How best to scientifically prove aging reversal with a #RealisticVirtualEarthForAgingReversal in say drosophila species w an adult fly and a juvenile drosophila fly, sliding betw them, and by adding this to actual physical biological drosophila flies?https://t.co/0Voup2MqAw ~
— WorldUnivandSch (@WorldUnivAndSch) June 26, 2026
https://x.com/WUaSPress/
Scientifically proving aging reversal by bridging a 4D Virtual Earth simulation with physical biological experiments in Drosophila melanogaster requires a systematic, closed-loop approach.
Here is a framework for how such an experiment can be structured using connectomics, multi-omics, and machine learning:
1. Constructing the 4D Virtual Twin (The Simulation)
To create a "sliding scale" between a juvenile and an adult fly, researchers leverage high-resolution structural and molecular maps to isolate the biomarkers of aging.
Mapping the Connectome Scaffold: Use the
dataset (which maps over 139,000 neurons and 50 million synapses) as the baseline 3D structural model.FlyWire connectome Layering the "Time Slider" (Transcriptomics): Overlay single-cell RNA sequencing (scRNA-seq) data from Drosophila at different life stages (e.g., day 1 juvenile vs. day 50 aged adult). This allows the AI to catalog which genes turn off or on, and which synaptic connections degrade over a timeline.
Identifying Master Regulatory Nodes: Focus the virtual model on the brain's "command and control" centers for systemic aging, such as the Insulin-Producing Cells (IPCs) in the pars intercerebralis, which regulate longevity-associated insulin-like peptides.
2. In Silico Reversal (The "Slide" Experiment)
Before moving to physical flies, computational models simulate the exact interventions needed to reset an old brain to a younger state.
Algorithmic Regression: Using machine learning models (built via frameworks like TensorFlow), researchers computationally "slide" the adult fly brain back to a juvenile state. The AI identifies the exact delta—the specific proteins, neurotransmitter densities, and gene expression patterns that changed.
Generative Target Discovery: Generative AI tools predict chemical or genetic interventions (such as specific CRISPR targets or synthetic neuropeptides) capable of forcing an adult neural network to mirror the connectivity and expression profile of a juvenile network.
3. In Vivo Validation (The Physical Experiment)
The final, critical proof requires taking the computational insights generated in the virtual environment and applying them to living, biological fruit flies.
[Virtual 4D Connectome] ➔ [AI Identifies Aging Delta] ➔ [Targeted In Vivo Interventions] ➔ [Quantified Reversal Proof]
Targeted In Vivo Interventions: Apply the AI-predicted changes to a cohort of aging physical flies. This can be achieved through:
Conditional Gene Activation: Using the GAL4/UAS system to selectively turn on "youth" genes or downregulate inflammatory genes in the identified command-center neurons of living adult flies.
Neuroendocrine Therapeutics: Administering synthesized compounds or neuropeptide analogs designed in the simulation to stabilize aging synapses.
Quantifying Actual Aging Reversal: To prove the reversal is genuine, the treated physical flies must be evaluated against clear metrics:
Functional Rejuvenation: Testing if motor functions (like climbing assays) and circadian rhythms return to juvenile baselines.
Lifespan Extension: Verifying if the biological clock has been reset by measuring significant increases in remaining life expectancy compared to untreated controls.
Post-Mortem Histology: High-resolution imaging of the treated adult flies to confirm that structural synaptic decay was physically halted or reversed to match the juvenile topology.
Would you like to explore the specific neuropeptide pathways or genetic tools (like the GAL4/UAS system) used to manipulate these target neurons in physical flies?
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#ScientificallyProve #AgingReversal w #FlyConnectome & @harvardmed & WUaS Academic Medical Center in a #RealisticVirtualEarthForAgingReversal?
#ScientificallyProve #AgingReversal w #FlyConnectome & @harvardmed? How best could @WorldUnivAndSch in a #WUaSMultimediaHospitalRoom (think #GStreetView w #GTimeSlider & #GCellView & #GeminiAI) in #Canyon94516 using https://t.co/5TeYZbOw8h#ReverseAging @geochurch @lucapinello ? https://t.co/WTz0qNN4NQ
— Scott - sgkmacleod@worlduniversityandschool.org (@scottmacleod) June 24, 2026
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add #juvenileFruitFlyBrain AND #adultFruitFlyBrain fr #FlywireConnectome to #GStreetView w #GTimeSlider & slide between, then code these w #GPegman as #Drosophila #AvatarAgentEHR then upload #juvenileFlyBrain #GCells or #GMolecules to #physicalAdultFly to #ReverseAging experiment https://t.co/kMdTQmzY7M
— HarbinBook (@HarbinBook) June 22, 2026
WOW: Take a flight through The BANChttps://t.co/w7IP4oivOo &#AgingReversalGenetics w #DrosophilaFly fr adult to juvenile re brains:https://t.co/CiIQ4xol8q
— WUaSPress (@WUaSPress) June 21, 2026
How #WUaSunivs to do this in #RealisticVirtualEarthForAgingReversal in #GStreetView w #GTimeSlider w #FlywireConnectome ?
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How to search across datasets in FlyWire Codex +
#FlywireConnectome - are (or could be) scientists mapping ALL cells & molecules & genes ... & how to develop this for aging reversal and extreme longevity genetic drug therapies, and in a #RealisticVirtualEarth?
https://x.com/Q_YogaMacFlower/
https://x.com/WorldUnivAndSch/
https://x.com/sgkmacleod/
https://x.com/WUaSPress/
https://x.com/scottmacleod/
https://x.com/HarbinBook/
https://x.com/sgkmacleod/
https://x.com/WUaSPress/
https://x.com/scottmacleod/
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Retweeting -
Michael Andregg
@michaelandregg
·
Mar 8
We've uploaded a fruit fly. We took the
@FlyWireNews
connectome of the fruit fly brain, applied a simple neuron model (
@Philip_Shiu
Nature 2024) and used it to control a MuJoCo physics-simulated body, closing the loop from neural activation to action.
A few things I want to say about what this means and where we're going at
@eonsys
.

https://x.com/michaelandregg/
https://mujoco.readthedocs.io/
as the Flywire connectome mapping wiring model diagram of the drosophila melanogaster fruit fly develops and continues are they and citizen scientists mapping both cells and molecules and genes of the fruit flies brain
are scientists mapping all cells and molecules and jeans of the fruit flies brain drosophila melanogaster and as the Flywire connectome project wiring model diagram of drosophila melanogaster develops and how to add this to a realistic virtual Earth in Google Street View with time slider Google Maps and Gemini and tensorflow AI
how after adding the Flywire connectome and all cells and molecules and genes of a fruit flies brain to something like Google Street View and importantly with time cider in a realistic virtual Earth to begin to develop both aging reversal and extreme longevity machine learning predictions with even developing new proteins synthesized proteins and genes
The FlyWire project has successfully mapped all 139,255 neurons and over 50 million synapses in the adult Drosophila brain. While the primary "wiring diagram" is based on electron microscopy (EM) images of cells, the project is rapidly expanding to include molecular and genetic data.
What is being mapped:
Cells: Every individual neuron has been traced and categorized into over 8,400 cell types.
Molecules (Neurotransmitters): AI models have predicted the specific neurotransmitters (e.g., dopamine, glutamate, GABA) for every synapse in the brain.
Genes: Researchers are currently overlaying single-cell RNA sequencing (scRNA-seq) data onto the connectome. This allows them to see which specific genes are "turned on" in different parts of the wiring diagram.
The Role of Citizen Scientists:
Citizen scientists and gamers (through platforms like Eyewire) have been essential for proofreading the AI's work. They identify where the AI mistakenly broke a branch or fused two separate cells together, ensuring the map is anatomically perfect.
Would you like me to explain how they use scRNA-seq to match genes to specific neurons in the map?
es, scientists have achieved monumental milestones in mapping the Drosophila melanogaster brain. As of March 2026, we have moved beyond just "wiring" to a full multi-omic understanding of the fly.
1. The Mapping Milestones
The Connectome: The FlyWire project has successfully mapped the full adult female and male brains, detailing over 140,000 neurons and 50 million synapses.
The Molecular Atlas: Researchers (notably from Oxford in early 2026) released a high-resolution molecular atlas capturing transcriptional data (gene expression) for nearly every individual neuron.
The "Digital Fly": Scientists have now integrated these maps into whole-brain emulations where virtual flies can execute motor commands and "behave" in simulated environments.
2. Integration: Google Maps, Gemini, and TensorFlow
While there is no "one-click" button to put a fly brain in Google Street View, you can bridge these technologies using the following workflow:
| Component | Role in Your Project |
| FlyWire/CAVE API | Access the raw 3D mesh and synaptic data via Python. |
| TensorFlow | Use the Keras API to train neural networks that predict behavior based on the connectome's wiring patterns. |
| Gemini API | Use Grounding with Google Maps to anchor your "virtual fly" to real-world coordinates and use Gemini to narrate the fly's sensory experience. |
| Google Maps SDK | Use Three.js or WebGL overlays to render the 3D fly brain model directly "inside" a Street View panorama at specific GPS coordinates. |
How to Build It:
Extract Data: Use the
CAVEclientPython library to pull neuron morphologies from FlyWire.Process with AI: Input this connectivity matrix into TensorFlow to simulate signal propagation.
Spatial Mapping: Use the Google Maps JavaScript API to place a 3D model of the fly brain at a specific location. Use the Time Slider (via the
streetView.setLinksor custom overlays) to show how the "brain state" changes over a timeline.Interface with Gemini: Feed the fly's "visual input" (derived from Street View images) into Gemini to describe what the fly "sees" or "decides" to do.
Would you like me to generate a Python starter script to help you connect to the FlyWire API and begin processing neuron data?
Integrating the FlyWire connectome (139,255 neurons) into a 4D virtual environment with "time sliders" allows you to treat the brain as a dynamic, interactive dataset. By mapping molecular and genetic layers onto this 3D scaffold, you create a "Digital Twin" of the fly.
1. Building the Multimodal Atlas
To achieve this, researchers use Neuroglancer (the engine behind the "Street View" experience) to overlay different data types:
Transcriptomics: Mapping gene expression (which genes are "on") to specific coordinates.
Connectomics: The wiring diagram showing how signals travel.
Molecular Layer: Tracking neurotransmitters and proteins at each synapse.
2. Predictions for Aging and Longevity
The "time slider" represents a Biological Clock. By training machine learning models on fly brains at different ages (e.g., day 1 vs. day 50), the AI can:
Identify Structural Decay: Find which synaptic connections weaken first.
Spot Genetic Shifts: Detect which genes "turn off" as the fly ages.
Reverse-Simulation: Use the AI to "roll back" the digital state of an old brain to a young one, identifying the specific molecular changes needed for rejuvenation.
3. Synthesizing New Proteins and Genes
Once the AI understands the "rejuvenation path," it can use Generative AI (like AlphaFold-derived models) to:
Design Proteins: Create synthetic proteins that stabilize aging synapses.
Gene Editing: Predict CRISPR targets to overwrite age-related genetic decline.
Virtual Testing: Instead of years of lab tests, you "apply" these new proteins to the virtual fly and observe if its behavior and neural health improve in the simulation.
Would you like me to find specific software tools used to simulate these neural-molecular interactions?
To map the "command and control" of aging using the FlyWire connectome, you must bridge the gap between fixed wiring and the chemical signals that orchestrate systemic decay.
1. The Brain as an Aging Control Center
The brain regulates aging across the body primarily through the endocrine system and the gut-brain axis.
Neurosecretory Cells: In Drosophila, specific neurons (like Insulin-Producing Cells or IPCs) act as the master controllers. They sense nutrients and release hormones like Insulin-like Peptides (dILPs) into the hemolymph (fly blood), which then signal tissues to grow, repair, or age.
Hypothalamic-Like Circuits: Just as the human hypothalamus governs systemic homeostasis via the pituitary gland, the fly's pars intercerebralis and corpora allata regulate Juvenile Hormone (JH), a key longevity determinant.
2. Mapping the "Aging Command" in FlyWire
The FlyWire connectome provides the structural "hardware," but mapping the "aging software" requires adding 4D layers:
Synaptic Plasticity Shifts: Use the "time slider" to identify neurons that lose connection density as the fly ages. The connectome allows you to see if the "Control Center" circuits (like those connecting the gut to IPCs) physically degrade or rewire over time.
Peptidergic Overlay: Since aging is chemical, you must map neuropeptide receptors onto the connectome nodes. This identifies which "Street View" paths are actually transmitting "aging instructions" via hormones rather than electric spikes.
Transcriptomic Integration: By mapping single-cell RNA sequencing data onto the FlyWire coordinates, you can see which specific neurons are expressing "aging genes" (like those for inflammation or oxidative stress) at different life stages.
3. Machine Learning for Longevity Predictions
With this 4D model, machine learning can:
Identify Critical Nodes: Pinpoint the exact neurons whose "silencing" or "activation" triggers systemic rejuvenation.
Protein Synthesis: Predict new, synthetic versions of Neuropeptide F (NPF) or insulin analogs that could be "injected" into the virtual model to stabilize the aging clock.
Human Translation: Because the insulin and circadian circuits are highly conserved, a successful "longevity hack" in the fly brain can suggest specific hypothalamic targets for human gene therapy or drug development.
Would you like to explore the specific neuropeptide receptors that act as the "switches" for these longevity pathways?
*
1)
add #juvenileFruitFlyBrain AND #adultFruitFlyBrain fr #FlywireConnectome to #GStreetView w #GTimeSlider & slide between, then code these w #GPegman as #Drosophila #AvatarAgentEHR then upload #juvenileFlyBrain #GCells or #GMolecules to #physicalAdultFly to #ReverseAging experiment
https://x.com/WorldUnivAndSch/
https://x.com/Q_YogaMacFlower/
https://x.com/scottmacleod/
https://x.com/TheOpenBand/
Retweeting -
WOW: Take a flight through The BANC
https://youtu.be/op_OwSRY6SI &
#AgingReversalGenetics w #DrosophilaFly fr adult to juvenile re brains:
https://share.google/aimode/
How #WUaSunivs to do this in #
https://x.com/WUaSPress/
2)
AND
Retweeting WUaS Press -
add #juvenileFruitFlyBrain AND #adultFruitFlyBrain fr #FlywireConnectome to #GStreetView w #GTimeSlider & slide between, then code these w #GPegman as #Drosophila #AvatarAgentEHR then upload #juvenileFlyBrain #GCells or #GMolecules to #physicalAdultFly to #ReverseAging experiment
https://x.com/WUaSPress/
https://x.com/sgkmacleod/
https://x.com/HarbinBook/
Retweeting -
WOW: Take a flight through The BANC
https://youtu.be/op_OwSRY6SI &
#AgingReversalGenetics w #DrosophilaFly fr adult to juvenile re brains:
https://share.google/aimode/
How #WUaSunivs to do this in #
https://x.com/WUaSPress/
https://x.com/WUaSPress/
https://x.com/HarbinBook/
https://x.com/scottmacleod/
https://x.com/Q_YogaMacFlower/
https://x.com/sgkmacleod/
https://x.com/TheOpenBand/
Connectome Influence Calculator
Authors/Creators
* * *
~ https://goo.gl/maps/
~ https://goo.gl/maps/
Scott MacLeod's
Naked Harbin Ethnography:
Hippies, Warm Pools, Counterculture, Clothing-Optionality & Virtual Harbin
by Scott MacLeod
sgkmacleod@
Foreword by Nelson H.H. Graburn
UC Berkeley Professor Emeritus of Sociocultural Anthropology
http://www.scottmacleod.com/
Academic Press at World University and School
http://
Wednesday, June 24, 2026
Thursday, June 18, 2026
Mentha aquatica: Restorative Yoga class on Saturdays (and as we may live to 150 and well beyond:) ~ 1 Having just seen Hank Greely's (Stanford Law and by courtesy a genetics' Professor) Twitter post about countercultural thinker (re The Whole Earth Catalog +) Stewart Brand's "fatal Idiopathic pulmonary fibrosis," I retweeted this to @HarbinBook and wonder how Yoga asana can help (and see the PS below re a question I asked Gemini about this, and much more) ~
--
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https://en.wikipedia.org/wiki/Red_flour_beetle
https://species.wikimedia.org/wiki/Tribolium_castaneum
https://en.wikipedia.org/wiki/Flour_beetle
species similar to drosophila flies colorful can be used for experiments - Japanese beetles?
https://share.google/aimode/yPwUREoPGPgVop1Rh
....


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