bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of Reoperation After Orthognathic Surgery in Patients With Cleft Palate: Two Decades of Insight
Authors: Pekcan Asli , Turk Marvee , Patel Raina K. , Bakovic Melanie , Mejia Valeria , Vallurupalli Medha , Magee William P. , Shakoori Pasha , Urata Mark , Hammoudeh Jeffrey 
Published: February 2025

Orthognathic surgery represents a critical intervention within the continuum of care for patients with cleft lip and palate (CLP). Postoperative relapse is a significant complication and often necessitates reoperation. This study assesses risk factors for reoperation due to relapse following cleft orthognathic surgery. A retrospective review was conducted of patients with CLP who underwent orthognathic surgery for correction of class III malocclusion between 2005 and 2024, excluding those with under 6 months of follow-up. Maxillary advancement techniques included surgically assisted maxillary protraction (SAMP), LeFort I advancement (LF1), and distraction osteogenesis (DO). The outcome of interest was reoperation for late relapse. Overall, 133 patients met the inclusion criteria. The median age at surgery was 18.4 years, and the median follow-up was 2.1 years. Sixteen patients (12.0%) underwent SAMP, 101 (76.9%) LF1, 7 (5.3%) DO, and 9 (6.8%) staged DO followed by LF1. Bilateral sagittal split osteotomy (BSSO) for mandibular setback was performed in 48.4%. The incidence of reoperation was 13.5%. Maxillary advancements >8.5 mm were 6.3 times more likely to require reoperation (P<0.001). Multivariable regression identified bilateral CLP (P=0.038) and multiple prior maxillary operations (P=0.009) as significant predictors of reoperation, while BSSO was associated with decreased odds of reoperation (P=0.027). Patients with bilateral CLP and multiple prior maxillary operations were significantly more likely to require reoperation for late relapse. Limiting sagittal movements to <8.5 mm or performing concurrent BSSO may mitigate the risk of reoperation.
How does DeepSeek-R1 perform on USMLE?
Authors: Faray de Paiva Lisle , Luijten Gijs , Puladi Behrus , Egger Jan 
Published: February 2025

AbstractDeepSeek, a Chinese artificial intelligence company, released its first free chatbot app based on its DeepSeek-R1 model. DeepSeek provides its models, algorithms, and training details to ensure transparency and reproducibility. Their new model is trained with reinforcement learning, allowing it to learn through interactions and feedback rather than relying solely on supervised learning. Reports showcase that DeepSeek’s model shows competitive performances against established large language models (LLMs) such as Anthropic’s Claude and OpenAI’s GPT-4o on established benchmarks in language understanding, mathematics (AIME 2024) and programming (Codeforces) while trained at a fraction of the costs. Additionally, running inference shows significantly lower costs, leading to DeepSeek surpassing ChatGPT as the most downloaded free app on the American iOS App Store. This development contributed to a nearly 17% drop in Nvidia’s share price, resulting in the most significant one-day loss in U.S. history, amounting to nearly $600 billion. The open-source models also bring a significant shift in the healthcare system, allowing cost-efficient medical LLMs to be deployed within hospital networks. To understand its performance in the healthcare sector, we analyse the new DeepSeek-R1 model on the United States Medical Licensing Examination (USMLE) and compare it to ChatGPT.
The Landscape of Prostate Tumour Methylation
Authors: Arbet Jaron , Yamaguchi Takafumi N. , Shiah Yu-Jia , Hugh-White Rupert , Wiggins Adriana , Oh Jieun , Gebo Tsumugi , Foucal Adrien , Lesurf Robert , Jung Chol-Hee , Dang Rachel M. A. , Agrawal Raag , Livingstone Julie , Salcedo Adriana , Yao Cindy Q. , Espiritu Shadrielle Melijah G. , Houlahan Kathleen E. , Yousif Fouad , Heisler Lawrence E , Fraser Michael , Kishan Amar , Berlin Alejandro , Chua Melvin LK , van der Kwast Theodorus , Hovens Christopher M. , Bristow Robert G. , Boutros Paul C. 
Published: February 2025

AbstractProstate cancer is characterized by profound heterogeneity in its clinical trajectory. While genomic heterogeneity has been well-characterized, epigenomic heterogeneity remains less understood. To fill this gap, we compiled 2,149 multi-ancestric prostate methylomes spanning normal tissue through localized disease of varying grades to poly-metastatic disease, most with multi-omic DNA and/or RNA characterization. We identify four subtypes that varied by stage, grade and mutational subtype. We identify extensive interplay between DNA ploidy and DNA methylation, with transcriptional consequences that vary across driver-genes. Each major prostate cancer driver gene mutation triggers a specific epigenetic dysregulation, and we define a set of 14 reusable models that accurately predict clinico-molecular features of a prostate cancer from DNA methylation data. Specific epigenetic features predict disease aggression, including metastasis, with epigenomic and genomic features synergizing to optimize predictions. These results define a complex interplay between tumour genetics and epigenetics that converges to modify gene-expression programs, and subsequent clinical presentation.
Accelerated memory T cell decline and tolerogenic recall responses to SARS-CoV-2 vaccination in diabetes
Authors: Jones Emma M , Sourij Caren , Stradner Martin , Schlenke Peter , Sereban Nazanin , Moser Othmar , Quinlan Rachael , Short Charlotte-Eve , Harris Benjamin H L , Fertleman Michael , Taylor Graham P , Oliver Nick , Sourij Harald , Dominguez-Villar Margarita 
Published: February 2025

AbstractType 1 and type 2 diabetes are associated with increased severity and mortality from respiratory virus infections, including SARS-CoV-2. Vaccination in the general population significantly reduces the risk of severe respiratory viral infection and triggers a strong, polyfunctional and lasting T cell response in healthy individuals. However, vaccine effectiveness in people with diabetes is unclear. Here we studied the magnitude and functional characteristics of vaccine-specific CD4+and CD8+T cell responses to the full vaccination protocol, and the recall response after a third booster dose of SARS-CoV-2 vaccine in people with type 1 and type 2 diabetes, and compared them to those of people without diabetes. We found defects in both CD4+and CD8+T cell memory maintenance and the functionality of the vaccine specific T cells in people with diabetes compared to people without. In those individuals with diabetes that harbored detectable vaccine-specific T cells, they displayed an unfocused, tolerogenic phenotype characterized by increased expression of IL-13 and IL-10 in T1D and T2D compared to people without diabetes. These results have implications for vaccination strategies for people with diabetes.
Real-world visual search goes beyond eye movements: Active searchers select 3D scene viewpoints too
Authors: Wu Tiffany C. , Tsotsos John K. 
Published: February 2025

AbstractVisual search is a ubiquitous task; people search for objects on a daily basis. However, the majority of the existing visual search literature focuses on passive search on a 2D computer screen, a far cry from emulating a real-world environment. Search is a real-world task that involves active observation. Search targets may be occluded, completely out of the observer’s line of sight, or oriented in unconventional ways. This is typically mitigated by actively selecting viewpoints, an important aspect of search behaviour with limited scope on a computer screen. Our goal was to explore viewpoint selection in active visual search. Subject eye and head movements were tracked as they moved freely while searching for toy objects in a controlled 3-dimensional environment, yielding the first such record of search-driven viewpoint selection. We found that subjects utilized their full range of eye and head motion to move from viewpoint to viewpoint, apparently employing a variety of objectives including changing viewing height and pose depending on object 3D pose. Subjects were also adept at selecting unobstructed views to search through otherwise occluded areas with objects. Furthermore, subjects completed the search task with high accuracy, even with no training on the environment. Although no learning was found in terms of accuracy over the duration of the experiment, increases in efficiency were found for other metrics such as response time, number of fixations, and distance travelled, particularly in target present trials where the target was not visible from the starting location. These results paint the story of a visual system that selects and moves to useful and informative views to facilitate the successful execution of an active visual search task, and stresses the significance of active vision research in understanding how vision is used in naturalistic environments.
Comprehensive analysis of αβT-cell receptor repertoires reveals signatures of thymic selection
Authors: Luppov Daniil V. , Vlasova Elizaveta K. , Chudakov Dmitry M. , Shugay Mikhail 
Published: February 2025

AbstractThymic selection is a multi-stage process that establishes a T-cell immunity that is efficient in fighting diverse foreign pathogens, while not being self-reactive. During the process, T-cell receptor (TCR)α and β chains are rearranged to form a highly diverse set of heterodimers that are selected based on their affinity to peptides presented by major histocompatibility molecules (MHC) in the thymus. Here we employ high-throughput TCR sequencing data, theoretical model of TCR rearrangement and dedicated statistical methods to infer how the selection process affects human TCR repertoire on different scales. On a global scale, our results indicate differences in V(D)J gene usage, complementarity determining region 3 (CDR3) amino acid composition, CDR3 physicochemical properties, k-mer composition and differences in loop structure induced by the selection process. On a local scale, we were able to determine enriched TCR motifs and “holes” in repertoire induced by positive and negative selection and characterize their features. Finally, we demonstrated how TCR sequence composition affects lineage commitment via thymic selection and highlighted the effect of individual MHC haplotype. Our results can aid in identification of potentially self-reactive TCRs in donor repertoires in autoimmunity and immunotherapy studies.Graphical abstractStudy overview.A.Datasets used in the study and the way TCR sequences were analyzed.B.Main directions in which thymic selection shapes TCR repertoire. Selection results in TCR-CDR3 losing positively charged and large amino-acids while increasing its flexibility. Unlike CDR3 of the TCRα chain, CDR3β hydrophobicity is also increased by selection. CDR3s carrying Cysteines and glycosylation sites are unlikely to pass the selection. In contrast, CDR3 carrying poly-Glycine regions are more likely to be selected for both chains. T-cells committed to CD8+ lineage were more likely to feature bulged CDR3s compared to CD4+.C.CDR3s enriched after thymic selection guide lineage commitment according to single-cell RNA sequencing data analysis, e.g. the MAIT cells and CD8+ phenotypes.D.Enrichment and depletion of certain TCR motifs pinpoint fine-structure of post-selection repertoires, as inferred by sequence neighborhood analysis.E.Comparative analysis of enriched and depleted TCR clusters in monozygotic twins revealed that the selection process is shaped by HLA haplotype.
Spatio-temporal distribution patterns and ecological correlates of new mammal records in China
Authors: Ding Chenchen , Ding Jiale , Qiao Huijie , Jiang Zhigang , Wang Zhiheng 
Published: February 2025

AbstractSpecies’ geographic distributions are central to research in biogeography, macroecology, and conservation biology. However, incomplete or inaccurate knowledge about their spatiotemporal ranges—known as the Wallacean shortfall—hampers our understanding of biodiversity patterns and processes. In this study, we systematically reviewed 192 papers that reported new distribution records of China’s mammals from 2001 to 2023, covering 150 species in 26 families across 7 orders. We examined the taxonomic, spatiotemporal, and biogeographic characteristics of these newly recorded species. We used Bayesian Phylogenetic Generalized Linear Mixed Models (BPGLMM) to assess how intrinsic traits and extrinsic factors influenced the likelihood of discoveries and partial Poisson regressions to evaluate how species-level attributes, environmental and socio-economic factors shaped the number of new occurrence records across provinces. Our results showed that Chiroptera (n=69), Eulipotyphla (n=26) and Rodentia (n=23) had the highest number of new records. Among provinces, Yunnan (n=31), Guangdong (n=22), and Xizang (n=18) yielded the most newly recorded species. The amount of annual discoveries varied and peaked between 2017 and 2021. The Western Mountain and Plateau (n=39) and the East Hilly Plain (n=33) zoogeographic subregions had the greatest number of newly recorded species, including two new records extending into historically unrecognized zoogeographic realms. Notably, 61 (40.7%) species were found to extend towards the north or northeast of their known ranges, and 32 (21.3%) eastward, mainly due to the sampling bias. Smaller-bodied species and those with broader habitat ranges are more likely to yield new records, and the total number of new records was positively correlated with regional species richness and current survey efforts (r > 0.5, p < 0.05). These findings expand the known distributions of China’s mammals and provide essential data for mitigating the Wallacean shortfall. They underscore the urgent need for intensified surveys in biodiversity-rich, underexplored regions—especially targeting small-bodied, data-deficient taxa—and for timely updates and data-sharing to better inform conservation strategies.
Protein language models accelerate the discovery of Plastic-Degrading Enzymes
Authors: Medina-Ortiz David , Alvarez-Saravia Diego , Soto-García Nicole , Sandoval-Vargas Diego , Aldridge Jacqueline , Rodríguez Sebastián , Andrews Barbara , Asenjo Juan A. , Daza Anamaría 
Published: February 2025

AbstractPlastic pollution presents a critical environmental challenge, necessitating innovative and sustainable solutions. In this context, biodegradation using microorganisms and enzymes offers an environmentally friendly alternative. This work introduces an AI-driven frame-work that integrates machine learning (ML) and generative models to accelerate the discovery and design of plastic-degrading enzymes. By leveraging pre-trained protein language models and curated datasets, we developed seven ML-based binary classification models to identify enzymes targeting specific plastic substrates, achieving an average accuracy of 89%. The framework was applied to over 6,000 enzyme sequences from the RemeDB to classify enzymes targeting diverse plastics, including PET, PLA, and Nylon. Besides, generative learning strategies combined with trained classification models in this work were applied forde novogeneration of PET-degrading enzymes. Structural bioinformatics validated potential candidates throughin-silicoanalysis, highlighting differences in physicochemical properties between generated and experimentally validated enzymes. Moreover, generated sequences exhibited lower molecular weights and higher aliphatic indices, features that may enhance interactions with hydrophobic plastic substrates. These findings highlight the utility of AI-based approaches in enzyme discovery, providing a scalable and efficient tool for addressing plastic pollution. Future work will focus on experimental validation of promising candidates and further refinement of generative strategies to optimize enzymatic performance.
RNA-EFM : Energy based Flow Matching for Protein-conditioned RNA Sequence-Structure Co-design
Authors: Abir Abrar Rahman , Zhang Liqing 
Published: February 2025

AbstractRibonucleic acids (RNAs) are essential biomolecules involved in gene regulation and molecular recognition. Designing RNA molecules that can bind specific protein targets is crucial for therapeutic applications but remains challenging due to the structural flexibility of RNA and the laborious nature of experimental techniques. We proposeRNA-EFM, a novelEnergy-basedFlowMatching framework for protein-conditioned RNA sequence and structure co-design. RNA-EFM integrates biophysical constraints, including the Lennard-Jones potential and sequence-derived free energy, to generate low-energy and biologically plausible RNA conformations. By incorporating an idempotent refinement strategy for iterative structural correction, RNA-EFM consistently outperforms existing baselines, achieving lower RMSD, higher lDDT, and superior sequence recovery across multiple evaluation splits.
Dual Translational Control in Cardiomyocytes by Heterogeneous mTORC1 and Hypertrophic ERK Activation
Authors: Uchida Keita , Scarborough Emily A. , Prosser Benjamin L. 
Published: February 2025

ABSTRACTBackgroundCardiac hypertrophy allows post-mitotic cardiomyocytes to meet increased hemodynamic demands but can predispose the heart to adverse clinical outcomes. Despite its central role in cardiac adaptation, the translational control mechanisms that drive cardiac hypertrophy are poorly understood. In this study, we elucidate the relative contributions of the various translational control mechanisms operant during homeostasis and hypertrophic growth.MethodsA combination of immunofluorescence and single myocyte protein synthesis assays were used to dissect the single-cardiomyocyte mechanisms of translational control under basal and hypertrophic conditions in isolated adult rat cardiomyocytes. Translational control mechanism were examined in a mouse model of acute hypertrophic phenylephrine (PE) stimulation prior to overt cardiac growth.ResultsWe observed strikingly heterogeneous activity of mTORC1, the master regulator of translation, across cardiomyocytes bothin situandex vivo. Heterogeneous mTORC1 activity drove heterogeneous protein synthesis, with translation primarily controlled via canonical mTORC1-dependent 4EBP1 phosphorylation at Thr36/Thr45/Thr69 under baseline conditions. Hypertrophic PE stimulation recruited more cardiomyocytes into a high mTORC1 activity state. PE induced a switch in 4EBP1 phosphorylation by increasing mTORC1-dependent phosphorylation at Thr36/Thr45, but not Thr69. Further, PE induced a novel mTORC1-independent, but MEK-ERK-dependent, pathway driving 4EBP1 phosphorylation at Ser64 in both isolated cardiomyocytes andin vivo. Ribosome biogenesis was also observed within hours upon hypertrophic stimulation, while the mTORC1-S6K-eEF2K-eEF2 pathway was not found to be a major driver of protein translation.ConclusionsProtein synthesis is heterogeneous across cardiomyocytes driven by heterogeneous mTORC1 activity. MEK-ERK signaling directly controls 4EBP1 phosphorylation to augment translation during cardiac hypertrophy and challenges the canonical model of translation initiation.Key points:mTORC1 activity is low and heterogeneous across cardiomyocytes at baseline.Heterogeneous mTORC1 activity drives variable 4EBP1 phosphorylation at Thr36/Thr45/Thr69, resulting in heterogeneous protein translation.Phenylephrine stimulation recruits more cardiomyocytes into a high mTORC1 activity state to augment protein synthesis through 4EBP1 phosphorylation at Thr36/Thr45, but not Thr69.Phenylephrine stimulation boosts protein translation through mTORC1-independent but ERK-dependent phosphorylation of 4EBP1 at Ser64.mTORC1-S6K-eEF2K-eEF2 pathway is not a major driver of global protein translation.Ribosome biogenesis is observed within hours after hypertrophic stimulation.The data demonstrates a dual input model of mTORC1 and ERK dependent phosphorylation of 4EBP1 to regulate protein translation in cardiomyocytes.
A fluorescent folding reporter uncovers myosin misfolding as a driver of Hypertrophic Cardiomyopathy
Authors: Arnese Renato , Dexheimer Philipp Julian , Escobar-Doncel Beatriz , Krüger Lotta , Adhikari Govinda , Krpan Nina , Sehr Daria , Kley Juliane , Deszcz Luiza , Meinhart Anton , Kirstein Janine , Clausen Tim 
Published: February 2025

AbstractHypertrophic cardiomyopathy (HCM) is a fatal genetic disorder causing the thickening of ventricular walls in the heart muscle. While certain mutations in cardiac myosin deregulate ATPase activity, the pathology mechanism of most HCM mutations is not known. Here, by designing a fluorescent reporter to monitor myosin folding in cells, we uncovered a distinct class of HCM mutations that cause graded defects in myosin maturation. UsingC. elegansas a disease model, we found that folding deficient HCM variants cause myofilament disruption, impaired motility, and reduced lifespan. Dietary restrictions resulted in a near-complete recovery from these detrimental defects by activating autophagy pathways through insulin/TOR signaling. In conclusion, our study identifies myosin misfolding as an important driver of HCM, revealing therapeutic opportunities to counteract muscle protein disorders.
From ancient fears to airborne threats: fMRI insights into neural fear responses
Authors: Rádlová Silvie , Pidnebesna Anna , Chomik Aleksandra , Tomeček David , Hlinka Jaroslav , Frynta Daniel , Landová Eva 
Published: February 2025

AbstractThreat perception is a fundamental aspect of human cognition, shaped by evolutionary pressures and modern environmental demands. While ancestral threats (e.g., snakes) have been shown to elicit stronger neural responses than modern threats (e.g., guns), less is known about how the brain processes airborne threats, such as depictions of individuals wearing face masks. This fMRI study investigates neural responses to ancestral, modern, and airborne threats to identify shared and distinct activation patterns.Sixty participants viewed visual stimuli from the three categories while undergoing fMRI scanning. Results showed heightened activation in the fear-processing network for all affective stimuli. In addition, activation of the ventral attention network was found for the ancestral threats. Modern threats elicited less intense responses, primarily engaging cortical regions associated with context-specific analysis. Notably, airborne threats elicited neural responses of similar intensity to ancestral threats but activated cortical regions overlapping with those for modern threats. This dual pattern highlights the brain’s capacity to integrate evolutionary biases with socially constructed threat awareness. These findings underscore the importance of recognizing airborne threats as a unique category of threat processing, with implications for public health and mental well-being.