Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
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We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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1. Introduction
Ivermectin is chemically derived from avermectin that was discovered and isolated from soil in Jan by Omura in 1973 [1]. It was approved by Federal Drug Administration (FDA) to use for anti-parasite drug in 1987, which has significantly improved global public health as an antiparasite medicine [2]. In 2015, its discovers Drs. Omura and Campbell earned the Nobel Prize in physiology or medicine [2]. Recent years, many studies have demonstrated that ivermectin has extensive roles in anti-bacteria, anti-virus, and anticancer, except for its anti-parasite effects [3, 4, 5]. Its anticancer effect has been shown by many in vitro and in vivo experiments in multiple cancers, including ovarian cancer, breast cancer, triple-negative breast cancer, cervical cancer, lung cancer, gastric cancer, colon cancer, glioblastoma, melanoma, and leukemia [4, 6], with a wide safe and clinically reachable drug concentration of anticancer according to its pharmacokinetic range in treatment of a parasite-infected patient [7]. It offers a promising opportunity to develop a new anticancer drug via drug repositioning of this existing compound with confirmed clinical safety [8].
Ovarian cancer, a very common cancer with high mortality and poor survival in women [9, 10], are involved in multiple signaling pathway network changes [11, 12]. Many intracellular molecules and signaling pathways would be the targets of ivermectin [13]. Ivermectin have shown a potential addition role for ovarian cancer treatment. For example, ivermectin can improve the chemosensitivity of overran cancer via targeting Akt/mTOR signaling pathway [14], and can inhibit PAK1-dependent growth of ovarian cancer cells via blocking the oncogenic kinase PAK1 [15]. Ivermectin also acts as a PAK1 inhibitor to induce autophagy in breast cancer [16]. Ivermectin can enhance p53 expression and cytochrome C release, and reduce the expression levels of CDK2, CDK4, CDK6, Bcl-2, cyclin E, and cyclin D1 in glioblastoma, those promoted the cancer cell apoptosis [17]. Ivermectin can inhibit cancer cell proliferation via decreasing YAP1 protein expression in the Hippo pathway [18]. Ivermectin represses WNT-TCF pathway in WNT-TCF-dependent disease [19]. Ivermectin can promote TFE3 (Ser321) dephosphorylation to block the binding between TFE3 and 14-3-3, and induce TFE3 accumulation in the nucleus of human melanoma cells [20]. Moreover, ivermectin also affects other signaling pathway network in human cancers, including oxidative stress, mitochondrial dysfunction, angiogenesis, epithelial-mesenchymal transition, drug resistance, and stemness in tumor [6]. Thereby, ivermectin demonstrates the potential therapeutic efficiency in multiple malignant tumors.
This book chapter discussed the anti-cancer effects of ivermectin on ovarian cancer in the following aspects: (i) ivermectin inhibited cell proliferation and growth, blocked cell cycle progression, and promoted cell apoptosis in ovarian cancer [4, 21]; (ii) ivermectin inhibited ovarian cancer growth through molecular networks to target the key molecules in energy metabolism pathways, including glycolysis, Kreb’s cycle, oxidative phosphorylation, and lactate shuttle pathways [21]; (iii) Integrated omics revealed that ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer capability [4, 13]; and (iv) lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565) that is significantly related to overall survival and clinicopathologic characteristics of ovarian cancers [4].
2. Methods
2.1 Ovarian cancer cell biological behaviors affected by ivermectin
The normal ovarian cells IOSE80 and ovarian cancer cells TOV-21 and SKOV3 were treated with ivermectin to measure ivermectin-mediated ovarian cancer cell biological behavior changes. (i) IOSE80, TOV-21G, and SKOV3 were treated with ivermectin (0–60 μM) for 24 h, followed by the use of CCK8 to measure the IC50 of ivermectin in each cell. (ii) TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, followed by the use of EdU assay to measure DNA synthesis in each cell. (iii) TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 48 h, followed by clonogenic assay to measure the in vitro effects of ivermectin in each cell. (iv)TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, followed by flow cytometry to measure cell cycle and cell apoptosis changes in each cell. (v) When A2780 and TOV-21G seeded in 6-well plates were grown to approximately 90% confluency, followed by the use of 10-μl pipette tip to make an artificial wound, and then treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, and measure the wound healing. The relative percentage of wound healing = (the width of wound at 0 h − the width of wound at 24 h)/the width of wound at 0 h. The detailed procedure was described previously [4, 21].
2.2 Ivermectin-mediated pathway network predicted by ingenuity pathway analysis
The classical pathway network analysis software, Ingenuity Pathway Analysis (IPA) (http://www.ingenuity.com) [5] was used to predict ivermectin-related potential target molecules in three energy metabolism pathways. For this analysis, ivermectin and target genes in three energy metabolism pathways are all input into the IPA tool. The detailed procedure was described previously [21]. The predicted ivermectin-mediated targets in energy metabolism pathways were the basis for further experiment verification.
2.3 Ivermectin-mediated target molecule changes in energy metabolism pathways verified at the mRNA and protein levels
TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, and 48 h. At the 24 h time point, the RNAs were extracted for quantitative real-time PCR (qRT-PCR) analysis to measure the mRNA expression of target molecules (CS, PDHB, IDH2, IDH3A, IDH3B, PFKP, PKM, MCT1, MCT4, OGDHL, ND2, ND5, CYTB, and UQCRH) in energy metabolism pathways. At the 48 h time point, the proteins were extracted for Western blot analysis to measure the protein expression of target molecules (CS, PDHB, IDH2, IDH3A, IDH3B, PFKP, PKM, MCT1, MCT4, OGDHL, ND2, ND5, CYTB, and UQCRH) in energy metabolism pathways. The detailed procedure was described previously [21].
2.4 Ivermectin-mediated proteome changes in ovarian cancer identified by SILAC-based quantitative proteomics
SILAC (stable isotope labeling with amino acids in cell culture)-based quantitative proteomics was used to identified differentially expressed proteins in ovarian cancer TOV-21G treated with and without 20 μM ivermectin [13]. The identified differentially expressed proteins were used for molecular network and signaling pathway analyses to obtain ivermectin-related signaling pathway networks [13]. The detailed procedure was described previously [13].
2.5 Transcriptomics and clinical data of ovarian cancer patients extracted from TCGA database
Level 3 RNA-seq V2 transcriptomics data of 411 OC patients were extracted from The Cancer Genome Atlas (TCGA) data portal (http://cancergenome.nih.gov/) with the corresponding clinical data, including cancer status (with tumor or tumor-free), clinical stage (stages IIA, IIB, IIC, IIIA, IIIB, IIIC, and IV), neoplasm histologic grade (G1, G2, G3, G4, and GX), anatomic neoplasm subdivision (right, left, and bilateral), age at initial pathologic diagnosis (aged from 30 to 87), lymphatic invasion (yes/no), primary therapy outcome success (complete remission/response, partial remission/response, progressive disease, and stable disease), additional radiation therapy (yes/no), survival time (days), tumor residual disease (no macroscopic disease, 1–10 mm, 11–20 mm, and > 20 mm), survival status (0 = alive, and 1 = dead), and PANCAN (Pan-Cancer Atlas). TANRIC (http://ibl.mdanderson.org/tanric/design/basic/index.html) was used for survival analysis of lncRNAs in ovarian cancer. The large-scale CLIP-Seq data with starBasev 2.0 (http://starbase.sysu.edu.cn/mirCircRNA.php) was used to predict the EIF4A3-binding mRNAs. The Kaplan–Meier method relative to the log-rank test was used for survival analysis of mRNAs in ovarian cancers. Statistical significance was set as p value <0.05. GenCLiP 3 (http://ci.smu.edu.cn/genclip3/analysis.php) was used for pathway enrichment analysis of the association of EIF4A3-binding mRNAs and patient survival rates. The detailed procedure was described previously [4].
2.6 Ivermectin-related lncRNAs verified with qRT-PCR
TRizol® Reagent (Invitrogen, CA, USA) was used to extract total RNAs of cells TOV21G and A2780 treated with different concentration of ivermectin (0 μM, 10 μM, 20 μM, and 30 μM). The extracted total RNAs was reversely transcribed into cDNAs for qRT-PCR analysis of each lncRNA expression, including KIF9-AS1, HCG15, PDCD4-AS1, ZNRF3-AS1, ZNF674-AS1, LINC00565, SOS1-IT1, WWTR1-AS1, PLCH1-AS1, LINC00517, SNHG3, STARD13-IT1, AL109767.1, HOXC-AS3, LEMD1-AS1, and LBX2-AS1. Beta-actin was set as internal control for qRT-PCR analysis. The detailed procedure was described previously [4].
2.7 LncRNA-based prognostic signature optimized with lasso regression for ovarian cancers
Lasso regression means least absolute shrinkage and selection operator regression, which was used to optimize and construct lncRNA-based prognostic signature, and the glmnet R package was used to measure the association between survival risk and lncRNA signature in ovarian cancers. Moreover, univariate and multivariate Cox regression, and Kaplan–Meier method were used to identify overall survival-related clinical characteristics described above in ovarian cancers to confirm the established lncRNA-based prognostic model. The detailed procedure was described previously [4].
2.8 Statistical significance
Benjamini–Hochberg (FDR) for multiple testing was used to correct the p values of IPA, GO, and KEGG analyses. Student’s t test was used for qRT-PCR and western blot data (p < 0.05) with data expression of mean ± SD (n = 3).
3. Results and discussion
3.1 Effects of ivermectin on biological behaviors of ovarian cancers
First, CCK8 experiments were used to measure cell proliferation changes between ovarian cancer cells (SKOV3; TOV-21G) and control cells (IOSE80), treated with and without ivermectin (Figure 1). Each type of cells was significantly inhibited by ivermectin with a dose-dependent relationship. The IC50 (half maximal inhibitory concentration) was 29.46 μM for IOSE80 cells, 20.85 μM for SKOV3, and 22.54 μM for TOV-21G (Figure 1A). The IC50 of ovarian cancers were significantly lower than the normal controls. Further, 20 μM ivermectin - slightly lower than IC50 – can effectively inhibit ovarian cancer proliferation (Figure 1B and C) [21]. For in vivo human trial, the highest FDA-approved ivermectin dose was 200 μg/kg for human use in anti-parasite; however, a study on 68 human subjects found that the dose up to 2,000 μg/kg still worked well without CNS toxicity. The mean area under the curve ratios for the 30 and 60 mg doses were 1.24 and 1.40, indicating a minimal accumulation of ivermectin [5, 22]. These data demonstrate that ivermectin was a well-tolerated safe drug. Second, EdU cell proliferation experiments also confirmed that ivermectin significantly suppressed cell proliferation of ovarian cancers with a time-dependent relationship (Figure 1D-F) [21]. Third, Clonogenic survival experiments confirmed that ivermectin effectively inhibited the formation of cell clones with a time-dependent relationship (Figure 1G-H) [21]. Moreover, 10 μM ivermectin cannot effectively inhibit cell proliferation of ovarian cancers, 30 μM ivermectin caused cell death of ovarian cancers, and 20 μM ivermectin was a suitable dose to significantly suppress growth and proliferation of ovarian cancer cells.
Figure 1.
Ivermectin suppressed ovarian cancer cell proliferation in vitro, measured with CCK8 (A-C), EdU (D-F), and clonogenic experiments (G, H). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.2 Effects of ivermectin on cell cycle and apoptosis in ovarian cancers
Flow cytometry was used to measure cell cycle and apoptosis of ovarian cancer cells treated with and without ivermectin (Figure 2) [21]. First, the cell proportion was significantly increased in G0/G phase, decreased in S phase, and no change in G2/M phase in the high concentration (20- and 30-μM) compared to the low concentration (0- and 10-μM) of ivermectin groups (Figure 2A-C). Second, compared to control group, the proportion of apoptosis cells was significantly increased in different concentration of ivermectin groups, with a dose-dependent relationship (Figure 2D and E).
Figure 2.
Ivermectin blocked cell cycle progression (A, B, C) and promoted cell apoptosis (D, E) of ovarian cancer cells. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.3 Effect of ivermectin on cell migration in ovarian cancers
Wound healing experiment was used to test the effect of ivermectin on cell migration of ovarian cancer cells. The results showed that cell migration was significantly inhibited in cells A2780 and TOV-21G after treatment of 20 μM and 30 μM ivermectin (Figure 3) [4].
Figure 3.
Ivermectin inhibited cell migration of ovarian cancer cells TOV-21G relative to control cells A2780, analyzed with wound healing experiments. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
3.4 Pharmaceutic molecular network predicted the association of ivermectin with ROS and energy metabolism
Ingenuity Pathway Analysis (IPA) was used for pharmaceutic molecular network analysis of ivermectin. The results showed that ivermectin was significantly associated with reactive oxygen species (ROS) and energy metabolism pathways, including pyruvate kinase muscle (PKM), oxoglutarate dehydrogenase L (OGDHL), mitochondrially encoded NADH dehydrogenase 2 (ND2), mitochondrially encoded NADH dehydrogenase 5 (ND5), CytB, and ubiquinolcytochrome c reductase hinge protein (UQCRH) (Figure 4) [21]. Moreover, ivermectin directly regulated Rbp, CYP3A4, P2RX7, ABCB1, GLRB, ABCG2, P2RX4, P glycoprotein, Abcb1b, strychnine, cytokine, and insulin; and indirectly regulated TNF, APP, MAPK1, ERK1/2, MAPK3, MAPK13, ROS, NFKBIA, testosterone, and STAT3 [21].
Figure 4.
Pharmaceutic molecular network predicted the associations of ivermectin with reactive oxygen species (ROS) and energy metabolism pathways (A) Disease and functional analysis of ivermectin based on IPA database (B-G). The association of ivermectin with PKM (B), OGDHL (C), ND2 (D), UQCRH (E), ND5 (F), and CYTB (G). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.5 SILAC quantitative proteomics revealed the effects of ivermectin on key proteins in energy metabolism pathways in ovarian cancer cells
SILAC quantitative proteomics was used to detect, identify, and quantify the key protein alterations in energy metabolic pathways in ovarian cancer cells treated with (SILAC: H) and without (SILAC: L) 20 μM ivermectin for 24 h (Table 1) [21]. This study found that ivermectin significantly reduced (i) the expression levels of glycolysis-related enzymes, including ADH5, ENO1, GPI, GAPDH, LDHA, LDHB, PFKP, and PKM; (ii) the Kreb’s cycle-related enzymes, including ACON, PCK2, PDHB, MDH2, CS, IDH2, IDH3A, IDH3B, SUCLG2, and OGDHL; (iii) the OXPHOS-related enzymes, including CYTB, UQCRH, COX17, COX1, COX6C, COX4I1, COX2, COX7A2L, COX7A2, ATP6V0C, and ATP6; and (iv) the lactate shuttle proteins MCT1 and MCT4, in ovarian cancer cells.
Pathway
Protein ID
Gene name
Protein name
Q-value
Intensity H
Intensity L
Ratio H/L
Glycolysis pathway
PFKAP
PFKP
ATP-dependent 6-phosphofructokinase, platelet type
cDNA FLJ53399, highly similar to Monocarboxylate transporter 1
0.00E+00
23799000
115420000
0.53
MOT4
MCT4
Monocarboxylate transporter 4
0.00E+00
818320000
2103700000
0.38
Table 1.
SILAC quantitative proteomics revealed the protein expression changes of key molecules in energy metabolic pathways in ovarian cancer cells TOV-21G treated with (SILAC: H) and without (SILAC: L) 20 μM ivermectin for 24 h. - means the protein expressed in L group but not in H group. + means the protein expressed in H group but not in L group. /means the protein with expressed value 0 in both H and L groups. Ratio H/L means the ratio of the ivermectin-treated group (SILAC: H) to the no ivermectin-treated group (SILAC: L). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.6 RT-qPCR and Western blot confirmed the effects of ivermectin on the key molecules in energy metabolism pathways at the mRNA and protein levels
RT-qPCR analysis confirmed the mRNA expression alterations of key molecules in energy metabolism pathways in ovarian cancer cells treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) (Figure 5), and further western blot analysis confirmed the protein expression alterations of those corresponding key molecules (Figure 6) [21]. These key molecules included PFKP, and PKM in glycolysis pathway, PDHB, CS, IDH2, IDH3A, IDH3B, and OGDHL in Kreb’s cycle pathway, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation pathway, MCT1, and MCT4 in lactate shuttle. These results clearly showed that ivermectin regulated energy metabolism pathways in ovarian cancer cells.
Figure 5.
RT-qPCR confirmed the effects of ivermectin on the mRNA expressions of key molecules in the energy metabolism pathways in ovarian cancer cells (a-f). The effects of different concentration of ivermectin (0, 10, 20, and 30 μM) on mRNA expressions of PFKP, PKM, CS, PDHB, IDH2, IDH3A, IDH3B, OGDHL, ND5, ND2, CYTB, UQCRH, MCT1, and MCT4. n = 3. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
Figure 6.
Western blot confirmed the effects of ivermectin on the protein expressions of key molecules in the energy metabolism pathways in ovarian cancer cells. n = 3. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.7 Ivermectin regulated lncRNA-EIF4A3-mRNA axis in ovarian cancer cells
Our quantitative mitochondrial proteomics data identified 1198 differentially mitochondrial proteins (mtDEPs) in human ovarian cancer tissues relative to control ovary tissues [11, 23]. Six RNA-binding proteins among those 1198 mtDEPs were identified, including EIF4A3, SFRS1, IGF2BP2, UPF1, C22ORF28, and EWSR1. Of them, only EIF4A3 was predicted to bind to the mRNA of key molecules in energy metabolism pathways. Further, Starbase predicted 3636 EIF4A3-biding mRNAs in various cancer; and of them, 306 EIF4A3-binding mRNAs was associated with ovarian cancer survival rate. Among 306 EIF4A3-binding mRNAs, the protein expressions of 116 EIF4A3-binding mRNAs and EIF4A3 were found to be inhibited by ivermectin, identified by SILAC quantitative proteomics in ovarian cancer cells treated with and without ivermectin (Table 2) [4].
Mediator of RNA polymerase II transcription subunit 20
MED20
0.01
2
0
18220000
NaN
H3BR38
Target of rapamycin complex subunit LST8
MLST8
0
3
0
13473000
NaN
P52815
39S ribosomal protein L12, mitochondrial
MRPL12
0.01
2
0
0
NaN
A0A024R1I3
Pyridoxal phosphate phosphatase
PDXP
0
6
0
40714000
NaN
A0A2R8YDS2
Ras/Rap GTPase-activating protein SynGAP
SYNGAP1
0
2
0
18400000
NaN
J3KQA0
Synaptotagmin-1
SYT1
0
26
0
339450000
NaN
Q5W0C6
Torsin-3A
TOR3A
0
3
0
16493000
NaN
B4DSK7
Mediator of RNA polymerase II transcription subunit 1
MED1
0
2
0
14356000
NaN
Q99549
M-phase phosphoprotein 8
MPHOSPH8
0
12
0
15782000
NaN
Table 2.
The proteins of 116 EIF4A3-biding mRNAs and EIF4A3 were inhibited by ivermectin, identified with SILAC quantitative proteomics in ovarian cancer cells treated with (H) and without (L) ivermectin. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
Moreover, TCGA transcriptomics analysis found that 16 lncRNAs had binding sites with EIF4A3 and associated with ovarian cancer survival rate, including SNHG3, HCG15, PDCD4-AS1, KIF9-AS1, ZNRF3-AS1, ZNF674-AS1, LINC00565, SOS1-IT1, WWTR1-AS1, PLCH1-AS1, LINC00517, STARD13-IT1, LEMD1-AS1, AL109767.1, HOXC-AS3, and LBX2-AS1 [23]. Further, RT-qPCR analysis of these 16 lncRNA expressions in ovarian cancer cells treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) compared to control cells, which found 9 lncRNAs (PDCD4-AS1, ZNRF3-AS1, HCG15, KIF9-AS1, LINC00565, ZNF674-AS1, AL109767.1, SOS1-IT1, and LBX2-AS1) were significantly affected by ivermectin (Figure 7) [4].
Figure 7.
RT-qPCR analysis revealed the effects of ivermectin on lncRNAs in ovarian cancers relative to control cells. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
These findings clearly demonstrated that ivermectin regulated lncRNA-EIF4A3-mRNA axis in ovarian cancer cells, and these mRNAs included the key molecules in energy metabolism pathways in ovarian cancer cells.
3.8 The prognostic model of ivermectin-related three-lncRNA signature for ovarian cancers identified and optimized by lasso regression
Based on those nine ivermectin-mediated lncRNAs in ovarian cancers, survival analysis and lasso regression were used to identify and optimize the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565) (Figure 8) [4]. This prognostic model was significantly related to overall survival and clinicopathologic characteristics in ovarian cancer patients [4], which might benefit for prognostic assessment and personalized drug therapy toward 3P medicine practice in ovarian cancer.
Figure 8.
Lasso regression identified and optimized the prognostic model of ivermectin-related three-lncRNA signature in ovarian cancers. (A and B). Lasso regression complexity is controlled by lambda using the glmnet R package. (C). Overall survival analysis of three-lncRNA signature between high-risk and low-risk groups. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
4. Conclusions
Ivermectin, as an old, common, and classic anti-parasite drug, has demonstrated its effective in vitro anti-cancer efficiency for ovarian cancer. Ivermectin significantly inhibited cell proliferation, growth and migration, blocked cell cycle progression, and promoted cell apoptosis of human ovarian cancer cells. Drug pathway network analysis of ivermectin revealed that it was significantly related to the key molecules of four energy metabolism pathways, and RT-qPCR and immunoaffinity blot analyses found that ivermectin significantly regulated these key molecules for those energy metabolism pathways, including PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation, and MCT1 and MCT4 in lactate shuttle. The integrative analysis of TCGA transcriptomics and mitochondrial proteomics in ovarian cancer revealed that 16 survival-related lncRNAs were mediated by ivermectin, which were further confirmed with RT-qPRC in human ovarian cancer cells. SILAC quantitative proteomics analysis revealed that the expressions of RNA-binding protein EIF4A3 and 116 EIF4A3-interacted genes were extensively inhibited by ivermectin. Those 116 EIF4A3-interacted proteins included those key molecules in four energy metabolism pathways, and those lncRNAs regulated EIF4A3-mRNA axes. Thus, ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer activities. Moreover, lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565), which was significantly associated with overall survival and clinicopathologic characteristics of ovarian cancer patients. These ivermectin-related molecular pattern alterations benefit for prognostic assessment and personalized drug therapy in the context of 3P medicine practice in ovarian cancer.
Moreover, one must realize that these achieved data about the anti-cancer activities of ivermectin in ovarian cancers are derived from the in vitro cell models. It is necessary to expand it into the in vivo animal experiments and pre-clinical and clinical experiments for its real application in ovarian cancers.
Acknowledgments
The authors acknowledge the financial supports from the Shandong First Medical University Talent Introduction Funds (to X.Z.), the Hunan Provincial Hundred Talent Plan (to X.Z.), and the grants from China “863” Plan Project (Grant No. 2014AA020610-1 to XZ).
Conflict of interest
We declare that we have no financial and personal relationships with other people or organizations.
Author’s contributions
X.Z. conceived the concept, designed the manuscript, wrote and critically revised the manuscript, coordinated and was responsible for the correspondence work and financial support. N.L. participated in preparing figures, and partial literature analysis.
Acronyms and abbreviations
FDA
Federal Drug Administration
mtDEPs
differentially mitochondrial proteins
RT-qPCR
quantitative real-time PCR
SILAC
stable isotope labeling with amino acids in cell culture
TCGA
The Cancer Genome Atlas
\n',keywords:"ovarian cancer, ivermectin, anti-cancer effect, therapeutic targets, prognostic assessment, biomarker, predictive preventive personalized medicine",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74781.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74781.xml",downloadPdfUrl:"/chapter/pdf-download/74781",previewPdfUrl:"/chapter/pdf-preview/74781",totalDownloads:965,totalViews:0,totalCrossrefCites:0,dateSubmitted:"December 14th 2020",dateReviewed:"December 19th 2020",datePrePublished:"January 13th 2021",datePublished:"October 6th 2021",dateFinished:"January 13th 2021",readingETA:"0",abstract:"Ivermectin is an old, common, and classic anti-parasite drug, which has been found to have a broad-spectrum anti-cancer effect on multiple human cancers. This chapter will focus on the anti-cancer effects of ivermectin on ovarian cancer. First, ivermectin was found to suppress cell proliferation and growth, block cell cycle progression, and promote cell apoptosis in ovarian cancer. Second, drug pathway network, qRT-PCR, and immunoaffinity blot analyses found that ivermectin acts through molecular networks to target the key molecules in energy metabolism pathways, including PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation, and MCT1 and MCT4 in lactate shuttle, to inhibit ovarian cancer growth. Third, the integrative analysis of TCGA transcriptomics and mitochondrial proteomics in ovarian cancer revealed that 16 survival-related lncRNAs were mediated by ivermectin, SILAC quantitative proteomics analysis revealed that ivermectin extensively inhibited the expressions of RNA-binding protein EIF4A3 and 116 EIF4A3-interacted genes including those key molecules in energy metabolism pathways, and also those lncRNAs regulated EIF4A3-mRNA axes. Thus, ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer capability. Further, lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565), which is significantly associated with overall survival and clinicopathologic characteristics in ovarian cancer patients. These ivermectin-related molecular pattern alterations benefit for prognostic assessment and personalized drug therapy toward 3P medicine practice in ovarian cancer.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74781",risUrl:"/chapter/ris/74781",signatures:"Xianquan Zhan and Na Li",book:{id:"10342",type:"book",title:"Ovarian Cancer",subtitle:"Updates in Tumour Biology and Therapeutics",fullTitle:"Ovarian Cancer - Updates in Tumour Biology and Therapeutics",slug:"ovarian-cancer-updates-in-tumour-biology-and-therapeutics",publishedDate:"October 6th 2021",bookSignature:"Gwo-Yaw Ho and Kate Webber",coverURL:"https://cdn.intechopen.com/books/images_new/10342.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-744-0",printIsbn:"978-1-83968-743-3",pdfIsbn:"978-1-83968-745-7",isAvailableForWebshopOrdering:!0,editors:[{id:"297757",title:null,name:"Gwo-Yaw",middleName:null,surname:"Ho",slug:"gwo-yaw-ho",fullName:"Gwo-Yaw Ho"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",fullName:"Xianquan Zhan",slug:"xianquan-zhan",email:"yjzhan2011@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",institution:null},{id:"438269",title:"Dr.",name:"Na",middleName:null,surname:"Li",fullName:"Na Li",slug:"na-li",email:"dummy.321487902897532@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Methods",level:"1"},{id:"sec_2_2",title:"2.1 Ovarian cancer cell biological behaviors affected by ivermectin",level:"2"},{id:"sec_3_2",title:"2.2 Ivermectin-mediated pathway network predicted by ingenuity pathway analysis",level:"2"},{id:"sec_4_2",title:"2.3 Ivermectin-mediated target molecule changes in energy metabolism pathways verified at the mRNA and protein levels",level:"2"},{id:"sec_5_2",title:"2.4 Ivermectin-mediated proteome changes in ovarian cancer identified by SILAC-based quantitative proteomics",level:"2"},{id:"sec_6_2",title:"2.5 Transcriptomics and clinical data of ovarian cancer patients extracted from TCGA database",level:"2"},{id:"sec_7_2",title:"2.6 Ivermectin-related lncRNAs verified with qRT-PCR",level:"2"},{id:"sec_8_2",title:"2.7 LncRNA-based prognostic signature optimized with lasso regression for ovarian cancers",level:"2"},{id:"sec_9_2",title:"2.8 Statistical significance",level:"2"},{id:"sec_11",title:"3. Results and discussion",level:"1"},{id:"sec_11_2",title:"3.1 Effects of ivermectin on biological behaviors of ovarian cancers",level:"2"},{id:"sec_12_2",title:"3.2 Effects of ivermectin on cell cycle and apoptosis in ovarian cancers",level:"2"},{id:"sec_13_2",title:"3.3 Effect of ivermectin on cell migration in ovarian cancers",level:"2"},{id:"sec_14_2",title:"3.4 Pharmaceutic molecular network predicted the association of ivermectin with ROS and energy metabolism",level:"2"},{id:"sec_15_2",title:"3.5 SILAC quantitative proteomics revealed the effects of ivermectin on key proteins in energy metabolism pathways in ovarian cancer cells",level:"2"},{id:"sec_16_2",title:"3.6 RT-qPCR and Western blot confirmed the effects of ivermectin on the key molecules in energy metabolism pathways at the mRNA and protein levels",level:"2"},{id:"sec_17_2",title:"3.7 Ivermectin regulated lncRNA-EIF4A3-mRNA axis in ovarian cancer cells",level:"2"},{id:"sec_18_2",title:"3.8 The prognostic model of ivermectin-related three-lncRNA signature for ovarian cancers identified and optimized by lasso regression",level:"2"},{id:"sec_20",title:"4. Conclusions",level:"1"},{id:"sec_21",title:"Acknowledgments",level:"1"},{id:"sec_24",title:"Conflict of interest",level:"1"},{id:"sec_21",title:"Author’s contributions",level:"1"},{id:"sec_24",title:"Acronyms and abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'Burg RW, Miller BM, Baker EE, et al. Avermectins, new family of potent anthelmintic agents: producing organism and fermentation. Antimicrob Agents Chemother 1979; 15(3): 361–367'},{id:"B2",body:'Crump A. Ivermectin: enigmatic multifaceted \'wonder\' drug continues to surprise and exceed expectations. J Antibiot (Tokyo) 2017; 70(5): 495–505'},{id:"B3",body:'Laing R, Gillan V, Devaney E. Ivermectin—old drug, new tricks? Trends Parasitol 2017; 33(6): 463–472'},{id:"B4",body:'Li N, Zhan X. Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes. EPMA J 2020; 11(2): 289–309'},{id:"B5",body:'Li N, Zhao L, Zhan X. Quantitative proteomics reveals a broad-spectrum antiviral property of ivermectin, benefiting for COVID-19 treatment. J Cell Physiol 2020. DOI: 10.1002/jcp.30055'},{id:"B6",body:'Liu J, Zhang K, Cheng L, Zhu H, Xu T. Progress in understanding the molecular mechanisms underlying the antitumour effects of ivermectin. Drug Des Devel Ther 2020; 14: 285–296'},{id:"B7",body:'Juarez M, Schcolnik-Cabrera A, Duenas-Gonzalez A. The multitargeted drug ivermectin: from an antiparasitic agent to a repositioned cancer drug. Am J Cancer Res 2018; 8(2): 317–331'},{id:"B8",body:'Kobayashi Y, Banno K, Kunitomi H, Tominaga E, Aoki D. Current state and outlook for drug repositioning anticipated in the field of ovarian cancer. J Gynecol Oncol 2019; 30(1): e10'},{id:"B9",body:'Triarico S, Capozza MA, Mastrangelo S, Attinà G, Maurizi P, Ruggiero A. Gynecological cancer among adolescents and young adults (AYA). Ann Transl Med 2020; 8(6): 397'},{id:"B10",body:'Li N, Zhan X. Mass spectrometry-based mitochondrial proteomics in human ovarian cancer. Mass Spectrom Rev 2020; 39(5–6): 471–498'},{id:"B11",body:'Li N, Zhan X. Signaling pathway network alterations in human ovarian cancers identified with quantitative mitochondrial proteomics. EPMA J 2019; 10(2): 153–172'},{id:"B12",body:'Li N, Li H, Cao L, Zhan X. Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas. Endocr Relat Cancer 2018; 25(10): 909–931'},{id:"B13",body:'Li N, Li J, Desiderio DM, Zhan X. SILAC quantitative proteomics analysis of vermectin-related proteomic profiling and molecular network alterations in human ovarian cancer cells. J Mass Spectrom 2020; e4659. DOI: 10.1002/jms.4659'},{id:"B14",body:'Zhang X, Qin T, Zhu Z, et al. Ivermectin augments the in vitro and in vivo efficacy of cisplatin in epithelial ovarian cancer by suppressing Akt/mTOR signaling. Am J Med Sci 2020; 359(2): 123–129'},{id:"B15",body:'Hashimoto H, Messerli SM, Sudo T, Maruta H. Ivermectin inactivates the kinase PAK1 and blocks the PAK1-dependent growth of human ovarian cancer and NF2 tumor cell lines. Drug Discov Ther 2009; 3(6): 243–246'},{id:"B16",body:'Dou Q, Chen HN, Wang K, et al. Ivermectin induces cytostatic autophagy by blocking the PAK1/Akt axis in breast cancer. Cancer Res 2016; 76(15): 4457–4469'},{id:"B17",body:'Song D, Liang H, Qu B, et al. Ivermectin inhibits the growth of glioma cells by inducing cell cycle arrest and apoptosis in vitro and in vivo. J Cell Biochem 2019; 120(1): 622–633'},{id:"B18",body:'Nambara S, Masuda T, Nishio M, et al. Antitumor effects of the antiparasitic agent ivermectin via inhibition of Yes-associated protein 1 expression in gastric cancer. Oncotarget 2017; 8(64): 107666–107677'},{id:"B19",body:'Melotti A, Mas C, Kuciak M, Lorente-Trigos A, Borges I, Ruiz i Altaba A. The river blindness drug ivermectin and related macrocyclic lactones inhibit WNT-TCF pathway responses in human cancer. EMBO Mol Med 2014; 6(10): 1263–1278'},{id:"B20",body:'Slade L, Pulinilkunnil T. The MiTF/TFE family of transcription tactors: master regulators of organelle signaling, metabolism, and stress adaptation. Mol Cancer Res 2017; 15(12):1637–1643'},{id:"B21",body:'Li N, Li H, Wang Y, Cao L, Zhan X. Quantitative proteomics revealed energy metabolism pathway alterations in human epithelial ovarian carcinoma and their regulation by the antiparasite drug ivermectin: data interpretation in the context of 3P medicine. EPMA J 2020; 11: 661–694'},{id:"B22",body:'Guzzo CA, Furtek CI, Porras AG, Chen C, Tipping R, Clineschmidt CM, Lasseter KC. Safety, tolerability, and pharmacokinetics of escalating high doses of ivermectin in healthy adult subjects. J Clin Pharmacol. 2002; 42(10): 1122–1133'},{id:"B23",body:'Li N, Zhan X, Zhan X. The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes. Gynecol Oncol. 2018; 150: 343–354'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Xianquan Zhan",address:"yjzhan2011@gmail.com",affiliation:'
University Creative Research Initiatives Center, Shandong First Medical University, China
Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, China
University Creative Research Initiatives Center, Shandong First Medical University, China
Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, China
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Please complete the publishing proposal form. The completed form should serve as an overview of your future Compacts, Monograph or Edited Book. Once submitted, your publishing proposal will be sent for evaluation, and a notice of acceptance or rejection will be sent within 10 to 30 working days from the date of submission.
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After approval, you will proceed in submitting your full-length manuscript. 50-130 pages for compacts, 130-500 for Monographs & Edited Books.Your full-length manuscript must follow IntechOpen's Author Guidelines and comply with our publishing rules. Once the manuscript is submitted, but before it is forwarded for peer review, it will be screened for plagiarism.
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Asiri and Kalsoom Akhtar",coverURL:"https://cdn.intechopen.com/books/images_new/8724.jpg",editedByType:"Edited by",editors:[{id:"245468",title:"Dr.",name:"Sher Bahadar",middleName:null,surname:"Khan",slug:"sher-bahadar-khan",fullName:"Sher Bahadar Khan"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7567",title:"Science, Technology and Advanced Application of Supercapacitors",subtitle:null,isOpenForSubmission:!1,hash:"6f3c82213ad65bc6260c0164da9319f4",slug:"science-technology-and-advanced-application-of-supercapacitors",bookSignature:"Takaya Sato",coverURL:"https://cdn.intechopen.com/books/images_new/7567.jpg",editedByType:"Edited by",editors:[{id:"51962",title:"Prof.",name:"Takaya",middleName:null,surname:"Sato",slug:"takaya-sato",fullName:"Takaya Sato"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6489",title:"Light-Emitting Diode",subtitle:"An Outlook On the Empirical Features and Its Recent Technological Advancements",isOpenForSubmission:!1,hash:"20818f168134f1af35547e807d839463",slug:"light-emitting-diode-an-outlook-on-the-empirical-features-and-its-recent-technological-advancements",bookSignature:"Jagannathan Thirumalai",coverURL:"https://cdn.intechopen.com/books/images_new/6489.jpg",editedByType:"Edited by",editors:[{id:"99242",title:"Prof.",name:"Jagannathan",middleName:null,surname:"Thirumalai",slug:"jagannathan-thirumalai",fullName:"Jagannathan Thirumalai"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6511",title:"Complementary Metal Oxide Semiconductor",subtitle:null,isOpenForSubmission:!1,hash:"96b2d63df3822f48468050aa7a44a44c",slug:"complementary-metal-oxide-semiconductor",bookSignature:"Kim Ho Yeap and Humaira Nisar",coverURL:"https://cdn.intechopen.com/books/images_new/6511.jpg",editedByType:"Edited by",editors:[{id:"24699",title:"Dr.",name:"Kim Ho",middleName:null,surname:"Yeap",slug:"kim-ho-yeap",fullName:"Kim Ho Yeap"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6275",title:"Supercapacitors",subtitle:"Theoretical and Practical Solutions",isOpenForSubmission:!1,hash:"94a2398d62d5bcefd79ae73a0003ad7a",slug:"supercapacitors-theoretical-and-practical-solutions",bookSignature:"Lionginas Liudvinavičius",coverURL:"https://cdn.intechopen.com/books/images_new/6275.jpg",editedByType:"Edited by",editors:[{id:"32614",title:"Dr.",name:"Lionginas",middleName:null,surname:"Liudvinavičius",slug:"lionginas-liudvinavicius",fullName:"Lionginas Liudvinavičius"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6509",title:"Energy Harvesting",subtitle:null,isOpenForSubmission:!1,hash:"9665f0b76c3e7d51613f12f86efc3767",slug:"energy-harvesting",bookSignature:"Reccab Manyala",coverURL:"https://cdn.intechopen.com/books/images_new/6509.jpg",editedByType:"Edited by",editors:[{id:"12002",title:"Associate Prof.",name:"Reccab",middleName:"Ochieng",surname:"Manyala",slug:"reccab-manyala",fullName:"Reccab Manyala"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5741",title:"Epitaxy",subtitle:null,isOpenForSubmission:!1,hash:"a5fad1c4783ec478a4c4877914ae5ca9",slug:"epitaxy",bookSignature:"Miao Zhong",coverURL:"https://cdn.intechopen.com/books/images_new/5741.jpg",editedByType:"Edited by",editors:[{id:"164790",title:"Dr.",name:"Miao",middleName:null,surname:"Zhong",slug:"miao-zhong",fullName:"Miao Zhong"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:15,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"56956",doi:"10.5772/intechopen.70694",title:"Electrochemical Capacitor Performance: Influence of Aqueous Electrolytes",slug:"electrochemical-capacitor-performance-influence-of-aqueous-electrolytes",totalDownloads:2124,totalCrossrefCites:17,totalDimensionsCites:34,abstract:"Due to low energy characteristics such as energy density and cyclic life, it is mandatory to enhance the energy characteristics of the supercapacitors (ESs). Electrolytes have been recognized as the most prominent ingredients in electrochemical supercapacitor performance. Most commercially available ESs use organic electrolytes and have some advantage like wide operating voltage. However, compared with aqueous alternatives, organic electrolytes are expensive, flammable, and, in some cases, toxic. It is reliable to assert that even though aqueous electrolytes examined by a cramped working voltage, the ions present in them are yet capable of incredibly faster carrier rates than organic electrolytes and can achieve better performance of ESs. Thus, efforts turned toward enlarging the working voltage window of aqueous electrolytes to increase overall operating potential and energy density of supercapacitor devices. This book chapter comprises the latest accomplishments in this area and provides an insight into the aqueous electrolyte advancement.",book:{id:"6275",slug:"supercapacitors-theoretical-and-practical-solutions",title:"Supercapacitors",fullTitle:"Supercapacitors - Theoretical and Practical Solutions"},signatures:"Rajendran Ramachandran and Fei Wang",authors:[{id:"212251",title:"Dr.",name:"Fei",middleName:null,surname:"Wang",slug:"fei-wang",fullName:"Fei Wang"},{id:"212284",title:"Dr.",name:"Rajendran",middleName:null,surname:"Ramachandran",slug:"rajendran-ramachandran",fullName:"Rajendran Ramachandran"}]},{id:"9781",doi:"10.5772/8564",title:"Advanced Plasma Processing: Etching, Deposition, and Wafer Bonding Techniques for Semiconductor Applications",slug:"advanced-plasma-processing-etching-deposition-and-wafer-bonding-techniques-for-semiconductor-applica",totalDownloads:7150,totalCrossrefCites:13,totalDimensionsCites:26,abstract:null,book:{id:"3644",slug:"semiconductor-technologies",title:"Semiconductor Technologies",fullTitle:"Semiconductor Technologies"},signatures:"Michael Shearn, Xiankai Sun, M. David Henry, Amnon Yariv and Axel Scherer",authors:null},{id:"16966",doi:"10.5772/18545",title:"Transparent Conductive Oxide (TCO) Films for Organic Light Emissive Devices (OLEDs)",slug:"transparent-conductive-oxide-tco-films-for-organic-light-emissive-devices-oleds-",totalDownloads:16564,totalCrossrefCites:10,totalDimensionsCites:20,abstract:null,book:{id:"253",slug:"organic-light-emitting-diode-material-process-and-devices",title:"Organic Light Emitting Diode",fullTitle:"Organic Light Emitting Diode - Material, Process and Devices"},signatures:"Sunyoung Sohn and Yoon Soo Han",authors:[{id:"31808",title:"Prof.",name:"Yoon Soo",middleName:null,surname:"Han",slug:"yoon-soo-han",fullName:"Yoon Soo Han"},{id:"91912",title:"Dr.",name:"Sunyoung",middleName:null,surname:"Sohn",slug:"sunyoung-sohn",fullName:"Sunyoung Sohn"}]},{id:"64083",doi:"10.5772/intechopen.80298",title:"Transition Metal Oxide-Based Nano-materials for Energy Storage Application",slug:"transition-metal-oxide-based-nano-materials-for-energy-storage-application",totalDownloads:1948,totalCrossrefCites:7,totalDimensionsCites:19,abstract:"With improvement of global economy, the fatigue of energy becomes inevitable in twenty-first century. It is expected that the increase of world energy requirements will be triple at the end of this century. Thus, there is an imperative need for development of renewable energy sources and storage systems. Among various energy storage systems, supercapacitors are ascertained one of the most significant storage devices. But the development of supercapacitor devices with high power and energy density are the greatest challenges for modern research. In this article, transition metal oxides such as TiO2-V2O5, NiMn2O4 etc. with porous structure are considered as high performance supercapacitors electrode. The effects of its structural, morphological and electrochemical properties have been studied extensively. A TiO2-V2O5 and NiMn2O4 based electrode delivered specific capacitance of 310 and 875 F g−1, respectively at a scan rate 2 mV s−1. This TiO2-V2O5 based asymmetric supercapacitor also exhibits excellent device performance with specific energy 20.18 W h kg−1 at specific power 5.94 kW kg−1, and retained 88.0% specific capacitance at current density of 10 A g−1 after 5000 cycles.",book:{id:"7567",slug:"science-technology-and-advanced-application-of-supercapacitors",title:"Science, Technology and Advanced Application of Supercapacitors",fullTitle:"Science, Technology and Advanced Application of Supercapacitors"},signatures:"Apurba Ray, Atanu Roy, Samik Saha and Sachindranath Das",authors:[{id:"24791",title:"Dr.",name:"Sachindra Nath",middleName:null,surname:"Das",slug:"sachindra-nath-das",fullName:"Sachindra Nath Das"},{id:"255864",title:"MSc.",name:"Apurba",middleName:null,surname:"Ray",slug:"apurba-ray",fullName:"Apurba Ray"},{id:"255910",title:"MSc.",name:"Atanu",middleName:null,surname:"Roy",slug:"atanu-roy",fullName:"Atanu Roy"},{id:"255912",title:"MSc.",name:"Samik",middleName:null,surname:"Saha",slug:"samik-saha",fullName:"Samik Saha"}]},{id:"60131",doi:"10.5772/intechopen.74136",title:"Dielectric Elastomers for Energy Harvesting",slug:"dielectric-elastomers-for-energy-harvesting",totalDownloads:1296,totalCrossrefCites:9,totalDimensionsCites:16,abstract:"Dielectric elastomers are a type of electroactive polymers that can be conveniently used as sensors, actuators or energy harvesters and the latter is the focus of this review. The relatively high number of publications devoted to dielectric elastomers in recent years is a direct reflection of their diversity, applicability as well as nontrivial electrical and mechanical properties. This chapter provides a review of fundamental mechanical and electrical properties of dielectric elastomers and up-to-date information regarding new developments of this technology and it’s potential applications for energy harvesting from various vibration sources explored over the past decade.",book:{id:"6509",slug:"energy-harvesting",title:"Energy Harvesting",fullTitle:"Energy Harvesting"},signatures:"Gordon Thomson, Daniil Yurchenko and Dimitri V. Val",authors:[{id:"227338",title:"Ph.D. Student",name:"Gordon",middleName:null,surname:"Thomson",slug:"gordon-thomson",fullName:"Gordon Thomson"},{id:"227344",title:"Dr.",name:"Daniil",middleName:null,surname:"Yurchenko",slug:"daniil-yurchenko",fullName:"Daniil Yurchenko"},{id:"227346",title:"Prof.",name:"Dimitry",middleName:null,surname:"Val",slug:"dimitry-val",fullName:"Dimitry Val"}]}],mostDownloadedChaptersLast30Days:[{id:"61888",title:"Work Function Setting in High-k Metal Gate Devices",slug:"work-function-setting-in-high-k-metal-gate-devices",totalDownloads:2634,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"As transistor size continues to shrink, SiO2/polysilicon gate stack has been replaced by high-k/metal gate to enable further scaling. Two different integration approaches have been implemented in high-volume production: gate first and gate last; the latter is also known as replacement gate approach. In both integration schemes, getting the right work functions and threshold voltages for N-type metal-oxide-semiconductor (NMOS) and P-type metal-oxide-semiconductor (PMOS) devices is critical. A number of recent studies have shown that the threshold voltage of devices is highly dependent on not just the deposited material properties but also on subsequent device processing steps. This chapter contains a description on the different mechanisms of work function setting in gate last and gate first technologies, the sensitivities to different process conditions and special measurement techniques for gate stack analysis is shown.",book:{id:"6511",slug:"complementary-metal-oxide-semiconductor",title:"Complementary Metal Oxide Semiconductor",fullTitle:"Complementary Metal Oxide Semiconductor"},signatures:"Elke Erben, Klaus Hempel and Dina Triyoso",authors:null},{id:"16962",title:"Organic Field-Effect Transistors Using Hetero-Layered Structure with OLED Materials",slug:"organic-field-effect-transistors-using-hetero-layered-structure-with-oled-materials",totalDownloads:6099,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"253",slug:"organic-light-emitting-diode-material-process-and-devices",title:"Organic Light Emitting Diode",fullTitle:"Organic Light Emitting Diode - Material, Process and Devices"},signatures:"Ken-Ichi Nakayama, Masaaki Yokoyama, Yong-Jin Pu and Junji Kido",authors:[{id:"48743",title:"Prof.",name:"Ken-Ichi",middleName:null,surname:"Nakayama",slug:"ken-ichi-nakayama",fullName:"Ken-Ichi Nakayama"},{id:"94247",title:"Prof.",name:"Masaaki",middleName:null,surname:"Yokoyama",slug:"masaaki-yokoyama",fullName:"Masaaki Yokoyama"},{id:"94248",title:"Prof.",name:"Yong-Jin",middleName:null,surname:"Pu",slug:"yong-jin-pu",fullName:"Yong-Jin Pu"},{id:"94249",title:"Prof.",name:"Junji",middleName:null,surname:"Kido",slug:"junji-kido",fullName:"Junji Kido"}]},{id:"57851",title:"Towards New Generation Power MOSFETs for Automotive Electric Control Units",slug:"towards-new-generation-power-mosfets-for-automotive-electric-control-units",totalDownloads:1495,totalCrossrefCites:1,totalDimensionsCites:0,abstract:"Power metal-oxide-semiconductor field-effect transistors (MOSFETs) are thought to be highly robust and versatile in high-speed switching applications in power electronics design due to its intrinsic high input impedance and compact size. This chapter concerns the development of a high-performance low voltage rating power MOSFET possessing low on-resistance and excellent avalanche current capability for an automotive electric power steering system (EPS). Using industry-standard Technology Computer-Aided Design (TCAD) tools, the planar- and trench-technology power MOSFETs, have been designed, modeled, simulated and compared. We surveyed and analyzed the specific on-resistance due to the different device structures, and various methods are highlighted and compared so that their benefits can be better understood and adopted. Additionally, the device ruggedness has been investigated and its improvement was evaluated and established for that of the trench MOSFET due to gate corner smoothing.",book:{id:"6511",slug:"complementary-metal-oxide-semiconductor",title:"Complementary Metal Oxide Semiconductor",fullTitle:"Complementary Metal Oxide Semiconductor"},signatures:"Kuan W.A. Chee and Tianhong Ye",authors:null},{id:"60757",title:"Selective Epitaxy of Group IV Materials for CMOS Application",slug:"selective-epitaxy-of-group-iv-materials-for-cmos-application",totalDownloads:1849,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"As the International Technology Roadmap for Semiconductors (ITRS) demands an increase of transistor density in the chip, the size of transistors has been continuously shrunk. In this evolution of transistor structure, different strain engineering methods were introduced to induce strain in the channel region. One of the most effective methods is applying embedded SiGe as stressor material in source and drain (S/D) regions by using selective epitaxy. This chapter presents an overview of implementation, modeling, and pattern dependency of selective epitaxy for S/D application in CMOS. The focus is also on the wafer in and ex situ cleaning prior to epitaxy, integrity of gate, and selectivity mode.",book:{id:"6511",slug:"complementary-metal-oxide-semiconductor",title:"Complementary Metal Oxide Semiconductor",fullTitle:"Complementary Metal Oxide Semiconductor"},signatures:"Guilei Wang, Henry H. Radamson and Mohammadreza Kolahdouz",authors:null},{id:"74939",title:"Polyimide in Electronics: Applications and Processability Overview",slug:"polyimide-in-electronics-applications-and-processability-overview",totalDownloads:648,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Polyimides are nowadays quite famous dielectrics and insulating materials widely used in electronics and electrical engineering applications from low voltage microelectronics up to high voltage engineering industry. They are well appreciated because of their excellent physical properties (i.e., thermal, electrical, and mechanical properties), as well as, their coating process ease either from a liquid or a gas phase. Consequently, polyimides appear in a various range of applications to efficiently separate metal levels or electrodes at different electrical potentials. This chapter intends to review the main chemical generalities of polyimides, the different monomer families, the coating and curing processes, and the main physical properties for electronic and high voltage industrial applications.",book:{id:"7783",slug:"polyimide-for-electronic-and-electrical-engineering-applications",title:"Polyimide for Electronic and Electrical Engineering Applications",fullTitle:"Polyimide for Electronic and Electrical Engineering Applications"},signatures:"Sombel Diaham",authors:[{id:"57115",title:"Dr.",name:"Sombel",middleName:null,surname:"Diaham",slug:"sombel-diaham",fullName:"Sombel Diaham"}]}],onlineFirstChaptersFilter:{topicId:"740",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81482",title:"A Review of Modeling and Control of Piezoelectric Stick-Slip Actuators",slug:"a-review-of-modeling-and-control-of-piezoelectric-stick-slip-actuators",totalDownloads:38,totalDimensionsCites:0,doi:"10.5772/intechopen.103838",abstract:"Piezoelectric stick-slip actuators with high precision, large actuating force, and high displacement resolution are currently widely used in the field of high-precision micro-nano processing and manufacturing. However, the non-negligible, non-linear factors and complexity of their characteristics make its modeling and control quite difficult and affect the positioning accuracy and stability of the system. To obtain higher positioning accuracy and efficiency, modeling and control of piezoelectric stick-slip actuators are meaningful and necessary. Firstly, according to the working principle of stick-slip drive, this paper introduces the sub-models with different characteristics, such as hysteresis, dynamics, and friction, and presents the comprehensive modeling representative piezoelectric stick-slip actuators. Next, the control approaches suggested by different scholars are also summarized. Appropriate control strategies are adopted to reduce its tracking error and position error in response to the influence of various factors. Lastly, future research and application prospects in modeling and control are pointed out.",book:{id:"11154",title:"Piezoelectric Actuators",coverURL:"https://cdn.intechopen.com/books/images_new/11154.jpg"},signatures:"Zhenguo Zhang, Piao Fan, Yikun Dong, Shuai Yu, Keping Liu and Xiaohui Lu"},{id:"81282",title:"Topology Optimization Methods for Flexure Hinge Type Piezoelectric Actuators",slug:"topology-optimization-methods-for-flexure-hinge-type-piezoelectric-actuators",totalDownloads:44,totalDimensionsCites:0,doi:"10.5772/intechopen.103983",abstract:"Piezoelectric actuators have the obvious advantages of simple and compact structure, high precision and long stroke. However, it is difficult to satisfy the various industrial requirements. Topology optimization method can be used to find the new configurations of the compliant mechanism, and different objective function and constraint conditions can be flexibly used to determine the compliant mechanism. In the research of piezoelectric actuators, due to the advantages of compact structure, no lubrication and large displacement magnification, compliant mechanism is extremely suitable to be introduced into the design of piezoelectric actuators. In recent years, topology optimization method is frequently used to design the compliant mechanism on piezoelectric actuator, and has become a research hotspot. In this chapter, the development of topology optimization method is introduced, the design and research on the compliant mechanism of piezoelectric actuator have been summarized, and the future research direction and challenges of topology optimization design for flexure hinge type piezoelectric actuators are prospected.",book:{id:"11154",title:"Piezoelectric Actuators",coverURL:"https://cdn.intechopen.com/books/images_new/11154.jpg"},signatures:"Shitong Yang, Yuelong Li, Guangda Qiao, Xiaosong Zhang and Xiaohui Lu"},{id:"81174",title:"Active Vibration Suppression Based on Piezoelectric Actuator",slug:"active-vibration-suppression-based-on-piezoelectric-actuator",totalDownloads:32,totalDimensionsCites:0,doi:"10.5772/intechopen.103725",abstract:"The piezoelectric constitutive equation states that the inverse piezoelectric effect can convert electrical energy into mechanical energy, resulting in small displacement and force changes with high resolution. The piezoelectric actuator based on inverse piezoelectric effect has an excellent performance in active vibration suppression because of its high frequency response, high positioning accuracy, and large output force. A new active-passive composite vibration suppression system can be formed by cascading it with passive vibration isolation elements in series and parallel. On this basis, by adding different control algorithms and control loops, such as the Sky-Hook damping feedback control algorithm and adaptive feedforward control algorithm, different vibration control effects can be realized.",book:{id:"11154",title:"Piezoelectric Actuators",coverURL:"https://cdn.intechopen.com/books/images_new/11154.jpg"},signatures:"Min Wang, Songquan Liao, Xuan Fang and Shibo Fu"},{id:"81039",title:"Influence of Piezoelectric Actuator Properties on Design of Micropump Driving Modules",slug:"influence-of-piezoelectric-actuator-properties-on-design-of-micropump-driving-modules",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.103789",abstract:"The chapter will briefly present three distinctive concepts of the micropump actuator driving module, each with its waveform specifics and their impact on particular micropump performance (pumping media, flow rate and backpressure). First presented concept is based on two mutually-exclusive boost switched-mode power supply modules. Characterization of this module identified output voltage asymmetry to be the limiting factor of micropump performance. To assure driving symmetry, an alternative driving module, based on independent high-voltage stages and optocouplers, was implemented. This design is capable of driving a piezoelectric micropump with a rectangular waveform of programmable frequency, positive and negative amplitudes, slew rates and dead time. While this design provides maximum flow and backpressure characteristics, it does not offer minimal current consumption and long-term operation. To overcome this difficulty, our current design is based on an embedded arbitrary waveform generator, which offers an efficient trade-off between high pumping performance and low current consumption.",book:{id:"11154",title:"Piezoelectric Actuators",coverURL:"https://cdn.intechopen.com/books/images_new/11154.jpg"},signatures:"Matej Možek, Borut Pečar, Drago Resnik and Danilo Vrtačnik"},{id:"80911",title:"Design, Analysis and Testing of Piezoelectric Tool Actuator for Elliptical Vibration Cutting",slug:"design-analysis-and-testing-of-piezoelectric-tool-actuator-for-elliptical-vibration-cutting",totalDownloads:27,totalDimensionsCites:0,doi:"10.5772/intechopen.103837",abstract:"In the field of ultraprecision machining, the structured surfaces with various micro/nano characteristics may have different advanced functions, such as wettability modifications, tribological control and hybrid micro-optics. However, the machining of micro/nano structured surfaces is becoming a challenge for present cutting method. Especially for the difficult-to-cut materials, it is impossible to manufacture complex micro/nano features by using traditional cutting methods. The complex features require a cutting tool no longer confined to the traditional motion guide. The cutting tool should have more quick response velocity and flexible modulated ability. This chapter aims to make an introduction for piezoelectric tool actuator used in elliptical vibration cutting, which can be offering tertiary cutting operations with quick response and flexible modulated ability. The content covers the working principle of piezoelectric tool actuator, compliant mechanism design, static modeling, kinematic and dynamic modeling, structure optimization and offline testing.",book:{id:"11154",title:"Piezoelectric Actuators",coverURL:"https://cdn.intechopen.com/books/images_new/11154.jpg"},signatures:"Jinguo Han, Mingming Lu and Jieqiong Lin"},{id:"80862",title:"Bionic Type Piezoelectric Actuators",slug:"bionic-type-piezoelectric-actuators",totalDownloads:37,totalDimensionsCites:0,doi:"10.5772/intechopen.103765",abstract:"Piezoelectric actuators have been applied in many research and industrial fields. However, how to improve the working performance of piezoelectric actuators is still a hot issue. Up to now, many new motion principles have been developed for new piezoelectric actuators. The bionic type piezoelectric actuator is a kind of the novel piezoelectric actuators, and it imitates the motion style of different creatures in nature to overcome the limitation of traditional piezoelectric actuators. Bionic type piezoelectric actuators are able to achieve large working stroke or large output force, which is of great significance for the development of piezoelectric actuators. 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Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. 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