The complex, branched morphology of dendrites is a cardinal feature of neurons and has been used as a criterion for cell type identification since the beginning of neurobiology. Regulated dendritic ...outgrowth and branching during development form the basis of receptive fields for neurons and are essential for the wiring of the nervous system. The cellular and molecular mechanisms of dendritic morphogenesis have been an intensely studied area. In this review, we summarize the major experimental systems that have contributed to our understandings of dendritic development as well as the intrinsic and extrinsic mechanisms that instruct the neurons to form cell type-specific dendritic arbors.
In recent years, supervised-deep-learning methods have shown some advantages over conventional methods in seismic data denoising, such as higher signal-to-noise ratio after denoising, complete ...separation of signals and noise in shared frequency bands and intelligent denoising without artificial parameter tuning. However, the lack of real noise data matched with raw seismic data has greatly limited its further application. In this paper, we take the surface seismic shot gather as an example to explore the corresponding solutions and propose a novel supervised-deep-learning method with weak dependence on real noise data based on the data augmentation of a generative adversarial network. We utilize the generative adversarial network to augment the pre-arrival noise data acquired from the shot gather itself, thereby obtaining a large amount of synthetic noise data whose probability distribution is extremely similar to that of the real noise in shot gather; the augmented synthetic noise data and sufficient synthetic signal data obtained by forward modeling together form the augmented training dataset. Meanwhile, the dilated convolution and gradual denoising strategy are adopted to construct the basic architecture of denoising convolution neural network. Finally, the above augmented dataset is used to train the network, so as to establish a nonlinear and complex mapping relationship between raw seismic data and desired signals. Both synthetic and real experiments demonstrate that our method can realize the intelligent denoising of different common-shot-point records in shot gather with the help of limited pre-arrival noise data.
Article Highlights
We introduce the data augmentation strategy into the field of deep-learning-based seismic denoising, thereby alleviating the dependence of supervised-deep-learning methods on real noise data
We propose a novel denoising network architecture with strong recovery ability for weak desired signals by using the gradual denoising strategy and dilated convolution
The augmented synthetic noise data can meet the requirement of supervised-deep-learning methods on the quantity and authenticity of training data, so this data augmentation strategy by using the Generative Adversarial Net (GAN) is a solution to the lack of real noise data
Itch is a unique sensory experience that is encoded by genetically distinguishable neurons both in the peripheral nervous system (PNS) and central nervous system (CNS) to elicit a characteristic ...behavioral response (scratching). Itch interacts with the other sensory modalities at multiple locations, from its initiation in a particular dermatome to its transmission to the brain where it is finally perceived. In this review, we summarize the current understanding of the molecular and neural mechanisms of itch by starting in the periphery, where itch is initiated, and discussing the circuits involved in itch processing in the CNS.
Dong and Dong summarize the current understanding of the molecular and neural mechanisms of itch. The authors first review the peripheral mediators that activate itch sensory neurons and then outline the circuits involved in itch processing in the CNS.
Quorum-sensing molecules (QSMs) are secreted by bacteria to signal population density. Upon reaching a critical concentration, QSMs induce transcriptional alterations in bacteria, which enable ...virulence factor expression and biofilm formation. It is unclear whether mammalian hosts can recognize QSMs to trigger responsive antibacterial immunity. We report that mouse mast-cell-specific G-protein-coupled receptor Mrgprb2 and its human homolog MRGPRX2 are receptors for Gram-positive QSMs, including competence-stimulating peptide (CSP)-1. CSP-1 activates Mrgprb2 and MRGPRX2, triggering mast cell degranulation, which inhibits bacterial growth and prevents biofilm formation. Such antibacterial functions are reduced in Mrgprb2-deficient mast cells, while wild-type mast cells fail to inhibit the growth of bacterial strains lacking CSP-1. Mrgprb2-knockout mice exhibit reduced bacterial clearance, while pharmacologically activating Mrgprb2 in vivo eliminates bacteria and improves disease score. These findings identify a host defense mechanism that uses QSMs as an “Achilles heel” and suggest MRGPRX2 as a potential therapeutic target for controlling bacterial infections.
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•The mammalian receptor Mrgprb2 and MRGPRX2 can detect bacterial QSMs•QSM detection by Mrgprb2 and MRGPRX2 in mast cells elicits antibacterial mediator release•Mrgprb2 recognition of QSMs is critical for an effective immune response to bacteria•Pharmacologic activation of Mrgprb2 and MRGPRX2 enhances bacterial clearance
Bacteria use quorum-sensing signaling for cross-species communication. Pundir et al. report that host mast cells detect Gram-positive-bacteria-derived quorum-sensing molecules via the Mrgpr receptors. Mrgpr activation triggers antibacterial activity and immune cell recruitment to efficiently clear bacteria, while animals deficient in Mrgpr are hypersusceptible to bacterial infection.
China's agricultural development has entered a period of transition, and improving the cultivated land use efficiency (CLUE) is of great significance for guaranteeing national food security. Based on ...the province panel data in China from 2000 to 2021, this research calculates the cultivated land use efficiency, and uses the Dagum-Gini coefficient, Kernel density estimation, and Markov chain to conduct an in-depth analysis of CLUE's regional variations and distribution dynamics in three food functional areas (TFA) of China. The study results showed that the trend of CLUE was characterized by “increasing levels and decreasing absolute differences,” not only in the whole country but also in the TFA. The inter-regional variation among TFA is gradually narrowing, and the cross-group degree of inter-regional variation is on the rise. The upward probability of CLUE was more effective than the probability of a transitionary change, and the mutual influence of CLUE between neighboring cities would lead to spatial convergence in the level of CLUE in the long term. Therefore, improving CLUE in China's TFA should not only grasp the regional differences in CLUE but also actively utilize the spatial spillover effects among functional regions to realize the cross-regional synergistic development of cropland utilization efficiency in China.
Ligand receptor interactions instruct axon guidance during development. How dendrites are guided to specific targets is less understood. The
PVD sensory neuron innervates muscle-skin interface with ...its elaborate dendritic branches. Here, we found that LECT-2, the ortholog of leukocyte cell-derived chemotaxin-2 (LECT2), is secreted from the muscles and required for muscle innervation by PVD. Mosaic analyses showed that LECT-2 acted locally to guide the growth of terminal branches. Ectopic expression of LECT-2 from seam cells is sufficient to redirect the PVD dendrites onto seam cells. LECT-2 functions in a multi-protein receptor-ligand complex that also contains two transmembrane ligands on the skin, SAX-7/L1CAM and MNR-1, and the neuronal transmembrane receptor DMA-1. LECT-2 greatly enhances the binding between SAX-7, MNR-1 and DMA-1. The activation of DMA-1 strictly requires all three ligands, which establishes a combinatorial code to precisely target and pattern dendritic arbors.
How to suppress the background noise and also recover signals is a widely-concerned and long standing problem in the field of seismic data processing. Effective seismic denoising methods can ...significantly enhance the quality of seismic data and its signal-to-noise ratio (SNR). Recently, deep-learning-based denoising methods have developed rapidly and achieved more remarkable results than traditional methods. To follow this promising trend and further reinforce the denoising performance, we propose a progressive denoising network (PDN) for land prestack seismic data and apply it to suppress the random noise and surface waves. This proposed PDN contains a feature extraction sub-network and a layer-by-layer denoising sub-network. With the cooperation of the two PDN achieves the layer-by-layer accurate separation of signals and noise according to the difference of low and high features extracted by applying continuous convolution operations. In addition, we utilize both synthetic and real seismic data to construct a rich training dataset with high authenticity and then adopt random-patch-based method to fed the network. The denoising result of synthetic example indicates the excellent attenuation performance of random noise by using PDN. In real example, PDN removes the random noise and surface waves from real land prestack seismic data simultaneously. Furthermore, compared with two existing deep-learning-based denoising methods, PDN has a stronger ability to recover weak reflections.
•Denoising the prestack seismic data by using deep-learning-based method.•Adopting some flexible label data can enhance the robustness of our network.•The proposed PDN can recover weak reflections almost without damaging signals.
Distributed optical fiber acoustic sensing (DAS) is a new and rapid-developing detection technology in seismic exploration. Unfortunately, due to the weak energy of scattered optical signals and the ...inferior coupling between DAS cable and receiving interface, the seismic data received by DAS are often characterized by low signal-to-noise ratio (SNR); this low SNR is likely to affect some subsequent analysis, such as inversion, imaging, and interpretation. In addition, the noise caused by the inferior coupling is a new kind of noise not presented on conventional seismic data. To enhance the SNR of DAS seismic data and suppress the DAS noise effectively, we propose a convolutional adversarial denoising network (CADN) based on the basic strategy of generative adversarial network (GAN) and the usage of a denoiser to replace the original generator in GAN. In CADN, the performance of denoiser is significantly strengthened via its own mean square error (MSE) loss and the adversarial loss between it and the discriminator. To balance the two losses and thus ensure the optimization of denoiser, we construct a novel loss function, where the optimal ratio of MSE and adversarial losses is determined by quantifying the denoising performance. Both real and synthetic examples are included to testify the denoising performance of CADN. Experimental results have demonstrated that CADN can suppress most of the DAS noise and enhance the SNR of DAS seismic data; also, it can recover the effective signals completely, even the extremely weak effective signals reflected by deep layers.
The construction of a large dendritic arbor requires robust growth and the precise delivery of membrane and protein cargoes to specific subcellular regions of the developing dendrite. How the ...microtubule-based vesicular trafficking and sorting systems are regulated to distribute these dendritic development factors throughout the dendrite is not well understood. Here we identify the small GTPase RAB-10 and the exocyst complex as critical regulators of dendrite morphogenesis and patterning in the C. elegans sensory neuron PVD. In rab-10 mutants, PVD dendritic branches are reduced in the posterior region of the cell but are excessive in the distal anterior region of the cell. We also demonstrate that the dendritic branch distribution within PVD depends on the balance between the molecular motors kinesin-1/UNC-116 and dynein, and we propose that RAB-10 regulates dendrite morphology by balancing the activity of these motors to appropriately distribute branching factors, including the transmembrane receptor DMA-1.
R-CDAs have been synthesized in a one-pot solvothermal procedure starting from 3,4-diaminobenzoic acid in an acidic medium. Transmission electron microscopy (TEM) revealed that R-CDAs nanoparticles ...exhibited a much larger diameter of 7.2–28.8 nm than traditional monodisperse carbon dots. X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FT-IR) revealed the presence of polar functional groups (hydroxyl, amino, carboxyl) on the surface of R-CDAs. Upon excitation with visible light (550 nm), R-CDAs emit stable, red fluorescence with a maximum at 610 nm. Under the optimum conditions, Cu
2+
ions quench the fluorescence of this probe, and the signal is linear in a concentration range of copper ions between 5 and 600 nM with the detection limit of only 0.4 nM. Recoveries from 98.0 to 105.0% and relative standard deviations (RSD) from 2.8 to 4.5% have been obtained for detection of Cu
2+
in real water samples. Furthermore, the R-CDAs fluorescent probe showed negligible cytotoxicity toward HeLa cells and good bioimaging ability, suggesting its potential applicability as a diagnostic tool in biomedicine.
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