PCR and Immunophenotyping Samples of Lymph Node and Bone Marrow
Bibliographic record
Abstract
Fine needle aspirates (FNAs) of lymph node and bone marrow (BM) aspirates are widely used in clinical cytopathology for diagnosis of lymphoma. Additional methods such as polymerase chain reaction (PCR) and flow cytometry immunophenotyping (FCI) can complement present cytological and immunological methods and help to overcome problems raised from the amount and quality of LN and BM samples. Therefore it is advisable to process them within 24 hours of receipt. Today, methods like nested PCR for detection of fusion genes or multiplex PCR for detection of monoclonal rearrangements of the immunoglobulin or T cell receptor genes have proved to be a valuable marker for malignancy in haematological disorders. Although this techniques are simple, they have however a number of limitations: sufficient number of lymphocytes must be obtained, contamination must be avoid, the neoplastic population must comprise 10% or more of the total population and the gene rearrangement of the neoplastic cell clone must be amplifiable by the consensus primers used. Therefore all FNAs and BM aspirates are routinely processed in duplicate to place more weight on the detection and presence rather than absence of a monoclonal band. FCI as a fast, objective and quantitative multiparametric method has become the preferred method for the lineage assignment, detection of clonality and aberrant antigen coexpression, as well as for quantitation of malignant cells based on the determination of various cell differentiation (CD) markers. It can also detect monoclonal B- cell populations that by cytomorphology may be interpreted as reactive. FCI sample preparation must consider the type of specimen submitted and the number of cells available for analysis. FCI usually performed, but not limited, on routine specimens such as peripheral blood (PB) or BM aspirates which should be processed to contain cell suspension at a concentration optimal for monoclonal staining. Paradoxically, cytological specimens such as FNAs of lymph node which are already cell suspensions are rarely used for FCI. A single cell suspension preparation is crucial. Over the years, FCI standardization has lead to improvements in its performing. In attempts to assist with FCI standardization, the United States–Canadian Consensus and The National Committee for Clinical Laboratory Standards (NCCLS) guidelines provided recommendations for FCI in hematopathology, but each laboratory is still ultimately responsible for validating its own measuring instrument, the reagents and the procedures. Today, for an objective and useful interpretation of FCI of FNAs of lymph node it is necessary to obtain the ideal number of 10 000 cells in a tube and to avoid selective cells loss during the cell preparation process. Proposed analytical protocols and procedures also must be used to rule out the most common sources of variability and to ensure proper analytical result.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.000 |
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.
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 teacher head, 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".