Identification of estrogen-responsive vitelline envelope protein fragments from rainbow trout (Oncorhynchus mykiss) plasma using mass spectrometry.

Plasma peptides previously associated with exposure of juvenile male rainbow trout (Oncorhynchus mykiss) to the hormone 17ß-estradiol (E2) were identified using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS). Specifically, plasma peptides of interest were fractionated and subsequently identified via spectra obtained by MALDI QqTOF MS/MS and LC-MALDI TOFTOF MS/MS analysis, de novo sequencing and database matching. The two peptide masses were identified as significant matches for fragments of the C-terminal propeptides from rainbow trout vitelline envelope protein (VEP)α and VEPγ isoforms. Our findings document the presence of the C-terminal propeptides from rainbow trout VEPα and VEPγ proteins in the bloodstream of juvenile male rainbow trout exposed to E2 via MALDI-TOF-MS detection. We provide three possible explanations for the presence of C-terminal propeptides in the bloodstream, as well as compare previously obtained hepatic transcriptomic results with the plasma proteomic results obtained in the present study.

Weight gain in type 2 diabetes mellitus.

OBJECTIVE: To investigate the potential causes of weight gain using insulin and combination therapy in type 2 diabetes. DESIGN AND METHODS: This was an open-label prospective study of 6-month duration. Randomization was performed to insulin monotherapy, insulin and pioglitazone 30 mg daily, or insulin and metformin up to 2000 mg daily. Fifty-seven subjects with poorly controlled type 2 diabetes were enrolled. The goal was to achieve a normal haemoglobin A1c (HbA1c) (<5.6%). Weight, resting energy expenditure (REE), reported energy intake and total energy expenditure, HbA1c, glycosuria, plasma leptin, ghrelin and adiponectin levels, and body fat were measured. RESULTS: A total of 49 subjects completed the study. At baseline, weight was 89.4 +/- 22.9 kg and HbA1c was 11.1 +/- 1.5%. Weight increased by 7.46, 7.60 and 7.12 kg in the monotherapy, metformin and pioglitazone groups, respectively [p = 0.98 between and <0.0001 within the groups by repeated measures-analysis of variance (RM-anova)]. HbA1c dropped to 7.8 +/- 0.9% in the monotherapy arm, 7.6 +/- 1.0% in the metformin arm and 7.2 +/- 1.2% in the pioglitazone arm. Reported energy intake decreased. Glycosuria decreased but was not correlated with weight gain, while HbA1c changes were correlated with weight gain. REE per lean mass decreased (p = 0.04 by RM-anova). The subcutaneous fat areas in the insulin monotherapy and pioglitazone arms showed increases (p = 0.02 and 0.004 respectively). CONCLUSIONS: Weight gain was probably not due to an increase in food intake, while REE per lean body mass decreased, suggesting a role for increased efficiency in fuel usage due to improved glycaemic control. A drop in glycosuria probably also contributed to weight gain. In the monotherapy and pioglitazone arms, the subcutaneous fat areas increased.

Potential causes of weight gain in type 1 diabetes mellitus.

AIM: To investigate the potential causes of weight gain with insulin therapy and improved diabetic control in type 1 diabetes mellitus. METHODS: This was an open-label prospective study of insulin therapy of 6 months duration in an academic medical centre. Twenty-one subjects with type 1 diabetes were enrolled. The goal was to achieve an haemoglobin A1c (HbA1c) in the range of individuals without diabetes (<5.6%). At baseline, 3 and 6 months, weight, resting energy expenditure, appetite assessment, food intake, activity level, HbA1c and 24-h glycosuria and urea nitrogen were measured. Plasma leptin, ghrelin and adiponectin levels and body fat were measured at baseline and 6 months. RESULTS: At baseline, average weight was 73.7 +/- 17.4 kg and HbA1c was 10.0 +/- 2.2%. Weight increased by 2.15 kg (2.69% of baseline) by 6 months whereas the HbA1c dropped by 1.71% (16.3%) to 7.9%. Energy intake differences between 3 and 6 months had a negative correlation with weight gain, but the changes in glycosuria, appetite scores and the frequency of hypoglycaemia did not correlate with weight gain. Glycaemic control did not correlate with weight change but tended to correlate with fat mass increase (p = 0.064; r = -0.51). An increase in the activity levels between 3 and 6 months correlated with decreasing fat mass (p = 0.037; r = -0.74). The changes in the appetite scores had a negative correlation with fat mass gain (p = 0.035; r = -0.61). The changes in lean body mass correlated with protein and total energy intake (p = 0.007, r = 0.85 and p = 0.003, r = 0.73 respectively). The changes in leptin levels correlated with weight gain. CONCLUSIONS: The lipogenic effect of insulin with subsequent increase in fat mass may be the primary cause of this weight gain that can be attenuated by the increases in the activity levels. The negative correlation of energy intake and appetite scores with fat mass gain suggests that they do not play a significant role in fat mass gain whereas energy intake did correlate with lean body mass gain.