AIMC Topic: Microalgae
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Dual-Stage Propulsion Strategy for Microalgae-Based Biohybrid Microrobots.
ACS applied materials & interfaces
Jun 3, 2025
Biohybrid microrobots, based on swimming microalgae, offer outstanding self-propulsion and functionalization capabilities, making them promising platforms for cargo loading and delivery. However, current technologies predominantly focus on in vitro n...
Living Microalgae-Based Magnetic Microrobots for Calcium Overload and Photodynamic Synergetic Cancer Therapy.
Advanced healthcare materials
Feb 27, 2025
The combination of Ca overload and reactive oxygen species (ROS) production for cancer therapy offers a superior solution to the lack of specificity in traditional antitumor strategies. However, current therapeutic platforms for this strategy are pri...
Detecting living microalgae in ship ballast water based on stained microscopic images and deep learning.
Marine pollution bulletin
Feb 1, 2025
Motivated by the need of rapid detection of living microalgae cells in ship ballast water, this study is intended to determine the activities of microalgae using stained microscopic images and detect the living cells with image processing algorithms....
AlgaeSperm: Microalgae-Based Soft Magnetic Microrobots for Targeted Tumor Treatment.
Small (Weinheim an der Bergstrasse, Germany)
Jan 13, 2025
Magnetic microrobots are significant platforms for targeted drug delivery, among which sperm-inspired types have attracted much attention due to their flexible undulation. However, mass production of sperm-like soft magnetic microrobots with high-spe...
Biological contaminants analysis in microalgae culture by UV-vis spectroscopy and machine learning.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jan 2, 2025
This study elucidates the utility and efficacy of UV-visible spectroscopy for the detection and characterization of biological contaminants within microalgae cultures, augmented by machine learning algorithms. Biological contamination, exemplified by...
Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.
Bioresource technology
Dec 28, 2024
Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predicting treated greywater quality is of great significance for water reuse. In this work, machine learning models were developed for simulating and predi...
Integration of spectroscopic techniques and machine learning for optimizing Phaeodactylum tricornutum cell and fucoxanthin productivity.
Bioresource technology
Dec 16, 2024
The development of sustainable and controlled microalgae bioprocesses relies on robust and rapid monitoring tools that facilitate continuous process optimization, ensuring high productivity and minimizing response times. In this work, we analyse the ...
Machine learning-based prediction and model interpretability analysis for algal growth affected by microplastics.
The Science of the total environment
Dec 14, 2024
Microplastics (MPs), the plastic debris smaller than 5 mm, are ubiquitous in waterbodies and have been shown to be toxic to aquatic organisms, especially to microalgae. The aim of this study is to use machine learning models to predict the effects of...
Insights into the characteristics and toxicity of microalgal biochar-derived dissolved organic matter by spectroscopy and machine learning.
The Science of the total environment
Nov 20, 2024
Microalgal biochar has potential applications in various fields; however, there is limited research on the properties and risks of microalgal biochar-derived dissolved organic matter (MBDOM). This study examined how different pyrolysis temperatures (...
Graph-learning-based machine learning improves prediction and cultivation of commercial-grade marine microalgae Porphyridium.
Bioresource technology
Nov 7, 2024
A graph learning [Binarized Attributed Network Embedding (BANE)] model enhances the single-target and multi-target prediction performances of random forest and eXtreme Gradient Boosting (XGBoost) by learning complex interrelationships between cultiva...
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