Urinary excretion of polyols and sugars in children with chronic kidney disease

Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes

Background

Individuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

Methods

Using data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

Findings

The model predicts the progression to diabetic kidney disease with accuracy: 0.96 ± 0.25 and 0.96 ± 0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75 ± 0.14 and 0.79 ± 0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

Interpretation

With further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

Funding

This study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Optimisation of Epoxide Ring-Opening Reaction for the Synthesis of Bio-Polyol from Palm Oil Derivative Using Response Surface Methodology

The development of bio-polyol from vegetable oil and its derivatives is gaining much interest from polyurethane industries and academia. In view of this, the availability of methyl oleate derived from palm oil, which is aimed at biodiesel production, provides an excellent feedstock to produce bio-polyol for polyurethane applications. In this recent study, response surface methodology (RSM) with a combination of central composite rotatable design (CCRD) was used to optimise the reaction parameters in order to obtain a maximised hydroxyl value (OHV). Three reaction parameters were selected, namely the mole ratio of epoxidised methyl oleate (EMO) to glycerol (1:5-1:10), the amount of catalyst loading (0.15-0.55%) and reaction temperature (90-150 °C) on a response variable as the hydroxyl value (OHV). The analysis of variance (ANOVA) indicated that the quadratic model was significant at 98% confidence level with (p-value > 0.0001) with an insignificant lack of fit and the regression coefficient (R2) was 0.9897. The optimum reaction conditions established by the predicted model were: 1:10 mole ratio of EMO to glycerol, 0.18% of catalyst and 120 °C reaction temperature, giving a hydroxyl value (OHV) of 306.190 mg KOH/g for the experimental value and 301.248 mg KOH/g for the predicted value. This result proves that the RSM model is capable of forecasting the relevant response. FTIR analysis was employed to monitor the changes of functional group for each synthesis and the confirmation of this finding was analysed by NMR analysis. The viscosity and average molecular weight (MW) were 513.48 mPa and 491 Da, respectively.

Clinical, biochemical, and molecular overview of transaldolase deficiency and evaluation of the endocrine function: Update of 34 patients

BACKGROUND

Transaldolase deficiency (TALDO-D) is a rare autosomal recessive inborn error of the pentose phosphate pathway. Since its first description in 2001, several case reports have been published, but there has been no comprehensive overview of phenotype, genotype, and phenotype-genotype correlation.

METHODS

We performed a retrospective questionnaire and literature study of clinical, biochemical, and molecular data of 34 patients from 25 families with proven TALDO-D. In some patients, endocrine abnormalities have been found. To further evaluate these abnormalities, we performed biochemical investigations on blood of 14 patients.

RESULTS AND CONCLUSIONS

Most patients (n = 22) had an early-onset presentation (prenatally or before 1 month of age); 12 patients had a late-onset presentation (3 months to 9 years). Main presenting symptoms were intrauterine growth restriction, dysmorphic facial features, congenital heart disease, anemia, thrombocytopenia, and hepato(spleno)megaly. An older sib of two affected patients was asymptomatic until the age of 9 years, and only after molecular diagnosis was hepatomegaly noted. In some patients, there was gonadal dysfunction with low levels of testosterone and secondary luteinizing hormone (LH) and follicle-stimulating hormone (FSH) abnormalities later in life. This overview provides information that can be helpful for managing patients and counseling families regarding prognosis. Diagnostic guidelines, possible genotype-phenotype correlations, treatment options, and pathophysiological disease mechanisms are proposed.