bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRACERx analysis identifies a role for FAT1 in regulating chromosomal instability and whole-genome doubling via Hippo signalling
Authors: Lu Wei-Ting , Zalmas Lykourgos-Panagiotis , Bailey Chris , Black James R. M. , Martinez-Ruiz Carlos , Pich Oriol , Gimeno-Valiente Francisco , Usaite Ieva , Magness Alastair , Thol Kerstin , Webber Thomas A. , Jiang Ming , Saunders Rebecca E. , Liu Yun-Hsin , Biswas Dhruva , Ige Esther O. , Aerne Birgit , Grönroos Eva , Venkatesan Subramanian , Stavrou Georgia , Karasaki Takahiro , Al Bakir Maise , Renshaw Matthew , Xu Hang , Schneider-Luftman Deborah , Sharma Natasha , Tovini Laura ,   TRACERx Consortium, Jamal-Hanjani Mariam , McClelland Sarah E. , Litchfield Kevin , Birkbak Nicolai J. , Howell Michael , Tapon Nicolas , Fugger Kasper , McGranahan Nicholas , Bartek Jiri , Kanu Nnennaya , Swanton Charles 
Published: December 2024

Abstract
Chromosomal instability (CIN) is common in solid tumours and fuels evolutionary adaptation and poor prognosis by increasing intratumour heterogeneity. Systematic characterization of driver events in the TRACERx non-small-cell lung cancer (NSCLC) cohort identified that genetic alterations in six genes, including FAT1, result in homologous recombination (HR) repair deficiencies and CIN. Using orthogonal genetic and experimental approaches, we demonstrate that FAT1 alterations are positively selected before genome doubling and associated with HR deficiency. FAT1 ablation causes persistent replication stress, an elevated mitotic failure rate, nuclear deformation and elevated structural CIN, including chromosome translocations and radial chromosomes. FAT1 loss contributes to whole-genome doubling (a form of numerical CIN) through the dysregulation of YAP1. Co-depletion of YAP1 partially rescues numerical CIN caused by FAT1 loss but does not relieve HR deficiencies, nor structural CIN. Importantly, overexpression of constitutively active YAP15SA is sufficient to induce numerical CIN. Taken together, we show that FAT1 loss in NSCLC attenuates HR and exacerbates CIN through two distinct downstream mechanisms, leading to increased tumour heterogeneity.
Estimation of internal displacement in Ukraine from satellite-based car detections
Authors: Rufener Marie-Christine , Ofli Ferda , Fatehkia Masoomali , Weber Ingmar 
Published: December 2024

AbstractEstimating the numbers and whereabouts of internally displaced people (IDP) is paramount to providing targeted humanitarian assistance. In conflict settings like the ongoing Russia-Ukraine war, on-the-ground data collection is nevertheless often inadequate to provide accurate and timely information. Satellite imagery may sidestep some of these challenges and enhance our understanding of the IDP dynamics. Our study thus aimed to evaluate whether internal displacement patterns can be estimated from changes in car counts using multi-temporal satellite imagery. We collected over 1000 very-high-resolution images across Ukrainian cities between 2019 and 2022, to which we applied a state-of-the-art computer vision model to detect and count cars. These counts were then linked to population data to predict displacements through ratio or non-linear models. Our findings suggest a clear East-to-West movement of cars in the first months following the war’s onset. Despite data sparsity hindered fine-grained evaluation, we distinguished a clear positive and non-linear trend between the number of people and cars in most cities, which further allowed to predict the sub-national people dynamics. While our approach is resource-saving and innovative, satellite imagery and computer vision models present some shortcomings that could mask detailed IDPs dynamics. We conclude by discussing these limitations and outline future research opportunities.
Refining minimal engineered receptors for specific activation of on-target signaling molecules
Authors: Miura Masashi , Kawahara Masahiro 
Published: December 2024

AbstractSince designer cells are attracting much attention as a new modality in gene and cell therapy, it would be advantageous to develop synthetic receptors that recognize artificial ligands and activate solely signaling molecules of interest. In this study, we refined the construction of our previously developed minimal engineered receptors (MERs) to avoid off-target activation of STAT5 while maintaining on-target activation of signaling molecules corresponding to tyrosine motifs. Among the myristoylated, cytoplasmic, and transmembrane types of MERs, the cytoplasmic type had the highest signaling efficiency, although there was off-target activation of STAT5 upon ligand stimulation. Tyrosine-to-phenylalanine ​​mutagenesis revealed that both the tyrosine motif for recruiting target signaling molecules and the tyrosine residues in the JAK-binding domain did not contribute to off-target activation of STAT5. Using alanine mutagenesis for Box1 of the JAK-binding domain of MERs, we ultimately found a Box1 mutation that slightly reduced activation of on-target signaling molecules but minimized off-target activation of STAT5. The refined MER enabled us to precisely analyze the signaling and cell fate-inducing properties of seven tyrosine motifs. Therefore, the refined MER, which realizes activation of on-target signaling molecules with high signal-to-noise ratios, will attract much attention as a tool for functionalizing designer cells and more broadly in the field of synthetic biology.
Experimental evidence of high tick infestation limiting chick growth and survival in a colonial seabird
Authors: Militão Teresa , Clessin Augustin , Gamble Amandine , Granadeiro José Pedro , Boulinier Thierry , Catry Paulo 
Published: December 2024

AbstractWhile numerous studies have established correlations between parasite load and negative effects on their hosts, establishing causality is more challenging because parasites can directly compromise host condition and survival or simply opportunistically thrive on an already weakened host. Here, we evaluated whether Ixodes uriae, a widespread seabird tick, can cause a decrease in growth parameters (body mass, bill length and growth rates) and survival of chicks of a colonially seabird, the black-browed albatross (Thalassarche melanophris) breeding on New Island (West Falkland). To investigate this, we daily removed the ticks from 28 randomly selected chicks during their first 14 days of life (treated chicks) and compared their growth and survival with 49 chicks of a control group. The tick load on control chicks correlated negatively with their body mass, growth rates and survival. Comparisons between treated and control chicks demonstrated that tick infestation depleted body mass and hampered the growth of control chicks. Treated chicks had a higher survival rate than control ones to fledgling age, but not to 14 days old, suggesting that the delayed higher mortality on control chicks was caused by the accumulation of sub-lethal effects of ticks. This study experimentally demonstrates that high tick infestation can cause reduced host growth and survival.
Intrusion detection system for V2X communication in VANET networks using machine learning-based cryptographic protocols
Authors: Venkatasamy Thiruppathy Kesavan , Hossen Md. Jakir , Ramasamy Gopi , Aziz Nor Hidayati Binti Abdul 
Published: December 2024

AbstractVehicle-to-everything (V2X) communication has many benefits. It improves fuel efficiency, road safety, and traffic management. But it raises privacy and security concerns. These include the risk of cyberattacks and the loss of drivers’ personal data. Eavesdropping, data manipulation, and unauthorized vehicle monitoring are major problems that need immediate attention. This paper proposes a new approach to intrusion detection in V2X communications. It uses machine learning-based cryptographic protocols for intrusion detection (ML-CPIDSs). The goal is to improve privacy and security in vehicular ad hoc networks (VANETs). The ML-CPIDS combines advanced cryptographic protocols with machine learning. It provides strong authentication, encryption, and real-time threat detection. Robust authentication and encryption techniques in modern cryptographic systems protect sensitive information. Using machine learning algorithms, it is feasible to identify and address security risks in real-time. The proposed technology solves key privacy and security issues. It has applications in many areas, including autonomous vehicle networks, urban traffic management, and vehicle communication systems. Extensive simulations show the ML-CPIDS works in different VANET environments. Privacy, security, and the ability to identify threats in real time are some of the areas that are evaluated in these simulations. The proposed ML-CPIDS approach outperforms current methods on several metrics. It has better privacy and authentication, lower latency, and stronger threat detection. It also improves the integrity and efficiency of V2X communications in VANET networks.
Machine-learning crystal size distribution for volcanic stratigraphy correlation
Authors: Jutzeler Martin , Carey Rebecca J. , Dagasan Yasin , McNeill Andrew , Cas Ray A. F. 
Published: December 2024

AbstractVolcanic stratigraphy reconstruction is traditionally based on qualitative facies analysis complemented by geochemical analyses. Here we present a novel technique based on machine learning identification of crystal size distribution to quantitatively fingerprint lavas, shallow intrusions and coarse lava breccias. This technique, based on a simple photograph of a rock (or core) sample, is complementary to existing methods and allows another strategy to identify and compare volcanic rocks for stratigraphic correlation. Phenocryst size distributions display overall homogeneity within one volcanic body but may vary considerably between igneous bodies. Restricted to shallow intrusions and volcanic lavas, this concept allows for stratigraphic fingerprinting of volcanic rocks in poorly exposed, up to moderately altered, and/or complexly tectonized formations. We built an automated image analysis workflow using machine-learning for crystal segmentation, followed by statistical analysis of physical descriptors to compare and match the size distribution of feldspar phenocrysts. The workflow comprises three instance segmentation models for pre-processing the images, automated scale measurement and grain segmentation using Mask R-CNN. This avoids the laborious and time-consuming task of manual picking by image analysis, and allows for a rapid, unbiased and quantitative approach to determine crystal size distribution (CSD). Our volcanic architecture reconstruction of multiple dacite bodies in the mineralized Cambrian Mt Read Volcanics in Tasmania, Australia, is independently validated by bulk-rock chemical analyses of key samples. This volcanic stratigraphy method can be applied to a large variety of igneous rocks and is complementary to geochemical analyses and qualitative crystal content assessment.
Noncanonical calcium binding motif controls folding of HopQ1, a Pseudomonas syringae type III secretion effector, in a pH-dependent manner
Authors: Giska Fabian , Rymaszewski Wojciech , Lichocka Malgorzata , Piechocki Marcin , Kwiatkowski Jakub , Poznański Jarosław , Górecka Magdalena , Krzymowska Magdalena 
Published: December 2024

AbstractVirulence of many gram-negative bacteria relies upon delivery of type three effectors into host cells. To pass through the conduit of secretion machinery the effectors need to acquire an extended conformation, and in many bacterial species specific chaperones assist in this process. In plant pathogenic bacterium Pseudomonas syringae, secretion of only few effectors requires the function of chaperones. This raises a question how chaperone-independent effectors achieve an appropriate conformation for the secretion. One such mechanism was previously described for AvrPto. It contains a pH-sensitive switch, which is involved in unfolding of the effector at the mildly acidic pH corresponding to the pH value of the bacterial cytosol, and refolding at the neutral pH. Therefore, it was proposed that the switch facilitates first translocation of AvrPto and then its maturation once the effector reaches the cytoplasm of host cell. Here we show that an atypical motif of HopQ1, another effector of P. syringae, reversibly binds calcium in pH-dependent manner, regulating the effector thermal stability. Therefore, we propose a model that HopQ1 traversing through the type three secretion system encounters conditions that maintain its extended conformation, while upon delivery into host cell the effector undergoes refolding.
TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion
Authors: He Lei , Wei Haijun , Sun Cunxun 
Published: December 2024

AbstractThe intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance. Firstly, we integrate a Transformer module based on the self-attention mechanism with the C3 module at the end of the backbone network to form a C3TR module. This integration enhances the global feature extraction capability of the backbone network and improves its ability to detect small target wear particles. Secondly, we introduce the convolutional block attention module (CBAM) into the neck network to enhance salience for detecting wear particles while suppressing irrelevant information interference. Furthermore, multi-scale feature maps extracted by the backbone network are fed into the bidirectional feature pyramid network (BiFPN) for feature fusion to enhance the model’s ability to detect wear particle feature maps at different scales. Lastly, Ghost modules are introduced into both the backbone network and the neck network to reduce their complexity and improve detection speed. Experimental results demonstrate that TCBGY-Net achieves outstanding precision in detecting wear particles against complex backgrounds, with a mAP@0.5 value of 98.3%, which is a 10.2% improvement over YOLOv5s. In addition, we conducted comprehensive ablation experiments, to validate the contribution of each module and the robustness of our model. TCBGY-Net also outperforms most current mainstream algorithms in terms of detection speed, with up to 89.2 FPS capability, thus providing favorable conditions for subsequent real-time online monitoring of changes in wear particles and fault diagnosis in ship power systems.
Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool
Authors: Galanty Maria , Luitse Dieuwertje , Noteboom Sijm H. , Croon Philip , Vlaar Alexander P. , Poell Thomas , Sanchez Clara I. , Blanke Tobias , Išgum Ivana 
Published: December 2024

AbstractMedical datasets are vital for advancing Artificial Intelligence (AI) in healthcare. Yet biases in these datasets on which deep-learning models are trained can compromise reliability. This study investigates biases stemming from dataset-creation practices. Drawing on existing guidelines, we first developed a BEAMRAD tool to assess the documentation of public Magnetic Resonance Imaging (MRI); Color Fundus Photography (CFP), and Electrocardiogram (ECG) datasets. In doing so, we provide an overview of the biases that may emerge due to inadequate dataset documentation. Second, we examine the current state of documentation for public medical images and signal data. Our research reveals that there is substantial variance in the documentation of image and signal datasets, even though guidelines have been developed in medical imaging. This indicates that dataset documentation is subject to individual discretionary decisions. Furthermore, we find that aspects such as hardware and data acquisition details are commonly documented, while information regarding data annotation practices, annotation error quantification, or data limitations are not consistently reported. This risks having considerable implications for the abilities of data users to detect potential sources of bias through these respective aspects and develop reliable and robust models that can be adapted for clinical practice.
New-onset gastrointestinal disorders in COVID-19 patients 3.5 years post-infection in the inner-city population in the Bronx
Authors: Changela Sagar , Ashraf Samad , Lu Justin Y. , Duong Kevin E. , Henry Sonya , Wang Stephen H. , Duong Tim Q. 
Published: December 2024

AbstractThis study examined the incidence, characteristics, and risk factors of new gastrointestinal disorders (GID) associated with SARS-CoV-2 infection up to 3.5 years post-infection. This retrospective study included 35,102 COVID-19 patients and 682,594 contemporary non-COVID-19 patients without past medical history of GID (controls) from the Montefiore Health System in the Bronx (3/1/2020 to 7/31/2023). Comparisons were made with unmatched and propensity-matched (1:2) controls. The primary outcome was new GID which included peptic ulcer, inflammatory bowel disease, irritable bowel syndrome, diverticulosis, diverticulitis, and biliary disease. Multivariate Cox proportional hazards model analysis was performed with adjustment for covariates. There were 2,228 (6.34%) COVID-19 positive patients who developed new GID compared to 38,928 (5.70%) controls. COVID-19 patients had an elevated risk of developing new GID (adjusted HR = 1.18 (95% CI 1.12–1.25) compared to propensity-matched controls, after adjusting for confounders that included smoking, obesity, diabetes, hypertension. These findings underscore the need for additional research and follow-up of at-risk individuals for developing GID post infection.
Competing fairness ideals underlie wealth inequality across decision contexts
Authors: Huijsmans Inge , Vahed Sarah , Răţală Cătălina E. , Llera Alberto , Sanfey Alan G. 
Published: December 2024

AbstractWealth inequality is one of the most profound challenges confronting society today. However, an important issue in addressing inequality lies in formalizing the diversity of individual perspectives regarding what constitutes a fair distribution of resources. We tackle this topic by simulating wealth inequality through the allocation of bonus endowments in both Dictator Game (DG) and Ultimatum Game (UG) settings and capturing distributive decisions. By integrating a computational model, we quantify individual differences in the interplay between financial self-interest and competing pro-social motivations that emerge in the context of pre-existing wealth inequity. Our behavioral results show that, on average, pre-existing wealth influences distributive preferences across both allocations and proposals. Yet, inequality elicits non-uniform fairness concerns. Using a hierarchical clustering approach, we objectively categorise participants’ behavior elucidating four distinct decision strategies: ‘Pro-Self’, ‘Table Egalitarianism’, ‘Total Egalitarianism’, and ‘Moral Opportunism’. A balanced distribution of strategies is observed during allocations (DG), whereas Table Egalitarianism prevails in strategic proposals (UG), highlighting the influence of strategic considerations on decision strategy. Furthermore, we demonstrate an association between strategies across decision contexts. Our findings thus contribute a principled framework to formalize distributive preferences, revealing that, with respect to both altruistic allocations and strategic proposals, competing ideals of fairness underlie distributive preferences under wealth inequality.
Anchoring spinel cobalt and zinc ferrites on zeolite for highly synergic photocatalytic reduction of chromium (VI)
Authors: Mehrbakhsh Moin , Honarmand Moones , Aryafar Ahmad 
Published: December 2024

AbstractTo tackle the challenges of increasing the efficiency of photocatalysts, a ternary magnetic heterojunction photocatalyst containing spinel cobalt and zinc ferrites, and zeolite (CZZ) was designed and fabricated. The physicochemical properties of the novel photocatalyst were verified using characterization techniques such as XRD, FT-IR, FE-SEM, EDS mapping, N2 adsorption-desorption, VSM, PL, and UV–Vis DRS. The CZZ photocatalyst exhibited a significant Cr (VI) reduction rate of 0.1535 min−1, which was 9.27, 5.37 and 3.58 times higher than those of single ZnFe2O4 nanoparticles (0.0166 min−1), CoFe2O4 nanoparticles (0.0286 min−1), and CoFe2O4–ZnFe2O4 (0.0428 min−1) respectively. CZZ showed an excellent reusability after three consecutive cycles of Cr(VI) reduction. The results from the experiments in different aqueous environments displayed that CZZ could be a promising photocatalyst to reduce Cr(VI) in the treatment of actual aqueous matrices. The present study not only provides a highly active catalytic system for the practical removal of Cr(VI) but also paves the way for the fabrication of high-performance heterojunction photocatalysts.
Starch can expedite the screening for bacterial aflatoxin degraders
Authors: Sandlin Natalie , Momeni Babak 
Published: December 2024

AbstractAflatoxins (AFs) are secondary fungal metabolites that contaminate common food crops and are harmful to humans and animals. The ability to degrade or remove aflatoxins from common feed commodities will improve health standards and counter the economic drain inflicted by AF contamination. Bioremediation is a promising solution to AF contamination because of its low cost and few undesired environmental side-effects. Identifying new degrader species is highly beneficial in that it can offer alternatives to overcome the limitations of existing biodegraders, such as narrow working conditions and low degradation rates. Here, we screen several environmental isolates for their AF detoxification ability, using aflatoxin G2. We use different carbon sources (glucose and starch) in isolation and culturing media to examine the effect of the environment on degradation ability. Strains isolated in media with starch as the primary carbon source showed a higher percentage of good AF degraders, 16% compared to 2% when glucose was the primary carbon source. Additionally, the majority of species isolated in glucose medium exhibited improved degradation efficiency when moved into starch medium, with one isolate improving degradation levels from 30 to 70%. Our starch screen also revealed three previously unidentified AF degrader bacterial species. Good aflatoxin G2 degraders also appear to perform well against aflatoxin B1. Overall, for AF degradation, starch medium expedites the screening process and generally improves the performance of isolates. We thus propose that using starch as the carbon source is a promising means to identify new AF degraders in the environment.