Value-Added Squalene in Single-Cell Oil Produced with Cutaneotrichosporon oleaginosus for Food Applications.

Single-cell oil (SCO) produced by oleaginous microorganisms is potentially a more land-efficient and sustainable alternative to vegetable oil. The cost of SCO production can be reduced by value-added co-products like squalene, a highly relevant compound for the food, cosmetic, and pharmaceutical industry. For the first time, squalene in the oleaginous yeast Cutaneotrichosporon oleaginosus was analyzed, reaching 172.95 ± 61.31 mg/100 g oil in a lab-scale bioreactor. Using the squalene monooxygenase inhibitor terbinafine, cellular squalene was significantly increased to 2169 ± 262 mg/100 g SCO, while the yeast remained highly oleaginous. Further, SCO from a 1000 L scale production was chemically refined. The squalene content in the deodorizer distillate (DD) was found to be higher than that in DD from typical vegetable oils. Overall, this study demonstrates squalene as a value-added compound in SCO from C. oleaginosus for application in food and cosmetics without the use of genetic modifications.

Novel Approaches for Elongation of Fish Oils into Very-Long-Chain Polyunsaturated Fatty Acids and Their Enzymatic Interesterification into Glycerolipids.

Elongation of the Very-Long-Chain Fatty Acids-4 (ELOVL4) enzyme that is expressed in neuronal tissues, sperm, and testes mediates biosynthesis of very-long-chain polyunsaturated fatty acids (VLC-PUFAs) from dietary long chain PUFAs (LC-PUFAs). The VLC-PUFAs are critical for neuronal and reproductive function. Therefore, mutations in ELOVL4 that affect VLC-PUFA biosynthesis contribute to retinal degenerative diseases including Autosomal Dominant Stargardt-like Macular Dystrophy (STGD3). Recent studies have also shown not only a depletion of retinal VLC-PUFAs with normal aging but also a more significant loss of VLC-PUFAs in donor eyes of patients with age-related macular degeneration (AMD). However, currently, there are no natural sources of VLC-PUFAs to be evaluated as dietary supplements for the attenuation of retinal degeneration in animal models of STGD3. Here, we report the development of a novel chemical approach for elongation of eicosapentaenoic (C20:5 n-3) and docosahexaenoic (C22:6 n-3) acids from fish oils by 6 carbon atoms to make a unique group of VLC-PUFAs, namely all-cis-hexacosa-11,14,17,20,23-pentaenoic acids (C26:5 n-3) and all-cis-octacosa-10,13,16,19,22,25-hexaenoic acids (C28:6 n-3). The three-step elongation approach that we report herein resulted in a good overall yield of up to 20.2%. This more sustainable approach also resulted in improved functional group compatibility and minimal impact on the geometrical integrity of the all-cis double bond system of the VLC-PUFAs. In addition, we also successfully used commercial deep-sea fish oil concentrate as an inexpensive material for the C6 elongation of fish oil LC-PUFAs into VLC-PUFAs, which resulted in the making of gram scales of VLC-PUFAs with an even higher isolation yield of 31.0%. The quality of fish oils and the content of oxidized lipids were key since both strongly affected the activity of the PEPPSI-IPr catalyst and ultimately the yield of coupling reactions. Downstream enzymatic interesterification was used for the first time to prepare structured glycerolipids enriched with VLC-PUFAs that could be evaluated in vivo to determine absorption and transport to target tissues relative to those of the free fatty acid forms. It turned out that in the synthesis of structured triacylglycerols and glycerophospholipids with VLC-PUFAs, the polarity of the immobilized lipase carrier and its humidity were essential.

Automatically designed machine vision system for the localization of CCA transverse section in ultrasound images.

The common carotid artery (CCA) is a source of important information that doctors can use to evaluate the patients' health. The most often measured parameters are arterial stiffness, lumen diameter, wall thickness, and other parameters where variation with time is usually measured. Unfortunately, the manual measurement of dynamic parameters of the CCA is time consuming, and therefore, for practical reasons, the only alternative is automatic approach. The initial localization of artery is important and must precede the main measurement. This article describes a novel method for the localization of CCA in the transverse section of a B-mode ultrasound image. The novel method was designed automatically by using the grammar-guided genetic programming (GGGP). The GGGP searches for the best possible combination of simple image processing tasks (independent building blocks). The best possible solution is represented with the highest detection precision. The method is tested on a validation database of CCA images that was specially created for this purpose and released for use by other scientists. The resulting success of the proposed solution was 82.7%, which exceeded the current state of the art by 4% while the computation time requirements were acceptable. The paper also describes an automatic method that was used in designing the proposed solution. This automatic method provides a universal approach to designing complex solutions with the support of evolutionary algorithms.

Novel method for localization of common carotid artery transverse section in ultrasound images using modified Viola-Jones detector.

This article describes a novel method for highly accurate and effective localization of the transverse section of the carotis comunis artery in ultrasound images. The method has a high success rate, approximately 97%. Unlike analytical methods based on geometric descriptions of the object sought, the method proposed here can cover a large area of shape variation of the artery under study, which normally occurs during examinations as a result of the pressure on the examined tissue, tilt of the probe, setup of the sonographic device, and other factors. This method shows great promise in automating the process of determining circulatory system parameters in the non-invasive clinical diagnostics of cardiovascular diseases. The method employs a Viola-Jones detector that has been specially adapted for efficient detection of transverse sections of the carotid artery. This algorithm is trained on a set of labeled images using the AdaBoost algorithm, Haar-like features and the Matthews coefficient. The training algorithm of the artery detector was modified using evolutionary algorithms. The method for training a cascade of classifiers achieves on a small number of positive and negative training data samples (about 500 images) a high success rate in a computational time that allows implementation of the detector in real time. Testing was performed on images of different patients for whom different ultrasonic instruments were used under different conditions (settings) so that the algorithm developed is applicable in general radiologic practice.