Advanced Carriers for Precise Delivery and Therapeutic Mechanisms of Traditional Chinese Medicines: Integrating Spatial Multi‐Omics and Delivery Visualization

Advanced Healthcare Materials, Год журнала: 2025, Номер unknown

Опубликована: Янв. 19, 2025

Abstract The complex composition of traditional Chinese medicines (TCMs) has posed challenges for in‐depth study and global application, despite their abundance bioactive compounds that make them valuable resources disease treatment. To overcome these obstacles, it is essential to modernize TCMs by focusing on precise This involves elucidating the structure‐activity relationships within compositions, ensuring accurate in vivo delivery, monitoring delivery process. review discusses research progress precision treatment from three perspectives: spatial multi‐omics technology therapeutic activity, carrier systems medical imaging visualizing aim establish a novel paradigm advances therapy TCMs.

Язык: Английский

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Transformer-based artificial intelligence on single-cell clinical data for homeostatic mechanism inference and rational biomarker discovery

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Март 25, 2025

Artificial intelligence (AI) applied to single-cell data has the potential transform our understanding of biological systems by revealing patterns and mechanisms that simpler traditional methods miss. Here, we develop a general-purpose, interpretable AI pipeline consisting two deep learning models: Multi- Input Set Transformer++ (MIST) model for prediction FastShap interpretability. We apply this large set routine clinical containing measurements circulating red blood cells (RBC), white (WBC), platelets (PLT) study population fluxes homeostatic hematological mechanisms. find MIST can use these explain 70-82% variation in cell sizes among patients (RBC count, PLT WBC count), compared 5-20% explained with current approaches. MIST's accuracy implies substantial information on cellular production clearance is present measurements. identified crosstalk RBC, WBC, populations, suggesting co-regulatory relationships validated investigated using interpretability maps generated FastShap. The identify granular subgroups most important each population's size, enabling generation evidence-based hypotheses also enable rational discovery single-WBC biomarker, "Down Shift", complements an existing marker inflammation strengthens diagnostic associations diseases including sepsis, heart disease, diabetes. This illustrates how be leveraged mechanistic inference relevance power scientific discovery.

Язык: Английский

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Perspectives on integrating artificial intelligence and single‐cell omics for cellular plasticity research

Quantitative Biology, Год журнала: 2025, Номер 13(4)

Опубликована: Апрель 24, 2025

Abstract Cellular plasticity enables cells to dynamically adapt environmental changes by altering their phenotype. This plays a crucial role in tissue repair and regeneration contributes pathological processes such as cancer metastasis. Advances single‐cell omics have significantly advanced the study of cellular states provided new opportunities for accurate cell classification uncovering transitions. In this perspective, we emphasize integrating chromatin accessibility data extrinsic factors, microenvironmental cues, with transcriptomic develop holistic models identifying plastic states. Additionally, coupling artificial intelligence offers transformative potential address existing challenges fill gaps characterizing cells. We envision development universal metric, standardized metric quantifying plasticity. would enable consistent measurement across diverse studies, creating unified framework that bridges fields developmental biology, research, regenerative medicine. Fostering innovative approaches analyzing promises not only deepen our understanding but also accelerate therapeutic advancements, paving way novel precision medicine strategies treat complex diseases cancer.

Язык: Английский

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Application of a novel numerical simulation to biochemical reaction systems

Frontiers in Cell and Developmental Biology, Год журнала: 2024, Номер 12

Опубликована: Сен. 6, 2024

Recent advancements in omics and single-cell analysis highlight the necessity of numerical methods for managing complexity biological data. This paper introduces a simulation program biochemical reaction systems based on natural number (NNS) method. novel approach ensures equitable treatment all molecular entities, such as DNA, proteins, H

Язык: Английский

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Machine Learning and Omic Data for Prediction of Health and Chronic Diseases

Elsevier eBooks, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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