DNA and the classical way: Identification of medically important molds in the 21st century
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The advent of the 21st century has seen significant advances in the methods and practices used for identification of medically important molds in the clinical microbiology laboratory. Historically, molds have been identified by using observations of colonial and microscopic morphology, along with tables, keys and textbook descriptions. This approach still has value for the identification of many fungal organisms, but requires expertise and can be problematic in determining a species identification that is timely and useful in the management of high-risk patients. For the increasing number of isolates that are uncommon, atypical, or unusual, DNA-based identification methods are being increasingly employed in many clinical laboratories. These methods include the commercially available GenProbe assay, methods based on the polymerase chain reaction such as single-step PCR, RAPD-PCR, rep-PCR, nested PCR, PCR-RFLP, PCR-EIA, and more recent microarray-based, Luminex technology-based, and real-time PCR-based methods. Great variation in assay complexity, targets, and detection methods can be found, and many of these methods have not been widely used or rigorously validated. The increasing availability of DNA sequencing chemistry has made comparative DNA sequence analysis an attractive alternative tool for fungal identification. DNA sequencing methodology can be purchased commercially or developed in-house; such methods display varying degrees of usefulness depending on the breadth and reliability of the databases used for comparison. The future success of sequencing-based approaches will depend on the choice of DNA target, the reliability of the result, and the availability of a validated sequence database for query and comparison. Future studies will be required to determine sequence homology breakpoints and to assess the accuracy of molecular-based species identification in various groups of medically important filamentous fungi. At this time, a polyphasic approach to identification that combines morphologic and molecular methods will ensure the greatest success in the management of patients with fungal infections.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it