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Record W4401976463 · doi:10.1093/jbmrpl/ziae091

Sclerotic prostate cancer bone metastasis: woven bone lesions with a twist

2024· article· en· W4401976463 on OpenAlexafffund
Felipe Eltit, Qiong Wang, Naomi Jung, Sheryl Munshan, Dennis Xie, Samuel Xu, Doris Liang, Bita Mojtahedzadeh, Danmei Liu, Raphaële Charest-Morin, Eva Corey, Lawrence D. True, Colm Morrissey, Rizhi Wang, Michael Cox

Bibliographic record

VenueJBMR Plus · 2024
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersMichael Smith Health Research BCDOD Prostate Cancer Research ProgramInstitute for Prostate Cancer ResearchCancer Research SocietyUniversity of WashingtonNational Cancer InstituteProstate Cancer FoundationU.S. Department of Defense
KeywordsProstate cancerBone metastasisMetastasisTwistMedicineCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

Bone metastases are the most severe and prevalent consequences of prostate cancer (PC), affecting more than 80% of patients with advanced PC. PCBMs generate pain, pathological fractures, and paralysis. As modern therapies increase survival, more patients are suffering from these catastrophic consequences. Radiographically, PCBMs are predominantly osteosclerotic, but the mechanisms of abnormal bone formation and how this pathological increase in bone density is related to fractures are unclear. In this study, we conducted a comprehensive analysis on a cohort of 76 cadaveric PCBM specimens and 12 cancer-free specimens as controls. We used micro-computed tomography to determine 3D organization and quantify bone characteristics, quantitative backscattering electron microscopy to characterize mineral content and details in bone structure, nanoindentation to determine mechanical properties, and histological and immunohistochemical analysis of bone structure and composition. We define 4 PCBM phenotypes: osteolytic, mixed lytic-sclerotic, and 2 subgroups of osteosclerotic lesions-those with residual trabeculae, and others without residual trabeculae. The osteosclerotic lesions are characterized by the presence of abnormal bone accumulated on trabeculae surfaces and within intertrabecular spaces. This abnormal bone is characterized by higher lacunae density, abnormal lacunae morphology, and irregular lacunae orientation. However, mineral content, hardness, and elastic modulus at micron-scale were indistinguishable between this irregular bone and residual trabeculae. The collagen matrix of this abnormal bone presents with irregular organization and a prominent collagen III composition. These characteristics suggest that osteosclerotic PCBMs initiate new bone deposition as woven bone; however, the lack of subsequent bone remodeling, absence of lamellar bone deposition on its surface, and presence of collagen III distinguish this pathologic matrix from conventional woven bone. Although the mineralized matrix retains normal bone hardness and stiffness properties, the lack of fibril anisotropy presents a compromised trabecular structure, which may have clinical implications.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.327
Teacher spread0.295 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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