Preparation of medium- and long-chain triacylglycerols rich in n-3 polyunsaturated fatty acids by bio-imprinted lipase-catalyzed interesterification.

Medium and long-chain triacylglycerol (MLCT) rich in n-3 polyunsaturated fatty acids (PUFAs) were obtained in three-hour interesterification of fish oil with medium-chain triacylglycerol (MCTs), using lipase bio-imprinted with surfactant as a catalyst. Initially, for bio-imprinted lipase preparation, the interesterification reaction conditions were optimized, resulting in a lipase with 1.47 times higher catalytic activity compared to control (non-bio-imprinted). Afterwards, the reaction conditions for MLCT synthesis were optimized, using bio-imprinted lipase as a catalyst. The reaction reached equilibrium within first three hours at 70 °C temperature, 4 wt% lipase load, and molar ratio of substrate 1:1.5. Under these conditions, final product contained 18.52% MCT, 56.65% MLCT, and 24.83% long-chain triacylglycerol (LCT). To reduce the MCT content, a solvent extraction process was performed, yielding 2.42% MCT, 56.19% MLCT, and 41.39% LCT. The obtained structured lipids (SLs), enriched in n-3 PUFAs, offer significant health benefits, enhanced bioavailability, with potential applications in functional foods and nutraceuticals.

Omega-3 long-chain polyunsaturated fatty acids: Metabolism and health implications.

Recently, omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFAs) have gained substantial interest due to their specific structure and biological functions. Humans cannot naturally produce these fatty acids (FAs), making it crucial to obtain them from our diet. This comprehensive review details n-3 LC-PUFAs and their role in promoting and maintaining optimal health. The article thoroughly analyses several sources of n-3 LC-PUFAs and their respective bioavailability, covering marine, microbial and plant-based sources. Furthermore, we provide an in-depth analysis of the biological impacts of n-3 LC-PUFAs on health conditions, with particular emphasis on cardiovascular disease (CVD), gastrointestinal (GI) cancer, diabetes, depression, arthritis, and cognition. In addition, we highlight the significance of fortification and supplementation of n-3 LC-PUFAs in both functional foods and dietary supplements. Additionally, we conducted a detailed analysis of the several kinds of n-3 LC-PUFAs supplements currently available in the market, including an assessment of their recommended intake, safety, and effectiveness. The dietary guidelines associated with n-3 LC-PUFAs are also highlighted, focusing on the significance of maintaining a well-balanced intake of n-3 PUFAs to enhance health benefits. Lastly, we highlight future directions for further research in this area and their potential implications for public health.

Fast distributed large-pixel-count hologram computation using a GPU cluster.

Large-pixel-count holograms are one essential part for big size holographic three-dimensional (3D) display, but the generation of such holograms is computationally demanding. In order to address this issue, we have built a graphics processing unit (GPU) cluster with 32.5 Tflop/s computing power and implemented distributed hologram computation on it with speed improvement techniques, such as shared memory on GPU, GPU level adaptive load balancing, and node level load distribution. Using these speed improvement techniques on the GPU cluster, we have achieved 71.4 times computation speed increase for 186M-pixel holograms. Furthermore, we have used the approaches of diffraction limits and subdivision of holograms to overcome the GPU memory limit in computing large-pixel-count holograms. 745M-pixel and 1.80G-pixel holograms were computed in 343 and 3326 s, respectively, for more than 2 million object points with RGB colors. Color 3D objects with 1.02M points were successfully reconstructed from 186M-pixel hologram computed in 8.82 s with all the above three speed improvement techniques. It is shown that distributed hologram computation using a GPU cluster is a promising approach to increase the computation speed of large-pixel-count holograms for large size holographic display.

Regular effective hologram regions for computer generated holography.

An effective hologram region (EHR) based approach is presented to speed up the computation of computer generated holograms (CGHs). The object space is predivided into subspaces, and an EHR for each subspace is predefined according to the maximum spatial frequency of interference fringes, light diffraction efficiency, and CGH binarization effect. To compute the hologram of an object, the object points are first categorized according to which subspace they are located in, and then their holograms are calculated using the corresponding EHRs. As each EHR usually takes up only a portion of the hologram plate, the CGH computational load is thus reduced. This new approach is highly suitable for large hologram display systems. In addition, when compared to the reconstructed image using the conventional approach, our experimental results show that more noise can be blocked off and the reconstructed image appears sharper without noticeable brightness reduction.

Fast CGH computation using S-LUT on GPU.

In computation of full-parallax computer-generated hologram (CGH), balance between speed and memory usage is always the core of algorithm development. To solve the speed problem of coherent ray trace (CRT) algorithm and memory problem of look-up table (LUT) algorithm without sacrificing reconstructed object quality, we develop a novel algorithm with split look-up tables (S-LUT) and implement it on graphics processing unit (GPU). Our results show that S-LUT on GPU has the fastest speed among all the algorithms investigated in this paper, while it still maintaining low memory usage. We also demonstrate high quality objects reconstructed from CGHs computed with S-LUT on GPU. The GPU implementation of our new algorithm may enable real-time and interactive holographic 3D display in the future.