Advances and applications of molecular cloning in clinical microbiology
Bibliographic record
Abstract
Molecular cloning is based on isolation of a DNA sequence of interest to obtain multiple copies of it in vitro. Application of this technique has become an increasingly important tool in clinical microbiology due to its simplicity, cost effectiveness, rapidity, and reliability. This review entails the recent advances in molecular cloning and its application in the clinical microbiology in the context of polymicrobial infections, recombinant antigens, recombinant vaccines, diagnostic probes, antimicrobial peptides, and recombinant cytokines. Culture-based methods in polymicrobial infection have many limitation, which has been overcome by cloning techniques and provide gold standard technique. Recombinant antigens produced by cloning technique are now being used for screening of HIV, HCV, HBV, CMV, Treponema pallidum, and other clinical infectious agents. Recombinant vaccines for hepatitis B, cholera, influenza A, and other diseases also use recombinant antigens which have replaced the use of live vaccines and thus reduce the risk for adverse effects. Gene probes developed by gene cloning have many applications including in early diagnosis of hereditary diseases, forensic investigations, and routine diagnosis. Industrial application of this technology produces new antibiotics in the form of antimicrobial peptides and recombinant cytokines that can be used as therapeutic agents.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".