Northwestern University researchers have developed a new injectable therapy that harnesses “dancing molecules” to reverse paralysis and repair tissue after severe spinal cord injuries. In a new study, researchers administered a single injection to tissues surrounding the spinal cords of paralyzed mice. Just four weeks later, the animals regained the ability to walk.

By sending bioactive signals to trigger cells to repair and regenerate, the breakthrough therapy dramatically improved severely injured spinal cords in five key ways: The severed extensions of neurons, called axons, regenerated. Scar tissue, which can create a physical barrier to regeneration and repair, significantly diminished. Myelin, the insulating layer of axons that is important in transmitting electrical signals efficiently, reformed around cells. Functional blood vessels formed to deliver nutrients to cells at the injury site. More motor neurons survived.
After the therapy performs its function, the materials biodegrade into nutrients for the cells within 12 weeks and then completely disappear from the body without noticeable side effects. This is the first study in which researchers controlled the collective motion of molecules through changes in chemical structure to increase a therapeutic’s efficacy.

“Our research aims to find a therapy that can prevent individuals from becoming paralyzed after major trauma or disease,” said Northwestern’s Samuel I. Stupp, who led the study. “For decades, this has remained a major challenge for scientists because our body’s central nervous system, which includes the brain and spinal cord, does not have any significant capacity to repair itself after injury or after the onset of a degenerative disease. We are going straight to the FDA to start the process of getting this new therapy approved for use in human patients, who currently have very few treatment options.”

Stupp is Board of Trustees Professor of Materials Science and Engineering, Chemistry, Medicine and Biomedical Engineering at Northwestern, where he is founding director of the Simpson Querrey Institute for BioNanotechnology (SQI) and its affiliated research center, the Center for Regenerative Nanomedicine.

Source: https://news.northwestern.edu/

The cerebral cortex is the thin surface layer of the brain found in vertebrate animals that has evolved most recently, showing the greatest variation in size among different mammals (it is especially large in humans). Each part of the cerebral cortex is six layered (e.g., L2), with different kinds of nerve cells (e.g., spiny stellate) in each layer. The cerebral cortex plays a crucial role in most higher level cognitive functions, such as thinking, memory, planning, perception, language, and attention. Although there has been some progress in understanding the macroscopic organization of this very complicated tissue, its organization at the level of individual nerve cells and their interconnecting synapses is largely unknown.

Petabyte connectomic reconstruction of a volume of human neocortex. Left: Small subvolume of the dataset. Right: A subgraph of 5000 neurons and excitatory (green) and inhibitory (red) connections in the dataset. The full graph (connectome) would be far too dense to visualize.

Mapping the structure of the brain at the resolution of individual synapses requires high-resolution microscopy techniques that can image biochemically stabilized (fixed) tissue. We collaborated with brain surgeons at Massachusetts General Hospital in Boston (MGH) who sometimes remove pieces of normal human cerebral cortex when performing a surgery to cure epilepsy in order to gain access to a site in the deeper brain where an epileptic seizure is being initiated. Patients anonymously donated this tissue, which is normally discarded, to our colleagues in the Lichtman lab. The Harvard researchers cut the tissue into ~5300 individual 30 nanometer sections using an automated tape collecting ultra-microtome, mounted those sections onto silicon wafers, and then imaged the brain tissue at 4 nm resolution in a customized 61-beam parallelized scanning electron microscope for rapid image acquisition.

Imaging the ~5300 physical sections produced 225 million individual 2D images. The team then computationally stitched and aligned this data to produce a single 3D volume. While the quality of the data was generally excellent, these alignment pipelines had to robustly handle a number of challenges, including imaging artifacts, missing sections, variation in microscope parameters, and physical stretching and compression of the tissue. Once aligned, a multiscale flood-filling network pipeline was applied (using thousands of Google Cloud TPUs) to produce a 3D segmentation of each individual cell in the tissue. Additional machine learning pipelines were applied to identify and characterize 130 million synapses, classify each 3D fragment into various “subcompartments” (e.g., axon, dendrite, or cell body), and identify other structures of interest such as myelin and cilia. Automated reconstruction results were imperfect, so manual efforts were used to “proofread” roughly one hundred cells in the data. Over time, the scientists expect to add additional cells to this verified set through additional manual efforts and further advances in automation.

Source: https://ai.googleblog.com/