Evaluation of the Anti-Atherosclerosis Effect of Shanhuaxiaozhi Formulation by Combination of Gc–Ms-Based Metabolomics and Tmt-Based Proteomics Technology

Recent research has highlighted the growing public health concern arising from mismanagement of malarial and non-malarial febrile illnesses that present with similar clinical symptoms. A retrospective examination of patient records suggests that a syndrome-based diagnosis results in over-diagnosis of malaria. Consequently, interventions to mitigate the frequency of presumptive treatment of fever in malaria-endemic settings have been sought, especially for resourcelimited areas. Guidelines that promote the use of microbiological tests and modern diagnostic kits have demonstrated laudable progress in the ongoing challenge of febrile illness management. However, this has brought attention to other factors like the complication of mixed infections. These issues, which remain significant limitations to current tools and methods in the accurate diagnosis and subsequent therapy of febrile illnesses, call for innovative diagnostic interventions. Advancements in biomedical research over the last decade have led to the introduction of state-of-the-art molecular techniques of omics origin that provide the possibility of diverse applications in disease diagnostics. Here, we present notable challenges in febrile illness management, describe currently available tools and methods for diagnosis, and discuss the opportunities for future progress, including harnessing cuttingedge transcriptional profiling and proteomics technology to detect host immunological signatures during infection.

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Top-down Proteomics: Technology Advancements and Applications to Heart Diseases

Expert Review of Proteomics ◽

10.1080/14789450.2016.1209414 ◽

2016 ◽

Vol 13 (8) ◽

pp. 717-730 ◽

Cited By ~ 56

Author(s):

Wenxuan Cai ◽

Trisha M. Tucholski ◽

Zachery R. Gregorich ◽

Ying Ge

Keyword(s):

Heart Diseases ◽

Top Down ◽

Proteomics Technology

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Identification of Multiple Metabolic Enzymes from Mice Cochleae Tissue Using a Novel Functional Proteomics Technology

PLoS ONE ◽

10.1371/journal.pone.0121826 ◽

2015 ◽

Vol 10 (3) ◽

pp. e0121826 ◽

Cited By ~ 4

Author(s):

David L. Wang ◽

Hui Li ◽

Ruqiang Liang ◽

Jianxin Bao

Keyword(s):

Metabolic Enzymes ◽

Functional Proteomics ◽

Proteomics Technology

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iTRAQ-Based Quantitative Proteomics Analysis of the Protective Effect of Yinchenwuling Powder on Hyperlipidemic Rats

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2017/3275096 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12

Author(s):

Zheyu Zhang ◽

Wenbo Wang ◽

Ling Jin ◽

Xin Cao ◽

Gonghui Jian ◽

...

Keyword(s):

Quantitative Proteomics ◽

Serum Levels ◽

Treated Group ◽

Research Approach ◽

Therapeutic Effects ◽

Proteomics Analysis ◽

Chinese Medicine Formula ◽

Calcitonin Gene ◽

Proteomics Technology ◽

Proteomics Research

Yinchenwuling powder (YCL) is an effective traditional Chinese medicine formula to modulate lipid levels. In this study, we established hyperlipidemic rat models and treated them with YCL. The serum concentrations of lipid, malondialdehyde (MDA), endothelin-1 (ET-1), and calcitonin gene-related peptide (CGRP) were measured. Adventitia-free vascular proteins between hyperlipidemic rats and YCL-treated rats were identified using iTRAQ-based quantitative proteomics research approach. Proteins with 1.3-fold difference were analyzed through bioinformatics, and proteomic results were verified by Western blot. The results showed that the serum levels of TC, TG, LDL-C, ET-1, and MDA were significantly decreased, whereas the HDL-C and CGRP levels were significantly increased in the YCL-treated group. Proteomics technology identified 4,382 proteins, and 15 proteins were selected on the basis of their expression levels and bioinformatics. Of these proteins, 2 (Adipoq and Gsta1) were upregulated and 13 (C3, C4, C6, Cfh, Cfp, C8g, C8b, Lgals1, Fndc1, Fgb, Fgg, Kng1, and ApoH) were downregulated in the YCL-treated rats. Their functions were related to immunity, inflammation, coagulation and hemostasis, oxidation and antioxidation, and lipid metabolism and transport. The validated results of ApoH were consistent with the proteomics results. This study enhanced our understanding on the therapeutic effects and mechanism of YCL on hyperlipidemia.

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Prediction of Peptide Detectability Based on CapsNet and Convolutional Block Attention Module

International Journal of Molecular Sciences ◽

10.3390/ijms222112080 ◽

2021 ◽

Vol 22 (21) ◽

pp. 12080

Author(s):

Minzhe Yu ◽

Yushuai Duan ◽

Zhong Li ◽

Yang Zhang

Keyword(s):

Feature Learning ◽

Peptide Identification ◽

Performance Assessments ◽

Network Training ◽

The Neural Network ◽

Proteomics Technology ◽

Experimental Process ◽

Quantitative Results ◽

Novel Method ◽

Peptide Detectability

According to proteomics technology, as impacted by the complexity of sampling in the experimental process, several problems remain with the reproducibility of mass spectrometry experiments, and the peptide identification and quantitative results continue to be random. Predicting the detectability exhibited by peptides can optimize the mentioned results to be more accurate, so such a prediction is of high research significance. This study builds a novel method to predict the detectability of peptides by complying with the capsule network (CapsNet) and the convolutional block attention module (CBAM). First, the residue conical coordinate (RCC), the amino acid composition (AAC), the dipeptide composition (DPC), and the sequence embedding code (SEC) are extracted as the peptide chain features. Subsequently, these features are divided into the biological feature and sequence feature, and separately inputted into the neural network of CapsNet. Moreover, the attention module CBAM is added to the network to assign weights to channels and spaces, as an attempt to enhance the feature learning and improve the network training effect. To verify the effectiveness of the proposed method, it is compared with some other popular methods. As revealed from the experimentally achieved results, the proposed method outperforms those methods in most performance assessments.

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