Showing papers by "Tsinghua University published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine, BBIBP-CorV: a randomised, double-blind, placebo-controlled, phase 1/2 trial.

Abstract: Summary Background The ongoing COVID-19 pandemic warrants accelerated efforts to test vaccine candidates. We aimed to assess the safety and immunogenicity of an inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine candidate, BBIBP-CorV, in humans. Methods We did a randomised, double-blind, placebo-controlled, phase 1/2 trial at Shangqiu City Liangyuan District Center for Disease Control and Prevention in Henan Province, China. In phase 1, healthy people aged 18–80 years, who were negative for serum-specific IgM/IgG antibodies against SARS-CoV-2 at the time of screening, were separated into two age groups (18–59 years and ≥60 years) and randomly assigned to receive vaccine or placebo in a two-dose schedule of 2 μg, 4 μg, or 8 μg on days 0 and 28. In phase 2, healthy adults (aged 18–59 years) were randomly assigned (1:1:1:1) to receive vaccine or placebo on a single-dose schedule of 8 μg on day 0 or on a two-dose schedule of 4 μg on days 0 and 14, 0 and 21, or 0 and 28. Participants within each cohort were randomly assigned by stratified block randomisation (block size eight) and allocated (3:1) to receive vaccine or placebo. Group allocation was concealed from participants, investigators, and outcome assessors. The primary outcomes were safety and tolerability. The secondary outcome was immunogenicity, assessed as the neutralising antibody responses against infectious SARS-CoV-2. This study is registered with www.chictr.org.cn, ChiCTR2000032459. Findings In phase 1, 192 participants were enrolled (mean age 53·7 years [SD 15·6]) and were randomly assigned to receive vaccine (2 μg [n=24], 4 μg [n=24], or 8 μg [n=24] for both age groups [18–59 years and ≥60 years]) or placebo (n=24). At least one adverse reaction was reported within the first 7 days of inoculation in 42 (29%) of 144 vaccine recipients. The most common systematic adverse reaction was fever (18–59 years, one [4%] in the 2 μg group, one [4%] in the 4 μg group, and two [8%] in the 8 μg group; ≥60 years, one [4%] in the 8 μg group). All adverse reactions were mild or moderate in severity. No serious adverse event was reported within 28 days post vaccination. Neutralising antibody geometric mean titres were higher at day 42 in the group aged 18–59 years (87·7 [95% CI 64·9–118·6], 2 μg group; 211·2 [158·9–280·6], 4 μg group; and 228·7 [186·1–281·1], 8 μg group) and the group aged 60 years and older (80·7 [65·4–99·6], 2 μg group; 131·5 [108·2–159·7], 4 μg group; and 170·87 [133·0–219·5], 8 μg group) compared with the placebo group (2·0 [2·0–2·0]). In phase 2, 448 participants were enrolled (mean age 41·7 years [SD 9·9]) and were randomly assigned to receive the vaccine (8 μg on day 0 [n=84] or 4 μg on days 0 and 14 [n=84], days 0 and 21 [n=84], or days 0 and 28 [n=84]) or placebo on the same schedules (n=112). At least one adverse reaction within the first 7 days was reported in 76 (23%) of 336 vaccine recipients (33 [39%], 8 μg day 0; 18 [21%], 4 μg days 0 and 14; 15 [18%], 4 μg days 0 and 21; and ten [12%], 4 μg days 0 and 28). One placebo recipient in the 4 μg days 0 and 21 group reported grade 3 fever, but was self-limited and recovered. All other adverse reactions were mild or moderate in severity. The most common systematic adverse reaction was fever (one [1%], 8 μg day 0; one [1%], 4 μg days 0 and 14; three [4%], 4 μg days 0 and 21; two [2%], 4 μg days 0 and 28). The vaccine-elicited neutralising antibody titres on day 28 were significantly greater in the 4 μg days 0 and 14 (169·5, 95% CI 132·2–217·1), days 0 and 21 (282·7, 221·2–361·4), and days 0 and 28 (218·0, 181·8–261·3) schedules than the 8 μg day 0 schedule (14·7, 11·6–18·8; all p Interpretation The inactivated SARS-CoV-2 vaccine, BBIBP-CorV, is safe and well tolerated at all tested doses in two age groups. Humoral responses against SARS-CoV-2 were induced in all vaccine recipients on day 42. Two-dose immunisation with 4 μg vaccine on days 0 and 21 or days 0 and 28 achieved higher neutralising antibody titres than the single 8 μg dose or 4 μg dose on days 0 and 14. Funding National Program on Key Research Project of China, National Mega projects of China for Major Infectious Diseases, National Mega Projects of China for New Drug Creation, and Beijing Science and Technology Plan.

Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China

Abstract: To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution In particular, large decreases in NOx emissions from transportation increased ozone and nighttime NO3 radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

Abstract: We report on the population of 47 compact binary mergers detected with a false-alarm rate of 0.01 are dynamically assembled. Third, we estimate merger rates, finding RBBH = 23.9-+8.614.3 Gpc-3 yr-1 for BBHs and RBNS = 320-+240490 Gpc-3 yr-1 for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.

RepVGG: Making VGG-style ConvNets Great Again.

Abstract: We present a simple but powerful architecture of convolutional neural network, which has a VGG-like inference-time body composed of nothing but a stack of 3x3 convolution and ReLU, while the training-time model has a multi-branch topology. Such decoupling of the training-time and inference-time architecture is realized by a structural re-parameterization technique so that the model is named RepVGG. On ImageNet, RepVGG reaches over 80% top-1 accuracy, which is the first time for a plain model, to the best of our knowledge. On NVIDIA 1080Ti GPU, RepVGG models run 83% faster than ResNet-50 or 101% faster than ResNet-101 with higher accuracy and show favorable accuracy-speed trade-off compared to the state-of-the-art models like EfficientNet and RegNet. The code and trained models are available at this https URL.

Programmable quantum simulations of spin systems with trapped ions

Abstract: Author(s): Monroe, C; Campbell, WC; Duan, LM; Gong, ZX; Gorshkov, AV; Hess, PW; Islam, R; Kim, K; Linke, NM; Pagano, G; Richerme, P; Senko, C; Yao, NY | Abstract: Laser-cooled and trapped atomic ions form an ideal standard for the simulation of interacting quantum spin models. Effective spins are represented by appropriate internal energy levels within each ion, and the spins can be measured with near-perfect efficiency using state-dependent fluorescence techniques. By applying optical fields that exert optical dipole forces on the ions, their Coulomb interaction can be modulated to produce long-range and tunable spin-spin interactions that can be reconfigured by shaping the spectrum and pattern of the laser fields in a prototypical example of a quantum simulator. Here the theoretical mapping of atomic ions to interacting spin systems, the preparation of complex equilibrium states, and the study of dynamical processes in these many-body interacting quantum systems are reviewed, and the use of this platform for optimization and other tasks is discussed. The use of such quantum simulators for studying spin models may inform our understanding of exotic quantum materials and shed light on the behavior of interacting quantum systems that cannot be modeled with conventional computers.

Climate warming enhances microbial network complexity and stability

Abstract: Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. These results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming. The authors examine the effect of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. They find warming increases network complexity, which is strongly correlated with network stability.

Observation of Gravitational Waves from Two Neutron Star–Black Hole Coalescences

Abstract: We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses 8.9−1.5+1.2 and 1.9−0.2+0.3M⊙ , whereas the source of GW200115 has component masses 5.7−2.1+1.8 and 1.5−0.3+0.7M⊙ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are 280−110+110 and 300−100+150Mpc , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of 45−33+75Gpc−3yr−1 when assuming that GW200105 and GW200115 are representative of the NSBH population or 130−69+112Gpc−3yr−1 under the assumption of a broader distribution of component masses.

Atomic-Level Modulation of Electronic Density at Cobalt Single-Atom Sites Derived from Metal-Organic Frameworks: Enhanced Oxygen Reduction Performance.

Abstract: Demonstrated here is the correlation between atomic configuration induced electronic density of single-atom Co active sites and oxygen reduction reaction (ORR) performance by combining density-functional theory (DFT) calculations and electrochemical analysis. Guided by DFT calculations, a MOF-derived Co single-atom catalyst with the optimal Co1 -N3 PS active moiety incorporated in a hollow carbon polyhedron (Co1 -N3 PS/HC) was designed and synthesized. Co1 -N3 PS/HC exhibits outstanding alkaline ORR activity with a half-wave potential of 0.920 V and superior ORR kinetics with record-level kinetic current density and an ultralow Tafel slope of 31 mV dec-1 , exceeding that of Pt/C and almost all non-precious ORR electrocatalysts. In acidic media the ORR kinetics of Co1 -N3 PS/HC still surpasses that of Pt/C. This work offers atomic-level insight into the relationship between electronic density of the active site and catalytic properties, promoting rational design of efficient catalysts.

PCT: Point cloud transformer

Abstract: The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer (PCT) for point cloud learning. PCT is based on Transformer, which achieves huge success in natural language processing and displays great potential in image processing. It is inherently permutation invariant for processing a sequence of points, making it well-suited for point cloud learning. To better capture local context within the point cloud, we enhance input embedding with the support of farthest point sampling and nearest neighbor search. Extensive experiments demonstrate that the PCT achieves the state-of-the-art performance on shape classification, part segmentation, semantic segmentation, and normal estimation tasks.

SimCSE: Simple Contrastive Learning of Sentence Embeddings

Abstract: This paper presents SimCSE, a simple contrastive learning framework that greatly advances the state-of-the-art sentence embeddings. We first describe an unsupervised approach, which takes an input sentence and predicts itself in a contrastive objective, with only standard dropout used as noise. This simple method works surprisingly well, performing on par with previous supervised counterparts. We hypothesize that dropout acts as minimal data augmentation and removing it leads to a representation collapse. Then, we draw inspiration from the recent success of learning sentence embeddings from natural language inference (NLI) datasets and incorporate annotated pairs from NLI datasets into contrastive learning by using "entailment" pairs as positives and "contradiction" pairs as hard negatives. We evaluate SimCSE on standard semantic textual similarity (STS) tasks, and our unsupervised and supervised models using BERT-base achieve an average of 74.5% and 81.6% Spearman's correlation respectively, a 7.9 and 4.6 points improvement compared to previous best results. We also show that contrastive learning theoretically regularizes pre-trained embeddings' anisotropic space to be more uniform, and it better aligns positive pairs when supervised signals are available.

Matching the kinetics of natural enzymes with a single-atom iron nanozyme

Abstract: Developing artificial enzymes with the excellent catalytic performance of natural enzymes has been a long-standing goal for chemists. Single-atom catalysts with well-defined atomic structure and electronic coordination environments can effectively mimic natural enzymes. Here, we report an engineered FeN3P-centred single-atom nanozyme (FeN3P-SAzyme) that exhibits comparable peroxidase-like catalytic activity and kinetics to natural enzymes, by controlling the electronic structure of the single-atom iron active centre through the precise coordination of phosphorus and nitrogen. In particular, the engineered FeN3P-SAzyme, with well-defined geometric and electronic structures, displays catalytic performance that is consistent with Michaelis–Menten kinetics. We rationalize the origin of the high enzyme-like activity using density functional theory calculations. Finally, we demonstrate that the developed FeN3P-SAzyme with superior peroxidase-like activity can be used as an effective therapeutic strategy for inhibiting tumour cell growth in vitro and in vivo. Therefore, SAzymes show promising potential for developing artificial enzymes that have the catalytic kinetics of natural enzymes. Nanozymes can provide cost and stability advantages over natural enzymes, but they usually display low catalytic activity and inferior kinetics. Now, a highly active nanozyme is developed that shows comparable kinetics to horseradish peroxidase in the oxidation of a commonly used artificial substrate.

Intrinsic Electrocatalytic Activity Regulation of M-N-C Single-Atom Catalysts for the Oxygen Reduction Reaction.

Abstract: Single-atom catalysts (SACs) with highly active sites atomically dispersed on substrates exhibit unique advantages regarding maximum atomic efficiency, abundant chemical structures, and extraordinary catalytic performances for multiple important reactions. In particular, M-N-C SACs (M=transition metal atom) demonstrate optimal electrocatalytic activity for the oxygen reduction reaction (ORR) and have attracted extensive attention recently. Despite substantial efforts in fabricating various M-N-C SACs, the principles for regulating the intrinsic electrocatalytic activity of their active sites have not been sufficiently studied. In this Review, we summarize the regulation strategies for promoting the intrinsic electrocatalytic ORR activity of M-N-C SACs by modulation of the center metal atoms, the coordinated atoms, the environmental atoms, and the guest groups. Theoretical calculations and experimental investigations are both included to afford a comprehensive understanding of the structure-performance relationship. Finally, future directions of developing advanced M-N-C SACs for electrocatalytic ORR and other analogous reactions are proposed.

Design concept for electrocatalysts

Abstract: Metal-based electrocatalysts with different sizes (single atoms, nanoclusters, and nanoparticles) show different catalytic behaviors for various electrocatalytic reactions. Regulating the coordination environment of active sites with precision to rationally design an efficient electrocatalyst is of great significance for boosting electrocatalytic reactions. This review summarizes the recent process of heterogeneous supported single atoms, nanoclusters, and nanoparticles catalysts in electrocatalytic reactions, respectively, and figures out the construct strategies and design concepts based on their strengths and weaknesses. Specifically, four key factors for enhancing electrocatalytic performance, including electronic structure, coordination environment, support property, and interfacial interactions are proposed to provide an overall comprehension to readers in this field. Finally, some insights into the current challenges and future opportunities of the heterogeneous supported electrocatalysts are provided.

RepVGG: Making VGG-style ConvNets Great Again

Abstract: We present a simple but powerful architecture of convolutional neural network, which has a VGG-like inference-time body composed of nothing but a stack of 3 × 3 convolution and ReLU, while the training-time model has a multi-branch topology. Such decoupling of the training-time and inference-time architecture is realized by a structural re-parameterization technique so that the model is named RepVGG. On ImageNet, RepVGG reaches over 80% top-1 accuracy, which is the first time for a plain model, to the best of our knowledge. On NVIDIA 1080Ti GPU, RepVGG models run 83% faster than ResNet-50 or 101% faster than ResNet-101 with higher accuracy and show favorable accuracy-speed trade-off compared to the state-of-the-art models like EfficientNet and RegNet. The code and trained models are available at https://github.com/megvii-model/RepVGG.

Indoor transmission of SARS-CoV-2.

Abstract: It is essential to understand where and how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted. Case reports were extracted from the local Municipal Health Commissions of 320 prefectural municipalities in China (not including Hubei Province). We identified all outbreaks involving three or more cases and reviewed the major characteristics of the enclosed spaces in which the outbreaks were reported and their associated indoor environmental aspects. Three hundred and eighteen outbreaks with three or more cases were identified, comprising a total of 1245 confirmed cases in 120 prefectural cities. Among the identified outbreaks, 53.8% involved three cases, 26.4% involved four cases, and only 1.6% involved ten or more cases. Home-based outbreaks were the dominant category (254 of 318 outbreaks; 79.9%), followed by transport-based outbreaks (108; 34.0%), and many outbreaks occurred in more than one category of venue. All identified outbreaks of three or more cases occurred in indoor environments, which confirm that sharing indoor spaces with one or more infected persons is a major SARS-CoV-2 infection risk.