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8 results on '"Bona Yun"'

1. Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens

Author

Bona Yun, Xinyu Liao, Jinsong Feng, and Tian Ding

Subjects
Foodborne pathogens, food safety, antimicrobial resistance, machine learning, Nutrition. Foods and food supply, TX341-641, Food processing and manufacture, TP368-456
Abstract

The World Health Organization (WHO) has identified antimicrobial resistance (AMR) as one of the top three global dangers to public health. One of the most vital factors contributing to the high prevalence of AMR is the misuse/overuse of antibiotics for treatment and/or as a growth promoter in the food industry. AMR can be transmitted to humans via food, the environment, or other channels through horizontal gene transfer. Therefore, efficient methods are urgently needed to determine whether bacteria are resistant to antibiotics. This work provides a review of the advances in machine learning (ML) techniques for predicting and identifying AMR in foodborne pathogens. We also emphasize the groundbreaking potential of whole genome sequencing (WGS) and spectroscopy technologies combined with ML in the context of AMR detection. These offer enormous potential because of their unique characteristics, which can overcome inherent limits in existing detection approaches.

Published
2024
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3. Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens.

Author

Yun, Bona, Liao, Xinyu, Feng, Jinsong, and Ding, Tian

Subjects
DRUG resistance in bacteria, HORIZONTAL gene transfer, WHOLE genome sequencing, DRUG resistance in microorganisms, FOOD pathogens
Abstract

The World Health Organization (WHO) has identified antimicrobial resistance (AMR) as one of the top three global dangers to public health. One of the most vital factors contributing to the high prevalence of AMR is the misuse/overuse of antibiotics for treatment and/or as a growth promoter in the food industry. AMR can be transmitted to humans via food, the environment, or other channels through horizontal gene transfer. Therefore, efficient methods are urgently needed to determine whether bacteria are resistant to antibiotics. This work provides a review of the advances in machine learning (ML) techniques for predicting and identifying AMR in foodborne pathogens. We also emphasize the groundbreaking potential of whole genome sequencing (WGS) and spectroscopy technologies combined with ML in the context of AMR detection. These offer enormous potential because of their unique characteristics, which can overcome inherent limits in existing detection approaches. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Reports from Zhejiang University Describe Recent Advances in Foodborne Diseases and Conditions (Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens).

Subjects
FOODBORNE diseases, FOOD poisoning, FOOD science, DRUG resistance in bacteria, TECHNOLOGICAL innovations
Abstract

A recent report from Zhejiang University discusses the pressing issue of antimicrobial resistance (AMR) in foodborne pathogens, identified as a global health threat by the World Health Organization. The misuse of antibiotics in the food industry contributes to the spread of AMR, which can be transmitted to humans through various channels. The report highlights the potential of machine learning techniques, whole genome sequencing, and spectroscopy technologies in detecting and predicting AMR, offering new avenues for more efficient detection methods. For more information, readers can refer to the article "Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens" in the CyTA - Journal of Food. [Extracted from the article]

Published
2024

5. New Hypoglycemia Study Findings Have Been Reported by Researchers at Ewha Womans University (Machine Learning-based Prediction of Risk Factors for Abnormal Glycemic Control In Diabetic Cancer Patients Receiving Nutrition Support: a Case-control...).

Subjects
GLYCEMIC control, PEOPLE with diabetes, HYPOGLYCEMIA, GLUCOSE metabolism disorders, RESEARCH personnel, HYPERGLYCEMIA
Abstract

Keywords: Seoul; South Korea; Asia; Cancer; Clinical Research; Clinical Trials and Studies; Cyborgs; Diet and Nutrition; Emerging Technologies; Glucose Metabolism Disorders; Health and Medicine; Hyperglycemia; Hypoglycemia; Machine Learning; Metabolic Diseases and Conditions; Nutritional and Metabolic Diseases and Conditions; Oncology; Risk and Prevention EN Seoul South Korea Asia Cancer Clinical Research Clinical Trials and Studies Cyborgs Diet and Nutrition Emerging Technologies Glucose Metabolism Disorders Health and Medicine Hyperglycemia Hypoglycemia Machine Learning Metabolic Diseases and Conditions Nutritional and Metabolic Diseases and Conditions Oncology Risk and Prevention 785 785 1 10/30/23 20231031 NES 231031 2023 OCT 31 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- Current study results on Nutritional and Metabolic Diseases and Conditions - Hypoglycemia have been published. Conclusion The use of SU and BUN level > 20 mg/dL increased the risk of hypoglycemia, whereas an initial blood glucose level >= 182.5 mg/dL, a supplied actual energy intake/ TEE >= 120%, and the use of DPP-4 inhibitors increased the risk of hyperglycemia.". [Extracted from the article]

Published
2023

6. Reports from Zhejiang University Describe Recent Advances in Foodborne Diseases and Conditions (Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens)

Subjects
Medical research -- Reports, Medicine, Experimental -- Reports, Drug resistance in microorganisms -- Reports, Machine learning -- Reports, Foodborne diseases -- Reports, Physical fitness -- Reports, Health
Abstract

2024 DEC 14 (NewsRx) -- By a News Reporter-Staff News Editor at Obesity, Fitness & Wellness Week -- Research findings on foodborne diseases and conditions are discussed in a new [...]

Published
2024

7. New Hypoglycemia Study Findings Have Been Reported by Researchers at Ewha Womans University (Machine Learning-based Prediction of Risk Factors for Abnormal Glycemic Control In Diabetic Cancer Patients Receiving Nutrition Support: a Case-control ...)

Subjects
Oncology, Experimental, Diabetes therapy -- Research, Cancer patients -- Diet therapy, Machine learning -- Research, Cancer -- Research, Hyperglycemia -- Diet therapy -- Research -- Risk factors, Business, Health, Health care industry
Abstract

2023 OCT 31 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- Current study results on Nutritional and Metabolic Diseases and Conditions - Hypoglycemia have been published. [...]

Published
2023

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