bluuebunny/crossref_metadata_2025_split huggingface dataset:
Notch signaling pathway in osteogenesis, bone development, metabolism, and diseases
Authors: Dilawar Muhammad , Yu Xuan , Jin Yuanyuan , Yang Jing , Lin Sisi , Liao Junguang , Dai Qi , Zhang Xingen , Nisar Muhammad Farrukh , Chen Guiqian 
Published: February 2025

AbstractThe skeletal system provides vital importance to support organ development and functions. The Notch signaling pathway possesses well‐established functions in organ development and cellular homeostasis. The Notch signaling pathway comprises five typical ligands (JAG1, JAG2, DLL1, DLL3, and DLL4), four receptors (Notch1‐4), and four intracellular domains (NICD1‐4). Each component of the Notch signaling pathway has been demonstrated to be fundamental in osteoblast differentiation and bone formation. The dysregulation in the Notch signaling pathway is highly linked with skeletal disorders or diseases at the developmental and postnatal stages. Recent studies have highlighted the importance of the elements of the Notch signaling pathway in the skeletal system, as well as its interaction with signaling, such as Wnt/β‐catenin, BMP, TGF‐β, FGF, autophagy, and hedgehog (Hh) to construct a potential gene regulatory network to orchestrate osteogenesis and ossification. Our review has provided a comprehensive summary of the Notch signaling pathway in the skeletal system, as well as the insights targeting Notch signaling for innovative potential drug discovery targets or therapeutic interventions to treat bone disorders, such as osteoporosis and osteoarthritis. An in‐depth molecular mechanistic strategy to modulate the Notch signaling pathway and its associated signaling pathway will be encouraged for consideration to trigger enhanced therapeutic approaches for bone disorders by defining Notch‐regulating drugs for clinical use.
The aryl hydrocarbon receptor affects the inflammatory response of bone marrow mesenchymal stem cell via the hippo–YAP pathway to exacerbate systemic lupus erythematosus
Authors: Yang Xingzhi , Si Mingjun , Liu Ting , Yang Jingyu , Jiang Lili , Sun Ximeng , Yu Haitao 
Published: February 2025

AbstractThe impaired immune regulation of bone marrow mesenchymal stem cells (BM‐MSCs) disrupts T‐cell homeostasis and alters the immunological environment in individuals with systemic lupus erythematosus (SLE). However, the specific molecular mechanisms underlying the defective immune functions of BM‐MSCs in patients with SLE remain unclear. Here, we report that BM‐MSCs derived from MRL/lpr mice exhibit a diminished proliferative capacity, elevated levels of aryl hydrocarbon receptor (AhR) and increased levels of secreted proinflammatory cytokines, including IL‐1β, IL‐6, and TNF‐α. These BM‐MSCs can increase splenocyte proliferation and upregulate the expression of retinoic acid receptor‐related orphan receptor gamma t (RORγt) in EL4 cells, which constitute a murine T‐cell lymphoblastic leukemia cell line. Furthermore, MRL/lpr mice treated with FICZ (an AhR agonist) displayed splenomegaly and exacerbated renal pathology, alongside increased levels of AhR, and inflammatory cytokines. Notably, BM‐MSCs isolated from FICZ‐treated mice also facilitated splenocyte proliferation and increased the RORγt level in EL4 cells during coculture. Similar effects were observed when BM‐MSCs were exposed to FICZ in vitro, but these effects were reversed by the administration of CH223191 (an AhR antagonist). Additionally, the expression of Yes‐associated protein (YAP) was significantly increased in both MRL/lpr mice and FICZ‐treated BM‐MSCs. Importantly, verteporfin (a Hippo–YAP inhibitor) attenuated the elevated RORγt levels in EL4 cells and the increased splenocyte proliferation. This study advances our understanding of SLE pathogenesis by pinpointing AhR as a pivotal modulator of the inflammatory response of BM‐MSCs through the Hippo–YAP pathway in individuals with SLE. This novel insight not only enriches the current knowledge of SLE mechanisms but also highlights new potential therapeutic targets for SLE.
ralphi: a deep reinforcement learning framework for haplotype assembly
Authors: Battistella Enzo , Maheshwari Anant , Ekim Barış , Berger Bonnie , Popic Victoria 
Published: February 2025

AbstractHaplotype assembly is the problem of reconstructing the combination of alleles on the maternally and paternally inherited chromosome copies. Individual haplotypes are essential to our understanding of how combinations of different variants impact phenotype. In this work, we focus on read-based haplotype assembly of individual diploid genomes, which reconstructs the two haplotypes directly from read alignments at variant loci. We introduceralphi, a novel deep reinforcement learning framework for haplotype assembly, which integrates the representational power of deep learning with reinforcement learning to accurately partition read fragments into their respective haplotype sets. To set the reward objective for reinforcement learning, our approach uses the classic reduction of the problem to themaximum fragment cutformulation on fragment graphs, where nodes correspond to reads and edge weights capture the conflict or agreement of the reads at shared variant sites. We trainedralphion a diverse dataset of fragment graph topologies derived from genomes in the 1000 Genomes Project. We show thatralphiconsistently achieves lower error rates at comparable or longer haplotype block lengths over the state of the art for short and long ONT reads at varying coverage in standard human genome benchmarks.ralphiis available athttps://github.com/PopicLab/ralphi.
Using The Cancer Genome Atlas from cBioPortal to Develop Genomic Datasets for Machine Learning Assisted Cancer Treatment
Authors: Asaduzzaman Abu , Thompson Christian C. , Sibai Fadi N. , Uddin Md J. 
Published: February 2025

AbstractPredicting the impact of genetic mutations is crucial for understanding diseases like cancer. Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant From Tolerant (SIFT) are key tools for assessing how amino acid substitutions affect protein function and mutation pathogenicity. To our knowledge, no ready-to-use genomic dataset exists for prediction models to identify potentially harmful mutations, which could support research and clinical decisions. This study develops genomic and non-genomic datasets using The Cancer Genome Atlas (TCGA) from cBioPortal and applies machine learning models to predict PolyPhen and SIFT scores. We explore three classification models: Random Forest (RF), Extreme Gradient Boosting (XGBoost), and an ensemble RF-XGBoost model. Experimental results show that genomic data yields more accurate predictions than non-genomic data. The ensemble RF-XGBoost model performs best on genomic data, achieving average accuracies of 88.43% for PolyPhen and 95.13% for SIFT, highlighting the potential of artificial intelligence in genetic mutation analysis for disease treatment.
DAF-18/PTEN protects LIN-35/Rb from CLP-1/CAPN-mediated cleavage to promote starvation resistance
Authors: Chen Jingxian , Chitrakar Rojin , Baugh L. Ryan 
Published: February 2025

ABSTRACTStarvation resistance is a fundamental trait with profound influence on fitness and disease risk. DAF-18, theC. elegansortholog of the tumor suppressor PTEN, promotes starvation resistance. PTEN is a dual phosphatase, and DAF-18 promotes starvation resistance as a lipid phosphatase by antagonizing insulin/IGF and PI3K signaling, activating the tumor suppressor DAF-16/FoxO. However, if or how DAF-18/PTEN protein-phosphatase activity promotes starvation resistance is unknown. Using genetic, genomic, bioinformatic, and biochemical approaches, we identified theC. elegansretinoblastoma/RB protein homolog, LIN-35/Rb, as a critical mediator of the effect of DAF-18/PTEN on starvation resistance. We show that DAF-18/PTEN protects LIN-35/Rb from cleavage by the μ-Calpain homolog CLP-1/CAPN, and that LIN-35/Rb together with the repressive DREAM complex promote starvation resistance. We conclude that the tumor suppressors DAF-18/PTEN and LIN-35/Rb function in a linear pathway, with LIN-35/Rb and the rest of the DREAM complex functioning as a transcriptional effector of DAF-18/PTEN protein-phosphatase activity resulting in repression of germline gene expression. This work is significant for revealing a network of tumor suppressors that promote survival during cellular and developmental quiescence.
Human ADME/PK is lost in translation and prediction fromin silicotoin vitrotoin vivo
Authors: Fagerholm Urban , Hellberg Sven 
Published: February 2025

ABSTRACTBackgroundMeasurements and predictions of aqueous solubility (S), apparent cell permeability (Papp), unbound microsomal intrinsic clearance (CLint,u), unbound fraction in plasma (fu), log D, Lipinski’s Rule of 5 (Ro5) and BBB+/BBB- (blood-brain-barrier) are commonly used in early drug discovery to evaluate whether compounds are likely to have adequate ADME/PK in humans. The main objective was to evaluate the validity and proposed thresholds for commonly usedin silicotoin vitro(with particular interest in the ADMET Predictor software) andin vitrotoin vivohuman ADME/PK prediction methods, and physicochemical estimates and rules of thumb. A secondary aim was to compare validity and thresholds to that for the prediction software ANDROMEDA.MethodsData were collected from literature and own studies. Main measures of validity were Q2(true predictive accuracy;in silicomodels), R2(correlation coefficient;in vitromodels), Q2• R2(for translation fromin silicotoin vivoviain vitro), skewness, range, % correct predicted class and clinical relevance.Results and DiscussionPoor accuracies (Q2• R2=0.05, 0.05, 0.36 and 0.45; ∼0 at low to moderate, decision-critical levels) and class predictions, limited ranges (not covering low to moderate estimates), systematic errors (often considerable overprediction at low values), poor clinical relevance and inadequate thresholds were found. Predictive accuracy was mainly lost in the translation fromin vitrotoin vivo. Log D and Ro5 are poor predictors of oral bioavailability and half-life. Ro5 produced 63 % false negatives for prediction of poor/good oral absorption. The overall mean Q2for ANDROMEDA was 3 times higher (0.57vs0.2). Advantages with ANDROMEDA compared toin vitrodata-basedin silicomodels include wider application domain (high resolution at low values), extrahepatic elimination models, minimal skewness, clinical relevance, balanced thresholds, and compound- and parameter-unique confidence intervals. ANDROMEDA successfully predicted the human clinical ADME/PK for all small drugs marketed in 2021, while thein silicotoin vitrotoin vivoapproach was out of reach for all.ConclusionThe validity of investigated methodologies (including ADMET Predictor) and thresholds were overall very low. Unless both predicted S, permeability and fuare high and CLintis moderate (an overall criterium not met for investigated modern small drugs) one is more or less lost in the translation, and will jeopardize compound selection and optimization. This clearly shows the need for better and thoroughly validated prediction models and software. Marked improvements in accuracy, range, balance and clinical relevance were achieved with ANDROMEDA, which predicts human clinical ADME/PK directly from chemical structures and has undergone extensive validation.
Single-cell transcriptomics identifies a dampened neutrophil function and accentuated T-cell cytotoxicity in tobacco flavored e-cigarette exposed mouse lungs
Authors: Kaur G , Lamb T , Tjitropranoto A , Rahman Irfan 
Published: February 2025

AbstractE-cigarettes (e-cigs) are a public health concern for young adults due to their popularity and evidence for increased oxidative stress and immunotoxicity. Yet an extensive study defining the cell-specific immune changes upon exposure to flavored e-cigs remains elusive. To understand the immunological lung landscape upon acute nose-only exposure of C57BL/6J to flavored e-cig aerosols we performed single-cell RNA sequencing (scRNA seq). scRNA profiles of 71,725 cells were generated from control and treatment groups (n=2/sex/group). A distinct phenotype of Ly6G-neutrophils was identified in lungs exposed to tobacco flavored e-cig aerosol which demonstrated dampened IL-1 mediated and pattern recognition signaling as compared to air controls. Differential gene expression analyses identified dysregulation of T-cell mediated pro-inflammation (Cct7,Cct8) and stress-response signals (Neurl3,Stap1,CirbpandHtr2c)in the lungs of mice exposed to e-cig aerosols, with pronounced effects for tobacco flavor. Flow cytometry analyses and cytokine/chemokine assessments within the lungs corroborated the scRNA seq data, demonstrating a significant increase in T-cell percentages and levels of T-cell associated cytokine/chemokines in the lungs of tobacco-flavored aerosol exposed mice. Increased levels ofKlra4andKlra8expression also suggest an enhanced natural killer (NK) cell activity in this mouse group. Overall, this is a pilot study identifying increase in the percentages of Ly6G-neutrophils that may be responsible for dampened innate immune responses and heightened T-cell cytotoxicity in lungs of tobacco-flavored e-cig aerosol exposed mice. In addition, we provide preliminary evidence for sex-specific changes in the transcriptional landscape of mouse lungs upon exposure to e-cig aerosol, an area that warrants further study.
Indigenous gut microbes modulate neural cell state and neurodegenerative disease susceptibility
Authors: Blackmer-Raynolds Lisa , Sampson Maureen M. , Kozlov Anna , Yang Aimee , Lipson Lyndsey , Hamilton Adam M. , Kelly Sean D. , Chopra Pankaj , Chang Jianjun , Sloan Steven A. , Sampson Timothy R. 
Published: February 2025

SUMMARYThe native microbiome influences a plethora of host processes, including neurological function. However, its impacts on diverse brain cell types remains poorly understood. Here, we performed single nucleus RNA sequencing on hippocampi from wildtype, germ-free mice and reveal the microbiome-dependent transcriptional landscape across all major neural cell types. We found conserved impacts on key adaptive immune and neurodegenerative transcriptional pathways, underscoring the microbiome’s contributions to disease-relevant processes. Mono-colonization with select indigenous microbes identified species-specific effects on the transcriptional state of brain myeloid cells. Colonization byEscherichia coliinduced a distinct adaptive immune and neurogenerative disease-associated cell state, suggesting increased disease susceptibility. Indeed,E. coliexposure in the 5xFAD mouse model resulted in exacerbated cognitive decline and amyloid pathology, demonstrating its sufficiency to worsen Alzheimer’s disease-relevant outcomes. Together, these results emphasize the broad, species-specific, microbiome-dependent consequences on neurological transcriptional state and highlight the capacity of specific microbes to modulate disease susceptibility.HighlightsThe microbiome impacts the transcriptional landscape of all major brain cell types.Discrete microbes specifically modulate resident myeloid cell status.GutE. colitriggers dynamic transcriptional responses across neural cell types.Exposure toE. coliexacerbates behavioral and cellular pathologies in 5xFAD mice.
Paired primary-metastasis patient-derived organoids and mouse models identify phenotypic evolution and druggable dependencies of peritoneal metastasis from appendiceal cancer
Authors: Mahmoud Ahmed , Choi Philip H. , Sukhwa Christine , Pintar Jura , Walch Henry , Zhao Nan , Bermeo Jonathan , Chung Sebastian , Raghavan Manisha , Bapat Samhita , Jiang Qingwen , Karagkounis Georgios , Meredith Julia , Giarrizzo Michael , Firat Canan , Cercek Andrea , Foote Michael B. , Schultz Nikolaus , Chatila Walid K. , Nash Garrett M. , Shia Jinru , Sanchez-Vega Francisco , Larson Steven , Dar Arvin C. , Rosen Neal , Ganesh Karuna 
Published: February 2025

SummaryPeritoneal carcinomatosis is a common yet deadly manifestation of gastrointestinal cancers, with few effective treatments. To identify targetable determinants of peritoneal metastasis, we focused on appendiceal adenocarcinoma (AC), a gastrointestinal cancer that metastasizes almost exclusively to the peritoneum. Current treatments are extrapolated from colorectal cancer (CRC), yet AC has distinct genomic alterations, mucinous morphology and peritoneum restricted metastatic pattern. Further, no stable preclinical models of AC exist, limiting drug discovery and representing an unmet clinical need. We establish a first-in-class stable biobank of 16 long-term cultured AC patient-derived organoids (PDOs), including 3 matched, simultaneously resected primary AC-peritoneal carcinomatosis (AC-PC) pairs. By enriching for cancer cells, AC PDOs enable accurate genomic characterization relative to paucicellular AC tissue. We establish an organoid orthotopic intraperitoneal xenograft model that recapitulates diffuse peritoneal carcinomatosis and show that PC-organoids retain increased metastatic capacity, decreased growth factor dependency and sensitivity to standard of care chemotherapy relative to matched primary AC organoids. Single cell profiling of AC-PC pairs reveals dedifferentiation from mucinous differentiated states in primary AC into intestinal stem cell and fetal progenitor states in AC-PC, with upregulation of oncogenic signaling pathways. Through hypothesis-driven drug testing, we identify KRASMULTI-ON inhibitor RMC-7977 and Wnt-targeting tyrosine kinase inhibitor WNTinib as novel, clinically actionable strategies to target AC-PC more effectively.
Reduced plasma hexosylceramides in frontotemporal dementia are a biomarker of white matter integrity
Authors: Marian Oana C. , Matis Sophie , Dobson-Stone Carol , Kim Woojin S. , Kwok John B. , Piguet Olivier , Halliday Glenda M. , Landin-Romero Ramon , Don Anthony S. 
Published: February 2025

AbstractINTRODUCTIONBlood biomarkers are needed to facilitate new therapeutic trials and improve management of behavioural variant frontotemporal dementia (bvFTD). Since altered white matter integrity is characteristic of bvFTD, this study aimed to determine if plasma levels of myelin-enriched glycolipids are altered in bvFTD and correlate with white matter integrity.METHODSNineteen glycolipids were quantified in bvFTD (n=31) and control (n=26) plasma samples. White matter integrity was assessed using MRI-derived fibre tract density and cross-section (FDC).RESULTSEleven lipids were significantly lower in bvFTD compared to control subjects, seven were inversely correlated with disease duration, and twelve were positively correlated with cognitive performance, with C22:0 hexosylceramide most strongly correlated. FDC was lower in frontotemporal white matter tracts of bvFTD compared to control subjects, and plasma C22:0 hexosylceramide was significantly correlated with FDC in these tracts.DISCUSSIONCirculating glycolipids may be a valuable biomarker of myelin integrity and disease progression in FTD.
Generation of appropriate protein structures for virtual screening using AlphaFold3 predicted protein–ligand complexes
Authors: Yasumitsu Yuki , Ohue Masahito 
Published: February 2025

AbstractIn early drug discovery, virtual screening—a computational method for selecting candidate compounds—helps reduce development costs. Traditionally, structure-based virtual screening required experimental protein structures, but advances like AlphaFold2 have begun to overcome this limitation. However, AlphaFold2 does not capture ligand-induced conformational changes (transition from apo to holo forms), limiting its utility for protein–ligand docking. In this study, we evaluate AlphaFold3, which predicts protein–ligand complex structures when both protein and ligand inputs are provided. Using the DUD-E dataset and Uni-Dock, we show that holo structures predicted with ligand inclusion yield higher screening performance than apo structures generated without ligand input. Notably, incorporating active ligands enhances screening performance, whereas inactive (decoy) ligands produce results similar to apo predictions. The use of template structures further improves outcomes. We also analyze the impact of ligand molecular weight, binding pocket location, and AlphaFold3 ranking scores on screening performance. Our findings indicate that lower molecular weight ligands tend to generate predicted structures that more closely resemble experimental holo structures, thus improving screening efficacy. Conversely, larger ligands (700–800) can induce open binding pockets that favor screening for some targets. These results suggest that employing AlphaFold3 with appropriate ligand inputs is a promising strategy for virtual screening, particularly for proteins lacking experimental structural data.
Dissecting Force Transmission across SUN Proteins Using Nuclear Tension Sensors
Authors: Wang Jinfeng , Qiu Juhui , Lu Shaoying , Ding Saiyang , Xu Fangning , Luo Yanfeng , Zhou Jing , Peng Qin 
Published: February 2025

AbstractForces on the linker of the nucleoskeleton and cytoskeleton (LINC) complex control nuclear mechano-sensing and mechano-adaptation. However, the force transmission dynamics across the LINC complex are not fully understood, mainly because of the lack of imaging tools. We developed a set of genetically-encoded fluorescence resonance energy transfer (FRET)-based nuclear tension sensors (NuTS) that measure tension forces across SUN1/2 proteins in living cells with high sensitivity. SUN2-based NuTS (NuTS2) responded rapidly to mechanical changes in cell contractility and matrix stiffness. Notably, NuTS2 dynamically showed force transmission with high spatiotemporal resolution during cell adhesion, migration and squeeze. We also used NuTS2 to monitor tension force changes as the notochord matures in zebrafish development. NuTS2 detected a gradient tension force that increased from the posterior tail buds to the anterior as vacuoles expanded in notochord cells. Force reduction affected notochord maturation and zebrafish embryo development. Our results provide a biophysical cue for dissecting how force transmission on SUN2 protein regulates embryo development.TeaserNuclear tension sensor (NuTS) was developed for direct force measurement across SUN proteins in living cells and zebrafish.