Dpp Signaling Determines Regional Stem Cell Identity in the Regenerating Adult Drosophila Gastrointestinal Tract

SummaryThe gastrointestinal tract is lined by a series of epithelia that share functional requirements but also have distinct, highly specialized roles. Distinct populations of somatic stem cells (SCs) regenerate these epithelia, yet the mechanisms that maintain regional identities of these SCs are not well understood. Here, we identify a role for the BMP-like Dpp signaling pathway in diversifying regenerative processes in the adult gastrointestinal tract of Drosophila. Dpp secreted from enterocytes at the boundary between the posterior midgut and the middle midgut (MM) sets up a morphogen gradient that selectively directs copper cell (CC) regeneration from gastric SCs in the MM and thus determines the size of the CC region. In vertebrates, deregulation of BMP signaling has been associated with Barrett’s metaplasia, wherein the squamous esophageal epithelium is replaced by a columnar epithelium, suggesting that the maintenance of regional SC identities by BMP is conserved

Capacitance Prediction Using Multi-cascade Convolutional Neural Network for Efficient Wireless Power Transfer

© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.1109/LAWP.2024.3390201The efficiency of the wireless power transfer is significantly impacted by misalignment between the transmitting and receiving coils due to impedance mismatching. To tackle this issue, an efficient power transfer solution is proposed, employing a capacitance prediction method based on a multi-cascade convolutional neural network. In the study, the impedance matching characteristic of a magnetic coupling resonant wireless power transfer system with an impedance matching network is analyzed. After that, a neural network-driven approach is introduced to establish a mapping between reflection impedance and the optimal capacitance, and the impedance matching performance of the system is assessed in the presence of coil misalignments.Peer reviewe

InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild

Understanding human interaction with objects is an important research topic for embodied Artificial Intelligence and identifying the objects that humans are interacting with is a primary problem for interaction understanding. Existing methods rely on frame-based detectors to locate interacting objects. However, this approach is subjected to heavy occlusions, background clutter, and distracting objects. To address the limitations, in this paper, we propose to leverage spatio-temporal information of hand-object interaction to track interactive objects under these challenging cases. Without prior knowledge of the general objects to be tracked like object tracking problems, we first utilize the spatial relation between hands and objects to adaptively discover the interacting objects from the scene. Second, the consistency and continuity of the appearance of objects between successive frames are exploited to track the objects. With this tracking formulation, our method also benefits from training on large-scale general object-tracking datasets. We further curate a video-level hand-object interaction dataset for testing and evaluation from 100DOH. The quantitative results demonstrate that our proposed method outperforms the state-of-the-art methods. Specifically, in scenes with continuous interaction with different objects, we achieve an impressive improvement of about 10% as evaluated using the Average Precision (AP) metric. Our qualitative findings also illustrate that our method can produce more continuous trajectories for interacting objects.Comment: IROS 202

Key pathways and genes controlling the development and progression of clear cell renal cell carcinoma (ccRCC) based on gene set enrichment analysis

BACKGROUND: Clear-cell renal cell carcinoma (ccRCC) is one of the most common types of kidney cancer in adults; however, its causes are not completely understood. The study was designed to filter the key pathways and genes associated with the occurrence or development of ccRCC, acquaint its pathogenesis at gene and pathway level, to provide more theory evidence and targeted therapy for ccRCC. METHODS: Gene set enrichment analysis (GSEA) and meta-analysis (Meta) were used to screen the critical pathways and genes which may affect the occurrence and progression of ccRCC on the transcription level. Corresponding pathways of significant genes were obtained with the online website DAVID (http://david.abcc.ncifcrf.gov/). RESULTS: Thirty seven consistent pathways and key genes in these pathways related to ccRCC were obtained with combined GSEA and meta-analysis. These pathways were mainly involved in metabolism, organismal systems, cellular processes and environmental information processing. CONCLUSION: The gene pathways that we identified could provide insight concerning the development of ccRCC. Further studies are needed to determine the biological function for the positive genes

Super-resolution reconstruction of digital rock CT images based on residual attention mechanism

Computer tomography technology is widely used in geological exploration because it is a nondestructive and three-dimensional imaging method that can be integrated with computer simulation. However, the large-scale application of the computer tomography technique is limited by economic costs and time consumption. Therefore, it is challenging and intractable to indicate the pore structure characteristics of rock. To address this issue, a super-resolution reconstruction algorithm based on convolutional neural networks, residual learning, and attention mechanism was proposed to generate super-resolution images in this study. This algorithm was applied to the reconstruction of carbonate rock and sandstone. The performance of two-dimensional image reconstruction was evaluated by quantitative extraction and qualitative visualization. The results from experiments indicate that the built model performs well on different upscaling factors and is superior to the existing super-resolution approaches based on convolutional neural network.Cited as: Shan, L., Bai, X., Liu, C., Feng, Y., Liu, Y., Qi, Y. Super-resolution reconstruction of digital rock CT images based on residual attention mechanism. Advances in Geo-Energy Research, 2022, 6(2): 157-168. https://doi.org/10.46690/ager.2022.02.0

Construction of 3D Arrays of Cylindrically Hierarchical Structures with ZnO Nanorods Hydrothermally Synthesized on Optical Fiber Cores

With ZnO nanorods hydrothermally synthesized on manually assembled arrays of optical fiber cores, 3D arrays of ZnO nanorod-based cylindrically hierarchical structures with nominal pitch 250 μm or 375 μm were constructed. Based on micrographs of scanning electron microscopy and image processing operators of MATLAB software, the 3D arrays of cylindrically hierarchical structures were quantitatively characterized. The values of the actual diameters, the actual pitches, and the parallelism errors suggest that the process capability of the manual assembling is sufficient and the quality of the 3D arrays of cylindrically hierarchical structures is acceptable. The values of the characteristic parameters such as roughness, skewness, kurtosis, correlation length, and power spectrum density show that the surface morphologies of the cylindrically hierarchical structures not only were affected significantly by Zn2+ concentration of the growth solution but also were anisotropic due to different curvature radii of the optical fiber core at side and front view

Multifactor dimensionality reduction analysis of syndrome characteristics of chronic persistent asthma

AbstractObjectiveTo analyze the syndrome characteristics in patients with chronic persistent asthma.Methods365 patients (121 males, 244 females, 60.8 ± 29.1 years old) with chronic persistent asthma were enrolled in this cross-sectional study. The information of syndrome, symptoms, signs, tongue coating and pulse were collected from all patients. The syndrome characteristics of chronic persistent asthma were examined through the multifactor dimensionality reduction (MDR) analysis and the results were verified by the Chi-square test.ResultsThe results of the MDR analysis and the Chi-square test showed the following positive correlation of the interaction among: the deficiency syndrome of the lung and spleen and deep pulse, disinclination to talk due to lack of qi, fatigue, lassitude and thick tongue coating; the deficiency syndrome of the lung and kidney and dizziness and disinclination to talk due to lack of qi, fatigue, lassitude and pallid complexion; the syndrome of phlegm-heat obstructing the lung and rapid pulse, abdominal distension, disinclination to talk due to lack of qi, frequent urination and lassitude; the syndrome of phlegm-dampness obstructing the lung and disinclination to talk due to lack of qi, greasy coating, fatigue and lassitude. (P < .05 for all).ConclusionThe syndrome of chronic persistent asthma is characterized by fatigue and lassitude due to dysfunction of the lung, spleen and kidney