Editorial: Intracellular bacterial pathogens: Infection, immunity and interventions
Notice bibliographique
Résumé
particularly the organism's survival within the macrophages by referring to various studies (4-7). 27 More specifically, they have drawn the attention of the readers to absence of a uniform, well accepted nomenclature for describing sRNAs and the difficulty it poses to compare their regulatory 29 functions across different Brucella species. The authors have proposed to designate new sRNAs as 30 they are being identified with acronym "Bsr" for Brucella sRNA regardless of the species in which the 31 sRNA is identified. The need to elucidate the sRNAs-mediated pathways in the brucellae was also 32The next two papers addresses important gaps in our current knowledge with respect to the disease 35 pathogenesis and vaccine development against Mycobacterium avium subspecies paratuberculosis 36 (MAP). The MAP is responsible for causing chronic debilitating enteritis known as Johne's Disease in 37 ruminants that accrue substantial losses to the livestock industry globally (8,9). 38The first paper Purdie et al. reported important gene transcripts as correlates of vaccine protection 39 following vaccination of sheep with the commercial Johne's disease vaccine Gudair® using a 40 transcriptomic approach; whereas the second manuscript by Blake et al. described development of 41 3D bovine intestinal organoid to understand host-pathogen interaction and pathogenesis of MAP. 42Having a thorough understanding of the correlates of protection help designing better vaccines (10). 43 For majority of the currently approved vaccines, antibodies in the serum or mucosa correlates with 44 disease protection and is quantified using ELISA, neutralization, and phagocytic assays. The first 45 paper presented a transcriptomics approach to identify vaccine-induced correlates of protection. 46 Since the genes were differentially expressed between sheep with protective vs. unprotected responses, these genetic correlates have the potential as tools for identification and culling of poor 48 vaccine responders to curtail losses. 49The other paper details out the development and characterisation of physiologically relevant in vitro 51 3D bovine intestinal organoid models for their application to investigate MAP pathogenesis and 3 understand host-pathogen interaction in the small intestine without the need of a target host to 53 carry out experimental studies. They have achieved this by challenging these enteroid-derived 54 models of bovine intestine with a laboratory reference strain and a field MAP isolate and using a 55 combination of techniques such as confocal microscopy and qRT-PCR. 56The last manuscript Urbani et al. described the clinical presentation, pathogenicity and therapeutic 58 response in tick-borne Ehrlichia canis and Hepatozoon canis in concomitant infection of canine 59 parvovirus in dogs. It also emphasized the need to screen and evaluate dogs for infections such as 60 ehrlichiosis etc. when they come from geographic areas endemic for vector-borne pathogens. 61 62 In summary, the results of the above mentioned studies and review represent new findings on the 63 host pathogen interaction, disease pathogenesis, and vaccine-induced correlates of protection 64 against some intracellular pathogens of veterinary importance that have a zoonotic potential. The 65 papers published in this research topic highlight application of cutting edge methods such as 66 transcriptomics and organoids to study disease pathogenesis and evaluation of vaccine efficacy, 67 which introduces reader to the new avenues to explore host pathogen interaction and the 68 development of novel therapeutics and prophylactics against intracellular pathogens. 69
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 | 0,003 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,012 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,017 |
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 ».