Publications

ABSTRACT We present optical and ultraviolet photometry, as well as optical spectra, for the type II supernova (SN) 2015bf. Our observations cover the phases from ∼2 to ∼200 d after explosion. The first spectrum is characterized by a blue continuum with a blackbody temperature of ∼24 000 K and flash-ionized emission lines. After about 1 week, the spectra of SN 2015bf evolve like those of a regular SN II. From the luminosity of the narrow emission component of H α, we deduce that the mass-loss rate is larger than ${\sim}3.7\times 10^{-3}\, {\rm M_\odot \, yr^{-1}}$. The disappearance of the flash features in the first week after explosion indicates that the circumstellar material is confined within ∼6 × 1014 cm. Thus, we suggest that the progenitor of SN 2015bf experienced violent mass loss shortly before the supernova explosion. The multiband light curves show that SN 2015bf has a high peak luminosity with an absolute visual magnitude MV = −18.11 ± 0.08 mag and a fast post-peak decline with a V-band decay of 1.22 ± 0.09 mag within ∼50 d after maximum light. Moreover, the R-band tail luminosity of SN 2015bf is fainter than that of SNe II with similar peak by 1–2 mag, suggesting a small amount of 56Ni (${\sim}0.009\, {\rm M_\odot }$) synthesized during the explosion. Such a low nickel mass indicates that the progenitor of SN 2015bf could be a super-asymptotic-giant-branch star that collapsed owing to electron capture.

Abstract Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number ( k cat ), Michaelis constant ( K m ), and catalytic efficiency ( k cat / K m ), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust k cat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

Acute graft-versus-host disease (aGVHD) remains a major complication of allogeneic bone marrow transplantation, which is caused by donor T cells specific for host alloantigens. In a murine model, we found that donor T cells expressed a natural killer cell inhibitory receptor, CD94/NKG2A, during the course of aGVHD. Administration of an anti-NKG2A mAb markedly inhibited the expansion of donor T cells and ameliorated the aGVHD pathologies. These results suggested that the CD94/NKG2A inhibitory receptor expressed on host-reactive donor T cells can be a novel target for the amelioration of aGVHD.

Spoiler alert: Claude and Gemini did better than GPT-4 in extracting information from chemistry literature.

Abstract Neuromorphic computing (NC) is a new generation of artificial intelligence. Memristors are promising candidates for NC owing to the feasibility of their ultrahigh‐density 3D integration and their ultralow energy consumption. Compared to traditional electrical memristors, the emerging optoelectronic memristors are more attractive owing to their ability to combine the advantages of both photonics and electronics. However, the inability to reversibly tune the memconductance with light has severely restricted the development of optoelectronic NC. Here, an all‐optically controlled (AOC) analog memristor is realized, with memconductance that is reversibly tunable over a continuous range by varying only the wavelength of the controlling light. The device is based on the relatively mature semiconductor material InGaZnO and a memconductance tuning mechanism of light‐induced electron trapping and detrapping. It is found that the light‐induced multiple memconductance states are nonvolatile. Furthermore, spike‐timing‐dependent plasticity learning can be mimicked in this AOC memristor, indicating its potential applications in AOC spiking neural networks for highly efficient optoelectronic NC.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

The first unsubstituted olefin-linked covalent organic framework, termed COF-701, was made by linking 2,4,6-trimethyl-1,3,5-triazine (TMT) and 4,4'-biphenyldicarbaldehyde (BPDA) through Aldol condensation. Formation of the unsubstituted olefin (-CH═CH-) linkage upon reticulation is confirmed by Fourier transform infrared (FT-IR) spectroscopy and solid-state ¹³C cross-polarization magic angle spinning (CP-MAS) NMR spectroscopy of the framework and of its ¹³C-isotope-labeled analogue. COF-701 is found to be porous (1715 m² g^-1) and to retain its composition and crystallinity under both strongly acidic and basic conditions. The high chemical robustness is attributed to the unsubstituted olefin linkages. Immobilization of the strong Lewis acid BF₃·OEt₂ in the pores of the structure yields BF₃⊂COF-701. In the material, the catalytic activity of the guest is retained, as evidenced in a benchmark Diels-Alder reaction.