Production optimization and characterization of immunomodulatory peptides obtained from fermented goat placenta

The goat placental immunomodulatory peptides were produced by fermentation with Aspergillus Niger. The objective of the present study was to investigate the effects of fermentation parameters (carbon source content, pH, and time) on spleen lymphocyte proliferation for the highest immune activity of the fermentation broth using response surface methodology (RSM). According to the data analysis by the Design-Expert® software, the stimulation index value (23.51&#37;), which is the maximum immune activity, was obtained under the following conditions: content of carbon source 1.97 g·L-1, initial pH 5.0, and 74.43 h of fermentation time. Under the optimized fermentation conditions, at a certain concentration range, the fermentation broth produced a significant effect on the proliferation of mouse spleen lymphocytes. Ultrafiltration technique was performed to separate the fermentation broth with different MW (molecular weight). It was found that peptides in the range of <10 KDa were the main bioactivity fractions for the immunomodulatory and antioxidant activities

A feature selection framework for video semantic recognition via integrated cross-media analysis and embedded learning

Abstract Video data are usually represented by high dimensional features. The performance of video semantic recognition, however, may be deteriorated due to the irrelevant and redundant components included into the high dimensional representations. To improve the performance of video semantic recognition, we propose a new feature selection framework in this paper and validate it through applications of video semantic recognition. Two issues are considered in our framework. First, while those labeled videos are precious, their relevant labeled images are abundant and available in the WEB. Therefore, a supervised transfer learning is proposed to achieve the cross-media analysis, in which the discriminative features are selected by evaluating feature’s correlation with the classes of videos and relevant images. Second, the labeled videos are normally rare in real-world applications. In our framework, therefore, an unsupervised subspace learning is added to retain the most valuable information and eliminate the feature redundancies by leveraging both labeled and unlabeled videos. The cross-media analysis and embedded learning are simultaneously learned in a joint framework, which enables our algorithm to utilize the common knowledge of cross-media analysis and embedded learning as supplementary information to facilitate decision making. An efficient iterative algorithm is proposed to optimize the proposed learning-based feature selection, in which convergence is guaranteed. Experiments on different databases have demonstrated the effectiveness of the proposed algorithm

Unveiling Pre-Transmetalation Intermediates in Base-Free Suzuki–Miyaura Cross-Couplings: A Computational Study

The pre-transmetalation intermediates are critically important in Suzuki–Miyaura cross-coupling (SMC) reactions and have become a hot spot of the current research. However, the pre-transmetalation intermediates under base-free conditions have not been clear. Herein, a comprehensive theoretical study is performed on the base-free Pd-catalyzed desulfonative SMC reaction. The fragile coordination feature and the acceleration role of the RuPhos chelate ligand are revealed. The hydrogen-bond complex between the Pd–F complex and aryl boronic acid is identified as an important pre-transmetalation intermediate, which increases the energy span to 32.5 kcal/mol. The controlling factor for the formation of the hydrogen-bond complexes is attributed to the electronegativities of halogen atoms in the metal halide complexes. What is more, other reported SMC reaction systems involving metal halide complexes and aryl boronic acids are reconsidered and suggest that the hydrogen-bond complexes widely exist as stable pre-transmetalation intermediates with influencing the catalytic activities. The earth-abundant Ni-catalyzed desulfonative SMC reaction is further designed and predicted to have a higher activity than the original Pd-catalyzed SMC reaction

Ketamine Modulates Zic5 Expression via the Notch Signaling Pathway in Neural Crest Induction

Ketamine is a potent dissociative anesthetic and the most commonly used illicit drug. Many addicts are women at childbearing age. Although ketamine has been extensively studied as a clinical anesthetic, its effects on embryonic development are poorly understood. Here, we applied the Xenopus model to study the effects of ketamine on development. We found that exposure to ketamine from pre-gastrulation (stage 7) to early neural plate (stage 13.5) resulted in disruption of neural crest (NC) derivatives. Ketamine exposure did not affect mesoderm development as indicated by the normal expression of Chordin, Xbra, Wnt8, and Fgf8. However, ketamine treatment significantly inhibited Zic5 and Slug expression at early neural plate stage. Overexpression of Zic5 rescued ketamine-induced Slug inhibition, suggesting the blockage of NC induction was mediated by Zic5. Furthermore, we found Notch signaling was altered by ketamine. Ketamine inhibited the expression of Notch targeted genes including Hes5.2a, Hes5.2b, and ESR1 and ketamine-treated embryos exhibited Notch-deficient somite phenotypes. A 15 bp core binding element upstream of Zic5 was induced by Notch signaling and caused transcriptional activation. These results demonstrated that Zic5 works as a downstream target gene of Notch signaling in Xenopus NC induction. Our study provides a novel teratogenic mechanism whereby ketamine disrupts NC induction via targeting a Notch-Zic5 signaling pathway