The Impact of Spironolactone Co-administration on Cyclosporin Initial Dosage Optimization for Pediatric Refractory Nephrotic Syndrome.

OBJECTIVES: Cyclosporin has been used for the treatment of pediatric refractory nephrotic syndrome (PRNS). However, the narrow therapeutic window and large pharmacokinetic variability make it difficult to individualize cyclosporin administration. Meanwhile, spironolactone has been reported to affect cyclosporin metabolism in PRNS patients. This study aims to explore the initial dosage optimization of cyclosporin in PRNS based on the impact of spironolactone co-administration. METHODS: Monte Carlo simulation based on a previously established cyclosporin population pharmacokinetic model for PRNS was used to design cyclosporin dosing regimen. RESULTS: In this study, the probability of drug concentration reaching the target and the convenience of times of administration were considered comprehensively. The optimal administration regimen in PRNS without spironolactone was 6, 5, 4 and 3 mg/kg cyclosporin split into two doses for the body weight of 5-8, 8-18, 18-46 and 46-70 kg, respectively. The optimal administration regimen in PRNS with spironolactone was 4, 3, 2 mg/kg cyclosporin split into two doses for body weight of 5-14, 14-65, and 65-70 kg, respectively. CONCLUSION: The cyclosporin dosing regimen for PRNS based on Monte Carlo simulation was systematically developed and the initial dosage optimization of cyclosporin in PRNS was recommended for the first time.

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with idiopathic membranous nephropathy (IMN) and recommend an appropriate dosage schedule via machine learning method. METHODS: The Emax model was constructed to analyze the effects of tacrolimus on proteinuria in patients with IMN. Data were mined from published literature and machine learning was built up with Emax model, among which the efficacy indicator was proteinuria change rates from baseline. 463 IMN patients were included for modeling, and tacrolimus therapeutic window concentrations were 4-10 ng/ml. RESULTS: In machine learning model, the Emax from tacrolimus effecting proteinuria in IMN patients was -72.7%, the ET50 was 0.43 months, and the time to achieving 25% Emax, 50% Emax, 75% Emax, and 80% (plateau) Emax of tacrolimus on proteinuria in patients with IMN were 0.15, 0.43, 1.29, and 1.72 months, respectively. CONCLUSION: For achieving better therapeutic effects from tacrolimus on proteinuria in patients with IMN, tacrolimus concentration range need to be maintained at 4-10 ng/ml for at least 1.72 months.

[Preliminary analysis of bitter substances in spica of Prunella vulgaris].

Volatile oil components and the contents and types of amino acid in spica of Prunella vulgaris were analysed by GC-MS and amino acid analyzer. Esters, fatty acids, aromatic hydrocarbon, ketone and several alcohol compounds were identified by mass spectrum comparison. In these ingredients, beta-ionone smelled aroma of cedar, raspberry, nerolidol showed weak sweet soft orange blossom flavor, neroli tasted sweet and fresh, nerolidol tasted sweet with light aroma of wood, hexadecanal showed a weak aroma of flowers and wax, alpha-sinensal had rich and fresh sweet orange flavor. To some extent, these types of aromatic substances can affect the taste of herbal tea or decoction made of Spica Prunellae. Among amino acids detected, natural amino acids accounted for a larger proportion, and those natural amino acids showed bitterness, slight bitterness, sourness (freshness), sweetness, slight sweetness, sourness (slight freshness). The results indicated that bitter and slightly bitter amino acids have the greatest impacts on the sense of Spica Prunellae.

A strategy for precise and large scale identification of core fucosylated glycoproteins.

Core fucosylation (CF) patterns of some glycoproteins are more sensitive and specific than evaluation of their total respective protein levels for diagnosis of many diseases, such as cancers. Global profiling and quantitative characterization of CF glycoproteins may reveal potent biomarkers for clinical applications. However, current techniques are unable to reveal CF glycoproteins precisely on a large scale. Here we developed a robust strategy that integrates molecular weight cutoff, neutral loss-dependent MS(3), database-independent candidate spectrum filtering, and optimization to effectively identify CF glycoproteins. The rationale for spectrum treatment was innovatively based on computation of the mass distribution in spectra of CF glycopeptides. The efficacy of this strategy was demonstrated by implementation for plasma from healthy subjects and subjects with hepatocellular carcinoma. Over 100 CF glycoproteins and CF sites were identified, and over 10,000 mass spectra of CF glycopeptide were found. The scale of identification results indicates great progress for finding biomarkers with a particular and attractive prospect, and the candidate spectra will be a useful resource for the improvement of database searching methods for glycopeptides.