Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a blood metabolomics study based on ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and efficient machine learning approach was performed on 23 PQ poisoned patients and 29 healthy subjects. The initial PQ plasma concentrations of PQ poisoned patients were >1000 ng/mL, and the blood samples were collected at before first hemoperfusion (HP), after first HP, and after last HP. The results showed that PQ poisoned patients all differed from healthy subjects, whatever they were before or after first HP or after last HP. The efficient machine learning approaches selected key metabolites from three UPLC/Q-TOF-MS data sets which had the highest classification performance in terms of classification accuracy, Matthews Correlation Coefficients, sensitivity, and specificity, respectively. The mass identification revealed that the most important metabolite was adenosine, which sustained in low level, regardless of whether PQ poisoned patients received HP treatment. In conclusion, decreased adenosine was the most important metabolite in PQ poisoned patients. The metabolic disturbance caused by PQ poisoning cannot be improved by HP treatment even the PQ was cleared from the blood.
Purpose: To evaluate the effects of age and gender on meibomian gland (MG) parameters and the associations among MG parameters in aged people using a deep-learning based artificial intelligence (AI).Methods: A total of 119 subjects aged ≥60 were enrolled. Subjects completed an ocular surface disease index (OSDI) questionnaire, received ocular surface examinations including Meibography images captured by Keratograph 5M, diagnosis of meibomian gland dysfunction (MGD) and assessment of lid margin and meibum. Images were analyzed using an AI system to evaluate the MG area, density, number, height, width and tortuosity.Results: The mean age of the subjects was 71.61 ± 7.36 years. The prevalence of severe MGD and meibomian gland loss (MGL) increased with age, as well as the lid margin abnormities. Gender differences of MG morphological parameters were most significant in subjects less than 70 years old. The MG morphological parameters detected by AI system had strong relationship with the traditional manual evaluation of MGL and lid margin parameters. Lid margin abnormities were significantly correlated with MG height and MGL. OSDI was related to MGL, MG area, MG height, plugging and lipid extrusion test (LET). Male subjects, especially the ones who smoke or drink, had severe lid margin abnormities, and significantly decreased MG number, height, and area than the females.Conclusion: The AI system is a reliable and high-efficient method for evaluating MG morphology and function. MG morphological abnormities developed with age and were worse in the aging males, and smoking and drinking were risk factors.
Objectives: To investigate the causal association between hypertension and primary open-angle glaucoma (POAG). Methods: The hypertension-associated genome-wide association study (GWAS) was from UK biobank (UKB), involving 463010 participants. The GWAS of POAG is obtained from FinnGene project involving 4433 cases and 210201 controls. All participants were of European ancestry. The inverse-variance weighted (IVW) method was used as the primary analysis method to estimate the causality of hypertension on POAG. Meanwhile, MR Egger, weighted median, Weighted Median estimation, calculation of Cochran Q statistics, MR-Egger intercept test, MR-PRESSO global test and leave-one-out analysis were performed to verify the efficiency and consistency of the results. Results: A total of 57 hypertension related single-nucleotide polymorphisms (SNPs) were strongly associated with POAG after excluding potential confounders (old age, diabetes, myopia) and harmonizing the variants. IVW results showed that the incidence of POAG in patients with hypertension was 5.372 times higher than that in the control group (OR: 6.372, 95% CI: 1.824-22.262, P = 0.004). The results of Weighted median (OR: 9.707, P = 0.017), Maximum likelihood (OR: 6.642, P = 0.003), Penalised weighted median (OR: 9.696, P = 0.013) verified the casual association between hypertension and POAG. And the results of heterogeneity analysis, egger intercept and MR-PRESSO global test further confirmed the reliability of the findings. Conclusions: A causal association was suggested between genetically increased hypertension and higher risk of POAG. Long-term cohort studies are expected to verify the impact of hypertension on POAG.
Acetylharpagide is the main active component of the herb Ajuga decumbens, which possesses anti-tumor, antivirus, and anti-inflammation properties. In this study, ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to measure the concentration of 8-O-acetylharpagide in mouse blood, with subsequent investigation of the pharmacokinetics of the drug after intravenous or oral administration. Shanzhiside methyl ester was used as an internal standard, and the acetonitrile precipitation method was used to process the blood samples. Chromatographic separation was achieved using an ultra-performance liquid chromatography ethylene-bridged hybrid (UPLC BEH) column (2.1 mm × 50 mm, 1.7 μm) with a gradient methanol-water mobile phase (containing 0.1% formic acid). The flow rate was 0.4 mL/min, and the elution time was 5.0 min. 8-O-Acetylharpagide was quantitatively measured using electrospray ionization (ESI) tandem mass spectrometry in multiple reaction monitoring (MRM) mode with positive ionization. The result indicated that, within the range of 5-500 ng/mL, the linearity of 8-O-acetylharpagide in mouse blood was satisfactory (r > 0.995), and the lower limit of quantification (LLOQ) was 5 ng/mL. Intra-day precision relative standard deviation (RSD) of 8-O-acetylharpagide in blood was lower than 9%, and the inter-day precision RSD was lower than 13%. The accuracy range was between 94.3% and 107.1%, average recovery was higher than 91.3%, and the matrix effect was between 100.8% and 110.8%. This analytical method was sensitive and fast with good selectivity and was successfully applied to perform pharmacokinetic studies of 8-O-acetylharpagide in mice. The bioavailability of 8-O-acetylharpagide was 10.8%, and the analysis of the primary pharmacokinetic parameters after oral and intravenous administration indicated that 8-O-acetylharpagide had a significant first pass effect after oral administration.
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