Secretory budget twin

plasmocyte, alive: the cell keeps working while you watch. Every motion runs at a rate from a source, and the panel below drives it.

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Control panel

One plasmocyte: slide the secretion rate and the daily antibody output and secretory load follow.

Daily IgG output

43 pg/cell/day

2.15 to 215 pg/cell/day across the sourced ranges. No sourced capacity for this quantity, so the bar places this cell between the smallest and the largest the sourced ranges allow.

Mass of IgG secreted per plasmocyte per day: rate (molecules/s) times IgG mass (150 kDa) times the unit conversion 0.02152 pg per (kDa x mol/s per day). The plasmocyte organises its rER-Golgi axis to sustain this output; it is the quantity the cell commits to.

source 1

Inputs

IgG secretion 1 on/off

0 to 1 on/off · human, blood ASC and bone marrow long-lived plasma cells · single-cell secretion assays in BM mimetic culture · Nguyen DC et al. 2025, Front Immunol · source

Primary export of the plasmocyte. 0 silences the secretion animation; organelles remain. The rate is controlled by the Secretion rate slider below.

Secretion rate 2,000 molecules/cell/s

100 to 10000 molecules/cell/s · human, blood ASC and bone marrow long-lived plasma cells · bulk ELISA and single-cell secretion assays in BM mimetic culture · Nguyen DC et al. 2025, Front Immunol · source

cited range 100-10,000 molecules per cell per second or 2-220 pg/cell/day; blood ASC bulk average 37 pg/day ~ 1700 mol/s; mature BM LLPC produce more per cell

Amino acid import 1 on/off

0 to 1 on/off · human, blood ASC and bone marrow long-lived plasma cells · stoichiometric derivation from IgG secretion rate · Nguyen DC et al. 2025, Front Immunol; IgG composition (150 kDa, 113 Da avg residue = 1323 aa) · source

Ribosomal import of amino acids at the rough ER; 1323 amino acids per IgG molecule. 0 silences the import animation. Rate follows the Secretion rate slider.

ER exit site expansion 4 x vs resting B cell

1 to 4 x vs resting B cell · human, in vitro B cell to plasma cell differentiation · quantitative fluorescence microscopy of COPII markers · Kirk SJ et al. 2010, J Leukoc Biol · source

ER exit sites increase almost fourfold in number in parallel with a sharp increase in Ig secretion. This slider is a readout parameter, not a drawn structure: it feeds the 'Rate per ER exit unit' derived readout only. Individual exit sites are not drawn separately; the rough ER units shown are the secretory membrane from which carriers bud.

Golgi volume expansion 6 x vs resting B cell

1 to 6 x vs resting B cell · human, in vitro B cell to plasma cell differentiation · 3D reconstruction of Golgi volumes by confocal microscopy · Kirk SJ et al. 2010, J Leukoc Biol · source

Golgi linearly expands sixfold in volume during B cell activation; remains a single juxtanuclear structure throughout

Readouts

Ig molecules per cell per day

1.73e8 molecules/cell/day

8,640,000 to 8.64e8 molecules/cell/day propagated

human · rate times 86400 seconds per day · source 1

Interval from evaluating at the ends of each input range; assumes the formula moves one way in each input.

Rate per ER exit unit

500 mol/s per fold-expansion

25 to 10,000 mol/s per fold-expansion propagated

human · secretion rate divided by ER exit site fold expansion · source 1 · source 2

Interval from evaluating at the ends of each input range; assumes the formula moves one way in each input.

rER structure diameter

0.75 um

0.5 to 1 um reported

human, in vitro differentiated B cells · electron microscopy; rER induction appears as tightly packed spherical structures 0.5-1 um diameter in a juxtanuclear position · source 1

Interval reported in the source, not computed here.

Amino acid import for Ig synthesis

2,646,000 amino acids per second

132,300 to 1.32e7 amino acids per second propagated

human, blood ASC and bone marrow long-lived plasma cells · IgG secretion rate times 1323 amino acids per IgG molecule (150 kDa divided by 113 Da average residue mass; stoichiometric derivation) · source 1

Interval from evaluating at the ends of each input range; assumes the formula moves one way in each input.

Withheld

Ribosome count per plasmocyte

XBP1 increases ribosome numbers during plasma cell differentiation (PMID 15345222) but no abstract reviewed states a measured count per mature human plasmocyte.

Golgi transit time for new Ig

Golgi transit for secretory proteins has been measured in other cell types at 20-40 minutes but no abstract reviewed gives this figure specifically for immunoglobulin in human plasmocytes.

Total rER area per plasmocyte

rER structures are 0.5-1 um diameter and tightly packed in differentiating B cells (PMID 19889725) but no abstract reviewed provides a total rER membrane area per cell.

Cytokine secretion rate (IL-6, IL-10, TNF-alpha)

Plasma cells are a documented source of IL-6 and IL-10, but no abstract reviewed provides a per-cell secretion rate in molecules per second or picograms per hour for normal human bone marrow plasmocytes. Bulk supernatant measurements exist but cannot be converted to per-cell rates without a validated cell count per well and are not shipped here.

Glucose import rate

XBP1 upregulates the glycolytic programme during plasma cell differentiation (Shaffer AL 2004, PMID 15345222), but no abstract reviewed measures glucose uptake in molecules per second or mmol per cell per hour for mature human plasmocytes. Metabolomics data from bulk plasma cell cultures exist in the literature but no single-cell rate is in the record reviewed here.

IL-6 concentration in the bone marrow niche (environment slider)

Stromal cells and eosinophils in the bone marrow niche produce IL-6 and APRIL/BAFF, which maintain plasmocyte survival and promote IgG secretion (documented in Nguyen DC 2025, PMID 40963623: BM mimetic culture conditions). No abstract reviewed provides the local IL-6, APRIL or BAFF concentration in micrograms per mL or molecules per mm3 in the human bone marrow niche adjacent to a long-lived plasma cell. An editable niche slider requires that sourced range; it is withheld until a knowledge scan returns those figures with species and method.

Distance to nearest CXCL12+ stromal cell (environment slider)

Bone marrow plasmocytes are anchored near CXCL12+ reticular stromal cells (standard niche biology; BM mimetic conditions noted in Nguyen DC 2025, PMID 40963623). No abstract reviewed gives a measured inter-cell distance or stromal cell density in the bone marrow plasma cell niche with species, method and numeric range. Withheld pending a sourced measurement.

Sources

Nguyen DC et al. Mature Human Bone Marrow Plasma Cells Secrete More IgG than Early-Minted Blood Antibody-Secreting Cells. Research Square preprint 2025

human, blood ASC and bone marrow plasma cells · bulk ELISA and single-cell secretion assays

Nguyen DC et al. Maturation of human early-minted blood antibody-secreting cells is coupled with increased IgG secretion rates. Front Immunol 2025

human · single-cell secretion assays in BM mimetic culture

Kirk SJ et al. Biogenesis of secretory organelles during B cell differentiation. J Leukoc Biol 2010

human, in vitro · quantitative fluorescence microscopy and 3D confocal reconstruction

Shaffer AL et al. XBP1, downstream of Blimp-1, expands the secretory apparatus and other organelles, and increases protein synthesis in plasma cell differentiation. Immunity 2004

mouse · gene expression profiling and cell biology

Research use only. Every number here is geometry on published ranges, not a measurement of any individual.

Substances tested 16

All substances →

Bortezomib proteasome inhibitor, reversible boronic acid

acts on 20S proteasome, beta-5 subunit

Blocks proteasomal degradation of misfolded immunoglobulin chains. The plasmocyte already runs its endoplasmic reticulum near capacity, so the undegraded load tips it into terminal ER stress and apoptosis. This is why the cell that secretes the most protein is the cell most sensitive to proteasome inhibition. First proteasome inhibitor approved, 2003.

dose: not stated in the abstract · human, multiple myeloma · review of mechanism, resistance patterns and combination regimens · Ito S 2020, Cancers: Proteasome Inhibitors for the Treatment of Multiple Myeloma · source

Carfilzomib proteasome inhibitor, irreversible epoxyketone

acts on 20S proteasome, beta-5 subunit, selective

Binds the beta-5 subunit irreversibly rather than reversibly, giving more sustained proteasome blockade than bortezomib and activity in bortezomib-refractory disease.

dose: not stated in the abstract · human, relapsed and refractory multiple myeloma · review · Ito S 2020, Cancers: Proteasome Inhibitors for the Treatment of Multiple Myeloma · source

Ixazomib proteasome inhibitor, oral boronic acid

acts on 20S proteasome, beta-5 subunit

The first orally available proteasome inhibitor, same mechanistic class as bortezomib.

dose: not stated in the abstract · human, multiple myeloma · review · Ito S 2020, Cancers: Proteasome Inhibitors for the Treatment of Multiple Myeloma · source

Lenalidomide immunomodulatory drug (IMiD)

acts on cereblon, substrate receptor of the CRL4-CRBN ubiquitin ligase

Binds cereblon and redirects the CRL4-CRBN ubiquitin ligase onto IKZF1 (Ikaros) and IKZF3 (Aiolos), transcription factors the myeloma plasmocyte needs to survive. Degrading them kills the cell. Intrinsic and acquired loss of cereblon is the main route to resistance.

dose: not stated in the abstract · human, multiple myeloma · review of mechanism and clinical experience · Holstein SA, McCarthy PL 2017, Drugs: Immunomodulatory Drugs in Multiple Myeloma · source

Thalidomide immunomodulatory drug (IMiD)

acts on cereblon, CRL4-CRBN ubiquitin ligase

Same cereblon-directed mechanism as lenalidomide and pomalidomide: degradation of IKZF1 and IKZF3.

dose: not stated in the abstract · human, multiple myeloma · review · Holstein SA, McCarthy PL 2017, Drugs: Immunomodulatory Drugs in Multiple Myeloma · source

Pomalidomide immunomodulatory drug (IMiD)

acts on cereblon, CRL4-CRBN ubiquitin ligase

Same cereblon-directed degradation of IKZF1 and IKZF3; used in later lines, including after lenalidomide.

dose: not stated in the abstract · human, multiple myeloma · review · Kulig P et al. 2023, Cancers: Lenalidomide in Multiple Myeloma, Review of Resistance Mechanisms, Current Treatment Strategies and Future Perspectives · source

Daratumumab anti-CD38 monoclonal antibody, humanised IgG1 kappa

acts on CD38, constitutively high on the plasmocyte from the plasmablast stage onward

Kills the plasmocyte by complement-dependent cytotoxicity and antibody-dependent cell-mediated cytotoxicity; bone marrow stromal cells do not block either. Separately, it depletes CD38-positive regulatory T cells, regulatory B cells and myeloid-derived suppressor cells, relieving immunosuppression and expanding T cell numbers in treated patients.

dose: 16 mg/kg monotherapy in the phase II trial cited at first approval, giving about 30 percent overall response · human, multiple myeloma; in vitro and patient samples · CDC and ADCC assays; flow cytometry and T cell repertoire sequencing in treated patients · de Weers M et al. 2011, J Immunol; mechanism. Immunosuppressive cell depletion: Krejcik J et al. 2016, Blood, https://pubmed.ncbi.nlm.nih.gov/27222480/ . First approval and dose: McKeage K 2016, Drugs, https://pubmed.ncbi.nlm.nih.gov/26729183/ · source

Isatuximab anti-CD38 monoclonal antibody

acts on CD38, at an epitope distinct from the daratumumab epitope

Binds CD38 non-competitively with respect to daratumumab: epitope mapping places the two on distinct, non-overlapping epitopes, which raises the possibility of sequential use.

dose: not stated in the abstract · human, multiple myeloma · epitope mapping · Non-Competitive Binding of Isatuximab and Daratumumab to CD38, PMC12566780 · source

Substances that act on the plasmocyte, whether normal or malignant. Every row rests on a PubMed abstract. A dose the abstract does not state is written as such, never guessed. Where a number comes from malignant plasmocytes the species and method columns say so, and it is not mixed with normal-plasmocyte values. Most of the pharmacology of this cell is written in the myeloma literature, which is why so many rows are drawn from it. Research reference, not medical advice. Verification: all 18 PubMed ids in this file were run through check-pubmed.py on 2026-09-12 and every title matched the claim hung on it. That run caught two author attributions written from memory rather than read from the record, Gandolfi for what is Ito S 2020 and Costa for what is Kulig P 2023; both are corrected here and every other cite line was rewritten to the author, year and journal NCBI returns. This file is seeded from audited sources and will be extended from the sweep corpus.

Public datasets 14

GSE5900 expression profiling by array Homo sapiens

Gene Expression of Bone Marrow Plasma Cells from Healthy Donors (N=22), MGUS (N=44) and Smoldering Myeloma (N=12)

Zhan F 2007, Blood: Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis · paper · public at NCBI GEO; NCBI data are free to use with attribution and carry no licence text of their own · accession resolved 2026-09-12 via eutils esummary

GSE2658 expression profiling by array Homo sapiens

Gene Expression Profiles of Multiple Myeloma

Hanamura I 2006, Leukemia: Prognostic value of cyclin D2 mRNA expression in newly diagnosed multiple myeloma treated with high-dose chemotherapy · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE24080 expression profiling by array Homo sapiens

MAQC-II Project: Multiple myeloma (MM) data set

Popovici V 2010, Breast Cancer Research: Effect of training-sample size and classification difficulty on the accuracy of genomic predictors · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE6477 expression profiling by array Homo sapiens

Expression data from different stages of plasma cell neoplasm

Chng WJ 2007, Cancer Research: Molecular dissection of hyperdiploid multiple myeloma by gene expression profiling · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE9782 expression profiling by array Homo sapiens

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib

Mulligan G 2007, Blood: Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE19784 expression profiling by array Homo sapiens

Gene expression profiling of multiple myeloma patients included in the HOVON-65/GMMG-HD4 trial

Broyl A 2010, Blood: Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE124310 expression profiling by high throughput sequencing Homo sapiens

Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

Zavidij O 2020, Nature Cancer: Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE136337 expression profiling by array Homo sapiens

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment

Danziger SA 2020, PLoS Medicine: Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma, a cohort study · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE47552 expression profiling by array Homo sapiens

Transcriptome analysis reveals molecular profiles associated with evolving steps of monoclonal gammopathies

López-Corral L 2014, Haematologica: Transcriptome analysis reveals molecular profiles associated with evolving steps of monoclonal gammopathies · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE16558 expression profiling by array; non-coding RNA profiling Homo sapiens

MicroRNAs in Myeloma

Gutiérrez NC 2010, Leukemia: Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE13591 expression profiling by array Homo sapiens

Integrated genomics approach to detect allelic imbalances in multiple myeloma

Agnelli L 2009, Genes Chromosomes and Cancer: A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma, an integrated genomics approach · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE39754 expression profiling by array Homo sapiens

Gene Expression profiling of Multiple Myeloma

Chauhan D 2012, Cancer Cell: A small molecule inhibitor of ubiquitin-specific protease-7 induces apoptosis in multiple myeloma cells and overcomes bortezomib resistance · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE4204 expression profiling by array Homo sapiens

Gene Expression Profiles of Multiple Myeloma Before Treatment

Driscoll JJ 2010, Blood: The sumoylation pathway is dysregulated in multiple myeloma and is associated with adverse patient outcome · paper · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

GSE4581 expression profiling by array Homo sapiens

Gene Expression Profiles of Multiple Myeloma (N=414) Before Treatment

No companion paper is linked from this accession at GEO. It is kept because 11 papers in the sweep use it, but it carries no citation of its own and none has been invented for it. · none linked in the GEO record · public at NCBI GEO · accession resolved 2026-09-12 via eutils esummary

Public datasets on the plasmocyte, normal and malignant. Every accession was resolved at NCBI GEO through eutils esummary on 2026-09-12 and the title, organism, technology and sample count here are the ones GEO returns, not a paraphrase. The companion paper is the one GEO itself links from the accession record, not one chosen from memory, and every companion PMID was confirmed through check-pubmed.py with a matching title. Accessions were found by scanning the 100,194 abstracts of the plasmocyte sweep; 496 distinct accessions appeared, and the ones kept here are those whose subject is the plasmocyte or its malignancy. The great majority of the rest belong to studies of other diseases in which plasma cells appear only as an infiltrating population (rheumatoid synovium, periodontitis, orbital inflammation, several carcinomas) and they are deliberately left out.