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To compare the impact of nanoselenium and sodium selenite on the performance, blood indices, and milk metabolites of dairy cows during the peak lactation period, two groups of dairy cows under the same conditions were selected as the control group (CON group) and treatment group (NSe group) for a 38-day (10 days for adaptation and 28 days for sampling) experiment. The control group (CON) was provided a basal diet +3.3 g/d of sodium selenite (purity1%), whereas the nanoselenium group (NSe) was offered the same diet +10 mL/d of nanoselenium (selenium concentration 1,500 mg/L). The results showed that NSe significantly increased the milk yield, milk selenium content, and feed efficiency (p 0.05). NSe significantly increased blood urea nitrogen (BUN) and alkaline phosphatase (ALP) (p 0.05). In addition, the nontargeted metabolomics of the milk was determined by LC–MS technology, and the differentially abundant metabolites and their enrichment pathways were screened. According to these findings, NSe considerably increased the contents of cetylmannoside, undecylenoic acid, 3-hydroxypentadecanoic acid, 16-hydroxypentadecanoic acid, threonic acid, etc., but decreased the contents of galactaric acid, mesaconic acid, CDP-glucose etc. Furthermore, the enriched metabolic pathways that were screened with an impact value greater than 0.1 included metabolism of niacin and niacinamide, pyruvate, citrate cycle, riboflavin, glycerophospholipid, butanoate and tyrosine. Pearson correlation analysis also revealed a relationship between different milk metabolites and blood selenium, as well as between milk selenium and blood biochemical indices. In conclusion, compared with sodium selenite, nanoselenium improves the milk yield, feed efficiency, and milk selenium content of dairy cows and regulates milk metabolites and related metabolic pathways in Holstein dairy cows during the peak lactation period, which has certain application prospects in dairy production.

Multitemporal change detection (CD) plays a crucial role in the remote sensing application field. In recent years, supervised deep learning methods have shown excellent performance in detecting changes in very-high-resolution (VHR) images. However, these methods require a large number of labeled samples for training, making the process time-consuming and labor-intensive. Unsupervised approaches are more attractive in practical applications since they can produce a CD map without relying on any ground reference or prior knowledge. In this article, we propose a novel unsupervised CD approach, named transformer-based multivariate alteration detection (trans-MAD). It utilizes a pre-detection strategy that combines the compressed change vector analysis and the iteratively reweighted multivariate alteration detection (IR-MAD) to generate reliable pseudotraining samples. More accurate and robust CD results can be achieved by leveraging the IR-MAD to detect insignificant changes and by incorporating the transformer-based attention mechanism to model the difference or similarity between two distant pixels in an image. The proposed trans-MAD approach was validated on two VHR bitemporal satellite remote sensing datasets, and the obtained experimental results demonstrated its superiority comparing with the state-of-the-art unsupervised CD methods.

The aim of this study was to investigate the effects of Lentilactobacillus plantarum (LP), cellulase (CE), and xylanase (XE) supplementation on the fermentation quality, chemical composition, and bacterial community of Caragana korshinskii Kom. silage. Four groups were designed for the study. No additives were used in the control group (CK), and LP (1 × 106 cfu/g), CE (1 × 104 IU/g) and XE (2 × 105 IU/g) were added to the experimental groups on a fresh matter basis, with three replicates per group. To promote fermentation, 5% molasses was added to all of the groups. On days 15 and 60, fermentation quality, chemical composition and the bacterial community were analysed. The pH of groups CE and XE was lower than that of the CK group at 60 days. During ensiling, the lactic acid (LA) content in the experimental groups and the acetic acid (AA) content in the CK and LP groups increased. At 60 days, the dominant genera in the CK and LP groups was Weissella and the dominant genera in the CE and XE groups was Lentilactobacillus. At different times during silage, nucleotide metabolism was enhanced, whereas the metabolism of carbohydrate, amino acids, energy, cofactors and vitamins was inhibited in the LP group. However, the metabolism of amino acids, energy, cofactors and vitamins in the CE and XE groups was increased, whereas the metabolism of nucleotides was inhibited. In conclusion, LP, CE and XE could exert a positive effect on the fermentation quality of C. korshinskii Kom. silage by shifting the bacterial community composition.

The objective of this experiment was to investigate the effects of Lactobacillus plantarum and molasses on the nutrient composition, fermentation quality, bacterial count, aerobic stability, and microflora of alfalfa silage in sandy grasslands. The experimental treatments included control (CK), 106 CFU/g Lactobacillus plantarum (L), 5% molasses (M), and 106 CFU/g Lactobacillus plantarum + 5% molasses (LM). The nutrient composition, fermentation quality, bacterial count, aerobic stability, and microflora were determined after 14 days and 56 days of ensiling, respectively. The results showed that the addition of L, M, and LM reduced dry matter loss (DM), neutral detergent fiber (NDF), and acid detergent fiber (ADF) content, and increased water-soluble carbohydrates (WSC) and ether extract (EE) content, compared to the CK group. Meanwhile, more lactic acid (LA) and accelerated fermentation were observed, causing the pH value to drop below 4.5 in the L, M, and LM groups after 56 days of ensiling. The addition of L, M, and LM promoted lactic acid bacteria (LAB), and inhibited yeast. The addition of L significantly increased the content of acetic acid (AA). In terms of microflora, the addition of L, M, and LM made Firmicutes become the dominant bacterial phylum earlier, while Lactobacillus, Weissella, and Pediococcus had a higher abundance. According to the result of Pearson's correlation, there is a very significant negative correlation between pH value and Lactobacillus (P < 0.01) and a very significant positive correlation between pH value and Lactococcus, Enterobacter, Enterococcus, and Leuconostoc (P < 0.01), which may be inhibited by Lactobacillus under the decreased pH value. The results of the prediction of microbial genes indicated that the addition of M could enhance the carbohydrate metabolism and membrane transport metabolism, which may contribute to LA production by LAB metabolism. In general, L, M and LM all improved the fermentation quality and reduced the loss of nutrients to varying degrees, but considering the fermentation quality, the overall effects of M and LM were better than L. M and LM are recommended to be used as silage additives in the process of alfalfa silage in sandy grasslands to improve the quality.

The present study assessed the effects of oligosaccharide-chelated organic trace minerals (OTM) on the growth performance, digestive enzyme activity, blood parameters, slaughter performance, and meat quality indexes of mutton sheep. A total of 60 East Ujumuqin × small-tailed Han crossbred mutton sheep were assigned to two groups (10 duplicates per group) by body weight (26.12 ± 3.22 kg) according to a completely randomized design. Compared to the CON group, the results of the OTM group showed: (1) no significant changes in the initial body weight, final body weight, dry matter intake, average daily gain, and feed conversion ratio (p > 0.05); (2) the activities of trypsin, lipase, and amylase in the jejunum were significantly increased (p 0.05); (5) shear force of mutton was significantly lower (p 0.05). The content of crude protein was significantly higher (p 0.05). Among these, the essential amino acids, threonine, valine, leucine, lysine in essential amino acids and arginine were significantly increased (p

China’s rapid urbanization drive, marked by extensive urban renewal projects, necessitates a meticulous examination of their transformational impact on the human settlement environment (HSE) across urban landscapes. This study investigates the impact of China’s urban renewal progress on the spatial–temporal changes in the HSE from 2009 to 2019, using data from 40 prefecture-level cities in the Yangtze River Delta. Our findings reveal an overall positive relationship between the spatio–temporal evolution of urban renewal and the HSE, suggesting that urban renewal projects have had a beneficial impact, particularly following the announcement of China’s New Urbanization policy in 2014. However, the extent of this positive impact varied among different areas, with more significant improvements observed in core cities and economically developed areas. Additionally, our study uncovered significant variations in how urban renewal influenced the HSE over time. We found that the primary influencing factor shifted from material renewal to industrial renewal. These findings offer valuable insights for improving the HSE during urban renewal processes, both in China and other regions undergoing rapid urbanization.

The fermentation substrate was supplemented with 0% guanidinoacetic acid (GAA) (control group, CON), 0.2% GAA (GAA02), 0.4% GAA (GAA04), 0.6% GAA (GAA06) and 0.8% GAA (GAA08) for 48 h of in vitro fermentation. Gas production was recorded at 2, 4, 6, 8, 12, 24, 36, and 48 h of fermentation. The gas was collected, and the proportions (%, v/v) of H2, CH4 and CO2 were determined. The rumen fermentation parameters, including pH, ammonia nitrogen (NH3-N), microbial protein (MCP) and volatile fatty acids (VFAs), were also determined. Furthermore, the bacterial community structure was analyzed through 16S rRNA high-throughput sequencing. The gene functions were predicted using PICRUSt1 according to the Kyoto Encyclopedia of Genes and Genomes (KEGG). The results showed that with the increase in GAA supplementation levels, the MCP and the concentration of rumen propionate were significantly increased, while the concentration of isovalerate was significantly decreased (p

Aiming at the machining of complex curved surface parts with parallel machine tools， a novel partially decoupled parallel manipulator （PM） is proposed. The degree of freedom and the decoupling performance of the mechanism are analyzed. The formula for the kinematic relationship between the driving branches and the moving platform is deduced by the vector method. The motion of each component in the parallel manipulator is analyzed. Considering the gravity， inertia force and moment of inertia of the components in the mechanism， a dynamic model of the parallel manipulator is established. The kinematic and dynamic equation of the PM is verified based on advanced CAD software. The singularity of the PM is analyzed， which provides theoretical and technical foundations for its application.

Hemp is an environmentally friendly porous fiber, and has good sound absorption properties, which can be used to reduce noise. In recent years, hemp-based composites have been widely studied, but most of them study the preparation methods of materials, Therefore, this paper studies the topic. Firstly, the material and specimens with different thickness and diameter were prepared, then, the standing wave tube method experiment was carried out, and the values of sound absorption coefficient of the specimens were measured and analyzed, while a novel model using genetic algorithm and artificial neural network is proposed. Secondly, the artificial neural network structure was designed, and the training data, verification data, test data are divided and the data is preprocessed. Thirdly, improved genetic algorithm is proposed to design to determine an optimal solution. Fourthly, the optimal solution was as the initial weight and threshold, and were input into the artificial neural network together with training data and verification data. Levenberg Marquardt algorithm were used to train the network. Finally, input the test data into the trained network to test the model. The results showed that there is only a minor deviation between the model output values and the measured values, the values of sound absorption coefficient of specimens with 10 mm thickness are between 0.9 and 1. It was also found that compared with artificial neural network model without genetic algorithm, the proposed model has the lower root mean squared error (RMSE) value, the larger coefficient of determination (R2) value.

Drought stress (DS) is a potential abiotic stress that is substantially reducing crop productivity across the globe. Likewise, salinity stress (SS) is another serious abiotic stress that is also a major threat to global crop productivity. The rapid climate change increased the intensity of both stresses which pose a serious threat to global food security; therefore, it is urgently needed to tackle both stresses to ensure better crop production. Globally, different measures are being used to improve crop productivity under stress conditions. Among these measures, biochar (BC) has been widely used to improve soil health and promote crop yield under stress conditions. The application of BC improves soil organic matter, soil structure, soil aggregate stability, water and nutrient holding capacity, and the activity of both beneficial microbes and fungi, which leads to an appreciable increase in tolerance to both damaging and abiotic stresses. BC biochar protects membrane stability, improves water uptake, maintains nutrient homeostasis, and reduces reactive oxygen species production (ROS) through enhanced antioxidant activities, thereby substantially improving tolerance to both stresses. Moreover, BC-mediated improvements in soil properties also substantially improve photosynthetic activity, chlorophyll synthesis, gene expression, the activity of stress-responsive proteins, and maintain the osmolytes and hormonal balance, which in turn improve tolerance against osmotic and ionic stresses. In conclusion, BC could be a promising amendment to bring tolerance against both drought and salinity stresses. Therefore, in the present review, we have discussed various mechanisms through which BC improves drought and salt tolerance. This review will help readers to learn more about the role of biochar in causing drought and salinity stress in plants, and it will also provide new suggestions on how this current knowledge about biochar can be used to develop drought and salinity tolerance.

In the present study, we investigated the effects of cellulase and Lactiplantibacillus plantarum (L. plantarum) on the fermentation quality, microbial diversity, gene function prediction, and in vitro rumen fermentation parameters of the Caragana korshinskii (C. korshinskii) silage. The experimental treatment groups included control (CK), cellulase (C), L. plantarum (L), and cellulase + L. plantarum (CL). Triplicate silos were sampled after 14 and 56 days of ensiling. The microbial diversity of C. korshinskii silage at 56 days was analyzed using Illumina MiSeq sequencing technology, and the effects of C. korshinskii silage on rumen fermentation were evaluated by the in vitro artificial rumen gas production method. The results showed that the addition of cellulose and L. plantarum treatments reduced ammonia-nitrogen (NH3-N), dry matter (DM), neutral detergent fiber (NDF), and acid detergent fiber content during ensiling. Compared with the CK group, higher lactic acid content was observed in the silage of the C and L groups, but the CL group had a higher acetic acid (AA) content. Compared with the CK group, the relative abundance of Lactiplantibacillus significantly increased, but that of Enterococcus, Weissella, Enterobacter, and Pediococcus significantly decreased in all other groups except the C group (p < 0.05). The results of gene function prediction were as follows: pyruvate kinase, 1-phosphofructokinase, and fructokinase were lactate production enzymes, which suggested the association of the high AA content in the CL group to the high abundance of 6-phosphate glucose dehydrogenase. The abundance of H + -transporting ATPase and ATP-binding cassette (ABC) transporters in the L and CL groups was higher than that in the CK groups. Metabolism of terpenoids and polyketides, mismatch repair, DNA replication, nucleotide excision repair, and homologous recombination increased in the CL group compared with those in the CK group. Compared with the CK group, NH3-N and microbial protein content and the degradation rates of DM and NDF increased in the L and CL groups. To conclude, the L and CL groups had increased Lactiplantibacillus abundance, improved fermentation quality, and high DM degradation rates compared with the CK group.

This article develops a robust feature fusion approach to enhance the classification performance of very high resolution (VHR) remote sensing images. Specifically, a novel two-stage multiple feature fusion (TsF) approach is proposed, which includes an intragroup and an intergroup feature fusion stages. In the first fusion stage, multiple features are grouped by clustering, where redundant information between different types of features is eliminated within each group. Then, features are pairwisely fused in an intergroup fusion model based on the guided filtering method. Finally, the fused feature set is imported into a classifier to generate the classification map. In this work, the original VHR spectral bands and their attribute profiles are taken as examples as input spectral and spatial features, respectively, in order to test the performance of the proposed TsF approach. Experimental results obtained on two QuickBird datasets covering complex urban scenarios demonstrate the effectiveness of the proposed approach in terms of generation of more discriminative fusion features and enhancing classification performance. More importantly, the fused feature dimensionality is limited at a certain level; thus, the computational cost will not be significantly increased even if multiple features are considered.

High-resolution (HR) satellite images, due to the technical constraints on spectral and spatial resolutions, usually contain only several broad spectral bands but with a very high spatial resolution. This provides rich spatial details of the objects on the Earth surface, while their spectral discrimination is relatively low. Recently, the increase of the satellite revisit times made it possible to acquire more frequent data coverage for finer classification. In this article, we proposed a novel multitemporal deep fusion network (MDFN) for short-term multitemporal HR images classification. Specifically, a two-branch structure of MDFN is designed, which includes a long short-term memory (LSTM) and a convolutional neural network (CNN). The LSTM branch is mainly used to learn the joint expression of different temporal-spectral features. For the CNN branch, the three-dimensional (3-D) convolution is firstly applied along the temporal and spectral dimensions to jointly learn the temporal-spatial and spectral-spatial information, respectively, and then the 2-D convolution is performed along the spatial dimension to further extract the spatial context information. Finally, features generated from the two different branches are fused to obtain the discriminative high-level semantic information for classification. Experimental results carried on two real multitemporal HR remote sensing datasets demonstrate that the proposed MDFN provides better classification performance over the state-of-the-art methods, and it also shows the potentiality to use short-term multitemporal HR images for more accurate land use/land cover mapping.

Machilus robusta W. W. Smith is an evergreen plant distributed in the Yangtze River Basin and the south regions of China. Here we analyzed the complete chloroplast (cp) genome sequence of M. robusta to determine its structure and evolutionary relationship to other Lauraceae. The cp genome is 152,737 bp in length and has an overall GC content of 39.2% The genome includes a large single-copy (LSC) region of 93,706 bp and a small single-copy (SSC) region of 18,885 bp, and these are separated by a pair of inverted repeats (IRs) of 20,073 bp. The cp genome contains 128 genes, including 83 protein-coding, 37 tRNAs, and 8 rRNAs. Phylogenetic analysis based on complete cp genome sequences fully resolved M. robusta in a clade with M. balansae. This work provides new molecular data for evolutionary studies of the Lauraceae.

Change detection from multi-temporal remote sensing images is an effective way to identify the burned areas after forest fires. However, the complex image scenario and the similar spectral signatures in multispectral bands may lead to many false positive errors, which make it difficult to exact the burned areas accurately. In this paper, a novel-burned area change detection approach is proposed. It is designed based on a new Normalized Burn Ratio-SWIR (NBRSWIR) index and an automatic thresholding algorithm. The effectiveness of the proposed approach is validated on three Landsat-8 data sets presenting various fire disaster events worldwide. Compared to eight index-based detection methods that developed in the literature, the proposed approach has the best performance in terms of class separability (2.49, 1.74 and 2.06) and accuracy (98.93%, 98.57% and 99.51%) in detecting the burned areas. Simultaneously, it can also better suppress the complex irrelevant changes in the background.

Cinnamomum camphora is a traditional aromatic plant used to produce linalool and borneol flavors in southern China; however, its leaves also contain many other unutilized essential oils. Herein, we report geographic relationships for the yield and compositional diversity of C. camphora essential oils. The essential oils of 974 individual trees from 35 populations in 13 provinces were extracted by hydrodistillation and analyzed qualitatively and quantitatively by gas chromatography-mass spectrometry and gas chromatography-flame ionization detection, respectively. Oil yields ranged from 0.01% to 3.46%, with a significantly positive correlation with latitude and a significantly negative correlation with longitude. In total, 41 compounds were identified, including 15 monoterpenoids, 24 sesquiterpenoids, and two phenylpropanoids. Essential oil compositions varied significantly among individuals and could be categorized into various chemotypes. The six main chemotypes were eucalyptol, nerolidol, camphor, linalool, selina, and mixed types. The other 17 individual plants were chemotypically rare and exhibited high levels of methyl isoeugenol, methyl eugenol, δ-selinene, or borneol. Eucalyptol-type plants had the highest average oil yield of 1.64%, followed in decreasing order by linalool-, camphor-, mixed-, selina-, and nerolidol-type plants. In addition, the five main compounds exhibited a clear geographic gradient. Eucalyptol and linalool showed a significantly positive correlation with latitude, while selina-6-en-4-ol was significantly and negatively correlated with latitude. trans-Nerolidol and selina-6-en-4-ol showed significantly positive correlations with longitude, whereas camphor was significantly and negatively correlated with longitude. Canonical correspondence analysis indicated that environmental factors could strong effect the oil yield and essential oil profile of C. camphora.

Acute skin damage caused by burns or cuts occurs frequently in people’s daily lives. Such wounds are difficult to heal normally and have persistent inflammation. Wound dressings not only improve the speed of wound healing, but also protect and cover the wound well. Hydrogels have the characteristics of good flexibility, high water content, and good biocompatibility, and are widely used in biomedicine and other fields. Common hydrogels are mainly natural hydrogels and synthetic hydrogels. Hydrogels cross-linked using different raw materials and different methods have different performance characteristics. Natural hydrogels prepared using polysaccharides are simple to obtain and have good biocompatibility, but are inferior to synthetic hydrogels in terms of mechanical properties and stability, and a single polysaccharide hydrogel cannot meet the component requirements for wound healing. Therefore, functional composite hydrogels with high mechanical properties, high biocompatibility, and high antibacterial properties are the current research hotspots. In this review, several common polysaccharides for hydrogel synthesis and the synthesis methods of polysaccharide hydrogels are introduced, and functional composite hydrogel dressings from recent years are classified. It is hoped that this can provide useful references for relevant research in this field.

Cinnamomum pauciflorum is a valuable aromatic tree of the genus Cinnamomum Trew in the family Lauraceae. To better determine its phylogenetic location with other Cinnamomum species, the complete chloroplast (cp) genome of C. pauciflorum was sequenced. The total cp genome size is 152,766 bp, consisting of a pair of inverted repeats (IRa/b) with a length of 20,074 bp separated by a large single-copy region (LSC) and a small single-copy region (SSC) which are 93,693 and 18,925 bp, respectively. The overall GC content of the cp genome is 39.14%. Maximum-likelihood analysis showed that C. pauciflorum has phylogenetic affinities with Cinnamomum osmophloeum, Cinnamomum aromaticum, Cinnamomum mollifolium, and Cinnamomum tenuipile, providing new insight into the evolution of Lauraceae.

Cinnamomum tenuipile Kosterm is a precious aromatic tree in Lauraceae. To better determine its phylogenetic location with other Cinnamomum species, the chloroplast genome of C. tenuipile was sequenced. The complete chloroplast genome size is 152,761 bp, consisting of a pair of inverted repeats (IRa/b) with a length of 20,074 bp separated by a large single-copy region (LSC) and a small single-copy region (SSC) which are 93,685 and 18,928 bp, respectively. The overall GC content of the cp genome is 39.16%. The maximum-likelihood phylogenetic tree showed that C. tenuipile is more closely related to C. aromaticum, providing new insight into the evolution of Lauraceae.

Antibacterial hydrogel has excellent antibacterial property and good biocompatibility, water absorption and water retention, swelling, high oxygen permeability, etc.; therefore, it widely applied in biomedicine, intelligent textiles, cosmetics, and other fields, especially for medical dressing. As a wound dressing, the antibacterial hydrogel has the characteristics of absorbing wound liquid, controlling drug release, being non-toxic, being without side effects, and not causing secondary injury to the wound. Its preparation method is simple, and can crosslink via covalent or non-covalent bond, such as γ-radiation croFsslinking, free radical polymerization, graft copolymerization, etc. The raw materials are easy to obtain; usually these include chondroitin sulfate, sodium alginate, polyvinyl alcohol, etc., with different raw materials being used for different antibacterial modes. According to the hydrogel matrix and antibacterial mode, the preparation method, performance, antibacterial mechanism, and classification of antibacterial hydrogels are summarized in this paper, and the future development direction of the antibacterial hydrogel as wound dressing is proposed.

Current acoustic modeling methods face problems such as complex processes or inaccurate sound absorption coefficients, etc. Therefore, this paper studies the topic. Firstly, the material samples were prepared, and standing wave tube method experiments were conducted. Material acoustic data were obtained, while a model using improved genetic algorithm and neural network was subsequently proposed. Secondly, the acoustic data obtained from the experiment were analyzed; a neural network structure was designed; and the training, verification, and test data were all divided. In order to facilitate data processing, a symmetrical method was used to inversely normalize all the data. Thirdly, by the design of real coding scheme, fitness function, crossover, and mutation operators, an improved genetic algorithm was proposed to obtain the optimal solution, as the initial weight and threshold, which were then input into the neural network along with the training and verification data. Finally, the test data were input into the trained neural network in order to test the model. The test results and statistical analysis showed that compared with other algorithms, the proposed model has the lower root mean squared error (RMSE) value, the maximum coefficient of determination (R2) value, and shorter convergence time.

Abstract Background Cinnamomum camphora has been cultivated as an economically important tree for its medicinal and aromatic properties. Selective breeding has produced Cinnamomum plants for special uses, including spice strains with characteristic flavors and aromas and high-potency medicinal cultivars. The molecular biology underlying terpenoid biosynthesis is still unexplored. Results Gas chromatography-mass spectrometry was used to analyze the differences in contents and compositions of essential oil terpenoids in linalool- and borneol-type chemotypes of C. camphora. The data revealed that the essential oils consist primarily of monoterpenes with only very minor quantities of sesquiterpenes and diterpenes and that the essential oil differs in different chemotypes of C. camphora, with higher yields of (−)-borneol from the borneol-type than from the linalool-type. To study the terpenoid biosynthesis of signature compounds of the major monoterpenes, we performed RNA sequencing to profile the leaf transcriptomes of the two chemotypes of C. camphora. A total of 23.76 Gb clean data was generated from two chemotypes and assembled into 156,184 unigenes. The total length, average length, N50 and GC content of unigenes were 155,645,929 bp, 997 bp, 1430 bp, and 46.5%, respectively. Among them, 76,421 unigenes were annotated by publicly available databases, of which 67 candidate unigenes were identified to be involved in terpenoid biosynthesis in C. camphora. A total of 2863 unigenes were identified to be differentially expression between borneol-type and linalool-type, including 1714 up-regulated and 1149 down-regulated unigenes. Most genes encoding proteins involved in terpenoid precursor MVA and MEP pathways were expressed in similar levels in both chemotypes of C. camphora. In addition, 10 and 17 DEGs were significantly enriched in the terpene synthase activity and oxidoreductase activity terms of their directed acyclic graphs (DAG), respectively. Three monoterpene synthase genes, TPS14-like1, TPS14-like2 and TPS14-like3 were up-regulated in the borneol-type compared to the linalool-type, and their expression levels were further verified using quantitative real-time PCR. Conclusions This study provides a global overview of gene expression patterns related to terpenoid biosynthesis in C. camphora, and could contribute to a better understanding of the differential accumulation of terpenoids in different C. camphora chemotypes.

A micro-channel distillation device was used for the process intensification method to separate boron isotopes, 10B and 11B. Three-dimensional (3D) printing technology was introduced to manufacture the micro-channel device, which used the chemical exchange method with anisole as the donor to separate the boron isotopes. This device was tested in total reflux mode, and the height of an equivalent theoretical plate of the micro-channel distillation equipment was reduced to 1.56 cm. The accurate control of pressure and temperature, as well as the flow rate of the complex, were factors that affected separation ability. Thus, for process intensification, this micro-channel distillation device can be operated horizontally and connected in series into similar modules to effectively improve separation efficiency and reduce the size of the equipment.

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Corn gluten meal (CGM) is a major by-product of corn wet milling. Pretreatments of CGM by Na2CO3, starch removal, and cooking reduced the total starch and fat by 93% and 78%, respectively. Higher antioxidant hydrolysate was prepared by using Alcalase, Protamex and Flavourzyme at a substrate concentration of 13.5% (w/w). The degree of hydrolysis reached 29.49% and 27.11%. The peptides in hydrolysate were in the range of 1200–250 Da. It increased the activities of superoxide dismutase, glutathione peroxidase, and reduced MDA equivalents of mice at a dose of 300 mg/kg. Therefore, corn gluten can be developed into an antioxidant supplement.

Cinnamomum camphora, a member of the Lauraceae family, is a valuable aromatic and timber tree that is indigenous to the south of China and Japan. All parts of Cinnamomum camphora have secretory cells containing different volatile chemical compounds that are utilized as herbal medicines and essential oils. Here, we reported the complete sequencing of the chloroplast genome of Cinnamomum camphora using illumina technology. The chloroplast genome of Cinnamomum camphora is 152,570 bp in length and characterized by a relatively conserved quadripartite structure containing a large single copy region of 93,705 bp, a small single copy region of 19,093 bp and two inverted repeat (IR) regions of 19,886 bp. Overall, the genome contained 123 coding regions, of which 15 were repeated in the IR regions. An analysis of chloroplast sequence divergence revealed that the small single copy region was highly variable among the different genera in the Lauraceae family. A total of 40 repeat structures and 83 simple sequence repeats were detected in both the coding and non-coding regions. A phylogenetic analysis indicated that Calycanthus is most closely related to Lauraceae, both being members of Laurales, which forms a sister group to Magnoliids. The complete sequence of the chloroplast of Cinnamomum camphora will aid in in-depth taxonomical studies of the Lauraceae family in the future. The genetic sequence information will also have valuable applications for chloroplast genetic engineering.