bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanisms of diabetic cardiomyopathy: Focus on inflammation
Authors: Bellemare Myriam , Bourcier Liane , Iglesies‐Grau Josep , Boulet Jacinthe , O'Meara Eileen , Bouabdallaoui Nadia 
Published: February 2025

AbstractPurpose of ReviewType 2 diabetes (T2D) significantly increases the risk of heart failure (HF), either through the progression of coronary artery disease (CAD) or through direct myocardial alterations, termed diabetic cardiomyopathy. This review examines key pathophysiological mechanisms underlying diabetic cardiomyopathy, focusing on the role of inflammation. It also addresses diagnostic and therapeutic approaches to mitigate myocardial damage in T2D.Recent FindingsChronic low‐grade inflammation is considered as a major contributor to diabetic cardiomyopathy. T2D‐related factors, including hyperglycemia and insulin resistance, activate inflammatory pathways that worsen myocardial dysfunction. Despite advances in understanding these mechanisms, no therapies specifically targeting the cardiac changes in T2D have been identified.SummaryWhile significant advances have been made in elucidating the inflammatory mechanisms contributing to diabetic cardiomyopathy, therapeutic advancements remain limited, potentially due to an incomplete understanding of regulatory pathways. A comprehensive investigation into the specific roles of immune cells and inflammatory mediators in diabetic cardiomyopathy is essential for identifying novel therapeutic targets. Expanding our knowledge of these molecular mechanisms has the potential to facilitate the development of innovative therapeutic strategies, thereby improving clinical outcomes in patients with T2D.
Characterizing insulin dosing behaviour and glycaemic excursions: Development of metrics using connected insulin pen and continuous glucose monitoring
Authors: Wolpert Howard , Rodbard David , Xue Jie , Johnson Jennal , Dassau Eyal 
Published: February 2025

AbstractAimsConnected insulin pens (CIPs) provide insulin dosing data that can be leveraged to drive improvements in glycaemic control. To realize this potential in routine care, insulin data need to be distilled into actionable insights for clinicians. We describe two algorithms for detecting glucose excursions using continuous glucose monitoring (CGM) data and then link excursions to CIP data to derive “insulin metrics” characterizing suboptimal bolus dosing practices.Materials and MethodsThis post hoc analysis used CGM and CIP data from a 12‐week observational study (clinicaltrials.gov: NCT03368807) of 64 adults with type 1 or type 2 diabetes receiving multiple daily injection insulin therapy and glycated haemoglobin ≥8%. Two updated algorithms were applied to analyse glucose excursions associated with pre‐meal boluses, missed bolus doses (MBDs), delayed boluses and correction boluses.ResultsGlycaemic metrics obtained using both algorithms were similar. Time in range (%TIR) was lower, and time above range (%TAR) and glycaemic variability (%GV) were higher, on days with MBDs. Compared with pre‐meal boluses, delayed and correction boluses were followed by glucose excursions with larger change in glucose, longer duration with glucose >180 mg/dL, lower post‐excursion %TIR and higher post‐excursion %TAR; excursions following MBDs showed lower %TIR, higher %TAR and lower percent recovery. Glucose excursions were larger and longer when CGM was masked than when unmasked.ConclusionsThis analysis demonstrates “insulin metrics”—characterizations of insulin dosing behaviour derived from integrated CGM and CIP data—and provides a foundation for future work that will expand the understanding of an individual's insulin self‐administration practices and improve clinical decision‐making.
Three‐Objects‐Three‐Places Episodic Memory Test to Screen Mild Cognitive Impairment and Mild Dementia: Validation in a Memory Clinic Population
Authors: Ribaldi Federica , Krug Sophie , Altomare Daniele , Garibotto Valentina , Scheffler Max , Mendes Augusto J. , Lathuiliere Aurelien , Assal Frederic , Fernandez Aldara Vazquez , Cappa Stefano F. , Chicherio Christian , Frisoni Giovanni B. 
Published: February 2025

ABSTRACTBackgroundThe Three‐Objects‐Three‐Places (3O3P) test is a 5‐min screen for episodic memory impairment due to Alzheimer's disease, known for its briefness and easy administration, culture‐ and language‐free nature, and the absence of specific equipment. However, no studies have validated its potential in memory clinic cohorts. The aim of this study was to test its convergent, discriminant, and known‐group validities and to define thresholds for its clinical use.MethodsWe included 2062 cognitively unimpaired (CU), mild cognitive impairment (MCI) and dementia patients from the Geneva Memory Center cohort who underwent the 3O3P test in the context of clinical practice. Convergent and discriminant validities were assessed using an exploratory factor analysis. The known‐group validity was assessed in CU vs. MCI and dementia using the area under the curve (AUC). 3O3P test scores vs. amyloid and tau positivity, neurodegeneration, and cognition (ATNC) were assessed using the Kruskal‐Wallis test. The 3O3P test cut‐offs were calculated using sensitivity, specificity, PPV, NPV, and accuracy.ResultsMean age was 72 years (SD = 11), 60% were female, mean education was 13 years (SD = 4), and mean MMSE was 25 (SD = 5). The 3O3P and Delayed Total Recall tests loaded strongly on the “memory” factor and weakly on “non‐memory” factors. The 3O3P test can discriminate CU vs. MCI (AUC = 0.71) and dementia (AUC = 0.92). Higher 3O3P scores were associated with lower prevalence of ATNC (p < 0.001). A 3O3P value of 7 can detect MCI and dementia patients.ConclusionsThe 3O3P test has demonstrated good convergent, discriminant, and known‐group validity in a large memory clinic population.
Forget Nature, Forget Humans: Redefining Our Approach toward Biodiversity
Authors: MORIER MARC‐ANTOINE 
Published: February 2025

PechaKucha Presentation AbstractWhile human‐centred approaches have enabled considerable progress to be made in the design of innovative and socially responsible solutions, they fail to take account of a decisive factor in maintaining our societies. Medicine, food, drinking water and breathable air… Biodiversity underpins many of the “services” that “nature” provides free of charge, and on which we are largely dependent. With biodiversity collapsing, how is it that we take so little account of it in our work? So how can we include living non‐humans in our investigations and creations?
How to Avoid Path Dependency: Learnings from Neuroscience, Physics and Organizational Theory
Authors: MAURY CYRIL 
Published: February 2025

PechaKucha Presentation AbstractIn 1814, the polymath Pierre Simon Laplace posited that “We may regard the present state of the universe as the effect of its past and the cause of its future”. This presentation will examine this core idea – the fact that what will happen next is determined by what happened before – from different vantage points: neuroscience (Hebbian plasticity, Canalization), economic theory (Bayes's Theorem) and organisational theory. How and how much does legacy narrow down what is possible next? How can we, at the individual and collective levels, carve out the space for alternative, unexpected futures?
“If Today's Problems Are So Urgent, Why Are We So Stuck?”
Authors: KINNEY MEG 
Published: February 2025

PechaKucha Presentation AbstractWe are surrounded by messages urging us to see the suffering, injustice, and corruption of both the natural and built world. But today, people seem to be gripped by passive despair. Why is that? Perhaps we are weighted by a loss of optimism. This presentation questions if optimism is misunderstood and if, as ethnographers, we are getting in our own way and underestimating it as a powerful tool of social transformation. Optimism requires us to examine our own emotional intelligence, capacity for change, and belief in our own human potential.
Surgical management of a bilateral mandibular fracture in a foal using LCPs as external fixator
Authors: Dias A. B. M. , Gustafsson K. , Kieffer P. J. 
Published: February 2025

SummaryThis report describes the use of locking compression plates (LCP) as external skeletal fixators (ESF‐LCP) in the surgical repair of a bilateral open mandibular fracture in a foal. A 3‐week‐old 90‐kg Swedish Warmblood colt presented with reluctance to nurse, bilateral mandibular swelling and haemorrhagic discharge from the mouth. Clinical examination and radiographs revealed a fracture of both mandibles, with complete fracture anatomy defined by computed tomography (CT). The right mandible had a complete, displaced, open fracture between the deciduous premolars Triadan 806 and 807. The left mandible had a minimally displaced, comminuted fracture in the caudal aspect of the interdental diastema (705–706). Both mandibles were surgically repaired using narrow 4.5 mm LCP plates as external skeletal fixators (ESF‐LCP) under general anaesthesia. The ESF‐LCPs were removed 36 days post‐operatively after radiographic healing was observed. Three months post‐operatively repeat radiographs were performed showing no abnormalities of the mandibular or dental function. At 3 years of age, a routine dental examination was performed that showed normal occlusion and function of the mandible with only a mild external callus. The use of LCP plates as ESF‐LCP in a bilateral mandibular fracture in a neonatal foal resulted in an excellent outcome and complete fracture healing with minimal complications.
Modelling Context and Content Features for Fake News Detection
Authors: Phan Huyen Trang , Hwang Dosam , Seo Yeong‐Seok , Nguyen Ngoc Thanh 
Published: February 2025

ABSTRACTWith the emergence and rapid development of social networks, an increasing amount of news has been spreading. In addition to the benefits of factual information, there are always risks associated with the dissemination of fake news and preventing the spread of fake news has been a concern for researchers. Many methods have been proposed to detect fake news, but they do not fully extract important information related to news content and context, and rarely consider modelling the simultaneous exploitation of the news context and content in fake news detection. This study proposes a method to improve the performance of fake news detection by modelling features related to news context and content. First, we combine contextualised embeddings (e.g., BERT) and dependency‐based embeddings (e.g., dependency‐based GCN) to enhance the performance of the content representations of news and reviews posting them. Second, we combine all available review texts related to news belonging to the user. Third, we explore all the reviews that other users had posted about current news by clearly creating review representations posted by the same user about the same news. This leads the model to quickly memorise all reviews related to news from one user. Finally, we model the news content features and the modelled news context features to enhance the richness of the news feature representations. Experimental results on the PolitiFact and GossipCop datasets show improvement to the state‐of‐the‐art method of more than three percentage points in the best case.
Feature Identification Using Hypotheses of Relevance and a 2D‐Cascade of SEQENS Ensembles
Authors: Arlandis Joaquim , Llobet Rafael , Navarro Cerdán J. Ramón , Arnal Laura , Signol François , Perez‐Cortes Juan‐Carlos 
Published: February 2025

ABSTRACTSEQENS is an ensemble method aimed at feature identification that has demonstrated strong performance in identifying relevant genes in high‐dimensional spaces, across different synthetic tasks. In this paper, we first introduce the differences between feature importance, feature selection (FS) and feature identification concepts. Following this, we present a framework based on SEQENS covering the following contributions: (1) computing the hypergeometric p‐value of the features of a SEQENS output ranking in order to be able to establish a threshold between relevant and non‐relevant features; (2) extending SEQENS by introducing the use of preselected features as hypotheses of relevance in the sequential FS, which may help to attract other features that might exhibit weak correlation with the target on their own, but gain relevance when combined with the preselected ones and; (3) designing an automated process based on a 2D‐cascade of SEQENS ensembles to obtain a purged feature set, or PFS, that is, having as many relevant features, and as few non‐relevant, as possible. The framework presented, named pc–SEQENS, integrates the former techniques so that the PFS is used as a hypothesis of relevance in a SEQENS ensemble. Performance is analysed in a gene expression identification task using the E‐MTAB‐3732 public database and synthetic targets. pc–SEQENS is compared to other state‐of‐the‐art methods, including SEQENS to check the effect of using hypotheses of relevance. On average, the proposed framework identifies better the relevant genes, especially in unfavourable sample‐to‐dimension rates, and exhibits a stronger stability.
Machine Learning‐Driven Passenger Demand Forecasting for Autonomous Taxi Transportation Systems in Smart Cities
Authors: Munawar Adeel , Piantanakulchai Mongkut 
Published: February 2025

ABSTRACTAutonomous Taxis (ATs) have seen remarkable global proliferation in recent years owing to the widespread adoption and advancements in Artificial Intelligence (AI) across various domains. ATs play a crucial role in Intelligent Transportation Systems (ITS) in smart cities. However, the effectiveness of ITS relies heavily on accurately forecasting the passenger demand for ATs, which poses a significant challenge. Precise prediction of passenger demand is essential for minimising waiting times and unnecessary cruising of ATs in metropolitan areas, which helps conserve energy. To address this issue, this study proposed an adaptive Bayesian Regularisation Backpropagation Neural Network (BRBNN) augmented with a Machine Learning (ML) model to predict passenger demand in different regions of metropolitan cities specifically for ATs. The study conducted extensive simulations using a real‐world dataset collected from 4781 taxis in Bangkok, Thailand. Using MATLAB2022b, the proposed model compared various state of art methods and existing research. The results indicate that proposed model outperforms existing methods in terms of performance metrics such as Root Mean Square Error (RMSE) and R‐squared () for passenger demand forecasting. These findings validated the effectiveness of the prediction model and its ability to accurately forecast passenger demand for ATs, thereby contributing to the advancement of efficient transportation systems in smart cities.
Loss and Gain: Temporal Succession in Different Facets of Fish Diversity Over a Half Century Under Cascade Dam Construction
Authors: Jia Yintao , Zhuo Yu , Cardoso Pedro , Li Junle , Wang Jun , Sui Xiaoyun , Feng Xiu , Zhu Ren , Li Kemao , Chen Yifeng 
Published: February 2025

ABSTRACTFreshwater biodiversity is increasingly imperilled by human activities, with dam construction posing significant threats to fish communities. Species composition changes through introductions and extinctions have been widely reported, yet the long‐term consequences of cascade dam construction on multiple facets of biodiversity remain poorly understood. Moreover, the compensatory effects of species introductions on extinction have received limited attention. This study presents a comprehensive evaluation of the impact of extinction‐introduction successions, triggered by cascade dam construction, on the taxonomic, phylogenetic, and functional diversity of fish assemblages in the upper Yellow River over five decades. Our results reveal that shifts in species composition significantly increased phylogenetic and functional diversity but not taxonomic diversity, suggesting a greater sensitivity of the former to cascade dam construction. However, introduced species only partially compensate for approximately 50% of phylogenetic and functional diversity losses caused by extinctions. Furthermore, the timing of significant increases in phylogenetic and functional diversity is not synchronised, with all measures gradually stabilising post‐dam construction. Cumulative reservoir capacity, reservoir age, and individual reservoir capacity were identified as key determinants of multifaceted diversity change after dam construction, with cumulative reservoir capacity and reservoir age generally having positive effects, while individual reservoir capacity tended to have a negative impact. These findings stress the urgent need to reassess the compensatory effects of introductions on extinctions under global change, emphasise caution in interpreting short‐term data due to non‐linear diversity patterns, and highlight the importance of using long‐term monitoring and multifaceted diversity metrics in biodiversity conservation actions.
Effect of MWCNTs on the Tension–Tension Fatigue Behavior of Woven Angle Ply GFRP Laminates
Authors: Radhakrishnan P. M. , Ramajeyathilagam K. 
Published: February 2025

ABSTRACTFatigue characteristics of multiwalled carbon nanotubes (MWCNTs) toughened glass fiber reinforced plastic (GFRP) composites made of woven angle ply (45°/−45°) fabric is presented. Fatigue experiments were conducted under tension–tension fatigue loading for stress ratios 0.1 and 0.3, and at three different stress intensities. The dispersion of 0.5 wt.% of MWCNTs in the modified GFRP resulted in better fatigue lifecycle compared with the GFRP modified with 1.0 wt.% of MWCNTs. In addition, MWCNTs dispersion also affected other fatigue properties, such as fatigue stiffness, cyclic creep, and dissipated energy. Analytical models were employed to demonstrate a substantial amount of reliability in accurately predicting the fatigue lifecycle of MWCNTs modified GFRP. Furthermore, a statistical methodology has been utilized to ascertain the design fatigue lifecycle at different levels of reliability.
A Hybrid Approach for Heat Source Identification and Heat Diffusion–Related Issues in the Fatigue Loading
Authors: Zaeimi Mohammad , De Finis Rosa , Palumbo Davide , Galietti Umberto 
Published: February 2025

ABSTRACTOver the past decades, thermographic methods have become a viable substitute for conventional approaches in the analysis of material fatigue behavior, due to their efficiency, cost‐effectiveness, and nondestructive nature. By examining the temperature signature generated by intrinsic heat dissipations during the fatigue loading, valuable insights into the behavior of the materials can be investigated. Substantial intrinsic dissipation—a marker of material damage—is linked to a transition from anelastic to inelastic strains. The main aim of this work is to explore heat dissipations during fatigue of materials by combining experimental techniques and numerical simulations, focusing on the fundamental temperature component in fully reversed loading, known as the second amplitude harmonic (SAH) of temperature. The hybrid method combines experimental data with numerical modeling to identify the specific volume generating heat during fatigue testing. Additionally, the effect of the mechanical loading frequency on SAH of temperature was also examined.
Allopatric Divergence and Secondary Contact Within a Single River System in a Freshwater Fish Group
Authors: Utama Ilham V. , Mandagi Ixchel F. , Lawelle Sjamsu A. , Masengi Kawilarang W. A. , Nagano Atsushi J. , Kusumi Junko , Yamahira Kazunori 
Published: February 2025

ABSTRACT

Because riverine fishes can disperse along linear river corridors and even between tributaries, allopatric divergence within river systems is limited to large rivers. Within small rivers, such as island rivers, allopatric divergence rarely occurs, and no cases of secondary contact have been reported to date.

Two congeneric riverine ricefishes, Oryzias dopingdopingensis and O. landangiensis, are found in the Doping‐doping and Cerekang Rivers, respectively, on Sulawesi Island, which are connected via estuarine waters. These two species are suggested to have diverged in allopatry within this single river system.

Phylogenetic and population genetic structure analyses using genome‐wide single nucleotide polymorphisms revealed that Oryzias individuals recently discovered from the downstream Cerekang River are phylogenetically distinct not only from O. dopingdopingensis in the Doping‐doping River but also from O. landangiensis in the upstream Cerekang River. Species tree analysis and demographic model inference revealed that the downstream Cerekang Oryzias diverged from upstream Cerekang Oryzias in allopatry approximately 57,000 generations ago, and they came into secondary contact with each other approximately 22,000 generations ago. Thereafter, the upstream Cerekang population split into two populations, O. landangiensis and O. dopingdopingensis, approximately 14,000 generations ago.

We are not aware of any freshwater fish groups that may have experienced both allopatric divergence and secondary contact within such a small single river system. The allopatric divergence and secondary contact within the Cerekang–Doping‐doping River system can be explained by assuming that a lake once existed in this region, where many tectonic lakes have formed and disappeared because of the collision and/or juxtaposition of tectonic subdivisions since the Pliocene/Pleistocene.

Gene flow from O. landangiensis to the downstream Cerekang Oryzias is also evident. Although the secondary contact between the upstream and downstream Cerekang populations was estimated to have occurred more than 40,000 years ago, they are still not completely homogenised within the linear corridor of the Cerekang River. This stagnation of homogenisation can be explained by their weak dispersal ability, which may reflect past adaptation to lacustrine environments.
Navigating Climate Change: Exploring the Dynamics Between Plant–Soil Microbiomes and Their Impact on Plant Growth and Productivity
Authors: Muhammad Murad , Wahab Abdul , Waheed Abdul , Hakeem Khalid Rehman , Mohamed Heba Ibrahim , Basit Abdul , Toor Muhammad Danish , Liu Yong‐Hong , Li Li , Li Wen‐Jun 
Published: February 2025

ABSTRACTUnderstanding the intricate interplay between plant and soil microbiomes and their effects on plant growth and productivity is vital in a rapidly changing climate. This review explores the interconnected impacts of climate change on plant–soil microbiomes and their profound effects on agricultural productivity. The ongoing rise in global temperatures, shifting precipitation patterns and extreme weather events significantly affect the composition and function of microbial communities in the rhizosphere. Changes in microbial diversity and activity due to rising temperatures impact nutrient cycling, microbial enzyme synthesis, soil health and pest and disease management. These changes also influence the dynamics of soil microbe communities and their capability to promote plant health. As the climate changes, plants' adaptive capacity and microbial partners become increasingly crucial for sustaining agriculture. Mitigating the adverse effects of climate change on plant growth and agricultural productivity requires a comprehensive understanding of the interconnected mechanisms driving these processes. It highlights various strategies for mitigating and adapting to environmental challenges, including soil management, stress‐tolerant crops, cover cropping, sustainable land and water management, crop rotation, organic amendments and the development of climate‐resilient crop varieties. It emphasises the need for further exploration of plant–soil microbiomes within the broader context of climate change. Promising mitigation strategies, including precision agriculture and targeted microbiome modifications, offer valuable pathways for future research and practical implementation of global food security and climate change.