Biomedical Engineering – From Theory to Applications

More documents

Recommendations

Info

244 Biomedical Engineering – From Theory to Applications Regeneration efficiencies were also estimated bisecting the animals and allowing regeneration in presence of QDs. During the first 48-72hr post amputation a great percentage of animals treated with the highest QD concentration were unable to regenerate a head and were found as stumps without tentacles (stage 0). Moreover, about 30% of the bisected animals died, demonstrating the high QD toxicity (see Figure 16, upper panel). Fig. 16. Impact of CdTe QDs on regeneration efficiency and growth rates Upper panel: representative histogram showing the impact of QDs on Hydra head regeneration. The regeneration stages are classified as in Fig.2. Basically, stage zero indicate the complete inhibition of regeneration (zero tentacles); stage 1, indicates heads with aberrant tentacles (one or two), while stage 2 indicates normal regeneration (tentacles from four to six at this time). The lowest QD concentration tested, 10nM, does not impair head regeneration, while the 25nM dose inhibits the whole process, and furthermore, causes lethality. Lower panel: influence of the QD treatment on Hydra population growth rate. Population growth test started with a population of four full-grown Hydra, incubated 24h with the indicated dose of QD, washed out and monitored every day for bud detachment. The logarithmic growth rate constant (k) is the slope of the regression line using the
An Ancient Model Organism to Test In Vivo Novel Functional Nanocrystals standard equation of logarithmic growth: ln (n/n0) = kt. In this representative graph the regression line is not drawn. Polyps treated with the highest QD concentration were impaired in the reproductive capabilities, as shown by the altered ratio n/n° along the monitored period (Ambrosone et al, unpublished). We also compared the effects of thioglycolic acid capped QDs (TGA-QDs) and glutathione capped QDs (GSH-QDs), by using the same approaches and observed that although both nanocrystals were toxic, the most severe effects were induced by TGA capped QDs (Tino et al., 2011). This confirms the importance of the nanocrystal surface chemistry in the interaction with living cells. The availability of a Hydra whole genome sequence allowed us to study the nanoparticleinduced cellular changes at three levels: non-genomic, genomic and epigenetic. The genes selectively involved in the apoptosis or in the necrosis process, as diverse as the Hymyc transcription factor, Caspase 3, Superoxide dismutase, Hsp70 have been analysed by quantitative real time PCR, and compared to the expression of animals treated with free cadmium salts (Ambrosone et al, unpublished). Aside from genotoxic effects, as nanoparticles could cause more subtle changes to living cells, such as long-term effects on gene expression, after the QD signal has been removed, epigenetic effects are being addressed. At the current stage of investigation, the elucidation of the possible molecular pathways activated by CdTe QDs appears rather complex, and it may concern universal stress response genes, Cd specific response genes or novel unidentified signalling cascades, initiated by the QDs at the cell surface. In conclusion, by using different approaches, from in vivo evaluation of morphological traits to the impact on growth rate and regeneration, to the molecular analysis of the genes potentially involved in the QD response, we determined animal behaviours and toxicological effects played by CdTe QDs, and proposed Hydra as a valuable model for nanotoxicology studies. Fig. 17. Methodological approaches for nanotoxicology using Hydra as model system The impact of nanoparticles on a living organism can be assessed by using the freshwater polyp Hydra. This system allows to evaluate in vivo, ex vivo and in vitro the responses of a whole animal to short or long exposures of any organic and inorganic compound, unless unstable in Hydra culture medium. 4. Hydra as a widely applicable tool for high-throughput screens of nanoparticles biocompatibility and (eco)toxicity The use of simple model organisms to dissect complex biological processes has permitted biology to advance at an impressive pace, and the knowledge generated by integrating 245
Page 1 and 2:
BIOMEDICAL ENGINEERING - FROM THEOR
Page 3:
free online editions of InTech Book
Page 6:
VI Contents Chapter 9 Targeted Magn
Page 10:
X Preface stand-alone and readers c
Page 14 and 15:
2 Biomedical Engineering - From The
Page 16 and 17:
4 Fig. 2. Process for retrieval inf
Page 18 and 19:
6 Biomedical search engine Scientif
Page 20 and 21:
8 Biomedical Engineering - From The
Page 22 and 23:
10 Biomedical Engineering - From Th
Page 24 and 25:
12 Bireme http://regional.bv salud.
Page 26 and 27:
14 Semantic Networks analysis Biome
Page 28 and 29:
Page 30 and 31:
Page 32 and 33:
Page 34 and 35:
Page 36 and 37:
Page 38 and 39:
Page 40 and 41:
Page 42 and 43:
Page 44 and 45:
Page 46 and 47:
Page 48 and 49:
Page 50 and 51:
Page 52 and 53:
Page 54 and 55:
Page 56 and 57:
Page 58 and 59:
Page 60 and 61:
Page 62 and 63:
Page 64 and 65:
Page 66 and 67:
Page 68 and 69:
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
Page 88 and 89:
Page 90 and 91:
Page 92 and 93:
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
100 Biomedical Engineering - From T
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
Page 120 and 121:
108 Method (Detection) CIEF-tITP-CZ
Page 122 and 123:
110 Method (Detection) Analyte Matr
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
120 6. Conclusion Biomedical Engine
Page 134 and 135:
Page 136 and 137:
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
Page 152 and 153:
Page 154 and 155:
Page 156 and 157:
Page 158 and 159:
Page 160 and 161:
Page 162 and 163:
150 5. Conclusions Biomedical Engin
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
162 1 st phase : half year 4 2 nd p
Page 176 and 177:
Page 178 and 179:
166 7. Innovative active training B
Page 180 and 181:
Page 182 and 183:
Page 184 and 185:
172 12. Maturing projects’ story
Page 186 and 187:
Page 188 and 189:
Page 190 and 191:
Page 192 and 193:
180 16. Acknowledgments Biomedical
Page 194 and 195:
Page 196 and 197:
Page 198 and 199:
Page 200 and 201:
Page 202 and 203:
190 R* M M M M MR*M O O O O M O R*
Page 204 and 205:
Page 206 and 207: 194 Biomedical Engineering - From T
Page 208 and 209: 196 Fig. 9. Chemical structure of 5
Page 210 and 211: 198 Relative Intensity (AU) Biomedi
Page 216 and 217: 204 2. Preparation of IO nanopartic
Page 268 and 269: 256 3. Deposition techniques Biomed
Page 306 and 307:
Page 308 and 309:
Page 310 and 311:
Page 312 and 313:
300 2. Nanoparticles in biomedical
Page 314 and 315:
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
Page 322 and 323:
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
Page 336 and 337:
Page 338 and 339:
Page 340 and 341:
Page 342 and 343:
Page 344 and 345:
Page 346 and 347:
Page 348 and 349:
Page 350 and 351:
Page 352 and 353:
Page 354 and 355:
Page 356 and 357:
Page 358 and 359:
Page 360 and 361:
Page 362 and 363:
Page 364 and 365:
Page 366 and 367:
Page 368 and 369:
Page 370 and 371:
Page 372 and 373:
Page 374 and 375:
Page 376 and 377:
Page 378 and 379:
Page 380 and 381:
Page 382 and 383:
Page 384 and 385:
Page 386 and 387:
Page 388 and 389:
Page 390 and 391:
Page 392 and 393:
Page 394 and 395:
Page 396 and 397:
Page 398 and 399:
Page 400 and 401:
Page 402 and 403:
Page 404 and 405:
Page 406 and 407:
Page 408 and 409:
Page 410 and 411:
Page 412 and 413:
Page 414 and 415:
Page 416 and 417:
Page 418 and 419:
Page 420 and 421:
Page 422 and 423:
Page 424 and 425:
Page 426 and 427:
Page 428 and 429:
Page 430 and 431:
Page 432 and 433:
Page 434 and 435:
Page 436 and 437:
Page 438 and 439:
Page 440 and 441:
Page 442 and 443:
Page 444 and 445:
Page 446 and 447:
434 3. Three dimensional virtual mo
Page 448 and 449:
Page 450 and 451:
Page 452 and 453:
Page 454 and 455:
Page 456 and 457:
Page 458 and 459:
Page 460 and 461:
Page 462 and 463:
Page 464 and 465:
Page 466 and 467:
454 In this case, the eigenvalues a
Page 468 and 469:
456 where Biomedical Engineering -
Page 470 and 471:
Page 472 and 473:
Page 474 and 475:
Page 476 and 477:
Page 478 and 479:
Page 480 and 481:
Page 482 and 483:
Page 484 and 485:
472 Nb b b l l1 Biomedical Engineer
Page 486 and 487:
Page 488 and 489:
Page 490 and 491:
478 Load F (μN) Parallel-oriented
Page 492 and 493:
Page 494 and 495:
Page 496 and 497:
Page 498:
show all

Biomedical Engineering – From Theory to Applications

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?