Fate of carotenoids in yeasts: synthesis and cleavage.

Carotenoids and their cleavage products (norisoprenoids) have excellent functional properties with diverse applications in foods, medicaments, cosmetics, etc. Carotenoids can be oxidatively cleaved through nonspecific reactions or by carotenoid cleavage oxygenases (CCOs), the product of which could further modify food flavor. This review provides comprehensive information on both carotenoid synthesis and cleavage processes with emphasis on enzyme characterization and biosynthetic pathway optimization. The use of interdisciplinary approaches of bioengineering and computer-aided experimental technology for key enzyme modification and systematic pathway design is beneficial to monitor metabolic pathways and assess pathway bottlenecks, which could efficiently lead to accumulation of carotenoids in microorganisms. The identification of CCOs spatial structures isolated from different species has made a significant contribution to the current state of knowledge. Current trends in carotenoid-related flavor modification are also discussed. In particular, we propose the carotenoid-synthesizing yeast Rhodotorula spp. for the production of food bioactive compounds. Understanding the behavior underlying the formation of norisoprenoids from carotenoids using interdisciplinary approaches may point toward other areas of investigation that could lead to better exploiting the potential use of autochthonous yeast in flavor enhancement.

[Association of different stages of histological chorioamnionitis with respiratory distress syndrome in preterm infants with a gestational age of < 32 weeks].

OBJECTIVE: To study the association of different stages of histological chorioamnionitis (HCA) with the incidence rate and severity of respiratory distress syndrome (RDS) in preterm infants. METHODS: Related data were collected from the infants and their mothers who were treated in the Neonatal Intensive Care Unit of Qingdao Women and Children's Hospital, Qingdao University, from January 2018 to June 2020. According to the presence or absence of HCA and its stage, the infants were divided into four groups: control (n=109), early-stage HCA (n=126), middle-stage HCA (n=105), and late-stage HCA (n=36). The four groups were compared in terms of gestational age, birth weight, sex, maternal age, placental abruption, prenatal use of antibiotics, and incidence rate of RDS. The correlation between HCA stage and RDS severity was analyzed. RESULTS: Compared with the control and late-stage HCA groups, the early-stage HCA group had a significantly lower incidence rate of placental abruption and a significantly higher rate of prenatal use of antibiotics (P < 0.05), and the early-stage HCA group had a significantly lower incidence rate of RDS than the control group (P < 0.05). The multivariate logistic regression analysis showed that early-, middle-, and late-stage HCA were protective factors against RDS (P < 0.05). The Spearman test showed that the severity of RDS in preterm infants was not correlated with the HCA stage (P > 0.05). CONCLUSIONS: Early-, middle-, and late-stage HCA can reduce the incidence rate of RDS in preterm infants. HCA stage may not be correlated with RDS severity in preterm infants, which needs to be verified by further research.

Preparation and Evaluation of Peptides with Potential Antioxidant Activity by Microwave Assisted Enzymatic Hydrolysis of Collagen from Sea Cucumber Acaudina Molpadioides Obtained from Zhejiang Province in China.

The present study was focused on the preparation and characterization of the antioxidant peptides by microwave-assisted enzymatic hydrolysis of collagen from sea cucumber Acaudina molpadioides (ASC-Am) obtained from Zhejiang Province in China. The results exhibited the effects of microwave irradiation on hydrolysis of ASC-Am with different protease. Neutrase was selected from the four common proteases (papain, pepsin, trypsin, and neutrase) based on the highest content and DPPH scavenging activity of hydrolysate Fa (Molecular weight < 1 kDa). The content and 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity of Fa obtained by hydrolysis of neutrase increased by 100% and 109% respectively at a microwave power of 300 W compared with no microwave irradiation. Five subfractions were obtained after performing the gel filtration chromatography, and the Fa.2 exhibited the highest DPPH scavenging activity. The amino acid analysis showed that the contents of Glutamic acid, Alanine, Tyrosine, and Phenylalanine in fraction Fa.2 increased significantly, but an obvious decrease in the content of Glycine was observed compared to Fa. Four peptides (Fa.2-A, Fa.2-B, Fa.2-C, and Fa.2-D) were purified from Fa.2 by high performance liquid chromatography, and Fa.2-C showed the highest DPPH scavenging activity. The sequence of Fa.2-C was identified as Phenylalanine-Leucine- Alanine-Proline with a half elimination ratio (EC50) of 0.385 mg/mL. The antioxidant activity of Fa.2-C was probably attributed to the small molecular sizes and the presence of hydrophobic amino acid residues in its sequence. This report provided a promising method for the preparation of antioxidant peptides from collagen for food and medicinal purposes.

Nonlinear model-based method for clustering periodically expressed genes.

Clustering periodically expressed genes from their time-course expression data could help understand the molecular mechanism of those biological processes. In this paper, we propose a nonlinear model-based clustering method for periodically expressed gene profiles. As periodically expressed genes are associated with periodic biological processes, the proposed method naturally assumes that a periodically expressed gene dataset is generated by a number of periodical processes. Each periodical process is modelled by a linear combination of trigonometric sine and cosine functions in time plus a Gaussian noise term. A two stage method is proposed to estimate the model parameter, and a relocation-iteration algorithm is employed to assign each gene to an appropriate cluster. A bootstrapping method and an average adjusted Rand index (AARI) are employed to measure the quality of clustering. One synthetic dataset and two biological datasets were employed to evaluate the performance of the proposed method. The results show that our method allows the better quality clustering than other clustering methods (e.g., k-means) for periodically expressed gene data, and thus it is an effective cluster analysis method for periodically expressed gene data.