Engineering of redox partners and cofactor NADPH supply of CYP68JX for efficient steroid two-step ordered selective hydroxylation activity.

CYP68JX, a P450 hydroxylase, derived from Colletotrichum lini ST-1 is capable of biotransforming dehydroepiandrosterone (DHEA) to 3ß,7α,15α-trihydroxy-5-androstene-17-one (7α,15α-diOH-DHEA). Redox partners and cofactor supply are important factors affecting the catalytic activity of CYP68JX. In this study, the heterologous expression of CYP68JX in Saccharomyces cerevisiae BY4741 was realized resulting in a 17.1% target product yield. In order to increase the catalytic efficiency of CYP68JX in S. cerevisiae BY4741, a complete cytochrome P450 redox system was constructed. Through the combination of CYP68JX and heterologous CPRs, the yield of the target product 7α,15α-diOH-DHEA in CYP68JX recombinant system was increased to 37.8%. Furthermore, by adding NADPH coenzyme precursor tryptophan of 40 mmol/L and co-substrate fructose of 20 g/L during the conversion process, the catalytic efficiency of CYP68JX was further improved, the target product yield reached 57.9% which was 3.39-fold higher than initial yield. Overall, this study provides a reference for improving the catalytic activity of P450s.

UFO-Net: A Linear Attention-Based Network for Point Cloud Classification.

Three-dimensional point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we designed an augmented sampling and grouping module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to extract point cloud's local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first tried to use a linearly normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module was adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that this method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which is 0.5% higher than PCT. Our network also achieved 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

Enhancing the Output Performance of a Triboelectric Nanogenerator Based on Modified Polyimide and Sandwich-Structured Nanocomposite Film.

Recently, scientists have been facing major obstacles in terms of improving the performances of dielectric materials for triboelectric nanogenerators. The triboelectric nanogenerator (TENG) is one of the first green energy technologies that can convert random mechanical kinetic energy into electricity. The surface charge density of TENGs is a critical factor speeding up their commercialization, so it is important to explore unique methods to increase the surface charge density. The key to obtaining a high-performance TENG is the preparation of dielectric materials with good mechanical properties, thermal stability and output performance. To solve the problem of the low output performance of PI-based triboelectric nanogenerators, we modified PI films by introducing nanomaterials and designed a new type of sandwich-shaped nanocomposite film. Herein, we used polyimide (PI) with ideal mechanical properties, excellent heat resistance and flexibility as the dielectric material, prepared an A-B-A sandwich structure with PI in the outer layer and modified a copper calcium titanate/polyimide (CCTO/PI) storage layer in the middle to improve the output of a TENG electrode. The doping amount of the CCTO was tailored. The results showed that at 8 wt% CCTO content, the electrical output performance was the highest, and the open-circuit voltage of CCTO/PI was 42 V. In the TENG, the open-circuit voltage, short-circuit current and transfer charge of the prepared sandwich-structured film were increased by 607%, 629% and 672% compared to the TENG with the PI thin film, respectively. This study presents a novel strategy of optimizing dielectric materials for triboelectric nano-generators and has great potential for the future development of high output-performance TENGs.

Effects of dietary starch sources on pellet-processing characteristics, growth performance and caecal microflora of meat rabbits.

This study evaluated the effects of starch sources on pellet-processing characteristics as well as the growth performance and caecal microflora of rabbits. Ninety-six 35-day-old rabbits were randomly allocated to four groups with 24 rabbits per group and were fed diets with different starch sources (corn, wheat, potato or pea starch). The trial lasted for 40 days. The greatest hardness and lowest powder ratio of feed pellets was associated with the use of potato starch (p > 0.05). Pellet bulk density was the highest with corn starch, and the density was greater than that of pea starch by 5.91% (p < 0.05). The pulverisation ratio of corn starch pellets was the lowest, 43.67% lower than that of the pea starch pellets (p < 0.05). The average daily gain of rabbits in the corn starch group was higher than in the potato and pea starch groups, by 7.89% and 10.81%, respectively (p < 0.05). Rabbits in the corn starch group had the best feed conversion ratio (p > 0.05). The feed intake of rabbits in the potato starch group was higher than in the wheat and pea starch groups, by 4.30% and 5.16% respectively (p < 0.05). The dominant caecal bacteria phyla were Firmicutes, Bacteroidetes, Verrucomicrobia and Proteobacteria. There were 12 bacterial genera with proportions greater than 0.1%. The caecal proportion of Clostridium in the pea starch group was 1.8%, which was higher than those of the other groups (p = 0.057). There was no significant difference in caecal microbial diversity among groups (p > 0.05). The highest microbial clustering effect was found in the corn starch treatment. In conclusion, the best pellet quality was found using potato starch; for rabbit growth, the optimal source was corn starch.

Effects of the dietary digestible fiber-to-starch ratio on pellet quality, growth and cecal microbiota of Angora rabbits.

OBJECTIVE: Substituting starch with digestible fiber (dF) can improve digestive health of rabbits and reduce costs. Therefore, it is necessary to develop a criterion for dF and starch supply. Effects of the dietary dF-to-starch ratio on pellet quality, growth and cecal microbiota of Angora rabbits were evaluated. METHODS: Five isoenergetic and isoproteic diets with increasing dF/starch ratios (0.59, 0.66, 0.71, 1.05, and 1.44) were formulated. A total of 120 Angora rabbits with an average live weight of 2.19 kg were randomly divided into five groups with four replicates. At the end of 40 day feeding trial, cecal digesta were collected to analyse microbiota. RESULTS: The results showed that the dF/starch ratio had linear effects on pellet variables (p<0.01). When the dF/starch ratio was 1.44, the pellets had the lowest powder and highest durability. The dF/starch ratio had unfavorable linear effects on growth variables (p<0.001). When analyzed by quadratic regression, the optimal dF/starch ratios for average weight gain and feed/gain were 0.59 and 0.74, respectively. There were differences in wool yield, fiber length and fiber diameter caused by the dF/starch ratio (p<0.05), and the dF/starch ratios that ranged from 0.66 to 1.06 were appropriate for good results. The cecal microbiota operational taxonomic unit (OTU) number index in the 1.05 dF/starch treatment was higher than that in the 0.66 and 0.71 dF/starch treatments. The higher dF/starch ratio resulted in a higher cecal microbiota OTU number index (p<0.05). The proportion of Ruminococcus in the 0.71 dF/starch treatment was higher than that in the 0.59 dF/starch treatment (p<0.05). CONCLUSION: The most suitable dF/starch ratio for feed pellet quality is 1.44, and for rabbit growth the optimal range of ratios is from 0.59 to 0.74. With combination of the wool growth, output cost, and cecal microbiota, we suggest that a dietary dF/starch ratio ranging from 0.74 to 1.06 is optimal.