Cellular fate of nanoparticles is vital to application of nanoparticles to cell imaging, bio-sensing, drug delivery, suppression of drug resistance, gene delivery, and cytotoxicity analysis. However, the current studies on cellular fate of nanoparticles have been controversial due to complications of interplay between many possible factors. By well-controlled experiments, we demonstrated unambiguously that the morphology of nanoparticles independently determined their cellular fate. We found that nanoparticles with sharp shapes, regardless of their surface chemistry, size, or composition, could pierce the membranes of endosomes that carried them into the cells and escape to the cytoplasm, which in turn significantly reduced the cellular excretion rate of the nanoparticles. Such features of sharp-shaped nanoparticles are essential for drug delivery, gene delivery, subcellular targeting, and long-term tracking. This work opens up a controllable, purely geometrical and hence safe, degree of freedom for manipulating nanoparticle-cell interaction, with numerous applications in medicine, bio-imaging, and bio-sensing.

Drug release simultaneously with carrier decomposition has been demonstrated in SiO2-drug composite nanoparticles. By creating a radial drug concentration gradient in the nanoparticle, controllable release of the drug is primarily driven by diffusion. Escape of the drug molecules then triggers the SiO2 carrier decomposition, which starts from the center of the nanoparticle and eventually leads to its complete fragmentation. The small size of the final carrier fragments enables their easy excretion via renal systems. Together with the known biocompatibility of SiO2, the feature of controllable drug release and simultaneous carrier decomposition achieved in the SiO2-drug nanoparticles make it ideal for a wide range of diagnostic and therapeutic applications with great promise for potential clinical translation.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.

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Unique data from a 1998 healthy longevity baseline survey provide demographic, socio-economic, and health characteristics of the oldest old, aged 80-105, in China. This subpopu-lation is growing rapidly and is likely to need extensive social and health services. A large majority of Chinese oldest old live with their children and rely mainly on children for financial support and care. Most Chinese oldest old had no or very little education. Ability to function independently in daily living declines rapidly and self-rated health declines moderately across the oldest old ages. As compared to their urban counterparts, the rural oldest old have far less pension support, are significantly less educated, and are more likely to be widowed and to rely on children for support. Apart from higher rates of survival, the female oldest old in China are far more disadvantaged than the male oldest old. Copyright 2002 by The Population Council, Inc..

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