Traditional Chinese Medicine: From Aqueous Extracts to Therapeutic Formulae

Traditional Chinese medicine (TCM) is one of the most established systems of medicine in the world. The therapeutic formulae used in TCM are frequently derived from aqueous decoctions of single plants or complex multicomponent formulae. There are aspects of plant cultivation and preparation of decoction pieces that are unique to TCM. These include Daodi cultivation, which is associated with high quality medicinal plant material that is grown in a defined geographical area, and Paozhi processing where the decoction pieces can be treated with excipients and are processed, which may fundamentally change the nature of the chemical metabolites. Therefore, a single plant part, processed in a variety of different ways, can each create a unique medicine. The quality of TCM materials, their safety and therapeutic efficacy are of critical importance. The application of metabolomic and chemometric techniques to these complex and multicomponent medicines is of interest to understand the interrelationships between composition, synergy and therapeutic activity. In this chapter, we present a short history of TCM, detail the role of Daodi and Paozhi in the generation of therapeutic formulae and look at the international practices and methodologies currently in use to ensure their sustainable production, quality, safety and efficacy

EasyNet: An Easy Network for 3D Industrial Anomaly Detection

3D anomaly detection is an emerging and vital computer vision task in industrial manufacturing (IM). Recently many advanced algorithms have been published, but most of them cannot meet the needs of IM. There are several disadvantages: i) difficult to deploy on production lines since their algorithms heavily rely on large pre-trained models; ii) hugely increase storage overhead due to overuse of memory banks; iii) the inference speed cannot be achieved in real-time. To overcome these issues, we propose an easy and deployment-friendly network (called EasyNet) without using pre-trained models and memory banks: firstly, we design a multi-scale multi-modality feature encoder-decoder to accurately reconstruct the segmentation maps of anomalous regions and encourage the interaction between RGB images and depth images; secondly, we adopt a multi-modality anomaly segmentation network to achieve a precise anomaly map; thirdly, we propose an attention-based information entropy fusion module for feature fusion during inference, making it suitable for real-time deployment. Extensive experiments show that EasyNet achieves an anomaly detection AUROC of 92.6% without using pre-trained models and memory banks. In addition, EasyNet is faster than existing methods, with a high frame rate of 94.55 FPS on a Tesla V100 GPU

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

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

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

In Vitro Kinetics of Ribosomal Incorporation of Unnatural Amino Acids

Ribosomal incorporation of unnatural amino acids (AAs) into peptides or proteins has found broad applications in studying translation mechanism, discovering potential therapeutics, and probing protein structure and function. However, such applications are generally limited by the low incorporation efficiencies of the unnatural AAs. With in vitro kinetics studies using a purified E. coli translation system, we found that the natural N-alkyl AA carrier, tRNAPro, could hasten the incorporation of N-methyl AAs. Also, the incorporation rate increased remarkably with increasing pH in the range of 7 to 8.5, suggesting the rate was limited by peptidyl transfer, not accommodation. Competition experiments revealed that several futile cycles of delivery and rejection of the A site N-methyl AA-tRNA were required per peptide bond formation, and the incorporation yield could be increased by using a higher Mg2+ concentration. Kinetics of ribosomal polymerization, using AA-tRNA substrates prepared from the standard N-NVOC-AA-pdCpA chemoenzymatic ligation method, clarified that the inefficiency of incorporation was due to the penultimate dC. This dC prompted faster peptidyl-tRNA drop-off, leading to loss of processivities along consecutive incorporations. Circumventing the penultimate dC by using our N-NVOC-AA-pCpA chemoenzymatic ligation or the flexizyme charging method to prepare the AA-tRNA substrates was able to improve the efficiencies of ribosomal consecutive incorporations of unnatural AAs. By studying the translation steps after aminoacylation of tRNAPyl, the favored carrier for unnatural AAs in vivo, we demonstrated surprisingly slow biphasic kinetics of tRNAPyl-mediated amber suppression in vitro. The fast phase amplitude increased with increasing EF-Tu concentration, allowing measurement of Kd of EF-Tu binding. Results revealed ~25-fold weaker EF-Tu binding affinity of the tRNAPyl body than that of E. coli tRNAPhe. The fast phase rate was ~30-fold slower than that of native substrates, and this rate was limited by the ~10-fold less efficient AA-tRNAPyl:EF-Tu:GTP ternary complex binding to the ribosome. The incorporation was so slow that termination by RF2 mis-reading of the amber codon became a significant competing reaction. The processivity was unexpectedly impaired as ~40% of the dipeptidyl-tRNAPyl could not be elongated to tripeptide. This new overall understanding opens a window of improving unnatural AA incorporation both in vitro and in vivo

In Vitro Kinetics of Ribosomal Incorporation of Unnatural Amino Acids

Ribosomal incorporation of unnatural amino acids (AAs) into peptides or proteins has found broad applications in studying translation mechanism, discovering potential therapeutics, and probing protein structure and function. However, such applications are generally limited by the low incorporation efficiencies of the unnatural AAs. With in vitro kinetics studies using a purified E. coli translation system, we found that the natural N-alkyl AA carrier, tRNAPro, could hasten the incorporation of N-methyl AAs. Also, the incorporation rate increased remarkably with increasing pH in the range of 7 to 8.5, suggesting the rate was limited by peptidyl transfer, not accommodation. Competition experiments revealed that several futile cycles of delivery and rejection of the A site N-methyl AA-tRNA were required per peptide bond formation, and the incorporation yield could be increased by using a higher Mg2+ concentration. Kinetics of ribosomal polymerization, using AA-tRNA substrates prepared from the standard N-NVOC-AA-pdCpA chemoenzymatic ligation method, clarified that the inefficiency of incorporation was due to the penultimate dC. This dC prompted faster peptidyl-tRNA drop-off, leading to loss of processivities along consecutive incorporations. Circumventing the penultimate dC by using our N-NVOC-AA-pCpA chemoenzymatic ligation or the flexizyme charging method to prepare the AA-tRNA substrates was able to improve the efficiencies of ribosomal consecutive incorporations of unnatural AAs. By studying the translation steps after aminoacylation of tRNAPyl, the favored carrier for unnatural AAs in vivo, we demonstrated surprisingly slow biphasic kinetics of tRNAPyl-mediated amber suppression in vitro. The fast phase amplitude increased with increasing EF-Tu concentration, allowing measurement of Kd of EF-Tu binding. Results revealed ~25-fold weaker EF-Tu binding affinity of the tRNAPyl body than that of E. coli tRNAPhe. The fast phase rate was ~30-fold slower than that of native substrates, and this rate was limited by the ~10-fold less efficient AA-tRNAPyl:EF-Tu:GTP ternary complex binding to the ribosome. The incorporation was so slow that termination by RF2 mis-reading of the amber codon became a significant competing reaction. The processivity was unexpectedly impaired as ~40% of the dipeptidyl-tRNAPyl could not be elongated to tripeptide. This new overall understanding opens a window of improving unnatural AA incorporation both in vitro and in vivo

Translational roles of the C75 2 ' OH in an in vitro tRNA transcript at the ribosomal A, P and E sites

Aminoacyl-tRNAs containing a deoxy substitution in the penultimate nucleotide (C75 2'OH -> 2'H) have been widely used in translation for incorporation of unnatural amino acids (AAs). However, this supposedly innocuous modification surprisingly increased peptidyl-tRNA(ugc)(Ala) drop off in biochemical assays of successive incorporations. Here we predict the function of this tRNA 2'OH in the ribosomal A, P and E sites using recent co-crystal structures of ribosomes and tRNA substrates and test these structure-function models by systematic kinetics analyses. Unexpectedly, the C75 2'H did not affect A-to P-site translocation nor peptidyl donor activity of tRNA(ugc)(Ala). Rather, the peptidyl acceptor activity of the A-site Ala-tRNA(ugc)(Ala) and the translocation of the P-site deacylated tRNA(ugc)(Ala) to the E site were impeded. Delivery by EF-Tu was not significantly affected. This broadens our view of the roles of 2'OH groups in tRNAs in translation