Comparison of the Protective Effects of Casein Hydrolysate Containing Tyr-Pro-Val-Glu-Pro-Phe and Casein on the Behaviors and Peripheral and Brain Functions in Mice with Chronic-Stress-Induced Anxiety and Insomnia.

Chronic stress is a major inducer of anxiety and insomnia. Milk casein has been studied for its stress-relieving effects. We previously prepared a casein hydrolysate (CP) rich in the sleep-enhancing peptide YPVEPF, and this study aims to systemically investigate the different protective effects of CP and casein on dysfunction and anxiety/insomnia behavior and its underlying mechanisms in chronically stressed mice. Behavioral results showed that CP ameliorated stress-induced insomnia and anxiety more effectively than milk casein, and this difference in amelioration was highly correlated with an increase in GABA, 5-HT, GABAA, 5-HT1A receptors, and BDNF and a decrease in IL-6 and NMDA receptors in stressed mice. Furthermore, CP restored these dysfunctions in the brain and colon by activating the HPA response, modulating the ERK/CREB-BDNF-TrκB signaling pathway, and alleviating inflammation. The abundant YPVEPF (1.20 ± 0.04%) and Tyr-based/Trp-containing peptides of CP may be the key reasons for its different effects compared to casein. Thus, this work revealed the main active structures of CP and provided a novel dietary intervention strategy for the prevention and treatment of chronic-stress-induced dysfunction and anxiety/insomnia behaviors.

Profiles and Developmental Transitions of Educational Future Orientation among Senior High School Students in China.

Adolescent future orientation is highly relevant to the sociocultural context in which they are situated. However, adolescents in non-Western cultures are underrepresented in literature. This study investigated the profiles and developmental transitions of adolescent educational future orientation, as well as the roles of adolescent academic achievement and perceived parental educational expectations within the context of Chinese culture. The sample was 605 (54.5% boys) urban and rural senior high school students followed for one and a half years. Three distinctive profiles were identified: the concentrated-committed profile characterized by the concentrated goals (i.e., hopes and fears for future education) and the highest level of planning and evaluation components, the low profile scoring the lowest on each component, and the tentative profile characterized by the highest level of hopes and fears density and mean levels of planning and evaluation components. Latent transition analysis revealed high stabilities for the concentrated-committed and the low profiles but very low stabilities for the tentative profile, and transitions were more common in ways from low or tentative profiles to the concentrated-committed profile rather than vice versa. Greater academic achievement predicted the concentrated-committed profile. Perceived parental educational expectations increased adolescent educational future orientation, particularly for urban adolescents or those in the tentative profile. Urban adolescents were more likely to be in or transition into the concentrated-committed profile, particularly for those with higher academic achievement or parental expectations. These findings demonstrate the heterogeneities of adolescent thinking about future education, reveal how the Chinese sociocultural factors contribute to shaping the development of adolescent future orientation, and provide implications for the promotion of adolescent future orientation in education.

Loop closure detection of visual SLAM based on variational autoencoder.

Loop closure detection is an important module for simultaneous localization and mapping (SLAM). Correct detection of loops can reduce the cumulative drift in positioning. Because traditional detection methods rely on handicraft features, false positive detections can occur when the environment changes, resulting in incorrect estimates and an inability to obtain accurate maps. In this research paper, a loop closure detection method based on a variational autoencoder (VAE) is proposed. It is intended to be used as a feature extractor to extract image features through neural networks to replace the handicraft features used in traditional methods. This method extracts a low-dimensional vector as the representation of the image. At the same time, the attention mechanism is added to the network and constraints are added to improve the loss function for better image representation. In the back-end feature matching process, geometric checking is used to filter out the wrong matching for the false positive problem. Finally, through numerical experiments, the proposed method is demonstrated to have a better precision-recall curve than the traditional method of the bag-of-words model and other deep learning methods and is highly robust to environmental changes. In addition, experiments on datasets from three different scenarios also demonstrate that the method can be applied in real-world scenarios and that it has a good performance.

A Simple High-Throughput Field Sample Preparation Method Based on Matrix-Induced Sugaring-Out for the Simultaneous Determination of 5-Hydroxymethylfurfural and Phenolic Compounds in Honey.

In the present work, a high-throughput field sample preparation method was reported for the simultaneous determination of 5-hydroxymethylfurfural and phenolic compounds in honey. Combining a simple and green homogenous liquid−liquid extraction, matrix-induced sugaring-out, with the use of a 96-deepwell plate and multichannel pipette, the proposed method showed its merits in instrument-free and high-throughput preparation. Due to the high-throughput property, the parameters of the method were rapidly and systematically studied using a constructed 4 × 2 × 4 × 3 array (sample amount × ratio of ACN:H2O × standing time × replicates) in a 96-deepwell plate. Analytical performance was fully validated, and the limits of detection and limits of quantification were in the range of 0.17−1.35 µg/g and 0.51−4.14 µg/g, respectively. Recoveries were between 83.98 and 117.11%, and all the precisions were <5%. Furthermore, the developed method was successfully applied in the outdoor preparation of commercial honey samples and the in-field preparation of raw honey samples in apiary. The current work presented a simple, rapid, and high-throughput method for the field sample preparation of honey and provides a valuable strategy for the design of field and on-site sample preparation.

Identification of a novel peptide that activates alcohol dehydrogenase from crucian carp swim bladder and how it protects against acute alcohol-induced liver injury in mice.

Alcoholism is a severe threat to public health, and there are no adequate treatments for alcoholic liver disease. The aim of this study was to identify bioactive peptides derived from natural proteins that prevent acute alcohol-induced liver injury. We identified a peptide with the sequence Gly-Leu-hydroxyproline-Gly-Glu-Arg (GLpGER) from the hydrolysate of crucian carp swim bladder using size-exclusion chromatography and reversed-phase chromatography. The in vitro EC50 value of GLpGER to activate alcohol dehydrogenase (ADH) was 137.9 ± 9 µM. Molecular docking experiments indicated that the mechanism by which GLpGER activates ADH may be related to the formation of stable complexes with ADH active pockets through hydrogen bonding, and electrostatic and hydrophobic interactions. Oral administration of GLpGER one hour before acute alcohol ingestion significantly increased alcohol metabolism, manifesting as reduced incidence of the loss of righting reflex, increased alcohol tolerance time, shortened sobering time, and decreased blood alcohol concentration level. GLpGER restored liver ADH activity, maintained the typical morphology of hepatocytes, and reduced serum levels of alanine aminotransferase and aspartate aminotransferase. These findings suggest that GLpGER might reduce acute alcohol-induced liver injury and may have the potential to be developed as an anti-inebriation ingredient.

High-throughput subzero-temperature assisted homogenous liquid-liquid extraction for the fast sample preparation of multiple phenolic compounds in propolis.

In the present study, a high-throughput homogenous liquid-liquid extraction method was developed for fast sample preparation of multiple phenolic compounds in propolis. This method was proposed based on cooling samples array in subzero temperature to induce phase separation of ACN-H2O extractant. Due to the high-throughput ability, optimization of extraction parameters was rapidly achieved by using a 5 × 4 × 3 samples array. In addition, multiple arrays were investigated for evaluating the analytical performance of the high-throughput method, which indicated that limits of detection and quantification were ranged from 0.04 to 0.35 µg/mL and 0.12 to 1.05 µg/mL, respectively. Recoveries and precisions in inter-day high-throughput studies were in the range of 90.55-105.50% and 2.58-4.30%, respectively. Comparing with the conventional liquid extraction method, this ecofriendly high-throughput method presented remarkable advantages in reducing sample and chemical consumption, as well as saving labor and time cost. The proposed method might provide a valuable strategy for the design of high-throughput extraction procedures.

Micro Salting-Out Assisted Matrix Solid-Phase Dispersion: A Simple and Fast Sample Preparation Method for the Analysis of Bisphenol Contaminants in Bee Pollen.

In the present work, a novel sample preparation method, micro salting-out assisted matrix solid-phase dispersion (µ-SOA-MSPD), was developed for the determination of bisphenol A (BPA) and bisphenol B (BPB) contaminants in bee pollen. The proposed method was designed to combine two classical sample preparation methodologies, matrix solid-phase dispersion (MSPD) and homogenous liquid-liquid extraction (HLLE), to simplify and speed-up the preparation process. Parameters of µ-SOA-MSPD were systematically investigated, and results indicated the significant effect of salt and ACN-H2O extractant on the signal response of analytes. In addition, excellent clean-up ability in removing matrix components was observed when primary secondary amine (PSA) sorbent was introduced into the blending operation. The developed method was fully validated, and the limits of detection for BPA and BPB were 20 µg/kg and 30 µg/kg, respectively. Average recoveries and precisions were ranged from 83.03% to 94.64% and 1.76% to 5.45%, respectively. This is the first report on the analysis of bisphenol contaminants in bee pollen sample, and also on the combination of MSPD and HLLE. The present method might provide a new strategy for simple and fast sample preparation of solid and semi-solid samples.

Matrix-Induced Sugaring-Out: A Simple and Rapid Sample Preparation Method for the Determination of Neonicotinoid Pesticides in Honey.

In the present work, we developed a simple and rapid sample preparation method for the determination of neonicotinoid pesticides in honey based on the matrix-induced sugaring-out. Since there is a high concentration of sugars in the honey matrix, the honey samples were mixed directly with acetonitrile (ACN)-water mixture to trigger the phase separation. Analytes were extracted into the upper ACN phase without additional phase separation agents and injected into the HPLC system for the analysis. Parameters of this matrix-induced sugaring-out method were systematically investigated. The optimal protocol involves 2 g honey mixed with 4 mL ACN-water mixture (v/v, 60:40). In addition, this simple sample preparation method was compared with two other ACN-water-based homogenous liquid-liquid extraction methods, including salting-out assisted liquid-liquid extraction and subzero-temperature assisted liquid-liquid extraction. The present method was fully validated, the obtained limits of detection (LODs) and limits of quantification (LOQs) were from 21 to 27 and 70 to 90 µg/kg, respectively. Average recoveries at three spiked levels were in the range of 91.49% to 97.73%. Precision expressed as relative standard deviations (RSDs) in the inter-day and intra-day analysis were all lower than 5%. Finally, the developed method was applied for the analysis of eight honey samples, results showed that none of the target neonicotinoid residues were detected.