YOLOv8-segANDcal: segmentation, extraction, and calculation of soybean radicle features.

The high-throughput and full-time acquisition of images of crop growth processes, and the analysis of the morphological parameters of their features, is the foundation for achieving fast breeding technology, thereby accelerating the exploration of germplasm resources and variety selection by crop breeders. The evolution of embryonic soybean radicle characteristics during germination is an important indicator of soybean seed vitality, which directly affects the subsequent growth process and yield of soybeans. In order to address the time-consuming and labor-intensive manual measurement of embryonic radicle characteristics, as well as the issue of large errors, this paper utilizes continuous time-series crop growth vitality monitoring system to collect full-time sequence images of soybean germination. By introducing the attention mechanism SegNext_Attention, improving the Segment module, and adding the CAL module, a YOLOv8-segANDcal model for the segmentation and extraction of soybean embryonic radicle features and radicle length calculation was constructed. Compared to the YOLOv8-seg model, the model respectively improved the detection and segmentation of embryonic radicles by 2% and 1% in mAP50-95, and calculated the contour features and radicle length of the embryonic radicles, obtaining the morphological evolution of the embryonic radicle contour features over germination time. This model provides a rapid and accurate method for crop breeders and agronomists to select crop varieties.

An exploration of the influence of ZnO NPs treatment on germination of radish seeds under salt stress based on the YOLOv8-R lightweight model.

BACKGROUND: Since traditional germination test methods have drawbacks such as slow efficiency, proneness to error, and damage to seeds, a non-destructive testing method is proposed for full-process germination of radish seeds, which improves the monitoring efficiency of seed quality. RESULTS: Based on YOLOv8n, a lightweight test model YOLOv8-R is proposed, where the number of parameters, the amount of calculation, and size of weights are significantly reduced by replacing the backbone network with PP-LCNet, the neck part with CCFM, the C2f of the neck part with OREPA, the SPPF with FocalModulation, and the Detect of the head part with LADH. The ablation test and comparative test prove the performance of the model. With adoption of germination rate, germination index, and germination potential as the three vitality indicators, the seed germination phenotype collection system and YOLOv8-R model are used to analyze the full time-series sequence effects of different ZnO NPs concentrations on germination of radish seeds under varying degrees of salt stress. CONCLUSIONS: The results show that salt stress inhibits the germination of radish seeds and that the inhibition effect is more obvious with the increased concentration of NaCl solution; in cultivation with deionized water, the germination rate of radish seeds does not change significantly with increased concentration of ZnO NPs, but the germination index and germination potential increase initially and then decline; in cultivation with NaCl solution, the germination rate, germination potential and germination index of radish seeds first increase and then decline with increased concentration of ZnO NPs.

Comparative transcriptomic profiling reveals a role for Olig1 in promoting axon regeneration.

The regenerative potential of injured axons displays considerable heterogeneity. However, the molecular mechanisms underlying the heterogeneity have not been fully elucidated. Here, we establish a method that can separate spinal motor neurons (spMNs) with low and high regenerative capacities and identify a set of transcripts revealing differential expression between two groups of neurons. Interestingly, oligodendrocyte transcription factor 1 (Olig1), which regulates the differentiation of various neuronal progenitors, exhibits recurrent expression in spMNs with enhanced regenerative capabilities. Furthermore, overexpression of Olig1 (Olig1 OE) facilitates axonal regeneration in various models, and down-regulation or deletion of Olig1 exhibits an opposite effect. By analyzing the overlapped differentially expressed genes after expressing individual Olig factor and functional validation, we find that the role of Olig1 is at least partially through the neurite extension factor 1 (Nrsn1). We therefore identify Olig1 as an intrinsic factor that promotes regenerative capacity of injured axons.

YOLOv8-Peas: a lightweight drought tolerance method for peas based on seed germination vigor.

Introduction: Drought stress has become an important factor affecting global food production. Screening and breeding new varieties of peas (Pisum sativum L.) for drought-tolerant is of critical importance to ensure sustainable agricultural production and global food security. Germination rate and germination index are important indicators of seed germination vigor, and the level of germination vigor of pea seeds directly affects their yield and quality. The traditional manual germination detection can hardly meet the demand of full-time sequence nondestructive detection. We propose YOLOv8-Peas, an improved YOLOv8-n based method for the detection of pea germination vigor. Methods: We constructed a pea germination dataset and used multiple data augmentation methods to improve the robustness of the model in real-world scenarios. By introducing the C2f-Ghost structure and depth-separable convolution, the model computational complexity is reduced and the model size is compressed. In addition, the original detector head is replaced by the self-designed PDetect detector head, which significantly improves the computational efficiency of the model. The Coordinate Attention (CA) mechanism is added to the backbone network to enhance the model's ability to localize and extract features from critical regions. The neck used a lightweight Content-Aware ReAssembly of FEatures (CARAFE) upsampling operator to capture and retain detailed features at low levels. The Adam optimizer is used to improve the model's learning ability in complex parameter spaces, thus improving the model's detection performance. Results: The experimental results showed that the Params, FLOPs, and Weight Size of YOLOv8-Peas were 1.17M, 3.2G, and 2.7MB, respectively, which decreased by 61.2%, 61%, and 56.5% compared with the original YOLOv8-n. The mAP of YOLOv8-Peas was on par with that of YOLOv8-n, reaching 98.7%, and achieved a detection speed of 116.2FPS. We used PEG6000 to simulate different drought environments and YOLOv8-Peas to analyze and quantify the germination vigor of different genotypes of peas, and screened for the best drought-resistant pea varieties. Discussion: Our model effectively reduces deployment costs, improves detection efficiency, and provides a scientific theoretical basis for drought-resistant genotype screening in pea.

Intrathecal delivery of AAV-NDNF ameliorates disease progression of ALS mice.

Amyotrophic lateral sclerosis (ALS) is a uniformly lethal neurodegenerative disease characterized by progressive deterioration of motor neurons and neuromuscular denervation. Adeno-associated virus (AAV)-mediated delivery of trophic factors is being considered as a potential disease-modifying therapeutic avenue. Here we show a marked effect of AAV-mediated over-expression of neuron-derived neurotrophic factor (NDNF) on SOD1G93A ALS model mice. First, we adopt AAV-PHP.eB capsid to enable widespread expression of target proteins in the brain and spinal cord when delivered intrathecally. Then we tested the effects of AAV-NDNF on SOD1G93A mice at different stages of disease. Interestingly, AAV-NDNF markedly improved motor performance and alleviated weight loss when delivered at early post-symptomatic stage. Injection in the middle post-symptomatic stages still improved the locomotion ability, although it did not alleviate the loss of body weight. Injection in the late stage also extended the life span of SOD1G93A mice. Furthermore, NDNF expression promoted the survival of spinal motoneurons, reduced abnormal protein aggregation, and preserved the innervated neuromuscular functions. We further analyzed the signaling pathways of NDNF expression and found that it activates cell survival and growth-associated mammalian target of rapamycin signaling pathway and downregulates apoptosis-related pathways. Thus, intrathecally AAV-NDNF delivery has provided a potential strategy for the treatment of ALS.

Intrinsic heterogeneity in axon regeneration.

The nervous system is composed of a variety of neurons and glial cells with different morphology and functions. In the mammalian peripheral nervous system (PNS) or the lower vertebrate central nervous system (CNS), most neurons can regenerate extensively after axotomy, while the neurons in the mammalian CNS possess only limited regenerative ability. This heterogeneity is common within and across species. The studies about the transcriptomes after nerve injury in different animal models have revealed a series of molecular and cellular events that occurred in neurons after axotomy. However, responses of various types of neurons located in different positions of individuals were different remarkably. Thus, researchers aim to find the key factors that are conducive to regeneration, so as to provide the molecular basis for solving the regeneration difficulties after CNS injury. Here we review the heterogeneity of axonal regeneration among different cell subtypes in different animal models or the same organ, emphasizing the importance of comparative studies within and across species.

Evaluation of an intelligent artificial climate chamber for high-throughput crop phenotyping in wheat.

BACKGROUND: The superposition of COVID-19 and climate change has brought great challenges to global food security. As a major economic crop in the world, studying its phenotype to cultivate high-quality wheat varieties is an important way to increase grain yield. However, most of the existing phenotyping platforms have the disadvantages of high construction and maintenance costs, immobile and limited in use by climatic factors, while the traditional climate chambers lack phenotypic data acquisition, which makes crop phenotyping research and development difficult. Crop breeding progress is slow. At present, there is an urgent need to develop a low-cost, easy-to-promote, climate- and site-independent facility that combines the functions of crop cultivation and phenotype acquisition. We propose a movable cabin-type intelligent artificial climate chamber, and build an environmental control system, a crop phenotype monitoring system, and a crop phenotype acquisition system. RESULT: We selected two wheat varieties with different early vigor to carry out the cultivation experiments and phenotype acquisition of wheat under different nitrogen fertilizer application rates in an intelligent artificial climate chamber. With the help of the crop phenotype acquisition system, images of wheat at the trefoil stage, pre-tillering stage, late tillering stage and jointing stage were collected, and then the phenotypic information including wheat leaf area, plant height, and canopy temperature were extracted by the crop type acquisition system. We compared systematic and manual measurements of crop phenotypes for wheat phenotypes. The results of the analysis showed that the systematic measurements of leaf area, plant height and canopy temperature of wheat in four growth periods were highly correlated with the artificial measurements. The correlation coefficient (r) is positive, and the determination coefficient (R2) is greater than 0.7156. The root mean square error (RSME) is less than 2.42. Among them, the crop phenotype-based collection system has the smallest measurement error for the phenotypic characteristics of wheat trefoil stage. The canopy temperature RSME is only 0.261. The systematic measurement values of wheat phenotypic characteristics were significantly positively correlated with the artificial measurement values, the fitting degree was good, and the errors were all within the acceptable range. The experiment showed that the phenotypic data obtained with the intelligent artificial climate chamber has high accuracy. We verified the feasibility of wheat cultivation and phenotype acquisition based on intelligent artificial climate chamber. CONCLUSION: It is feasible to study wheat cultivation and canopy phenotype with the help of intelligent artificial climate chamber. Based on a variety of environmental monitoring sensors and environmental regulation equipment, the growth environment factors of crops can be adjusted. Based on high-precision mechanical transmission and multi-dimensional imaging sensors, crop images can be collected to extract crop phenotype information. Its use is not limited by environmental and climatic factors. Therefore, the intelligent artificial climate chamber is expected to be a powerful tool for breeders to develop excellent germplasm varieties.

Review on Microscale Sensors with 3D Engineered Structures: Fabrication and Applications.

The intelligence of modern technologies relies on perceptual systems based on microscale sensors. However, because of the traditional top-down fabrication approaches performed on planar silicon wafers, a large proportion of existing microscale sensors have 2D structures, which severely restricts their sensing capabilities. To overcome these restrictions, over the past few decades, increasing efforts have been devoted to developing new fabrication methods for microscale sensors with 3D engineered structures, from bulk chemical etching and 3D printing to molding and stress-induced assembly. Herein, the authors systematically review these fabrication methods based on the applications of the resulting 3D sensors and discuss their advantages compared to their 2D counterparts. This is followed by a perspective on the remaining challenges and possible opportunities.

WSVAS: A YOLOv4 -based phenotyping platform for automatically detecting the salt tolerance of wheat based on seed germination vigour.

Salt stress is one of the major environmental stress factors that affect and limit wheat production worldwide. Therefore, properly evaluating wheat genotypes during the germination stage could be one of the effective ways to improve yield. Currently, phenotypic identification platforms are widely used in the seed breeding process, which can improve the speed of detection compared with traditional methods. We developed the Wheat Seed Vigour Assessment System (WSVAS), which enables rapid and accurate detection of wheat seed germination using the lightweight convolutional neural network YOLOv4. The WSVAS system can automatically acquire, process and analyse image data of wheat varieties to evaluate the response of wheat seeds to salt stress under controlled environments. The WSVAS image acquisition system was set up to continuously acquire images of seeds of four wheat varieties under three types of salt stress. In this paper, we verified the accuracy of WSVAS by comparing manual scoring. The cumulative germination curves of wheat seeds of four genotypes under three salt stresses were also investigated. In this study, we compared three models, VGG16 + Faster R-CNN, ResNet50 + Faster R-CNN and YOLOv4. We found that YOLOv4 was the best model for wheat seed germination target detection, and the results showed that the model achieved an average detection accuracy (mAP) of 97.59%, a recall rate (Recall) of 97.35% and the detection speed was up to 6.82 FPS. This proved that the model could effectively detect the number of germinating seeds in wheat. In addition, the germination rate and germination index of the two indicators were highly correlated with germination vigour, indicating significant differences in salt tolerance amongst wheat varieties. WSVAS can quantify plant stress caused by salt stress and provides a powerful tool for salt-tolerant wheat breeding.

A method for obtaining field wheat freezing injury phenotype based on RGB camera and software control.

BACKGROUND: Low temperature freezing stress has adverse effects on wheat seedling growth and final yield. The traditional method to evaluate the wheat injury caused by the freezing stress is by visual observations, which is time-consuming and laborious. Therefore, a more efficient and accurate method for freezing damage identification is urgently needed. RESULTS: A high-throughput phenotyping system was developed in this paper, namely, RGB freezing injury system, to effectively and efficiently quantify the wheat freezing injury in the field environments. The system is able to automatically collect, processing, and analyze the wheat images collected using a mobile phenotype cabin in the field conditions. A data management system was also developed to store and manage the original images and the calculated phenotypic data in the system. In this experiment, a total of 128 wheat varieties were planted, three nitrogen concentrations were applied and two biological and technical replicates were performed. And wheat canopy images were collected at the seedling pulling stage and three image features were extracted for each wheat samples, including ExG, ExR and ExV. We compared different test parameters and found that the coverage had a greater impact on freezing injury. Therefore, we preliminarily divided four grades of freezing injury according to the test results to evaluate the freezing injury of different varieties of wheat at the seedling stage. CONCLUSIONS: The automatic phenotypic analysis method of freezing injury provides an alternative solution for high-throughput freezing damage analysis of field crops and it can be used to quantify freezing stress and has guiding significance for accelerating the selection of wheat excellent frost resistance genotypes.

Experimental Wear Behavior Analysis of Coated Spindle Hook Teeth under Real Harvesting Work Conditions.

This study aimed to investigate the wear failure changes of spindle hook teeth and the reasons for such failure during field work. Spindle samples were obtained from a fixed position of the spindle bar under different field picking area conditions and combined with the spatial distribution characteristics of cotton bolls in Xinjiang. After cutting a spindle sample, a scanning electron microscope and an energy spectrum analyzer were used to characterize the micromorphology and element composition of the hook tooth surface and cross section under different working area conditions. The wear parameters of the hook teeth were then extracted. The results showed that the thickness of the coating on the surface of the hook tooth used in this study was between 66.1 µm and 74.4 µm. The major chemical element was chromium, with a small amount of nickel. During the field picking process, failure of the coating on the surface of the hook teeth initially appeared on the tooth tip and tooth edge, and then spread to the entire hook tooth surface. The wear failure of the hook teeth resulted from abrasive wear, oxidative wear, and fatigue peeling. As the picking area increased, the wear area of the hook teeth increased exponentially, while the wear width increased linearly. When the field picking area reached 533.33 ha, the maximum change rate of the wear area was 2.33 × 103 µm2/ha, and the wear width was 1.84 µm/ha. During field work, the thickness of the coating decreased from the cutting surface to the tooth edge, and the wear rate gradually increased. The wear rate at Position 1 was the slowest, at 0.01 µm/ha, and the wear rate at Position 5 was the fastest, at 0.25 µm/ha.

Heterogeneous nuclear ribonucleoprotein A3 controls mitotic progression of neural progenitors via interaction with cohesin.

Cortex development is controlled by temporal patterning of neural progenitor (NP) competence with sequential generation of deep and superficial layer neurons, but underlying mechanisms remain elusive. Here, we report a role for heterogeneous nuclear ribonucleoprotein A3 (HNRNPA3) in regulating the division of early cortical NPs that mainly give rise to deep-layer neurons via direct neurogenesis. HNRNPA3 is expressed at high levels in NPs of mouse and human cortex at early stages, with a unique peri-chromosome pattern. Intriguingly, downregulation of HNRNPA3 caused chromosome disarrangement, which hindered normal separation of chromosomes during NP division, leading to mitotic delay. Furthermore, HNRNPA3 is associated with the cohesin-core subunit SMC1A and controls its association with chromosomes, implicating a mechanism for the role of HNRNPA3 in regulating chromosome segregation in dividing NPs. Hnrnpa3-deficient mice exhibited reduced cortical thickness, especially of deep layers. Moreover, downregulation of HNRNPA3 in cultured human cerebral organoids led to marked reduction in NPs and deep-layer neurons. Thus, this study has identified a crucial role for HNRNPA3 in NP division and highlighted the relationship between mitosis progression and early neurogenesis.

Measurement Method for Height-Independent Vegetation Indices Based on an Active Light Source.

A coefficient CW, which was defined as the ratio of NIR (near infrared) to the red reflected spectral response of the spectrometer, with a standard whiteboard as the measuring object, was introduced to establish a method for calculating height-independent vegetation indices (VIs). Two criteria for designing the spectrometer based on an active light source were proposed to keep CW constant. A designed spectrometer, which was equipped with an active light source, adopting 730 and 810 nm as the central wavelength of detection wavebands, was used to test the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) in wheat fields with two nitrogen application rate levels (NARLs). Twenty test points were selected in each kind of field. Five measuring heights (65, 75, 85, 95, and 105 cm) were set for each test point. The mean and standard deviation of the coefficient of variation (CV) for NDVI in each test point were 3.85% and 1.39% respectively, the corresponding results for RVI were 2.93% and 1.09%. ANOVA showed the measured VIs possessed a significant ability to discriminate the NARLs and had no obvious correlation with the measurement heights. The experimental results verified the feasibility and validity of the method for measuring height-independent VIs.

Tumor necrosis factor alpha mediates neuromuscular synapse elimination.

During the development of mammalian neuromuscular junction (NMJ), the original supernumerary axon inputs are gradually eliminated, finally leaving each muscle fiber innervated by a single axon terminal. However, the molecular cues that mediate the elimination of redundant axon inputs remain unclear. Here we show that tumor necrosis factor-α (TNFα) expressed in postsynaptic muscle cells plays an important role in presynaptic axonal elimination at the NMJ. We found that intramuscular injection of TNFα into the levator auris longus (LAL) muscles caused disassociation of presynaptic nerve terminals from the postsynaptic acetylcholine receptor (AChR) clusters. By contrast, genetic ablation of TNFα globally or specifically in skeletal muscle cells, but not in motoneurons or Schwann cells, delayed the synaptic elimination. Moreover, ablation of TNFα in muscle cells attenuated the tendency of activity-dependent competition in a motoneuron-muscle coculture system. These results suggest a role of postsynaptic TNFα in the elimination of redundant synaptic inputs.

Corrosion resistance of Ni-P/SiC and Ni-P composite coatings prepared by magnetic field-enhanced jet electrodeposition.

To extend the working life of 45# steel, Ni-P and Ni-P/SiC composite coatings were prepared on its surface by magnetic field-enhanced jet electrodeposition. This study investigated the effect of magnetic field on the corrosion resistance of Ni-P and Ni-P/SiC composite coatings prepared by conventional jet electrodeposition. The surface and cross-sectional morphologies, microstructure, and composition of the composite coatings were determined by scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), and X-ray diffraction (XRD), respectively. The corrosion resistance was studied using a LEXT4100 laser confocal microscope. The introduction of a stable magnetic field was found to improve the surface morphology of the coatings, increase the growth rate, and reduce the agglomeration of nano-SiC (3 g L-1, 40 nm) particles, thus significantly improving the corrosion resistance of the coatings. The corrosion potential of the Ni-P coating increased from -0.78 V (0 T) to -0.46 V (0.5 T), and the corrosion current density decreased from 9.56 × 10-6 A dm-2 (0 T) to 4.31 × 10-6 A dm-2 (0.5 T). The corrosion potential of the Ni-P/SiC coating increased from -0.59 V (0 T) to -0.28 V (0.5 T), and the corrosion current density decreased from 6.01 × 10-6 A dm-2 (0 T) to 2.90 × 10-6 A dm-2 (0.5 T).

Electrochemical Corrosion Behavior of Ni-Fe-Co-P Alloy Coating Containing Nano-CeO2 Particles in NaCl Solution.

In order to study the effect of nano-CeO2 particles doping on the electrochemical corrosion behavior of pure Ni-Fe-Co-P alloy coating, Ni-Fe-Co-P-CeO2 composite coating is prepared on the surface of 45 steel by scanning electrodeposition. The morphology, composition, and phase structure of the composite coating are analyzed by means of scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD). The corrosion behavior of the coatings with different concentrations of nano-CeO2 particles in 50 g/L NaCl solution is studied by Tafel polarization curve and electrochemical impedance spectroscopy. The corrosion mechanism is discussed. The experimental results show that the obtained Ni-Fe-Co-P-CeO2 composite coating is amorphous, and the addition of nano-CeO2 particles increases the mass fraction of P. With the increase of the concentration of nano-CeO2 particles in the plating solution, the surface flatness of the coating increases. The surface of Ni-Fe-Co-P-1 g/L CeO2 composite coating is uniform and dense, and its self-corrosion potential is the most positive; the corrosion current and corrosion rate are the smallest, and the charge transfer resistance is the largest, showing the best corrosion resistance.

Evaluating Geometric Measurement Accuracy Based on 3D Reconstruction of Automated Imagery in a Greenhouse.

Geometric dimensions of plants are significant parameters for showing plant dynamic responses to environmental variations. An image-based high-throughput phenotyping platform was developed to automatically measure geometric dimensions of plants in a greenhouse. The goal of this paper was to evaluate the accuracy in geometric measurement using the Structure from Motion (SfM) method from images acquired using the automated image-based platform. Images of nine artificial objects of different shapes were taken under 17 combinations of three different overlaps in x and y directions, respectively, and two different spatial resolutions (SRs) with three replicates. Dimensions in x, y and z of these objects were measured from 3D models reconstructed using the SfM method to evaluate the geometric accuracy. A metric power of unit (POU) was proposed to combine the effects of image overlap and SR. Results showed that measurement error of dimension in z is the least affected by overlap and SR among the three dimensions and measurement error of dimensions in x and y increased following a power function with the decrease of POU (R² = 0.78 and 0.88 for x and y respectively). POUs from 150 to 300 are a preferred range to obtain reasonable accuracy and efficiency for the developed image-based high-throughput phenotyping system. As a study case, the developed system was used to measure the height of 44 plants using an optimal POU in greenhouse environment. The results showed a good agreement (R² = 92% and Root Mean Square Error = 9.4 mm) between the manual and automated method.

Caspase-3 cleavage of dishevelled induces elimination of postsynaptic structures.

During the development of vertebrate neuromuscular junction (NMJ), agrin stabilizes, whereas acetylcholine (ACh) destabilizes AChR clusters, leading to the refinement of synaptic connections. The intracellular mechanism underlying this counteractive interaction remains elusive. Here, we show that caspase-3, the effector protease involved in apoptosis, mediates elimination of AChR clusters. We found that caspase-3 was activated by cholinergic stimulation of cultured muscle cells without inducing cell apoptosis and that this activation was prevented by agrin. Interestingly, inhibition of caspase-3 attenuated ACh agonist-induced dispersion of AChR clusters. Furthermore, we identified Dishevelled1 (Dvl1), a Wnt signaling protein involved in AChR clustering, as the substrate of caspase-3. Blocking Dvl1 cleavage prevented induced dispersion of AChR clusters. Finally, inhibition or genetic ablation of caspase-3 or expression of a caspase-3-resistant form of Dvl1 caused stabilization of aneural AChR clusters. Thus, caspase-3 plays an important role in the elimination of postsynaptic structures during the development of NMJs.

ProBDNF and mature BDNF as punishment and reward signals for synapse elimination at mouse neuromuscular junctions.

During development, mammalian neuromuscular junctions (NMJs) transit from multiple-innervation to single-innervation through axonal competition via unknown molecular mechanisms. Previously, using an in vitro model system, we demonstrated that the postsynaptic secretion of pro-brain-derived neurotrophic factor (proBDNF) stabilizes or eliminates presynaptic axon terminals, depending on its proteolytic conversion at synapses. Here, using developing mouse NMJs, we obtained in vivo evidence that proBDNF and mature BDNF (mBDNF) play roles in synapse elimination. We observed that exogenous proBDNF promoted synapse elimination, whereas mBDNF infusion substantially delayed synapse elimination. In addition, pharmacological inhibition of the proteolytic conversion of proBDNF to mBDNF accelerated synapse elimination via activation of p75 neurotrophin receptor (p75(NTR)). Furthermore, the inhibition of both p75(NTR) and sortilin signaling attenuated synapse elimination. We propose a model in which proBDNF and mBDNF serve as potential "punishment" and "reward" signals for inactive and active terminals, respectively, in vivo.

Lgl1 activation of rab10 promotes axonal membrane trafficking underlying neuronal polarization.

Directed membrane trafficking is believed to be crucial for axon development during neuronal morphogenesis. However, the underlying mechanisms are poorly understood. Here, we report a role of Lgl1, the mammalian homolog of Drosophila tumor suppressor Lethal giant larvae, in controlling membrane trafficking underlying axonal growth. We find that Lgl1 is associated with plasmalemmal precursor vesicles and enriched in developing axons. Lgl1 upregulation promoted axonal growth, whereas downregulation attenuated it as well as directional membrane insertion. Interestingly, Lgl1 interacted with and activated Rab10, a small GTPase that mediates membrane protein trafficking, by releasing GDP dissociation inhibitor (GDI) from Rab10. Furthermore, Rab10 lies downstream of Lgl1 in axon development and directional membrane insertion. Finally, both Lgl1 and Rab10 are required for neocortical neuronal polarization in vivo. Thus, the Lgl1 regulation of Rab10 stimulates the trafficking of membrane precursor vesicles, whose fusion with the plasmalemma is crucial for axonal growth.