Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

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A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Mass Collaboration in Earthquake Risk Management

The mechanism of mass collaboration in risk management was studied during the Sichuan earthquake under a Web-based “PeopleFinder” project, where information is contributed and shared among mass contributors. The case study is provided by a great earthquake that happened in Wenchuan County, Sichuan Province, of southwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced the rescue and relief efforts for the great earthquake. In this article, two fundamental frameworks are developed to study the mechanism of mass collaboration. Mass collaboration is proven to be effective in a big public crisis such as the Sichuan earthquake.     

Construction and Characterization of a CTLA-4-Targeted scFv–Melittin Fusion Protein as a Potential Immunosuppressive Agent for Organ Transplant

Immunotoxins with selective cytotoxicity are frequently used as therapeutic immunosuppressive agents in solid-organ transplantation because of their efficiency and high specificity. In this study, we present a new recombinant immunotoxin termed anti-CTLA-4-scFv–melittin prepared from Escherichia coli aimed at clearing activated T cells at the same time avoiding all-round decline in systematic immunity. This fusion protein is composed of anti-CTLA-4-scFv unit and melittin analog unit with properties of low immunogenicity and selective cytotoxicity to CTLA-4-positive T cells. In preliminary biological activity assays, our results confirmed the feasibility of activated T cell clearance strategy and there were significant differences in cell survival rates between CTLA-4-positive group and control group at all experimental concentrations of the immunotoxin. The selective cytotoxicity, low immunogenicity, and low production cost make it an attractive alternate to traditional immunosuppressants.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.     

On the classification of Calligonum juochiangense and C. pumilum (Polygonaceae)

After observing specimens of Calligonum pumilum Losinsk. and C. juochiangense Y. X. Liou in both the field and in herbarium collections, it was found that the morphological characters of these two species are quite different, especially with respect of the twisted direction of fruit ribs, number of bristle rows along each rib, rigidity and degree of interweaving of bristles, as well as their geographic distribution. Therefore, it is concluded that C. pumilum and C. juochiangense should be accepted as two independent species.     

Effects of SOX2 on Proliferation,Migration and Adhesion of Human Dental Pulp Stem Cells

As a key factor for cell pluripotent and self-renewing phenotypes, SOX2 has attracted scientists’ attention gradually in recent years. However, its exact effects in dental pulp stem cells (DPSCs) are still unclear. In this study, we mainly investigated whether SOX2 could affect some biological functions of DPSCs. DPSCs were isolated from the dental pulp of human impacted third molar. SOX2 overexpressing DPSCs (DPSCs-SOX2) were established through retroviral infection. The effect of SOX2 on cell proliferation, migration and adhesion ability was evaluated with CCK-8, trans-well system and fibronectin-induced cell attachment experiment respectively. Whole genome expression of DPSCs-SOX2 was analyzed with RNA microarray. Furthermore, a rescue experiment was performed with SOX2-siRNA in DPSC-SOX2 to confirm the effect of SOX2 overexpression in DPSCs. We found that SOX2 overexpression could result in the enhancement of cell proliferation, migration, and adhesion in DPSCs obviously. RNA microarray analysis indicated that some key genes in the signal pathways associated with cell cycle, migration and adhesion were upregulated in different degree, and the results were further confirmed with qPCR and western-blot. Finally, DPSC-SOX2 transfected with SOX2-siRNA showed a decrease of cell proliferation, migration and adhesion ability, which further confirmed the biological effect of SOX2 in human DPSCs. This study indicated that SOX2 could improve the cell proliferation, migration and adhesion ability of DPSCs through regulating gene expression about cell cycle, migration and adhesion, and provided a novel strategy to develop seed cells with strong proliferation, migration and adhesion ability for tissue engineering.     

Effect of redox-responsive DTSSP crosslinking on poly(l-lysine)-grafted-poly(ethylene glycol) nanoparticles for delivery of proteins

Therapeutic proteins are utilized in a variety of clinical applications, but side effects and rapid in vivo clearance still present hurdles. An approach that addresses both drawbacks is protein encapsulation within in a polymeric nanoparticle, which is effective but introduces the additional challenge of destabilizing the nanoparticle shell in clinically relevant locations. This study examined the effects of crosslinking self-assembled poly(l -lysine)-grafted-poly(ethylene glycol) nanoparticles with redox-responsive 3,3′-dithiobis(sulfosuccinimidyl propionate) (DTSSP) to achieve nanoparticle destabilization in a reductive environment. The polymer-protein nanoparticles (DTSSP NPs) were formed through electrostatic self-assembly and crosslinked with DTSSP, which contains a glutathione-reducible disulfide. As glutathione is upregulated in various cancers, DTSSP NPs could display destabilization within cancer cells. A library of DTSSP NPs was formed with varying copolymer to protein (C:P) and crosslinker to protein (X:P) mass ratios and characterized by size and encapsulation efficiency. DTSSP NPs with a 7:1 C:P ratio and 2:1 X:P ratio were further characterized by stability in the presence proteases and reducing agents. DTSSP NPs fully encapsulated the model protein and displayed 81% protein release when incubated with 5 mM dithiothreitol for 12 hr. This study contributes to understanding stimulus-responsive crosslinking of polymeric nanoparticles and could be foundational to clinical administration of therapeutic proteins.