Fixing Death v1.0-Identifying reasons for death

In our quest to find solutions to every aspect of error and degradation (wear and tear) that cumulatively leads to human death, we have arrived at an initial map that plots the possible causative errors with respect to cell death.

We believe that it is critical to create an integrated and holistic view, wherein it is paramount to correlate all of the factors that lead to the survival and enhancement of the longevity of cellular mechanisms, inclusive of the damage or degradation that may occur through various traumatic or pathogenic pathways.

Introduction and Approach

We believe that the state of being alive may be reduced to an elegantly orchestrated synchronized automation of micro events (primarily stimuli and induced responses). The expansion of a single cell to a massive cell complex based on inherent rules is testimony to the fact that we are largely automated soft “machines” that functionally perform very well, with the proviso that all processes are operating optimally, and not being hindered by corrupt code or untoward redundancies, or even a lack in supply of necessary functional elements.

If we take an average life span to be 70 years, one can observe that automation has worked efficiently enough for 70 long years; all starting from a single cell. A thorough understanding of the unifying concepts that are involved in this automation should easily assist us in performing well for a 100 years more! This may be accomplished through the monitoring of this automation, combined with application of specific predictive and preventive strategies.

We have already seen proof of humans who have lived for approximately 120+ years. We may consider these instances of such automation must be very well optimized, and it can be attributed to the repair capabilities of one’s immune system. The cells of centenarians were found to contain characteristics typical of those from younger people, who have significantly higher activity in their DNA repair mechanism. This study was based on lymphoblastoid cell lines that were established from blood samples of humans who had lived beyond 100 years of age.

To put this automation in further perspective, human beings and other cellular species are  machines (at a fundamental level) that grow from a base framework of rules that have been acquired from a host combination. These rules (patterns) determine the function and progress of the machine.

It is in our interest to assist the body to play within these rules, such that we may experience qualitatively enhanced life for many more years; all through the maintenance of optimal performance.

Our optimized systems come with inbuilt automated repair systems that are capable of addressing errors and malfunctions with less complexity and severity. However, when these unfortunate errors occur consistently, or accumulate in the system, they fail to manage the repair routines effectively, thus leading to the degradation of performance.

Hence, it is critical to identify the key parameters that are responsible for these errors and further, to be able to provide adequate support to the repair systems to facilitate improvements in the management of errors, thereby augmenting performance to match optimal parameters.

Targeting the cell

In order to address these challenges, we targeted the cell, which is the primary component of this automation. Our initial step was to break the cell down to its fundamental constituents, life cycle, macro functions, and the deviations that lead to their breakdown.


An initial exercise was to investigate the pathways of automation, proceeding from initiation (birth) to termination (death). The cell duplication process may be considered to be a critical process, which continuously cycles in order to keep the system functioning. The capacity of this process is currently set to 50 such cycles (Hayflick Limit), before the process loses a necessary component (telomere), which halts the cycle (senescent stage). Since the component loses its performance, it becomes redundant and another rule is executed to clear the accumulated redundancy and to replace it with a new component to maintain continuity.

If no duplication errors occur, every cell will be able to perform this 50-cycle loop prior to reaching their termination stage. Considering all current parameters, this would constitute the most optimal path to achieve in toward realizing the full utilization of the machine.

Since there are also external factors that influence this automation, duplication errors are invariably encountered. Though the process is backed by repair checks, there is the possibility that certain errors may not be repaired. Based on the possibility of causing further cascading errors the automation process may be halted (senescent) or terminated without utilizing the full potential of this automation, as shown.


This macro automation exposes two primary issues that need to be resolved in order to maintain continuity and integrity in the automation.

  • Making sure that replication errors are fully resolved to thereby ensure a viable code to continue the cycle to its limit capacity.
  • Prolonging the limit capacity.

Having these parameters under our control should enable us to manage the entire automation in order to achieve the goals of youthful and healthy longevity. In order to achieve solutions to help resolve the above limitations it would be necessary to understand all of the sub-rules and processes involved.

Apart from replication, the cell is programmed to perform a specific set of unique tasks when expressed. The initiated cells are guided by a set of protocols for the generation of specific materials that are important for the orchestration of the cell community.

The initiated cell contains an inherent error correction program for self repair. It also comes with a distinct scalable process to assist with the generation of energy in order to execute all the known  processes of replication, production, and repair.  There are ~200 such cells that perform specific tasks to coordinate the well-being and continuity of the cell community (the entire body).

These sub-processes reveal micro-processes that are involved in the performance of smaller tasks. The tracking and management of these processes can give us control required to achieve our primary objective.

(1) Mediating the grow/stop signaling function in the duplication/replication process

(2) Monitoring and managing the complete production line covering steps from Transcription > Translation > Protein construct > Micro-arrays > Package out > Target location > Delivery > Feedback. Any small failures in this process may initiate error paths.

(3) Ability to supervise the repair processes in a self-learning model that will build new responses to stress. The ability to include unavailable responses will give us more control.

Understanding each process down to its molecular level through its behavior is optimal for elucidating all of the processes that this finite machine is capable of.

In order to achieve our objective, we may work our way up in reverse through the identification of possible causes of cell death, while developing viable fixes in order to maintain continuity. The purpose of the diagram below is to articulate a holistic blueprint that depicts the breakdown of the autonomous nature of functional physiological processes within the human body.

The showcased diagram focuses on cell death, which is the primary basis for the degeneration of the body, along with the various underlying process errors that are instrumental toward cell death. The area highlighted in green conveys the typical checkpoints where solutions might be formulated through the monitoring and design of fall-back mechanisms. However, autophagy and apoptosis are complimentary processes, as they are natural mechanisms for optimized corporeal performance; thus they need not be prioritized.


Favorable processes such as autophagy (clearing redundancies) and apoptosis (avoiding redundancies) are inbuilt to compliment the automation process. Other aspects that lead to death require serious resolution. One may describe these “bugs” as listed below:

  • Machinery or component damage (structural damage) – external and internal protection techniques.
  • Underperformers due to corruption of code and loss of duplication capabilities (senescence) – code cleanup, lengthening of telomeres, or the induction of auxiliary energy supplies employing nanomedical techniques.
  • Code – rule mismatches (autoimmune diseases and cancer) – code or rule corrections.

Other issues we face pertain to the cleanup activities of past redundancies, which have already accumulated, in order to reestablish optimal machine functionality. We arrived at this diagram so as to make it easier to visualize and focus on the resolution of encountered problems, via connecting all of the many distinct silos in current research.

This formative map above has been created with the primary intent of obtaining feedback from other users, as there will likely be areas that might have been overlooked in its rendering.  Should readers find anything that has been overlooked, notice any flow corrections that are required, or wish to suggest an alternate or simpler representative style, we welcome you to post your comments. We will judiciously incorporate and publish them in the next iteration of the chart.


One thought on “Fixing Death v1.0-Identifying reasons for death

  1. Pingback: Precise Health Insights Using Unified Semantic Data Model – QuahogLife

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