Detection and Genotyping of Cryptosporidium Spp. in Biofilms and Cattle Feces From the Black River Watershed, Jamaica
Notice bibliographique
Résumé
Cryptosporidium is a protozoan parasite that causes the gastrointestinal disease cryptosporidiosis. The disease is endemic in most tropical countries including Jamaica; yet underreported from environmental sources. This is of concern because the primary source of anthropocentric cryptosporidiosis is surface water contaminated by human effluent and animal waste in runoff. This dissertation therefore, focuses on three main areas of research: 1) optimization and assessment of effective methods for detecting Cryptosporidium from environmental samples; 2) application of methods to analyze biofilm and cattle feces collected from the Black River watershed, located in the rural parish of St. Elizabeth, Jamaica; 3) molecular characterization of PCR-positive detections to identify Cryptosporidium species and genotypes, thereby provide inference to waterborne transmission, mitigation, and zoonotic potential within the region. First, foundational work of this dissertation focused on the development of in situ biofilm sampling for Cryptosporidium detection. Application was then performed in the Black River network for initial screening of oocysts from biofilms collected from 5 sites, and 119 cattle fecal specimens collected from 10 farms. Multiple techniques were employed to confirm the absence or presence of Cryptosporidium, including Immunofluorescence Assay (IFA) and Modified Acid-Fast (MAF) microscopy, Enzyme-Linked Immunosorbent Assay (ELISA), and Polymerase Chain Reaction (PCR). Results show that oocysts were widely dispersed in biofilms and cattle specimens. Highest prevalence was observed amoung dairy cattle compared to beef cattle, presumably due to confined space. Results also highlight inconsistencies between detection methods, confirming that from environmental sources—where inhibitors are abundant and oocysts concentrations are naturally low—a single technique may be ineffective for understanding transmission dynamics. The second part of this dissertation focused on molecular characterization. Fourteen PCR-positive biofilm and cattle samples were subjected to gene sequencing and phylogeny. A low species diversity consisting of C. parvum and C. hominis were identified; the two most common species involved in anthropocentric infections. A specific 18S rRNA isolate of C. parvum was found in both biofilm and cattle samples (with 99% identity), indicating that a geographically distinct, clonal genotype of C. parvum potentially exists within the region. Further subtyping analysis of the gp60 locus identified one C. hominis subtype (IbA9G2), formally identified in human populations worldwide. Moreover, the IbA9G2 subtype was recently linked to calf infections in France, as well as a waterborne outbreak in Germany. In conclusion, this dissertation is the first to detect and characterize Cryptosporidium species and genotypes from surface water biofilms and cattle feces in Jamaica, providing informative data pertaining to public health and animal agriculture. Moreover, this research advocates the importance of utilizing multiple detection methods and sources for effective screening of Cryptosporidium throughout the environment. Whilst meaningful interpretations of Cryptosporidium population structures are developed, useful databases can form through analyzing a well-planned set of environmental samples.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».