bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanism study of lncRNA RMRP regulating esophageal squamous cell carcinoma through miR-580-3p/ATP13A3 axis
Authors: Tan ZiRui , Luan ShengJie , Wang XiaoPeng , Jiao WenPeng , Jiang Pu 
Published: May 2024

Abstract
Objective
It is well-known that lncRNAs regulate energy metabolism in tumors. This study focused on the action of RMRP on esophageal squamous cell carcinoma (ESCC) cell proliferation, apoptosis, and glycolysis.

Methods
In the resected ESCC tissues and adjacent tissues from patients, RMRP/miR-580-3p/ATP13A3 expressions were evaluated. ESCC cell proliferation rates and apoptotic rates were measured by CCK-8 and flow cytometry, respectively. Apoptosis related markers were examined by Western blot. Moreover, glucose uptake, lactic acid, and ATP were measured by commercial kits, whereas HK2 and PKM2 were evaluated by Western blot to study ESCC cell glycolysis. Finally, the editing program of RMRP/miR-580-3p/ATP13A3 was translated by luciferase reporter assay and RIP analysis.

Results
RMRP and ATP13A3 were induced, while miR-580-3p was reduced in their expression in ESCC tissues. Silencing RMRP reduced proliferation, glycolysis, and anti-apoptosis ability of ESCC cells. RMRP sequestered miR-580-3p to target ATP13A3. Silenced ATP13A3 or overexpressed miR-580-3p rescued overexpressed RMRP-mediated promotion of proliferation, glycolysis, and anti-apoptosis of ESCC cells.

Conclusion
RMRP accelerates ESCC progression through the miR-580-3p/ATP13A3 axis, renewing a reference for lncRNA-based therapies for tumors.
Fe-Incorporated Metal-Organic Cobalt Hydroxide Toward Efficient Oxygen Evolution Reaction
Authors: Jiang Tao , Yao Yuechao , Wu Feiyan , Aziz Iram , Zhang Wenjing 
Published: May 2024

AbstractMetal-organic cobalt hydroxide emerges as a cost-effective electrocatalyst for the oxygen evolution reaction (OER) in energy conversion. However, the limited active sites and poor conductivity hinder their large-scale application. This study employed salicylate as a bridging ligand to synthesize iron-incorporated metal-organic cobalt hydroxide. The influence of Fe intercalation on Co(OH)(Hsal) (where Hsal denotes o-HOC6H4COO−) was investigated using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). Fe0.2Co0.8(OH)(Hsal) demonstrates remarkable electrocatalytic activity, displaying an OER overpotential of 298 mV at 10 mA cm−2 and a Tafel slope of 57.46 mV dec−1. This enhancement can be attributed to improved charge transfer kinetics and increased active sites. This work highlights the crucial role of Fe in improving the efficiency of Co-based oxygen-evolving catalysts (OECs) and its potential for boosting efficient hydrogen generation in alkaline environments.
Graphical Abstract
Coordination in social learning: expanding the narrative on the evolution of social norms
Authors: Müller Basil 
Published: May 2024

AbstractA shared narrative in the literature on the evolution of cooperation maintains that social learning evolves early to allow for the transmission of cumulative culture. Social norms, whilst present at the outset, only rise to prominence later on, mainly to stabilise cooperation against the threat of defection. In contrast, I argue that once we consider insights from social epistemology, an expansion of this narrative presents itself: An interesting kind of social norm — an epistemic coordination norm — was operative in early and important instances of specialised social learning. I show how there’s a need for such norms in two key social learning strategies and explain how this need is constituted. In assessor-teaching (e.g. Castro et al., 2019b, 2021), epistemic coordination norms allow agents to coordinate around the content of social learning, i.e., what is to be known and how this is to be done. These norms also allow agents to coordinate around the form of cultural learning in what’s sometimes called strategic social learning (Laland, 2004; Hoppitt & Laland, 2013; Heyes, 2018, Chap. 5) and elsewhere. Broadly speaking, this concerns how cultural learning is organised within the social group. The upshot is that the evolution of social learning and social norms are intertwined in important and underappreciated ways from early on. The above matters as it informs our views about the evolution of social norms more generally. Truly social norms emerged to coordinate a plurality of complex behaviours and interactions, amongst them specialised social learning. I substantiate this view by contrasting it with Jonathan Birch’s views on the evolution of norms. What results is a general but cohesive narrative on the early evolution of social norms.
Griefbots, Deadbots, Postmortem Avatars: on Responsible Applications of Generative AI in the Digital Afterlife Industry
Authors: Hollanek Tomasz , Nowaczyk-Basińska Katarzyna 
Published: May 2024

AbstractTo analyze potential negative consequences of adopting generative AI solutions in the digital afterlife industry (DAI), in this paper we present three speculative design scenarios for AI-enabled simulation of the deceased. We highlight the perspectives of the data donor, data recipient, and service interactant – terms we employ to denote those whose data is used to create ‘deadbots,’ those in possession of the donor’s data after their death, and those who are meant to interact with the end product. We draw on the scenarios to map out several key ethical concerns posed by ‘re-creation services’ and to put forward recommendations on the ethical development of AI systems in this specific area of application. The recommendations, targeted at providers of AI-enabled re-creation services, include suggestions for developing sensitive procedures for retiring deadbots, ensuring meaningful transparency, restricting access to such services to adult users only, and adhering to the principle of mutual consent of both data donors and service interactants. While we suggest practical solutions to the socio-ethical challenges posed by the emergence of re-creation services, we also emphasize the importance of ongoing interdisciplinary research at the intersection of the ethics of AI and the ethics of the DAI.
Psychometric properties of the Oxford Happiness Questionnaire Short Form (OHQ-SF) in a Greek student sample
Authors: Grigoriadou Evangelia , Kolias Pavlos , Theocharidou Melissa , Gkioka Mara 
Published: May 2024

Abstract
Background
The purpose of the current study was to adapt and explore the psychometric properties of the Oxford Happiness Questionnaire Short Form (OHQ-SF) in a Greek student sample.

Aim
This quantitative cross-sectional study was applied in order to translate and validate the Oxford Happiness Questionnaire Short Form (OHQ-SF) into Greek and to assess the psychometric properties.

Method
The English version of OHQ-SF was translated into Greek using the forward and backward translation. The sample was consisted of 88 adult students from the Public Educational Training Institution in Thessaloniki. Two self-report measures the Greek version of OHQ-SF and the Greek version of the Life Orientation Test Revised (LOT-R—to check the construct validity) were completed twice, for test and retest assessment, in full anonymity and confidentiality.

Statistical analysis
The psychometric properties of OHQ-SF/GR, namely the internal–external reliability and construct validity, were assessed, and the expected unidimensional structure was tested with Confirmatory Factor Analysis (CFA).

Results and discussion
The Greek version of OHQ-SF (OHQ-SF/GR), for both test and retest, has adequate internal reliability, satisfactory structural validity, and adequate construct validity. The CFA indicated the unidimensional structure of the OHQ-SF/GR, and the fit indexes displayed good fit with the data. One item was removed due to poor correlation with the latent factor of happiness. The current study reveals that the final seven-item OHQ-SF/GR has very satisfactory psychometric properties being useful instrument to measure happiness levels in Greek adult students and is a valid tool that can be utilised in research field.
Water extraction in aero gas turbines for contrail mitigation
Authors: Gao X. , Isoldi A. , Nalianda D. , Nikolaidis T. 
Published: May 2024

AbstractWater vapour and particles in aero engine exhaust can give rise to condensation trails (contrails) in the wake of aircrafts, and recent studies suggest that persistent contrails and contrail cirrus account for circa 50% of the total aviation-derived radiative forcing (RF). The Schmidt-Appleman criterion is widely used to qualitatively predict the formation of contrails. The criterion indicates that the formation of contrails is affected by both aero engine exhaust and ambient air conditions and can therefore provide the theoretical basis to devise contrail mitigation strategies and further allows quantitative assessment of these strategies. This work focuses on water extraction from the aircraft engine exhaust for contrail mitigation. The fuel water emission index (
${\rm{E}}{{\rm{I}}_{{{\rm{H}}_2}{\rm{O}}}}$
) is one of the key factors that determines whether persistent contrails form or not. It indicates the amount of water produced for every kg of fuel burnt. Research has indicated that water extraction from the exhaust of the aero engine has been considered for Nitrogen oxides (NOx) reduction, but not for contrail mitigation. Assuming that water extraction is indeed possible, the emphasis of this work will therefore be on understanding how much water is needed to be extracted for contrail mitigation depending on the altitude and the relative humidity (RH), with the aim to carry out a meaningful study on the mitigation of persistent contrails and contrail cirrus to enable a fast and considerable reduction in aviation-derived RF.
$\beta$
-wave-based exploration of sensitive EEG features and classification of situation awareness
Authors: Feng C. , Liu S. , Wanyan X. , Dang Y. , Wang Z. , Qian C. 
Published: May 2024

AbstractThe purpose of this study was to explore the electroencephalogram (EEG) features sensitive to situation awareness (SA) and then classify SA levels. Forty-eight participants were recruited to complete an SA standard test based on the multi-attribute task battery (MATB) II, and the corresponding EEG data and situation awareness global assessment technology (SAGAT) scores were recorded. The population with the top 25% of SAGAT scores was selected as the high-SA level (HSL) group, and the bottom 25% was the low-SA level (LSL) group. The results showed that (1) for the relative power of
$\beta$
1 (16–20Hz),
$\beta$
2 (20–24Hz) and
$\beta$
3 (24–30Hz), repeated measures analysis of variance (ANOVA) in three brain regions (Central Central-Parietal, and Parietal) × three brain lateralities (left, midline, and right) × two SA groups (HSL and LSL) showed a significant main effect for SA groups; post hoc comparisons revealed that compared with LSL, the above features of HSL were higher. (2) for most ratio features associated with
$\beta$
1 ∼
$\beta$
3, ANOVA also revealed a main effect for SA groups. (3) EEG features sensitive to SA were selected to classify SA levels with small-sample data based on the general supervised machine learning classifiers. Five-fold cross-validation results showed that among the models with easy interpretability, logistic regression (LR) and decision tree (DT) presented the highest accuracy (both 92%), while among the models with hard interpretability, the accuracy of random forest (RF) was 88.8%, followed by an artificial neural network (ANN) of 84%. The above results suggested that (1) the relative power of
$\beta$
1 ∼
$\beta$
3 and their associated ratios were sensitive to changes in SA levels; (2) the general supervised machine learning models all exhibited good accuracy (greater than 75%); and (3) furthermore, LR and DT are recommended by combining the interpretability and accuracy of the models.
Development and initial psychometric properties of the Research Complexity Index
Authors: Norful Allison A. , Capili Bernadette , Kovner Christine , Jarrín Olga F. , Viera Laura , McIntosh Scott , Attia Jacqueline , Adams Bridget , Swartz Kitt , Brown Ashley , Barton-Burke Margaret 
Published: May 2024

Abstract

Objective:
Research study complexity refers to variables that contribute to the difficulty of a clinical trial or study. This includes variables such as intervention type, design, sample, and data management. High complexity often requires more resources, advanced planning, and specialized expertise to execute studies effectively. However, there are limited instruments that scale study complexity across research designs. The purpose of this study was to develop and establish initial psychometric properties of an instrument that scales research study complexity.

Methods:
Technical and grammatical principles were followed to produce clear, concise items using language familiar to researchers. Items underwent face, content, and cognitive validity testing through quantitative surveys and qualitative interviews. Content validity indices were calculated, and iterative scale revision was performed. The instrument underwent pilot testing using 2 exemplar protocols, asking participants (n = 31) to score 25 items (e.g., study arms, data collection procedures).

Results:
The instrument (Research Complexity Index) demonstrated face, content, and cognitive validity. Item mean and standard deviation ranged from 1.0 to 2.75 (Protocol 1) and 1.31 to 2.86 (Protocol 2). Corrected item-total correlations ranged from .030 to .618. Eight elements appear to be under correlated to other elements. Cronbach’s alpha was 0.586 (Protocol 1) and 0.764 (Protocol 2). Inter-rater reliability was fair (kappa = 0.338).

Conclusion:
Initial pilot testing demonstrates face, content, and cognitive validity, moderate internal consistency reliability and fair inter-rater reliability. Further refinement of the instrument may increase reliability thus providing a comprehensive method to assess study complexity and related resource quantification (e.g., staffing requirements).
Opening a conversation on responsible environmental data science in the age of large language models
Authors: Oliver Ruth Y. , Chapman Melissa , Emery Nathan , Gillespie Lauren , Gownaris Natasha , Leiker Sophia , Nisi Anna C. , Ayers David , Breckheimer Ian , Blondin Hannah , Hoffman Ava , Pagniello Camille M.L.S. , Raisle Megan , Zimmerman Naupaka 
Published: May 2024

Abstract
The general public and scientific community alike are abuzz over the release of ChatGPT and GPT-4. Among many concerns being raised about the emergence and widespread use of tools based on large language models (LLMs) is the potential for them to propagate biases and inequities. We hope to open a conversation within the environmental data science community to encourage the circumspect and responsible use of LLMs. Here, we pose a series of questions aimed at fostering discussion and initiating a larger dialogue. To improve literacy on these tools, we provide background information on the LLMs that underpin tools like ChatGPT. We identify key areas in research and teaching in environmental data science where these tools may be applied, and discuss limitations to their use and points of concern. We also discuss ethical considerations surrounding the use of LLMs to ensure that as environmental data scientists, researchers, and instructors, we can make well-considered and informed choices about engagement with these tools. Our goal is to spark forward-looking discussion and research on how as a community we can responsibly integrate generative AI technologies into our work.
Brightness enhancement on a narrow-linewidth fiber Bragg grating-based master oscillator power amplification fiber laser
Authors: Tian Xin , Rao Binyu , Wang Meng , Xi Xiaoming , Li Zhixian , Chen Zilun , Xiao Hu , Ma Pengfei , Wang Zefeng 
Published: May 2024

Abstract
In this paper, we have experimentally demonstrated a high-power and high-brightness narrow-linewidth fiber amplifier seeded by an optimized fiber oscillator. In order to improve the temporal stability, the fiber oscillator consists of a composite fiber Bragg grating-based cavity with an external feedback structure. By optimizing the forward and backward pumping ratio, the nonlinear effects and stimulated Raman scattering-induced mode distortion of the fiber amplifier are suppressed comprehensively, accompanied with the simultaneous improvement of beam quality and output power. The laser brightness is enhanced further by raising the threshold of transverse mode instability by approximately 1.0 kW by coiling the gain fiber with a novel curvature shape. Finally, a 6 kW narrow-linewidth laser is achieved with beam quality (M2) of approximately 1.4. The laser brightness doubled compared to the results before optimization. To the best of our knowledge, it is the highest brightness narrow-linewidth fiber laser based on a one-stage master oscillator power amplification structure.
Dynamics of English gratitude expression: a corpus-assisted analysis of UK government COVID-19 briefings
Authors: Wei Jilan , Murphy M. Lynne 
Published: May 2024

AbstractWith a focus on politicians’ and medical experts’ gratitude expressions in UK government COVID-19 briefings, this research describes how perspective and intensity were modulated in expressing gratitude to realise different pragmatic intentions. This corpus-assisted analysis finds that retrospective or prospective gratitude expression was adopted by the two British elite groups to build solidarity (encouraging) and/or make requests (directing) for protecting public health. Gratitude of varying intensities was expressed (e.g. by highlighting metaphorical dimensions such as WIDTH and DEPTH) to correspond to the importance of a benefit (judged by how much the given benefit matches the receiver’s needs and preferences) and/or to implicitly display the evaluation of the benefactor’s responsibility and efforts. We tentatively formulate a dynamic model of gratitude expression in public discourse and shed light on the metaphorical conceptualisation of English gratitude expression and the power of gratitude expression in boosting social cohesion and directing social actions in a discourse of crisis.
First insights into the spatio-temporal ecology of sympatric large carnivores in Niokolo-Koba National Park, Senegal
Authors: Horion Robin , Woodgate Zoe , Drouilly Marine 
Published: May 2024

AbstractLarge carnivores play a crucial role in their native ecosystems, but their populations are rapidly declining across the African continent. West Africa is no exception, with large protected areas often forming the last strongholds for these species. Little is known about the population status and ecology of large carnivores in the region, hampering the design and implementation of effective conservation strategies. We conducted a camera-trap survey during the dry season in Niokolo-Koba National Park, the largest terrestrial protected area in Senegal and the second largest in West Africa, to investigate the spatio-temporal ecology of the four large carnivores inhabiting the Park: the spotted hyaena Crocuta crocuta, leopard Panthera pardus, West African lion Panthera leo leo and African wild dog Lycaon pictus. Spotted hyaenas and leopards had the widest spatial distribution and highest probability of site use. Spotted hyaena site use was positively associated with leopard relative abundance index and negatively associated with normalized difference vegetation index, whereas only distance to the nearest road influenced leopard site use. Distance to the Gambian River was the most important covariate positively affecting site use by lions. African wild dog site use was negatively associated with the relative abundance indices of lions and leopards. Lions, spotted hyaenas and leopards showed strong overlap in their activity patterns. By providing new information on the ecology of large carnivores in West Africa, including where they range and which habitats are critical for their survival, our study will facilitate conservation planning. Our findings lay the foundations for future research to conserve these threatened species in West Africa effectively and to guide ranger patrol efforts, which are key for their long-term survival.
Uncovering novel drug targets for bipolar disorder: a Mendelian randomization analysis of brain, cerebrospinal fluid, and plasma proteomes
Authors: Jia Tingting , Liu Tiancheng , Hu Shiyi , Li Yongjun , Chen Peixi , Qin Fengqin , He Yongji , Han Feng , Zhang Chengcheng 
Published: May 2024

AbstractBackgroundThere is a clear demand for innovative therapeutics for bipolar disorder (BD).MethodsWe integrated the largest BD genome-wide association study (GWAS) dataset (NCase = 41 917, NControl = 371 549) with protein quantitative trait loci from brain, cerebrospinal fluid, and plasma. Using a range of integrative analyses, including Mendelian randomization (MR), Steiger filter analysis, Bayesian colocalization, and phenome-wide MR analysis, we prioritized novel drug targets for BD. Additionally, we incorporated data from the UK Biobank (NCase = 1064, NControl = 365 476) and the FinnGen study (NCase = 7006, NControl = 329 192) for robust biological validation.ResultsThrough MR analysis, we found that in the brain, downregulation of DNM3, MCTP1, ABCB8 and elevation of DFNA5 and PDF were risk factors for BD. In cerebrospinal fluid, increased BD risk was associated with increased levels of FRZB, AGRP, and IL36A and decreased CTSF and LRP8. Plasma analysis revealed that decreased LMAN2L, CX3CL1, PI3, NCAM1, and TIMP4 correlated with increased BD risk, but ITIH1 did not. All these proteins passed Steiger filtering, and Bayesian colocalization confirmed that 12 proteins were colocalized with BD. Phenome-wide MR analysis revealed no significant side effects for potential drug targets, except for LRP8. External validation further underscored the concordance between the primary and validation cohorts, confirming MCTP1, DNM3, PDF, CTSF, AGRP, FRZB, LMAN2L, NCAM1, and TIMP4 are intriguing targets for BD.ConclusionsOur study identified druggable proteins for BD, including MCTP1, DNM3, and PDF in the brain; CTSF, AGRP, and FRZB in cerebrospinal fluid; and LMAN2L, NCAM1, and TIMP4 in plasma, delineating promising avenues to development of novel therapies.
Early-treatment cerebral blood flow change as a predictive biomarker of antidepressant treatment response: evidence from the EMBARC clinical trial
Authors: Dang Yi , Lu Bin , Vanderwal Tamara , Castellanos Francisco Xavier , Yan Chao-Gan 
Published: May 2024

AbstractBackgroundMajor depressive disorder (MDD) is one of the most prevalent and disabling illnesses worldwide. Treatment of MDD typically relies on trial-and-error to find an effective approach. Identifying early response-related biomarkers that predict response to antidepressants would help clinicians to decide, as early as possible, whether a particular treatment might be suitable for a given patient.MethodsData were from the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial. A whole-brain, voxel-wise, mixed-effects model was applied to identify early-treatment cerebral blood flow (CBF) changes as biomarkers of treatment response. We examined changes in CBF measured with arterial spin labeling 1-week after initiating double-masked sertraline/placebo. We tested whether these early 1-week scans could be used to predict response observed after 8-weeks of treatment.ResultsResponse to 8-week placebo treatment was associated with increased cerebral perfusion in temporal cortex and reduced cerebral perfusion in postcentral region captured at 1-week of treatment. Additionally, CBF response in these brain regions was significantly correlated with improvement in Hamilton Depression Rating Scale score in the placebo group. No significant associations were found for selective serotonin reuptake inhibitor treatment.ConclusionsWe conclude that early CBF responses to placebo administration in multiple brain regions represent candidate neural biomarkers of longer-term antidepressant effects.