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1.
J Ginseng Res ; 47(2): 173-182, 2023 Mar.
Article in English | MEDLINE | ID: mdl-36926617

ABSTRACT

Cancer is a global public health issue that becomes the second primary cause of death globally. Considering the side effects of radio- or chemo-therapy, natural phytochemicals are promising alternatives for therapeutic interventions to alleviate the side effects and complications. Ginsenoside Rh2 (GRh2) is the main phytochemical extracted from Panax ginseng C.A. Meyer with anticancer activity. GRh2 could induce apoptosis and autophagy of cancer cells and inhibit proliferation, metastasis, invasion, and angiogenesis in vitro and in vivo. In addition, GRh2 could be used as an adjuvant to chemotherapeutics to enhance the anticancer effect and reverse the adverse effects. Here we summarized the understanding of the molecular mechanisms underlying the anticancer effects of GRh2 and proposed future directions to promote the development and application of GRh2.

2.
Int Immunopharmacol ; 101(Pt B): 108316, 2021 Dec.
Article in English | MEDLINE | ID: mdl-34768129

ABSTRACT

PURPOSE: Previously, we reported the octyl ester derivative of ginsenoside Rh2 (Rh2-O) had better antitumor and immunomodulatory effects than Rh2 in H22 tumor-bearing mice. Therefore, this study further explored the effects of Rh2-O on splenic lymphocytes in H22 tumor-bearing mice and the underlying mechanism. METHODS: Wild type and Tlr4-/- mice were selected to establish the H22 tumor-bearing mice model. After the treatment of Rh2-O (10 mg/kg by gavage) for 15 days, the sizes of tumor were measured. Subsequently, the splenic lymphocytes were isolated and the activities (eg. cell proliferation, cytotoxicity and cytokine secretion) were evaluated. Then, the proteins and mRNA expression levels of TRAF6 and NF-ĸB p65 in splenic lymphocytes were examined. RESULTS: The results showed that Rh2-O administration enhanced the proliferative capacity and cytotoxicity of splenic lymphocytes, and the effects were Tlr4-associated. Compared to WT mice, the up-regulation of cytokines secretion (eg. IFN-γ, IL-2 and IL-4) in isolated splenic lymphocytes after Rh2-O administration was lower in Tlr4-/- mice. Moreover, the results showed Rh2-O increased the expression of TRAF6 and the level of endonuclear NF-ĸB p65, which was inhibited in Tlr4-/- mice (P < 0.05). CONCLUSION: Rh2-O could exert immunomodulatory effects on splenic lymphocytes with the partial participation of TLR4 in H22 tumor-bearing mice.


Subject(s)
Ginsenosides/therapeutic use , Animals , Antineoplastic Agents, Phytogenic/pharmacology , Apoptosis/drug effects , Carcinoma, Hepatocellular/drug therapy , Cell Line, Tumor , Cell Proliferation/drug effects , Liver Neoplasms/drug therapy , Lymphocytes/pathology , Mice , Spleen/pathology , Toll-Like Receptor 4
3.
Proc Inst Mech Eng H ; 228(9): 952-61, 2014 Sep.
Article in English | MEDLINE | ID: mdl-25313026

ABSTRACT

The laryngeal video stroboscope is an important instrument to test glottal diseases and read vocal fold images and voice quality for physician clinical diagnosis. This study is aimed to develop a medical system with functionality of automatic intelligent recognition of dynamic images. The static images of glottis opening to the largest extent and closing to the smallest extent were screened automatically using color space transformation and image preprocessing. The glottal area was also quantized. As the tongue base movements affected the position of laryngoscope and saliva would result in unclear images, this study used the gray scale adaptive entropy value to set the threshold in order to establish an elimination system. The proposed system can improve the effect of automatically captured images of glottis and achieve an accuracy rate of 96%. In addition, the glottal area and area segmentation threshold were calculated effectively. The glottis area segmentation was corrected, and the glottal area waveform pattern was drawn automatically to assist in vocal fold diagnosis. When developing the intelligent recognition system for vocal fold disorders, this study analyzed the characteristic values of four vocal fold patterns, namely, normal vocal fold, vocal fold paralysis, vocal fold polyp, and vocal fold cyst. It also used the support vector machine classifier to identify vocal fold disorders and achieved an identification accuracy rate of 98.75%. The results can serve as a very valuable reference for diagnosis.


Subject(s)
Glottis/pathology , Image Processing, Computer-Assisted/methods , Laryngeal Diseases/pathology , Algorithms , Humans , Support Vector Machine , Video Recording
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