Results 261 to 270 of about 422,605 (335)

Allosteric DNAzyme‐Enabled Sensitive and Multiplex Detection of Biomarkers for Rapid Diagnosis of Urinary Tract Infections

Advanced Science, EarlyView.
A catalytic allosteric DNAzyme assay (SMART) is developed by engineering DNAzyme into a unimolecular biosensor, enabling highly sensitive and multiplex detection of small molecules and nucleic acids. SMART enables extraction‐free, one‐pot, one‐step, isothermal, and cost‐effective detection of biological markers, achieving >95% accuracy for rapid ...
Yanzhe Shen, Chenzhi Shi, Xiaowei Ma, Pengfei Hou, Haomin Zhang, Juanxiu Qin, Li Pan, Guilin Li, Lifei Gao, Qian Ma, Donglei Yang, Min Li, Pengfei Wang   +12 more
wiley   +1 more source

Application of untargeted plasma metabolomics and machine learning to construct a diagnostic model for hypertrophic cardiomyopathy: a case-control study. [PDF]

Metabolomics
Li R, Wang B, Shan B, Sun M, Ta S, Zhao J, Kang N, Yang F, Yuan Y, Li X, Wang H, Fan L, Zheng H, Wang J, Liu L.   +14 more
europepmc   +1 more source

Advances in Gastric Cancer Research: Insights Into Carcinogenesis, the Tumor Microenvironment, Metastasis, and Factors Influencing Prognosis

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background The Department of Gastroenterological Surgery at Kumamoto University has maintained a commitment to integrating cutting‐edge clinical practice with fundamental research, particularly concerning malignant diseases of the digestive tract.
Hideo Baba, Takatsugu Ishimoto, Yoshifumi Baba, Hiromitsu Hayashi, Masaaki Iwatsuki   +4 more
wiley   +1 more source

What's in a name? Metabolite identification: challenges and pitfalls in untargeted metabolomics. [PDF]

Metabolomics
Theodoridis G, Fiehn O, Holčapek M, Goodacre R, Raftery D, Plumb R, Ebbels TMD, Witting M, Gika H, Wilson ID.   +9 more
europepmc   +1 more source

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

Advanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren, Bohao Liu, Zhiyuan Qu, Xue Jiang, Heng Zhao, Danyao Qu, Ruizhi Ning, Chen Su, Taoping Liu, Guangjian Zhang, Weiwei Wu   +10 more
wiley   +1 more source

Detecting and subtyping ketoacidosis from metabolomic patterns in forensic casework. [PDF]

Sci Rep
Monte REC, Magnusson R, Söderberg C, Gréen H, Elmsjö A, Nyman E.   +5 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Downfield magnetic resonance signals serve as endogenous imaging biomarkers of nucleotide metabolism in glioma. [PDF]

Commun Biol
Zhu X, Zhou K, Cao Y, Zhou J, Liu Y, Liu Y, Chen S, Wang M.   +7 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

A Practical Roadmap for Clinical Translation of Metabolic Biomarkers: A Review. [PDF]

Int J Mol Sci
Kim KH, Yoo M, Choi MY, Yoo BC.
europepmc   +1 more source