Influence of Physical States (Crystalized Versus Solubilized) of Bioactive Components And Oil Composition on Bioaccessibility And Bioavailability

Three systems were compared in the first case study: (1). pre-dissolved β-carotene nanoemulsion (d\u3c 200nm); (2). corn oil emulsion (d\u3c 200nm) with β-carotene crystals being added before digestion; (3). phosphate buffer saline with β-carotene being added before digestion. Oil-in-water nanoemulsions were formed by high-pressure homogenization using Tween 20 as emulsifier and corn oil as carrier oil and then they were subjected to a simulated mouth, stomach and small intestine digestion. The rate and extent of free fatty acid production in small intestine decreased in the order (2)\u3e(1)\u3e(3); whereas the β-carotene bioaccessibility decreased in the order (1)\u3e\u3e(2)\u3e(3). In system (3), even without any fat content, there is still noticeable consumption of NaOH, which is due to the ester bonds existing in the non-ionic surfactant (Tween 20). In the second case study, we developed two comparing groups by differentiating their oil concentration (20%, 4% respectively). The bioaccessibility of the high fat group is only half of the low fat group due to the insufficient digestion of fat in the former group. In the third case study, the bioaccessibility of nobiletin with different physical states (crystalized vs solubilized) and in different delivery system (conventional emulsion vs nanoemulsion) was compared. Not like β-carotene, the bioaccessibility of nobiletin as crystals in slightly lower than it is as solubilized state. Meanwhile, in conventional emulsion, the bioaccessibility is slightly lower than in nanoemulsion. This study provides important information for developing effective delivery systems for lipophilic bioactive components in food and beverage applications

Mining the Relationship Between COVID-19 Sentiment and Market Performance

At the beginning of the COVID-19 outbreak in March, we observed one of the largest stock market crashes in history. Within the months following this, a volatile bullish climb back to pre-pandemic performances and higher. In this paper, we study the stock market behavior during the initial few months of the COVID-19 pandemic in relation to COVID-19 sentiment. Using text sentiment analysis of Twitter data, we look at tweets that contain key words in relation to the COVID-19 pandemic and the sentiment of the tweet to understand whether sentiment can be used as an indicator for stock market performance. There has been previous research done on applying natural language processing and text sentiment analysis to understand the stock market performance, given how prevalent the impact of COVID-19 is to the economy, we want to further the application of these techniques to understand the relationship that COVID-19 has with stock market performance. Our findings show that there is a strong relationship to COVID-19 sentiment derived from tweets that could be used to predict stock market performance in the future.Comment: 18 pages, 7 figures, 5 table

Dynamic Analysis of Corporate ESG Reports: A Model of Evolutionary Trends

Environmental, social, and governance (ESG) reports are globally recognized as a keystone in sustainable enterprise development. This study aims to map the changing landscape of ESG topics within firms in the global market. A dynamic framework is developed to analyze ESG strategic management for individual classes, across multiple classes, and in alignment with a specific sustainability index. The output of these analytical processes forms the foundation of an ESG strategic model. Utilizing a rich collection of 21st-century ESG reports from technology companies, our experiment elucidates the changes in ESG perspectives by incorporating analytical keywords into the proposed framework. This work thus provides an empirical method that reveals the concurrent evolution of ESG topics over recent years.Comment: 22 pages, 13 figure

A Quantitative Analysis of Open Source Software Code Quality: Insights from Metric Distributions

Code quality is a crucial construct in open-source software (OSS) with three dimensions: maintainability, reliability, and functionality. To accurately measure them, we divide 20 distinct metrics into two types: 1) threshold-type metrics that influence code quality in a monotonic manner; 2) non-threshold-type metrics that lack a monotonic relationship to evaluate. We propose a distribution-based method to provide scores for metrics, which demonstrates great explainability on OSS adoption. Our empirical analysis includes more than 36,460 OSS projects and their raw metrics from SonarQube and CK. Our work contributes to the understanding of the multi-dimensional construct of code quality and its metric measurements

Genome-wide identification and characterization of LcCCR13 reveals its potential role in lignin biosynthesis in Liriodendron chinense

IntroductionWood formation is closely related to lignin biosynthesis. Cinnamoyl-CoA reductase (CCR) catalyzes the conversion of cinnamoyl-CoA to cinnamaldehydes, which is the initiation of the lignin biosynthesis pathway and a crucial point in the manipulation of associated traits. Liriodendron chinense is an economically significant timber tree. Nevertheless, the underlying mechanism of wood formation in it remains unknown; even the number of LcCCR family members in this species is unclear.Materials and ResultsThis study aimed to perform a genome-wide identification of genes(s) involved in lignin biosynthesis in L. chinense via RT-qPCR assays and functional verification. Altogether, 13 LcCCR genes were identified that were divided into four major groups based on structural and phylogenetic features. The gene structures and motif compositions were strongly conserved between members of the same groups. Subsequently, the expression patterns analysis based on RNA-seq data indicated that LcCCR5/7/10/12/13 had high expression in the developing xylem at the stem (DXS). Furthermore, the RT-qPCR assays showed that LcCCR13 had the highest expression in the stem as compared to other tissues. Moreover, the overexpression of the LcCCR13 in transgenic tobacco plants caused an improvement in the CCR activity and lignin content, indicating that it plays a key role in lignin biosynthesis in the stems.DiscussionOur research lays a foundation for deeper investigation of the lignin synthesis and uncovers the genetic basis of wood formation in L. chinense

Nonviral gene editing via CRISPR/Cas9 delivery by membrane-disruptive and endosomolytic helical polypeptide

Effective and safe delivery of the CRISPR/Cas9 gene-editing elements remains a challenge. Here we report the development of PEGylated nanoparticles (named P-HNPs) based on the cationic α-helical polypeptide poly(γ-4-((2-(piperidin-1-yl)ethyl)aminomethyl)benzyl-L-glutamate) for the delivery of Cas9 expression plasmid and sgRNA to various cell types and gene-editing scenarios. The cell-penetrating α-helical polypeptide enhanced cellular uptake and promoted escape of pCas9 and/or sgRNA from the endosome and transport into the nucleus. The colloidally stable P-HNPs achieved a Cas9 transfection efficiency up to 60% and sgRNA uptake efficiency of 67.4%, representing an improvement over existing polycation-based gene delivery systems. After performing single or multiplex gene editing with an efficiency up to 47.3% in vitro, we demonstrated that P-HNPs delivering Cas9 plasmid/sgRNA targeting the polo-like kinase 1 (Plk1) gene achieved 35% gene deletion in HeLa tumor tissue to reduce the Plk1 protein level by 66.7%, thereby suppressing the tumor growth by >71% and prolonging the animal survival rate to 60% within 60 days. Capable of delivering Cas9 plasmids to various cell types to achieve multiplex gene knock-out, gene knock-in, and gene activation in vitro and in vivo, the P-HNP system offers a versatile gene-editing platform for biological research and therapeutic applications

Effects of yeast culture and oxalic acid supplementation on in vitro nutrient disappearance, rumen fermentation, and bacterial community composition

Hemicellulose is an important polysaccharide in ruminant nutrition, but it has not been studied as thoroughly as cellulose. Further research is needed to explore supplements that can improve its digestibility and ruminal buffering effects. Our previous research demonstrated the efficacy of oxalic acid (OA) as an essential nutrient in yeast culture (YC) for improving rumen fermentation performance. Consequently, we conducted in vitro rumen digestion experiments to examine the effects of YC and OA on rumen fermentation and bacterial composition. Two diets containing different levels of hemicellulose were formulated: diet 1 with 10.3% and diet 2 with 17% hemicellulose. Three levels of YC (0.00, 0.625, and 1.25 g/kg) and three doses of OA (0.0, 0.4, and 0.8 g/kg, DM) were added into each diet with a 3 × 3 factorial design. A comprehensive assessment was conducted on a total of 18 experimental treatments at fermentation periods of 0, 6, 12, 24, and 48 h. In the first experiment (diet 1), the supplementation of YC, OA, and their interaction significantly increased in vitro DM disappearance (IVDMD) and NDF disappearance (IVNDFD; p < 0.001). In the second experiment (diet 2), the supplementation of OA and the interaction between YC and OA (p < 0.001) increased IVDMD and IVCPD, but had no significant effects on IVNDFD. The interactions of YC and OA significantly increased ammonia nitrogen (p < 0.001). The production of acetic acid, propionic acid, and total volatile fatty acids (TVFA), and pH levels were significantly higher in treatments supplemented with YC and OA (p < 0.001). YC and OA in both diets significantly altered the rumen bacterial community leading to increased Shannon and Simpson diversity indices (p < 0.001). In both diets, OA supplementation significantly increased the relative abundance of the phylum Bacteroidetes and Prevotella genus. The result also showed a positive correlation between the Prevotella and Selenomonas genera with IVDMD, IVNDFD, propionic acid, and TVFA production, suggesting that these dominant bacteria enhanced nutrient disappearance in the rumen. In conclusion, adding YC and OA resulted in modifications to the bacterial community’s composition and diversity, and improved nutrient disappearance. These changes indicate improved rumen fermentation efficiency, which is promising for future in vivo studies

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO