Near-Infrared Emissive π-Conjugated Oligomer Nanoparticles for Three- and Four-Photon Deep-Brain Microscopic Imaging Beyond 1700 nm Excitation DOI

Lijun Kan,

Yingxian Zhang, Yu Luo

et al.

ACS Nano, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

High-resolution visualization of the deep brain is still a challenging and very significant issue. Multiphoton microscopy (MPM) holds great promise for high-spatiotemporal deep-tissue imaging under NIR-III NIR-IV excitation. However, thus far, their applications have been seriously restricted by scarcity efficient organic probes. Herein, we designed synthesized two donor-acceptor-donor-type conjugated small molecules (

Language: Английский

Cancer drug-tolerant persister cells: from biological questions to clinical opportunities DOI
Mariangela Russo,

Mengnuo Chen,

Elisa Mariella

et al.

Nature reviews. Cancer, Journal Year: 2024, Volume and Issue: 24(10), P. 694 - 717

Published: Sept. 2, 2024

Language: Английский

Citations

20
Artificial intelligence for high content imaging in drug discovery DOI Creative Commons
Jordi Carreras‐Puigvert, Ola Spjuth

Current Opinion in Structural Biology, Journal Year: 2024, Volume and Issue: 87, P. 102842 - 102842

Published: May 25, 2024

Artificial intelligence (AI) and high-content imaging (HCI) are contributing to advancements in drug discovery, propelled by the recent progress deep neural networks. This review highlights AI's role analysis of HCI data from fixed live-cell imaging, enabling novel label-free multi-channel fluorescent screening methods, improving compound profiling. experiments rapid cost-effective, facilitating large set accumulation for AI model training. However, success discovery also depends on high-quality data, reproducible experiments, robust validation ensure performance. Despite challenges like need annotated compounds managing vast image potential phenotypic profiling is significant. Future improvements AI, including increased interpretability integration multiple modalities, expected solidify HCI's discovery.

Language: Английский

Citations

15
Linking Metastatic Behavior and Metabolic Heterogeneity of Circulating Tumor Cells at Single‐Cell Level Using an Integrative Microfluidic System DOI Creative Commons
Ying Hou, Jiaxu Lin,

Hongren Yao

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Abstract Circulating tumor cells (CTCs) are pivotal biomarkers in metastasis, however, the underlying molecular mechanism of CTCs behavioral heterogeneity during metastasis remains unexplored. Here, an integrative workflow is developed to link behavior characteristics metabolic profiling within individual CTCs, which simulates metastatic process on a microfluidic system and combined with single‐cell mass spectrometry (MS) detection. Spheroid‐derived HCT116 tracked extracted via temporary vascular system, revealing various arrest patterns under biomimetic shear flow. Downstream MS analysis characterizes 17 cellular metabolites associates profiles de‐adhesion behaviors same identifying potential high‐metastatic subpopulation enhanced ability evaluating critical involved pathways. Additionally, metastasis‐inhibiting effect anti‐tumor drug 5‐fluorouracil by reducing spheroids elucidated. This approach offers valuable opportunity dissect interplay foster insights into mechanisms phenotypes process.

Language: Английский

Citations

2
A Foundation Model for Cell Segmentation DOI Creative Commons

Uriah Israel,

Markus Marks, Rohit Dilip

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 20, 2023

Abstract Cells are a fundamental unit of biological organization, and identifying them in imaging data – cell segmentation is critical task for various cellular experiments. While deep learning methods have led to substantial progress on this problem, most models use specialist that work well specific domains. Methods learned the general notion “what cell” can identify across different domains proven elusive. In work, we present CellSAM, foundation model generalizes diverse data. CellSAM builds top Segment Anything Model (SAM) by developing prompt engineering approach mask generation. We train an object detector, CellFinder, automatically detect cells SAM generate segmentations. show allows single achieve human-level performance segmenting images mammalian (in tissues culture), yeast, bacteria collected modalities. has strong zero-shot be improved with few examples via few-shot learning. also unify bioimaging analysis workflows such as spatial transcriptomics tracking. A deployed version available at https://cellsam.deepcell.org/ .

Language: Английский

Citations

21
Perspective on quantitative phase imaging to improve precision cancer medicine DOI Creative Commons
Yang Liu, Shikhar Uttam

Journal of Biomedical Optics, Journal Year: 2024, Volume and Issue: 29(S2)

Published: March 26, 2024

SignificanceQuantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast translating associated shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine providing quantitative characterization of the biophysical properties cells and tissue in natural states.AimThis perspective aims discuss increase our understanding development its response therapeutics. also explores new developments methods towards personalized therapy early detection.ApproachWe begin detailing technical advancements QPI, examining implementations across transmission reflection geometries retrieval methods, both interferometric non-interferometric. The focus then QPI's applications research, including dynamic cell mass drug assessment, risk stratification, in-vivo imaging.ResultsQPI has emerged as crucial tool medicine, offering insights tumor biology treatment efficacy. Its sensitivity detecting changes promise enhancing diagnostics, prognostication. future is envisioned integration artificial intelligence, morpho-dynamics, spatial biology, broadening impact research.ConclusionsQPI presents redefining diagnosis, monitoring, treatment. Future directions include harnessing high-throughput imaging, 3D realistic models, combining intelligence multi-omics extend capabilities. As result, stands at forefront research clinical application care.

Language: Английский

Citations

9
The glowing frontier: Carbon dots' journey for customized cancer treatments DOI

Anqi Liang,

Jie Yang,

Xiao Zhu

et al.

Journal of Drug Delivery Science and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 106658 - 106658

Published: Feb. 1, 2025

Language: Английский

Citations

1
Mapping T cell dynamics to molecular profiles through behavior-guided transcriptomics DOI
Amber K. L. Wezenaar,

Utsav Pandey,

Farid Keramati

et al.

Nature Protocols, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

Language: Английский

Citations

1
In vitro and in vivo bioimaging by Quinoline conjugated probes and dyes DOI
Avijit Ghosh, Arghya Adhikary

Coordination Chemistry Reviews, Journal Year: 2025, Volume and Issue: 536, P. 216654 - 216654

Published: April 10, 2025

Language: Английский

Citations

1
Tumor-immune metaphenotypes orchestrate an evolutionary bottleneck that promotes metabolic transformation DOI Creative Commons
Jeffrey West, Frederika Rentzeperis,

Casey Adam

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Feb. 15, 2024

Introduction Metabolism plays a complex role in the evolution of cancerous tumors, including inducing multifaceted effect on immune system to aid escape. Immune escape is, by definition, collective phenomenon requiring presence two cell types interacting close proximity: tumor and immune. The microenvironmental context these interactions is influenced dynamic process blood vessel growth remodelling, creating heterogeneous patches well-vascularized or acidic niches. Methods Here, we present multiscale mathematical model that captures phenotypic, vascular, microenvironmental, spatial heterogeneity which shapes acid-mediated invasion over biologically-realistic time scale. explores several mechanisms such as i) acid inactivation cells, ii) competition for glucose, iii) inhibitory checkpoint receptor expression (PD-L1). We also explore efficacy anti-PD-L1 sodium bicarbonate buffer agents treatment. To understanding cellular phenomenon, define six phenotypes (termed “meta-phenotypes”): Self-Acidify, Mooch Acid, PD-L1 Attack, PD-L1, Proliferate Fast, Starve Glucose. Results Fomenting stronger response leads initial benefits (additional cytotoxicity), but this advantage offset increased turnover accelerated emergence aggressive phenotypes. This creates bimodal therapy landscape: either should be maximized complete cure, kept check avoid rapid invasive cells. These constraints are dependent vascular context, acidification, strength response. Discussion helps untangle key evolutionary costs three phenotypic axes treatment: acid-resistance, glycolysis, expression. concomitant treatments promising treatment strategy limit adverse effects

Language: Английский

Citations

6
Probing the protrusions: lamellipodia and filopodia in cancer invasion and beyond DOI Creative Commons

Laras Pratiwi,

Elisa Elisa,

Henry Sutanto

et al.

Mechanobiology in Medicine, Journal Year: 2024, Volume and Issue: 2(2), P. 100064 - 100064

Published: March 21, 2024

The dynamic protrusions of lamellipodia and filopodia have emerged as crucial players in tumor progression metastasis. These membrane structures, governed by intricate actin cytoskeletal rearrangements, facilitate cancer cell migration, invasion, interaction with the microenvironment. This review provides a comprehensive examination structural functional attributes filopodia, shedding light on their pivotal roles mediating invasion. Navigating through landscape biology, illuminates signaling pathways regulatory mechanisms orchestrating formation activity these protrusions. discussion extends to clinical implications exploring potential diagnostic prognostic markers, delving into therapeutic strategies that target structures impede progression. As we delve future, outlines emerging technologies unexplored facets beckon further research, emphasizing need for collaborative efforts unravel complexities cancer, ultimately paving way innovative interventions.

Language: Английский

Citations

5