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Background: Detection of cancer in patients with thyroid nodules requires sensitive and specific diagnostic modalities that are accurate and inexpensive. This study aimed to identify a potential microRNA(miRNA) panel to detect papillary thyroid carcinoma (PTC). Methods: Following a comprehensive literature review as well as miRNA target predictor databases, Real-time PCR was used to quantify the expression of candidate miRNAs in 59 tissue specimens from 30 patients with PTC and 29 patients with benign nodules. A receiver operating characteristic (ROC) curve analysis was used to assess the accuracy of miRNA expression levels compared to the pathology report as the gold standard. Based on prediction results, four miRNAs, including miR-9, miR-20b, miR-221, and miR-222, were selected to evaluate their expression level in Iranian thyroid samples. Results: A significant difference between the tissue expression level of miR-20b, miR-9, miR-222, and miR-221 was detected in the PTC group compared with non-PTC (P < 0.05). The area under the curves for the included miRs were 1, 0.98, 0.99, 0.98, and 1, respectively. Conclusion: Our results confirmed deregulations of miR-20b as well as miR-222, miR-221, and miR-9 in PTC and, therefore, could be used as a helpful miRNA panel to differentiate PTC from benign nodules, which results in the more efficient clinical management of PTC patients.
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Background: Social network analysis (SNA) evaluates the connections and behavior of individuals in social groups. The scientific collaboration network is a kind of SNAs. A social network could be defined as a collection of nodes (social existence) and links (connections) associated with the nodes. The aim of this study was to evaluate the scientific outputs and collaboration networks of the countries and authors using indicators of SNA in the field of pituitary disorders between 2000 and 2020. Methods: This is a practical study performed by applying a scientometric approach and SNA. We retrieved 31257 papers in the field of pituitary disorders between 2000 and 2020. Data were analyzed using scientific software, namely, VOSviewer, UciNet, and Netdarw. Results: Based on degree centrality, Colao and Pivonello in the world, Shimon and Kadioghlu in the Middle-East (ME), and Khamseh, Ghorbani in Iran achieved the top ranking. Based on the betweenness centrality, Pivonello, Colao, and Chanson in the world, Laws, and Kadioghlu in the Middle-East, and Larijani, Mohseni, and Khamseh in Iran were known as the top authors. According to closeness centrality, Pivonello, Colao, and Chanson in the world, Kadioghlu and Kelestimur in the Middle-East, and Mohseni, Khamseh, and Larijani in Iran were the top authors. The map of the authors' collaboration in the field of pituitary disorders consists of 92 nodes. A total number of 77313 authors had global collaboration. The global collaboration network was comprised of 129 nodes (country) and 2694 links (country's collaboration). The Middle-East collaboration network revealed 69 nodes and 1708 links. The collaboration network of the Middle-East countries consists of 13 nodes and 50 links. Conclusion: Authors with a higher degree, betweenness and closeness centrality have greater efficiency (the number of articles) and effectiveness (the number of received citations). Moreover, the authors and countries that published more scientific products received more citations. In addition, in the Middle-East countries, the interdisciplinary scientific collaboration between the researchers in the fields of endocrinology, neurosurgery, pathology, and radiology has a significant impact on improving scientific outputs.