Untargeted metabolomics reveals novel serum biomarker of renal damage in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic progressive disease, it often involves kidney, lung, heart, and other systems.Renal damage is quite common in RA. Exploring of biomarkers of renal damage in the course of RA progression is of significant importance for disease diagnosis and treatment. We use type II Collagen-Induced Arthritis(CIA) Model. Serums were collected at the 4th, 6th, 8th, and 10th week after the first immunization. An untargeted metabonomic strategy based on UPLC-Q/TOF/MS with support vector machine(SVM) was developed to discover the biomarkers in the rats' serum samples between the RA stage(4-6 weeks in RA model, at which time the kidneys are not affected) and renal damage in RA stage(8-10 weeks in RA model, and the kidneys are affected). Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to analyze the metabolic profiles of rat serum. The support vector machine (SVM) method was used to screen the specific markers of renal damage in RA. Following multivariate statistical and integration analysis, 5 specific markers of renal damage in RA were screened and found. After the analysis of these metabolites, pentose and glucuronate interconversions are closely related to the pathogenesis of RA renal damage. The present study first use untargeted dmetabonomics combined with the pathological features in the different phases of CIA model rats. This will provide a basis for the choice of treatment drugs for patients with RA who may be complicated by renal damage.

Chemical composition and larvicidal activity against Aedes mosquitoes of essential oils from Arisaema fargesii.

BACKGROUND: Dengue fever is caused by the spread of dengue virus by Aedes mosquito vectors. Currently, the most effective way to control dengue is by preventing mosquitoes from spreading the disease. Arisaema fargesii is a Chinese herbal medicine commonly used to repel mosquitoes. In our laboratory, anti-mosquito chemical components were extracted from A. fargesii, and the effects of these substances on mosquito larvae were examined. RESULTS: In total, 48 compounds corresponding to 98.79% of the total oil were identified and the major compounds identified were linalool (12.38%), carvacrol (8.27%), eugenol (5.21%), and ß-selinene (5.36%). Essential oil had larvicidal activity against Ae. aegypti and Ae. albopictus with LC50 values of 40.49 mg/L, 47.01 mg/L, respectively. The LC50 values of carvacrol, eugenol, linalool and ß-selinene were 32.78, 56.34, 70.56, 136.03 mg/L against Ae. aegypti larvae, and 39.08, 52.07, 82.34, 151.74 mg/L, respectively, against Ae. albopictus larvae. Biochemical assays of Aedes larvae showed that the activities of acetylcholinesterase (AChE), monooxygenases (MO), glutathione-S-transferase (GST), p-Nitrophenyl acetate (p-NPA) esterase, α-esterase and ß-esterase were significantly affected by carvacrol. Essential oil induced the detoxification mechanism for the action of GST and MO. CONCLUSION: The result indicates that essential oil of A. fargesii and its isolated constituent have good inhibitory effects on the defense enzymes of Aedes mosquito larvae. A. fargesii essential oil can be used to control Aedes mosquito larvae to prevent the spread of dengue fever. © 2019 Society of Chemical Industry.

Enhanced fluoride removal behaviour and mechanism by dicalcium phosphate from aqueous solution.

Dicalcium phosphate was prepared by ethylenediaminetetraacetic acid as a calcium chelating agent, and further explored to remove the fluoride ions from aqueous solution. The as-prepared samples main existed in the monetite phase from the result of XRD. The dried sample consisted of small nanoparticles and displayed irregular particles with a size of ca. 3 µm due to the agglomeration. The fluoride removal ability was evaluated by batch adsorption experiments. The as-prepared adsorbent exhibited the enhanced fluoride removal behaviour with the maximum adsorption capacity of 66.72 mg/g from the Langmuir isotherm model, which was higher than that of other previously reported calcium phosphate. The adsorbent could be utilized in the wide pH range of 3-10. The adsorption kinetics could be better described by the pseudo-second-order model than first-second-order model. The co-existing anions had a negligible influence on the fluoride adsorption. The investigation of adsorption mechanism suggested that the chemical reaction and/or dissolution - precipitation mechanism should be dominant in the fluoride adsorption process, accompanying with electronic interaction and ions exchange, which enhanced the fluoride removal performance.

Urine Metabonomics Reveals Early Biomarkers in Diabetic Cognitive Dysfunction.

Recently, increasing attention has been paid to diabetic encephalopathy, which is a frequent diabetic complication and affects nearly 30% of diabetics. Because cognitive dysfunction from diabetic encephalopathy might develop into irreversible dementia, early diagnosis and detection of this disease is of great significance for its prevention and treatment. This study is to investigate the early specific metabolites biomarkers in urine prior to the onset of diabetic cognitive dysfunction (DCD) by using metabolomics technology. An ultra-high performance liquid-chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-Q/TOF-MS) platform was used to analyze the urine samples from diabetic mice that were associated with mild cognitive impairment (MCI) and nonassociated with MCI in the stage of diabetes (prior to the onset of DCD). We then screened and validated the early biomarkers using OPLS-DA model and support vector machine (SVM) method. Following multivariate statistical and integration analysis, we found that seven metabolites could be accepted as early biomarkers of DCD, and the SVM results showed that the prediction accuracy is as high as 91.66%. The identities of four biomarkers were determined by mass spectrometry. The identified biomarkers were largely involved in nicotinate and nicotinamide metabolism, glutathione metabolism, tryptophan metabolism, and sphingolipid metabolism. The present study first revealed reliable biomarkers for early diagnosis of DCD. It provides new insight and strategy for the early diagnosis and treatment of DCD.