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Background: Pyroptosis is the term for caspase-1-dependent cell death associated with pro-inflammatory cytokines. The role of alveolar macrophage (AM) pyroptosis in the pathogenesis of the acute lung injury and acute respiratory distress syndrome (ALI/ARDS) remains unclear. Methods: C57BL/6 wild-type mice were assigned to sham, lipopolysaccharide (LPS) + vehicle, LPS + acetyl-tyrosyl-valyl- alanyl-aspartyl-chloromethylketone (Ac-YVAD-CMK) and LPS + Z-Asp-Glu-Val-Asp-fluoromethylketone groups. Mice were given intraperitoneal (IP) injections of LPS. Drugs were IP injected 1 h before LPS administration. Mice were sacrificed 16 h after LPS administration, and AMs were isolated. Western blot analysis for active caspase-1 and cleaved caspase-3, evaluation of lung injury and a cytokine release analysis were performed. AMs were treated with LPS and adenosine triphosphate (ATP); caspase-1-dependent cell death was evaluated using flow cytometry; the apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) pyroptosomes were examined by immunofluorescence. Results: The expression of activated caspase-1 in AMs was enhanced following LPS challenge compared with the sham group. In the ex vivo study, the caspase-1/propidium iodide-positive cells, caspase-1 specks and ASC pyroptosomes were up-regulated in AMs following LPS/ATP stimulation. The specific caspase-1 inhibitor Ac-YVAD-CMK inhibited the activation of caspase-1 and pyroptotic cell death. Ac-YVAD-CMK also reduced the lung injury, pulmonary edema and total protein in bronchoalveolar lavage fluid (BALF). In addition, Ac-YVAD-CMK significantly inhibited interleukin-α2 (IL-1α2) release both in serum and BALF and reduced the levels of IL-18, tumor necrosis factor-α± (TNF-α±), High Mobility Group Box 1 (HMGB1) in BALF during LPS-induced ALI/ARDS. Conclusions: This study reported AM pyroptosis during LPS-induced ALI/ARDS in mice and has demonstrated that Ac-YVAD-CMK can prevent AM-induced pyroptosis and lung injury. These preliminary findings may form the basis for further studies to evaluate this pathway as a target for prevention or reduction of ALI/ARDS.

As the issue of traditional antibiotic resistance continues to worsen, exploring new antimicrobial substances has become crucial to addressing this challenge. Antimicrobial peptides (AMPs), recognized for their low resistance levels and minimal bacterial mutation frequencies, have garnered significant attention from researchers. However, traditional screening methods for AMPs are inefficient and costly. This study proposes a combined AMP screening model based on long short-term memory (LSTM) neural networks with an attention mechanism. By analyzing the characteristics of peptide segments, which are simulated enzymatic hydrolysis products of proteins expressed in sludge microbial genomes, the model accurately identifies peptide segments with potential antimicrobial activity. Molecular docking and dynamic simulation results validate three potential antimicrobial peptide candidates: LLPRLLARRY, GVREIHGLNPGGCLHTVRLVCR, and FRTTLAPHVLTRLLAPCW. These candidates exhibit high binding stability and affinity with target proteins, confirming the efficiency of the proposed AMP screening model.