bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Phase 1b study of the OxPhos inhibitor ME-344 with bevacizumab in refractory metastatic colorectal cancer
Authors: Boland Patrick M. , Lenz Heinz-Josef , Ciombor Kristen K. , Florou Vaia , Pishvaian Michael J. , Cusnir Michael , Cohen Deirdre , Guo Jessie Y. , Tang Min , Rajagopalan Prabhu , Wiley Sandra E. , Ghalie Richard G. , Hochster Howard S. 
Published: December 2024

AbstractAntiangiogenic drugs may cause vascular normalization and correct hypoxia in tumors, shifting cells to mitochondrial respiration as the primary source of energy. In turn, the addition of an inhibitor of mitochondrial respiration to antiangiogenic therapy holds potential to induce synthetic lethality. This study evaluated the mitochondrial inhibitor ME-344 in combination with bevacizumab in patients with refractory metastatic colorectal cancer (mCRC). Patients were eligible if they had disease progression after standard therapies, adequate hematologic, hepatic and renal function, and no contraindications to bevacizumab. ME-344 was administered intravenously on days 1, 8 and 15 and bevacizumab on days 1 and 15 of 28-day cycles until disease progression or intolerance. The primary efficacy endpoint was progression-free survival (PFS) at week 16. In the 23 patients enrolled, the median age was 58 years, median number of prior lines of therapy was 4, and median interval from last therapy was 3 months. The most common adverse events (all grades/grade ≥ 3) were fatigue (48%/13%), abdominal pain (35%/4%), diarrhea (30%/4%) and constipation (30%/0%). No patient had an objective response; 9 patients (39%) achieved stable disease. The 16-week PFS was 30.6% (95% confidence interval [CI]: 12.2–51.3), the median PFS was 1.9 months (95% CI: 1.6–4.7), and the median overall survival was 6.7 months (95% CI: 3.4-not reached). ME-344 plus bevacizumab was well tolerated. Disease control was limited in this heavily pretreated patient population. Additional investigations in earlier lines are indicated, and extended-release ME-344 formulations may provide longer drug exposure to maximize benefit. (Trial registration number ClinicalTrials.gov NCT05824559. Registration date 22 March 2022).
The spatiotemporal effect of sea surface temperature on the seasonal migrations of the bonnethead, Sphyrna tiburo
Authors: Keller Bryan A. , Frazier Bryan S. , Grubbs R. Dean 
Published: December 2024

AbstractTo better understand the effects of climatic variation on migratory behavior, we used passive acoustic telemetry to track the migrations of 44 bonnetheads, Sphyrna tiburo, tagged in the North Edisto River, South Carolina. We monitored individuals for up to 2804 days along ~ 1070 km of United States Atlantic coastline. The majority of these sharks exhibited strong site fidelity and returned annually, residing in the estuary from April to November. Climatic migrations occurred annually and overwintering habitats were located in nearshore Atlantic waters from Georgia to central Florida. Given the strong site fidelity, we were able to measure the distance and timing of migration and assess, for the first time to our knowledge, the interannual effects of climatic variation on the return migrations of individual sharks. We found that shark size and winter sea surface temperature had significant effects on the migration distance of female S. tiburo, the latter also contributing to interannual variation in migration duration and the date of arrival to overwintering areas. These data suggest that overwintering habitats are selected, at least in part, based on thermal preference or tolerance and not solely physical location. These results indicate that climate change may affect both the timing and distance of migrations for migratory sharks and highlight the benefit of maintaining long-term longitudinal datasets for studying complex animal behavior.
Nuclear error phenotypes in the two-cell embryo are correlated to blastocyst formation rate after assisted reproduction
Authors: Stenberg Amanda , Baumgart Juliane , Adolfsson Emma 
Published: December 2024

Abstract

Purpose
Map the nuclear error phenotypes in the two-cell embryo after assisted reproduction using time lapse images and the effect on good quality blastocyst formation.

Methods
Retrospective cohort study using time lapse images, categorizing 2331 two-cell embryos from 392 patient couples and 504 ART cycles categorizing each embryo as mononucleated, multinucleated, micronucleated, binucleated, split nucleation or mixed error. Correlating nuclear error phenotype with good quality blastocyst formation rate (BFR) using contingency tables and unadjusted odds ratio.

Results
An overall nuclear error rate of 47.1% was observed in two-cell embryos. The most frequent error was multi-nucleation (14.2%) followed by mixed error (11%), micro-nucleation (8.6%), bi-nucleation (7.4%) and split nucleation (5.8%). Blastocyst formation rate (BFR) was reduced in embryos with nuclear errors, 46.2% for embryos with one cell affected, 27.6% for embryos with both cells affected, compared to 58.6% for mononucleated cells, p < 0.001 for both. Binucleated embryos were as likely as mononucleated embryos to become clinically useful blastocysts (56.8% vs 58.6%, n.s., unadjusted OR 0.94), whereas all the other phenotypes were less likely to develop into good quality blastocysts. The worst outcome was noted for embryos with split nucleation, with just 12.4% BFR, OR 0.12 (0–08-0.21), p < 0.001.

Conclusion
Nuclear errors are common at the two-cell stage. Overall, presence of nuclear errors reduces the likelihood of becoming good quality blastocysts. Both the number of affected cells and the different nuclear error phenotypes have impact on blastocyst formation rate, except binucleated embryos.
Adaptive velocity control for UAV boat landing: A neural network and particle swarm optimization approach
Authors: Wu Li-Fan , Wang Zihan , Rastgaar Mo , Mahmoudian Nina 
Published: December 2024

AbstractAchieving precise landing of Unmanned Aerial Vehicles (UAVs) onto moving platforms, such as Autonomous Surface Vehicles (ASVs), is challenging, particularly in GPS-denied environments with dynamic disturbances. Conventional methods often rely on high-level waypoint navigation, extensive manual tuning, and expensive sensors. In this work, we propose an adaptive Proportional-Integral-Derivative (PID) controller optimization using a Neural Network-Particle Swarm Optimization (NN-PSO) algorithm. The algorithm dynamically tunes the PID controller, significantly reducing manual tuning effort, while relying solely on a low-cost camera and altitude sensor. The NN-PSO algorithm allows the UAV to land with an average error of 5 cm on static platforms and 10 cm on moving boats, based on multiple test flights. Our method also increases the maximum landing speed to 80.9% of the UAV’s top flight speed, a considerable improvement over existing systems. Our approach not only optimizes landing precision but also introduces techniques for ensuring soft landings, reducing oscillations, and preventing target misses. These enhancements make the method robust across varying flight altitudes and ASV speeds. Furthermore, this approach is applicable to a variety of GPS-denied scenarios, including rescue missions, package deliveries, and workspace inspections, without requiring costly equipment or extensive parameter tuning. Field experiments confirm the precision and stability of the proposed system, validating its performance in real-world conditions. [Video]
Jets Downstream of Collisionless Shocks: Recent Discoveries and Challenges
Authors: Krämer Eva , Koller Florian , Suni Jonas , LaMoury Adrian T. , Pöppelwerth Adrian , Glebe Georg , Mohammed-Amin Tara , Raptis Savvas , Vuorinen Laura , Weiss Stefan , Xirogiannopoulou Niki , Archer Martin , Blanco-Cano Xóchitl , Gunell Herbert , Hietala Heli , Karlsson Tomas , Plaschke Ferdinand , Preisser Luis , Roberts Owen , Simon Wedlund Cyril , Temmer Manuela , Vörös Zoltán 
Published: December 2024

Abstract
Plasma flows with enhanced dynamic pressure, known as magnetosheath jets, are often found downstream of collisionless shocks. As they propagate through the magnetosheath, they interact with the surrounding plasma, shaping its properties, and potentially becoming geoeffective upon reaching the magnetopause. In recent years (since 2016), new research has produced vital results that have significantly enhanced our understanding on many aspects of jets. In this review, we summarise and discuss these findings. Spacecraft and ground-based observations, as well as global and local simulations, have contributed greatly to our understanding of the causes and effects of magnetosheath jets. First, we discuss recent findings on jet occurrence and formation, including in other planetary environments. New insights into jet properties and evolution are then examined using observations and simulations. Finally, we review the impact of jets upon interaction with the magnetopause and subsequent consequences for the magnetosphere-ionosphere system. We conclude with an outlook and assessment on future challenges. This includes an overview on future space missions that may prove crucial in tackling the outstanding open questions on jets in the terrestrial magnetosheath as well as other planetary and shock environments.
Three Rich-Lexicon Theories of Slurs: A Comparison
Authors: Zeman Dan 
Published: December 2024

AbstractMany authors writing on slurs think that they are lexically rich, in the sense that their lexical meaning comprises both a descriptive dimension and an expressive/evaluative one, the latter accounting for their derogatory character. However, more fine-grained theories of slurs have recently been proposed, drawing on frameworks from lexical semantics. My main aim in this paper is to compare three such fine-grained rich-lexicon theories—the one put forward by myself in previous work with two similar ones, Croom’s (2011, 2013) and Neufeld’s (2019, 2022). While my primary aim is to underlie the commonalities and differences between the three views, I also aim at showing that the latter views have some issues that are easily avoided in the framework I propose.
On How to Determine Surface Roughness Power Spectra
Authors: Rodriguez N. , Gontard L. , Ma C. , Xu R. , Persson B. N. J. 
Published: December 2024

Abstract
Analytical contact mechanics theories depend on surface roughness through the surface roughness power spectrum. In the present study, we evaluated the usability of various experimental methods for studying surface roughness. Our findings indicated that height data obtained from optical methods often lack accuracy and should not be utilized for calculating surface roughness power spectra. Conversely, engineering stylus instruments and atomic force microscopy (AFM) typically yield reliable results that are consistent across the overlapping roughness length scale region. For surfaces with isotropic roughness, the two-dimensional (2D) power spectrum can be derived from the one-dimensional (1D) power spectrum using several approaches, which we explored in this paper.

Graphical Abstract
Validation of quantitative [18F]NaF PET uptake parameters in bone diseases: a systematic review
Authors: de Ruiter Ruben D. , Zwama Jolien , Raijmakers Pieter G. H. M. , Yaqub Maqsood , Burchell George L. , Boellaard Ronald , Lammertsma Adriaan A. , Eekhoff Elisabeth M. W. 
Published: December 2024

Abstract

Purpose
[18F]NaF PET has become an increasingly important tool in clinical practice toward understanding and evaluating diseases and conditions in which bone metabolism is disrupted. Full kinetic analysis using nonlinear regression (NLR) with a two-tissue compartment model to determine the net rate of influx (K

i
) of [18F]NaF is considered the gold standard for quantification of [18F]NaF uptake. However, dynamic scanning often is impractical in a clinical setting, leading to the development of simplified semi-quantitative parameters. This systematic review investigated which uptake parameters have been used to evaluate bone disorders and how they have been validated to measure disease activity.

Methods
A literature search (in PubMed, Embase.com, and Clarivate Analytics/Web of Science Core Collection) was performed up to 28th November 2023, in collaboration with an information specialist. Each database was searched for relevant literature regarding the use of [18F]NAF PET/CT to measure disease activity in bone-related disorders. The main aim was to explore whether the reported semi-quantitative uptake values were validated against full kinetic analysis. A second aim was to investigate whether the chosen uptake parameter correlated with a disease-specific outcome or marker, validating its use as a clinical outcome or disease marker.

Results
The initial search included 1636 articles leading to 92 studies spanning 29 different bone-related conditions in which [18F]NaF PET was used to quantify [18F]NaF uptake. In 12 bone-related disorders, kinetic analysis was performed and compared with simplified uptake parameters. SUVmean (standardized uptake value) and SUVmax were used most frequently, though normalization of these values varied greatly between studies. In some disorders, various studies were performed evaluating [18F]NaF uptake as a marker of bone metabolism, but unfortunately, not all studies used this same approach, making it difficult to compare results between those studies.

Conclusion
When using [18F]NaF PET to evaluate disease activity or treatment response in various bone-related disorders, it is essential to detail scanning protocols and analytical procedures. The most accurate outcome parameter can only be obtained through kinetic analysis and is better suited for research. Simplified uptake parameters are better suited for routine clinical practice and repeated measurements.
A framework for optimal portfolios with sustainable assets and climate scenarios
Authors: Korn Ralf 
Published: December 2024

AbstractWith the increasing impact of global warming and climate change, governments must take actions to reduce $$\text {CO}_2$$

CO
2

output and to encourage more environmentally friendly industrial processes. As the use of climate scenarios is the common method in illustrating possible consequences of the climate changes, we assume that it will also be the basis for political decisions with respect to future sustainability requirements on companies and thus (directly or indirectly) for sustainability constraints for life insurance companies and pension funds. Hence, we assume that bonus/malus measures by the government will already be laid out conditioned on the finally realized climate scenario. We will therefore present a corresponding framework for optimal investment under agreed government measures for the realization of future climate scenarios. This framework is particularly suited for strategies of large institutional investors such as life insurances. It will also be illustrated by explicit examples.
Multi-variate hybrid modeling for pacific ocean acidification: predicting future pH trends and analyzing key biogeochemical drivers
Authors: Vasanth K. , Kishore R. K. , Sugumaran Vijayan , Krishnamoorthy Raja , Ramdas Rithvik , Tadepalli Satya Kiranmai 
Published: December 2024

AbstractOcean acidification, driven by rising atmospheric carbon dioxide levels, poses a significant threat to the health of marine ecosystems, particularly in the Pacific Ocean. This study employs a multi-variate hybrid machine learning approach to predict future pH trends within the Pacific and to analyze the influence of key biogeochemical drivers on these trends. Hybrid models, strategically combining the strengths of individual algorithms, were developed for predicting several ocean acidification parameters. A performance analysis demonstrated the superior accuracy of hybrid models compared to their counterparts. The predicted pH trends reveal a concerning shift towards increased acidity within the Pacific Ocean, highlighting the urgency of understanding and mitigating its impacts. In-depth analysis was conducted to identify the relative influence of key biogeochemical factors on the changing pH dynamics. This research aims to provide crucial insights for developing targeted mitigation strategies and protecting the vulnerable ecosystems of the Pacific Ocean from the escalating consequences of ocean acidification.
Impact of dementia and mild cognitive impairment on bone health in older people
Authors: Curtis Elizabeth M. , Miguel Mario , McEvoy Claire , Ticinesi Andrea , Torre Carla , Al-Daghri Nasser , Alokail Majed , Bałkowiec-Iskra Ewa , Bruyère Olivier , Burlet Nansa , Cavalier Etienne , Cerreta Francesca , Clark Patricia , Cherubini Antonio , Cooper Cyrus , D’Amelio Patrizia , Fuggle Nicholas , Gregson Celia , Halbout Philippe , Kanis John A. , Kaufman Jean , Laslop Andrea , Maggi Stefania , Maier Andrea , Matijevic Radmila , McCloskey Eugene , Ormarsdóttir Sif , Yerro Concha Prieto , Radermecker Régis P. , Rolland Yves , Singer Andrea , Veronese Nicola , Rizzoli René , Reginster Jean-Yves , Harvey Nicholas C. 
Published: December 2024

AbstractMild cognitive impairment, dementia and osteoporosis are common diseases of ageing and, with the increasingly ageing global population, are increasing in prevalence. These conditions are closely associated, with shared risk factors, common underlying biological mechanisms and potential direct causal pathways. In this review, the epidemiological and mechanistic links between mild cognitive impairment, dementia and skeletal health are explored. Discussion will focus on how changes in brain and bone signalling can underly associations between these conditions, and will consider the molecular and cellular drivers in the context of inflammation and the gut microbiome. There is a complex interplay between nutritional changes, which may precede or follow the onset of mild cognitive impairment (MCI) or dementia, and bone health. Polypharmacy is common in patients with MCI or dementia, and there are difficult prescribing decisions to be made due to the elevated risk of falls associated with many drugs used for associated problems, which can consequently increase fracture risk. Some medications prescribed for cognitive impairment may directly impact bone health. In addition, patients may have difficulty remembering medication without assistance, meaning that osteoporosis drugs may be prescribed but not taken. Cognitive impairment may be improved or delayed by physical activity and exercise, and there is evidence for the additional benefits of physical activity on falls and fractures. Research gaps and priorities with the aim of reducing the burden of osteoporosis and fractures in people with MCI or dementia will also be discussed.
Association between social engagement decline and cognitive function changes: mediating effect of depressive symptoms
Authors: Ni Ping , Chen Hongxiu , Hu Xiuying 
Published: December 2024

Abstract
Background
Cognitive decline is a significant public health problem worldwide, but little is known about social engagement’s impact on cognitive changes over time. This study aimed to explore the relationship between social engagement decline and cognitive function change in Chinese adults, and to analyze the effect of changes in depressive symptoms on this relationship.

Methods
Participants were selected from the China Health and Retirement Longitudinal Study. Multiple linear regression was conducted to determine the association between social engagement decline and cognitive function changes, and a three-step method was used to test the mediating role of changes in depressive symptoms.

Results
During the four-year follow-up, participants’ overall cognitive function decreased by an average of 0.41 points (3.0%). The decline in social engagement was significantly associated with subsequent poorer global cognitive function (Model 1: β = − 0.060, P =.005; Model 2: β = − 0.056, P =.009), and changes in depressive symptoms partially mediated this effect, accounting for 15.3% of the total effect in Model 1 and 13.8% in Model 2. Model 1 adjusted for sociodemographic characteristics, and Model 2 adjusted for health-related factors based on Model 1.

Conclusion
When developing programs for cognitive improvement in middle-aged and older adults, measures to enhance social engagement should be considered. This may not only reduce depressive symptoms but also help to minimize cognitive decline.
Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring
Authors: Kulicki Maksymilian , Cabo Carlos , Trzciński Tomasz , Będkowski Janusz , Stereńczak Krzysztof 
Published: December 2024

Abstract
Purpose of Review
This paper provides an overview of integrating artificial intelligence (AI), particularly deep learning (DL), with ground-based LiDAR point clouds for forest monitoring. It identifies trends, highlights advancements, and discusses future directions for AI-supported forest monitoring.

Recent Findings
Recent studies indicate that DL models significantly outperform traditional machine learning methods in forest inventory tasks using terrestrial LiDAR data. Key advancements have been made in areas such as semantic segmentation, which involves labeling points corresponding to different vegetation structures (e.g., leaves, branches, stems), individual tree segmentation, and species classification. Main challenges include a lack of standardized evaluation metrics, limited code and data sharing, and reproducibility issues. A critical issue is the need for extensive reference data, which hinders the development and evaluation of robust AI models. Solutions such as the creation of large-scale benchmark datasets and the use of synthetic data generation are proposed to address these challenges. Promising AI paradigms like Graph Neural Networks, semi-supervised learning, self-supervised learning, and generative modeling have shown potential but are not yet fully explored in forestry applications.

Summary
The review underscores the transformative role of AI, particularly DL, in enhancing the accuracy and efficiency of forest monitoring using ground-based 3D point clouds. To advance the field, there is a critical need for comprehensive benchmark datasets, open-access policies for data and code, and the exploration of novel DL architectures and learning paradigms. These steps are essential for improving research reproducibility, facilitating comparative studies, and unlocking new insights into forest management and conservation.