A child manikin for Cardiopulmonary Resuscitation (CPR) training includes the trachea mechanism, neck mechanism, lung mechanism, heart pump mechanism, artificial skin, and sensor system. All components work together to function similar to a real child. It can be used to practice heart pumping and resuscitation. The manikin has been designed and verified by resuscitation experts. It has a system to evaluate the accuracy of the training and display the results on the computer for real-time monitoring.
ปัจจุบันในท้องตลาดมีหุ่นสำหรับฝึกการกู้ชีพมากมาย แต่หุ่นจำลองเด็กสำหรับฝึกการกู้ชีพยังไม่พบมากนัก นอกจากนี้หุ่นที่มีขายในท้องตลาดยังขาดระบบการประเมินผลการฝึกที่แม่นยำ ไม่มีการรับรองความถูกต้องของผลที่ได้จากการใช้งาน ดังนั้นในงานวิจัยนี้จึงประดิษฐ์หุ่นจำลองเด็กอัจฉริยะสำหรับฝึกการกู้ชีพ โดยหุ่นมีกลไกหลอดลม กลไกคอ กลไกปอด กลไกการปั้มหัวใจ ผิวหนังเทียม และระบบเซนเซอร์ ทั้งหมดทำงานร่วมกันคล้ายเด็กจริง โดยมีระบบผู้เชี่ยวชาญ (Expert System) ทำหน้าที่ประเมินผลการฝึกฝนและแสดงแบบทันทีบนหน้าจอ หุ่นนี้ได้รับการตรวจสอบและยืนยันความถูกต้องจากการใช้งานโดยผู้เชี่ยวชาญด้านการกู้ชีพตัวจริง
คณะวิทยาศาสตร์
Cancer remains a major global health challenge as the second-leading cause of human death worldwide. The traditional treatments for cancer beyond surgical resection include radiation and chemotherapy; however, these therapies can cause serious adverse side effects due to their high killing potency but low tumor selectivity. The FDA approved monoclonal antibodies (mAbs) that target TIGIT/PVR (T-cell immunoglobulin and ITIM domain/poliovirus receptor) which is an emerging immune checkpoint molecules has been developed; however, the clinical translation of immune checkpoint inhibitors based on antibodies is hampered due to immunogenicity, immunological-related side effects, and high costs, even though these mAbs show promising therapeutic efficacy in clinical trials. To overcome these bottlenecks, small-molecule inhibitors may offer advantages such as better oral bioavailability and tumor penetration compared to mAbs due to their smaller size. Here, we performed structure-based virtual screening of FDA-approved drug repertoires. The 100 screened candidates were further narrowed down to 10 compounds using molecular docking, with binding affinities ranging from -9.152 to -7.643 kcal/mol. These compounds were subsequently evaluated for their pharmacokinetic properties using ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, which demonstrated favorable drug-like characteristics. The lead compounds will be further analyzed for conformational changes and binding stability against TIGIT through molecular dynamics (MD) simulations to ensure that no significant conformational changes occur in the protein structure. Collectively, this study represents the potential of computational methods and drug repurposing as effective strategies for drug discovery, facilitating the accelerated development of novel cancer treatments.
คณะอุตสาหกรรมอาหาร
Tepache is a traditional Mexican fermented beverage commonly made using pineapple peels, which naturally contain sugars and the enzyme bromelain. These components contribute to its distinctive aroma and unique flavor. This project aims to develop a health-enhancing tepache by fermenting pineapple peels with probiotic yeast and lactic acid bacteria. Additionally, prebiotics, including inulin and xylo-oligosaccharides, are incorporated as nutrients to support probiotic growth. The resulting synbiotic tepache promotes gut microbiota balance, exhibits antioxidant properties, and enhances the immune system, making it a functional and beneficial beverage for consumers.
คณะวิทยาศาสตร์
Otitis Media is an infection of the middle ear that can occur in individuals of all ages. Diagnosis typically involves analyzing images taken with an otoscope by specialized physicians, which relies heavily on medical experience to expedite the process. This research introduces computer vision technology to assist in the preliminary diagnosis, aiding expert decision-making. By utilizing deep learning techniques and convolutional neural networks, specifically the YOLOv8 and Inception v3 architectures, the study aims to classify the disease and its five characteristics used by physicians: color, transparency, fluid, retraction, and perforation. Additionally, image segmentation and classification methods were employed to analyze and predict the types of Otitis Media, which are categorized into four types: Otitis Media with Effusion, Acute Otitis Media with Effusion, Perforation, and Normal. Experimental results indicate that the classification model performs moderately well in directly classifying Otitis Media, with an accuracy of 65.7%, a recall of 65.7%, and a precision of 67.6%. Moreover, the model provides the best results for classifying the perforation characteristic, with an accuracy of 91.8%, a recall of 91.8%, and a precision of 92.1%. In contrast, the classification model that incorporates image segmentation techniques achieved the best overall performance, with an mAP50-95 of 79.63%, a recall of 100%, and a precision of 99.8%. However, this model has not yet been tested for classifying the different types of Otitis Media.