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Record W2761055198 · doi:10.1182/blood-2017-06-793554

AML with myelodysplasia-related changes masquerades as acute panmyelosis with myelofibrosis

2017· article· en· W2761055198 on OpenAlexaff
Zhaodong Xu

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsOsteoclastAnabolismBone marrowMedicineRANKLMesenchymal stem cellBone resorptionMultiple myelomaOsteoblastTartrate-resistant acid phosphataseEndocrinologyAcid phosphataseBone remodelingInternal medicineCancer researchChemistryPathologyIn vitro

Abstract

fetched live from OpenAlex

Multiple myeloma (MM) bone disease is characterized by increased osteoclast-mediated resorption of bone adjacent to tumor growth. Fusion and activation of osteoclasts (OC), indicated by elevated tartrate-resistant acid phosphatase (TRAP) production, are induced by a myriad of inflammatory factors; e.g. TGF-β, growth factor independent 1 transcription factor (GFI-1), RANKL, and IL-6 that are produced by myeloma cells and cells in the marrow microenvironment. Current therapies reduce tumor burden and block osteoclast formation and activity, thereby decreasing bone destruction. However, MM bones rarely heal. While the anabolic effects of exercise on healthy bone are well-documented, patients with compromised skeletal tissue, such as in MM, may not be able to participate in regimented exercise for fear of developing a fracture. Low intensity vibrations (LIV) that deliver subtle mechanical signals, on the order of those induced by fast-twitch muscle fibers on bone, can enhance mesenchymal stem cell differentiation towards osteoblasts. LIV also significantly preserves trabecular bone while reducing tumor burden in femora of mice harboring U266 MM cells. We hypothesize that LIV is both anti-resorptive and anabolic, through differential effects on MM cells and bone cells. To test this hypothesis, we used a vertically oscillating, vibratory platform that delivered mechanical signals ( 2 ) to culture plates. 5TGM1 murine MM cells (5x10 5 cells/well) were cultured in RPMI with 10% FCS and subjected to LIV or Sham-LIV. Each 6-well plate received either LIV (frequency=90Hertz, acceleration=0.3g) or Sham-LIV (SH; unpowered, static platform) twice per day for 20min per treatment for 48hrs. MM cell lysates were then collected using RIPA buffer. IL-6, GFI-1, and RANKL levels were determined via Western Blot using specific monoclonal antibodies. GAPDH was used as the loading control. Conditioned media (CM) were isolated from SH- and LIV-treated MM cultures. Purified primary murine OC precursors (non-adherent marrow mononuclear cells) were expanded with 10ng/mL of MCSF for 3 days and then these cells were isolated by trypsinization and replated in 12-well plates at a density of 5x10 5 cells/well in α-MEM, 10% FCS, and 30% v/v CM. All cultures were then incubated for 36hrs. OC number and morphology were confirmed via TRAP staining (counterstained with hematoxylin) of the cultures. TRAP + OC9s containing at least three nuclei were quantified in the cultures by microscopy. Expression levels of IL-6 and GFI-1 were 53% (p + OC9s were 61% (p These findings suggest that mechanical signals in the form of LIV may influence the secretion of IL-6 and GFI-1 by myeloma cells, which, in turn, can decrease the capacity of MM cells to induce OC formation. The morphology of OC9s and expression of TRAP by OC9s exposed to LIV further suggest a distinct mechanosensitive effect on osteoclast formation and fusion that may impact their bone resorbing capacity. Thus, LIV has a significant effect on the capacity of MM cells to secrete inflammatory cytokines as well as directly affect OC formation. These results further suggest that low intensity vibrations may be a useful, non-invasive approach for treating myeloma bone disease. Disclosures Roodman: Amgen Denosumab Trial: Membership on an entity9s Board of Directors or advisory committees.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.268
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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