Radiotherapy is the main way to treat the Nasopharyngeal Carcinoma. But there are a lot of serious complications, the most common one of then is radioactive xerostomia. It seriously affect the patients's quality of life, even make patients change or stop their radiotherapy. It is extremely important to prevent and treat xerostomia caused by radiotherapy.
Carcinoma ; Humans ; Nasopharyngeal Carcinoma ; Nasopharyngeal Neoplasms ; complications ; radiotherapy ; Quality of Life ; Radiotherapy ; adverse effects ; Xerostomia ; etiology ; prevention & control

Microbial nitrilases have attracted increasing attention in nitrile hydrolysis for carboxylic acid production in recent years. A bacterium with nitrilase activity was isolated and identified as Pseudomonas putida CGMCC3830 based on its morphology, physiological and biochemical characteristics, as well as 16S rRNA gene sequence. The nitrilase production was optimized by varying culture conditions using the one-factor-at-a-time method and response surface methodology. Glycerol 13.54 g/L, tryptone 11.59 g/L, yeast extract 5.21 g/L, KH2PO4 1 g/L, NaCl 1 g/L, urea 1 g/L, initial pH 6.0 and culture temperature 30 degrees C were proved to be the optimal culture conditions. It resulted in the maximal nitrilase production of 36.12 U/mL from 2.02 U/mL. Investigations on substrate specificity demonstrate P. putida nitrilase preferentially hydrolyze aromatic nitriles. When applied in nicotinic acid synthesis, 2 mg/mL P. putida cells completely hydrolyzed 20.8 g/L 3-cyanopyridine into nicotinic acid in 90 min. The results indicated P. putida CGMCC3830 displayed potential for industrial production of nicotinic acid.
Aminohydrolases ; biosynthesis ; Culture Media ; Hydrolysis ; Niacin ; biosynthesis ; Nitriles ; metabolism ; Pseudomonas putida ; enzymology ; Pyridines ; metabolism ; RNA, Ribosomal, 16S ; genetics ; Substrate Specificity ; Temperature

Objective:To investigate the diagnostic performance of a new artificial intelligence (AI) model incorporating SAM-YOLOV 5 deep learning network and image processing techniques for Breast Imaging Reporting and Data System (BI-RADS) 4 category breast masses in dynamic ultrasound classification.Methods:A total of 530 pathologically proven breast lesions of BI-RADS category 4 in 458 patients were retrospectively collected from May 2019 to June 2023 at the First Affiliated Hospital of Shantou University Medical College. The model was trained and tested at ratio of 7∶3, the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value of the model were determined. Firstly, the test results of the model were compared with a single static image, then, compared with the three conventional deep learning networks as well as senior and junior radiologists. The diagnostic efficiency of the new model in BI-RADS categories 4a, 4b, and 4c masses were analyzed.Results:The AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model based on dynamic ultrasound video were higher than those using a single ultrasound static imaging (all P<0.05). Based on dynamic ultrasound video, the AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model were significantly higher than those of YOLOV 5, VGG 16, Resnet 50 and the junior group (all P<0.05), lower than the senior group (just specificity and negative predictive value, P<0.05). The diagnostic efficiency of new model for BI-RADS category 4b masses was the lowest. Conclusions:Based on the SAM-YOLOV 5 deep learning network and image processing techniques, the new model has a high diagnostic value for breast mass dynamic ultrasound classification and is expected to be used in assisting clinical diagnosis.

Due to the availability of 18F-FDG in PET centers, this article aims to advocate and promote the standardization of 18F-FDG PET brain imaging in dementia in order to improve the reliability, repeatability and comparison of the imaging process and results. It is also provided to guide the PET imaging operation standard and to give suggestions on image interpretation.