AIMC Topic: Fluorescent Dyes

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Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN).

Biomolecules
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image ...

Deep learning permits imaging of multiple structures with the same fluorophores.

Biophysical journal
Fluorescence microscopy, which employs fluorescent tags to label and observe cellular structures and their dynamics, is a powerful tool for life sciences. However, due to the spectral overlap between different dyes, a limited number of structures can...

Perovskite Probe-Based Machine Learning Imaging Model for Rapid Pathologic Diagnosis of Cancers.

ACS nano
Accurately distinguishing tumor cells from normal cells is a key issue in tumor diagnosis, evaluation, and treatment. Fluorescence-based immunohistochemistry as the standard method faces the inherent challenges of the heterogeneity of tumor cells and...

Plastic particles and fluorescent brightener co-modify Chlorella pyrenoidosa photosynthesis and a machine learning approach predict algae growth.

Journal of hazardous materials
Global release of plastics exerts various impacts on the ecological cycle, particularly on primary photosynthesis, while the impacts of plastic additives are unknown. As a carrier of fluorescent brightener, plastic particles co-modify Chlorella pyren...

Dual-Mode Fluorescent/Intelligent Lateral Flow Immunoassay Based on Machine Learning Algorithm for Ultrasensitive Analysis of Chloroacetamide Herbicides.

Analytical chemistry
Given the harmful effect of pesticide residues, it is essential to develop portable and accurate biosensors for the analysis of pesticides in agricultural products. In this paper, we demonstrated a dual-mode fluorescent/intelligent (DM-f/DM-i) latera...

A supramolecular fluorescence sensor array for the differentiation of multiple anions and prediction of iodine in artificial urine using machine learning.

Mikrochimica acta
The simultaneous discrimination and detection of multiple anions in an aqueous solution has been a major challenge due to their structural similarity and low charge radii. In this study, we have constructed a supramolecular fluorescence sensor array ...

Machine-Learning-Assisted Rational Design of Si─Rhodamine as Cathepsin-pH-Activated Probe for Accurate Fluorescence Navigation.

Advanced materials (Deerfield Beach, Fla.)
High-performance fluorescent probes stand as indispensable tools in fluorescence-guided imaging, and are crucial for precise delineation of focal tissue while minimizing unnecessary removal of healthy tissue. Herein, machine-learning-assisted strateg...

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Analytical chemistry
Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic microorganisms is especially important for diagnosing infections. Herein, three tetraphenylethylene der...

Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe.

Chemosphere
Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality...

DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology.

Nature communications
Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing sli...