins and endometriosis.
Methods: Using pooled statistics from genome-wide association studies of predominantly European ancestry and utilizing Mendelian randomization (MR), we analyzed the causal effect of the selectins E/P/L on endometriosis and the causal association of selectins with endometriosis at different sites.
Results: This study revealed a causal relationship between E-selectin and endometriosis (ratio of 0.92, 95% CI (0.86, 0.98) p = 0.01). And the causal relationship between selectins and endometriosis at different sites.
Conclusion: Our genetic predictions suggest that higher levels of selectins may provide protection against endogamy and may serve as therapeutic targets in the future.
Approximate bound energies of diatomic molecules interactions by solving Schrodinger equation case of the modified Kratzer plus Hulthen potential
Authors: Reggab Khalid 
Published: March 2024

Abstract
The equation of Schrodinger is a fundamental mathematical framework used to clarify the motion of the wave form, which is a phenomenon in the field of quantum physics. A method's wave function contains the complete description of its particles. The computational solution of the Schrodinger problem is a multifaceted problem. The eigenvalues and typical functions of the modified Kratzer plus Hulthen potential were ascertained analytically in this study. This study used an estimating approach that Nikiforov-Uvarov functional analysis had suggested for dealing with the problem. Estimating energy spectra and applying the results to certain specific diatomic molecules was the aim. The excellent results obtained from this strategy were confirmed by comparing our eigenvalue data with additional numerical data that was gathered by other researchers.
Backbone and methyl side-chain resonance assignments of the single chain Fab fragment of trastuzumab
Authors: Gagné Donald , Aramini James M. , Aubin Yves 
Published: March 2024

Abstract

Trastuzumab is a therapeutic monoclonal antibody developed to target human epidermal growth factor receptor 2 (HER2) present at higher levels in early cancers. Here we report the near complete resonance assignment of trastuzumab-scFab fragment backbone and the methyl groups of isoleucine, leucine and valine residues, as well as their stereo-assignments. The antibody fragment was produced using a single chain approach in Escherichia coli.