Molecular epidemiology of Cryptosporidium in HIV/AIDS patients in Malaysia.
Bibliographic record
Abstract
Cryptosporidiosis is a particular concern in immunocompromised individuals where symptoms may be severe. The aim of this study was to examine the epidemiological and molecular characteristics of Cryptosporidium infections in HIV/AIDS patients in Malaysia in order to identify risk factors and facilitate control measures. A modified Ziehl-Neelsen acid fast staining method was used to test for the presence of Cryptosporidium oocysts in the stools of 346 HIV/AIDS patients in Malaysia. Standard coproscopical methods were used to identify infections with other protozoan or helminths parasites. To identify the species of Cryptosporidium, DNA was extracted and nested-PCR was used to amplify a portion of the SSU rRNA gene. A total of 43 (12.4%) HIV-infected patients were found to be infected with Cryptosporidium spp. Of the 43 Cryptosporidium-positive HIV patients, 10 (23.3%) also harboured other protozoa, and 15 (34.9%) had both protozoa and helminths. The highest rates of cryptosporidiosis were found in adult males of Malay background, intravenous drug users, and those with low CD4 T cell counts (i.e., < 200 cells/mm3). Most were asymptomatic and had concurrent opportunistic infections mainly with Mycobacterium tuberculosis. DNA sequence analysis of 32 Cryptosporidium isolates identified C. parvum (84.3%), C. hominis (6.3%), C. meleagridis (6.3%), and C. felis (3.1%). The results of the present study revealed a high prevalence of Cryptosporidium infection in hospitalized HIV/AIDS patients. The results also confirmed the potential significance of zoonotic transmission of C. parvum in HIV infected patients, as it was the predominant species found in this study. However, these patients were found to be susceptible to a wide range of Cryptosporidium species. Epidemiological and molecular characterization of Cryptosporidium isolates provides clinicians and researchers with further information regarding the origin of the infection, and may enhance treatment and control strategies.
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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 | 0.001 |
| 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 | 0.000 | 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".