Induction of long-term synaptic potentiation (LTP) in excitatory neurons triggers a transient enlargement of dendritic spines followed by decay to sustained size expansion, a process termed ...structural LTP which contributes to the cellular basis of learning and memory. The activity-induced structural changes in dendritic spines involve spatiotemporal coordination of actin cytoskeleton reorganization, membrane trafficking and membrane remodeling. In this review, we discuss recent progresses in understanding the complex mechanisms underlying structural LTP, with an emphasis on the interplay between the spine plasma membrane and the actin cytoskeleton. We also highlight open questions and challenges to further understand this interesting cell neurobiological phenomenon.
•Dendritic spines undergo activity-dependent structural expansion termed sLTP.•sLTP is achieved by an interplay between the plasma membrane and the actin cytoskeleton.•Signaling via the ECM-plasma membrane–cytoskeleton interaction regulates sLTP.
In eukaryotic cells, organelles and the cytoskeleton undergo highly dynamic yet organized interactions capable of orchestrating complex cellular functions. Visualizing these interactions requires ...noninvasive, long-duration imaging of the intracellular environment at high spatiotemporal resolution and low background. To achieve these normally opposing goals, we developed grazing incidence structured illumination microscopy (GI-SIM) that is capable of imaging dynamic events near the basal cell cortex at 97-nm resolution and 266 frames/s over thousands of time points. We employed multi-color GI-SIM to characterize the fast dynamic interactions of diverse organelles and the cytoskeleton, shedding new light on the complex behaviors of these structures. Precise measurements of microtubule growth or shrinkage events helped distinguish among models of microtubule dynamic instability. Analysis of endoplasmic reticulum (ER) interactions with other organelles or microtubules uncovered new ER remodeling mechanisms, such as hitchhiking of the ER on motile organelles. Finally, ER-mitochondria contact sites were found to promote both mitochondrial fission and fusion.
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•Super-resolution live-cell imaging up to 266 fps at 97-nm resolution•Hitchhiking interactions among organelles remodel ER and mitochondrial networks•ER-mitochondrion contacts promote coalescence of mitochondrial membranes•Collision of late endosomes or lysosomes carried along microtubules split ER tubules
A new approach for visualizing dynamic processes within cells offers insight into membrane-membrane contact interactions and microtubule function.
Terrain features are an important basis for realizing high‐precision landform classification, and feature selection is a key step of machine learning and knowledge mining. However, the feature ...selection process is facing challenges due to the multidimensionality and correlation of multisource terrain feature datasets and factors. Traditional feature selection methods lack enough consideration for the interpretability and transparency of feature factors, but the transparent decision‐making process of feature selection precisely determines the modelling effect and the reliability of model application results. Current research urgently needs to work out the black holes of visual representation during feature selection. In the process of intelligent landform classification, multiple and effective terrain feature is an essential factor in enhancing the performance and generalisation ability of the network. Therefore, we initially selected 40 terrain feature parameters, including basic terrain factors and digital elevation model (DEM) terrain textures, to calculate the feature contribution degree and sort the parameter importance based on the SHapley Additive exPlanations (SHAP) method, then reserved 10%, 20%, 30%, 40% and 50% terrain features in turn for constructing the landform classification dataset. Because the traditional UNet network cannot completely capture abrupt landform features, the convolutional block attention module (CBAM) was integrated into the UNet, and a deep learning model was established for the fine‐grained classification of regional landforms. Considering the calculation rate, even though there are large regional spatial differences and genetic mechanisms, it is appropriate to retain 20% of terrain features for intelligent landform classification. The classification accuracy of typical regions, namely, the Hanzhong Basin, North China Plain, Yunnan–Guizhou Plateau and Tibetan Plateau, reached 98.76%, 97.36%, 96.3% and 92.78%, respectively, and what's more, some accuracies went up to a higher level under other feature combinations. Meanwhile, given the different feature combinations corresponding to regional landform types, the combinative stability and spatial orderliness characteristics were explored to explain the accuracy variation trend.
For the sake of realizing the intelligent landform classification in typical regions, a framework of deep learning network model is constructed, which reflects the complete process from extraction to selection to learning of terrain features, and obtains high classification accuracy in the complex landforms. It contributes to the utilisation of interpretable AI and also helps to understand the role of geographical attribute characteristics in geospatial AI modelling and decision‐making.
Cyclin-dependent kinase 5 (Cdk5) is an important serine/threonine kinase that plays critical roles in many physiological processes. Recently, Cdk5 has been reported to phosphorylate TRPV1 at ...threonine 407 (Thr-407) in humans (Thr-406 in rats), which enhances the function of TRPV1 channel and promotes thermal hyperalgesia in the complete Freund's adjuvant (CFA)-induced inflammatory pain rats. However, the underlying mechanisms are still unknown. Here, we demonstrate that Cdk5 phosphorylates TRPV1 at Threonine 406 and promotes the surface localization of TRPV1, leading to inflammatory thermal hyperalgesia. The mutation of Thr-406 of TRPV1 to alanine reduced the interaction of TRPV1 with the cytoskeletal elements and decreased the binding of TRPV1 with the motor protein KIF13B, which led to reduced surface distribution of TRPV1. Disrupting the phosphorylation of TRPV1 at Thr-406 dramatically reduced the surface level of TRPV1 in HEK 293 cells after transient expression and the channel function in cultured dorsal root ganglion (DRG) neurons. Notably, intrathecal administration of the interfering peptide against the phosphorylation of Thr-406 alleviated heat hyperalgesia and reduced the surface level of TRPV1 in inflammatory pain rats. Together, these results demonstrate that Cdk5-mediated phosphorylation of TRPV1 at Thr-406 increases the surface level and the function of TRPV1, while the TAT-T406 peptide can effectively attenuate thermal hyperalgesia. Our studies provide a potential therapy for inflammatory pain.
•Cdk5-mediated phosphorylation of TRPV1 at Thr-406 promotes the interaction between TRPV1 and cytoskeletal elements.•Cdk5-mediated phosphorylation of TRPV1 at Thr-406 increases the surface level and the function of TRPV1.•Intrathecal administration of a TAT peptide designed to inhibit phosphorylation of Thr-406 alleviated inflammatory heat hyperalgesia in rats
•Spatiotemporal differentiation characteristics of NPP in Shandong were presented.•NPP was predicted to experience a short-term decline in the near future.•The quantitative impact of NPP showed a ...pattern of “three zones and two lines”.
Exploring the spatiotemporal changes of vegetation net primary productivity (NPP) and its driving mechanism is crucial for green and low-carbon development. Based on the MOD17A3HGF data, this study introduced the gravity center model, wavelet analysis, coefficient of variation, Hurst index, correlation analysis, and Thornthwaite Memorial model to explore the spatiotemporal patterns of NPP and its driving factors in Shandong Province from 2000 to 2019. The following results were attained. (1) Between 2000 and 2019, Shandong’s yearly average NPP showed an upward trend. The first main cycle of the NPP’s interannual cycle lasted 14 years. NPP was predicted to experience a short-term decline in the near future. (2) In Shandong, the NPP displayed a geographical pattern with high values in the east and low values in the west, high values in the south and low values in the north, and progressively declining values from the coast to the interior. The growth rate and increment of NPP in 2000–2019 were the largest in the northeast direction in the Southwest Plain, while those in the Jiaodong Hills, the Central and Southern Mountains, and the Northwest Plain were the largest in the northwest direction. Hurst index analysis showed that NPP would show weak anti-continuity changes in the Central and Southern Mountains and the Jiaodong Hills in the future. (3) Shandong’s NPP exhibited a “three zones and two lines” pattern of the effect of climate change and human activities. This research offers a scientific theoretical foundation for environmental protection and carbon management.
pH-sensitive fluorescent proteins (FPs) are highly advantageous for the non-invasive monitoring of exocytosis events. Superecliptic pHluorin (SEP), a green pH-sensitive FP, has been widely used for ...imaging single-vesicle exocytosis. However, the docking step cannot be visualized using this FP, since the fluorescence signal inside vesicles is too low to be observed during docking process. Among the available red pH-sensitive FPs, none is comparable to SEP for practical applications due to unoptimized pH-sensitivity and fluorescence brightness or severe photochromic behavior. In this study, we engineer a bright and photostable red pH-sensitive FP, named pHmScarlet, which compared to other red FPs has higher pH sensitivity and enables the simultaneous detection of vesicle docking and fusion. pHmScarlet can also be combined with SEP for dual-color imaging of two individual secretory events. Furthermore, although the emission wavelength of pHmScarlet is red-shifted compared to that of SEP, its spatial resolution is high enough to show the ring structure of vesicle fusion pores using Hessian structured illumination microscopy (Hessian-SIM).
Due to the complex imaging mechanism of SAR images and the lack of multi-angle and multi-parameter real scene SAR target data, the generalization performance of existing deep-learning-based synthetic ...aperture radar (SAR) image target detection methods are extremely limited. In this paper, we propose an unsupervised domain-adaptive SAR ship detection method based on cross-domain feature interaction and data contribution balance. First, we designed a new cross-domain image generation module called CycleGAN-SCA to narrow the gap between the source domain and the target domain. Second, to alleviate the influence of complex backgrounds on ship detection, a new backbone using a self-attention mechanism to tap the potential of feature representation was designed. Furthermore, aiming at the problems of low resolution, few features and easy information loss of small ships, a new lightweight feature fusion and feature enhancement neck was designed. Finally, to balance the influence of different quality samples on the model, a simple and efficient E12IoU Loss was constructed. Experimental results based on a self-built large-scale optical-SAR cross-domain target detection dataset show that compared with existing cross-domain methods, our method achieved optimal performance, with the mAP reaching 68.54%. Furthermore, our method achieved a 6.27% improvement compared to the baseline, even with only 5% of the target domain labeled data.
Fludarabine (FA) is still considered as a first-line chemotherapy drug for hematological tumors related to B lymphocytes. However, it is worth noting that the non-specific distribution and ...non-different cytotoxicity of FA may lead to irreversible consequences such as central nervous system damage such as blindness, coma, and even death. Therefore, it is very important to develop a system to targeting delivery FA. In preliminary studies, it was found that B lymphoma cells would specific highly expressing the sialic acid-binding immunoglobulin-like lectin 2 (known as CD22). Inspired by the specific recognition of sialic acid residues and CD22, we have developed a supramolecular prodrug based on polysialic acid, an endogenous biomacromolecule, achieving targeted-therapy of B-cell non-Hodgkin's lymphoma (B-NHL). Specifically, the prepared hydrophobic reactive oxygen species-responsive FA dimeric prodrug (F.sub.2A) interacts with the TPSA, which polysialic acid were modified by the thymidine derivatives, through non-covalent intermolecular interactions similar to "Watson-Crick" base pairing, resulting in the formation of nanoscale supramolecular prodrug (F@TPSA). Cell experiments have confirmed that F@TPSA can be endocytosed by CD22.sup.+ B lymphoma cells including Raji and Ramos cells, and there is a significant difference of endocytosis in other leukocytes. Furthermore, in B-NHL mouse model, compared with FA, F@TPSA is determined to have a stronger tumor targeting and inhibitory effect. More importantly, the distribution of F@TPSA in vivo tends to be enriched in lymphoma tissue rather than nonspecific, thus reducing the leukopenia of FA. The targeted delivery system based on PSA provides a new prodrug modification strategy for targeted treatment of B-NHL.
The uncertainty verification of satellite ocean color products and the bias analysis of multiple data are both indispensable in the evaluation of ocean color products. Incidentally, ocean color ...products often have missing information that causes the methods mentioned above to be difficult to evaluate these data effectively. We propose an analysis and evaluation method based on data-free area. The objective of this study is to evaluate the quality of ocean color products with respect to information integrity and continuity. First, we use an improved Spectral Angle Mapper, also called ISAM. It can automatically obtain the optimal threshold value for each class of objects. Then, based on ISAM, we perform spectral information mining on first-level Yellow Sea and Bohai Sea data obtained from the Geostationary Ocean Color Imager (GOCI), Moderate Resolution Imaging Spectroradiometer (MODIS) and Ocean and Land Color Instrument (OLCI). In this manner, quantitative results of information related to data-free areas of ocean data products are obtained. The findings indicate that the product data of OLCI are optimal with respect to both completeness and continuity. GOCI and MODIS have striking similarities in their quantitative or visualization results for both evaluation metrics. Moreover, a concomitant phenomenon of ocean-covered objects is apparent in the data-free area with temporal and spatial distribution characteristics. The two characteristics are subsequently explored for further analysis. The evaluation method adopted in this study can help to enrich the content of ocean color product evaluation, facilitate the research of cloud detection algorithms and further understand the composition of the data-free regional information of marine data products. The method proposed in this study has a wide application value.
Satellite remote sensing provides an effective technical means for the precise extraction of information on aquacultural areas, which is of great significance in realizing the scientific supervision ...of the aquaculture industry. Existing optical remote sensing methods for the extraction of aquacultural area information mostly focus on the use of image spatial features and research on classification methods of single aquaculture patterns. Accordingly, the comprehensive utilization of a combination of spectral information and deep learning automatic recognition technology in the feature expression and discriminant extraction of aquaculture areas needs to be further explored. In this study, using Sentinel-2 remote sensing images, a method for the accurate extraction of different algae aquaculture zones combined with spectral information and deep learning technology was proposed for the characteristics of small samples, multidimensions, and complex water components in marine aquacultural areas. First, the feature expression ability of the aquaculture area target was enhanced through the calculation of the normalized difference aquaculture water index (NDAWI). Second, on this basis, the improved deep convolution generative adversarial network (DCGAN) algorithm was used to amplify the samples and create the NDAWI dataset. Finally, three semantic segmentation methods (UNet, DeepLabv3, and SegNet) were used to design models for classifying the algal aquaculture zones based on the sample amplified time series dataset and comprehensively compare the accuracy of the model classifications for achieving accurate extraction of different algal aquaculture information within the seawater aquaculture zones. The results show that the improved DCGAN amplification exhibited a better effect than the generative adversarial networks (GANs) and DCGAN under the indexes of structural similarity (SSIM) and peak signal-to-noise ratio (PSNR). The UNet classification model constructed on the basis of the improved DCGAN-amplified NDAWI dataset achieved better classification results (Lvshunkou: OA = 94.56%, kappa = 0.905; Jinzhou: OA = 94.68%, kappa = 0.913). The algorithmic model in this study provides a new method for the fine classification of marine aquaculture area information under small sample conditions.
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