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Bacterial Biopolymer: Its Role in Pathogenesis to Effective Biomaterials

期刊

POLYMERS
卷 13, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/polym13081242

关键词

cell factories; bacterial biopolymers; pathogenesis; biomaterials; synthetic biology

资金

  1. Fundamental Research Grant Scheme - Ministry of Higher Education, Malaysia [203/PPSK/6171258]

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Bacteria are major cell factories that can convert nitrogen and carbon sources into various biopolymers, with important medicinal applications and roles in pathogenicity.
Bacteria are considered as the major cell factories, which can effectively convert nitrogen and carbon sources to a wide variety of extracellular and intracellular biopolymers like polyamides, polysaccharides, polyphosphates, polyesters, proteinaceous compounds, and extracellular DNA. Bacterial biopolymers find applications in pathogenicity, and their diverse materialistic and chemical properties make them suitable to be used in medicinal industries. When these biopolymer compounds are obtained from pathogenic bacteria, they serve as important virulence factors, but when they are produced by non-pathogenic bacteria, they act as food components or biomaterials. There have been interdisciplinary studies going on to focus on the molecular mechanism of synthesis of bacterial biopolymers and identification of new targets for antimicrobial drugs, utilizing synthetic biology for designing and production of innovative biomaterials. This review sheds light on the mechanism of synthesis of bacterial biopolymers and its necessary modifications to be used as cell based micro-factories for the production of tailor-made biomaterials for high-end applications and their role in pathogenesis.

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Summary: In this study, Pinocembrin was identified as a potential HDAC1 inhibitor and could be used in epigenetic therapy for cancer such as brain cancer and lung cancer to regulate gene expression.

APPLIED BIOCHEMISTRY AND BIOTECHNOLOGY (2023)

Proceedings Paper Computer Science, Information Systems

Radish Freshness Classification Using Deep Learning

Tanupriya Choudhury, Thipendra Pal Singh, Prakhar Jain, V. R. Arunachalaeshwaran, Tanmay Sarkar

Summary: This paper discusses the application of deep learning and computer vision in automating freshness classification. It demonstrates the effectiveness of these new technologies in improving accuracy and efficiency compared to manual labor methods.

INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2 (2023)

Proceedings Paper Computer Science, Information Systems

CNN-Based Freshness Grading of Mourala Fish (Amblypharyngodon Mola)

Tanupriya Choudhury, Ayush Aryan, Hussain Falih Mahdi, V. R. Arunachalaeshwaran, Tanmay Sarkar

Summary: Accurate assessment of fish freshness is crucial for consumers. Manual analysis is time-consuming and can result in false assessment and various diseases. With the emergence of computer vision and deep learning methods, an automatic system for fish freshness grading is possible.

INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2 (2023)

Meeting Abstract Hematology

PRELIMINARY STUDY ON THE DIVERSITY OF MANNOSE-BINDING LECTIN POLYMORPHISMS IN KELANTAN POPULATION

Muhamad Aidil Zahidin, Noor Haslina Mohd Noor, Muhammad Farid Johan, Abu Dzarr Abdullah, Zefarina Zulkafli, Hisham Atan Edinur

INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY (2023)

Article Food Science & Technology

Hybrid Deep Learning Algorithm-Based Food Recognition and Calorie Estimation

Ritu Agarwal, Tanupriya Choudhury, Neelu J. Ahuja, Tanmay Sarkar

Summary: In this study, a hybrid architecture that utilizes deep learning algorithms is proposed to forecast the number of calories in food items on a bowl. The approach consists of segmentation, classification, and calculating the volume and calories of the food items. The accuracy of identifying and forecasting the calories of food items using this method reaches 97.12%.

JOURNAL OF FOOD PROCESSING AND PRESERVATION (2023)

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