Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases1,2, advances in genotyping and sequencing technology have made genome-wide association (GWA) studies an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available because once these lines have been genotyped, they can be phenotyped multiple times, making it possible (as well as extremely cost-effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly selfing model plant, known to harbor considerable genetic variation for many adaptively important traits3. Our results are dramatically different from those of human GWA studies in that we identify many common alleles with major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true from false associations. However, a priori candidates are significantly overrepresented among these associations as well, making many of them excellent candidates for follow-up experiments by the Arabidopsis community. Our study clearly demonstrates the feasibility of GWA studies in A. thaliana, and suggests that the approach will be appropriate for many other organisms.

Highlights d 8,558 IgG1 + antigen-binding clonotypes were identified by high-throughput scRNA/VDJ-seq d 14 potent SARS-CoV-2 neutralizing antibodies were found from 60 convalescent patients d BD-368-2 showed high therapeutic and prophylactic efficacy in SARS-CoV-2-infected mice d Neutralizing antibodies can be directly selected based on predicted CDR3 H structures

Pluripotent stem cells can be induced from somatic cells, providing an unlimited cell resource, with potential for studying disease and use in regenerative medicine. However, genetic manipulation and technically challenging strategies such as nuclear transfer used in reprogramming limit their clinical applications. Here, we show that pluripotent stem cells can be generated from mouse somatic cells at a frequency up to 0.2% using a combination of seven small-molecule compounds. The chemically induced pluripotent stem cells resemble embryonic stem cells in terms of their gene expression profiles, epigenetic status, and potential for differentiation and germline transmission. By using small molecules, exogenous "master genes" are dispensable for cell fate reprogramming. This chemical reprogramming strategy has potential use in generating functional desirable cell types for clinical applications.

Compressive surface strains have been necessary to boost oxygen reduction reaction (ORR) activity in core/shell M/platinum (Pt) catalysts (where M can be nickel, cobalt, or iron). We report on a class of platinum-lead/platinum (PtPb/Pt) core/shell nanoplate catalysts that exhibit large biaxial strains. The stable Pt (110) facets of the nanoplates have high ORR specific and mass activities that reach 7.8 milliampere (mA) per centimeter squared and 4.3 ampere per milligram of platinum at 0.9 volts versus the reversible hydrogen electrode (RHE), respectively. Density functional theory calculations reveal that the edge-Pt and top (bottom)-Pt (110) facets undergo large tensile strains that help optimize the Pt-O bond strength. The intermetallic core and uniform four layers of Pt shell of the PtPb/Pt nanoplates appear to underlie the high endurance of these catalysts, which can undergo 50,000 voltage cycles with negligible activity decay and no apparent structure and composition changes.

Two-inch-sized perovskite crystals, CH3 NH3 PbX3 (X=I, Br, Cl), with high crystalline quality are prepared by a solution-grown strategy. The availability of large perovskite crystals is expected to transform its broad applications in photovoltaics, optoelectronics, lasers, photodetectors, LEDs, etc., just as crystalline silicon has done in revolutionizing the modern electronics and photovoltaic industries.

Recently, a new model based on Pythagorean fuzzy set (PFS) has been presented to manage the uncertainty in real‐world decision‐making problems. PFS has much stronger ability than intuitionistic fuzzy set to model such uncertainty. In this paper, we define some novel operational laws of PFSs and discuss their desirable properties. For the multicriteria decision‐making problems with PFSs, we propose an extended technique for order preference by similarity to ideal solution method to deal effectively with them. In this approach, we first propose a score function based comparison method to identify the Pythagorean fuzzy positive ideal solution and the Pythagorean fuzzy negative ideal solution. Then, we define a distance measure to calculate the distances between each alternative and the Pythagorean fuzzy positive ideal solution as well as the Pythagorean fuzzy negative ideal solution, respectively. Afterward, a revised closeness is introduced to identify the optimal alternative. At length, a practical example is given to illustrate the developed method and to make a comparative analysis.

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