A fully-automatic semi-supervised deep learning model for difficult airway assessment.

Background: Difficult airway conditions represent a substantial challenge for clinicians. Predicting such conditions is essential for subsequent treatment planning, but the reported diagnostic accuracies are still quite low. To overcome these challenges, we developed a rapid, non-invasive, cost-effective, and highly-accurate deep-learning approach to identify difficult airway conditions through photographic image analysis.

The protective effects of Omarigliptin against Lipopolysaccharide (LPS)- induced inflammatory response and expression of mucin 5AC (MUC5AC) in human bronchial epithelial cells.

The epidemic of chronic inflammatory lung diseases such as asthma, bronchitis, and chronic obstructive pulmonary disease (COPD) has become a global public health problem. Oxidative stress, inflammation, and overproduction of airway mucus play critical roles in the progression of these diseases. Omarigliptin, an oral dipeptidyl peptidase 4 (DPP-4) inhibitor, has been demonstrated to have anti-inflammatory effects in patients with type II diabetes.

[Comparison of the efficacy of different venous intubation in venous-arterial extracorporeal membrane oxygenation assisted lung transplantation].

Objective: To compare the curative effects of different venous cannulas and drainage to improve patient's whole body oxygenation during the auxiliary process of venous-arterial extracorporeal membrane oxygenation (VA-ECMO) in lung transplantation.

Methods: From December 2016 to December 2019, 12 patients who were assisted by VA-ECMO in one lung transplantation in People's Hospital of Henan Province were selected as the research objects. According to the number of side holes of venous cannulas, they were divided into two groups: one group with few side holes and other group with multiple side holes.