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Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems. In a complex traffic environment, the signal of the Global Navigation Satellite System (GNSS) will be blocked, leading to inaccurate vehicle positioning. To ensure the security of automatic electric campus vehicles, this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain (LEGO-LOAM) algorithm with a monocular vision system added. An algorithm framework based on Lidar-IMU-Camera (Lidar means light detection and ranging) fusion was proposed. A lightweight monocular vision odometer model was used, and the LEGO-LOAM system was employed to initialize monocular vision. The visual odometer information was taken as the initial value of the laser odometer. At the back-end opti9mization phase error state, the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning. The visual word bag model was applied to perform loopback detection. Taking the test results into account, the laser radar loopback detection was further optimized, reducing the accumulated positioning error. The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment. The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav. Compared with the LEGO-LOAM algorithm, the results show that the proposed algorithm can effectively reduce map drift, improve map resolution, and output more accurate driving trajectory information.

Abstract Background Proper flowering time is important for the growth and development of plants, and both too early and too late flowering impose strong negative influences on plant adaptation and seed yield. Thus, it is vitally important to study the mechanism underlying flowering time control in plants. In a previous study by the authors, genome-wide association analysis was used to screen the candidate gene SISTER OF FCA (SSF) that regulates FLOWERING LOCUS C (FLC), a central gene encoding a flowering suppressor in Arabidopsis thaliana. Results SSF physically interacts with Protein arginine methyltransferase 5 (PRMT5, SKB1). Subcellular co—localization analysis showed that SSF and SKB1 interact in the nucleus. Genetically, SSF and SKB1 exist in the same regulatory pathway that controls FLC expression. Furthermore, RNA-sequencing analysis showed that both SSF and SKB1 regulate certain common pathways. Conclusions This study shows that PRMT5 interacts with SSF, thus controlling FLC expression and facilitating flowering time control.

Abstract Through pumping a spin current from ferromagnet into heavy metal (HM) via magnetization precession, parts of the injected spins are in-plane rotated by the lattice vibration, namely acoustic spin rotation (ASR), which manifests itself as an inverse spin Hall voltage in HM with an additional 90° difference in angular dependency. When reversing the stacking order of bilayer with a counter-propagating spin current or using HMs with an opposite spin Hall angle, such ASR voltage shows the same sign, strongly suggesting that ASR changes the rotation direction due to interface spin-orbit interaction. With the drift-diffusion model of spin transport, we quantify the efficiency of ASR up to 30%. The finding of ASR endows the acoustic device with an ability to manipulate spin, and further reveals a new spin-orbit coupling between spin current and lattice vibration.

Photodynamic therapy (PDT) has limited effects in treating metastatic breast cancer. Immune checkpoints can deplete the function of immune cells; however, the expression of immune checkpoints after PDT is unclear. This study investigates whether the limited efficacy of PDT is due to upregulated immune checkpoints and tries to combine the PDT and immune checkpoint inhibitor to observe the efficacy. A metastatic breast cancer model was treated by PDT mediated by hematoporphyrin derivatives (HpD-PDT). The anti-tumor effect of HpD-PDT was observed, as well as CD4[Formula: see text]T, CD8[Formula: see text]T and calreticulin (CRT) by immunohistochemistry and immunofluorescence. Immune checkpoints on T cells were analyzed by flow cytometry after HpD-PDT. When combining PDT with immune checkpoint inhibitors, the antitumor effect and immune effect were assessed. For HpD-PDT at 100[Formula: see text]mW/cm2 and 40, 60 and 80[Formula: see text]J/cm2, primary tumors were suppressed and CD4[Formula: see text]T, CD8[Formula: see text]T and CRT were elevated; however, distant tumors couldn’t be inhibited and survival could not be prolonged. Immune checkpoints on T cells, especially PD1 and LAG-3 after HpD-PDT, were upregulated, which may explain the reason for the limited HpD-PDT effect. After PDT combined with anti-PD1 antibody, but not with anti-LAG-3 antibody, both the primary and distant tumors were significantly inhibited and the survival time was prolonged, additionally, CD4[Formula: see text]T, CD8[Formula: see text]T, IFN-[Formula: see text]CD4[Formula: see text]T and TNF-[Formula: see text]CD4[Formula: see text]T cells were significantly increased compared with HpD-PDT. HpD-PDT could not combat metastatic breast cancer. PD1 and LAG-3 were upregulated after HpD-PDT. Anti-PD1 antibody, but not anti-LAG-3 antibody, could augment the antitumor effect of HpD-PDT for treating metastatic breast cancer.

Inflammatory bowel disease (IBD) is a nonspecific chronic inflammatory disease resulting from an immune disorder in the intestine that is prone to relapse and incurable. The understanding of the pathogenesis of IBD remains unclear. In this study, we found that ace (angiotensin-converting enzyme), expressed abundantly in the intestine, plays an important role in IBD. The deletion of ace in zebrafish caused intestinal inflammation with increased expression of the inflammatory marker genes interleukin 1 beta (il1b), matrix metallopeptidase 9 (mmp9), myeloid-specific peroxidase (mpx), leukocyte cell-derived chemotaxin-2-like (lect2l), and chemokine (C-X-C motif) ligand 8b (cxcl8b). Moreover, the secretion of mucus in the ace−/− mutants was significantly higher than that in the wild-type zebrafish, validating the phenotype of intestinal inflammation. This was further confirmed by the IBD model constructed using dextran sodium sulfate (DSS), in which the mutant zebrafish had a higher susceptibility to enteritis. Our study reveals the role of ace in intestinal homeostasis, providing a new target for potential therapeutic interventions.

The purpose of semi-supervised video object segmentation (VOS) is to predict and generate object masks in subsequent video frames after being provided with the initial frame’s object mask. Currently, mainstream methods leverage historical frame information for enhancing the network’s performance. However, this approach faces the following issues: (1) They often overlook important shape information, leading to decreased accuracy in segmenting object-edge areas. (2) They often use pixel-level motion estimation to guide the matching for addressing distractor objects. However, this brings heavy computation costs and struggle against occlusion or fast/blurry motion. For the first problem, this paper introduces an object shape extraction module that exploits both the high-level and low-level features to obtain object shape information, by which the shape information can be used to further refine the predicted masks. For the second problem, this paper introduces a novel object-level motion prediction module, in which it stores the representative motion features during the training stage, and predicts the object motion by retrieving them during the inference stage. We evaluate our method on benchmark datasets compared with recent state-of-the-art methods, and the results demonstrate the effectiveness of the proposed method.