Publications by authors named "Yaxiong Chen"

Article Synopsis
  • Traditional disease detection in plants usually requires a lot of time and human effort, but this study introduces a deep hash convolutional neural network (DHCNN) to improve efficiency.
  • The DHCNN uses a collision-resistant hashing technique, allowing it to effectively identify similar disease features, achieving over 98.4% precision and true positive rate for single-plant disease detection.
  • For multi-plant scenarios, the method shows even better results, with a precision of 99.5%, a true positive rate of 99.6%, and an F-score of 99.58%, making it a robust solution for diverse plant disease retrieval.
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Vicinal dithiol proteins (VDPs) facilitate cellular redox homeostasis, modulate protein synthesis and participate in post-translational modifications through the dynamic equilibrium of dithiol and disulfide bonds. Herein, an activatable red emitting fluorescent probe, VDP-red, is developed for detecting VDPs. With the aid of this probe, we have discovered for the first time a reduction in the levels of reduced VDPs in a stroke mouse model.

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Background: Endometrial cancer (EC) poses a serious threat to women's health. Radiotherapy has been widely used for EC treatment. However, the mechanism of FIRRE in EC development and radioresistance remains unknown.

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The purpose of makeup transfer (MT) is to transfer makeup from a reference image to a target face while preserving the target's content. Existing methods have made remarkable progress in generating realistic results but do not perform well in terms of semantic correspondence and color fidelity. In addition, the straightforward extension of processing videos frame by frame tends to produce flickering results in most methods.

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Article Synopsis
  • Ionizing radiation from space, medical devices, or nuclear incidents poses significant health risks, highlighting the need for better countermeasures against radiation exposure.
  • Researchers identified a specific circulating microRNA (miR-342) in mouse serum that decreases after X-ray radiation exposure, suggesting its potential as a biomarker for radiation injuries.
  • By injecting synthetic miR-342 after radiation exposure, the study found that it helps protect immune cells, improves immune response, and enhances survival in mice suffering from acute radiation injuries, indicating its therapeutic promise.
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The minimally invasive biomarkers that can facilitate a rapid dose assessment are valuable for the early medical treatment when accidental or occupational radiation exposure happens. Our previous proteomic research identified one kind of circulating protein, Insulin-like Growth Factor Binding Protein 3 (IGFBP-3), which showed a significant increase after total body exposure of mice to carbon ions and X-rays. However, several critical issues such as the responses to diverse radiation, the origin and underlying mechanism in radiation response obstruct the utilization of circulating IGFBP-3 as a reliable radiation biomarker.

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For medical image retrieval task, deep hashing algorithms are widely applied in large-scale datasets for auxiliary diagnosis due to the retrieval efficiency advantage of hash codes. Most of which focus on features learning, whilst neglecting the discriminate area of medical images and hierarchical similarity for deep features and hash codes. In this paper, we tackle these dilemmas with a new Multi-scale Triplet Hashing (MTH) algorithm, which can leverage multi-scale information, convolutional self-attention and hierarchical similarity to learn effective hash codes simultaneously.

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Glutathione (GSH), the most prevalent nonprotein thiol in biological systems, acts as both an antioxidant to manipulate intracellular redox homeostasis and a nucleophile to detoxify xenobiotics. The fluctuation of GSH is closely related to the pathogenesis of diverse diseases. This work reports the construction of a nucleophilic aromatic substitution-type probe library based on the naphthalimide skeleton.

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Article Synopsis
  • Cardiac glycosides (CGs) are being studied as potential cancer treatments due to their diverse structures and strong biological effects.
  • In the research, fifteen CGs were isolated from a plant, with three being new discoveries, and their structures were analyzed through various advanced scientific methods.
  • The results showed that these CGs, particularly compound 1, had potent cytotoxic effects on cancer cell lines and interfered with the cell cycle, indicating potential for further development as cancer therapies.
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Inhibition of thioredoxin reductase (TrxR) is a crucial strategy for the discovery of antineoplastic drugs and radiosensitizers. As an anticancer candidate derived from Michelia, micheliolide (MCL) is converted readily from parthenolide (PTL), and has better stability and solubility than PTL. However, the anticancer mechanism of MCL has not been fully dissected.

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The effective and minimally invasive radiation biomarkers are valuable for exposure scenarios in nuclear accidents or space missions. Recent studies have opened the new sight of circulating small non-coding RNA (sncRNA) as radiation biomarkers. The tRNA-derived small RNA (tsRNA) is a new class of sncRNA.

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Thioredoxin reductase (TrxR) enzymes are critical in regulating redox homeostasis in cells. We report the first two-photon fluorescent probe of mammalian TrxR (TP-TRFS). TP-TRFS retains high specificity in recognizing TrxR.

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Rationale: Triple or more primary malignancies are rare, with only 23 previous cases including breast cancer reported in the English language studies between January 1990 and December 2019.

Patient Concerns: The patient was a 67-year-old woman with a mass in her right breast. She had a previous history of uterine and colon cancer.

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Purpose: Mitochondrial antiviral signaling (MAVS) protein, located in the mitochondrial out-membrane, is necessary for IFN-beta induction and IFN-stimulated gene expression in response to external stress such as viral invasion and ionizing radiation (IR). Although the involvement of radiation induced bystander effect (RIBE) has been investigated for decades for secondary cancer risk related to radiotherapy, the underlying regulatory mechanisms remain largely unclear, especially the roles played by the immune factors such as MAVS.

Material And Methods: MAVS gene knockout cells using CRISPR/Cas9 technology were used as donor cells or recipient cells to assess the role of MAVS in RIBE by means of co-cultured system.

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Although the mitochondrial antiviral signaling protein (MAVS), located in the mitochondrial outmembrane, is believed to be a signaling adaptor with antiviral feature firstly, it has been shown that suppression of MAVS enhanced radioresistance. The mechanisms underlying this radioresistance remain unclear. Our current study demonstrated that knockdown of MAVS alleviated the radiation-induced mitochondrial dysfunction (mitochondrial membrane potential disruption and ATP production), downregulated the expressions of proapoptotic proteins, and reduced the generation of ROS in cells after irradiation.

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The hashing technique has been extensively used in large-scale image retrieval applications due to its low storage and fast computing speed. Most existing deep hashing approaches cannot fully consider the global semantic similarity and category-level semantic information, which result in the insufficient utilization of the global semantic similarity for hash codes learning and the semantic information loss of hash codes. To tackle these issues, we propose a novel deep hashing approach with triplet labels, namely, deep category-level and regularized hashing (DCRH), to leverage the global semantic similarity of deep feature and category-level semantic information to enhance the semantic similarity of hash codes.

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For large-scale image retrieval, hashing has been extensively explored in approximate nearest neighbor search methods due to its low storage and high computational efficiency. With the development of deep learning, deep hashing methods have made great progress in image retrieval. Most existing deep hashing methods cannot fully consider the intra-group correlation of hash codes, which leads to the correlation decrease problem of similar hash codes and ultimately affects the retrieval results.

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For large-scale image retrieval task, a hashing technique has attracted extensive attention due to its efficient computing and applying. By using the hashing technique in image retrieval, it is crucial to generate discrete hash codes and preserve the neighborhood ranking information simultaneously. However, both related steps are treated independently in most of the existing deep hashing methods, which lead to the loss of key category-level information in the discretization process and the decrease in discriminative ranking relationship.

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A pair of enantiomeric polyketides, (+)- and (-)-alternamgin (1), featuring an unprecedented 6/6/6/6/5/6/6 seven ring backbone, were isolated from the endophytic fungi Alternaria sp. MG1. The relative configuration of 1 was determined using X-ray diffraction, and the absolute configurations of (±)-1 were confirmed by comparing the experimental and calculated ECD data.

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Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features.

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Seven cardenolides isolated from the ethanol extract of the stems of Calotropis gigantea were evaluated in vitro against human cancer cells and the structure-activity relationships were discussed. The results demonstrated that a compound, named CGN (coroglaucigenin), had better anti-proliferative activity with the IC50 value less than 6 μM among these compounds. Further, we found that CGN displayed much lower cytotoxicity to normal lung epithelial cells (BEAS-2B) than cancer cells (A549).

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Three dimensional (3D) culture in vitro is a new cell culture model that more closely mimics the physiology features of the in vivo environment and is being used widely in the field of medical and biological research. It has been demonstrated that cancer cells cultured in 3D matrices are more radioresistant compared with cells in monolayer (2D). However, the mechanisms causing this difference remain largely unclear.

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Radiation-induced genomic instability plays a vital role in carcinogenesis. Bod1 is required for proper chromosome biorientation, and Bod1 depletion increases premature chromatid separation. MiR-142-3p influences cell cycle progression and inhibits proliferation and invasion in cervical carcinoma cells.

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In vitro 3D growth of tumors is a new cell culture model that more closely mimics the features of the in vivo environment and is being used increasingly in the field of biological and medical research. It has been demonstrated that cancer cells cultured in 3D matrices are more radio-resistant compared with cells in monolayers. However, the mechanisms causing this difference remain unclear.

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It is believed that epigenetic modification plays roles in cancer initiation and progression. Both microRNA and DNA methyltransferase are epigenetic regulation factors. It was found that miR-145 upregulates while DNMT3b downregulates in PC3 cells.

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