bluuebunny/crossref_metadata_2025_split huggingface dataset:
Esophageal adenocarcinoma relapse after chemoradiation is dominated by a basal-like subtype
Authors: Hoppe Sascha , Noseir Soha , Yazbeck Ali , Zaburannyi Nestor , Großbach Jan , Lyu Su Ir , Camacho Oscar Velazquez , Müller Stefan , Gebauer Florian , Richartz Vanessa , Holz Barbara , Berg Johannes , Achter Viktor , Altmüller Janine , Becker Kerstin , Arolt Christoph , Meder Lydia , Zhao Yue , Schlößer Hans , Baus Wolfgang W. , Kamp Florian , Baues Christian , Beyer Andreas , Odenthal Margarete , Quaas Alexander , Buettner Reinhard , Hillmer Axel M. 
Published: February 2025

SummaryNeoadjuvant chemoradiation therapy (RCT) is a frequently used treatment regimen for esophageal adenocarcinoma (EAC); however, the response varies dramatically, and resistance is a clinical challenge. We aimed to identify the molecular mechanisms underlying RCT resistance. We established a mouse xenograft RCT model with human EAC cell lines representing different response groups, and tested enhanced genomic instability as a potential evolutionary modulator by reducingBRCA2function. Xenografts that relapsed after RCT displayed upregulation of stress response keratins, includingKRT6andKRT16connected with a basal-like transcriptomic/ proteomic phenotype. We screened our cohort of 728 patients with EAC and found significantly shorter overall survival for patients with KRT6-high tumors, driven by patients receiving neoadjuvant treatment. Overall, we identified a basal-like cell state in EAC that reflects RCT relapse. The basal-like subtype is a marker of treatment failure, providing a new avenue for translational research to overcome RCT resistance.
Database-Augmented Transformer-Based Large Language Models Achieve High Accuracy in Mapping Gene-Phenotype Relationships
Authors: Suhardi Nicolas Matthew , Oktarina Anastasia , Bostrom Mathias P.G. , Yang Xu , Suhardi Vincentius Jeremy 
Published: February 2025

AbstractTransformer-based large language models (LLMs) have demonstrated significant potential in the biological and medical fields due to their ability to effectively learn from large-scale, diverse datasets and perform a wide range of downstream tasks. However, LLMs are limited by issues such as information processing inaccuracies and data confabulation, which hinder their utility for literature searches and other tasks requiring accurate and comprehensive extraction of information from extensive scientific literature. In this study, we evaluated the performance of various LLMs in accurately retrieving peer-reviewed literature and mapping correlations between 102 genes and four phenotypes: bone formation, cartilage formation, fibrosis, and cell proliferation. Our analysis included standard transformer-based LLMs (ChatGPT4o and Gemini1.5 Pro), fine-tuned LLMs with dedicated custom databases containing peer-reviewed articles (SciSpace and ScholarAI), and fine-tuned LLMs without dedicated databases (PubMedGPT and ScholarGPT). Using human-curated gene-to-phenotype mappings as the ground truth, we found that fine-tuned LLMs with dedicated databases (SciSpace and ScholarAI) achieved high accuracy (>80%) in gene-to-phenotype mapping. Additionally, these models were able to provide relevant peer-reviewed publications supporting each gene-to-phenotype correlation. These findings underscore the importance of database augmentation and finetuning in enhancing the reliability and utility of LLMs for biomedical research applications.
DyAb: sequence-based antibody design and property prediction in a low-data regime
Authors: Lin Joshua Yao-Yu , Hofmann Jennifer L. , Leaver-Fay Andrew , Liang Wei-Ching , Vasilaki Stefania , Lee Edith , Pinheiro Pedro O. , Tagasovska Natasa , Kiefer James R. , Wu Yan , Seeger Franziska , Bonneau Richard , Gligorijevic Vladimir , Watkins Andrew , Cho Kyunghyun , Frey Nathan C. 
Published: February 2025

ABSTRACTProtein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a new model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in protein properties, rather than absolute values. DyAb is built on top of a pre-trained protein language model and achieves a Spearman rank correlation of up to 0.85 on binding affinity prediction across molecules targeting three different antigens (EGFR, IL-6, and an internal target), given as few as 100 training data. We employ DyAb in two design contexts: as a ranking model to score combinations of known mutations, and combined with a genetic algorithm to generate new sequences. Our method consistently generates novel antibody candidates with high binding rates, including designs that improve on the binding affinity of the lead molecule by more than ten-fold. DyAb represents a powerful tool for engineering therapeutic protein properties in low data regimes common in early-stage drug development.
SCGclust: Single Cell Graph clustering using graph autoencoders integrating SNVs and CNAs
Authors: Potu Teja , Hu Yunfei , Khan Rituparna , Dharani Srinija , Ni Jingchao , Zhang Liting , Zhou Xin Maizie , Mallory Xian 
Published: February 2025

AbstractIntra-tumor heterogeneity (ITH) is a compounding factor for cancer prognosis and treatment. Single-cell DNA sequencing (scDNA-seq) provides cellular resolution of the variations in a cell and has been widely used to study cancer progression and responses to drug and treatment. While the low coverage scDNA-seq technologies typically provides a large number of cells, accurate cell clustering is essential for effectively characterizing ITH. Existing cell clustering methods typically are based on either single nucleotide variations (SNV) or copy number alterations (CNA), without leveraging both signals together. Since both SNVs and CNAs are indicative of the cell subclonality, in this paper, we designed a robust cell clustering tool that integrates both signals using a graph autoencoder. Our model co-trains the graph autoencoder and a graph convolutional network (GCN) to guanrantee meaningful clustering results and to prevent all cells from collapsing into a single cluster. Given the low dimensional embedding generated by the autoencoder, we adopted a Gaussian Mixture Model to further cluster cells. We evaluated our method on eight simulated datasets and a real cancer sample. Our results demonstrate that our method consistently achieves higher V-measure scores compared to SBMClone, a SNV-based method, and a K-means method, which relies solely on CNA signals. These findings highlight the advantage of integrating both SNV and CNA signals within a graph autoencoder framework for accurate cell clustering. SCGclust is publicly available athttps://github.com/compbio-mallory/cellClustering_GNN.
A unique two-excipient heat stable tablet formulation of oral insulin: preliminary results
Authors: Lai Manshun , Zhu Changcheng , Delarosa Jaclyn , Lal Manjari 
Published: February 2025

AbstractWe report a novel formulation approach for development of a thermostable oral insulin tablet. Using freeze drying to form a heat stable tablet in a single-step process, we demonstrate hydroxypropyl beta cyclodextrin (HP-β-CD) encapsulated lipophilic ion-pair complex of insulin using bile salt achieves intestinal absorption and sustained glucose levels. The tablets produced using this simple approach with only two excipients offer protection from enzymatic and stomach acid degradation and facilitate insulin uptake, without any need for specialized drug manufacturing or enteric coating. Insulin in this innovative formulation is thermotolerant, capable of maintaining stability even under heat stress at 30-40°C/65-75% RH. The convenient presentation of insulin as a thermostable oral tablet presents a low-cost scalable manufacturing method that simplifies the logistics of storage, transport, and distribution in any setting, including areas where cold storage maybe limited or unavailable.Graphical AbstractOur unique formulation approach protects insulin from stomach and temperature induced degradation, improves intestinal permeability providing a sustained release of insulin for glycemic control. The freeze dried tablet product format is easily scalable and flexible, increasing accessibility across all populations.
Latitudinal gradients in stable hydrogen isotopes of North American trees
Authors: Keppler Frank , Berger Lars , Greule Markus , Esper Jan , Wieland Anna 
Published: February 2025

AbstractStable hydrogen isotopes (δ2H values) of plant matter provide information about ambient climate conditions and physiological processes.δ2H values of tree stem wood methoxy groups (δ2HTM) are increasingly used to reconstruct the isotope composition of precipitation (δ2Hprecip) and temperature variability in mid latitudes regions. However, empirical evidence of the basic latitudinal gradients in North America and their inter-continental context are still missing. We sampled 104 tree cores in 13 North American sites ranging from 38°-69°N and investigated the relationship betweenδ2HTMandδ2Hprecipvalues. Recordedδ2HTMvalues are highly depleted in2H relative to meteoric water and align closely with predictions from a biochemical model. Reconstructed temperature changes, derived fromδ2HTMvalues, agree well with instrumental data in North American since 1932. Our results reveal that the latitudinal gradients ofδ2HTMvalues closely resembleδ2Hprecipvalues across North America. When combining these spatial patterns withδ2HTMandδ2Hprecipdata from Europe a strong correlation (R2= 0.94, p < 0.001) and a consistent fractionation of –193 ± 13 mUr, representative for Northern Hemisphere mid-to-high latitude sites, is established. The validation across North American and European transects serves as a foundational basis for advancing applications in biogeochemistry and paleoclimate research.
Managing risks and trade-offs in multispecies fisheries: the role of trophic control and price asymmetry
Authors: Villain Théo , Poggiale Jean-Christophe , Loeuille Nicolas 
Published: February 2025

AbstractEcosystem-based fisheries management (EBFM) aims to balance ecological and economic goals while employing precautionary measures to address uncertainties in knowledge and management. This study investigates fishing strategies to achieve this balance while minimizing the associated risks. Using a simplified prey-predator model, we explored various scenarios reflecting the diversity of global fisheries. The model integrates key ecological dynamics (bottom-up and top-down forces), economic factors (price structures), and aggregates the diversity of fishing practices by distributing fishing mortality across species. Our findings reveal that predators are always more affected by fishing than prey, regardless of the effort distribution. High yields are achieved by reducing predator densities—either maximizing predator catches when they are highly valued or reducing predation pressure to enhance prey harvests when prey prices are high. Such strategies result in significant ecological impacts, leading to systematic trade-offs. Elevated prey prices and top-down controlled systems intensify these trade-offs, increasing ecological risks. Regarding uncertainties, we demonstrate that maximizing yields poses risks to both biodiversity and profitability. Reconciliation is challenging but feasible when both species are fished. This balance can be achieved only in bottom-up controlled systems where prey valuation is not disproportionately high compared to predator prices.
Nonconscious processing of fearful and neutral faces modulates the N170
Authors: Bruchmann Maximilian , Schindler Sebastian , Breitwieser Pia , Tilly Lynn , Bölte Jens , Dellert Torge , Straube Thomas 
Published: February 2025

AbstractPrioritized processing of fearful compared to neutral faces is reflected in differential event-related potentials (ERPs). There is an ongoing debate about the extent to which faces in general and fearful faces in particular enhance specific ERPs if they are not consciously perceived. Specifically, the N170 has been suggested as the most likely candidate for enhanced processing of nonconscious fearful faces. In this pre-registered study, we tested in a large sample based on sequential Bayesian sampling (N= 64) whether early components of the ERP (P1, N170, and early posterior negativity; EPN) discriminate between fearful faces, neutral faces, and non-facial control stimuli. Consciousness was manipulated by presenting stimuli for 17 ms in a backward masking design, with the mask following immediately or after a delay of 200 ms. Participants rated their subjective perception on a perceptual awareness scale in each trial. Importantly, only trials in which nothing but the mask was perceived were considered for the analysis of nonconscious effects. The results showed strong evidence for an increased N170 in response to nonconscious fearful compared to neutral faces; however, this difference was significantly smaller than in the conscious condition. Furthermore, we obtained strong evidence for N170 differences between nonconscious faces and no-faces. For P1 and EPN amplitudes, no significant effects were observed in the nonconscious conditions, although exploratory analyses of the P1 peak interval suggest nonconscious face-no-face differentiation. These results support the notion that nonconscious emotion and face processing are detectable in early neural responses and show that these nonconscious effects are considerably weaker than the corresponding conscious effects.
Dicer loss in Müller glia leads to a defined sequence of pathological events beginning with cone dysfunction
Authors: Larbi Daniel , Rief Alexander M. , Kang Seoyoung , Chen Shaoheng , Batsuuri Khulan , Fuhrmann Sabine , Viswanathan Suresh , Wohl Stefanie G. 
Published: February 2025

AbstractPurposeThe loss of Dicer in Müller glia (MG) results in severe photoreceptor degeneration as it occurs in retinitis pigmentosa or AMD. However, the sequence of events leading to this severe degenerative state is unknown. The aim of this study was to conduct a chronological functional and structural characterization of the pathological events in MG-specific Dicer-cKO micein vivoand histologically.MethodsTo delete Dicer and mature microRNAs (miRNAs) in MG, two conditional Dicer1 knock-out mouse strains namely RlbpCre:Dicer-cKOMGand GlastCre:Dicer-cKOMG,were created. Optical coherence tomography (OCT), electroretinograms (ERGs) as well as histological analyses were conducted to investigate structural and functional changes up to six months after Dicer deletion.ResultsDicer/miRNA loss in MG leads to 1) impairments of the external limiting membrane (ELM) – retinal pigment epithelium (RPE), 2) cone photoreceptor dysfunction and 3) retinal remodeling and functional loss of the inner retina, 1, 3 and 6 months after Dicer loss, respectively, in both strains. Furthermore, in the Rlbp:Dicer-cKOMGstrain, rod photoreceptor impairment was found 4 months after Dicer depletion (4) accompanied by alteration of RPE integrity (5).ConclusionsMG Dicer loss in the adult mouse retina impacts cone function prior to any measurable changes in rod function, suggesting a pivotal role for MG Dicer and miRNAs in supporting cone health. A partially impaired RPE however seems to accelerate rod degeneration and overall degenerative events.
Gut-Brain Hydraulics: Brain motion and CSF circulation is driven by mechanical coupling with the abdomen
Authors: Garborg C. Spencer , Ghitti Beatrice , Zhang Qingguang , Ricotta Joseph M. , Frank Noah , Mueller Sara J. , Greenawalt Denver I. , Turner Kevin L. , Kedarasetti Ravi T. , Mostafa Marceline , Lee Hyunseok , Costanzo Francesco , Drew Patrick J. 
Published: February 2025

AbstractThe brain moves within the skull, but the drivers and function of this motion are not understood. We visualized brain motion relative to the skull in awake head-fixed mice using high-speed, multi-plane two-photon microscopy. Brain motion was primarily rostrally and laterally directed, and was tightly correlated with locomotion, but not with respiration or the cardiac cycle. Electromyography recordings in abdominal muscles and microCT reconstructions of the trunk and spinal vasculature showed that brain motion was driven by abdominal muscle contractions that activate a hydraulic-like vascular connection between the nervous system and the abdominal cavity. Externally-applied abdominal pressure generated brain motion similar to those seen during abdominal muscle contractions. Simulations showed that brain motion drives substantial volumes of interstitial fluid through and out of the brain (at volumetric rates several times higher than production) into the subarachnoid space, in the opposite direction of fluid flow seen during sleep. The brain is hydraulically linked to the abdominal compartment, and fluid flow in the brain is coupled to body movements, providing a mechanism by which the mechanics of the viscera directly impact brain health.
FETCH enables fluorescent labeling of membrane proteinsin vivowith spatiotemporal control inDrosophila
Authors: Rostam Kevin D. , Morano Nicholas C. , Menon Kaushiki P. , Lopez Davys H. , Shapiro Lawrence , Zinn Kai , Feng Siqian , Mann Richard S. 
Published: February 2025

ABSTRACTFluorescent labeling approaches are crucial for elucidating protein function and dynamics. While enhancer trapping inDrosophilahas been useful for the characterization of gene transcription, protein-specific visualizationin vivohas been more elusive. To overcome these limitations, we developed Fluorescent Endogenous Tagging with a Covalent Hook (FETCH) to label cell surface proteins (CSPs)in vivothrough a stable covalent bond mediated by the DogTag-DogCatcher peptide partner system1. FETCH leverages a spontaneous covalent isopeptide bond that forms between the 23-amino acid DogTag and the 15-kDa DogCatcher. Unlike most tags that work best at protein termini, DogTag is optimized for function in protein loops, expanding the range of sites that can be targeted in proteins. In FETCH, DogTag is introduced into extracellular loops of CSPs through genome engineering, enabling covalent bond formation with a genetically encoded DogCatcher-GFP fusion protein that can be secreted from a variety of cell types. We describe a flow cytometry-based platform for the identification of efficient DogTag insertion sitesin vitroand demonstrate the ability to visualize both tagged DIP-α and Dpr10in vivo, two immunoglobulin superfamily proteins that facilitate neuronal target recognition atDrosophilaneuromuscular junctions and brain synapses. The versatility of FETCH enables fluorescent labeling with precise temporal and spatial controlin vivo, enabling applications previously unfeasible.
In vivo targeted gene delivery using Adenovirus-antibody molecular glue conjugates
Authors: Rice-Boucher Paul J. , Kashentseva Elena A. , Dmitriev Igor P. , Guo Hongjie , Tremblay Jacqueline M. , Shoemaker Charles B. , Curiel David T. , Lu Zhi Hong 
Published: February 2025

AbstractSafe and efficient nucleic acid delivery to targeted cell populations remains a significant unmet need in the fields of cell and gene therapy. Towards this end, we pursued Adenoviral vectors genetically modified with the “DogTag” molecular glue peptide, which forms a spontaneous covalent bond with its partner protein, “DogCatcher”. Genetic fusion of DogCatcher to single-domain or single-chain antibodies allowed covalent tethering of the antibody at defined locales on the vector capsid. This modification allowed simple, effective and exclusive targeting of the vector to cells bound by the linked antibody. This dramatically enhanced gene transfer into primary B and T cellsin vitroandin vivoin mice. These studies form the basis of a novel method for targeting Adenovirus that is functional in stringentin vivocontexts and can be combined with additional well characterized Adenovirus modifications towards applications in cell engineering, gene therapy, vaccines, oncolytics, and others.
Gene module-trait network analysis uncovers cell type specific systems and genes relevant to Alzheimer’s Disease
Authors: de Paiva Lopes Katia , Vialle Ricardo A. , Green Gilad , Fujita Masashi , Gaiteri Chris , Menon Vilas , Schneider Julie A. , Wang Yanling , De Jager Philip L. , Habib Naomi , Tasaki Shinya , Bennett David A. 
Published: February 2025

AbstractAlzheimer’s Disease (AD) is marked by the accumulation of pathology, neuronal loss, and gliosis and frequently accompanied by cognitive decline. Understanding brain cell interactions is key to identifying new therapeutic targets to slow its progression. Here, we used systems biology methods to analyze single-nucleus RNA sequencing (snRNASeq) data generated from dorsolateral prefrontal cortex (DLPFC) tissues of 424 participants in the Religious Orders Study or the Rush Memory and Aging Project (ROSMAP). We identified modules of co-regulated genes in seven major cell types, assigned them to coherent cellular processes, and assessed which modules were associated with AD traits such as cognitive decline, tangle density, and amyloid-β deposition. Coexpression network structure was conserved in the majority of modules across cell types, but we also found distinct communities with altered connectivity, especially when compared to bulk RNASeq, suggesting cell-specific gene co-regulation. These coexpression modules can also capture signatures of cell subpopulations and be influenced by cell proportions. Using a Bayesian network framework, we modeled the direction of relationships between the modules and AD progression. We highlight two key modules, a microglia module (mic_M46), associated with tangles; and an astrocyte module (ast_M19), associated with cognitive decline. Our work provides cell-specific molecular networks modeling the molecular events leading to AD.
Post-transcriptional monoadenylation by TENT2 terminates human RNA polymerase III transcript 3’ end processing and promotes 7SL RNA biogenesis
Authors: Ocheltree Cody , Skrable Blake , Pimentel Anastasia , Nicholson-Shaw Timothy , Lee Suzanne R. , Lykke-Andersen Jens 
Published: February 2025

ABSTRACTSmall non-coding RNAs (sncRNAs) are subject to a variety of 3’ end trimming and tailing activities during biogenesis, which dictate whether they undergo maturation or are instead subjected to degradation. To investigate the dynamics of human sncRNA 3’ end processing at a global level we performed genome-wide 3’ end sequencing of nascently-transcribed and steady state sncRNAs. This revealed widespread post-transcriptional adenylation of nascent sncRNAs, which came in two distinct varieties. One is characterized by oligoadenylation, which is transient, promoted by TENT4A/4B polymerases, and observed primarily on unstable snoRNAs and scaRNAs that are not fully processed at their 3’ ends. The other is characterized by monoadenylation, which is broadly catalyzed by TENT2 and stably accumulates at the 3’- end of many RNA Polymerase-III-transcribed (Pol-III) RNAs as well as a subset of small nuclear RNAs. This monoadenylation event terminates 3’ end uridylation/deuridylation dynamics characteristic of nascent Pol-III RNAs and, in the case of 7SL RNAs, prevents their accumulation with nuclear La protein and promotes their biogenesis towards assembly into cytoplasmic signal recognition particles.