光声分子影像

光声分子影像是近期发展起来的新型无创在体影像技术。该技术结合了光声层析成像和分子影像,具有成像深度深、分辨率高和特异性强的优点。光声分子影像已经被广泛用于活体动物实验中,在对一些恶性肿瘤和炎症的检测中获得了令人振奋的结果。重点介绍了光声分子影像的机制和研究现状,并对其应用前景进行展望。     

微环境促进的侵袭性肿瘤生长的元胞自动机模拟

肿瘤的侵袭和转移行为, 常常是导致病人的死亡的原因. 而人们对这些由复杂的肿瘤宿主以及肿瘤细胞与细胞之间相互作用而产生的群体性行为知之甚少. 对这一过程了解的加深, 需要多学科间的合作. 在本篇文章中, 作者将简要回顾肿瘤物理领域的一种新手段, 即近年来由作者参与的通过元胞自动机(CA)模型来研究微环境促进的实体瘤侵袭性生长的研究, 该模型整合了一系列微观的肿瘤宿主相互作用, 包含了肿瘤细胞对细胞外基质的降解, 肿瘤细胞趋向养分的迁移, 肿瘤生长导致的局部组织压力累积以及该压力对局部的肿瘤宿主界面稳定性的影响, 并且, 肿瘤生长时细胞间的粘连也被明确地考虑进来. 该元胞自动机模型能成功地重现出一系列的标志性的肿瘤侵袭行为, 这有力地表明出该模型的有效性和预测能力. 这一模型, 如果能与临床数据结合, 理论上能够拓展从医学数据中得到的现有结论, 帮助设计新的实验, 检验假说, 并且在实验难以检测到的情形下, 预测肿瘤的行为, 协助癌症的早期诊断和预后, 并针对不同病人, 提出最优的个体化医疗方案.     

Multivariate analysis of combined Raman and fibre‐optic reflectance spectra for the identification of binder materials in simulated medieval paints

The non‐invasive identification of paint materials used in works of art is essential, both for preserving and restoring them, and also for understanding and verifying the history surrounding their creation. As such, the development of suitable non‐invasive techniques has received much interest in recent years. We have investigated the use of Fourier transform (FT)‐Raman spectroscopy and fibre‐optic reflectance spectroscopy (FORS), together with multivariate principal‐component analysis (PCA) techniques, in order to identify the pigment and binding materials used in made‐up samples representative of real artwork. We demonstrate that both types of spectroscopy provide complementary information which can be used to identify the pigments and binders in paint samples. We show that PCA with FT‐Raman spectra can be used to assist in the identification of oil‐based binders, and that the additional data provided by FORS spectra enables PCA on combined spectra to identify more complex proteinaceious and polysaccharide‐based binding media. The results presented here demonstrate that multivariate analyses of lead‐based paints, using data measured by FT‐Raman and FORS in conjunction, have much potential for identifying individual pigments and binders in paint samples. This provides a path towards computer‐assisted characterisation of paint materials on artwork. Copyright © 2013 John Wiley & Sons, Ltd.     

A Highly Integrated 3D MEMS Force Sensing Module With Variable Sensitivity for Robotic-Assisted Minimally Invasive Surgery

In robotic-assisted minimally invasive surgery (RMIS), non-sentient surgical instruments make it impossible for surgeons to perceive operational force during the procedure. To facilitate surgeons with force telepresence during surgery, a highly integrated MEMS-based piezoresistive 3D force sensing module, which is composed of a MEMS-based piezoresistive sensor chip, an encapsulation cap with miniature pyramids, and a top elastic layer, is demonstrated. This innovative combined construction allows for rapid replacement of elastic layers with different thicknesses and different Young's modulus, so as to realize an adjustable sensitivity and measurement range for different surgeries. By replacing the elastic layer, the same amount of change in resistance can be achieved for external force of 3 and 10 N in the Z-axis; the sensitivity in X- and Y-axes can be increased by a maximum of eight and seven times, respectively. Meanwhile, miniature size enables it to be integrated into various surgical instruments’ tip. Experimental demonstrations involving palpation simulated nodule detection of kidney, ex vivo puncture, and threading forces estimation of tissue-mimicking are conducted to validate the effectiveness of adjusting sensitivity and range. This sensing module is potentially a promising solution for low-cost and versatility to surgical instruments, which can facilitate unification of force-sensing/intelligent surgical instruments.