Health,Stem Cells, and Technology

Friday, November 23, 2012

A High-Performance Neural Prosthesis

When a paralyzed person imagines moving a limb, cells in the part of the brain that controls movement activate, as if trying to make the immobile limb work again. Neural prostheses translate neural activity from the brain into control signals for guiding prosthetic devices, such as computer cursors and robotic limbs, and thus offer individuals with disabilities greater interaction with the world. However, relatively low performance remains a critical barrier to successful clinical translation; current neural prostheses are considerably slower, with less accurate control, than the native arm.

Professor Shenov and team at Stanford present a new control algorithm, the recalibrated feedback intention–trained Kalman filter (ReFIT-KF) that incorporates assumptions about the nature of closed-loop neural prosthetic control. When tested in rhesus monkeys implanted with motor cortical electrode arrays, the ReFIT-KF algorithm outperformed existing neural prosthetic algorithms in all measured domains and halved target acquisition time. This control algorithm permits sustained, uninterrupted use for hours and generalizes to more challenging tasks without retraining. Using this algorithm, they demonstrate repeatable high performance for years after implantation in two monkeys, thereby increasing the clinical viability of neural prostheses.

Despite a neurological injury or disease that has severed the pathway between brain and muscle, the region where the signals originate remains intact and functional. In recent years, neuroscientists and neuroengineers working in prosthetics have begun to develop brain-implantable sensors that can measure signals from individual neurons. After those signals have been decoded through a mathematical algorithm, they can be used to control the movement of a cursor on a computer screen – in essence, the cursor is controlled by thoughts. The work is part of a field known as neural prosthetics.

The Stanford researchers have now developed a new algorithm, known as ReFIT, that vastly improves the speed and accuracy of neural prosthetics that control computer cursors. The results were published Nov. 18 in the journal Nature Neuroscience in a paper by Dr. Krishna Shenoy, a professor of electrical engineering, bioengineering and neurobiology at Stanford, and a team led by research associate Dr. Vikash Gilja and bioengineering doctoral candidate Paul Nuyujukian. 

Scientists and engineers will soon make an implantable device, controlled by the mind, that surgeons can implant, leading to the control of artificial limbs and actuators by the patient.

Monday, November 19, 2012

More Evidence For Somatic Cell Mosaicism; There Is No One Genome In A Person


In a new study from Stanford and Yale published in Nature, somatic copy number mosaicism in human skin is revealed in induced pluripotent stem cells. That is, within our somatic cells, in this case 30% of fibroblasts in the skin, differences in their genomes frequently occur. Once again, as I have stated before, their is no one genome in human adults, rather the genome must be considered for single cells, with a high probability that the genome in one somatic cell will differ from that in another somatic cell.

Abstract from their paper:

Reprogramming somatic cells into induced pluripotent stem cells (iPSCs) has been suspected of causing de novo copy number variation1234. To explore this issue, here we perform a whole-genome and transcriptome analysis of 20 human iPSC lines derived from the primary skin fibroblasts of seven individuals using next-generation sequencing. We find that, on average, an iPSC line manifests two copy number variants (CNVs) not apparent in the fibroblasts from which the iPSC was derived. Using PCR and digital droplet PCR, we show that at least 50% of those CNVs are present as low-frequency somatic genomic variants in parental fibroblasts (that is, the fibroblasts from which each corresponding human iPSC line is derived), and are manifested in iPSC lines owing to their clonal origin. Hence, reprogramming does not necessarily lead to de novo CNVs in iPSCs, because most of the line-manifested CNVs reflect somatic mosaicism in the human skin. Moreover, our findings demonstrate that clonal expansion, and iPSC lines in particular, can be used as a discovery tool to reliably detect low-frequency CNVs in the tissue of origin. Overall, we estimate that approximately 30% of the fibroblast cells have somatic CNVs in their genomes, suggesting widespread somatic mosaicism in the human body. Our study paves the way to understanding the fundamental question of the extent to which cells of the human body normally acquire structural alterations in their DNA post-zygotically.

Nature
 
(2012)
 
doi:10.1038/nature11629
Received
 
Accepted
 
Published online
 

Friday, November 9, 2012

Lung-on-a-Chip For Drug Discovery



Researchers, including Charles Lindbergh in the early 1900s, have been attempting to cultivate organs and combinations of tissues for years in hopes that they would imitate working organs, and thereby serve as testing grounds for novel drugs to treat a wide variety of conditions.That promise has come a step closer to reality with the report in this week's issue of Science Translational Medicine. A team of academic and drug company researchers shows that an engineered "lung-on-a-chip" can not only faithfully model a serious respiratory ailment known as pulmonary edema, but can also accurately predict the toxicity of a compound that causes the disease and the ability of a new drug to prevent it.
Nonclinical drug development studies currently rely on costly and time-consuming animal testing because existing cell culture models fail to recapitulate systems biology, organ-level disease processes in humans. Working in the realm of systems biology and synthetic biology, Harvard and GlaxoSmithKline scientists provide the proof of principle for using a biomimetic microdevice that reconstitutes organ-level lung functions to create a human disease model-on-a-chip that successfully models pulmonary edema. The microfluidic device, which reconstitutes the alveolar-capillary interface of the human lung, consists of channels lined by closely apposed layers of human pulmonary epithelial and endothelial cells that experience air and fluid flow, as well as cyclic mechanical strain to mimic normal breathing motions. This device was used to reproduce drug toxicity–induced pulmonary edema observed in human cancer patients treated with interleukin-2 (IL-2) at similar doses and over the same time frame. 
Professor Ingber, who has long studied mechanical signal transduction, directed this research. Studies using this on-chip disease model revealed that mechanical forces associated with physiological breathing motions play a crucial role in the development of increased vascular leakage that leads to pulmonary edema, and that circulating immune cells are not required for the development of this disease. These studies also led to identification of potential new therapeutics, including angiopoietin-1 (Ang-1) and a new transient receptor potential vanilloid 4 (TRPV4) ion channel inhibitor (GSK2193874), which might prevent this life-threatening toxicity of IL-2 in the future