Wave-Packet Surface Propagation for Light-Induced Molecular Dynamics.

Recent advances in laser technology have enabled tremendous progress in light-induced molecular reactions, at the heart of which the breaking and formation of chemical bonds are located. Such progress has been greatly facilitated by the development of an accurate quantum-mechanical simulation method, which, however, does not necessarily accompany clear dynamical scenarios and is rather computationally heavy. Here, we develop a wave-packet surface propagation (WASP) approach to describe the molecular bond-breaking dynamics from a hybrid quantum-classical perspective. Via the introduction of quantum elements including state transitions and phase accumulations to the Newtonian propagation of the nuclear wave packet, the WASP approach naturally comes with intuitive physical scenarios and accuracies. It is carefully benchmarked with the H_{2}^{+} molecule and is shown to be capable of precisely reproducing experimental observations. The WASP method is promising for the intuitive visualization of light-induced molecular dynamics and is straightforward extensible towards complex molecules.

Integrated multi-locus genome-wide association studies and transcriptome analysis for seed yield and yield-related traits in Brassica napus.

Rapeseed (Brassica napus L.), the third largest oil crop, is an important source of vegetable oil and biofuel for the world. Although the breeding and yield has been improved, rapeseed still has the lowest yield compared with other major crops. Thus, increasing rapeseed yield is essential for the high demand of vegetable oil and high-quality protein for live stocks. Silique number per plant (SN), seed per pod (SP), and 1000-seed weight (SW) are the three important factors for seed yield in rapeseed. Some yield-related traits, including plant height (PH), flowering time (FT), primary branch number (BN) and silique number per inflorescence (SI) also affect the yield per plant (YP). Using six multi-locus genome-wide association study (ML-GWAS) approaches, a total of 908 yield-related quantitative trait nucleotides (QTNs) were identified in a panel consisting of 403 rapeseed core accessions based on whole-genome sequencing. Integration of ML-GWAS with transcriptome analysis, 79 candidate genes, including BnaA09g39790D (RNA helicase), BnaA09g39950D (Lipase) and BnaC09g25980D (SWEET7), were further identified and twelve genes were validated by qRT-PCRs to affect the SW or SP in rapeseed. The distribution of superior alleles from nineteen stable QTNs in 20 elite rapeseed accessions suggested that the high-yielding accessions contained more superior alleles. These results would contribute to a further understanding of the genetic basis of yield-related traits and could be used for crop improvement in B. napus.

FRCNN-AA-CIF: An automatic detection model of colon polyps based on attention awareness and context information fusion.

It is noted that the foreground and background of the polyp images detected under colonoscopy are not highly differentiated, and the feature map extracted by common deep learning object detection models keep getting smaller as the number of networks increases. Therefore, these models tend to ignore the details in pictures, resulting in a high polyp missed detection rate. To reduce the missed detection rate, this paper proposes an automatic detection model of colon polyps based on attention awareness and context information fusion (FRCNN-AA-CIF) based on a two-stage object detection model Faster Region-Convolutional Neural Network (FR-CNN). First, since the addition of attention awareness can make the feature extraction network pay more attention to polyp features, we propose an attention awareness module based on Squeeze-and-Excitation Network (SENet) and Efficient Channel Attention Module (ECA-Net) and add it after each block of the backbone network. Specifically, we first use the 1*1 convolution of ECA-Net to extract local cross-channel information and then use the two fully connected layers of SENet to reduce and increase the dimension, to filter out the channels that are more useful for feature learning. Further, because of the presence of air bubbles, impurities, inflammation, and accumulation of digestive matter around polyps, we used context information around polyps to enhance the focus on polyp features. In particular, after the network extracts the region of interest, we fuse the region of interest with its context information to improve the detection rate of polyps. The proposed model was tested on the colonoscopy dataset provided by Huashan Hospital. Numerical experiments show that FRCNN-AA-CIF has the highest detection accuracy (mAP of 0.817), the lowest missed detection rate of 4.22%, and the best classification effect (AUC of 95.98%). Its mAP increased by 3.3%, MDR decreased by 1.97%, and AUC increased by 1.8%. Compared with other object detection models, FRCNN-AA-CIF has significantly improved recognition accuracy and reduced missed detection rate.

Conservation and Divergence of the Trihelix Genes in Brassica and Expression Profiles of BnaTH Genes in Brassica napus under Abiotic Stresses.

Trihelix (TH) proteins are a family of plant-specific transcription factors that play a role in light response and are extensively involved in plant growth and development, as well as in various stress responses. However, the function of TH genes in Brassica napus (B. napus) remains unclear, as does the evolution and differentiation pattern of TH genes in Brassica plants. Here, we identified a total of 455 TH genes in seven species, including six Brassica species and Arabidopsis, which were grouped into five clades, GT-1, GT-2, GTγ, SH4, and SIP1, each with 69, 142, 44, 55, and 145 members, respectively. The types and distributions of motifs of the TH proteins and the structures of the TH genes are conserved in the same subgroup, and some variations in certain amino acid residues occur in B. napus when inheriting motifs from Brassica rapa (B. rapa) and Brassica oleracea (B. oleracea). Collinearity analysis revealed that the massive expansion of TH genes in tetraploid species was attributed to the hetero-tetraploidization of diploid ancestors and gene duplication events within the tetraploid species. Comparative analysis of the membership numbers of five subgroups in different species revealed that the GT-2 and SIP1 genes underwent significant expansion during evolution, possibly to support the better adaptation of plants to their environments. The differential expression of the BnaTH genes under five stresses indicates that the BnaTH genes are involved in plant responses to stresses such as drought, cold, and heat. The presence of different stress-responsive cis-elements in the upstream promoter region of the genes indicated that BnaTH genes have the potential to cope with variable environments. Meanwhile, qRT-PCR analyses also confirmed that five TH genes respond to different abiotic stresses. Our results provide information and candidates for further studies on the role of TH genes in stress resistance of B. napus.