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We have previously reported detailed structures of the mucosal nerve network in the rat ileum, but the mechanisms underlying the development of this nerve network remain unclear. Therefore, we aimed to clarify the developmental process of the mucosal nerve network and submucosal neurons (SM-neurons) or ganglia (SMG), which are the main source of nerve fibers projected to the mucosa, in the rat ileum during the postnatal period. Immunohistochemistry against tubulin beta III (Tuj1) revealed that Tuj1-immunopositivities were more abundant in the lamina propria at 2 weeks old (2wk; pre-weaning) than at postnatal day 0 (P0) or 4 weeks old (4wk; post-weaning) and more frequent on the mesenteric side than on the antimesenteric side at 2wk. Hu antigen D (HuD)-immunopositive SM-neurons and SMG were also more abundantly localized on the mesenteric side than the antimesenteric side at P0 and 2wk. On the other hand, cells immunopositive for SRY-related HMG-box 10 (Sox10), which is the marker for enteric nervous system progenitor cells and enteric glial cells, were homogenously scattered in the submucosa throughout the entire circumference at all ages. Glial cell marker S100 calcium-binding protein B (S100β) in the submucosa was detected at all ages without any significant difference between the mesenteric and antimesenteric sides. These findings indicate that SMG formation and associated neurite extension into the mucosa in the rat ileum might occur preferentially on the mesenteric side by the weaning period, leading us to hypothesize that the mechanism by which the mucosal nerve network and SMG develop differs along the mesenteric–antimesenteric side axis.

Deep foundation pit excavation not only faces complex hydro-geological and engineering geological conditions, but also meets many unknown engineering risks. Deep foundation pit excavation not only faces complex hydro-geological and engineering geological conditions, but also needs to make full use of BP nerve network. Based on this, this paper first analyzes the connotation and function of BP nerve network, then studies the simulation of deep foundation pit construction earthwork excavation, and finally gives the BP nerve network simulation and optimization method of deep foundation pit construction earthwork excavation.

Traditional data analysis methods and methods are difficult to effectively mine and analyze a large number of Rail Geometry state data, which makes the value of data cannot be fully utilized and played. Based on this, this paper first analyses the characteristics of railway track geometric irregularity, then studies the BP neural network prediction method and steps of railway track geometric irregularity, and gives its prediction effect.

Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. Setting out to \"reverse engineer\" the brain -- disassembling it to understand it -- Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of \"anticipatory regulation\"; identify constraints on neural design and the need to \"nanofy\"; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes \"save only what is needed.\"Sterling and Laughlin avoid speculation about how the brainmightwork and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.

Rapid detection and accurate mapping of landslides are crucial for damage detection and subsequent prevention of secondary damage. In this study, a deep learning-based segmentation model called CAM-K-SEG was proposed, which combined Grad-CAM visualization and K-Mean clustering methods to automatically detect landslide areas using satellite images. The methodology involved applying the CAM-K-SEG model to satellite images in the Bijou region of China and comparing its performance with that of K-Mean clustering and U-Net segmentation models. The optimum K value was determined by the elbow method to determine the effective color number. The weighted object was detected by removing small objects from the image, and the convolution process was performed with the mean Kernel method to remove noise or improve features. The performance of the CAM-K-SEG model was evaluated based on Intersection-Over-Union (IoU), the most used metric in semantic segmentation. The results demonstrated that the CAM-K-SEG model performed comparably to the U-Net model in segmenting landslide areas and could help improve the rapid detection of landslide areas after an event. Overall, the study contributed to the development of a new model for landslide image segmentation, which could more precisely and sensitively distinguish landslide regions. The CAM-K-SEG model was identified as a promising tool for automatic landslide detection and could be used in various applications that required accurate detection of landslide areas.

A wide variety of rudimentary and apparently non-functional traits have persisted over extended evolutionary time. Recent evidence has shown that some of these traits may be maintained as a result of developmental constraints or neutral energetic cost, but for others their true function was not recognized. The adipose fin is small, fleshy, non-rayed and located between the dorsal and caudal fins on eight orders of basal teleosts and has traditionally been regarded as vestigial without clear function. We describe here the ultrastructure of the adipose fin and for the first time, to our knowledge, present evidence of extensive nervous tissue, as well as an unusual subdermal complex of interconnected astrocyte-like cells equipped with primary cilia. The fin contains neither adipose tissue nor fin rays. Many fusiform actinotrichia, comprising dense striated macrofibrils, support the free edge and connect with collagen cables that link the two sides. These results are consistent with a recent hypothesis that the adipose fin may act as a precaudal flow sensor, where its removal can be detrimental to swimming efficiency in turbulent water. Our findings provide insight to the broader themes of function versus constraints in evolutionary biology and may have significance for fisheries science, as the adipose fin is routinely removed from millions of salmonids each year.

Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure. We investigated the evolution of small, adaptive logic-gate networks (\"animats\") in task environments where falling blocks of different sizes have to be caught or avoided in a 'Tetris-like' game. Solving these tasks requires the integration of sensor inputs and memory. Evolved networks were evaluated using measures of information integration, including the number of evolved concepts and the total amount of integrated conceptual information. The results show that, over the course of the animats' adaptation, i) the number of concepts grows; ii) integrated conceptual information increases; iii) this increase depends on the complexity of the environment, especially on the requirement for sequential memory. These results suggest that the need to capture the causal structure of a rich environment, given limited sensors and internal mechanisms, is an important driving force for organisms to develop highly integrated networks (\"brains\") with many concepts, leading to an increase in their internal complexity.

Modern clinical trials have produced controversial data interpretation which refutes conventional standard teachings and practices. Acupuncture scholars and practitioners have been stimulated to scrutinize these trials and analyze conventional practices. This paper presents two acupuncture models which address these issues. One rationalizes the clinical trial results with newer understanding of acupuncture points and techniques, while the other reconciles these results with rediscovered techniques of palpating points and performing needling. These two models indicate that acupuncture is in transition from classical model to evidence-based models.

Background: Myofascial trigger points (MTrPs) injection has been effectively used for the management of chronic painful diseases. Latent MTrPs can induce autonomic nerve phenomena. In our clinic, we observed that allergic rhinitis (AR) symptoms significantly improved when latent MTrPs injection was performed for migraine. Objective: To compare the efficacy and safety between latent MTrPs injection and sublingual immunotherapy (SLIT) in patients with persistent, moderate to severe AR. Methods: This randomized controlled trial was conducted with 112 patients with AR. Patients were randomized to receive SLIT ( n = 56) or latent MTrPs injection. Total nasal symptom score (TNSS, n = 56), nasal symptoms, medication days, and adverse events were evaluated during the 9 months follow-up period after treatment in both groups. Results: Latent MTrPs injection significantly reduced TNSS to a greater level from baseline (from 8.36 ± 1.96 to 4.43 ± 2.18) than SLIT (from 8.66 ± 2.31 to 7.80 ± 2.47) at week 1 ( P < 0.001), and sustained the improvement in symptoms throughout to month 9. Latent MTrPs showed statistically significant differences vs . SLIT for the TNSS reduction both at month 2 (6.59 ± 2.37 vs. 2.64 ± 2.38; p < 0.001) and month 3 (4.59 ± 2.77 vs. 2.62 ± 2.43; p <0.001). Latent MTrPs also showed a better improvement in the onset time of efficacy compared with SLIT. Adverse reactions were few and non-serious in both treatment groups. Conclusions: Latent MTrPs injection significantly improved symptoms and decreased symptom-relieving medication use in patients with AR and was well tolerated. Clinical Trials Registration: Chinese Clinical Trial Registry, ChiCTR1900020590. Registered 9 January 2019, http://www.chictr.org.cn/index.aspx .

Small inhibitory neuronal circuits have long been identified as key neuronal motifs to generate and modulate the coexisting rhythms of various motor functions. Our paper highlights the role of a cellular switching mechanism to orchestrate such circuits. The cellular switch makes the circuits reconfigurable, robust, adaptable, and externally controllable. Without this cellular mechanism, the circuit rhythms entirely rely on specific tunings of the synaptic connectivity, which makes them rigid, fragile, and difficult to control externally. We illustrate those properties on the much studied architecture of a small network controlling both the pyloric and gastric rhythms of crabs. The cellular switch is provided by a slow negative conductance often neglected in mathematical modeling of central pattern generators. We propose that this conductance is simple to model and key to computational studies of rhythmic circuit neuromodulation.