Transcriptomics and metabolomics reveal the primary and secondary metabolism changes in Glycyrrhiza uralensis with different forms of nitrogen utilization

The roots and rhizomes of Glycyrrhiza uralensis Fisch. represent the oldest and most frequently used herbal medicines in Eastern and Western countries. However, the quality of cultivated G. uralensis has not been adequate to meet the market demand, thereby exerting increased pressure on wild G. uralensis populations. Nitrogen, vital for plant growth, potentially influences the bioactive constituents of plants. Yet, more information is needed regarding the effect of different forms of nitrogen on G. uralensis. G. uralensis seedlings were exposed to a modified Hoagland nutrient solution (HNS), varying concentrations of nitrate (KNO3), or ammonium (NH4)2SO4. We subsequently obtained the roots of G. uralensis for physiology, transcriptomics, and metabolomics analyses. Our results indicated that medium-level ammonium nitrogen was more effective in promoting G. uralensis growth compared to nitrate nitrogen. However, low-level nitrate nitrogen distinctly accelerated the accumulation of flavonoid ingredients. Illumina sequencing of cDNA libraries prepared from four groups—treated independently with low/medium NH4+ or NO3- identified 364, 96, 103, and 64 differentially expressed genes (DEGs) in each group. Our investigation revealed a general molecular and physiological metabolism stimulation under exclusive NH4+ or NO3- conditions. This included nitrogen absorption and assimilation, glycolysis, Tricarboxylic acid (TCA) cycle, flavonoid, and triterpenoid metabolism. By creating and combining putative biosynthesis networks of nitrogen metabolism, flavonoids, and triterpenoids with related structural DEGs, we observed a positive correlation between the expression trend of DEGs and flavonoid accumulation. Notably, treatments with low-level NH4+ or medium-level NO3- positively improved primary metabolism, including amino acids, TCA cycle, and glycolysis metabolism. Meanwhile, low-level NH4+ and NO3- treatment positively regulated secondary metabolism, especially the biosynthesis of flavonoids in G. uralensis. Our study lays the foundation for a comprehensive analysis of molecular responses to varied nitrogen forms in G. uralensis, which should help understand the relationships between responsive genes and subsequent metabolic reactions. Furthermore, our results provide new insights into the fundamental mechanisms underlying the treatment of G. uralensis and other Glycyrrhiza plants with different nitrogen forms

HCSC: Hierarchical Contrastive Selective Coding

Hierarchical semantic structures naturally exist in an image dataset, in which several semantically relevant image clusters can be further integrated into a larger cluster with coarser-grained semantics. Capturing such structures with image representations can greatly benefit the semantic understanding on various downstream tasks. Existing contrastive representation learning methods lack such an important model capability. In addition, the negative pairs used in these methods are not guaranteed to be semantically distinct, which could further hamper the structural correctness of learned image representations. To tackle these limitations, we propose a novel contrastive learning framework called Hierarchical Contrastive Selective Coding (HCSC). In this framework, a set of hierarchical prototypes are constructed and also dynamically updated to represent the hierarchical semantic structures underlying the data in the latent space. To make image representations better fit such semantic structures, we employ and further improve conventional instance-wise and prototypical contrastive learning via an elaborate pair selection scheme. This scheme seeks to select more diverse positive pairs with similar semantics and more precise negative pairs with truly distinct semantics. On extensive downstream tasks, we verify the superior performance of HCSC over state-of-the-art contrastive methods, and the effectiveness of major model components is proved by plentiful analytical studies. We build a comprehensive model zoo in Sec. D. Our source code and model weights are available at https://github.com/gyfastas/HCSCComment: Accepted by CVPR 2022. arXiv v3: 800 epoch multi-crop model released; arXiv v2: more model weights released; arXiv v1: code & model weights release

Tyrosinase inhibition by p-coumaric acid ethyl ester identified from camellia pollen

A tyrosinase inhibitor was separated from camellia pollen with the aid of solvent fraction, macroporous adsorptive resin chromatography, and high-speed countercurrent chromatography. The inhibitor was identified to be p-coumaric acid ethyl ester (p-CAEE) by nuclear magnetic resonance and mass spectrum. Its inhibitory activity (IC50 = 4.89 μg/ml) was about 10-fold stronger than arbutin (IC50 = 51.54 μg/ml). The p-CAEE inhibited tyrosinase in a noncompetitive model with the KI and Km of 1.83 μg/ml and 0.52 mM, respectively. Fluorescence spectroscopy analysis showed the p-CAEE quenched an intrinsic fluorescence tyrosinase. UV-Vis spectroscopy analysis showed the p-CAEE did not interact with copper ions of the enzyme. Docking simulation implied the p-CAEE induced a conformational change in the catalytic region and thus changed binding forces of L-tyrosine. Our findings suggest that p-CAEE plays an important role in inhibiting tyrosinase and provides a reference for developing pharmaceutical, cosmetic, and fruit preservation products using pollen

Effect of oxygen and heating on aromas of pummelo (<i>Citrus maxima</i>) essential oil

<p><b>Objective</b>: To investigate effects of oxygen and heating on aromas and volatile components of pummelo essential oil (PEO). <b>Method</b>: The PEOs were analyzed by sensory evaluation, gas chromatography coupled with mass spectrometry (GC-MS), GC-olfactometry (GC-O) and sensory reconstruction analysis. <b>Results</b>: The PEO co-treated by oxygen and heating exhibited significant differences in both aromas and volatile compositions from those of the fresh, the nitrogen-protected, the heated and the oxygen-exposed PEOs. The strong sweet and floral notes of the oxygen and heating co-treated PEO were attributed to high concentration of limonene oxides; the strong minty note was resulted from the increase of <i>L</i>-carvone. <b>Conclusion</b>: The results indicate that limonene oxides and <i>L</i>-carvone could significantly change the aroma of PEO co-treatment by oxygen and heating, providing valuable information for the production and storage of aromatic products of PEO.</p

Patients with Asian-type DEL can safely be transfused using RhD-positive blood

Red blood cells (RBCs) of the Asian-type DEL phenotype express few RhD proteins and are typed as serologic RhD-negative (D-) in routine testing. RhD-positive (D+) RBC transfusion for Asian-type DEL patients has been proposed but has not been generally adopted due to a lack of direct evidence regarding its safety and underlying mechanism. We performed a single-arm multicenter clinical trial to document the outcome of D+ RBC transfusion in Asian-type DEL patients; none of the recipients (0/42; 95% confidence interval, 0%-8.40%) developed alloanti-D after a median follow-up of 226 days. We conducted a large retrospective study to detect alloanti-D immunization in 4,045 serologic D- pregnant women throughout China; alloanti-D was found only in true D- individuals (2.63%, 79/3,009), but not in those with Asian-type DEL (0/1,032). We further retrospectively examined 127 serologic D- pregnant women who had developed alloanti-D and found none with Asian-type DEL (0/127). Finally, we analyzed RHD transcripts from Asian-type DEL erythroblasts and examined antigen epitopes expressed by various RHD transcripts in vitro, finding a low abundance of full-length RHD transcripts (0.18% of the total) expressing RhD antigens carrying the entire repertoire of epitopes, which could explain the immune tolerance against D+ RBCs. Our results provide multiple lines of evidence that individuals with Asian-type DEL cannot produce alloanti-D when exposed to D+ RBCs following transfusion or pregnancy. Therefore, we recommend considering D+ RBC transfusion and discontinuing anti-D prophylaxis in Asian-type DEL patients, including pregnant women. This clinical trial is registered at www.clinicaltrials.gov as NCT03727230

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of $\times$4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution.Comment: Validation code of the baseline model is available at https://github.com/ofsoundof/IMDN. Validation of all submitted models is available at https://github.com/ofsoundof/NTIRE2022_ES