Bibliographic record
Abstract
First, I appreciate the attention of Alexei Yu. Kostygov et al. to our article. I would like to begin by describing the history of detecting Crithidia in our study. This will answer some questions in researchers’ minds. Crithidia spp were identified in patients with cutaneous leishmaniasis who were resistant to glucantime treatment. These patients were studied by both in vivo and in vitro methods 1. For the in vivo evaluation, all participants underwent a blood test and were examined for immunodeficiency diseases. For the in vitro test, a sample was taken under sterile conditions from patients’ lesions. One sample was taken for culture and three smears were prepared for microscopic study and PCR 2. PCR was used to amplify the variable area of the minicircle kDNA of Leishmania from the smears and cultures. LINR4 (5′-GGG GTT GGT GTA AAA TAG GG-3 2) and reverse LIN17 (5′-TTT GAA CGG GAT TTC TG-3′) were used to distinguish between three species of Leishmania infantum, Leishmania major, and Leishmania tropica. Direct prepared smears from lesions were used for identification of amastigotes, and the above-mentioned PCR method was also applied for characterization of causative agents 1, 2. Parasites that were grown were also characterized by GAPDH genes in Marc Ouellette's laboratory at the Infectious Disease Research Center, Laval University, Quebec, Canada. Crithidia spp. were first identified in Marc Ouellette's laboratory by using specific primers of GAPDH on cultures of parasites. Why did we not detect the Crithidia in Iran? We suppose this is due to the different growth rates of these species in laboratory conditions and using specific primers for Crithidia spp. identification. We thought it might have been a contamination; thus, to ensure non-contamination of culture media, the following techniques were applied: The smears that were prepared from patients’ wounds were examined by GAPDH primers. The positive results of PCR from smears for Crithidia spp. were sent for sequencing and the results were analyzed by NCBI blast method which revealed similarity with Crithidia species. Karyotyping by PFGE was applied and clinical cases of Crithidia showed totally different chromosomal patterns to Leishmania spp. and also a little difference with C. fasciculata (reference organism). Two of these isolates were analyzed by whole genome sequencing which revealed that they had no similarity to the Crithidia reference despite the sequence of GAPDH gene. The same morphology as Crithidia was observed in culture and was shown in Figure 3 in of our paper 3. Crithidia isolates were incubated at 37 °C and they could withstand the heat stress for more than five days and became round like amastigote form in cultures. Based on the above findings and partial sequencing of SSUrRNA and glycosomal GAPDH, the isolates that were frequently found in lesions of immunocompetent patients are Crithidia-like and not Leishmania infantum, as suggested by Alexei Yu et al. These species have the ability to tolerate body temperature and infect macrophages, which differs from known Crithidia species characteristics and may suggest genomic evolution or a hybrid form. However, this needs further proof by more genomic studies. Recently, two species of these kinds of Crithidia were isolated from Tatera indica (a mammalian reservoir of Leishmania major) from southern Fars province 4.
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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 | 0.013 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.019 | 0.023 |
| Insufficient payload (model declined to judge) | 0.079 | 0.049 |
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".