Label-free white blood cells classification using a deep feature fusion neural network.

White blood cell (WBC) classification is a valuable diagnostic approach for identifying diseases. However, conventional methods for WBC detection, such as flow cytometers, have limitations in terms of their high cost, large system size, and laborious staining procedures. As a result, deep learning-based label-free WBC image analysis methods are gaining popularity. Nevertheless, most existing deep learning WBC classification techniques fail to effectively utilize the subtle differences in the internal structures of WBCs observed under a microscope. To address this issue, we propose a neural network with feature fusion in this study, which enables the detection of label-free WBCs. Unlike conventional convolutional neural networks (CNNs), our approach combines low-level features extracted by shallow layers with high-level features extracted by deep layers, generating fused features for accurate bright-field WBC identification. Our method achieves an accuracy of 80.3 % on the testing set, demonstrating a potential solution for deep-learning-based biomedical diagnoses. Considering the proposed method simplifies the cell detection process and eliminates the need for complex operations like fluorescent staining, we anticipate that this automatic and label-free WBC classification network could facilitate more precise and effective analysis, and it could contribute to the future adoption of miniatured flow cytometers for point-of-care (POC) diagnostics applications.

Rosmarinic acid alleviates septic acute respiratory distress syndrome in mice by suppressing the bronchial epithelial RAS-mediated ferroptosis.

Activating angiotensin-converting enzyme 2 (ACE2) is an important player in the pathogenesis of septic-related acute respiratory distress syndrome (ARDS). Rosmarinic acid (RA) as a prominent polyphenolic secondary metabolite derived from Rosmarinus officinalis modulates ACE2 in sepsis remains unclear, although its impact on ACE inhibition and septic-associated lung injury has been explored. The study investigated the ACE2 expression in lipopolysaccharide (LPS)-induced lungs in mice and BEAS2B cells. Additionally, molecular docking, protein-protein interaction (PPI) network analysis, and western blotting were employed to predict and evaluate the molecular mechanism of RA on LPS-induced ferroptosis in vivo and in vitro. LPS-induced glutathione peroxidase 4 (GPX4) downregulation, ACE/ACE2 imbalance, and alteration of frequency of breathing (BPM), minute volume (MV), and the expiratory flow at 50% expired volume (EF50) were reversed by captopril pretreatment in vitro and in vivo. RA notably inhibited the infiltration into the lungs of neutrophils and monocytes with increased amounts of GPX4 and ACE2 proteins, lung function improvement, and decreased inflammatory cytokines levels and ER stress in LPS-induced ARDS in mice. Molecular docking showed RA was able to interact with ACE and ACE2. Moreover, combined with different pharmacological inhibitors to block ACE and ferroptosis, RA still significantly inhibited inflammatory cytokines Interleukin-1ß (IL-1ß), tumor necrosis factor-α (TNF-α), and C-X-C motif chemokine 2 (CXCL2) levels, as well as improved lung function, and enhanced GPX4 expression. Particularly, the anti-ferroptosis effect of RA in LPS-induced septic ARDS is RAS-dependent.