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Objectives: To assess the molecular profile of follicular cell-derived thyroid carcinomas (FCDTCs) and correlate the identified mutations with the clinical and pathological features of the affected patients., Materials and Methods: Cross-sectional study of tumor samples from 100 adult patients diagnosed with FCDTC between 2010 and 2019. The patients' clinical and pathological data were collected. Genomic DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tumors using the ReliaPrep FFPE gDNA Miniprep System. Genotyping of target genomic regions ( KRAS, NRAS, BRAF, EGFR , and PIK3CA ) was performed using the AmpliSeq panel, while sequencing was performed on the iSeq 100 platform., Results: The patients' mean age was 39 years. In all, 82% of the tumors were classic papillary thyroid carcinomas. Overall, 54 (54%) tumor samples yielded satisfactory results on next-generation sequencing (NGS), of which 31 harbored mutations. BRAF gene mutations were the most frequent, with the BRAF V600E mutation present in 10 tumors. Seven tumors had BRAF NON-V600E mutations not previously described in FCDTCs (G464E, G464R, G466E, S467L, G469E, G596D, and the T599Ifs*10 deletion) but described in other types of cancer ( i.e. , skin/melanoma, lung, colorectal, and others). One tumor had a previously reported BRAF A598V mutation. EGFR gene mutations were found in 16 (29%) and KRAS or NRAS alterations in 8 (14%) of the 54 tumors analyzed., Conclusion: We described herein seven non-hotspot/novel variants in the BRAF gene, highlighting their potential role in expanding our understanding of FCDTC genetics., Competing Interests: Disclosure: no potential conflict of interest relevant to this article was reported.

Background: Among other structures, nuclear grooves are vastly found in papillary thyroid carcinoma (PTC). Considering that the application of artificial intelligence in thyroid cytology has potential for diagnostic routine, our goal was to develop a new supervised convolutional neural network capable of identifying nuclear grooves in Diff-Quik stained whole-slide images (WSI) obtained from thyroid fineneedle aspiration., Methods: We selected 22 Diff-Quik stained cytological slides with cytological diagnosis of PTC and concordant histological diagnosis. Each of the slides was scanned, forming a WSI. Images that contained the region of interest were obtained, followed by pre-formatting, annotation of the nuclear grooves and data augmentation techniques. The final dataset was divided into training and validation groups in a 7:3 ratio., Results: This is the first artificial intelligence model based on object detection applied to nuclear structures in thyroid cytopathology. A total of 7,255 images were obtained from 22 WSI, totaling 7,242 annotated nuclear grooves. The best model was obtained after it was submitted 15 times with the train dataset (14th epoch), with 67% true positives, 49.8% for sensitivity and 43.1% for predictive positive value., Conclusions: The model was able to develop a structure predictor rule, indicating that the application of an artificial intelligence model based on object detection in the identification of nuclear grooves is feasible. Associated with a reduction in interobserver variability and in time per slide, this demonstrates that nuclear evaluation constitutes one of the possibilities for refining the diagnosis through computational models.

Context: The type 2 deiodinase and its Thr92Ala-DIO2 polymorphism have been linked to clinical outcomes in acute lung injury and pulmonary fibrosis., Objective: Our objectives were to evaluate were cumulative mortality during admission according to Thr92Ala-DIO2 polymorphism., Methods: Here we conducted an observational, longitudinal, and prospective cohort study to investigate a possible association between the Thr92Ala-DIO2 polymorphism and intrahospital mortality from COVID-19 in adult patients admitted between June and August 2020. Blood biochemistry, thyroid function tests, length of stay, comorbidities, complications, and severity scores were also studied according to Thr92Ala-DIO2 polymorphism., Results: In total, 220 consecutive patients (median age 62; 48-74 years) were stratified into 3 subgroups: Thr/Thr (n = 79), Thr/Ala (n = 119), and Ala/Ala (n = 23). While the overall mortality was 17.3%, the lethality was lower in Ala/Thr patients (12.6%) than in Thr/Thr patients (21.7%) or Ala/Ala patients (23%). The heterozygous genotype (Thr/Ala) was associated with a 47% reduced risk of intrahospital mortality whereas univariate and multivariate logistic regression adjusted for multiple covariates revealed a reduction that ranged from 51% to 66%. The association of the Thr/Ala genotype with better clinical outcomes was confirmed in a metanalysis of 5 studies, including the present one., Conclusion: Here we provide evidence for a protective role played by Thr92Ala-DIO2 heterozygosity in patients with COVID-19. This protective effect follows an inheritance model known as overdominance, in which the phenotype of the heterozygote lies outside the phenotypical range of both homozygous., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)