Mapping fusion-driven cell reprogramming through integrative single-cell computational frameworks [0.03%]
通过综合单细胞计算框架绘制融合驱动的细胞重编程图谱
Fateme Nazaryabrbekoh,JoAnne Huang,Syeda S Shoaib et al.
Fateme Nazaryabrbekoh et al.
Cell fusion generates hybrid cells with unique traits. To understand the transcriptional and signaling alterations after fusion, we analyzed a published single-cell RNA-sequencing dataset of fused murine cardiomyocytes (mHL1) and mesenchyma...
Modelling dysfunction-specific interventions for seizure termination in epilepsy [0.03%]
构建针对癫痫 seizures 终止的紊乱特异性干预措施模型
Aravind Kumar Kamaraj,Matthew Parker Szuromi
Aravind Kumar Kamaraj
Epileptic seizures result from abnormal synchronous neuronal firing caused by an imbalance between excitatory and inhibitory neurotransmission. While most seizures are self-limiting, those lasting over five minutes, termed status epilepticu...
Author Correction: Neural mechanisms balancing accuracy and flexibility in working memory and decision tasks [0.03%]
作者更正：在工作记忆和决策任务中平衡准确性和灵活性的神经机制
Han Yan,Jin Wang
Han Yan
Published Erratum
NPJ systems biology and applications. 2025 Dec 16;11(1):138. DOI:10.1038/s41540-025-00634-7 2025
Biophysical simulation enables segmentation and nervous system atlas mapping for image first spatial omics [0.03%]
生物物理模拟使图像优先空间组学的分割和神经系统图谱映射成为可能
Lina Mohammed Ali,Aldrin Kay Yuen Yim,Emanuel Gerbi et al.
Lina Mohammed Ali et al.
Spatial omics (SO) produces high-definition mapping of subcellular molecules within tissue samples. Mapping transcripts to anatomical regions requires segmentation, but this remains challenging in tissue cross-sections with tubular structur...
Unraveling anti-inflammatory metabolic signatures of Glycyrrhiza uralensis and isoliquiritigenin through multiomics [0.03%]
基于多组学的甘草及光果甘草素抗炎代谢标志物研究
Saki Kiuchi,Mi Hwa Chung,Hina Sakai et al.
Saki Kiuchi et al.
Glycyrrhiza uralensis, a key component of over 70% of traditional herbal medicines (Kampo) in Japan, exhibits diverse pharmacological effects, including immunoregulation, anti-tumor, and antioxidant properties. Despite over 300 identified c...
Modelling reliable metabolic phenotypes by analysing the context-specific transcriptomics data [0.03%]
通过分析上下文特异性转录组数据建模可靠的代谢表型
Pavan Kumar S,Nirav Pravinbhai Bhatt
Pavan Kumar S
Genome-scale metabolic models (GEMs) are valuable tools for investigating healthy and disease states, but often lack the specificity to capture context-dependent metabolic adaptations. Tailoring GEMs using transcriptomic data is crucial for...
Challenges and opportunities for oncology drug repurposing informed by synthetic lethality [0.03%]
合成致死性对肿瘤药物再定位的挑战与机遇
Michael Vermeulen,Andrew W Craig,Tomas Babak
Michael Vermeulen
Although two-thirds of cancers arise from loss-of-function mutations in tumor suppressor genes, there are few approved targeted therapies linked to these alterations. Synthetic lethality offers a promising strategy to treat such cancers by ...
Measurable imaging-based changes in enhancement of intrahepatic cholangiocarcinoma after radiotherapy reflect physical mechanisms of response [0.03%]
基于影像学的可测量的放射治疗后肝内胆管细胞癌增强变化反映其物理反应机制
Brian De,Prashant Dogra,Mohamed Zaid et al.
Brian De et al.
Escalated doses of radiotherapy associate with improved local control and overall survival (OS) in intrahepatic cholangiocarcinoma (iCCA), but personalization remains limited because conventional size-based CT criteria correlate poorly with...
Javad Aminian-Dehkordi,Mohammad Parsa,Andrew Dickson et al.
Javad Aminian-Dehkordi et al.
Predicting how gut microbial communities assemble and change requires models that capture the underlying mechanisms driving interspecies interactions, not just taxonomic correlations. We present SIMBA, a simulation-augmented graph neural ne...
Feature learning augmented with sampling and heuristics (FLASH) improves model performance and biomarker identification [0.03%]
采样和启发式特征学习（FLASH）可提高模型性能和生物标志物识别能力
Shivam Kumar,Abhinav Agarwal,Samrat Chatterjee
Shivam Kumar
Big biological datasets, such as gene expression profiles, often contain redundant features that degrade model performance and limit generalization across independent datasets with complexities like class imbalance and hidden sub-clusters. ...