Enzymatic Preparation, In-Depth Molecular Analysis, and In Vitro Digestion Simulation of Palmitoleic Acid (ω-7)-Enriched Fish Oil Triacylglycerols.

In this study, an enzymatic reaction was developed for synthesizing pure triacylglycerols (TAG) with a high content of palmitoleic acid (POA) using fish byproduct oil. The characteristics of synthesized structural TAGs rich in POA (POA-TAG) were analyzed in detail through ultrahigh-performance liquid chromatography Q Exactive orbitrap mass spectrometry. Optimal conditions were thoroughly investigated and determined for reaction systems, including the use of Lipozyme TL IM and Novozym 435, 15 wt % lipase loading, substrate mass ratio of 1:3, and water content of 2.5 and 0.5 wt %, respectively, resulting in yields of 67.50 and 67.45% for POA-TAG, respectively. Multivariate statistical analysis revealed that TAG 16:1/16:1/20:4, TAG 16:1/16:1/16:1, TAG 16:1/16:1/18:1, and TAG 16:0/16:1/18:1 were the main variables in Lipozyme TL IM and Novozym 435 enzyme-catalyzed products under different water content conditions. Finally, the fate of POA-TAG across the gastrointestinal tract was simulated using an in vitro digestion model. The results showed that the maximum release of free fatty acids and apparent rate constants were 71.44% and 0.0347 s-1, respectively, for POA-TAG lipids, and the physical and structural characteristics during digestion depended on their microenvironments. These findings provide a theoretical basis for studying the rational design of POA-structural lipids and exploring the nutritional and functional benefits of POA products.

DeepS: Accelerating 3D Mass Spectrometry Imaging via a Deep Neural Network.

Mass spectrometry imaging (MSI) is a powerful methodology that enables the visualization of the spatial distribution of biomolecules, including lipids, peptides, and proteins, from biological tissue sections. While two-dimensional (2D) MSI has been widely reported in various applications, three-dimensional (3D) MSI can enable the mapping of biomolecule distribution in complex biological structures (e.g., organs) with an added dimension. However, traditional 3D MSI techniques are time-consuming since 3D MS images are constructed from 2D MSI analyses of a series of tissue sections. In this study, we propose a 3D MSI workflow, termed DeepS, which uses a 3D sparse sampling network (3D-SSNet) and a sparse sampling strategy to significantly accelerate 3D MSI analyses. Sparsely sampled tissue sections are reconstructed using 3D-SSNet, yielding results comparable to those using full sampling MSI, even at a sampling ratio of 20-30%. The workflow performed well when applied to 3D imaging of a mouse brain with Alzheimer's disease, and combined with transfer learning, it is successfully used for the 3D MSI analyses of more heterogeneous samples, e.g., a mouse brain with glioblastoma and a mouse kidney.

Clinical significance of the serum miR-455-5p expression in patients with neonatal sepsis.

Sepsis is a systemic inflammatory response caused by infection and is a major cause of neonatal death. This study explored the miR-455-5p in neonatal sepsis, and further investigated the diagnostic and prognostic value of miR-455-5p in neonatal sepsis (NS). The levels of serum miR-455-5p in 88 healthy controls and 90 NS patients were examined by quantitative real-time polymerase chain reaction (qRT-PCR). Pearson correlation coefficient was used to evaluate the correlation between miR-455-5p and clinical features. Receiver operating characteristic (ROC) curve analysis was performed for the diagnostic evaluation on miR-455-5p. The prognostic value of miR-455-5p in NS was analyzed by Kaplan-Meier survival curve and multivariate Cox regression. The expression of serum miR-455-5p in NS patients was highly expressed in comparison to healthy controls (P < 0.001), and the level of miR-455-5p was positively correlated with white blood cell count (WBC) and other clinical characteristics (P < 0.01). The AUC value of ROC curve was 0.895, suggesting that miR-455-5p had diagnostic value for NS. Survival analysis illustrated that patient with high miR-455-5p expression had poor prognosis (log rank P = 0.015), and miR-455-5p may be a potential prognostic marker for NS (HR = 3.454, 95% CI = 1.165-10.234, P = 0.025). The expression of miR-455-5p had the ability to distinguish NS from healthy people, and highly expressed miR-455-5p was associated with poor prognosis in NS patients.

GLAGC: Adaptive Dual-Gamma Function for Image Illumination Perception and Correction in the Wavelet Domain.

Low-contrast or uneven illumination in real-world images will cause a loss of details and increase the difficulty of pattern recognition. An automatic image illumination perception and adaptive correction algorithm, termed as GLAGC, is proposed in this paper. Based on Retinex theory, the illumination of an image is extracted through the discrete wavelet transform. Two features that characterize the image illuminance are creatively designed. The first feature is the spatial luminance distribution feature, which is applied to the adaptive gamma correction of local uneven lighting. The other feature is the global statistical luminance feature. Through a training set containing images with various illuminance conditions, the relationship between the image exposure level and the feature is estimated under the maximum entropy criterion. It is used to perform adaptive gamma correction on global low illumination. Moreover, smoothness preservation is performed in the high-frequency subband to preserve edge smoothness. To eliminate low-illumination noise after wavelet reconstruction, the adaptive stabilization factor is derived. Experimental results demonstrate the effectiveness of the proposed algorithm. By comparison, the proposed method yields comparable or better results than the state-of-art methods in terms of efficiency and quality.