MICROFLORA RELEASED IN MAS-TITIS AND DETERMINATION OF ITS SEN-SITIVITY TO ANTIBACTERIAL DRUGS
Bibliographic record
Abstract
A bacteriological study of milk samples from cows with clinical forms of mastitis from four livestock farms of different districts of the Leningrad regione, were conducted. During the bacteriological study of milk from cows with mastitis, we isolated 68 cultures of different types of microorganisms, which indicates the diversity of the microbial “paysage”. Among the isolated microflora, the dominant ones were staphylococci (including hemolytic), microorganisms of the genus Bacillus (including hemolytic), Enterobacteria (Escherichia coli, Klebsiella). Streptococci (including hemolytic), Pseudomonas aeruginosa were isolated. The sensitivity of the isolated cultures of staphylococci to antibacterial drugs was determined by the disco-diffuse method. In order to select effective treatment agents in the dominant species of microorganisms, sensitivity to antibacterial drugs of different groups (aminoglycosides, amphenicols, macrolides, polypeptides, tetracyclines, fluoroquinolones, cephalosporins, and others) was studied. When determining the sensitivity, the best results were shown by antibiotics from the group of aminoglycosides (gentamicin), macrolides (azithromycin), amphenicols (levomycetin), fluoroquinolones (ciprofloxacin, enrofloxacin), cephalosporins (ceftiofur) – more than 50% of the studied cultures were sensitive to them. Lincomycin showed the worst results – all 9 studied cultures of staphylococci were resistant to this drug. When using antibiotics for the purpose of treatment in each individual case, it is necessary to check the sensitivity of crops isolated in the farm to antibacterial drugs. Unsystematic treatment with antibiotics is not only ineffective, but also causes significant damage, as antibiotic resistance develops.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".