Aggregatibacter actinomycetemcomitans is a key pathogen in periodontal disease, damaging periodontal ligaments and alveolar bone through biofilm formation. D-LL-31, an engineered antimicrobial peptide, exhibits superior biofilm-killing ability compared to conventional treatments, while DNase I enhances its efficacy by disrupting the biofilm matrix. This study evaluated the combined effects of D-LL-31 and DNase I on A. actinomycetemcomitans biofilms. Results showed that D-LL-31 effectively eradicated biofilms, and its combination with DNase I further enhanced biofilm disruption without cytotoxicity to gingival epithelial cells. The D-LL-31 and DNase I combination shows potential for development as a mouthwash to improve oral health and combat periodontal disease.
โรคปริทันต์เป็นปัญหาสุขภาพช่องปากที่พบบ่อย โดยมี Aggregatibacter actinomycetemcomitans (Aa) เป็นหนึ่งในเชื้อก่อโรคสำคัญ เชื้อชนิดนี้สามารถสร้างไบโอฟิล์ม ซึ่งเป็นกลไกหลักที่ช่วยให้เชื้อดื้อยาต้านจุลชีพและหลบเลี่ยงระบบภูมิคุ้มกัน ทำให้การรักษาด้วยยาปฏิชีวนะทั่วไปไม่ได้ผลอย่างมีประสิทธิภาพ การพัฒนาแนวทางใหม่ในการกำจัดไบโอฟิล์มจึงเป็นสิ่งจำเป็น งานวิจัยนี้มุ่งเน้นศึกษาประสิทธิภาพของ D-LL-31 ซึ่งเป็นเปปไทด์ต้านจุลชีพที่ถูกแปลงทางวิศวกรรม เพื่อทำลายเชื้อที่อยู่ในไบโอฟิล์ม และการใช้ DNase I เพื่อสลายโครงสร้างเมทริกซ์ของไบโอฟิล์มร่วมกัน ซึ่งอาจเป็นแนวทางใหม่ในการพัฒนา น้ำยาบ้วนปาก ที่ช่วยลดเชื้อก่อโรคในช่องปากและป้องกันโรคปริทันต์ได้อย่างมีประสิทธิภาพ
คณะเทคโนโลยีการเกษตร
Threadfin breams is an economically important fish that can be found in fisheries in both the Gulf of Thailand and Andaman Sea and is cheap. In addition, the consumption of raw fish as sashimi is increasingly popular in Thailand. Therefore, it is necessary to promote its consumption to increase its value. This study investigated the preservation of threadfin breams (N. furcosus) for raw or sashimi consumption. The preservation of threadfin breams consisted of Ikejime (K) and cold seawater (S) methods, and the preservation of the fish by Gutting (G) and whole (W) and storing for 3 days on ice (I) or in a refrigerator (F). The freshness quality of threadfin breams was evaluated by sensory, physicochemical (TVB-N, TMA-N and pH), freshness index (Ki-value) and microbiological methods. It was found that after being stored for 3 days, the KGF group of threadfin breams had the highest overall sensory score, which was 8.36±0.80 points, and the KWI, SWI and SWF groups of threadfin breams had the lowest overall sensory scores, which were 8.13±0.77, 8.13±0.77 and 8.13±0.81 points, respectively. And the overall sensory scores of all experimental groups of fish increased significantly (p<0.05). The TVB-N value of threadfin breams in KGF group had the lowest TVB-N value, which was 1.37±0.93 mg nitrogen/100 g sample. The threadfin breams in SGI group had the highest TVB-N value, which was 2.36±1.15 mg nitrogen/100 g sample. The TVB-N of fish in all experimental groups increased significantly (p<0.05). The TMA-N value of threadfin breams in KGF group had the lowest TMA-N value, which was 1.56±0.88 mg nitrogen/100 g sample. The threadfin breams in SWF group had the highest TMA-N value, which was 2.17±1.22 mg nitrogen/100 g sample. The TMA-N of fish in all experimental groups increased significantly (p<0.05). The pH value of threadfin breams in KGF group had the lowest pH value, which was 6.40±0.12. The threadfin breams in SWF group had the highest pH value, which was 6.78±0.25. The pH of fish in all experimental groups increased significantly (p<0.05). Ki value The threadfin breams in KGF group had the lowest Ki value, which was 9.05±0.73%. The threadfin breams in KWI group had the highest Ki value, which was 12.88±4.19%. The Ki value of all experimental groups of fish increased without statistical significance (p>0.05). In terms of freshness quality in microbiology, it was found that in all experimental groups, Salmonella spp., S. aureus, B. cereus, C. perfringens and E. coli were found in all experimental groups of threadfin breams. All types of microorganisms in all groups of threadfin breams increased with statistical significance (p<0.05). When compared with the freshness quality criteria in terms of sensory, chemical, physical, freshness index and microbiology, it was found that all groups of threadfin breams were very fresh and suitable for raw consumption during the preservation and storage for 3 days. After 3 days of storage, the threadfin breams should be consumed cooked because the freshness quality of the fish is not suitable for raw consumption due to the increase in various parameters. The increase in various parameters is due to the deterioration of the fish and the activities of microorganisms. Therefore, threadfin breams is suitable to promote raw consumption within 3 days of storage. In addition, fish preservation, especially by Ikejime method, then cutting open the belly and storing in the refrigerator, can help improve the freshness of the fish. The results of this study can be used to develop techniques for preserving fish after capture for fishermen and can promote the increase in the value of threadfin breams in the future.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
The concept for this work came from my curiosity about what would happen if, during interdimensional travel in space, a teleportation system were used. This system involves removing matter from one point and transferring it to another while maintaining its original state. If an error occurs and the matter is recreated or fused together, it could result in an experimental creature merging with the spacecraft. I choose the tardigrade as the first experimental subject for teleportation because the water bear has already been sent into space and survived. Therefore, I thought that if we were to actually test this teleportation system, the tardigrade would likely be one of the creatures chosen for experimentation.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
Durian is an important economic crop in Thailand that is affected by foliar diseases such as rust, leaf blight, and leaf spot. These diseases reduce the quality of the yield and increase management costs. This research focuses on developing AI software for screening durian leaf diseases by applying deep learning technology to classify different types of leaf lesions.