Stiffened tumor microenvironment enhances perineural invasion in breast cancer via integrin signaling.

BACKGROUND: Accumulating studies have shown that tumors are regulated by nerves, and there is abundant nerve infiltration in the tumor microenvironment. Many solid tumors including breast cancer (BRCA) have different degrees of perineural invasion (PNI), which is closely related to the tumor occurrence and progression. However, the regulatory mechanism of PNI in BRCA remains largely unexplored. METHODS: PNI-related molecular events are analyzed by the RNAseq data of BRCA samples deposited in The Cancer Genome Atlas (TCGA) database. Extracellular matrix (ECM) components within the tumor microenvironment are analyzed by immunohistochemical staining of α-SMA, Sirius red staining, and Masson trichrome staining. Soft and stiff matrix gels, living cell imaging, and dorsal root ganglion (DRG) coculture assay are used to monitor cancer cell invasiveness towards nerves. Western blotting, qRT-PCR, enzyme-linked immunosorbent assay combined with neutralizing antibody and small molecular inhibitors are employed to decode molecular mechanisms. RESULTS: Comparative analysis that the ECM was significantly associated with PNI status in the TCGA cohort. BRCA samples with higher α-SMA activity, fibrillar collagen, and collagen content had higher frequency of PNI. Compared with soft matrix, BRCA cells cultured in stiff matrix not only displayed higher cell invasiveness to DRG neurons but also had significant neurotrophic effects. Mechanistically, integrin ß1 was identified as a functional receptor to the influence of stiff matrix on BRCA cells. Moreover, stiffened matrix-induced activation of integrin ß1 transduces FAK-YAP signal cascade, which enhances cancer invasiveness and the neurotrophic effects. In clinical setting, PNI-positive BRCA samples had higher expression of ITGB1, phosphorylated FAK, YAP, and NGF compared with PNI-negative BRCA samples. CONCLUSIONS: Our findings suggest that stiff matrix induces expression of pro-metastatic and neurotrophic genes through integrin ß1-FAK-YAP signals, which finally facilitates PNI in BRCA. Thus, our study provides a new mechanism for PNI in BRCA and highlights nerve-based tumor treatment strategies.

Fast and accurate object detector for autonomous driving based on improved YOLOv5.

Autonomous driving is an important branch of artificial intelligence, and real-time and accurate object detection is key to ensuring the safe and stable operation of autonomous vehicles. To this end, this paper proposes a fast and accurate object detector for autonomous driving based on improved YOLOv5. First, the YOLOv5 algorithm is improved by using structural re-parameterization (Rep), enhancing the accuracy and speed of the model through training-inference decoupling. Additionally, the neural architecture search method is introduced to cut redundant branches in the multi-branch re-parameterization module during the training phase, which ameliorates the training efficiency and accuracy. Finally, a small object detection layer is added to the network and the coordinate attention mechanism is added to all detection layers to improve the recognition rate of the model for small vehicles and pedestrians. The experimental results show that the detection accuracy of the proposed method on the KITTI dataset reaches 96.1%, and the FPS reaches 202, which is superior to many current mainstream algorithms and effectively improves the accuracy and real-time performance of unmanned driving object detection.

Atmospheric HONO formation during and after the Spring Festival holidays in a coastal city of China.

Nitrous acid (HONO) is an important source of hydrogen oxides (HOx), which affects air quality, the atmospheric oxidation capacity, and human health. Here, we present ambient measurements of the HONO concentrations in Zhuhai, a coastal city in Southern China, from February 7 to March 15, 2021. The campaign was classified into two periods during (P1) and after (P2) the Spring Festival holidays. The average HONO mixing ratio during P2 (1.19 ± 0.85 ppbv) was much higher than that during P1 (0.24 ± 0.18 ppbv), likely due to the contribution of homogeneous HONO formation. During nighttime, the heterogeneous conversion rate during P2 (0.0089/hr) was considerably higher than that during P1 (0.0057/hr), suggesting a higher heterogeneous NO2 conversion potential. However, the heterogeneous NO2 conversion was the dominant way during P1 with a high percentage of 88%, while comparable ratios of heterogeneous and homogeneous formation were found (54% vs. 46%) during P2, indicating that the homogeneous formation was also important during P2. During daytime, homogeneous reaction was the major known pathway, with a contribution of 16% during P1 and 27% during P2, leaving large unknown HONO sources which reasonably correlated with the photo-enhanced NO2 conversion. Two case scenarios were additionally explored, showing that there might be a primary emission source during one scenario (February 17-18) and vehicle emissions might be the major unknown HONO source for another scenario (March 3-5). The results suggest that large unknown daytime sources still exist which need more future ambient and laboratory studies.

Cruise observation of the marine atmosphere and ship emissions in South China Sea: Aerosol composition, sources, and the aging process.

Marine atmospheric aerosols impact the global climate and biogeochemical cycles. However, how the composition, sources, and aging of these aerosols affect the above processes has not been thoroughly studied. Here, we conducted ship-based measurements in the northern South China Sea to investigate the chemical composition and aging of aerosols from various sources during the summer of 2019. Separate measurements were conducted at the bow (marine environment) and stern (cooking, smoking, and engine exhaust) of the ship. Source apportionment of organic aerosols (OAs) was conducted using positive matrix factorization (PMF) and trajectory models. The results showed that ship exhaust and coastal submicron particles were composed of comparable sulfate and organic fractions (both approximately 43%), distinct from the sulfate-dominated particles in the marine atmosphere (52-77%). PMF using the multilinear engine-2 solver identified five factors for the stern sampling period: hydrocarbon-like OA (HOA-I, 9%), slightly oxidized HOA (HOA-II, 25%), cooking OA (COA, 13%), cigarette smoke OA (CSOA, 4%), and low-volatility oxygenated OA (LV-OOA, 49%). The primary OAs (HOA-I/II + COA + CSOA), derived mostly from direct ship-related emissions, contributed to approximately half of the OAs, whereas the contribution from the highly aged marine atmosphere was only 20%. Notably, certain living-related emissions (i.e., COA and CSOA), which were often neglected in previous studies, might represent a considerable contribution to OA emissions from the ship. Four factors were identified for the bow sampling periods: HOA (13%), biomass burning OA (BBOA, 9%), semi-volatile OOA (7%), and LV-OOA (71%). The BBOAs from the Indo-China and Malay peninsulas were aged, converted to secondary organic aerosols (SOAs) during transport, and influenced by the combined photo-oxidation and liquid-phase reactions, indicating a substantial impact of BB on SOA formation. Our study highlights the influence of ship and inland emissions and their aging during transport on marine atmospheric aerosols.

A simple and efficient method to quantify the cell parameters of the seed coat, embryo and silique wall in rapeseed.

BACKGROUND: Researchers interested in the seed size of rapeseed need to quantify the cell size and number of cells in the seed coat, embryo and silique wall. Scanning electron microscope-based methods have been demonstrated to be feasible but laborious and costly. After image preparation, the cell parameters are generally evaluated manually, which is time consuming and a major bottleneck for large-scale analysis. Recently, two machine learning-based algorithms, Trainable Weka Segmentation (TWS) and Cellpose, were released to overcome this long-standing problem. Moreover, the MorphoLibJ and LabelsToROIs plugins in Fiji provide user-friendly tools to deal with cell segmentation files. We attempted to verify the practicability and efficiency of these advanced tools for various types of cells in rapeseed. RESULTS: We simplified the current image preparation procedure by skipping the fixation step and demonstrated the feasibility of the simplified procedure. We developed three methods to automatically process multicellular images of various tissues in rapeseed. The TWS-Fiji (TF) method combines cell detection with TWS and cell measurement with Fiji, enabling the accurate quantification of seed coat cells. The Cellpose-Fiji (CF) method, based on cell segmentation with Cellpose and quantification with Fiji, achieves good performance but exhibits systematic error. By removing border labels with MorphoLibJ and detecting regions of interest (ROIs) with LabelsToROIs, the Cellpose-MorphoLibJ-LabelsToROIs (CML) method achieves human-level performance on bright-field images of seed coat cells. Intriguingly, the CML method needs very little manual calibration, a property that makes it suitable for massive-scale image processing. Through a large-scale quantitative evaluation of seed coat cells, we demonstrated the robustness and high efficiency of the CML method at both the single-cell level and the sample level. Furthermore, we extended the application of the CML method to developing seed coat, embryo and silique wall cells and acquired highly precise and reliable results, indicating the versatility of this method for use in multiple scenarios. CONCLUSIONS: The CML method is highly accurate and free of the need for manual correction. Hence, it can be applied for the low-cost, high-throughput quantification of diverse cell types in rapeseed with high efficiency. We envision that this method will facilitate the functional genomics and microphenomics studies of rapeseed and other crops.

Source apportionment of marine atmospheric aerosols in northern South China Sea during summertime 2018.

Marine atmospheric aerosols play important roles in the global radiation balance and climate change. Hence, measuring physiochemical aerosol properties is essential to better understand their formation, aging processes, and source origins. However, high temporal resolution measurements of submicron particles are currently scarce in the northern South China Sea (SCS). In this study, we conducted a ship-based cruise campaign with a scanning mobility particle sizer and an online time of flight aerosol chemical speciation monitor to measure the particle number size distribution (PNSD) and the chemical composition of submicron particles over the northern SCS during summer 2018. The mean concentration of non-refractory submicron particulate matter (NR-PM1) was generally 9.11 ± 4.86 µg m-3; sulfate was the most abundant component, followed by organics, ammonium, nitrate, and chloride. Positive matrix factorization (PMF) analysis was applied to the PNSD (size PMF) and organic aerosols (OA PMF) and further investigated the source apportionment of the submicron particles. The size PMF identified four factors, including ship exhaust, ship influencing marine primary, continent affected marine secondary, and mixed accumulation aerosols. The most abundant particles in the number concentration were associated with ship emissions, which accounted for approximately 44 %. The submicron organic aerosols were highly oxidized and composed of low-volatility oxygenated OA (LV-OOA, 68 %), semi-volatile OOA (SV-OOA, 21 %), and hydrocarbon-like OA (HOA, 11 %). The backward trajectory of air masses showed that the northern SCS was most frequently (64.7 %) influenced by air masses from the Indo-Chinese Peninsula (ICP) during the campaign, implying that pollutants from ICP have a significant impact on the atmosphere of the northern SCS during summer. Thus, in situ ship-based cruise measurements can provide valuable data on the physiochemical characteristics of marine atmospheric aerosols to better understand their source origins.