A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including tuberculosis. We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing image preprocessing, data augmentation, and deep learning classification techniques. Four distinct deep CNNs (Xception, InceptionV3, InceptionResNetV2, and MobileNetV2) were trained, validated, and evaluated for the classification of tuberculosis and nontuberculosis cases using transfer learning from their pretrained starting weights. With an F1-score of 99 percent, InceptionResNetV2 had the highest accuracy. This research is more accurate than earlier published work. Additionally, it outperforms all other models in terms of reliability. The suggested approach, with its state-of-the-art performance, may be helpful for computer-assisted rapid TB detection.

Partial purification and characterization of glutathione S-transferase from the somatic tissue of Gastrothylax crumenifer (Trematoda: Digenea).

AIM: Aim of the present study was to carry out the partial purification and biochemical characterization of glutathione S-transferase (GST) from the somatic tissue of ruminal amphistome parasite, Gastrothylax crumenifer (Gc) infecting Indian water buffalo (Bubalus bubalis). MATERIALS AND METHODS: The crude somatic homogenate of Gc was subjected to progressive ammonium sulfate precipitation followed by size exclusion chromatography in a Sephacryl S 100-HR column. The partially purified GST was assayed spectrophotometrically, and the corresponding enzyme activity was also recorded in polyacrylamide gel. GST isolated from the amphistome parasite was also exposed to variable changes in temperature and the pH gradient of the assay mixture. RESULTS: The precipitated amphistome GST molecules showed maximum activity in the sixth elution fraction. The GST subunit appeared as a single band in the reducing polyacrylamide gel electrophoresis with an apparent molecular weight of 26 kDa. The GST proteins were found to be fairly stable up to 37°C, beyond this the activity got heavily impaired. Further, the GST obtained showed a pH optima of 7.5. CONCLUSION: Present findings showed that GST from Gc could be conveniently purified using gel filtration chromatography. The purified enzyme showed maximum stability and activity at 4°C.