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Tetracycline

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Tuning the Performance of Synthetic Riboswitches using Machine Learning.

ACS synthetic biology
Riboswitch development for clinical, technological, and synthetic biology applications constantly seeks to optimize regulatory behavior. Here, we present a machine learning approach to improve the regulation of a tetracycline (tc)-dependent riboswitc...

Membrane separation of antibiotics predicted with the back propagation neural network.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Antibiotics and antibiotic resistance genes (ARGs) have been frequently detected in the aquatic environment and are regarded as emerging pollutants. The prediction models for the removal effect of four target antibiotics by membrane separation techno...

Nanozyme-induced deep learning-assisted smartphone integrated colorimetric and fluorometric dual-mode for detection of tetracycline analogs.

Analytica chimica acta
In this work, a colorimetric and fluorescent dual-mode probe controlled by NH-MIL-88 B (Fe, Ni) nanozymes was developed to visually detect tetracycline antibiotics (TCs) residues quantitatively, as well as accurately distinguish the four most widely ...

Ratiometric fluorescence sensor based on deep learning for rapid and user-friendly detection of tetracycline antibiotics.

Food chemistry
The detection of tetracycline antibiotics (TCs) in food holds great significance in minimizing their absorption within the human body. Hence, this study aims to develop a rapid, convenient, real-time, and accurate detection method for detecting antib...

Machine learning and statistical physics modeling of tetracycline adsorption using activated carbon derived from Cynometra ramiflora fruit biomass.

Environmental research
The current investigation reports the usage of adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN), the two recognized machine learning techniques in modelling tetracycline (TC) adsorption onto Cynometra ramiflora fruit ...

Deep learning assisted logic gates for real-time identification of natural tetracycline antibiotics.

Food chemistry
The overuse and misuse of tetracycline (TCs) antibiotics, including tetracycline (TTC), oxytetracycline (OTC), doxycycline (DC), and chlortetracycline (CTC), pose a serious threat to human health. However, current rapid sensing platforms for tetracyc...

Prediction of g-CN-based photocatalysts in tetracycline degradation based on machine learning.

Chemosphere
Investigating the effects of g-CN-based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learni...

Unveiling the role of artificial intelligence in tetracycline antibiotics removal using UV/sulfite/phenol advanced reduction process.

Journal of environmental management
UV/sulfite-based advanced reduction processes (ARP) have attracted increasing attention due to their high capability for removing a wide range of pollutants. Therefore, developing UV/sulfite ARP systems with assisted Artificial Intelligence (AI) mode...

Graphene FET biochip on PCB reinforced by machine learning for ultrasensitive parallel detection of multiple antibiotics in water.

Biosensors & bioelectronics
Antibiotics like Ciprofloxacin (Cfx), tetracycline (Tet) and Tobramycin (Tob) are commonly used against a broad-spectrum of bacterial infection. Recent surge in their uptake through the presence of their residues in environmental water has been linke...

Based on T.E.S.T toxicity prediction and machine learning to forecast toxicity dynamics in the photocatalytic degradation of tetracycline.

Physical chemistry chemical physics : PCCP
The integration of photocatalysis and biological treatment provides an effective strategy for controlling antibiotic contamination, which requires precise monitoring of toxicity changes during the photocatalytic process. In this study, nanoscale TiO ...