Chemical composition of Chinese palm fruit and chemical properties of the oil extracts

The proximate composition, mineral concentration of fleshy mesocarp, palm meat (PM) and palm kernel (PK) of oil palm fruit (Elaeis guineensis S.L.Dura) produced in Hainan, China were investigated. The fatty acid composition, chemical properties and minor constituents of palm oil (PO) and palm kernel oil (PKO) were also studied. The crude fat of PM and PK were 68.09±3.57% and 49.36±2.61%, respectively. The PM and PK were found to be good sources of minerals. The acid value (AV) and free fatty acid (FFA) of PO extracted from fresh PM were much higher. If the fresh PM were heated at 100ºC for 30 min, the AV and % FFA could be reduced to 4.62±0.04 mgKOH/g and 2.72±0.002%, respectively. The major fatty acid of PO was palmitic acid 39.93±1.66% and that of PKO was lauric acid 48.01±0.69%. Tocopherol isomer (α-, (β+γ)- and δ-) contents in PO were 68.8±1.84, 22.8±0.54 and 11.8±0.12 mg/kg, respectively. The β-carotene content in PO was 901.5±11.95 mg/kg. The content of sterols in PO and PKO were 880.0±5.23 and 858.0±4.37 mg/kg, respectively. PO and PKO exhibited good chemical properties and could be used as edible oils and for industrial applications. There are almost no data about Chinese palm fruit now and this study systematically researched on it, which can provide useful information for Chinese oil palm industry.Key words: Chemical composition, palm fruit, palm oil, palm kernel oil, chemical properties

Effect of enzymatically produced tuna oil acylglycerol on the characteristics of gelatin O/W emulsion during microencapsulation using complex coacervation

Complex coacervation is an effective process to deliver ingredients for functional food applications. A stable oil-in-water (O/W) emulsion with desired characteristics significantly affects the complex coacervation and the quality of final microcapsules. In this study, tuna oil was partially hydrolyzed using TL100 and ADL lipases to produce acylglycerols TL100-AC and ADL-AC, respectively. These lipids were subsequently stabilized by gelatin in the O/W emulsion, followed by the complex coacervation with sodium hexametaphosphate. The effect of lipids on emulsion properties, such as interfacial properties, rheological properties, protein conformation and microcapsule formation during complex coacervation, was investigated. Compared with tuna oil-based emulsion, acylglycerol-based ones exhibited reduced droplet size (75%). These changes were beneficial to the formation of coagulant and flocculant so that gelatin-stabilized acylglycerol-based O/W emulsion resulted in improved complex coacervation between gelatin and sodium hexametaphosphate. This study provides a scientific basis for designing specific gelatin O/W emulsions and microencapsulation for the stabilization and delivery of omega-3 fatty acids

Molecular Cloning and Expression Analysis of the Endogenous Cellulase Gene MaCel1 in Monochamus alternatus

The purpose of this study was to characterize the endogenous cellulase gene MaCel1 of Monochamus alternatus, which is an important vector of Bursaphelenchus xylophilus, a pine wood nematode, which causes pine wilt disease (PWD). In this study, MaCel1 was cloned by rapid amplification of cDNA end (RACE), and its expression analyzed by RT-qPCR (real-time quantitative PCR detecting). A total of 1778 bp of cDNA was obtained. The encoding region of this gene was 1509 bp in length, encoding a protein containing 502 amino acids with a molecular weight of 58.66 kDa, and the isoelectric point of 5.46. Sequence similarity analysis showed that the amino acids sequence of MaCel1 had high similarity with the beta-Glucosinolate of Anoplophora glabripennis and slightly lower similarity with other insect cellulase genes (GH1). The beta-D-Glucosidase activity of MaCel1 was 256.02 +/- 43.14 U/L with no beta-Glucosinolate activity. MaCel1 gene was widely expressed in the intestine of M. alternatus. The expression level of MaCel1 gene in male (3.46) and female (3.51) adults was significantly higher than that in other developmental stages, and the lowest was in pupal stage (0.15). The results will help reveal the digestive mechanism of M. alternatus and lay the foundation for controlling PWD by controlling M. alternatus

Impact of intestinal microbiota on metabolic toxicity and potential detoxification of amygdalin

Amygdalin (Amy) is metabolized into cyanide in vivo, which may lead to fatal poisoning after oral administration. The defense mechanisms against toxic cyanide have not yet been adequately studied. In this study, comparative toxicokinetics study of Amy was performed in normal and pseudo germ-free rats. The efficiency of cyanide release was significant higher in normal group when given a single oral dose of 440 mg/kg (50% median lethal dose). Thiocyanate, the detoxification metabolite, was firstly detected in feces, caecum, and intestinal microbiota incubation enzymic system. The results suggest intestinal microbiota is involved in bidirectional regulation of toxicity and detoxification of Amy. We further identified the species related to cyanogenesis of Amy with metagenomic sequencing, such as Bifidobacterium pseudolongum, Marvinbryantia formatexigens, and Bacteroides fragilis. Functional analysis of microbiota reveals the detoxification potential of intestinal microbiota for cyanide. Sulfurtransferase superfamily, such as rhodanese, considered as main detoxification enzymes for cyanide, are largely found in Coriobacteriaceae bacterium, Butyricicoccus porcorum, Akkermansia muciniphila, etc. Besides, cyanoamino acid metabolism pathway dominated by Escherichia coli may contribute to the detoxification metabolism of cyanide. In summary, intestinal microbiota may be the first line of defense against the toxicity induced by Amy

Gut Bacterial Communities of Lymantria xylina and Their Associations with Host Development and Diet

The gut microbiota of insects has a wide range of effects on host nutrition, physiology, and behavior. The structure of gut microbiota may also be shaped by their environment, causing them to adjust to their hosts; thus, the objective of this study was to examine variations in the morphological traits and gut microbiota of Lymantria xylina in response to natural and artificial diets using high-throughput sequencing. Regarding morphology, the head widths for larvae fed on a sterilized artificial diet were smaller than for larvae fed on a non-sterilized host-plant diet in the early instars. The gut microbiota diversity of L. xylina fed on different diets varied significantly, but did not change during different development periods. This seemed to indicate that vertical inheritance occurred in L. xylina mutualistic symbionts. Acinetobacter and Enterococcus were dominant in/on eggs. In the first instar larvae, Acinetobacter accounted for 33.52% of the sterilized artificial diet treatment, while Enterococcus (67.88%) was the predominant bacteria for the non-sterilized host-plant diet treatment. Gut microbe structures were adapted to both diets through vertical inheritance and self-regulation. This study clarified the impacts of microbial symbiosis on L. xylina and might provide new possibilities for improving the control of these bacteria

Magnetic resonance imaging based deep-learning model: a rapid, high-performance, automated tool for testicular volume measurements

BackgroundTesticular volume (TV) is an essential parameter for monitoring testicular functions and pathologies. Nevertheless, current measurement tools, including orchidometers and ultrasonography, encounter challenges in obtaining accurate and personalized TV measurements.PurposeBased on magnetic resonance imaging (MRI), this study aimed to establish a deep learning model and evaluate its efficacy in segmenting the testes and measuring TV.Materials and methodsThe study cohort consisted of retrospectively collected patient data (N = 200) and a prospectively collected dataset comprising 10 healthy volunteers. The retrospective dataset was divided into training and independent validation sets, with an 8:2 random distribution. Each of the 10 healthy volunteers underwent 5 scans (forming the testing dataset) to evaluate the measurement reproducibility. A ResUNet algorithm was applied to segment the testes. Volume of each testis was calculated by multiplying the voxel volume by the number of voxels. Manually determined masks by experts were used as ground truth to assess the performance of the deep learning model.ResultsThe deep learning model achieved a mean Dice score of 0.926 ± 0.034 (0.921 ± 0.026 for the left testis and 0.926 ± 0.034 for the right testis) in the validation cohort and a mean Dice score of 0.922 ± 0.02 (0.931 ± 0.019 for the left testis and 0.932 ± 0.022 for the right testis) in the testing cohort. There was strong correlation between the manual and automated TV (R2 ranging from 0.974 to 0.987 in the validation cohort; R2 ranging from 0.936 to 0.973 in the testing cohort). The volume differences between the manual and automated measurements were 0.838 ± 0.991 (0.209 ± 0.665 for LTV and 0.630 ± 0.728 for RTV) in the validation cohort and 0.815 ± 0.824 (0.303 ± 0.664 for LTV and 0.511 ± 0.444 for RTV) in the testing cohort. Additionally, the deep-learning model exhibited excellent reproducibility (intraclass correlation >0.9) in determining TV.ConclusionThe MRI-based deep learning model is an accurate and reliable tool for measuring TV

Identifying Highly Conserved and Highly Differentiated Gene Ontology Categories in Human Populations

Detecting and interpreting certain system-level characteristics associated with human population genetic differences is a challenge for human geneticists. In this study, we conducted a population genetic study using the HapMap genotype data to identify certain special Gene Ontology (GO) categories associated with high/low genetic difference among 11 Hapmap populations. Initially, the genetic differences in each gene region among these populations were measured using allele frequency, linkage disequilibrium (LD) pattern, and transferability of tagSNPs. The associations between each GO term and these genetic differences were then identified. The results showed that cellular process, catalytic activity, binding, and some of their sub-terms were associated with high levels of genetic difference, and genes involved in these functional categories displayed, on average, high genetic diversity among different populations. By contrast, multicellular organismal processes, molecular transducer activity, and some of their sub-terms were associated with low levels of genetic difference. In particular, the neurological system process under the multicellular organismal process category had low levels of genetic difference; the neurological function also showed high evolutionary conservation between species in some previous studies. These results may provide a new insight into the understanding of human evolutionary history at the system-level

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io