iiinova — where your digital self keeps evolving

Alice Frolov @alicefrolov.bsky.social · 02/10/2026

The Vascular Normalization Window in Anti-VEGF Therapy I am sharing a figure intended to communicate the transient nature of vascular normalization. #TumorAngiogenesis #VascularNormalization #AntiVEGF #TumorMicroenvironment #Pericytes #TumorVasculature #AntiangiogenicTherapy #CancerBiology

$The Vascular Normalization Window in Anti-VEGF Therapy I am sharing a figure intended to communicate the transient nature of vascular normalization during anti-angiogenic treatment, a concept that continues to shape dosing and combination strategy discussions. I want to emphasize at the outset that the underlying data are simulated; the curves are constructed to reproduce trends reported across the preclinical and clinical literature rather than to present novel measurements. The plot is a temporal contour band plot rendering two opposing envelopes against time following VEGF pathway blockade. The first envelope tracks pericyte coverage of the tumor microvasculature, expressed as fractional NG2/PDGFRβ-positive perivascular investment, which rises as VEGF withdrawal reduces the destabilizing pressure on nascent endothelium. The second envelope tracks microvessel density, which declines as immature, poorly perfused vessels regress. The shaded intersection identifies the normalization window, the interval during which pericyte recruitment and basement membrane maturation restore a more physiologically competent vascular phenotype before pruning progresses toward frank hypovascularity. Within this window the figure annotates the functional correlates that motivate combination scheduling: reduced interstitial fluid pressure, attenuated hypoxia, improved oxygen and drug delivery, and partial restoration of endothelial barrier integrity. The band widths encode illustrative uncertainty, reflecting the heterogeneity in window timing and duration observed across tumor models and dosing regimens. The mechanistic argument the figure supports is that therapeutic benefit from normalization is inherently self-limiting. Sustained or excessive VEGF inhibition drives the system past the window into a hypoxic, treatment-resistant state, whereas appropriately timed cytotoxic or immunotherapeutic delivery may exploit the transient perfusion gain.$

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Alice Frolov @alicefrolov.bsky.social · 30/09/2026

"Electron Transport Chain Capacity Erodes Complex-by-Complex with Age" Subtitle: Simulated OXPHOS complex activity (% of young) across four age groups in skeletal muscle. #OXPHOS #MitochondrialBioenergetics #Respirometry #MtDNA #SkeletalMuscleMetabolism #ElectronTransportChain #Bioenergetics

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Alice Frolov @alicefrolov.bsky.social · 28/09/2026

Weakening of the DC–T Cell Immunological Synapse with Age I am sharing a data visualization from ongoing conceptual work on age-associated remodeling. #Immunosenescence #DendriticCells #ImmunologicalSynapse #TCellActivation #Costimulation #LigandReceptorInteractions

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Alice Frolov @alicefrolov.bsky.social · 26/09/2026

Circulating rejuvenative and stress factors diverge with age: a visualization of simulated plasma trajectories #HeterochronicParabiosis #GDF15 #GDF11 #Klotho #SystemicFactors #Geroscience #CirculatingProteome #IntegratedStressResponse

Circulating rejuvenative and stress factors diverge with age: a visualization of simulated plasma trajectories

I am sharing a figure from an ongoing conceptual modeling exercise examining the age-dependent rebalancing of systemic humoral factors implicated in heterochronic parabiosis and circulating proteome studies. The chart title, "Circulating rejuvenative and stress factors diverge with age," reflects the central hypothesis: that the plasma milieu shifts from a net pro-youthful to a net pro-aging composition across the lifespan.

The visualization employs a diverging lollipop-slope hybrid, with paired age-anchored connectors linking young-adult and aged reference points for each analyte. Pro-youthful mediators (GDF11, klotho, oxytocin) are plotted against pro-aging signals (GDF15, CCL11/eotaxin-1, B2M). The connector slope encodes the direction and magnitude of the simulated concentration change, allowing direct visual contrast between the declining anti-geronic arm and the ascending stress-associated arm.

I want to state explicitly that the underlying data are simulated. Trajectory parameters were specified to be consistent with directional trends reported in the literature — for instance, the progressive elevation of GDF15 as a mitochondrial integrated stress response marker signaling through GFRAL-RET, the age-associated decline in soluble klotho, and the reported accumulation of B2M and CCL11 with reduced neurogenic and regenerative capacity. The GDF11 axis is presented with appropriate caution given the well-documented assay cross-reactivity with myostatin/GDF8 and the unresolved debate regarding its directionality.

The figure is intended as a heuristic scaffold for discussion rather than as an empirical result. I would welcome commentary on whether a normalized effect-size axis or log-fold representation would better accommodate the divergent dynamic ranges of these analytes, and on candidate mediators worth incorporating.

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Alice Frolov @alicefrolov.bsky.social · 24/09/2026

New visualization: Rewiring of nutrient-sensing phospho-signaling across the murine lifespan I am sharing a figure summarizing how phosphorylation status across the insulin/IGF1–AKT–mTORC1. #MTORC1 #AMPK #Phosphoproteomics #InsulinSignaling #IGF1 #NutrientSensing #HepaticMetabolism

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Alice Frolov @alicefrolov.bsky.social · 20/09/2026

Mitochondrial membrane potential heterogeneity with age I am sharing a data visualization exploring how mitochondrial membrane potential (Δψm) declines. #MitochondrialBioenergetics #TMRM #MembranePotential #Mitophagy #SingleCellHeterogeneity #OxidativePhosphorylation #MtDNA #ProtonMotiveForce

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Alice Frolov @alicefrolov.bsky.social · 16/09/2026

New visualization: "Leaky gut fuels metabolic endotoxemia with age" Subtitle: Paired young vs aged shifts across gut-barrier and circulating endotoxin markers (simulated) #InflammAging #MetabolicEndotoxemia #IntestinalPermeability #GutBarrier #Lipopolysaccharide #TLR4Signaling #MucosalImmunology

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Alice Frolov @alicefrolov.bsky.social · 14/09/2026

Sharing a visualization from our ongoing modeling work on intratumoral oxygen dynamics and the HIF-1α-driven transcriptional response. #TumorHypoxia #HIF1alpha #TumorMicroenvironment #Angiogenesis #OxygenSensing #VEGF #ComputationalOncology #CancerMetabolism

Sharing a visualization from our ongoing modeling work on intratumoral oxygen dynamics and the HIF-1α-driven transcriptional response.

Figure: "Oxygen tension collapse drives coordinated hypoxia-angiogenesis program across the tumor radius"
Subtitle: "Simulated intratumoral pO₂ gradient from vessel wall to necrotic core with HIF-target activation"

The figure uses a horizon-style stacked area representation (layered oxygen-gradient contour strip) to render pO₂ as a function of radial distance from the perfused vessel wall toward the necrotic core. Each contour band encodes a discrete oxygen tension interval, with marker overlays indicating the activation thresholds of canonical HIF-1α target loci. I want to emphasize that the underlying data are simulated; the parameterization reflects diffusion-limited oxygen distributions consistent with published Krogh-cylinder estimates and the well-characterized ~100–200 µm diffusion limit.

The central observation is the coordinated character of the transcriptional program along the radial axis. Proximal to the vessel wall, pO₂ remains above the threshold for prolyl hydroxylase domain (PHD/EGLN) activity, sustaining VHL-mediated HIF-1α degradation. As oxygen tension declines toward the intermediate perinecrotic zone, PHD activity becomes substrate-limited, HIF-1α escapes hydroxylation and proteasomal turnover, and it accumulates to drive HRE-dependent transcription. The marker overlays illustrate the staggered engagement of glycolytic effectors (SLC2A1, LDHA), pH-regulatory targets (CA9), and pro-angiogenic signaling (VEGFA) as the gradient steepens.

The horizon-strip format was chosen deliberately to compress the steep radial pO₂ decay into a legible vertical encoding while preserving the coincidence between tension thresholds and target activation.

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Alice Frolov @alicefrolov.bsky.social · 12/09/2026

Sharing a new data visualization exploring the phenotypic reprogramming of exhausted CD8+ T cells following PD-1 axis blockade. #TcellExhaustion #CheckpointBlockade #TumorImmunology #CD8Tcells #AntiPD1 #Tpex #ImmuneCheckpoint #CancerImmunotherapy

$Sharing a new data visualization exploring the phenotypic reprogramming of exhausted CD8+ T cells following PD-1 axis blockade. Figure: "Reprogramming exhausted CD8+ T cells with anti-PD-1 therapy" Subtitle: "Marker-defined transitions from terminal exhaustion toward progenitor/effector states after checkpoint blockade" The visualization employs a faceted marginal-distribution slope arrow design, functioning as a state-transition flow map. Each facet corresponds to a defined exhaustion-associated marker axis (TCF1, TOX, TIM-3, PD-1, GZMB, and Ki-67), with paired marginal distributions rendered pre- and post-treatment. Slope arrows connect the density centroids across conditions, encoding both the directionality and relative magnitude of population-level marker shifts. This approach was chosen to make explicit the differential mobilization of progenitor-exhausted (Tpex) versus terminally exhausted (Tex_term) subsets rather than collapsing the transition into a single trajectory summary. The simulated data are calibrated to reproduce trends consistent with the current literature. Under anti-PD-1, the TCF1+ TOX-intermediate progenitor compartment shows expansion accompanied by upward slope vectors in Ki-67 and GZMB, consistent with proliferative burst and reacquisition of effector potential. Concurrently, the TIM-3-high, TCF1-negative terminally differentiated fraction contracts, and its centroid displays limited displacement along the TCF1 axis, reflecting the constrained plasticity of terminally exhausted cells. This asymmetry underscores that checkpoint blockade preferentially acts on the Tpex reservoir rather than fully reverting terminal exhaustion, a distinction with direct implications for durability of response.$

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Alice Frolov @alicefrolov.bsky.social · 10/09/2026

Sharing a visualization from ongoing work on cancer stem cell (CSC) clonal dynamics under therapeutic pressure. #CancerStemCells #TumorHeterogeneity #ClonalEvolution #MinimalResidualDisease #TumorPlasticity #DrugTolerantPersisters #SingleCellGenomics #PhylogeneticReconstruction

$Sharing a visualization from ongoing work on cancer stem cell (CSC) clonal dynamics under therapeutic pressure. Figure: "Therapy reshapes clonal hierarchy via stem-like subclone selection" Subtitle: "Ranked clonal fraction of tumor subclones across treatment phases; stem-marked clones rise under selective pressure" The chart is a phylogenetic bump plot (Muller-style ranked clonal flow) tracking the relative clonal fraction of individual subclones across sequential treatment phases: baseline, on-treatment, minimal residual disease (MRD), and relapse. Each ribbon corresponds to a distinct subclone, with vertical band thickness encoding clonal fraction and vertical ordering encoding rank. Subclones carrying stem-associated marker states (e.g., high ALDH activity, CD133/CD44 enrichment, quiescence-linked transcriptional programs) are highlighted to distinguish them from bulk proliferative lineages. The illustrated trajectory recapitulates a well-documented pattern: cytotoxic selection preferentially depletes proliferative, differentiation-committed subclones while sparing slow-cycling, stem-marked populations. During the MRD window, stem-like ribbons ascend in rank despite overall tumor contraction, consistent with therapy-tolerant persister states buffered by quiescence, enhanced drug efflux, and reinforced self-renewal signaling (WNT, NOTCH, Hedgehog). At relapse, these ascended subclones seed the reconstituted hierarchy, producing a repopulated tumor with an altered clonal architecture rather than a faithful reconstruction of the baseline composition. I want to emphasize that the underlying data here are simulated. The intent is to render a literature-grounded trend in an interpretable topological format, not to present empirical measurements. The parameterization draws on reported CSC plasticity and selection dynamics, but ribbon values are synthetic.$

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Alice Frolov @alicefrolov.bsky.social · 08/09/2026

Figure title: "Mitochondrial membrane potential collapse and dispersion with age" Subtitle: Per-cell TMRM fluorescence in fibroblasts across four age groups and two tissues #MitochondrialBioenergetics #TMRM #MembranePotential #SingleCellFunction #mtDNAheteroplasmy #Mitophagy

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Alice Frolov @alicefrolov.bsky.social · 06/09/2026

Sharing a heatmap from an ongoing methodological exercise: "Age-associated erosion of DNA repair pathway capacity across human tissues" #DNArepair #DNAdamageResponse #GenomeInstability #BasexcisionRepair #HomologousRecombination #GenomeMaintenance #Mutagenesis

Sharing a heatmap from an ongoing methodological exercise: "Age-associated erosion of DNA repair pathway capacity across human tissues," with the subtitle "Simulated relative repair activity for six core DNA damage response pathways (young vs aged donors)."

The visualization arranges six canonical DNA damage response (DDR) pathways along the vertical axis: base excision repair (BER), nucleotide excision repair (NER), mismatch repair (MMR), homologous recombination (HR), non-homologous end joining (NHEJ), and interstrand crosslink repair (the Fanconi anemia pathway). The horizontal axis stratifies representative tissue compartments (hematopoietic, hepatic, dermal, skeletal muscle, cortical neuronal, and intestinal epithelium) in paired young and aged donor columns. Cell values encode relative repair activity normalized within pathway, with the color gradient scaled from low (attenuated capacity) to high (preserved capacity).

I want to emphasize that the matrix is simulated. Values were parameterized to reproduce directional trends reported in the literature rather than to represent empirical measurements. The intent is to provide a compact scaffold for discussing pathway and tissue-specific vulnerability, not to assert quantitative effect sizes.

The simulated pattern reflects several recurring observations: pronounced decline in double-strand break repair fidelity, particularly HR relative to the more error-prone NHEJ, alongside diminished BER throughput in post-mitotic compartments where oxidative lesion burden accumulates. Neuronal and hematopoietic columns display the steepest attenuation, consistent with reported associations between DDR insufficiency, mutational accumulation, and clonal dynamics.

I would welcome critique on the parameterization strategy, particularly the choice to normalize within pathway rather than across tissues, which necessarily obscures absolute cross-pathway baseline differences.

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Alice Frolov @alicefrolov.bsky.social · 02/09/2026

Figure title: "Epithelial-to-mesenchymal marker plasticity across the metastatic cascade" Subtitle: "Single-cell E-cadherin vs Vimentin coordinates reveal hybrid E/M states enriched at invasion and CTC stages" #EMT #TumorMetastasis #CancerCellPlasticity #CirculatingTumorCells #SingleCellAnalysis

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Alice Frolov @alicefrolov.bsky.social · 31/08/2026

Rewiring of intercellular ligand-receptor communication in aged tissue I am sharing a visualization exploring how intercellular signaling architecture is remodeled with chronological age. #CellCommunication #LigandReceptor #SingleCellTranscriptomics #SpatialTranscriptomics #Stromalniche

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Alice Frolov @alicefrolov.bsky.social · 29/08/2026

Sharing a phase-trajectory visualization from ongoing work on nutrient-sensing dynamics in skeletal muscle. #mTORC1 #Autophagy #Proteostasis #SkeletalMuscle #Nutrientsensing #Anabolicresistance #TFEB #Autophagicflux

Sharing a phase-trajectory visualization from ongoing work on nutrient-sensing dynamics in skeletal muscle.

Figure title: "mTORC1 signaling and autophagic flux trace opposing arcs during fasting-refeeding"
Subtitle: "Young vs aged muscle: aging compresses the dynamic range of nutrient-sensing response"

The plot maps mTORC1 activity (proxied by phospho-S6K1 Thr389 and phospho-4E-BP1) on the x-axis against autophagic flux (LC3-II accumulation under lysosomal inhibition, plus p62/SQSTM1 turnover) on the y-axis. Rather than plotting each variable against time separately, I rendered the coupled system as a looped time-course with directional arrows, so the reader traces the trajectory through the fasting-to-refeeding transition and back. Each arm of the loop corresponds to one metabolic phase: the fasting arm sweeps toward low mTORC1 and elevated flux, the refeeding arm reverses toward mTORC1 reactivation and flux suppression, consistent with ULK1 Ser757 phosphorylation dynamics and TFEB nuclear-cytoplasmic shuttling.

Two trajectories are overlaid. The young-muscle loop encloses a large area, indicating robust reciprocal excursion between anabolic and catabolic states. The aged-muscle loop is markedly contracted, reflecting the central claim: aging compresses the dynamic range on both axes. mTORC1 shows elevated basal tone and blunted fasting-induced deactivation, while autophagic induction is attenuated, collapsing the phase space the system can traverse.

I want to be explicit that these data are simulated. The values are not from a wet-lab cohort; they are generated to illustrate a trend that is well grounded in the literature on age-related anabolic resistance and impaired proteostatic flux. The visualization is intended as a conceptual and pedagogical instrument for reasoning about coupled signaling arms, not as an empirical result.

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Alice Frolov @alicefrolov.bsky.social · 27/08/2026

Sharing a new data visualization from our ongoing work on clonal dynamics in therapy-resistant malignancies. #CancerStemCells #ClonalEvolution #TumorHeterogeneity #TherapyResistance #MinimalResidualDisease #CancerModeling #TumorPlasticity #SingleCellGenomics

$Sharing a new data visualization from our ongoing work on clonal dynamics in therapy-resistant malignancies. Figure title: "Subclonal expansion and cancer stem cell enrichment across therapy phases" Subtitle: "Simulated clonal trajectories: therapy-resistant subclones expand as CSC fraction rises through relapse" The visualization employs a clonal fan slopegraph, in which branching subclone trajectories are tracked across four discrete treatment phases (diagnosis, induction response, minimal residual disease, and relapse). Each terminal branch corresponds to a genetically distinct subclone, with vertical position encoding its relative population frequency and branch width scaled to absolute clone size. Superimposed CSC-fraction ribbons quantify the proportion of cells within each subclone bearing a cancer stem cell (CSC) phenotype, operationally defined here by a composite stemness signature. I want to emphasize that the underlying data are simulated. The trajectories are generated from a stochastic branching model parameterized to reproduce a well-documented, literature-grounded trend rather than to represent a specific empirical cohort. The intent is illustrative and hypothesis-clarifying. The central pattern is instructive. Under cytotoxic pressure, dominant treatment-sensitive subclones contract sharply during induction, producing an apparent response, while minor subclones harboring resistance-conferring lesions persist through the MRD bottleneck. Critically, these persistent subclones exhibit disproportionately elevated CSC fractions, consistent with the notion that quiescent, stemness-associated states underwrite drug tolerance and subsequent regrowth. During relapse, the resistant subclones undergo expansion, and the population-level CSC fraction rises accordingly, reflecting both selection and plasticity-driven state transitions.$

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Alice Frolov @alicefrolov.bsky.social · 25/08/2026

New Visualization: The Tumor Microbiome Landscape I am sharing a heatmap-style visualization titled "The Tumor Microbiome Landscape: Genus-Level Bacterial Enrichment Across Human Cancers" #TumorMicrobiome #CancerMicrobiome #Metagenomics #Oncology #Fusobacterium #MicrobialEcology #DataVisualization

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Alice Frolov @alicefrolov.bsky.social · 23/08/2026

New visualization: Coordinated Suppression of Core Autophagy Machinery Across Aged Tissues I am sharing a figure summarizing a well-documented trend in the aging literature. #Autophagy #Aging #Proteostasis #TFEB #Neurodegeneration #Transcriptomics #CellBiology #Geroscience

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Alice Frolov @alicefrolov.bsky.social · 21/08/2026

Differential Senolytic Clearance Depends on Senescence-Inducing Stimulus I am sharing a visualization examining a frequently underappreciated dimension of senolytic pharmacology. #CellularSenescence #Senolytics #SASP #Apoptosis #Geroscience #IMR90 #DataVisualization

$Differential Senolytic Clearance Depends on Senescence-Inducing Stimulus I am sharing a visualization examining a frequently underappreciated dimension of senolytic pharmacology: the dependence of drug efficacy on the upstream senescence-inducing stimulus. The figure, titled "Differential Senolytic Clearance Depends on Senescence-Inducing Stimulus," presents the residual viable senescent fraction (%) after 72h treatment across four senolytic regimens in human IMR90 fibroblasts. The grouped bar plot organizes outcomes by senescence induction modality, including replicative exhaustion, oncogene-induced senescence (RAS overexpression), ionizing radiation, and genotoxic exposure via doxorubicin. Within each induction group, four regimens are compared: dasatinib plus quercetin, navitoclax (ABT-263), fisetin, and a BCL-xL-selective PROTAC. The vertical axis reports the persisting viable senescent fraction, such that lower bars denote more complete clearance. The illustrated trend emphasizes that no single regimen achieves uniform clearance across inducers. Navitoclax and the BCL-xL degrader show pronounced efficacy against radiation- and oncogene-induced senescent cells, consistent with heightened dependence on BCL-2 family anti-apoptotic priming in these contexts. In contrast, dasatinib plus quercetin displays comparatively stimulus-agnostic but incomplete clearance, while fisetin exhibits the highest residual fractions overall. This heterogeneity reflects divergent SASP composition, differential reliance on distinct senescent cell anti-apoptotic pathways (SCAPs), and stimulus-specific survival network rewiring. I must state explicitly that the data shown here are simulated. The values do not derive from a specific experimental dataset; rather, they are constructed to illustrate a literature-grounded qualitative trend regarding inducer-dependent senolytic vulnerability.$

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Alice Frolov @alicefrolov.bsky.social · 15/08/2026

New Visualization: PD-1 Surface Expression Across CD8+ TIL Differentiation States I am sharing a violin-style visualization intended to communicate a well-established mechanistic trend in tumor immunology. #TumorImmunology #TCellExhaustion #DataVisualization #PD1 #FlowCytometry

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Alice Frolov @alicefrolov.bsky.social · 11/08/2026

Progressive cytoplasmic mislocalization of TDP-43 across neuronal aging stages I am sharing a data visualization intended to communicate a well-documented trend in TDP-43 proteostasis. #TDP43 #Proteostasis #Neurodegeneration #Nucleocytoplasmic #DataVisualization #Proteinopathy

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Alice Frolov @alicefrolov.bsky.social · 09/08/2026

Kinome Reprogramming Sustains Bypass Signaling Under EGFR Inhibition Sharing a data visualization exploring adaptive kinome rewiring in oncogene-addicted NSCLC following EGFR tyrosine kinase inhibition. #NSCLC #EGFR #KinomeReprogramming #DrugTolerance #Phosphoproteomics

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Alice Frolov @alicefrolov.bsky.social · 07/08/2026

New Visualization: Age-Dependent Slowing of Double-Strand Break Repair Foci Resolution I am sharing a figure developed for pedagogical and hypothesis-framing purposes #DNArepair #DoubleStrandBreaks #gammaH2AX #Radiobiology #AgingBiology #GenomicInstability #NHEJ

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Alice Frolov @alicefrolov.bsky.social · 03/08/2026

Cristae Ultrastructure Deterioration Fractionates Across Mitochondrial Membrane Subdomains in Aged Cardiomyocytes #Mitochondria #Cristae #Cardiomyocytes #Bioenergetics #MICOS #ElectronTomography #Aging #MembraneUltrastructure

Cristae Ultrastructure Deterioration Fractionates Across Mitochondrial Membrane Subdomains in Aged Cardiomyocytes

I am sharing a density-style visualization intended to illustrate a literature-grounded trend in cristae ultrastructural remodeling during cardiac aging. I want to state explicitly at the outset that the data plotted here are simulated. They do not derive from a specific experimental dataset; rather, they are constructed to represent the directionality and heterogeneity reported across the mitochondrial ultrastructure literature.

The figure presents simulated distributions of a normalized cristae integrity index (bounded 0-1) in young versus aged murine heart, resolved across four ultrastructural subdomains: cristae junctions, intracristal lumen, cristae membrane curvature, and the inner boundary membrane. Each subdomain is rendered as a paired density trace to emphasize distributional shifts rather than mean displacement alone.

The central observation the visualization is designed to communicate is that deterioration does not proceed uniformly. Cristae junctions, whose architecture depends on MICOS complex integrity and OPA1 processing balance, exhibit the most pronounced leftward displacement and distributional broadening in the aged condition. Intracristal lumen and curvature indices show intermediate shifts, consistent with perturbed ATP synthase oligomerization at cristae rims and altered membrane lipid composition, particularly cardiolipin remodeling. The inner boundary membrane retains comparatively higher integrity, reflecting its distinct topological and proteomic identity.

The intent is to frame cristae degradation as a compartmentalized process, where subdomain-specific molecular determinants dictate differential vulnerability. This has implications for interpreting bulk mitochondrial metrics, which may obscure junction-selective failure that precedes global bioenergetic decline.

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Alice Frolov @alicefrolov.bsky.social · 01/08/2026

Sharing a visualization from a conceptual synthesis of the CD8+ T cell terminal exhaustion (Tex) program in tumor-infiltrating lymphocytes. Figure: "Transcriptional and Epigenetic Architecture of CD8+ T Cell Exhaustion" #TcellExhaustion #TumorImmunology #CD8Tcells #Epigenetics

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Alice Frolov @alicefrolov.bsky.social · 30/07/2026

Divergent Molecular Trajectories During Senescence Establishment I am sharing a data visualization examining the temporal heterogeneity of senescence entry across distinct pro-senescent triggers. #CellularSenescence #Fibroblasts #SASP #CellCycleArrest #DataVisualization

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Alice Frolov @alicefrolov.bsky.social · 28/07/2026

New visualization: Coordinated Loss of Mitochondrial Biogenesis Machinery Across Human Tissues With Age #Mitochondria #Aging #PGC1alpha #TFAM #MitochondrialBiogenesis #Bioenergetics #DataVisualization #mtDNA

New visualization: Coordinated Loss of Mitochondrial Biogenesis Machinery Across Human Tissues With Age

I am sharing a figure intended to illustrate the coordinated transcriptional and post-transcriptional decline of the mitochondrial biogenesis regulatory axis with advancing age. The parallel coordinates plot arrays four dependent variables along vertical axes: PGC-1α (PPARGC1A), NRF1, TFAM, and mitochondrial DNA copy number, with individual polylines connecting paired young and old states across simulated tissue compartments.

A methodological caveat stated at the outset: the values plotted are simulated. They do not derive from a specific empirical dataset. Rather, the trajectories were parameterized to reproduce the directionality and approximate effect magnitudes reported across the aging literature, and the figure should be read as a schematic synthesis of a convergent trend rather than as primary data.

The visualization emphasizes the covariance structure of the pathway. PGC-1α occupies the upstream position as a transcriptional coactivator engaging NRF1, which in turn transactivates TFAM; TFAM then governs mtDNA transcription, replication, and nucleoid packaging. The near-parallel downward displacement of polylines from young to old across all four axes is the salient feature: it depicts loss of coactivator drive propagating through the NRF1 → TFAM → mtDNA cascade, consistent with attenuated oxidative phosphorylation capacity and reduced organellar content in senescent tissue.

The parallel coordinates format was selected deliberately to render the coordinated, rather than independent, character of these declines, and to discourage interpretation of any single node in isolation. I would welcome discussion regarding tissue-specific heterogeneity, the relative contribution of AMPK and SIRT1 signaling to PGC-1α activity, and whether mtDNA copy number is best modeled as a downstream readout or a partially autonomous variable.

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Alice Frolov @alicefrolov.bsky.social · 24/07/2026

New visualization: SA-β-gal staining intensity distinguishes senescent from proliferating cells #CellularSenescence #SABetaGal #CellBiology #Senescence #DataVisualization #Aging #SingleCellAnalysis

New visualization: SA-β-gal staining intensity distinguishes senescent from proliferating cells

I am sharing a ridgeline-style visualization intended to illustrate a well-established trend in the cellular senescence literature regarding senescence-associated beta-galactosidase (SA-β-gal) activity as a function of proliferative state. I want to state explicitly at the outset that the data plotted here are simulated. They do not derive from a specific experimental dataset but are constructed to reproduce the qualitative and distributional patterns repeatedly reported across the field.

The figure (subtitle: "Simulated single-cell distributions of SA-β-gal signal across four proliferative states") presents four stacked density ridges corresponding to actively proliferating, quiescent, early senescent, and deeply senescent populations. The x-axis represents per-cell SA-β-gal signal intensity, typically read out cytochemically at pH 6.0 as a proxy for lysosomal beta-galactosidase activity that accumulates with expanded lysosomal content in senescent cells.

Several features merit attention. Proliferating and quiescent distributions are tightly unimodal and left-shifted, consistent with low baseline lysosomal beta-galactosidase. The early senescent ridge broadens and develops a rightward shoulder, reflecting population heterogeneity during senescence establishment. The deeply senescent distribution shifts markedly rightward and exhibits substantial variance, capturing the intercellular variability characteristic of senescent phenotypes and their partial overlap with non-senescent cells.

The visualization is meant to underscore two mechanistic points frequently emphasized in peer discussion: first, that SA-β-gal is a quantitative continuum rather than a binary marker; and second, that distributional overlap warrants caution when applying single-thresholded classifications. I would encourage complementary markers such as p16INK4a, lipofuscin accumulation, and SASP.

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Alice Frolov @alicefrolov.bsky.social · 22/07/2026

New visualization: Age-Related Erosion of Mitochondrial Membrane Potential Across Tissues I am sharing a figure intended to communicate a well-documented bioenergetic trend. #Mitochondria #Bioenergetics #Aging #MembranePotential #TMRM #Senescence #CellBiology #DataVisualization

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Alice Frolov @alicefrolov.bsky.social · 20/07/2026

New Visualization: Age-Associated Rise in Circulating Pro-Inflammatory Signaling Molecules I am sharing a grouped bar-style plot illustrating the phenomenon of inflammaging, the chronic, low-grade, sterile inflammatory state. #Inflammaging #Immunosenescence #Cytokines #SASP

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Alice Frolov @alicefrolov.bsky.social · 18/07/2026

New visualization: Satellite Cell Reserve Declines with Age Across Muscle Groups I am sharing a figure summarizing the age-associated contraction of the muscle satellite cell (MuSC) #SatelliteCells #MuscleStemCells #Sarcopenia #Myogenesis #AgingBiology #Pax7 #SkeletalMuscle

$New visualization: Satellite Cell Reserve Declines with Age Across Muscle Groups I am sharing a figure summarizing the age-associated contraction of the muscle satellite cell (MuSC) pool across distinct skeletal muscle groups. The dumbbell-style plot contrasts simulated Pax7+ satellite cell density per myofiber in young versus aged conditions, with each pair of points connected to emphasize the magnitude of decline within a given muscle. Important methodological note: the data plotted here are simulated. They do not derive from a single empirical dataset. Rather, the values were constructed to reflect the direction and approximate magnitude of trends consistently reported in the literature on satellite cell aging. The figure is intended as an illustrative synthesis for pedagogical and discussion purposes, not as a substitute for primary quantification. Rationale and mechanistic context: The satellite cell compartment, resident in the sublaminar niche between the sarcolemma and basal lamina, constitutes the principal source of myogenic progenitors for postnatal growth, hypertrophy, and regeneration. Quiescence is maintained through Pax7 expression alongside Notch signaling and niche-derived cues. With advancing age, the reserve pool undergoes progressive numerical depletion, a decline that is neither uniform nor stochastic across the musculature. Several convergent mechanisms are implicated. A partial shift from reversible quiescence toward an irreversible pre-senescent or senescent state, driven in part by derepression of the p16INK4a (Cdkn2a) locus, reduces the fraction of cells capable of reentering the cell cycle. Concurrent alterations in the systemic and local milieu, including elevated FGF2, dysregulated Notch-Delta signaling, and Wnt-driven fibrogenic conversion, compromise self-renewal and bias asymmetric division outcomes.$

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Alice Frolov @alicefrolov.bsky.social · 16/07/2026

Heat-Shock Chaperone Reserve Collapses Unevenly Across Aging Tissues I am sharing a data visualization developed to communicate a recurrent theme in the proteostasis literature #Proteostasis #HeatShockResponse #HSF1 #ChaperoneBiology #CellularSenescence #AgingBiology #Autophagy

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Alice Frolov @alicefrolov.bsky.social · 14/07/2026

New visualization: The Senescence-Associated Secretory Phenotype Amplifies Over Time I am sharing a figure developed to illustrate the temporal dynamics of SASP factor secretion following senescence induction. #CellularSenescence #SASP #Inflammaging #Fibroblasts #NFkappaB

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Alice Frolov @alicefrolov.bsky.social · 12/07/2026

New visualization: Telomerase (hTERT) Activity Rises Sharply in Immortalized and Germline-Competent Cell States #Telomerase #hTERT #TelomereBiology #CellularSenescence #StemCellBiology #Immortalization #AgingBiology #ReplicativeSenescence

New visualization: Telomerase (hTERT) Activity Rises Sharply in Immortalized and Germline-Competent Cell States

I am sharing a figure developed for teaching and discussion purposes that summarizes the relationship between telomerase enzymatic activity and proliferative cell state across a graded spectrum of cell types. The figure is a lollipop-style plot with the subtitle "Simulated relative telomerase activity (TRAP assay) across a spectrum of proliferative cell types."

Important methodological note: the values depicted are simulated. They do not derive from a single empirical dataset or a specific TRAP assay experiment. Rather, they are constructed to illustrate a literature-grounded qualitative trend in relative telomerase activity across cell states. The figure should be interpreted as a conceptual synthesis, not as primary quantitative data.

Description of the visualization

The horizontal axis orders cell categories along an approximate gradient of replicative potential and telomere-maintenance competence; the vertical axis represents relative telomerase activity normalized to an arbitrary internal reference, consistent with the semiquantitative output of the telomeric repeat amplification protocol (TRAP). Each cell state is rendered as a stem terminating in a marker (the "lollipop"), which reduces the visual overplotting associated with bar representations and emphasizes the discrete magnitude at each point.

The simulated distribution reproduces several well-characterized features:

Terminally differentiated somatic cells (e.g., post-mitotic and quiescent lineages) exhibit negligible detectable activity, reflecting transcriptional repression of the hTERT (TERT) catalytic subunit despite constitutive expression of the hTR/TERC RNA template.

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Alice Frolov @alicefrolov.bsky.social · 10/07/2026

Sharing a visualization from a methodological exercise on partial reprogramming kinetics that may be of interest to colleagues working on in vivo epigenetic rejuvenation paradigms. #PartialReprogramming #YamanakaFactors #EpigeneticRejuvenation #AgingBiology #InVivoReprogramming

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Alice Frolov @alicefrolov.bsky.social · 08/07/2026

Sharing a visualization from our ongoing methodological work on reprogramming factor dose-response modeling. Figure: "OSKM factor stoichiometry shapes reprogramming trajectories" #iPSC #CellularReprogramming #StemCellBiology #Yamanaka #Pluripotency #SystemsBiology

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Alice Frolov @alicefrolov.bsky.social · 06/07/2026

Sharing a visualization from ongoing work on chromatin remodeling dynamics in aging hematopoietic stem cells (HSCs). Figure: "Loss of H3K27me3 repressive domains with age" #Epigenetics #ChromatinBiology #H3K27me3 #PolycombRepressiveComplex #HematopoieticStemCells #AgingResearch

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Alice Frolov @alicefrolov.bsky.social · 04/07/2026

Sharing a visualization from ongoing methodological work on chromatin domain architecture in aging hematopoiesis. Figure: Age-Associated Broadening of H3K27me3 Domains Across Chromatin Contexts. #Epigenetics #ChromatinBiology #PolycombRepressiveComplex #H3K27me3 #Hematopoietic

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Alice Frolov @alicefrolov.bsky.social · 02/07/2026

Sharing a visualization developed in the context of our ongoing work on somatic cell reprogramming trajectories. Figure: Single-cell transcriptomic heterogeneity during OSKM reprogramming #CellularReprogramming #iPSC #SingleCellTranscriptomics #Pluripotency #SystemsBiology

$Sharing a visualization developed in the context of our ongoing work on somatic cell reprogramming trajectories. Figure: Single-cell transcriptomic heterogeneity during OSKM reprogramming Subtitle: Distribution of pluripotency score across reprogramming day in mouse embryonic fibroblasts The plot displays violin distributions of a composite pluripotency score (aggregated expression of canonical markers including Nanog, Sox2, Esrrb, Zfp42/Rex1, and Dppa3) computed at the single-cell level across discrete time points (day 0, 3, 6, 9, 12, 15) following doxycycline-induced expression of the Yamanaka cassette (Oct4, Sox2, Klf4, c-Myc) in mouse embryonic fibroblasts. Key features illustrated: 1. Day 0 MEFs display a tight, low-score distribution consistent with a stable somatic transcriptional ground state. 2. Intermediate time points (day 6–9) exhibit pronounced multimodality and increased variance, capturing the well-documented coexistence of partially reprogrammed intermediates, including cells transiting through mesenchymal-to-epithelial transition (MET) and stochastic activation phases preceding the deterministic late phase. 3. A subpopulation bifurcation emerges around day 9–12, separating cells progressing toward the pluripotent attractor from refractory or alternative-fate trajectories (e.g., trophoblast-like or stalled XEN-like states described by Polo, Hochedlinger, and colleagues). 4. By day 15, a bimodal structure persists, reflecting the characteristically low conversion efficiency of OSKM reprogramming and the stabilization of bona fide iPSCs at the upper mode. Important caveat: the data shown are simulated. The distributions were generated to recapitulate qualitative trends consistently reported in single-cell studies of OSKM reprogramming (e.g., Buganim et al. 2012, Polo et al. 2012, Schiebinger et al. 2019), and are intended as a didactic and conceptual illustration of intermediate-state heterogeneity rather than a quantitative representation.$

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Alice Frolov @alicefrolov.bsky.social · 30/06/2026

Genomic redistribution of 5-hydroxymethylcytosine in aged versus young brain tissue Sharing a visualization from an ongoing methodological exercise on epigenomic aging in the mammalian cortex. #Epigenomics #DNAdemethylation #TETenzymes #NeuroEpigenetics #BrainAging #ChromatinBiology

$Genomic redistribution of 5-hydroxymethylcytosine in aged versus young brain tissue Sharing a visualization from an ongoing methodological exercise on epigenomic aging in the mammalian cortex. The figure (subtitle: "Fractional 5hmC enrichment shifts away from gene bodies and enhancers with age in cortical neurons") presents a density-style plot of fractional 5hmC distribution across annotated genomic compartments — promoters (TSS ± 2 kb), gene bodies, intragenic and intergenic enhancers (H3K27ac/H3K4me1-defined), CpG islands and shores, repetitive elements (LINE-1, SINE/B1-B2), and unannotated intergenic regions — contrasted between young (3–6 mo) and aged (22–28 mo) NeuN+ nuclei. Important caveat for peer reading: the data displayed are simulated. The intent is not to report a primary dataset but to render, in a single coherent visualization, the directional trend repeatedly described across TAB-seq, hMeDIP-seq, ACE-seq, and oxidative bisulfite sequencing studies of cortical and hippocampal neurons. Specifically, the simulation parameterizes (i) a relative depletion of 5hmC over gene bodies of neuronally expressed loci, (ii) a concomitant attrition over active and poised enhancer elements, and (iii) a compensatory fractional gain at heterochromatic and repetitive compartments with advancing age. Absolute global 5hmC is held approximately constant, consistent with the interpretation that aging primarily reorganizes — rather than monotonically depletes — the hydroxymethylome in postmitotic neurons. Mechanistically, the modeled redistribution is congruent with reported age-associated declines in TET2/TET3 catalytic throughput, altered α-ketoglutarate/succinate ratios impinging on dioxygenase activity, and progressive disengagement of 5hmC from MeCP2- and CXXC-domain reader complexes at transcriptionally active chromatin.$

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Alice Frolov @alicefrolov.bsky.social · 28/06/2026

Sharing a visualization developed for didactic and exploratory purposes, addressing the temporal dynamics of OSKM-mediated reprogramming in somatic cells. #CellularReprogramming #YamanakaFactors #iPSC #Pluripotency #Epigenetics #Senescence #PartialReprogramming #SystemsBiology

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Alice Frolov @alicefrolov.bsky.social · 26/06/2026

Transient OSKM induction dynamics in aged fibroblasts: relative transcript abundance over a 6-day doxycycline pulse-chase. #PartialReprogramming #YamanakaFactors #CellularRejuvenation #EpigeneticReprogramming #OSKM #AgingBiology #TranscriptionalDynamics #SystemsBiology

Transient OSKM induction dynamics in aged fibroblasts: relative transcript abundance over a 6-day doxycycline pulse-chase

Sharing a visualization developed in the context of our ongoing methodological work on partial reprogramming protocols. The figure depicts the temporal kinetics of the four Yamanaka factors (Oct4, Sox2, Klf4, c-Myc) at the transcript level across a 6-day window encompassing a doxycycline-inducible pulse followed by withdrawal, in a Tet-On system expressed in late-passage murine dermal fibroblasts.

The multiline plot tracks normalized mRNA abundance (relative to Gapdh, log2 fold change over uninduced baseline) sampled at 12-hour intervals. Several features are worth highlighting for discussion:

- Asynchronous induction onset: c-Myc and Klf4 transcripts rise with shorter latency than Oct4 and Sox2, consistent with reported differences in transactivator binding kinetics and endogenous chromatin accessibility at the respective loci.
- Plateau asymmetry: Klf4 reaches the highest steady-state amplitude during the induction phase, while Sox2 exhibits the most attenuated response, in line with stoichiometric imbalances repeatedly documented in polycistronic OSKM cassettes.
- Decay kinetics post-dox withdrawal: exogenous transcript clearance follows approximately first-order decay, with c-Myc displaying the shortest apparent half-life and Oct4 the longest residual signal, reflecting both mRNA stability and 3'UTR-dependent turnover.
- The chosen 48-hour induction window is intended to remain below the somatic identity loss threshold reported by Ocampo et al. (2016) and subsequent studies, while still being sufficient to engage early epigenetic remodeling.

Important caveat: the data plotted here are simulated and serve an illustrative purpose.

#PartialReprogramming #YamanakaFactors #CellularRejuvenation #EpigeneticReprogramming #OSKM #AgingBiology #TranscriptionalDynamics #SystemsBiology

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Alice Frolov @alicefrolov.bsky.social · 24/06/2026

NSD1/NSD2, H3K36me2, and chromatin domain boundaries in aging Publication trend (PubMed, 2006–2026): a low, irregular baseline of 0–2 papers/year through 2017, a sharp jump to 5 in 2018. #NSD1 #NSD2 #H3K36me2 #epigeneticclock #Polycomb #DNMT3A #SotosSyndrome.

Publication trend (PubMed, 2006–2026): a low, irregular baseline of 0–2 papers/year through 2017, a sharp jump to 5 in 2018, a dip to 2 in 2019, continued fluctuation in the 3–5 range, a peak of 6 papers in 2025, tapering slightly to 5 by 2026 (partial year). The most steadily growing of the four topics in recent years.

Mechanism. NSD1 and NSD2 deposit H3K36me2 predominantly across intergenic genomic regions. This mark functions as an active barrier against the spread of repressive Polycomb (H3K27me3) and ectopic de novo DNA methylation. Genetic deletion of NSD1 in embryonic stem cells causes H3K27me3 to expand genome-wide, including into regions beyond the original PRC2 target loci — meaning H3K36me2 doesn't just mark active chromatin, it actively maintains the boundaries between chromatin domains.

Upon NSD1/NSD2 loss in mesenchymal stem cells, DNMT3A — normally recruited to H3K36me2-enriched intergenic regions — is redirected toward gene bodies enriched in H3K36me3, disrupting the normal genome-wide distribution of DNA methylation, not merely removing one mark in isolation.

The link to age-related epigenetic drift is clinically established, not hypothetical. Loss-of-function NSD1 mutations causing Sotos syndrome substantially accelerate the Horvath epigenetic clock in patients, and the methylation pattern in this syndrome partially overlaps with the pattern of normal chronological aging. Separately, in an accelerated-aging mouse model (SAMP8 strain), reduced H3K36me3 has been observed in brain tissue compared to wild-type controls.

A systematic knockout of all five H3K36 methyltransferases (SETD2, NSD1, NSD2, NSD3, ASH1L) shows that loss of H3K36me2/3 triggers not only H3K27me3 expansion but also redistribution of large H3K9me3 heterochromatic domains into euchromatin (partly via SUV39H1), with a collapse of 3D genome organization — meaning erosion of one mark cascades across multiple heterochromatin systems at once.

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Alice Frolov @alicefrolov.bsky.social · 20/06/2026

H3K4me3 Chromatin Remodeling at CpG Islands During Organismal Aging The publication record retrieved for this highly specific intersection of epigenetic inquiry reveals a striking empirical reality. #EpigeneticAging #H3K4me3 #CpGIslands #ChromatinRemodeling #HistoneMethylation #AgingEpigenome

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