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According to Aubrey de Grey, SENS (Strategies for Engineered Negligible
Senescence) is a panel of proposed interventions in mammalian aging that “may be sufficiently feasible, comprehensive, and amenable to subsequent incremental refinement that it could prevent death from old age (at any age) within a time frame of decades.” As explained in the foundational SENS paper: “Aging is a three-stage process: metabolism, damage, and pathology.
Intervention in metabolism can only modestly postpone pathology, because production of toxins is so intrinsic a property of metabolic processes that greatly reducing that production would entail fundamental redesign of those processes. Similarly, intervention in pathology is a losing battle if the damage that drives it is accumulating unabated. By contrast, intervention to remove the accumulating damage would sever the link between metabolism and pathology, and so has the potential to postpone aging indefinitely. The term ‘negligible senescence’ (Finch 1990) was coined to denote the absence of a statistically detectable increase with organismal age in a species’ mortality rate.”
Seven major categories of such accumulative age-related damage have thus
far been identified and targeted for anti-aging treatment within SENS. As
late as 2007 the prospective SENS treatment protocols still lacked any serious discussion of future contributions from nanotechnology, an unfortunate omission which is corrected here by adding nanomedicine (medical nanorobotics) to SENS, obtaining “NENS”
Below are two of the seven sections that describe each part of nanotechnology enabled SENS. This builds upon the other sections in the work of Freitas which includes details on each nanotechnology device and the various mechanisms of aging and disease and how to apply nanotechnology to each part of comprehensive rejuvenation.
Medical nanorobots can provide targeted treatments to individual organs, tissues, cells and even intracellular components, and can intervene in biological processes at the molecular level under direct supervision of the physician. Programmable micron-scale robotic devices will make possible comprehensive cures for human disease, the reversal of physical trauma, and individual cell repair.
Removing Extracellular Aggregates
Extracellular aggregates are biomaterials that have accumulated and aggregated into deposits outside of the cell. These biomaterials are biochemical byproducts with no useful physiological or structural function that have proven resistant to natural biological degradation and disposal. Two primary examples are relevant to the SENS agenda.
First, there is the acellular lipid core of mature atherosclerotic plaques – which macrophages attempt to consume, but then die when they become full of the inert indigestible material, adding their necrotic mass to the growing plaques. One proposed SENS solution is to administer a bone marrow transplant of new bone marrow stem cells (cells that produce macrophages) that have been genetically reprogrammed to encode a new artificial macrophage phenotype that incorporates more robust intracellular degradation machinery. The resulting enhanced macrophages could then completely digest the resistant plaque material in the normal manner, though the full course of treatment would require months to run to completion and would likely yield only incomplete genetic substitution of stem cell genomes.
Using NENS, vasculocytes (Section 188.8.131.52) would completely remove plaque deposits in less than a day, providing immediate vascular clearance and healing the vascular walls. For protection against future plaque development, chromallocytes (Section 184.108.40.206) could be targeted to the entire population of bone marrow stem cells to install the proposed more-robust macrophage phenotype using chromosome replacement therapy, in a thorough treatment also lasting less than a day. Second, there are amyloid plaques that form as globules of indigestible material in small amounts in normal brain tissue but in large amounts in the brain of an Alzheimer’s disease patient (Finder and Glockshuber 2007). Similar aggregates form in other tissues during aging and age-related diseases, such as the islet amyloid (Hull et al. 2004) in type 2 diabetes that crowds out the insulin-producing pancreatic beta cells, and in immunoglobulin amyloid (Solomon et al. 2003). Senile Systemic Amyloidosis or SSA (Tanskanen et al. 2006), caused by protein aggregation and precipitation in cells throughout the body, is apparently (Primmer 2006) a leading killer of people who live to the age of 110 and above (supercentenarians). One proposed SENS solution being pursued by Elan Pharmaceuticals to combat brain plaque is vaccination to stimulate the immune system (specifically, microglia) to engulf the plaque material, which would then be combined with the enhanced macrophages as previously described – although anti-amyloid immunization has not had great success experimentally (Schenk 2002; Patton et al. 2006). In NENS, amyloid binding sites could be installed on the external recognition modules of tissue-mobile microbivore-class scavenging nanorobots (Section 220.127.116.11), allowing them to quickly seek, bind, ingest, and fully digest existing plaques throughout the relevant tissues, in the manner of artificial mechanical macrophages. Chromallocytes could again be targeted to phagocyte progenitor cells to install the more robust macrophage phenotype to provide continuing protection against future plaque development.
Among the most promising investigational anti-amyloid therapies for Alzheimer’s disease (Aisen 2005) is another potential SENS treatment for brain amyloid using anti-amyloid plaque peptides – one 5-residue peptide has already shown the ability, in lab rats, to prevent the formation of the abnormal protein plaques blamed for Alzheimer’s and to break up plaques already formed (Soto et al.1998), and to increase neuronal survival while decreasing brain inflammation in a transgenic mouse model (Permanne et al. 2002). However, a major challenge to the use of peptides as drugs in neurological diseases is their rapid metabolism by proteolytic enzymes and their poor blood-brain barrier (BBB) permeability (Adessi et al. 2003). In a NENS treatment model, a mobile pharmacyte-class nanorobot (Section 18.104.22.168) could steer itself through the BBB (Freitas 2003aa); release an appropriate engineered peptide antimisfolding agent (Estrada et al. 2006) in the immediate vicinity of encountered plaques so as to maintain a sufficiently high local concentration (Section 22.214.171.124) despite degradation; re-acquire the agents or their degradation products after the plaque dissolves; then exit the brain via the same entry route. Tissue-mobile microbivore-class devices could also be used to fully digest the plaques if it is deemed acceptable to ignore possible resultant localized deficits of normal soluble unaggregated amyloid-beta peptides. Nanorobots operating in the brain must be designed to accommodate the tight packing of axons and dendrites found there.
Removing Extracellular Crosslinks
While intracellular proteins are regularly recycled to keep them in a generally undamaged state, many extracellular proteins are laid down early in life and are never, or only rarely, recycled. These long-lived proteins (mainly collagen and elastin) usually serve passive structural functions in the extracellular matrix and give tissue its elasticity (e.g., artery wall), transparency (e.g., eye lens), or high tensile strength (e.g., ligaments). Occasional chemical reactions with other molecules in the extracellular space may little affect these functions, but over time cumulative reactions can lead to random chemical bonding (crosslinks) between two nearby long-lived proteins that were previously unbonded and thus able to slide across or along each other. Such crosslinking in artery walls makes them more rigid and contributes to high blood pressure.
The NENS strategy proceeds similarly but more safely, using nanorobots as the delivery vehicle for the link-breaking molecules. In the first scenario, a population of ~10^12 (1 terabot) mobile pharmacytes would transverse the extracellular matrix in a grid pattern, releasing synthetic single-use deglycating enzymes (perhaps tethered (Craig et al. 2003; Holmbeck et al. 2004) to energy molecules, e.g., ATP) into the ECM to digest cross-linkages, then retrieving dispensed molecules before the nanorobot moves out of diffusive range. As an example, human skin and glomerular basement membrane (GBM) collagen has ~0.2 glucosepane (MW ~500 gm/mole) crosslinks per 100,000 kD strand of collagen in normally crosslinked aging tissue (Sell et al. 2005), indicating ~2 × 10^18 glucosepane crosslinks in the entire human body which will require a very modest whole-body treatment chemical scission energy of ~0.2 joule per each ATP-ADP conversion event (~0.5 eV) required to energize cleavage of individual crosslink bonds. Each nanorobot would contain ~2 × 10^6 enzyme molecules in a ~1 micron3 onboard tank and would travel at ~3 micron/sec through ECM, releasing and retrieving enzymes in a ~10 micron wide diffusion cloud over a ~100 sec mission duration, with 10 successive terabot waves able to process all ~32,000 cm3 of ECM tissue in the reference 70 kg adult male body in a total treatment time of ~1000 sec. Only 1 of every 10 enzymes released and retrieved are discharged by performing a crosslink bond scission; the rest are recovered unused. This treatment would likely be complete because full saturation of the targeted tissue volume can probably be achieved via diffusion, though some enzyme molecules may exit the diffusion cloud and become lost – lost molecules that must produce no side effects elsewhere or must be safely degradable via natural processes. In the second scenario, assuming ~10^19 collagen fibers in all ECM and allowing ~10 sec for a nanorobot to find and examine each fiber (thus removing one crosslink every ~50 sec), then ~10^14 nanorobots (~0.3% by volume of ECM tissue) using manipulators with enzymatic end-effectors could patrol ECM tissues, seeking out unwanted crosslink bonds and clipping them off, processing ~1 cm3/min of crosslinked tissue and finishing the entire body in ~22 days. Enzymatically active components remain tethered and cannot be lost, reducing side effects to near-zero, but there may be some tight spaces that cannot easily be reached by the manipulator arms, possibly yielding an incomplete treatment. Further study is needed to determine the optimal combination of these two strategies.
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