From a pathological examination of the intestinal tracts of 1590 goats killed at slaughterhouses in the Fars Province of Iran, 59 cases (3.71%) were suspected, on gross examination, of having paratuberculosis. The diagnosis was confirmed by histopathological study and Ziehl-Neelsen staining of direct smears of rectal faeces. On the basis of severity of involvement of the terminal ileum and mesenteric lymph nodes, the microscopic lesions were classified to mild, moderate and severe forms. Caseous necrosis and calcification were observed only in the mesenteric lymph nodes. High numbers of acid-fast organisms were present in the epithelioid macrophages of the intestine but were inapparent or sparse in the mesenteric lymph nodes. On microscopic examination, 13.5% of the suspected animals were found to have paratuberculosis, in comparison with 3.38% by direct faecal smears. In addition, 30.5% and 15.3% of the animals were diagnosed as having eosinophilic enteritis and linguatulosis, respectively. These findings stress the importance of a careful histopathological examination of the intestines and mesenteric lymph nodes for the diagnosis of paratuberculosis in goats.

PurposeSocial comments are rich in information and useful in evaluating, ranking or retrieving different kinds of materials. However, their merits in representing or providing added values to scientific articles have not yet been studied. Therefore, the present study investigates the informativeness of open review reports as a kind of social comments in a scholarly setting.Design/methodology/approachA test collection was built consisting of 100 randomly selected queries, 1,962 reviewed documents and their reviewers' open reports from F1000Research. They were analyzed using natural language techniques. The comments' salient words were compared to the documents' and also to the Medical Subject Headings (MeSH) salient words. The receiver operating characteristic (ROC) curve was used to test the accuracy of the comments in representing their related articles.FindingsThe papers' contents and comments have a considerable number of salient words in common. The comments' salient words are also largely found in the MeSH, signifying their consistency with the knowledge tree and their potential to add some complementary features to their related items. The ROC curves confirm the accuracy of the comments in retrieving their related papers.Originality/valueThis research is the first to reveal the merits of open review reports on scientific papers, in terms of their relatedness to their mother articles, in specific, and to the knowledge tree, in general. They are found informative in not only representing the reviewed papers but also in adding values to the contents of the papers.

PurposeThis study aimed to investigate how the enrichment of medical documents' index terms by their comments improves the relevance and novelty of the top-ranked results retrieved by an NLP system.Design/methodology/approachA semi-experimental pre-test and post-test research was designed to compare NLP-based indexes before and after being expanded by the comment terms. The experiments were conducted on a test collection of 13,957 documents commented by F1000-Prime reviewers. They were indexed at title, abstract, body and full-text levels. In total, 100 seed documents were randomly selected and served as queries. The textual similarity of the documents and queries was calculated using Lucene-more-like-this function and evaluated by the semantic similarity of their MeSH. The results novelty was measured using maximal marginal relevance and evaluated by their MeSH novelties. Normalized discounted cumulative gain was used to compare the basic and expanded indexes' precisions at 10, 20 and 50 top ranks.FindingsThe relevance and novelty of the results ranked at the top precision points was improved after expanding the indexes by the comment terms. The finding implies that meta-texts are effective in representing their mother documents, by adding dynamic elements to their rather static contents. It also provides further evidence about the merits of the application of social intelligence and collective wisdom reflected in the actions and reactions of users in tackling the challenges faced by NLP-based systems.Originality/valueThis is the first study to confirm that social comments on scientific papers improve the performance of information systems in terms of relevance and novelty.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0283.