bluuebunny/crossref_metadata_2025_split huggingface dataset:
MLKL deficiency elevates testosterone production in male mice independently of necroptotic functions
Authors: Chiou Shene , Cawthorne Wayne , Soerianto Thomas , Hofferek Vinzenz , Patel Komal M. , Garnish Sarah E. , Tovey Crutchfield Emma C. , Hall Cathrine , Hildebrand Joanne M. , McConville Malcolm J. , Lawlor Kate E. , Hawkins Edwin D. , Samson Andre L. , Murphy James M. 
Published: November 2024

AbstractMixed lineage kinase domain-like (MLKL) is a pseudokinase, best known for its role as the terminal effector of the necroptotic cell death pathway. MLKL-mediated necroptosis has long been linked to various age-related pathologies including neurodegeneration, atherosclerosis and male reproductive decline, however many of these attributions remain controversial. Here, we investigated the role of MLKL and necroptosis in the adult mouse testis: an organ divided into sperm-producing seminiferous tubules and the surrounding testosterone-producing interstitium. We find that sperm-producing cells within seminiferous tubules lack expression of key necroptotic mediators and thus are resistant to a pro-necroptotic challenge. By comparison, coordinated expression of the necroptotic pathway occurs in the testicular interstitium, rendering cells within this compartment, especially the lysozyme-positive macrophages, vulnerable to necroptotic cell death. We also uncover a non-necroptotic role for MLKL in regulating testosterone levels. Thus, MLKL serves two roles in the mouse testes – one involving the canonical response of macrophages to necroptotic insult, and the other a non-canonical function in male reproductive hormone control.
In-context learning enables multimodal large language models to classify cancer pathology images
Authors: Ferber Dyke , Wölflein Georg , Wiest Isabella C. , Ligero Marta , Sainath Srividhya , Ghaffari Laleh Narmin , El Nahhas Omar S. M. , Müller-Franzes Gustav , Jäger Dirk , Truhn Daniel , Kather Jakob Nikolas 
Published: November 2024

AbstractMedical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processing, in-context learning provides an alternative, where models learn from within prompts, bypassing the need for parameter updates. Yet, in-context learning remains underexplored in medical image analysis. Here, we systematically evaluate the model Generative Pretrained Transformer 4 with Vision capabilities (GPT-4V) on cancer image processing with in-context learning on three cancer histopathology tasks of high importance: Classification of tissue subtypes in colorectal cancer, colon polyp subtyping and breast tumor detection in lymph node sections. Our results show that in-context learning is sufficient to match or even outperform specialized neural networks trained for particular tasks, while only requiring a minimal number of samples. In summary, this study demonstrates that large vision language models trained on non-domain specific data can be applied out-of-the box to solve medical image-processing tasks in histopathology. This democratizes access of generalist AI models to medical experts without technical background especially for areas where annotated data is scarce.
Influence of resonant plasmonic nanoparticles on optically accessing the valley degree of freedom in 2D semiconductors
Authors: Bucher Tobias , Fedorova Zlata , Abasifard Mostafa , Mupparapu Rajeshkumar , Wurdack Matthias J. , Najafidehaghani Emad , Gan Ziyang , Knopf Heiko , George Antony , Eilenberger Falk , Pertsch Thomas , Turchanin Andrey , Staude Isabelle 
Published: November 2024

AbstractThe valley degree of freedom in atomically thin transition metal dichalcogenides, coupled with valley-contrasting optical selection rules, holds great potential for future electronic and optoelectronic devices. Resonant optical nanostructures emerge as promising tools for controlling this degree of freedom at the nanoscale. However, their impact on the circular polarization of valley-selective emission remains poorly understood. In our study, we explore a hybrid system where valley-specific emission from a molybdenum disulfide monolayer interacts with a resonant plasmonic nanosphere. Contrary to the simple intuition that a centrosymmetric nanoresonator mostly preserves the degree of circular polarization, our cryogenic experiments reveal significant depolarization of the photoluminescence scattered by the nanoparticle. This striking effect presents an ideal platform for studying the mechanisms governing light-matter interactions in such hybrid systems. Our full-wave numerical analysis provides insights into the key physical mechanisms affecting the polarization response, offering a pathway toward designing novel valleytronic devices.
Whole-genome sequencing to identify rare variants in East Asian patients with dementia with Lewy bodies
Authors: Kimura Tetsuaki , Fujita Kosuke , Sakurai Takashi , Niida Shumpei , Ozaki Kouichi , Shigemizu Daichi 
Published: November 2024

AbstractDementia with Lewy bodies (DLB) is the second most common form of age-related dementia, following Alzheimer’s disease (AD). DLB is associated with a worse prognosis than AD and is characterized by a more rapid progression of cognitive impairment and a poorer quality of life. In addition, the pathogenesis of DLB is less understood than that of AD, and only three genes—SNCA (α‐synuclein), APOE (apolipoprotein E), and GBA1 (glucosylceramidase beta 1)—have been convincingly demonstrated to be associated with DLB. In this study, we utilized whole-genome sequencing data from 1744 Japanese individuals, comprising 45 DLB patients and 1699 cognitively normal older adults, aiming to identify new genes associated with DLB. Our genome-wide association studies of genes with potentially deleterious mutations identified the CDH23 gene as being associated with DLB, reaching a Bonferroni-corrected significance (P = 7.43 × 10−4). The gene contained three ethnicity-specific heterozygous missense variants (rs181275139, rs563688802, and rs137937502). CDH23 has been linked to deafness syndromes, and DLB patients carrying these mutations displayed symptoms of subjective hearing loss, suggesting a potential association between DLB onset and auditory impairment. Additionally, we explored human leukocyte antigen (HLA) genotypes associated with DLB but found no significant associations. This result suggests that the pathology of DLB differs from that of Parkinson’s disease, which has been reported to have an association with HLA. Although a limitation of this study is the lack of replication of our findings, which require further validation in independent cohorts, our study enhances the understanding of the etiology of DLB in the Japanese population and provides new insights into the underlying mechanisms of its pathogenesis.
Web-browsing patterns reflect and shape mood and mental health
Authors: Kelly Christopher A. , Sharot Tali 
Published: November 2024

Abstract
Humans spend on average 6.5 hours a day online. A large portion of that time is dedicated to information-seeking. How does this activity impact mental health? We assess this over four studies (n = 1,145). We reveal that the valence of information sought affects mental health, which in turn influences the valence of information sought, forming a self-reinforcing loop. We quantified the valence of text on webpages participants chose to browse using natural language processing and found that browsing more negative information was associated with worse mental health and mood. By manipulating the webpages browsed and measuring mood and vice versa, we show that the relationship is causal and bidirectional. Finally, we developed an intervention that altered web-browsing patterns in a manner that improved mood. Together, the findings suggest that the information sought reflects mental state and shapes it, creating a loop that may perpetuate mental health problems. The results also provide a potential method for assessing and enhancing welfare in the digital age.
Spatially resolved emulated annual temperature projections for overshoot pathways
Authors: Schwaab Jonas , Hauser Mathias , Lamboll Robin D. , Beusch Lea , Gudmundsson Lukas , Quilcaille Yann , Lejeune Quentin , Schöngart Sarah , Schleussner Carl-Friedrich , Nath Shruti , Rogelj Joeri , Nicholls Zebedee , Seneviratne Sonia I. 
Published: November 2024

AbstractDue to insufficient climate action over the past decade, it is increasingly likely that 1.5 °C of global warming will be exceeded – at least temporarily – in the 21st century. Such a temporary temperature overshoot carries additional climate risks which are poorly understood. Earth System Model climate projections are only available for a very limited number of overshoot pathways, thereby preventing comprehensive analysis of their impacts. Here, we address this issue by presenting a novel dataset of spatially resolved emulated annual temperature projections for different overshoot pathways. The dataset was created using the FaIR and MESMER emulators. First, FaIR was employed to translate ten different emission scenarios, including seven that are characterised by overshoot, into a large ensemble of forced global mean temperatures. These global mean temperatures were then converted into stochastic ensembles of local annual temperature fields using MESMER. To ensure an optimal tradeoff between accurate characterization of the ensemble spread and storage requirements for large ensembles, this procedure was accompanied by testing the sensitivity of sample quantiles to different ensemble sizes. The resulting dataset offers the unique opportunity to study local and regional climate change impacts of a range of overshoot scenarios, including the timing and magnitude of temperature thresholds exceedance.
Database of surface water diversion sites and daily withdrawals for the Upper Colorado River Basin, 1980–2022
Authors: Lopez Samuel F. , Knight Jacob E. , Tilman Fred D. , Masbruch Melissa D. , Wise Daniel R. , Jones Casey J. , Miller Matthew P. 
Published: November 2024

Abstract
The Colorado River drains about 8% of the conterminous United States, provides water for 40 million people, and is one of the most overallocated rivers in the world. As the upper Colorado River Basin (UCOL) contributes an estimated 92% of the total basin natural streamflow, knowledge of the location and amount of surface water withdrawals in the UCOL is important for managing the Colorado River system. Since the UCOL encompasses portions of five states, water use data are dispersed among numerous federal and state agency databases, and there is no centralized dataset that documents surface water use within the entire UCOL at a fine spatial and temporal resolution. This article presents an inventory of 1,358 major structures that divert surface water from and within the UCOL with corresponding daily time series withdrawal records from 1980 through 2022. Data compilation efforts, processing methods, and contents of this diversion database are documented, and summary information is provided.
A data-driven framework for identifying patient subgroups on which an AI/machine learning model may underperform
Authors: Subbaswamy Adarsh , Sahiner Berkman , Petrick Nicholas , Pai Vinay , Adams Roy , Diamond Matthew C. , Saria Suchi 
Published: November 2024

AbstractA fundamental goal of evaluating the performance of a clinical model is to ensure it performs well across a diverse intended patient population. A primary challenge is that the data used in model development and testing often consist of many overlapping, heterogeneous patient subgroups that may not be explicitly defined or labeled. While a model’s average performance on a dataset may be high, the model can have significantly lower performance for certain subgroups, which may be hard to detect. We describe an algorithmic framework for identifying subgroups with potential performance disparities (AFISP), which produces a set of interpretable phenotypes corresponding to subgroups for which the model’s performance may be relatively lower. This could allow model evaluators, including developers and users, to identify possible failure modes prior to wide-scale deployment. We illustrate the application of AFISP by applying it to a patient deterioration model to detect significant subgroup performance disparities, and show that AFISP is significantly more scalable than existing algorithmic approaches.
Migrating subaqueous dunes capture clay flocs
Authors: de Lange Sjoukje I. , van der Wilk Anne , Chassagne Claire , Ali Waqas , Born Maximilian P. , Brodersen Kristian , Hoitink Antonius J. F. , Waldschläger Kryss 
Published: November 2024

AbstractRecent research highlights the abundance of floccule (flocs) in rivers, formed by aggregation of clay particles with organic matter. These flocs affect the transport and the eventual fate of clay. Flocs exhibit distinct behaviour from the unflocculated sedimentary counterparts: they can deform and break, and have higher settling velocities, which may in turn cause flocs to deposit and possibly interact with the riverbed. Here, we conducted systematic experiments in a laboratory flume to identify the mechanisms by which flocs and bedforms interact. Flocs showed a saltating (bouncing) behaviour, and were incorporated in the sediment bed as single flocs, clusters, or strings, via deposition and burial in the lee of a dune. Dune geometry was negligibly impacted by the presence of flocs. In natural systems, the burial of flocculated clay particles can affect contaminant spreading, aquatic ecology, the interpretation of deposition patterns, and clay transport.
Amphibian richness, rarity, threats, and conservation prospects across the U.S. National Park System
Authors: LaFrance Benjamin J. , Ray Andrew M. , Tercek Michael T. , Fisher Robert N. , Hossack Blake R. 
Published: November 2024

AbstractWe assessed amphibian diversity, rarity, and threats across the National Park System (U.S.A.), which covers 3.5% of the country and 12% of federal lands. At least 230 of 354 (65%) amphibian species documented in the country occur on National Park Service lands. Of species in parks, 17% are at-risk globally and 20% are uncategorized, reflecting still-widespread data deficiencies. National parks in the Northwest and Northeast had the steepest species‒area relationships. Non-native crayfishes and amphibians occur within 50 km of 60% and 25% of parks, respectively, illustrating the broad threat of non-native predators. Projected mid-century (2040–2069) changes in climatic water deficit, based on 25 climate futures, produced an expected 34% increase in dryness across all national parks in the conterminous U.S.A. Our analyses highlight the extent and regional differences in current and future threats and reveal gaps in species protection, but also reveal opportunities for targeted expansion and active management.
Non-Hermitian selective thermal emitter for thermophotovoltaics
Authors: Samuel Prasad Ciril , Naik Gururaj V. 
Published: November 2024

AbstractFor a sustainable future, efficient, compact, and solid-state energy converters are critical. Thermophotovoltaics (TPV)—a solid-state scheme to convert heat into electricity—is promising for thermal storage and generation1. TPV systems employing selective thermal emitters allow compact designs for various terrestrial and space applications and, hence, have garnered much attention. Despite significant research efforts, these systems have low efficiency. The selective thermal emitter and the low-bandgap photovoltaic cell contribute to this problem. Here, we solve the shortcomings of the thermal emitter by using a novel approach inspired by non-Hermitian optics. We demonstrate a hybrid metal-dielectric non-Hermitian selective emitter (NHE) with high spectral efficiency (> 60%) and employ the NHE in a TPV system operating at 1273 K. We show that a maximum TPV conversion efficiency of 12% is possible at 1273 K, though our preliminary experiments employing an uncooled PV cell showed a much lower efficiency.
Tunable heteroassembly of 2D CoNi LDH and Ti3C2 nanosheets with enhanced electrocatalytic activity for oxygen evolution
Authors: Lu Xueyi , Jia Lulu , Hou Minchen , Wu Xuemin , Ni Chang , Xiao Gaofei , Ma Renzhi , Lu Xia 
Published: November 2024

CoNi LDH/Ti3C2 heterostructures are obtained by electrostatic attraction of positively charged LDH and negatively charged Ti3C2 nanosheets, which serve as effective catalysts for oxygen evolution reaction with enhanced electrocatalytic activity.
Trajectory tracking control of autonomous vehicles based on event‐triggered model predictive control
Authors: Zhang Jindou , Wang Zhiwen , Li Long , Yang Kangkang , Lu Yanrong 
Published: November 2024

AbstractThis paper presents a lateral control scheme based on event‐triggered model predictive control for trajectory tracking of autonomous vehicles. Firstly, the augmentation system is constructed based on the known road curvature information, and the model predictive controller is utilized to obtain the optimal control sequence. Then, an event‐triggered mechanism is introduced to improve the real‐time performance of the control system. The strategy targets to reduce the computational complexity and solving frequency of the optimization problem. In addition, a contraction constraint is structured using the backstepping control strategy to ensure the stability of the control system. Finally, experiments are conducted through the CarSim/Simulink joint simulation platform, and compared with the traditional model predictive control, the method proposed in this paper has better tracking accuracy and improves the real‐time performance of the control system.
Automated detection of satellite trails in ground-based observations using U-Net and Hough transform
Authors: Stoppa F. , Groot P. J. , Stuik R. , Vreeswijk P. , Bloemen S. , Pieterse D. L. A. , Woudt P. A. 
Published: November 2024

Aims. The expansion of satellite constellations poses a significant challenge to optical ground-based astronomical observations, as satellite trails degrade observational data and compromise research quality. Addressing these challenges requires developing robust detection methods to enhance data processing pipelines, creating a reliable approach for detecting and analyzing satellite trails that can be easily reproduced and applied by other observatories and data processing groups.
Methods. Our method, called ASTA (Automated Satellite Tracking for Astronomy), combined deep learning and computer vision techniques for effective satellite trail detection. It employed a U-Net based deep learning network to initially detect trails, followed by a probabilistic Hough transform to refine the output. ASTA’s U-Net model was trained on a dataset of manually labeled full-field MeerLICHT telescope images prepared using the user-friendly LABKIT annotation tool. This approach ensured high-quality and precise annotations while facilitating quick and efficient data refinements, which streamlined the overall model development process. The thorough annotation process was crucial for the model to effectively learn the characteristics of satellite trails and generalize its detection capabilities to new, unseen data.
Results. The U-Net performance was evaluated on a test set of 20 000 image patches, both with and without satellite trails, achieving approximately 0.94 precision and 0.94 recall at the selected threshold. For each detected satellite, ASTA demonstrated a high detection efficiency, recovering approximately 97% of the pixels in the trails, resulting in a False Negative Rate (FNR) of only 0.03. When applied to around 200 000 full-field MeerLICHT images focusing on Geostationary (GEO) and Geosynchronous (GES) satellites, ASTA identified 1742 trails −19.1% of the detected trails – that could not be matched to any objects in public satellite catalogs. This indicates the potential discovery of previously uncatalogued satellites or debris, confirming ASTA’s effectiveness in both identifying known satellites and uncovering new objects.
Enhancing photometric redshift catalogs through color-space analysis: Application to KiDS-bright galaxies
Authors: Jalan Priyanka , Bilicki Maciej , Hellwing Wojciech A. , Wright Angus H. , Dvornik Andrej , Georgiou Christos , Heymans Catherine , Hildebrandt Hendrik , Joudaki Shahab , Kuijken Konrad , Mahony Constance , Nakoneczny Szymon Jan , Radovich Mario , van den Busch Jan Luca , Yan Ziang , Yoon Mijin 
Published: November 2024

Aims. We present a method for refining photometric redshift galaxy catalogs based on a comparison of their color-space matching with overlapping spectroscopic calibration data. We focus on cases where photometric redshifts (photo-z) are estimated empirically. Identifying galaxies that are poorly represented in spectroscopic data is crucial, as their photo-z may be unreliable due to extrapolation beyond the training sample.
Methods. Our approach uses a self-organizing map (SOM) to project a multidimensional parameter space of magnitudes and colors onto a 2D manifold, allowing us to analyze the resulting patterns as a function of various galaxy properties. Using SOM, we compared the Kilo-Degree Survey’s bright galaxy sample (KiDS-Bright), limited to r < 20 mag, with various spectroscopic samples, including the Galaxy And Mass Assembly (GAMA).
Results. Our analysis reveals that GAMA tends to underrepresent KiDS-Bright at its faintest (r ≳ 19.5) and highest-redshift (z ≳ 0.4) ranges; however, no strong trends are seen in terms of color or stellar mass. By incorporating additional spectroscopic data from the SDSS, 2dF, and early DESI, we identified SOM cells where the photo-z values are estimated suboptimally. We derived a set of SOM-based criteria to refine the photometric sample and improve photo-z statistics. For the KiDS-Bright sample, this improvement is modest, namely, it excludes the least represented 20% of the sample reduces photo-z scatter by less than 10%.
Conclusions. We conclude that GAMA, used for KiDS-Bright photo-z training, is sufficiently representative for reliable redshift estimation across most of the color space. Future spectroscopic data from surveys such as DESI should be better suited for exploiting the full improvement potential of our method.