Plant Foods and Their Bioactives as Dietary Enhancers for Colon Cancer Treatment with 5-Fluorouracil

Food Reviews International, Год журнала: 2025, Номер unknown, С. 1 - 50

Опубликована: Янв. 4, 2025

Cancer is the world's second most common cause of death, with colon cancer (CC) ranking third in prevalence and cancer-related fatalities. CC originates or rectum influenced by genetic mutations, lifestyle, diet. Although chemotherapy, especially 5-fluorouracil (5-FU), fundamental to treatment has improved patient survival, its benefits are often limited significant side effects emerging drug resistance. Recently, plant-based foods have drawn interest research for their natural bioactive compounds relatively low toxicity. Certain plant not only exhibit anti-cancer activity but may also boost effectiveness 5-FU while reducing adverse effects. Despite evidence suggesting a synergistic effect between 5-FU, this area remains fragmented. This review consolidates current on including fruits, vegetables, legumes, tea bioactives treatment. Besides, it explores mechanisms through which these enhance efficacy reduce effects, evaluates clinical application prospects, identifies challenges future directions. comprehensive analysis aims provide scientific foundation integrated CC, highlighting potential enhancing chemotherapy associated toxicities.

Язык: Английский

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COLD-12: A Multi-Level Feature Extraction Hybrid CNN Model for Accurate Cotton Disease Diagnosis

Franklin Open, Год журнала: 2025, Номер unknown, С. 100263 - 100263

Опубликована: Апрель 1, 2025

Язык: Английский

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Detection of small foreign objects in Pu-erh sun-dried green tea: An enhanced YOLOv8 neural network model based on deep Learning

Food Control, Год журнала: 2024, Номер unknown, С. 110890 - 110890

Опубликована: Сен. 1, 2024

Язык: Английский

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Intelligent Grading System for Mangosteen Based on Faster-FRNet: Enhancing Accuracy and Efficiency in Post-Harvest Quality Control

Journal of Food Composition and Analysis, Год журнала: 2025, Номер unknown, С. 107394 - 107394

Опубликована: Фев. 1, 2025

Язык: Английский

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Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery

Ecological Informatics, Год журнала: 2025, Номер unknown, С. 103204 - 103204

Опубликована: Май 1, 2025

Язык: Английский

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Adaptation of deep learning models to distinguish species with strongly overlapping characteristics: the example of spores of the genus Riccia

Ecological Informatics, Год журнала: 2025, Номер unknown, С. 103226 - 103226

Опубликована: Май 1, 2025

Язык: Английский

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Tricho-Vision: The Use of computer vision in trichotaxonomy for enhancing wildlife conservation of priority species

Ecological Informatics, Год журнала: 2025, Номер unknown, С. 103161 - 103161

Опубликована: Июнь 1, 2025

Язык: Английский

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Phytochemicals with anticancer activity from poisonous plants: potential leads for cancer therapy

Phytochemistry Reviews, Год журнала: 2024, Номер unknown

Опубликована: Окт. 3, 2024

Язык: Английский

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Leveraging AI in Ayurvedic Agriculture: A RAG Chatbot for Comprehensive Medicinal Plant Insights Using Hybrid Deep Learning Approaches

Telematics and Informatics Reports, Год журнала: 2024, Номер unknown, С. 100181 - 100181

Опубликована: Дек. 1, 2024

Язык: Английский

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Autoencoder‐Based Eggshell Crack Detection Using Acoustic Signal

Journal of Food Process Engineering, Год журнала: 2024, Номер 47(11)

Опубликована: Ноя. 1, 2024

ABSTRACT Breaks or cracks in eggshells offer substantial food safety issues. Bacteria and viruses, particular, are more likely to enter the egg through breaks cracks, increasing risk of poisoning. Furthermore, deformations shell may compromise integrity protective shell, exposing external variables causing it lose freshness decay faster. To reduce such hazards, this research created an innovative crack detection system based on autoencoder (AE) that uses acoustic signals from eggshells. A creates effect by hitting eggshell without damaging was designed, these effects were recorded a microphone. Acoustic signal data size 1 × 1000 fed into k nearest neighbor (kNN), decision tree (DT), support vector machine (SVM) classifiers. AE employed order accommodate raw data's unique features. This model, which reduces size, used with many classifiers able accurately distinguish between intact cracked eggs. The built AE‐based classifier model completed classification procedure 100% accuracy, including microcracks invisible naked eye.

Язык: Английский

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