|
1
|
WHO: Global tuberculosis report 2017.
http://wwwwhoint/tb/publications/global_report/en/2017
|
|
2
|
WHO: Latent tuberculosis infection Updated
and consolidated guidelines for programmatic management. http://appswhoint/iris/bitstream/10665/260233/1/9789241550239-engpdf?ua=12018
|
|
3
|
Palomino JC, Martin A, Von Groll A and
Portaels F: Rapid culture-based methods for drug-resistance
detection in Mycobacterium tuberculosis. J Microbiol
Methods. 75:161–166. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Tang P and Johnston J: Treatment of latent
tuberculosis infection. Curr Treat Options Infect Dis. 9:371–379.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Alvarez-León EE, Espinosa-Vega E,
Santana-Rodriguez E, Molina-Cabrillana JM, Pérez-Arellano JL,
Caminero JA and Serrano-Aguilar P: Screening for tuberculosis
infection in spanish healthcare workers: Comparison of the
QuantiFERON-TB gold in-tube test with the tuberculin skin test.
Infect Control Hosp Epidemiol. 30:876–883. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Menzies D, Pai M and Comstock G:
Meta-analysis: New tests for the diagnosis of latent tuberculosis
infection: areas of uncertainty and recommendations for research.
Ann Intern Med. 146:340–354. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Jiang W, Shao L, Zhang Y, Zhang S, Meng C,
Xu Y, Huang L, Wang Y, Wang Y, Weng X and Zhang W: High-sensitive
and rapid detection of Mycobacterium tuberculosis infection
by IFN-gamma release assay among HIV-infected individuals in
BCG-vaccinated area. BMC Immunol. 10:312009. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Matulis G, Juni P, Villiger PM and Gadola
SD: Detection of latent tuberculosis in immunosuppressed patients
with autoimmune diseases: Performance of a Mycobacterium
tuberculosis antigen-specific interferon gamma assay. Ann Rheum
Dis. 67:84–90. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
WHO: Guidelines on the management of
latent tuberculosis infection. http://wwwwhoint/tb/publications/latent-tuberculosis-infection/en/2014.
|
|
10
|
Bartel DP: MicroRNAs: Genomics,
biogenesis, mechanism, and function. Cell. 116:281–297. 2004.
View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Lukiw WJ: Micro-RNA speciation in fetal,
adult and Alzheimer's disease hippocampus. Neuroreport. 18:297–300.
2007. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Hayes J, Peruzzi PP and Lawler S:
MicroRNAs in cancer: Biomarkers, functions and therapy. Trends Mol
Med. 20:460–469. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Chen H, Lan HY, Roukos DH and Cho WC:
Application of microRNAs in diabetes mellitus. J Endocrinol.
222:R1–R10. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Kumarswamy R and Thum T: Non-coding RNAs
in cardiac remodeling and heart failure. Circ Res. 113:676–689.
2013. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Jin BX, Zhang YH, Jin WJ, Sun XY, Qiao GF,
Wei YY, Sun LB, Zhang WH and Li N: MicroRNA panels as disease
biomarkers distinguishing hepatitis B virus infection caused
hepatitis and liver cirrhosis. Sci Rep. 5:150262015. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Staedel C and Darfeuille F: MicroRNAs and
bacterial infection. Cellular microbiology. 15:1496–1507. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Wu LS, Lee SW, Huang KY, Lee TY, Hsu PW
and Weng JT: Systematic expression profiling analysis identifies
specific microRNA-gene interactions that may differentiate between
active and latent tuberculosis infection. Biomed Res Int.
2014:8951792014. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Meng QL, Liu F, Yang XY, Liu XM, Zhang X,
Zhang C1 and Zhang ZD: Identification of latent tuberculosis
infection-related microRNAs in human U937 macrophages expressing
Mycobacterium tuberculosis Hsp16.3. BMC Microbiol.
14:372014. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Rai G, Rai R, Saeidian AH and Rai M:
Microarray to deep sequencing: Transcriptome and miRNA profiling to
elucidate molecular pathways in systemic lupus erythematosus.
Immunol Res. 64:14–24. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Zheng Y, Qing T, Song Y, Zhu J, Yu Y, Shi
W, Pusztai L and Shi L: Standardization efforts enabling
next-generation sequencing and microarray based biomarkers for
precision medicine. Biomark Med. 9:1265–1272. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Zheng L, Leung E, Lee N, Lui G, To KF,
Chan RC and Ip M: Differential microRNA expression in human
macrophages with Mycobacterium tuberculosis infection of
Beijing/W and NON-Beijing/W strain types. PLoS One.
10:e01260182015. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Gentleman RC, Carey VJ, Bates DM, Bolstad
B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al:
Bioconductor: Open software development for computational biology
and bioinformatics. Genome Biol. 5:R802004. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Mizrachi E, Verbeke L, Christie N, Fierro
AC, Mansfield SD, Davis MF, Gjersing E, Tuskan GA, Van Montagu M,
Van de Peer Y, et al: Network-based integration of systems genetics
data reveals pathways associated with lignocellulosic biomass
accumulation and processing. Proc Natl Acad Sci USA. 114:1195–1200.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Agarwal V, Bell GW, Nam JW and Bartel DP:
Predicting effective microRNA target sites in mammalian mRNAs.
Elife. 4:2015. View Article : Google Scholar
|
|
25
|
Szklarczyk D, Franceschini A, Wyder S,
Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos
A, Tsafou KP, et al: STRING v10: Protein-protein interaction
networks, integrated over the tree of life. Nucleic Acids Res.
43:(Database Issue). D447–D452. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Muetze T, Goenawan IH, Wiencko HL,
Bernal-Llinares M, Bryan K and Lynn DJ: contextual hub analysis
tool (CHAT): A Cytoscape app for identifying contextually relevant
hubs in biological networks. F1000 Res. 5:17452016. View Article : Google Scholar
|
|
27
|
Su G, Morris JH, Demchak B and Bader GD:
Biological network exploration with Cytoscape 3. Curr Protoc
Bioinformatics. 47:8.13.1–24. 2014. View Article : Google Scholar
|
|
28
|
Du J, Yuan Z, Ma Z, Song J, Xie X and Chen
Y: KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway
analysis using a path analysis model. Mol Biosyst. 10:2441–2447.
2014. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Wang JH, Zhao LF, Lin P, Su XR, Chen SJ,
Huang LQ, Wang HF, Zhang H, Hu ZF, Yao KT and Huang ZX: GenCLiP
2.0: A web server for functional clustering of genes and
construction of molecular networks based on free terms.
Bioinformatics. 30:2534–2536. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Xin H, Yang Y, Liu J, Li X, Li M, Feng B,
Li Z, Zhang H, Li H, Shen F, et al: Association between
tuberculosis and circulating microRNA hsa-let-7b and hsa-miR-30b: A
pilot study in a Chinese population. Tuberculosis (Edinb).
99:63–69. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Fu Y, Yi Z, Li J and Li R: Deregulated
microRNAs in CD4+ T cells from individuals with latent tuberculosis
versus active tuberculosis. J Cell Mol Med. 18:503–513. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Wang C, Yang S, Sun G, Tang X, Lu S,
Neyrolles O and Gao Q: Comparative miRNA expression profiles in
individuals with latent and active tuberculosis. PLoS One.
6:e258322011. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Ndzi EN, Nkenfou CN, Mekue LM, Zentilin L,
Tamgue O, Pefura EWY, Kuiaté JR, Giacca M and Ndjolo A: MicroRNA
hsa-miR-29a-3p is a plasma biomarker for the differential diagnosis
and monitoring of tuberculosis. Tuberculosis (Edinb). 114:69–76.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Sabir N, Hussain T, Shah SZA, Peramo A,
Zhao D and Zhou X: miRNAs in tuberculosis: new avenues for
diagnosis and host-directed therapy. Front Microbiol. 9:6022018.
View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Kleinsteuber K, Heesch K, Schattling S,
Kohns M, Sander-Jülch C, Walzl G, Hesseling A, Mayatepek E,
Fleischer B, Marx FM and Jacobsen M: Decreased expression of
miR-21, miR-26a, miR-29a, and miR-142-3p in CD4+ T cells
and peripheral blood from tuberculosis patients. PLoS One.
8:e616092013. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Pan D, Pan M and Xu YM: Mir-29a
expressions in peripheral blood mononuclear cell and cerebrospinal
fluid: Diagnostic value in patients with pediatric tuberculous
meningitis. Brain Res Bull. 130:231–235. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Zhao C, Wang G, Zhu Y, Li X, Yan F, Zhang
C, Huang X and Zhang Y: Aberrant regulation of miR-15b in human
malignant tumors and its effects on the hallmarks of cancer. Tumour
Biol. 37:177–183. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Guerrieri F, Belloni L, D'Andrea D,
Pediconi N, Le Pera L, Testoni B, Scisciani C, Floriot O, Zoulim F,
Tramontano A and Levrero M: Genome-wide identification of direct
HBx genomic targets. BMC Genomics. 18:1842017. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Valencia-Quintana R, Sánchez-Alarcón J,
Tenorio-Arvide MG, Deng Y, Montiel-González JM, Gómez-Arroyo S,
Villalobos-Pietrini R, Cortés-Eslava J, Flores-Márquez AR and
Arenas-Huertero F: The microRNAs as potential biomarkers for
predicting the onset of aflatoxin exposure in human beings: A
review. Front Microbiol. 5:1022014. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Aguilar BJ, Zhou H and Lu Q: Cdc42
signaling pathway inhibition as a therapeutic target in ras-
related cancers. Curr Med Chem. 24:3485–3507. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Chang H, Sung JH, Moon SU, Kim HS, Kim JW
and Lee JS: EGF Induced RET inhibitor resistance in CCDC6-RET lung
cancer cells. Yonsei Med J. 58:9–18. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Kato F, Fiorentino FP, Alibés A, Perucho
M, Sánchez-Céspedes M, Kohno T and Yokota J: MYCL is a target of a
BET bromodomain inhibitor, JQ1, on growth suppression efficacy in
small cell lung cancer cells. Oncotarget. 7:77378–77388. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Cui M, Augert A, Rongione M, Conkrite K,
Parazzoli S, Nikitin AY, Ingolia N and MacPherson D: PTEN is a
potent suppressor of small cell lung cancer. Mol Cancer Res.
12:654–659. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Nicoletti F, Fagone P, Meroni P, McCubrey
J and Bendtzen K: mTOR as a multifunctional therapeutic target in
HIV infection. Drug Discov Today. 16:715–721. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Nicoletti F, Lapenta C, Donati S, Spada M,
Ranazzi A, Cacopardo B, Mangano K, Belardelli F, Perno C and Aquaro
S: Inhibition of human immunodeficiency virus (HIV-1) infection in
human peripheral blood leucocytes-SCID reconstituted mice by
rapamycin. Clin Exp Immunol. 155:28–34. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Donia M, McCubrey JA, Bendtzen K and
Nicoletti F: Potential use of rapamycin in HIV infection. Br J Clin
Pharmacol. 70:784–793. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Nitulescu GM, Van De Venter M, Nitulescu
G, Ungurianu A, Juzenas P, Peng Q, Olaru OT, Grădinaru D, Tsatsakis
A, Tsoukalas D, et al: The Akt pathway in oncology therapy and
beyond (Review). Int J Oncol. 53:2319–2331. 2018.PubMed/NCBI
|
|
48
|
Chen D, Mao C, Zhou Y, Su Y, Liu S and Qi
WQ: PF-04691502, a dual PI3K/mTOR inhibitor has potent pre-clinical
activity by inducing apoptosis and G1 cell cycle arrest in
aggressive B-cell non-Hodgkin lymphomas. Int J Oncol. 48:253–260.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Moon du G, Lee SE, Oh MM, Lee SC, Jeong
SJ, Hong SK, Yoon CY, Byun SS, Park HS and Cheon J: NVP-BEZ235, a
dual PI3K/mTOR inhibitor synergistically potentiates the antitumor
effects of cisplatin in bladder cancer cells. Int J Oncol.
45:1027–1035. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Maksimovic-Ivanic D, Fagone P, McCubrey J,
Bendtzen K, Mijatovic S and Nicoletti F: HIV-protease inhibitors
for the treatment of cancer: Repositioning HIV protease inhibitors
while developing more potent NO-hybridized derivatives? Int J
Cancer. 140:1713–1726. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Mammana S, Bramanti P, Mazzon E, Cavalli
E, Basile MS, Fagone P, Petralia MC, McCubrey JA, Nicoletti F and
Mangano K: Preclinical evaluation of the PI3K/Akt/mTOR pathway in
animal models of multiple sclerosis. Oncotarget. 9:8263–8277. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Fagone P, Mangano K, Pesce A, Portale TR,
Puleo S and Nicoletti F: Emerging therapeutic targets for the
treatment of hepatic fibrosis. Drug Discov Today. 21:369–375. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Wang FY, Wang XM, Wang C, Wang XF, Zhang
YQ, Wu JD, Wu F, Zhang WJ and Zhang L: Suppression of Mcl-1 induces
apoptosis in mouse peritoneal macrophages infected with
Mycobacterium tuberculosis. Microbiol Immunol. 60:215–227.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Kim KH, Yang CS, Shin AR, Jeon SR, Park
JK, Kim HJ and Jo EK: Mycobacterial heparin-binding hemagglutinin
antigen activates inflammatory responses through PI3-K/Akt, NF-κB,
and MAPK pathways. Immune Netw. 11:123–133. 2011. View Article : Google Scholar : PubMed/NCBI
|
