A comparative Brownian dynamics investigation between small linear and circular DNA: Scaling of diffusion coefficient with size and topology of DNA

FISH and chips: a review of microfluidic platforms for FISH analysis

Fluorescence in situ hybridization (FISH) allows visualization of specific nucleic acid sequences within an intact cell or a tissue section. It is based on molecular recognition between a fluorescently labeled probe that penetrates the cell membrane of a fixed but intact sample and hybridizes to a nucleic acid sequence of interest within the cell, rendering a measurable signal. FISH has been applied to, for example, gene mapping, diagnosis of chromosomal aberrations and identification of pathogens in complex samples as well as detailed studies of cellular structure and function. However, FISH protocols are complex, they comprise of many fixation, incubation and washing steps involving a range of solvents and temperatures and are, thus, generally time consuming and labor intensive. The complexity of the process, the relatively high-priced fluorescent probes and the fairly high-end microscopy needed for readout render the whole process costly and have limited wider uptake of this powerful technique. In recent years, there have been attempts to transfer FISH assay protocols onto microfluidic lab-on-a-chip platforms, which reduces the required amount of sample and reagents, shortens incubation times and, thus, time to complete the protocol, and finally has the potential for automating the process. Here, we review the wide variety of approaches for lab-on-chip-based FISH that have been demonstrated at proof-of-concept stage, ranging from FISH analysis of immobilized cell layers, and cells trapped in arrays, to FISH on tissue slices. Some researchers have aimed to develop simple devices that interface with existing equipment and workflows, whilst others have aimed to integrate the entire FISH protocol into a fully autonomous FISH on-chip system. Whilst the technical possibilities for FISH on-chip are clearly demonstrated, only a small number of approaches have so far been converted into off-the-shelf products for wider use beyond the research laboratory.

Multistep, effective drug distribution within solid tumors

The distribution of drugs within solid tumors presents a long-standing barrier for efficient cancer therapies. Tumors are highly resistant to diffusion, and the lack of blood and lymphatic flows suppresses convection. Prolonged, continuous intratumoral drug delivery from a miniature drug source offers an alternative to both systemic delivery and intratumoral injection. Presented here is a model of drug distribution from such a source, in a multistep process. At delivery onset the drug mainly affects the closest surroundings. Such ‘priming’ enables drug penetration to successive cell layers. Tumor ‘void volume’ (volume not occupied by cells) increases, facilitating lymphatic perfusion. The drug is then transported by hydraulic convection downstream along interstitial fluid pressure (IFP) gradients, away from the tumor core. After a week tumor cell death occurs throughout the entire tumor and IFP gradients are flattened. Then, the drug is transported mainly by ‘mixing’, powered by physiological bulk body movements. Steady state is achieved and the drug covers the entire tumor over several months. Supporting measurements are provided from the LODER™ system, releasing siRNA against mutated KRAS over months in pancreatic cancer in-vivo models. LODER™ was also successfully employed in a recent Phase 1/2 clinical trial with pancreatic cancer patients.

An analytical correlated random walk model and its application to understand subdiffusion in crowded environment

Subdiffusion in crowded environment such as movement of macromolecule in a living cell has often been observed experimentally. The primary reason for subdiffusion is volume exclusion by the crowder molecules. However, other effects such as hydrodynamic interaction may also play an important role. Although there are a large number of computer simulation studies on understanding molecular crowding, there is a lack of theoretical models that can be connected to both experiment and simulation. In the current work, we have formulated a one-dimensional correlated random walk model by connecting this to the motion in a crowded environment. We have found the exact solution of the probability distribution function of the model by solving it analytically. The parameters of our model can be obtained either from simulation or experiment. It has been shown that this analytical model captures some of the general features of diffusion in crowded environment as given in the previous literature and its prediction for transient subdiffusion closely matches the observations of a previous study of computer simulation of Escherichia coli cytoplasm. It is likely that this model will open up more development of theoretical models in this area.