bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of factors influencing age and cognitive function in older adults: a cross-sectional study
Authors: Li Xiaomin , He Guixiang 
Published: August 2024

Abstract

Background Cognitive impairment in the elderly continues to be a serious problem, and existing studies have mostly focused on the elderly as a whole and used multiple linear regression to study the influencing factors, without subdividing them by age, which is a limitation that does not allow us to propose targeted strategies. Therefore, the decision tree and multiple linear regression model were jointly applied in this study to study the cognitive function status and influencing factors of elderly people in different age groups, with other age groups as the research subjects.
Methods Data from the China Health and Aging Tracking Survey (CHARLS) 2020 were used to select older adults aged 60-89 as the study subjects, and SPSS 26.0 was used to analyze the data. The factors affecting cognitive function in older adults of different ages were analyzed using the one-way analysis, linear regression model, and decision tree model.
Results High level of education, good memory status, and living in towns and cities were protective factors for cognitive function in older adults of all ages. Depression and unsocialization were risk factors for cognitive function in 60-79-year-olds, but not in 80-89-year-olds.Women as a protective factor for cognitive function in 60-69-year-olds, but not in 70-89-year-olds. Disability was a risk factor for cognitive function in 70-79-year-olds, not a factor influencing cognitive function in 60-69 and 80-89-year-olds. Low life satisfaction and lack of pension insurance were risk factors for cognitive function in 80- to 89-year-olds, but not in 60- to 79-year-olds.
Conclusion The cognitive condition of older adults deteriorates with age, and there are commonalities and differences in the effects of various factors on the cognitive function of older adults in different age groups. In practice, individualized intervention models should be developed for different age groups to reduce the incidence of cognitive dysfunction in various age groups.
Flecainide enhances blood-brain barrier function: Novel mode of action of sodium channel blocking in experimental autoimmune encephalomyelitis (EAE)
Authors: Sindi Mustafa , Dobelmann Vera , Ricci Rebekka , Klees Diana , Hecker Christina , Müntefering Thomas , Issberner Andrea , Gruchot Joel , Hartung Hans-Peter , Ruck Tobias , Kurz Thomas , Stark Holger , Küry Patrick , Engelhardt Britta , Lyck Ruth , Meuth Sven G. , Dietrich Michael , Albrecht Philipp 
Published: August 2024

Abstract

Introduction
Multiple Sclerosis (MS), an autoimmune disorder, is characterized by severe neuroinflammation, leading to demyelination and neuronal damage in the CNS, resulting in significant clinical impairment. MS progression involves complex pathological processes like immune cell invasion and cytokine-mediated recruitment to the CNS. Experimental autoimmune encephalomyelitis (EAE), a model for MS, has been crucial for identifying effective treatments. Recent studies have shown that sodium channel (Nav) blockers and monoamine oxidase- (MAO) B inhibitors can alleviate symptoms of EAE and optic neuritis (ON), but their mode of action remains partially unclear.
Methods
To evaluate the effects and understand the action mechanism of Nav blockers and MAO-B inhibitors (rasagiline ,safinamide, flecainide and phenytoin) in neurological conditions, various techniques were used, including optical coherence tomography (OCT), optomotor response measurement (OMR), flow cytometry, histological evaluations, Evans blue assay, blood-brain barrier (BBB) permeability assay and gene expression analyses.
Results
The study found that the primary therapeutic effect comes from inhibiting the Nav 1.5 sodium channel, not MAO-B inhibition. Flecainide, a Nav 1.5 channel blocker, significantly reduced EAE disability scores, mitigated neurodegeneration, preserved visual function, and restricted immune cell migration into the CNS. Importantly, blocking the Nav 1.5 channel had an effect on the BBB, limiting lymphocyte entry into the CNS.
Discussion/Conclusion
This research highlights sodium channel blockers' potential in treating neuroinflammatory diseases like MS. The findings demonstrate reduced disease progression and neuroprotection, suggesting a novel therapeutic approach. Crucially, it reveals for the first time that Nav 1.5 channel blockade leads to neuroprotection primarily by affecting the BBB, a key factor in controlling immune cell migration, thus addressing a critical aspect of MS pathology.
Using a K-mer Based Approach with Machine Learning Classifiers for Enhancer Identification and Classification
Authors: Pillai Cyril , Benton Mary Lauren 
Published: August 2024

Abstract

Background
Enhancers are genetic elements that modulate the level of gene expression in cells; because they are essential for cellular function, enhancer dysfunction is associated with many complex diseases including many types of cancers. Furthermore, current research highlights the challenge of enhancer identification due to variability in enhancer definitions and identification approaches. Developing a machine learning pipeline to distinguish enhancers from other DNA elements would greatly aid the ability to study enhancers and their role in disease. In this project, we developed a random forest machine learning model to distinguish between human liver enhancer sequences with low versus high levels of support across eight different enhancer identification methods.
Results
Enhancers were classified as “shared” if they had support from multiple methods and “unique” otherwise; the threshold for the number of methods that made an enhancer region “shared” or “unique” was adjusted as an independent variable. We also extracted a set of random sequences from the human genome to evaluate potential differences between shared/unique enhancer regions and genomic background. Our machine learning model used the frequency of k length sequence (k-mer) patterns as features to classify the shared versus unique enhancer regions. We hypothesized that the distribution of k-mer frequencies would correlate with transcription factor binding sites on the enhancer and distinguish them from other types of DNA sequence.
Conclusions
The final shared vs random models perform with 93.8–99.9% accuracy, the final unique vs random models perform with 93.4–99.8% accuracy, but the final shared model performs with only 56.8–61.4% accuracy. These results indicate that the k-mer frequency distributions for shared and unique enhancers are not significantly different although shared/unique sequences differ from the genomic background.
Genetic associations with human longevity are enriched for oncogenic genes
Authors: Park Junyoung , Peña-Tauber Andrés , Talozzi Lia , Greicius Michael , Guen Yann Le 
Published: August 2024

Abstract

Human lifespan is shaped by both genetic and environmental exposures and their interaction. To enable precision health, it is essential to understand how genetic variants contribute to earlier death or prolonged survival. In this study, we tested the association of common genetic variants and the burden of rare non-synonymous variants in a survival analysis, using age-at-death (N = 35,551, median [min, max] = 72.4 [40.9, 85.2]), and last-known-age (N = 358,282, median [min, max] = 71.9 [52.6, 88.7]), in European ancestry participants of the UK Biobank. The associations we identified seemed predominantly driven by cancer, likely due to the age range of the cohort. Common variant analysis highlighted three longevity-associated loci: APOE, ZSCAN23, and MUC5B. We identified six genes whose burden of loss-of-function variants is significantly associated with reduced lifespan: TET2, ATM, BRCA2, CKMT1B, BRCA1 and ASXL1. Additionally, in eight genes, the burden of pathogenic missense variants was associated with reduced lifespan: DNMT3A, SF3B1, CHL1, TET2, PTEN, SOX21, TP53 and SRSF2. Most of these genes have previously been linked to oncogenic-related pathways and some are linked to and are known to harbor somatic variants that predispose to clonal hematopoiesis. A direction-agnostic (SKAT-O) approach additionally identified significant associations with C1orf52, TERT, IDH2, and RLIM, highlighting a link between telomerase function and longevity as well as identifying additional oncogenic genes.
Our results emphasize the importance of understanding genetic factors driving the most prevalent causes of mortality at a population level, highlighting the potential of early genetic testing to identify germline and somatic variants increasing one’s susceptibility to cancer and/or early death.
Associations of demographic, health, and risk-taking behaviors with tattooing in a population-based cross-sectional study of ~18,000 US adults
Authors: McCarty Rachel D , Trabert Britton , Millar Morgan M , Kriebel David , Grieshober Laurie , Barnard Mollie E , Collin Lindsay J , Lawson-Michod Katherine A , Gibson Brody , Gilreath Jeffrey A , Shami Paul J , Doherty Jennifer A 
Published: August 2024

Abstract

Background
Little is known about current characteristics of individuals with tattoos. We quantified the prevalence of tattooing and associations of demographic, health, and risk-behavior factors with tattooing.
Methods
We computed adjusted prevalence ratios (PR) of tattooing in a population-based analysis of > 18,000 Utah adults from the 2020–2021 Behavioral Risk Factor Surveillance System survey.
Results
The prevalence of tattooing was 26% among women and 22% among men, with the highest prevalence among women ages 25–29 (45%). Tattoo prevalence was higher among younger individuals, individuals with a lower education level, and those without religious affiliation. Tattoo prevalence was higher among indviduals with current tobacco (women: PR = 2.89 [95% confidence interval (CI): 2.60, 3.20]; men: 3.39 [2.98, 3.86]), e-cigarette (women: 2.44 [2.21, 2.69]; men: 2.64 [2.37, 2.94]), and heavy alcohol use (women: 2.16 [1.93, 2.43]; men: 1.89 [1.63, 2.19]). Tattoo prevalence was lower among individuals receiving a flu (women: 0.84 [0.76, 0.92]; men: 0.75 [0.67, 0.84]) or COVID-19 vaccine (women: 0.65 [0.54, 0.79]; men: 0.75 [0.61, 0.92]).
Conclusions
Several risk-taking behaviors were associated with tattooing. Tattoo studios/conventions may present opportunities for partnership with tobacco cessation, alcohol reduction, and vaccination public health initiatives.
The Role of Green Networks for Environmental Innovation in European Regions
Authors: Fabrizi Andrea , Fiorelli Cristiana , Meliciani Valentina 
Published: August 2024

Abstract

This paper investigates the role of green research networks in green innovation capabilities (proxied by green patents) in European regions. Our hypothesis is based on the idea that cross-border collaboration facilitates the diffusion of knowledge, thereby favouring the green innovation of the regions belonging to the network. We exploit information contained in the European Framework Programmes by looking at the role of intra and extra-regional collaborations and at the diversity of institutional partners. We find that both intra and extra regional collaborations matter for green innovation, although external knowledge appears to be more relevant. We also find a positive effect of both firms and universities and a non-linear effect of network heterogeneity. We discuss the implications of the results for green innovation policies.
Atomic short-range order in SiGeSn alloys
Authors: LIU Jifeng , Liu Shang , Chen Shunda , Jin Xiaochen , Bae Jin-Hee , Bikmukhametov Ilias , Jaeger David , Concepcion Omar , Covian Alejandra , Wang Xiaoxin , Cline Cory , Akey Austin , Vogl Lilian , Zhao Haochen , Zeng Yuping , Minor Andrew , Yu Shui-Qing , Buca Dan , Li Tianshu 
Published: August 2024

Abstract

Neighborhood at atomic scale is important for the properties of advanced alloys. The preference or avoidance between neighboring atomic species is known as chemical short-range order (SRO). While SRO in metallic medium/high entropy alloys has garnered substantial attention recently, understanding SRO in semiconductor alloys remains underdeveloped. Motivated by theoretically predicted SRO and its dramatic impact on band structure, here we perform statistical analyses of atom probe tomography data to quantify SRO in SixGe1-x-ySny alloys (x<12 at.%, y<16 at.%). Leveraging a side-by-side experiment-theory comparison at the same spatial scale enabled by machine-learning neuroevolution potentials of first-principles accuracy, we reveal, for the first time, a notable SRO favoring Si-Si 1st nearest neighbors even at dilute Si and Sn compositions. The SRO can be tuned by varying precursors, offering a new degree of freedom for band engineering beyond composition and strain, and enabling new phase-change materials based on SRO transitions for Si electronics/photonics.
A secreted Botrytis cinerea stage-specific effector promotes virulence by targeting the plant ROS-generating machinery
Authors: Sharon Amir , Bi kai , Wang Ziyao , Nie Xiaofei , Liang Yong , Zhu Wenjun 
Published: August 2024

Abstract

Necrotrophic plant pathogens are assumed to exploit the plant hypersensitive response (HR), but the molecular mechanism underlying this exploitation remains largely unclear. Here, we report the discovery and characterization of BcCELP1, an early infection-specific, cell death-inducing effector required for plant colonization by the phytopathogenic fungus Botrytis cinerea. We demonstrate that BcCELP1 is necessary during the initial stage of plant colonization, and that it interacts with the host scaffold protein NbRACK1, promoting NbRACK1’s interaction with the reduced nicotinamide adenine dinucleotide phosphate oxidase NbRBOHB, and thereby contributing to excessive ROS production. We further show that BcCELP1 is produced and specifically leveraged during plant invasion to facilitate the formation of necrotic tissue patches, which serve as foci for subsequent fungal spread. Misregulation of bccelp1 disrupts pathogen development, resulting in reduced disease symptoms. Collectively, these findings reveal an unsuspected sophisticated strategy employed by a necrotrophic pathogen, whereby a fungal effector activates the host ROS-generating machinery in a stage-specific manner to promote effective invasion.
The far-reaching distributional effects of global warming:
Evidence from half a century of climate and inequality data
Authors: Castells-Quintana David , McDermott Thomas 
Published: August 2024

Abstract

Climate change is already impacting several development outcomes, including economic growth, human health and mortality, agricultural productivity and even conflict. Moreover, the impact of climate change is expected to be unevenly distributed across locations and population groups. In particular, the worst effects of climate change are expected to be felt in low-income countries. Similarly, within countries, the most vulnerable to these effects are typically low-income regions and households. While the literature to date has provided evidence of the between-countries inequality-increasing effect of global warming, evidence for inequality within countries remains limited. In this paper, we empirically explore the connection between climate change and long-run distributional dynamics within countries. To do so, we first build a global panel dataset combining gridded data on climate variables with gridded population data, and country-level data on a range of inequality measures and development outcomes. We use these data to test climate effects on several dimensions of inequality, including the (interpersonal) distribution of income, using traditional Gini coefficients, indices of concentration of both income and wealth, proxies of inequality in the spatial distribution of economic activity within countries, and measures of inequality in life expectancy. Our evidence shows a clear positive and statistically significant relationship between higher temperatures and increases in different measures and dimensions of inequality. The role of higher temperatures is robust to a wide range of controls, different specifications and estimation techniques. We complement our country-level analysis with an exploratory analysis at the subnational level for selected countries (US, Russia and Spain).
Prediksi Jumlah Calon Siswa Baru Menggunakan Metode Double Exponential Smoothing Brown (Studi Kasus: SMK Ma’arif NU 1 Purwokerto Tahun Pelajaran 2024/2025)
Authors: Nurohmah Siti , Kartika Dwiani Listya , Muhassanah Nuraini , Yuniarti Dwi Ariani Finda 
Published: August 2024

The number of new students registering at SMK Ma'arif NU 1 Purwokerto from 2010 to 2023 has increased and decreased. This fluctuating pattern is a problem faced in determining strategies to attract new students to register. Large fluctuations in student numbers can cause instability in school revenues, which affects all operational aspects and will impact the school's reputation in the eyes of the community and prospective students. In this regard, it is necessary to take action, namely forecasting the number of new students registering for the 2024/2025 academic year. The aim of this research is to determine the prediction of the number of prospective new students at SMK Ma'arif NU 1 Purwokerto using theDouble Exponential Smoothing Brown in the 2024/2025 academic year. From the research results, it was obtained that the number of new students in the 2024/2025 academic year was based on overall data on students who registered with the best α parameter α = 0.2 with a value ofMAD = 6,02, MSE = 68,37, andMAP= 20.23%, namely 42 students. The forecast for the number of new students registering at SMK Ma'arif NU 1 Purwokerto based on overall data from the school has increased from the previous year. Value resultsMAPshows that the forecasting that has been carried out falls into the category of adequate forecasting method capabilities so that it can be used to predict the number of new students enrolling at SMK Ma'arif NU 1 Purwoketo and the predicted value for the following year can be known.Keywords: predictions, forecasting, new students, Double Exponential Smoothing Brown
Self-attention transformer model for pan evaporation prediction: a case study in Australia
Authors: Abed Mustafa , Imteaz Monzur Alam , Huang Yuk Feng , Ahmed Ali Najah 
Published: August 2024

ABSTRACT
In drought-prone regions like Australia, accurately assessing evaporation rates is essential for effectively managing and maximising the use of precious water resources and reservoirs. Current estimates show that evaporation reduces Australia's open water lake capacity by about 40% annually. With climate change, this water loss is expected to become an even greater concern. This study investigates a transformer-based neural network (TNN) to estimate monthly evaporation in three Australian locations. The models were trained and tested using monthly weather data spanning from 2009 to 2022. Input parameters were chosen based on Pearson's correlation coefficient values to identify the most impactful combinations. The developed TNN model was compared with two widely used empirical methods, namely Thornthwaite and Stephens and Stewart. The TNN model's impressive accuracy in evaporation prediction, attributed to its unique self-attention mechanism, suggests its promising potential for future use in evaporation forecasting. Additionally, the study revealed an intriguing result: Despite using the same input datasets, the TNN model surpassed traditional methods, achieving an average improvement of 18% in prediction accuracy. The TNN prediction model accurately predicts water loss (average R² = 0.970), supports irrigation management and agricultural planning and offers financial benefits to farming and related industries.
Impact of projected climate variability on agricultural water demand of key crops in drought-prone central India region
Authors: Vishwakarma Ankur , Choudhary Mahendra Kumar , Chauhan Mrityunjay Singh 
Published: August 2024

ABSTRACT

Water scarcity predominantly affects agriculture production. It is mandatory to save future water to prevent its shortage due to variations in climate. Variation in climate is a significant factor responsible for frequent droughts over the Bundelkhand region in central India. It is necessary to obtain early warning studies in this region to manage and arrange future agricultural water. Out of best Regional Climate Models (RCMs) under the Coordinated Regional Downscaling Experiment (CORDEX) and their driving Coupled Model Intercomparison Project Phase 5 (CMIP5), General Circulation Models (GCMs) for India, the most effective model has been found based on the observed multiscale data for the region. The daily projected data (2021–2100) of best GCM, Earth System Model, ESM-2M have been used to evaluate the future water requirements for major rabi and hot weather crops grown in the region. The climate change effect is seen in the majority, especially in the upper Bundelkhand part. Most of the crops will need more water than the present condition, especially from 2071 to 2100. The findings will also help researchers and policymakers to utilize the future projected data to propose suitable water management strategies for agriculture.
Assessing the influence of land use/land cover dynamics and climate change on water resources in Upper Blue Nile, Ethiopia
Authors: Tikuye Birhan Getachew , Ray Ram L. , Gebeyehu Kindie , Teshome Menberu 
Published: August 2024

ABSTRACT

This study evaluates the impact of climate and land use changes on Lake Tana Basin's hydrology, using datasets on land use, weather patterns, topography, soil characteristics, and discharge. Future climate data were obtained from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase Five (CMIP5) and generated using the Weather Generator (LARS-WG) tool from the Long Ashton Research Station with five distinct GCMs. Land use changes were projected using the Markov chain model based on cellular automata (CA). The Soil and Water Assessment Tool (SWAT) model was used to assess changes in hydrological elements between reference and future periods, with calibration and validation ensured by the Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT). Projections indicate a 4.9 °C increase in ensemble mean annual temperature and a 16% rise in precipitation by the end of the 21st century under Representative Concentration Pathway (RCP) 8.5. Additionally, average annual hydrological components, including water yield, soil water, percolation, lateral flow, runoff, and actual and potential evapotranspiration, are expected to increase due to combined climate and land use changes. Therefore, it is crucial to fully understand these cumulative impacts before formulating and implementing water resource management strategies in the basin.