Comparison of R-Peak and T-Peak Detection Between Scipy and Neurokit2 Library Using Python

Abstract

Antibiotic resistance is currently reaching alarmingly high levels throughout the world. The discovery of novel antibiotic resistance mechanisms threatens our ability to treat contagious diseases. Antibiotic resistance is a severe issue for doctors who treat infectious diseases because it is associated with increased morbidity and mortality rates. The urgency also occurs in the primary clinic in Klang Valley, Malaysia. Some patients are displaying clinical signs of resistance to the prescribed drug. Clinical evidence of the resistance was the continued growth of the infection after therapy, which was indicated by a protracted sickness and no improvement in signs and symptoms after treatment with conventional antibiotics. Thus the profiling of antibiotic-resistant genes from each participant's sample will be the main focus of this investigation. PCR from the throat swab sample is conducted to validate antibiotic resistance by detecting the presence of antibiotic-resistant genes in bacterial samples. The presence of the ermC, gyrA, gyrB, grlA, grlB, and tetA genes—which result in resistance to specific antibiotics—was confirmed by the PCR result. However, all samples lacked the ermB and tetK genes. So, it is evident that the ermB and tetK genes do not bring about the resistance effect in these situations. In addition, because the primers for the genes ermA, mrsA, tetM, blaAmpC, tetB, tetC, and tetD are not explicitly bound to the region of the genes, the thus unspecific result was obtained.