Continuous and comprehensive atmospheric observations in Beijing : a station to understand the complex urban atmospheric environment

Peer reviewe

The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5-3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3-7 and 7-15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.Peer reviewe

POSS-CNN: An Automatically Generated Convolutional Neural Network with Precision and Operation Separable Structure Aiming at Target Recognition and Detection

Artificial intelligence is changing and influencing our world. As one of the main algorithms in the field of artificial intelligence, convolutional neural networks (CNNs) have developed rapidly in recent years. Especially after the emergence of NASNet, CNNs have gradually pushed the idea of AutoML to the public’s attention, and large numbers of new structures designed by automatic searches are appearing. These networks are usually based on reinforcement learning and evolutionary learning algorithms. However, sometimes, the blocks of these networks are complex, and there is no small model for simpler tasks. Therefore, this paper proposes POSS-CNN aiming at target recognition and detection, which employs a multi-branch CNN structure with PSNC and a method of automatic parallel selection for super parameters based on a multi-branch CNN structure. Moreover, POSS-CNN can be broken up. By choosing a single branch or the combination of two branches as the “benchmark”, as well as the overall POSS-CNN, we can achieve seven models with different precision and operations. The test accuracy of POSS-CNN for a recognition task tested on a CIFAR10 dataset can reach 86.4%, which is equivalent to AlexNet and VggNet, but the operation and parameters of the whole model in this paper are 45.9% and 45.8% of AlexNet, and 29.5% and 29.4% of VggNet. The mAP of POSS-CNN for a detection task tested on the LSVH dataset is 45.8, inferior to the 62.3 of YOLOv3. However, compared with YOLOv3, the operation and parameters of the model in this paper are reduced by 57.4% and 15.6%, respectively. After being accelerated by WRA, POSS-CNN for a detection task tested on an LSVH dataset can achieve 27 fps, and the energy efficiency is 0.42 J/f, which is 5 times and 96.6 times better than GPU 2080Ti in performance and energy efficiency, respectively

Structural and functional insights into the lipid regulation of human anion exchanger 2

Abstract Anion exchanger 2 (AE2) is an electroneutral Na+-independent Cl-/HCO3 - exchanger belongs to the SLC4 transporter family. The widely expressed AE2 participates in a variety of physiological processes, including transepithelial acid-base secretion and osteoclastogenesis. Both the transmembrane domains (TMDs) and the N-terminal cytoplasmic domain (NTD) are involved in regulation of AE2 activity. However, the regulatory mechanism remains unclear. Here, we report a 3.2 Å cryo-EM structure of the AE2 TMDs in complex with PIP2 and a 3.3 Å full-length mutant AE2 structure in the resting state without PIP2. We demonstrate that PIP2 at the TMD dimer interface is involved in the substrate exchange process. Mutation in the PIP2 binding site leads to the displacement of TM7 and further stabilizes the interaction between the TMD and the NTD. Reduced substrate transport activity and conformation similar to AE2 in acidic pH indicating the central contribution of PIP2 to the function of AE2

A conserved N-terminal motif of CUL3 contributes to assembly and E3 ligase activity of CRL3KLHL22

Abstract The CUL3-RING E3 ubiquitin ligases (CRL3s) play an essential role in response to extracellular nutrition and stress stimuli. The ubiquitin ligase function of CRL3s is activated through dimerization. However, how and why such a dimeric assembly is required for its ligase activity remains elusive. Here, we report the cryo-EM structure of the dimeric CRL3KLHL22 complex and reveal a conserved N-terminal motif in CUL3 that contributes to the dimerization assembly and the E3 ligase activity of CRL3KLHL22. We show that deletion of the CUL3 N-terminal motif impairs dimeric assembly and the E3 ligase activity of both CRL3KLHL22 and several other CRL3s. In addition, we found that the dynamics of dimeric assembly of CRL3KLHL22 generates a variable ubiquitination zone, potentially facilitating substrate recognition and ubiquitination. These findings demonstrate that a CUL3 N-terminal motif participates in the assembly process and provide insights into the assembly and activation of CRL3s

Whole-brain monosynaptic inputs and outputs of leptin receptor b neurons of the nucleus tractus solitarii in mice

The nucleus tractus solitarii (NTS) is the primary central station that integrates visceral afferent information and regulates respiratory, gastrointestinal, cardiovascular, and other physiological functions. Leptin receptor b (LepRb)-expressing neurons of the NTS (NTSLepRb neurons) are implicated in central respiration regulation, respiratory facilitation, and respiratory drive enhancement. Furthermore, LepRb dysfunction is involved in obesity, insulin resistance, and sleep-disordered breathing. However, the monosynaptic inputs and outputs of NTSLepRb neurons in whole-brain mapping remain to be elucidated. Therefore, the exploration of its whole-brain connection system may provide strong support for comprehensively understanding the physiological and pathological functions of NTSLepRb neurons. In the present study, we used a cell type-specific, modified rabies virus and adeno-associated virus with the Cre-loxp system to map monosynaptic inputs and outputs of NTSLepRb neurons in LepRb-Cre mice. The results showed that NTSLepRb neurons received inputs from 48 nuclei in the whole brain from five brain regions, including especially the medulla. We found that NTSLepRb neurons received inputs from nuclei associated with respiration, such as the pre-Bötzinger complex, ambiguus nucleus, and parabrachial nucleus. Interestingly, some brain areas related to cardiovascular regulation—i.e., the ventrolateral periaqueductal gray and locus coeruleus—also sent a small number of inputs to NTSLepRb neurons. In addition, anterograde tracing results demonstrated that NTSLepRb neurons sent efferent projections to 15 nuclei, including the dorsomedial hypothalamic nucleus and arcuate hypothalamic nucleus, which are involved in regulation of energy metabolism and feeding behaviors. Quantitative statistical analysis revealed that the inputs of the whole brain to NTSLepRb neurons were significantly greater than the outputs. Our study comprehensively revealed neuronal connections of NTSLepRb neurons in the whole brain and provided a neuroanatomical basis for further research on physiological and pathological functions of NTSLepRb neurons