Identification of free fatty acids profiling of type 2 diabetes mellitus and exploring possible biomarkers by GC–MS coupled with chemometrics

This paper reviews the factors affecting the fatty acid composition of adipose tissue and muscle in pigs, sheep and cattle and shows that a major factor is the total amount of fat. The effects of fatty acid composition on meat quality are also reviewed. Pigs have high levels of polyunsaturated fatty acids (PUFA), including the long chain (C20-22) PUFA in adipose tissue and muscle. The full range of PUFA are also found in sheep adipose tissue and muscle whereas cattle 'conserve' long chain PUFA in muscle phospholipid. Linoleic acid (18:2n-6) is a major ingredient of feeds for all species. Its incorporation into adipose tissue and muscle in relation to the amount in the diet is greater than for other fatty acids. It is deposited in muscle phospholipid at a high level where it and its long chain products eg aracidonic acid (20:4n-6) compete well for insertion into phospholipid molecules. Its proportion in pig adipose tissue declines as fat deposition proceeds and is an index of fatness. The same inverse relationships are not seen in ruminant adipose tissue but in all species the proportion of 18:2n-6 declines in muscle as fat deposition increases. The main reason is that phospholipid, where 18:2n-6 is located, declines as a proportion of muscle lipid and the proportion of neutral lipid, with its higher content of saturated and monounsaturated fatty acids, increases. Oleic acid (18:1cis-9), formed from stearic acid (18:0) by the enzyme stearoyl Co-A desaturase, is a major component of neutral lipid and in ruminants the same enzyme forms conjugated linoleic acid (CLA), an important nutrient in human nutrition. Like 18:2n-6, α-linolenic acid (18:3n-3) is an essential fatty acid and is important to ruminants since it is the major fatty acid in grass. However it does not compete well for insertion into phospholipid compared with 18:2n-6 and its incorporation into adipose tissue and muscle is less efficient. Greater biohydrogenation of 18:3n-3 and a long rumen transit time for forage diets also limits the amount available for tissue uptake compared with 18:2n-6 from concentrate diets. A positive feature of grass feeding is that levels of the nutritionally important long chain n-3 PUFA are increased ie EPA (20:5n-3) and DHA (22:6n-3). Future research should focus on increasing n-3 PUFA proportions in lean carcasses and the use of biodiverse pastures and conservation processes which retain the benefits of fresh leafy grass offer opportunities to achieve this. The varying fatty acid compositions of adipose tissue and muscle have profound effects on meat quality. Fatty acid composition determines the firmness/oiliness of adipose tissue and the oxidative stability of muscle, which in turn affects flavour and muscle colour. Vitamin E is an essential nutrient, which stabilises PUFA and has a central role in meat quality, particularly in ruminants.

Type 2 diabetes mellitus has become an epidemic, and virtually no physician is without patients who have the disease. Whereas insulin insensitivity is an early phenomenon partly related to obesity, pancreas beta-cell function declines gradually over time already before the onset of clinical hyperglycaemia. Several mechanisms have been proposed, including increased non-esterified fatty acids, inflammatory cytokines, adipokines, and mitochondrial dysfunction for insulin resistance, and glucotoxicity, lipotoxicity, and amyloid formation for beta-cell dysfunction. Moreover, the disease has a strong genetic component, but only a handful of genes have been identified so far: genes for calpain 10, potassium inward-rectifier 6.2, peroxisome proliferator-activated receptor gamma, insulin receptor substrate-1, and others. Management includes not only diet and exercise, but also combinations of anti-hyperglycaemic drug treatment with lipid-lowering, antihypertensive, and anti platelet therapy.

By employing the simple but effective principle 'survival of the fittest' on which Darwin's Evolution Theory is based, a novel strategy for selecting an optimal combination of key wavelengths of multi-component spectral data, named competitive adaptive reweighted sampling (CARS), is developed. Key wavelengths are defined as the wavelengths with large absolute coefficients in a multivariate linear regression model, such as partial least squares (PLS). In the present work, the absolute values of regression coefficients of PLS model are used as an index for evaluating the importance of each wavelength. Then, based on the importance level of each wavelength, CARS sequentially selects N subsets of wavelengths from N Monte Carlo (MC) sampling runs in an iterative and competitive manner. In each sampling run, a fixed ratio (e.g. 80%) of samples is first randomly selected to establish a calibration model. Next, based on the regression coefficients, a two-step procedure including exponentially decreasing function (EDF) based enforced wavelength selection and adaptive reweighted sampling (ARS) based competitive wavelength selection is adopted to select the key wavelengths. Finally, cross validation (CV) is applied to choose the subset with the lowest root mean square error of CV (RMSECV). The performance of the proposed procedure is evaluated using one simulated dataset together with one near infrared dataset of two properties. The results reveal an outstanding characteristic of CARS that it can usually locate an optimal combination of some key wavelengths which are interpretable to the chemical property of interest. Additionally, our study shows that better prediction is obtained by CARS when compared to full spectrum PLS modeling, Monte Carlo uninformative variable elimination (MC-UVE) and moving window partial least squares regression (MWPLSR).