Cancer nanotherapeutics are rapidly progressing and are being implemented to solve several limitations of conventional drug delivery systems such as nonspecific biodistribution and targeting, lack of water solubility, poor oral bioavailability, and low therapeutic indices. To improve the biodistribution of cancer drugs, nanoparticles have been designed for optimal size and surface characteristics to increase their circulation time in the bloodstream. They are also able to carry their loaded active drugs to cancer cells by selectively using the unique pathophysiology of tumors, such as their enhanced permeability and retention effect and the tumor microenvironment. In addition to this passive targeting mechanism, active targeting strategies using ligands or antibodies directed against selected tumor targets amplify the specificity of these therapeutic nanoparticles. Drug resistance, another obstacle that impedes the efficacy of both molecularly targeted and conventional chemotherapeutic agents, might also be overcome, or at least reduced, using nanoparticles. Nanoparticles have the ability to accumulate in cells without being recognized by P-glycoprotein, one of the main mediators of multidrug resistance, resulting in the increased intracellular concentration of drugs. Multifunctional and multiplex nanoparticles are now being actively investigated and are on the horizon as the next generation of nanoparticles, facilitating personalized and tailored cancer treatment.

https://clincancerres.aacrjournals.org/content/clincanres/14/5/1310.full.pdf

Therapeutic Nanoparticles for Drug Delivery in Cancer

Magnetic Nanoparticles in MR Imaging and Drug Delivery

This article reviews the requirements for successful compressed sensing (CS), describes their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The authors emphasize on an intuitive understanding of CS by describing the CS reconstruction as a process of interference cancellation. There is also an emphasis on the understanding of the driving factors in applications, including limitations imposed by MRI hardware, by the characteristics of different types of images, and by clinical concerns.

/pdf/compressed-sensing-mri-2wgw41cvre.pdf

Compressed Sensing MRI

Optogenetics in neural systems.

Poststroke optogenetic stimulations can promote functional recovery. However, the circuit mechanisms underlying recovery remain unclear. Elucidating key neural circuits involved in recovery will be invaluable for translating neuromodulation strategies after stroke. Here, we used optogenetic functional magnetic resonance imaging to map brain-wide neural circuit dynamics after stroke in mice treated with and without optogenetic excitatory neuronal stimulations in the ipsilesional primary motor cortex (iM1). We identified key sensorimotor circuits affected by stroke. iM1 stimulation treatment restored activation of the ipsilesional corticothalamic and corticocortical circuits, and the extent of activation was correlated with functional recovery. Furthermore, stimulated mice exhibited higher expression of axonal growth-associated protein 43 in the ipsilesional thalamus and showed increased Synaptophysin+/channelrhodopsin+ presynaptic axonal terminals in the corticothalamic circuit. Selective stimulation of the corticothalamic circuit was sufficient to improve functional recovery. Together, these findings suggest early involvement of corticothalamic circuit as an important mediator of poststroke recovery.

Brain-wide neural dynamics of poststroke recovery induced by optogenetic stimulation.

Methods and systems for analyzing brain functional activity data are provided. Also provided are systems that find use in performing the present methods.

Method and systems for analyzing functional imaging data

Examples described herein may predict therapy efficacy and/or therapeutic parameters using a comparison of individual patient status data and brain network response maps for the therapy. For example, VNS parameters may be predicted using a comparison of patient EEG data and brain network response maps of VNS therapy at various parameters.

Efficacy and/or therapeutic parameter recommendation using individual patient data and therapeutic brain network maps

Magnetic resonance imaging (MRI) is often times limited by scan time To reduce scan time, there have been various efforts to reduce the number of sampling points In most cases, this is done by utilizing a priori knowledge of the signal of interest In this paper, we propose an algorithm that will guide the determination of an optimal sampling pattern based on prior knowledge of the signal Applications of this method include optimal variable-density k-space trajectory design or reduced phase encoding in 3DFT and spectroscopy Preliminary results are shown as a proof of concept

Optimal variable-density k-space sampling in MRI

Replying to N. K. Logothetis , 10.1038/nature09532 (2010)
 This is a welcome opportunity to discuss ofMRI, a technology for testing the causal and global impact of defined cell populations in vivo1. The accompanying Comment2 reviews well-known neuroanatomy, but does seem, in its entirety, to be founded on a suggestion that, after experiments were conducted to drive a defined circuit element and measure resulting BOLD signals1, we concluded that no other contributory circuit element was recruited by the driven population. This was not the case, however, as correctly understood by others in the fMRI community3,4,5 and as explained in the paper (for example, “contributions from additional cells and processes downstream of the defined optically triggered population are expected and indeed represent an important aspect of this approach”1). Moreover, the complexity of the brain dictates that such possible contributory mechanisms are more numerous than listed in the Comment2, including many other circuit and feedback mechanisms and classes of cells within neural circuitry6,7,8,9,10. As was discussed1, this is one of the most important and useful aspects of the ofMRI approach.
 https://www.nature.com/articles/nature09532

Jin Hyung Lee

Papers

Brain-wide neural dynamics of poststroke recovery induced by optogenetic stimulation.

Method and systems for analyzing functional imaging data

Efficacy and/or therapeutic parameter recommendation using individual patient data and therapeutic brain network maps

Optimal variable-density k-space sampling in MRI

Lee et al. reply