Identification of pyruvic and maleic acid as potential markers for disease activity and prognosis in chronic urticaria.

BACKGROUND: Population-based studies have highlighted the link between chronic urticaria (CU) and metabolic syndrome, and metabolic alterations have been revealed in CU. However, to our knowledge, a comprehensive metabolomics study on a large cohort of patients with CU has not been reported. OBJECTIVE: We sought to explore the underlying metabolic subtypes and novel metabolite biomarkers for CU diagnosis and therapy. METHODS: Plasma samples from 80 patients with CU and 82 healthy controls were collected for metabolomics quantification and bioinformatics analysis. Another independent cohort consisting of 144 patients with CU was studied to validate the findings. Bone marrow-derived mast cells and mice with IgE-induced passive cutaneous anaphylaxis were used for in vitro and in vivo experiments, respectively. RESULTS: We observed clear metabolome differences between CU patients and healthy controls. Meanwhile, differential metabolites N6-acetyl-l-lysine, l-aspartate, maleic acid, and pyruvic acid were used to construct random forest classifiers and achieved area under receiver operating characteristic curve values greater than 0.85, suggesting their potential as diagnostic biomarkers of CU. More importantly, by exploring the underlying metabolic subtypes of CU, we found that the low abundance of pyruvic acid and maleic acid was significantly related to the activity of CU, poor efficacy of second-generation H1 antihistamines, and short relapse-free time. The results were validated in the independent cohort. Moreover, supplementation with pyruvate or maleate could significantly attenuate IgE-mediated mast cell activation in vitro and in vivo. CONCLUSIONS: Plasma pyruvic acid and maleic acid may be effective biomarkers for predicting disease activity, therapeutic efficacy, and prognosis for patients with CU.

Therapeutic potential of TNFα inhibitors in chronic inflammatory disorders: Past and future.

In the past 20 years, patients with rheumatoid arthritis (RA), Crohn's disease (CD), and other immune diseases have witnessed the impact of a great treatment advance with the availability of biological TNFα inhibitors. With 5 approved anti-TNFα biologics on the market and soon available biosimilars, patients have more treatment options and have benefited from understanding the biology of TNFα. Nevertheless, many unmet needs remain for people living with TNFα-related diseases, namely some side effects and tolerance of current anti-TNFα biologics and resistance to therapies. Furthermore, common diseases such as osteoarthritis and back/neck pain may respond to anti-TNFα therapies at early onset of symptoms. Development of new TNFα inhibitors focusing on TNFR1 specific inhibitors, preferably small molecules that can be delivered orally, is much needed.

Microbial transformation of hederagenin by Cunninghamella echinulate, Mucor subtilissimus, and Pseudomonas oleovorans.

The pentacyclic triterpenoid hederagenin (1) was subjected to biotransformation by Cunninghamella echinulate CGMCC 3.2000, Mucor subtilissimus CGMCC 3.2454 and Pseudomonas oleovorans CGMCC 1.1641. Three metabolites were obtained. On the basis of nuclear magnetic resonance and high-resolution mass spectral analyses, their structures were characterized as 3ß, 23-dihydroxyolean-12-en-28-oic acid 28-O-ß-D-glucopyranosyl ester (2), 3ß, 15α, 23-trihydroxyolean-12-en-28-oic acid (3), 1ß, 3ß, 23-trihydroxyolean-12-en-28-oic acid (4), and metabolite (3) was a new compound. This was the first report on the biotransformation of hederagenin.

Biosorption of Pb(2+) by Saccharomyces cerevisiae in static and dynamic adsorption tests.

This paper demonstrates the Pb(2+) adsorption capacity and adsorption rate of Saccharomyces cerevisiae by both static and dynamic testing to verify its feasibility as a heavy metal bio-absorbent in wastewater treatment. The static testing was divided into two parts. First, we tested S. cerevisiae by itself, and then we tested immobilized S. cerevisiae. In static testing of the non-immobilized S. cerevisiae, the Pb(2+) adsorption capacity and adsorption rate increased up to 6.52 mg/g and 52.94%, respectively, with time. After immobilization, the Pb(2+) adsorption capacity and adsorption rate reached 10 mg/g and 80%, respectively. In dynamic testing, the optimal saturated adsorption capacity of immobilized S. cerevisiae for Pb(2+) was 6.64 mg/g. In addition to the static and dynamic testing of adsorption capacity and rate, we used SEM imaging to analyze the mechanics of adsorption, and the images showed that the cell wall played the major roll in Pb(2+) adsorption.

Evaluation of water quality in Er-longshan reservoir by fuzzy model.

The Er-longshan reservoir, located in Harbin city, Heilongjiang province, plays a significant role in development of economy and society. It's one of the most important fresh water sources for drinking as well as the safeguard of flood and soil erosion. Thus, as the monitored place in this study, its water quality was measured and predicted through a fuzzy model. The objective of this paper is to illustrate how to set up an appropriate subjection function model to solve the fuzzy problem. Most environmental monitoring data that can not be compared may be mapped into subjection degrees, and analyzed for their weight coefficients, yielding the best situation in multi-objective comprehensive exponential decision-making matrix.An appropriate subjection function model was set up to solve the fuzzy problem. Five kinds of pollution sources were investigated: the point source, the plane source, the entering river (Feiketu river), precipitation and falling dust and touring pollution around the reservoir area respectively. The distribution of floating algae in Er-longshan reservoir was also examined. Farmland plane source pollution was found to be the major controllable pollution source by monitoring TN and TP pollution loads, which occupy 84.8% and 84.0% of the controllable pollution source respectively. When we evaluate data of water quality, the concentration of part pollutant factors increases while others may decreases, then whether the whole water quality is to increase or decrease, from the monitor data is not easy to judge. In this study we used the fuzzy theory to analyze the trends of water quality fluctuations in the Er-longshan reservoir. COD(Mn), BOD, TN and TP were selected as main contamination factors. The results showed that the primary pollutants were nitrogen and phosphorus by calculating the weight coefficient e(i) of contamination factors from 1996 to 2005. According to fuzzy comprehensive exponent z(j) evaluating water quality of reservoir from 1996 to 2005, the ten-year water quality dynamic trend was studied.