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    • Figure 1. 

      Framework overview of cytoskeletal checkpoints as state-control nodes in the aging microglial targetome. (a) Microglial state transition under aging stress: young/homeostatic microglia (ramified, cool blue) shift to aged/dystrophic microglia (coral red) as aging proceeds, with amyloid and vascular burden acting as the disease-stage context. Sex is enforced as a mandatory covariate at every tier of the framework (gold-bordered badge). (b) Six cytoskeletal checkpoints organised by evidence tier: Pfn1, Rho GTPase network, and Cdk1/MT remodelling enter the Validated tier (solid borders) with Evidence-Tier Scores of 2.5, 4.0, and 2.0, respectively; Arp2/3 complex, Piezo1, and the actomyosin-podosome surveillance module enter the Candidate tier (dashed borders) with ETS values of 1.5, 1.0, and 1.0. (c) The Bayesian-style prior π(node) follows the two-tier normalisation rule (Validated: ETS/8.5; Candidate: ETS/17.0), giving per-node weights of 0.29 (Pfn1), 0.47 (Rho GTPase), 0.24 (Cdk1/MT), 0.09 (Arp2/3), 0.06 (Piezo1), and 0.06 (actomyosin–podosome). The sex-by-context routing grid (Male/Female × Aging/AD) maps to the H-A directional working hypothesis (male = Rac1-PAK2/CFL1 surveillance failure) and H-B (female = RhoA/ROCK contractility-rigid state), with the full per-cell sex-stratified ETS matrix and the eight directional hypotheses H-A through H-H in Supplementary Table S1. (d) Mixed-pathology routing and MVP validation: amyloid-burden and vascular-burden context gates re-weight the six-node ETS prior and up- or down-weight the relevant directional hypotheses; the resulting prior is then tested through the single-endpoint mCytoMAP MVP validation pathway, selection of a single sex-stratified ETS-anchored readout, testing in independent cohorts with sex stratification, and Bayesian update of node evidence tiers and priors. Sex covariate enforcement is mandatory in all routing, weighting, and validation steps.

    • Figure 2. 

      Pfn1 and Arp2/3 as the two anchor cytoskeletal checkpoints of the cascade-class distinction framework. (a) The Pfn1 cascade: actin-monomer-handling failure drives sequential decoupling of actin-microtubule coordination, ERK/NF-κB activation, SASP elaboration (IL-1β, TNF-α, MMP9), and selective parvalbumin-positive (PV+) interneuron failure through combined MMP9-driven perineuronal-net proteolysis and cytokine-driven bioenergetic stress on fast-spiking interneurons; mechanistic anchors are the adult-onset microglia-specific Pfn1-cKO[11], microglial PNN proteolysis in AD brain[34], and PNN-buffered PV+ redox protection[35]. (b) The Arp2/3 cascade: branched-actin nucleation failure aborts TGFβ receptor trafficking, excludes phospho-SMAD2/3 from the nucleus, collapses the homeostatic transcriptional program (P2RY12, TMEM119, Cx3cr1, Sall1 loss), and drives DAM-like state entry with APOE/Ms4a7 gain and myelin-phagocytic bias; mechanistic anchor is conditional Arpc4-KO microglia[12]; constitutive Cx3cr1-Cre, so developmental and adult-onset contributions remain confounded, see Limitations. (c) The two cascades converge on shared functional endpoints, loss of surveillance, AD-associated gene upregulation, and injury-directed motility failure, through divergent mechanistic intermediates (NF-κB/SASP for Pfn1; TGFβ/SMAD for Arp2/3). The framework prediction is that cascade class, not the specific molecule, determines the circuit-level endpoint: inhibitory synaptic vulnerability for NF-κB/SASP-elaborating cascades, and white-matter/DAM phenotype for TGFβ/SMAD-collapsing cascades. (d) The discriminating experiment is a side-by-side adult-onset, microglia-specific Pfn1-cKO vs Arpc4-cKO comparison (sex-stratified) with five matched cortical readouts, MMP9 zymography, perineuronal-net integrity (WFA/aggrecan around PV+ cells), PV+ firing-fidelity together with mitochondrial respiration on PV-sorted cells, gamma-band local field potential power, and TGFβ/SMAD phosphorylation together with the homeostatic gene panel. The predicted-outcome matrix (cool blue = Pfn1-cKO cascade-positive; coral red = Arpc4-cKO cascade-positive) operationalises framework falsifiability: statistical equivalence of the two knockouts' multivariate readout profiles, tested within pre-specified margins under a genotype × sex model, would refute the cascade-class distinction. This experiment has not yet been performed.

    • Figure 3. 

      Computational architecture, minimum viable product, and biophysical next-step extension of mCytoMAP. (a) mCytoMAP architecture organised in three layers and nine components (Supplementary Box 4). The Input layer carries the CytoState token (a learned multi-omic embedding of actin-microtubule coordination state). The Data-driven L(node|data) layer carries five components: cyto-state gap, susceptibility index, module drift, conditional entropy, and the multi-modal validation layer (live imaging + phosphoproteomics + electrophysiology). The Anchor layer carries the literature-derived Evidence-tier prior πnorm(node). The Synthesis layer carries the posterior priority Pposterior(node) $\varpropto $ πnorm(node) × L(node|data). Sex is a mandatory covariate at every layer. (b) The MVP single-endpoint validation pipeline (Supplementary Box 5b): four atlas inputs (Allen Brain Cell Atlas[43]; SEA-AD MTG[44]; ImmGen Aging[45]; Hammond developmental-adult mouse atlas[40]) → cytoskeletal-module Z-score → CytoState token training → held-out Pfn1-cKO morphodynamic-recurrence-quartile prediction (Portugal et al.[11]) → macro-average AUC ≥ 0.75 (sex-stratified, inverse-frequency class-weighted). Stop/go/ warning criteria are stated alongside the 12–18-month single-laboratory timeline; the bridge from snRNA-seq training to live-imaging validation is unpaired but class-matched (cross-modal). (c) The two-tier Bayesian-style prior πnorm(node) under the current rubric. Validated tier (cool blue solid bars; πnorm = ETS/ΣvalidatedETS = ETS/8.5): Rho GTPase network 0.47 (highest prior weight), Pfn1 0.29, Cdk1/MT 0.24 (sum = 1.00). Candidate tier (dashed teal bars; πnorm = ETS/(2 × Σvalidated ETS) = ETS/17.0): Arp2/3 0.09, Piezo1 0.06, actomyosin-podosome 0.06 (sum = 0.21). The two-tier prior is frozen across the MVP validation cycle; Bayesian updating resumes only after MVP closure. Falsifiability criterion: operational Spearman rank correlation ρ between ETS(node) and held-out Pposterior(node) across the six nodes must satisfy ρ ≥ 0.6 with P < 0.05 by two-sided permutation (n = 6 nodes; n_permutations = 720). (d) FUTURE SCOPE biophysical/ODE next-step extension, not in the current MVP. The mCytoMAP transcriptomic state (CytoState token) feeds a state-to-parameter map φ: CytoState → θ_bio = (σ_active, k_pol, κ_MT, γ_cortex, k_sub, n_adh), implemented as a supervised regression, a Gaussian-process emulator or neural-network surrogate trained on jointly acquired transcriptomic and biophysical reference cohorts, that maps each cytoskeletal-checkpoint node onto a unit-bearing mesoscale active-gel parameter: RhoA/ROCK activity → active cortical contractility σ_active (Pa); Arp2/3 and Pfn1 fluxes → effective filament polymerisation rate k_pol ([µmol·L−1]−1·s−1); Cdk1/MT remodelling → microtubule bending rigidity κ_MT (N m2); Piezo1 and adhesion activity → cortical tension γ_cortex (N m−1) and substrate-coupling stiffness k_sub (Pa m−1); actomyosin–podosome module → focal-adhesion density n_adh (µm−2). These parameters drive a coupled ODE/PDE active-gel protrusion model with explicit constitutive structure, overdamped force balance $\triangledown \cdot \sigma $_total + f_act − ξ u = 0 (inertia negligible in the cellular low-Reynolds-number regime), where u is the cytoplasmic velocity field (µm s−1), σ_total = σ_visc + σ_active the total stress tensor combining viscous (σ_visc = η$\triangledown $u) and active (σ_active = θ_bio[0]) contributions, f_act the local protrusive force density from barbed-end polymerisation, and ξ the cell-substrate friction; G-actin monomer-concentration dynamics ∂_t [G] = −k_pol·[G]·[B] + k_off·[B] + S_pool, where [B] is the free barbed-end concentration, k_pol the elongation rate, k_off the depolymerisation rate, and S_pool the Pfn1-gated monomer-release source, whose actin-network, crosslinker, and focal-adhesion topology produces outputs directly comparable to live morphodynamic readouts: protrusion speed, morphodynamic recurrence, shape persistence, and force-displacement curves. Polymerisation kinetics anchors: barbed-end addition rate k+ ≈ 11.6 (µmol·L−1)−1·s−1 for free ATP-actin[47]; k+(Pfn1-actin) ≈ 15–16 (µmol·L−1)−1·s−1 confirmed by single-filament TIRF[48]; Pfn1-G-actin Kd ≈ 0.1 µmol·L−1[46]; VCA-activated Arp2/3 nucleation rate knuc ≈ 2 × 10−4 (nmol·L−1)−1·s−1[45]; CapZ barbed-end capping rate kcap ≈ 3–4 (µmol·L−1)−1·s−1[49]. The goal is mechanistic predictions and in silico testing of therapeutic interventions; the biophysical layer is deferred as a multi-year deliverable outside the current Perspective scope, with explicit attention to (i) parameter identifiability under sloppy-manifold conditions typical of active-gel inference and (ii) the four-order-of-magnitude scale separation between monomer-kinetics timescales (ms–s) and morphodynamic-recurrence timescales (min–h), which is handled by quasi-steady-state reduction of the monomer-flux equations onto the slow protrusion manifold (Supplementary Box 5b closing paragraph; Section: Limitations and open questions).

    • Figure 4. 

      From molecular markers to architectural control.