Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease worldwide, characterized by progressive neuron degeneration or loss due to excessive accumulation of β-amyloid (Aβ) peptides, formation of neurofibrillary tangles (NFTs), and hyperphosphorylated tau. The treatment of AD has been only partially successful as the majority of the pharmacotherapies on the market may alleviate some of the symptoms. In the occurrence of AD, increasing attention has been paid to neurodegeneration, while the resident glial cells, like microglia are also observed. Microglia, a kind of crucial glial cells associated with the innate immune response, functions as double-edge sword role in CNS. They exert a beneficial or detrimental influence on the adjacent neurons through secretion of both pro-inflammatory cytokines as well as neurotrophic factors. In addition, their endocytosis of debris and toxic protein like Aβ and tau ensures homeostasis of the neuronal microenvironment. In this review, we will systematically summarize recent research regarding the roles of microglia in AD pathology and latest microglia-associated therapeutic targets mainly including pro-inflammatory genes, anti-inflammatory genes and phagocytosis at length, some of which are contradictory and controversial and warrant to further be investigated.

/pdf/microglia-in-the-neuroinflammatory-pathogenesis-of-3v3v5454.pdf

Microglia in the Neuroinflammatory Pathogenesis of Alzheimer’s Disease and Related Therapeutic Targets

A DAMP-scavenging, IL-10-releasing hydrogel promotes neural regeneration and motor function recovery after spinal cord injury.

Exosomes derived from bone marrow mesenchymal stem cells protect the injured spinal cord by inhibiting pericyte pyroptosis.

Traumatic brain injury (TBI) is one of the leading causes of morbidity and mortality. Consequences vary from mild cognitive impairment to death and, no matter the severity of subsequent sequelae, it represents a high burden for affected patients and for the health care system. Brain trauma can cause neuronal death through mechanical forces that disrupt cell architecture, and other secondary consequences through mechanisms such as inflammation, oxidative stress, programmed cell death, and, most importantly, excitotoxicity. This review aims to provide a comprehensive understanding of the many classical and novel pathways implicated in tissue damage following TBI. We summarize the preclinical evidence of potential therapeutic interventions and describe the available clinical evaluation of novel drug targets such as vitamin B12 and ifenprodil, among others.

/pdf/revisiting-excitotoxicity-in-traumatic-brain-injury-from-knpiy2jc.pdf

Revisiting Excitotoxicity in Traumatic Brain Injury: From Bench to Bedside

https://doi.org/10.1016/j.bioactmat.2022.03.040

ROS-responsive 18β-glycyrrhetic acid-conjugated polymeric nanoparticles mediate neuroprotection in ischemic stroke through HMGB1 inhibition and microglia polarization regulation

Spinal cord injury (SCI) favors a persistent pro-inflammatory macrophages/microglia-mediated response with only a transient appearance of anti-inflammatory phenotype of immune cells. However, the mechanisms controlling this special sterile inflammation after SCI are still not fully elucidated. It is known that damage-associated molecular patterns (DAMPs) released from necrotic cells after injury can trigger severe inflammation. High mobility group box 1(HMGB1), a ubiquitously expressed DNA binding protein, is an identified DAMP, and our previous study demonstrated that reactive astrocytes could undergo necroptosis and release HMGB1 after SCI in mice. The present study aimed to explore the effects and the possible mechanism of HMGB1on macrophages/microglia polarization, as well as the neuroprotective effects by HMGB1 inhibition after SCI. In this study, the expression and the concentration of HMGB1 was determined by qRT-PCR, ELISA, and immunohistochemistry. Glycyrrhizin was applied to inhibit HMGB1, while FPS-ZM1 to suppress receptor for advanced glycation end products (RAGE). The polarization of macrophages/microglia in vitro and in vivo was detected by qRT-PCR, immunostaining, and western blot. The lesion area was detected by GFAP staining, while neuronal survival was examined by Nissl staining. Luxol fast blue (LFB) staining, DAB staining, and western blot were adopted to evaluate the myelin loss. Basso-Beattie-Bresnahan (BBB) scoring and rump-height Index (RHI) assay was applied to evaluate locomotor functional recovery. Our data showed that HMGB1 can be elevated and released from necroptotic astrocytes and HMGB1 could induce pro-inflammatory microglia through the RAGE-nuclear factor-kappa B (NF-κB) pathway. We further demonstrated that inhibiting HMGB1 or RAGE effectively decreased the numbers of detrimental pro-inflammatory macrophages/microglia while increased anti-inflammatory cells after SCI. Furthermore, our data showed that inhibiting HMGB1 or RAGE significantly decreased neuronal loss and demyelination, and improved functional recovery after SCI. The data implicated that HMGB1-RAGE axis contributed to the dominant pro-inflammatory macrophages/microglia-mediated pro-inflammatory response, and inhibiting this pathway afforded neuroprotection for SCI. Thus, therapies designed to modulate immune microenvironment based on this cascade might be a prospective treatment for SCI.

/pdf/inhibiting-hmgb1-rage-axis-prevents-pro-inflammatory-46t9hhxwnh.pdf

Inhibiting HMGB1-RAGE axis prevents pro-inflammatory macrophages/microglia polarization and affords neuroprotection after spinal cord injury

Learning fusion feature representation for garbage image classification model in human–robot interaction

Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line system). Moreover, a new information extraction technique is extended by employing Synchrosqueezed Wavelet Transform (SSWT) to improve the accuracy of the MASD method. With the extended information extraction technique, the time-frequency information of the anomalies can be efficiently distinguished from the power frequency magnetic anomaly signal. The multi-component of the time-frequency information is separated by extracting the time-frequency ridges in the spectrogram. The complexity of time-frequency information is evaluated using Rayleigh entropy. Compared with the continuous wavelet transform and short-time Fourier transform, the Rayleigh entropy of our method is reduced by 4.1886 and 4.3623, respectively. Finally, the efficiency of the new method is verified by the outfield experiments.

/pdf/pfmd-a-power-frequency-magnetic-anomaly-signal-detection-qmj1com1.pdf

PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Construction tool detection is an important link in the operation and maintenance management of professional facilities in public works. Due to the large number and types of construction equipment and the complex and changeable construction environment, manual checking and inventory are still required. It is very challenging to count the variety of tools in a full-time environment automatically. To solve this problem, this paper aims to develop a full-time domain target detection system based on a deep learning network for difficult, complex railway environment image recognition. First, for the different time domain images, the image enhancement network with brightness channel decision is used to set different processing weights according to the images in different time domains to ensure the robustness of image enhancement in the entire time domain. Then, in view of the collected complex environment and the overlapping placement of the construction tools, a lightweight attention module is added on the basis of YOLOX, which makes the detection more purposeful, and the features cover more parts of the object to be recognized to improve the model. Overall detection performance. At the same time, the CIOU loss function is used to consider the distance fully, overlap rate, and penalty between the two detection frames, which is reflected in the final detection results, which can bring more stable target frame regression and further improve the recognition accuracy of the model. Experiments on the railway engineering dataset show that our RYOLO achieves a mAP of 77.26% for multiple tools and a count frame rate of 32.25FPS. Compared with YOLOX, mAP increased by 3.16%, especially the AP of woven bags with a high overlap rate increased from 0.15 to 0.57. Therefore, the target detection system proposed in this paper has better environmental adaptability and higher detection accuracy in complex railway environments, which is of great significance to the development of railway engineering intelligence.

/pdf/rapid-detection-of-tools-of-railway-works-in-the-full-time-2qa97xpt.pdf

Rapid Detection of Tools of Railway Works in the Full Time Domain

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Xia Li

Author Tools

Chat about Author

Papers

Inhibiting HMGB1-RAGE axis prevents pro-inflammatory macrophages/microglia polarization and affords neuroprotection after spinal cord injury

Learning fusion feature representation for garbage image classification model in human–robot interaction

PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Rapid Detection of Tools of Railway Works in the Full Time Domain