AML with myelodysplasia-related changes masquerades as acute panmyelosis with myelofibrosis
Bibliographic record
Abstract
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".