Linoleic acid (LA), an essential fatty acid, has emerged as a pivotal regulator in disorders associated with inflammation in recent years; however, the underlying mechanisms are still not completely understood. We utilized network pharmacology and experimental methodologies to elucidate the mechanisms underlying the anti-inflammatory effects of LA. Our network pharmacology analysis revealed that LA shares common targets with sepsis. These targets are enriched in various pathways comprising C-type signaling pathway, PI3K-Akt signaling pathway, toll-like receptor signaling pathway, neutrophil extracellular trap formation, AMPK signaling pathway, and autophagy-animal. These findings suggest that LA may exert regulatory effects on inflammation and autophagy during sepsis. Subsequently, we established in vivo and ex vivo models of sepsis using lipopolysaccharide (LPS) in experimental study. Treatment with LA reduced lung damage in mice with LPS-induced lung injury, and reduced tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in plasma, bronchoalveolar lavage fluid (BALF), and peritoneal lavage fluid (PLF). LA also decreased the production of TNF-α and IL-6 in RAW264.7 macrophages exposed to LPS. In LPS-induced RAW264.7 macrophages, LA induced an elevation in LC3-II while causing a reduction in p62, which was associated with downregulation of toll-like receptor 4 (TLR4). We utilized 3-methyladenine (3-MA) to inhibit the autophagic activity, which reversed the modulatory effects of LA on LC3-II and p62. 3-MA also prevented the decline in TLR4 expression along with reduction in pro-inflammatory cytokines secretion. Our findings suggest that the activation of autophagy by LA may lead to the downregulation of TLR4, thereby exerting its anti-inflammatory effects.

• MeSH
• autofagie * účinky léků   MeSH
• kyselina linolová * farmakologie   MeSH
• lipopolysacharidy * toxicita   MeSH
• makrofágy * účinky léků   metabolismus   imunologie   MeSH
• myši MeSH
• RAW 264.7 buňky MeSH
• sepse chemicky indukované   farmakoterapie   metabolismus   imunologie   MeSH
• signální transdukce účinky léků   MeSH
• toll-like receptor 4 * metabolismus   MeSH
• zánět * metabolismus   farmakoterapie   chemicky indukované   patologie   MeSH
• zvířata MeSH
• Check Tag
• mužské pohlaví MeSH
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC using a single test remains unfeasible due to the low prevalence and potential harms of false positives. Non-contrast computed tomography (CT), routinely performed for clinical indications, offers the potential for large-scale screening, however, identification of PDAC using non-contrast CT has long been considered impossible. Here, we develop a deep learning approach, pancreatic cancer detection with artificial intelligence (PANDA), that can detect and classify pancreatic lesions with high accuracy via non-contrast CT. PANDA is trained on a dataset of 3,208 patients from a single center. PANDA achieves an area under the receiver operating characteristic curve (AUC) of 0.986-0.996 for lesion detection in a multicenter validation involving 6,239 patients across 10 centers, outperforms the mean radiologist performance by 34.1% in sensitivity and 6.3% in specificity for PDAC identification, and achieves a sensitivity of 92.9% and specificity of 99.9% for lesion detection in a real-world multi-scenario validation consisting of 20,530 consecutive patients. Notably, PANDA utilized with non-contrast CT shows non-inferiority to radiology reports (using contrast-enhanced CT) in the differentiation of common pancreatic lesion subtypes. PANDA could potentially serve as a new tool for large-scale pancreatic cancer screening.

• MeSH
• deep learning * MeSH
• duktální karcinom slinivky břišní * diagnostické zobrazování   patologie   MeSH
• lidé MeSH
• nádory slinivky břišní * diagnostické zobrazování   patologie   MeSH
• pankreas diagnostické zobrazování   patologie   MeSH
• počítačová rentgenová tomografie MeSH
• retrospektivní studie MeSH
• umělá inteligence MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH