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Purpose: Intra-abdominal infections (IAI) are gradually becoming common in the emergency department, though the incidence is low and the prognosis is fair, as the symptoms are similar to other intra-abdominal diseases, rapid and accurate diagnosis of the causative agents is essential for clinical management. This study aimed to evaluate the diagnostic performance of metagenomic next-generation sequencing (mNGS) in detecting IAI in the emergency department. Patients and Methods: This was a retrospective, single-centered study including patients admitted to the emergency department from January 1st, 2021 to August 31st, 2022 with diagnosis of IAI. The comparison between mNGS and microbial culture using paracentesis fluid samples was performed to evaluate the diagnostic performance of mNGS for IAI. Meanwhile, paracentesis fluid and peripheral blood mNGS were compared to explore the sample specificity. Further, the microbial community structure of the patients with pyogenic liver abscesses (PLA) was analyzed. Results: Thirty-four IAI patients including 23 with pyogenic liver abscesses (PLA), 3 with parapancreatic abscesses, and 8 with other IAI were included in this study. Compared with the conventional microbial culture of paracentesis fluid, mNGS using paracentesis fluid detected more positive cases of IAI (93.75% vs 81.25%), and identified more species of pathogens, especially in obligate anaerobes and viral pathogens. Peripheral blood mNGS presented a relatively high consistency with the paracentesis fluid mNGS (91% mutual positive). The microbial community structure of PLA patients with diabetes is less diverse than that of those without diabetes. Patients with diabetes are at high risk of PLA caused by Klebsiella pneumonia. Conclusion: mNGS has advantages in detecting IAI in the emergency department, and peripheral blood mNGS can be a non-invasive choice for early diagnosis.
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Lung cancer has high incidence and mortality rates, in which lung squamous cell carcinoma (LUSC) is a primary type of non-small cell lung carcinoma (NSCLC). The aim of our study was to discover long non-coding RNAs (lncRNAs) associated with diagnose and prognosis for LUSC. RNA sequencing data obtained from LUSC samples were extracted from The Cancer Genome Atlas database (TCGA). Two prognosis-associated lncRNAs (including SFTA1P and LINC00519) were selected from LUSC samples, and the expression levels were also verified to be associated abnormal in LUSC clinical samples. Our findings demonstrate that lncRNAs SFTA1P and LINC00519 exert important functions in human LUSC and may serve as new targets for LUSC diagnosis and therapy.
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Alzheimer's disease (AD) is characterized by amyloid plaques and neurofibrillary tangles associated with chronic inflammation. APPswe/PS1dE9 is an AD mouse model bearing mutant transgenes of amyloid precursor protein and presenilin-1. Amyloid deposition is present in this mouse model at early stage of life. However, the progression of inflammation and its relationship with amyloid deposition have not been characterized. Here we showed that amyloid plaques were present at 4 months of age and increased with age. CD11b-positive microglia clusters appeared in hippocampus and neocortex at 4 months of age and increased with age. Clustered glial fibrillary acidic protein (GFAP)-positive astrocytes were observed in hippocampus and cortex after 6 months of age and increased with age. Double staining with CD11b/GFAP antibody and thioflavin S showed clustered microglia and astrocytes were in close association with amyloid plaques. Expression of TNF-alpha was detected at 8 months of age, while IL-1 beta, IL-6 and MCP-1 at 10 months. These cytokines increased with age. Double immunostaining of cell specific marker and cytokine indicated TNF-alpha, IL-1 beta, IL-6 and MCP-1 were expressed by activated microglia and a small part of activated astrocytes. MCP-1 was also expressed by neurons, which support recent finding that MCP-1 expression was increased in neurons of AD patient. These results demonstrate amyloid plaques and its associated inflammatory response developed at early stage of life and progressively increased with age, both activated glia and neurons are involved in chronic inflammation in AD. APPswe/PS1dE9 model provides a mean for studying the mechanisms and novel therapeutics for AD.