Publications by authors named "Jian-feng Lin"

Objective: To analyze the clinical characteristics of neonatal infection during the outbreak of COVID-19 omicron variant in Guangdong province of China.

Method: The clinical data of neonates infected with COVID-19 omicron variant were collected from three hospitals of Guangdong province, their epidemiological history, clinical manifestation and prognosis were summarized.

Results: From December 12, 2022 to January 15, 2023, a total of 52 neonates with COVID-19 infection were identified across three hospitals in Guangdong Province, including 34 males and 18 females.

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Objective: We aimed to develop a deep learning artificial intelligence (AI) algorithm to detect impacted animal bones on lateral neck radiographs and to assess its effectiveness for improving the interpretation of lateral neck radiographs.

Methods: Lateral neck radiographs were retrospectively collected for patients with animal bone impaction between January 2010 and March 2020. Radiographs were then separated into training, validation, and testing sets.

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Background: Families play a prominent role in the eventual organ donation decision. Because the deceased cannot directly express their wishes, their families become the actual decision makers. In China, families are permitted to make decisions regarding organ donation that may not be in accordance with the wishes of the deceased family member, and objections by families are a main bottleneck in the donation process.

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Visible stain is still the most popular protein staining method used in proteomic approaches. However, most published data have been derived from comparisons between visible dyes and fluorescent dyes. In this work, we have focused on seven widely used visible staining procedures--Neuhoff CCB, blue silver, and five silver stains (LKB SN, He SN, Yan SN, Vorum SN, and Blum SN)--and studied their stain efficiencies and MALDI-TOF MS compatibilities on 1-D and 2-D PAGE.

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Although serum prostate specific antigen (PSA) is a well-established diagnostic tool for prostate cancer (PCa) detection, the definitive diagnosis of PCa is based on the information contained in prostate needle biopsy (PNBX) specimens. To define the proteomic features of PNBX specimens to identify candidate biomarkers for PCa, PNBX specimens from patients with PCa or benign prostatic hyperplasia (BPH) were subjected to comparative proteomic analysis. 2-DE revealed that 52 protein spots exhibited statistically significantly changes among PCa and BPH groups.

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