Objective:To investigate the types of cervical epithelial cells and the Human Papillomavirus (HPV) infection subtypes of 7 646 women specimens in Anhui province, and provide evidence for cervical cancer prevention.Methods:Thinprep cytologic test (TCT) and flow fluorescence hybridization technique were used to detect cervical epithelial lesions and HPV subtypes.Results:The total positive rate for TCT was 20.25%, and the positive rate was the highest in ≥ 60 age group (28.41%), followed by 10 to ≤ 19 age group (26.32%). The atypical squamous cells-undetermined significance (ASC-US), cannot exclude high-grade squamous intraepithelial lesion (ASC-H) and HSIL positive rates were the highest in the ≥60 age group, and the low-grade squamous intraepithelial lesions (LSIL) positive rate was highest in the 10-19 age group. The proportion of patients with 40-49 age group was the highest, and that of ≥60 age group was the highest. The single infection rate of different cervical epithelial cell lesions was higher than that of multiple infection rates. As the deepening degree of the lesion, the high-risk single infection rate of HPV showed a increasing trend from ASCUS, LSIL, ASC-H to high-grade squamous intraepithelial lesions (HSIL); The common subtypes of HPV infection in negative for intraepithelial lesion or malignancy (NILM) are 52, 16, 58, 53 and 6. The common subtypes of ASCUS are 52, 16, 53, 58 and 51. The common subtypes of ASC-H are 18, 58 and16. LSIL common subtypes are 16, 52, 56, 58, 53 and 66, HSIL common subtypes are16, 58, 33, 52 and 59 type.Conclusions:The high risk and single genotypes of infection were dominant in different cervical epithelial cell lesions in Anhui. Women who aged ≥60 should pay attention and regularly undergo HPV testing and cervical cancer screening. The HPV infection subtypes of different cervical epithelial cell lesions are different, and the common subtypes are HPV52, 16, 58, 53, among which types 16, 58 and 33 are common infection subtypes detected in different lesions.

Objective:To explore the feasibility of deep learning-based restoration of obscured thyroid ultrasound images.Methods:A total of 358 images of thyroid nodules were retropectively collected from January 2020 to October 2021 at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, and the images were randomly masked and restored using DeepFillv2. The difference in grey values between the images before and after restoration was compared, and 6 sonographers (2 chief physicians, 2 attending physicians, 2 residents) were invited to compare the rate of correctness of judgement and detection of image discrepancies. The ultrasound features of thyroid nodules (solid composition, microcalcifications, markedly hypoechoic, ill-defined or irregular margins, or extrathyroidal extensions, vertical orientation and comet-tail artifact) were extracted according to the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS). The consistency of ultrasound features of thyroid nodules before and after restoration were compared.Results:The mean squared error of the images before and after restoration ranged from 0.274 to 0.522, and there were significant differences in the rate of correctness of judgement and detection of image discrepancies between physicians of different groups(all P<0.001). The overall accuracy rate was 51.95%, the overall detection rate was 1.79%, there were significant differences also within the chief physicians and resident groups (all P<0.001). The agreement rate of all ultrasound features of the nodules before and after image restoration was higher than 70%, over 90% agreement rate for features such as solid composition and comet-tail artifact. Conclusions:The algorithm can effectively repair obscured thyroid ultrasound images while preserving image features, which is expected to expand the deep learning image database, and promote the development of deep learning in the field of ultrasound images.

Beta-lactams are the most widely used antibiotics. One of the principle mechanisms for Gram-negative bacteria to resist β-lactams is by producing β-lactamases that degrade β-lactams. This review highlights two regulatory mechanisms for inducing β-lactamase in Gram-negative bacteria. In the ampR-ampC paradigm, the induction of β-lactamase is intimately linked to peptidoglycan recycling. AmpR, a LysR-type transcriptional regulator, plays a central role in regulating expression of β-lactamase. Recent studies found that two-component signal transduction pathway is activated by β-lactams, which in turn induces the expression of β-lactamase. Finally, we discussed the future research directions in β-lactam resistance in Gram-negative bacteria.