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Cordyceps militaris extract (CME) contains many bioactive compounds, mainly cordycepin (CPN). This study aimed to investigate the possible mechanisms underlying the amelioration of LPS-induced acute liver injury in piglets by CME or CPN supplementation using multi-omics analysis. Twenty-four weaned piglets were randomly distributed into 4 groups (n = 6): the control and LPS groups were fed basal diets; the CPN + LPS (CPN-LPS) and CME + LPS (CME-LPS) groups were fed the basal diets supplemented with CME or CPN. The results showed that CPN or CME supplementation significantly decreased the C-reactive protein level (p < 0.05) and improved liver tissue pathology to prevent acute liver injury after LPS treatment. Compared with LPS, the transcriptomic analysis indicated that CPN supplementation significantly downregulated cell adhesion molecules, while CME supplementation significantly downregulated inflammatory mediator regulation of TRP channels, complement and coagulation cascades and cytokine-cytokine receptor interaction. The metabolomic results showed that CPN or CME supplementation significantly reduced disease biomarker of bicyclo-prostaglandin E2, and increased levels of deoxyinosine and 3-hydroxyanthranilic acid (p < 0.05). The combined transcriptome and metabolome helped identify two metabolites PC 34:2 and PC 36:0, which may be associated with the restoration of liver cell morphology. In conclusion, CPN and CME could attenuate LPS-induced acute liver injury by regulating immune-related genes and metabolites. This study elucidates the potential protective mechanism of CPN or CME supplementation against acute liver injury.

Cordycepin is considered a major bioactive component in Cordyceps militaris extract. This study was performed to evaluate the ameliorative effect of Cordyceps militaris extract (CME) and cordycepin (CPN) supplementation on intestinal damage in LPS-challenged piglets. The results showed that CPN or CME supplementation significantly increased the villus height (p < 0.01) and villus height/crypt depth ratio (p < 0.05) in the jejunum and ileum of piglets with LPS-induced intestinal inflammation. Meanwhile, CPN or CME supplementation alleviated oxidative stress and inflammatory responses by reducing the levels of MDA (p < 0.05) and pro-inflammatory cytokines in the serum. Additionally, supplementation with CPN or CME modulated the structure of the intestinal microbiota by enriching short-chain fatty acid-producing bacteria, and increased the level of butyrate (p < 0.05). The RNA-seq results demonstrated that CME or CPN altered the complement and coagulation-cascade-related genes (p < 0.05), including upregulating gene KLKB1 while downregulating the genes CFD, F2RL2, CFB, C4BPA, F7, C4BPB, CFH, C3 and PROS1, which regulate the complement activation involved in inflammatory and immune responses. Correlation analysis further demonstrated the potential relation between the gut microbiota and intestinal inflammation, oxidative stress, and butyrate in piglets. In conclusion, CPN or CME supplementation might inhibit LPS-induced inflammation and oxidative stress by modulating the intestinal microbiota and its metabolite butyrate in piglets.

Objective: We aimed to develop an algorithm that accurately identifies children with Down syndrome (DS) using administrative data., Methods: We identified a cohort of children born between 2000 and 2017, enrolled in the Tennessee Medicaid Program (TennCare), who either had DS coded on their birth certificate or had a diagnosis listed using an International Classification of Diseases (ICD) code (suspected DS), and who received care at Vanderbilt University Medical Center, a comprehensive academic medical center, in the United States. Children with suspected DS were defined as having DS if they had (a) karyotype-confirmed DS indicated on their birth certificate; (b) karyotype-pending DS indicated on their birth certificate (or just DS if test type was not specified) and at least two healthcare encounters for DS during the first 6 years of life; or (c) at least three healthcare encounters for DS, with the first and last encounter separated by at least 30 days, during the first six years of life. The positive predictive value (PPV) of the algorithm and 95% confidence interval (CI) were reported., Results: Of the 411 children with suspected DS, 354 (86.1%) were defined as having DS by the algorithm. According to medical chart review, the algorithm correctly identified 347 children with DS (PPV = 98%, 95%CI: 96.0-99.0%). Of the 57 children the algorithm defined as not having DS, 50 (97.7%, 95%CI: 76.8-93.9%) were confirmed as not having DS by medical chart review., Conclusions: An algorithm that accurately identifies individuals with DS using birth certificate data and/or ICD codes provides a valuable tool to study DS using administrative data.