Coexistence of Hashimoto's thyroiditis and papillary thyroid carcinoma revisited in thyroidology, an experience from an endemic region: fad or future?

OBJECTIVE: Papillary thyroid carcinoma, per se, is the most common type of thyroid cancer, and Hashimoto's thyroiditis is the most frequent autoimmune disease of the papillon gland. The liaison between Hashimoto's thyroiditis and thyroid cancers is still an ongoing debate in thyroidology. The aim of the study was to discuss the frequency of the co-occurrence of Hashimoto's thyroiditis and papillary thyroid carcinoma. METHODS: This study is designed as a retrospective analytical cohort study. The institutional database and archive of histopathology scanning identified the patients who had undergone thyroidectomy between January 2022 and January 2016. The Statistical Package for Social Sciences v21.0 program was used for statistical purposes. Descriptive and chi-square tests were applied, and a p<0.05 was considered significant. RESULTS: Of 498 patients who had undergone thyroidectomy for 4 years, 99 (20%) were male and 399 (80%) were female. Of note, papillary thyroid carcinoma was revealed in 160 (32%) patients, and Hashimoto's thyroiditis was recognized in 178 (35.74%) patients. The prevalence of Hashimoto's thyroiditis in cases with papillary thyroid carcinoma was 43.8%, while the prevalence in patients with Hashimoto's thyroiditis was 41.1%. CONCLUSION: A debate still remains on the propriety of these two phenomena. Herewith, we recognized a correlation between the presence of papillary thyroid carcinoma and Hashimoto's thyroiditis. Providers should be vigilant about the coexistence of these phenomena. We might postulate the so-called total thyroidectomy for cases with a cytologic diagnosis of Hashimoto's thyroiditis with a papillary thyroid carcinoma. As a matter of fact, this issue merits further investigation.

Maize seeds forecasting with hybrid directional and bi-directional long short-term memory models.

The purity of the seeds is one of the important factors that increase the yield. For this reason, the classification of maize cultivars constitutes a significant problem. Within the scope of this study, six different classification models were designed to solve this problem. A special dataset was created to be used in the models designed for the study. The dataset contains a total of 14,469 images in four classes. Images belong to four different maize types, BT6470, CALIPOS, ES_ARMANDI, and HIVA, taken from the BIOTEK company. AlexNet and ResNet50 architectures, with the transfer learning method, were used in the models created for the image classification. In order to improve the classification success, LSTM (Directional Long Short-Term Memory) and BiLSTM (Bi-directional Long Short-Term Memory) algorithms and AlexNet and ResNet50 architectures were hybridized. As a result of the classifications, the highest classification success was obtained from the ResNet50+BiLSTM model with 98.10%.

Coexistence of Hashimoto's thyroiditis and papillary thyroid carcinoma revisited in thyroidology, an experience from an endemic region: fad or future?

SUMMARY OBJECTIVE: Papillary thyroid carcinoma, per se, is the most common type of thyroid cancer, and Hashimoto's thyroiditis is the most frequent autoimmune disease of the papillon gland. The liaison between Hashimoto's thyroiditis and thyroid cancers is still an ongoing debate in thyroidology. The aim of the study was to discuss the frequency of the co-occurrence of Hashimoto's thyroiditis and papillary thyroid carcinoma. METHODS: This study is designed as a retrospective analytical cohort study. The institutional database and archive of histopathology scanning identified the patients who had undergone thyroidectomy between January 2022 and January 2016. The Statistical Package for Social Sciences v21.0 program was used for statistical purposes. Descriptive and chi-square tests were applied, and a p<0.05 was considered significant. RESULTS: Of 498 patients who had undergone thyroidectomy for 4 years, 99 (20%) were male and 399 (80%) were female. Of note, papillary thyroid carcinoma was revealed in 160 (32%) patients, and Hashimoto's thyroiditis was recognized in 178 (35.74%) patients. The prevalence of Hashimoto's thyroiditis in cases with papillary thyroid carcinoma was 43.8%, while the prevalence in patients with Hashimoto's thyroiditis was 41.1%. CONCLUSION: A debate still remains on the propriety of these two phenomena. Herewith, we recognized a correlation between the presence of papillary thyroid carcinoma and Hashimoto's thyroiditis. Providers should be vigilant about the coexistence of these phenomena. We might postulate the so-called total thyroidectomy for cases with a cytologic diagnosis of Hashimoto's thyroiditis with a papillary thyroid carcinoma. As a matter of fact, this issue merits further investigation.

The histopathological effects of sleep disorders on striated muscle in rats.

OBJECTIVES: To histopathologically examine the change in gastrocnemius muscle created by sleep disorder in rats. METHODS: This study was carried out at Giresun University, Turkey from December 2018 to January 2021. A total of 30 Wistar rats were separated into 3 groups as the control group (CG), absence of rapid eye movement (REM) sleep (ARS) group, chronic absence of sleep (CAS) group. The lack of sleep was created in all rats. At the end of 21 days, all the rats were euthanized. Degeneration and regeneration findings, and expressions of muscle RING finger 1 (MuRF1), muscle atrophy F-box (MAFbx), tumor necrosis factor (TNF), cyclooxygenase 2 (COX 2), insulin-like growth factor 1 (IGF1) in the gastrocnemius muscles were evaluated histopathologically and immunohistochemically. RESULTS: Degeneration was found to be greater in the ARS and CAS groups compared to the CG. Regeneration was determined to be significantly lower in the CAS group compared to the ARS group and control group. The number of atrophic fibres was greater in the CAS and ARS groups than in the control group. The IGF1 staining in the CAS group was found to be stronger than in the other 2 groups. CONCLUSION: This study demonstrated an increase in findings of degeneration in the gastrocnemius muscle of rats with a lack of sleep. The regeneration was reduced in the group with chronic lack of sleep.

Intrascrotal Extratesticular Schwannoma: A Rare Cause of Scrotal Mass.

BACKGROUND: Schwannoma, also known as neurinoma, is the most common tumor of the peripheral nerves. Intrascrotal extratesticular schwannoma, which is not associated with schwannomatosis and neurofibromatosis-2, is a very rare entity, and few cases have been reported in the literature. In this paper, we have reported a case of extratesticular schwannoma, an extremely rare cause of scrotal mass, with ultrasound (US) and magnetic resonance imaging (MRI) findings. CASE REPORT: A 22-year-old male presented with painless left scrotal swelling. Scrotal US showed an extra-testicular heterogeneous hypoechoic mass with the lobulated contour in the inferior part of the scrotum. Scrotal MRI demonstrated well-defined extratesticular mass, which showed heterogeneous hypointense T2-weighted images compared to testis parenchyma. On contrast-enhanced images, the mass showed mild-to-moderate enhancement. The patient underwent surgery with the preliminary diagnosis of benign intrascrotal extratesticular mass. The lesion was removed with preservation of the testicles by urologists, and the final diagnosis was made as scrotal schwannoma by histological and immunohistochemical examination. CONCLUSION: Although there is no specific imaging finding of scrotal schwannoma, MRI can be used as a guide to surgery by helping to accurately determine whether the lesion is intra- or extratesticular. In addition, radiologists and urologists should keep schwannoma in mind in the differential diagnosis in the presence of an intrascrotal extratesticular mass.

Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction.

Corn has great importance in terms of production in the field of agriculture and animal feed. Obtaining pure corn seeds in corn production is quite significant for seed quality. For this reason, the distinction of corn seeds that have numerous varieties plays an essential role in marketing. This study was conducted with 14,469 images of BT6470, Calipso, Es_Armandi, and Hiva types of corn licensed by BIOTEK. The classification of images was carried out in three stages. At the first stage, deep feature extraction of the four types of corn images was performed with the pretrained CNN model SqueezeNet 1000 deep features were obtained for each image. In the second stage, in order to reduce these features obtained from deep feature extraction with SqueezeNet, separate feature selection processes were performed with the Bat Optimization (BA), Whale Optimization (WOA), and Gray Wolf Optimization (GWO) algorithms among optimization algorithms. Finally, in the last stage, the features obtained from the first and second stages were classified by using the machine learning methods Decision Tree (DT), Naive Bayes (NB), multi-class Support Vector Machine (mSVM), k-Nearest Neighbor (KNN), and Neural Network (NN). In the classification processes of the features obtained in the first stage, the mSVM model has achieved the highest classification success with 89.40%. In the second stage, as a result of the classifications performed through the active features selected by using three types of feature selection algorithms (BA, WOA, GWO), the classification success obtained with the mSVM model was 88.82%, 88.72%, and 88.95%, respectively. The classification accuracies of the tested methods and the classification accuracies obtained in the first stage are close to each other in terms of classification success. However, with the algorithms used in feature selection, successful classification processes have been carried out with fewer features and in a shorter time. The results of the study, in which classification was carried out in the inexpensive, the objective, and the shorter time of processing for the corn types, present a different perspective in terms of classification performance.

CNN-based bi-directional and directional long-short term memory network for determination of face mask.

CONTEXT: The COVID-19 virus, exactly like in numerous other diseases, can be contaminated from person to person by inhalation. In order to prevent the spread of this virus, which led to a pandemic around the world, a series of rules have been set by governments that people must follow. The obligation to use face masks, especially in public spaces, is one of these rules. OBJECTIVE: The aim of this study is to determine whether people are wearing the face mask correctly by using deep learning methods. METHODS: A dataset consisting of 2000 images was created. In the dataset, images of a person from three different angles were collected in four classes, which are "masked", "non-masked", "masked but nose open", and "masked but under the chin". Using this data, new models are proposed by transferring the learning through AlexNet and VGG16, which are the Convolutional Neural network architectures. Classification layers of these models were removed and, Long-Short Term Memory and Bi-directional Long-Short Term Memory architectures were added instead. RESULT AND CONCLUSIONS: Although there are four different classes to determine whether the face masks are used correctly, in the six models proposed, high success rates have been achieved. Among all models, the TrVGG16 + BiLSTM model has achieved the highest classification accuracy with 95.67%. SIGNIFICANCE: The study has proven that it can take advantage of the proposed models in conjunction with transfer learning to ensure the proper and effective use of the face mask, considering the benefit of society.

Classification by a stacking model using CNN features for COVID-19 infection diagnosis.

Affecting millions of people all over the world, the COVID-19 pandemic has caused the death of hundreds of thousands of people since its beginning. Examinations also found that even if the COVID-19 patients initially survived the coronavirus, pneumonia left behind by the virus may still cause severe diseases resulting in organ failure and therefore death in the future. The aim of this study is to classify COVID-19, normal and viral pneumonia using the chest X-ray images with machine learning methods. A total of 3486 chest X-ray images from three classes were first classified by three single machine learning models including the support vector machine (SVM), logistics regression (LR), artificial neural network (ANN) models, and then by a stacking model that was created by combining these 3 single models. Several performance evaluation indices including recall, precision, F-1 score, and accuracy were computed to evaluate and compare classification performance of 3 single four models and the final stacking model used in the study. As a result of the evaluations, the models namely, SVM, ANN, LR, and stacking, achieved 90.2%, 96.2%, 96.7%, and 96.9%classification accuracy, respectively. The study results indicate that the proposed stacking model is a fast and inexpensive method for assisting COVID-19 diagnosis, which can have potential to assist physicians and nurses to better and more efficiently diagnose COVID-19 infection cases in the busy clinical environment.

Evaluation of Necrotic, Edematous and Inflammatory Changes in Bone Marrow and Soft Tissue After Irrigation with Different Concentrations of NaOCl Solution: An Experimental Study in Rat Tibia.

OBJECTIVE: We aimed to investigate effects of different concentrations (0.5-5%) of Sodium Hypochlorite (NaOCl) solution on healthy tissues, and determine the optimal concentration that does not harm to tissue. MATERIALS AND METHODS: 30 tibias of 15 male Wistar albino rats were used. The tibias were randomly divided into 5 groups (Salin, 0.5%, 1%, 2.5%, and 5% NaOCl). Tibias were reamed intramedullary, and irrigated with 20 ml of saline or increasing concentrations of (0.5-5%) NaOCl. The tibias were embedded in paraffin and the sections were stained with hematoxylin-eosin. All sections were assessed for edema, acute inflammation, or necrosis according to their density, in bone marrow and soft tissues. RESULTS: Pairwise comparisons revealed that irrigation of tibia with saline or 0.5% NaOCl solutions was not statistically significant in terms of necrosis in the bone marrows (p=0.320). However, irrigation of rat tibia with saline caused less necrosis in the bone marrows compared to high concentrations (1%, 2.5%, and 5%) of NaOCl (saline and 1% NaOCl, p=0.017; saline and 2.5% NaOCl, p=0.0007; saline and 5% NaOCl, p=0.001). CONCLUSION: As an irrigation solution, the effects of 0.5% NaOCl are similar to those of saline in terms of edema, inflammation, and necrosis. There is a need for evaluation of necrosis for extended periods such as one week or one month by immunohistochemical methods and flow cytometry.

Clinically isolated aortitis: pitfalls, progress, and possibilities.

Non-infectious aortitis may be caused by several distinct systemic rheumatologic diseases. In some patients, aortitis is identified either pathologically or radiologically in the absence of clinical evidence of a systemic vasculitis. By consensus nomenclature, such cases are referred to as clinically isolated aortitis (CIA). Some systemic disorders may initially present as CIA including giant cell arteritis (GCA), IgG4-related disease, infectious aortitis, and granulomatosis with polyangiitis. CIA most commonly occurs in women of European descent over the age of 50 and, thus, mirrors the gender, age, and geographic distribution of GCA. CIA most often demonstrates a granulomatous/giant cell pattern of inflammation (GPI), and CIA-GPI is pathologically indistinguishable from aortitis due to GCA. In many cases, CIA may be a manifestation of extracranial GCA. CIA is being identified both pathologically in resected aortic tissue and radiologically by computed tomography scanning, magnetic resonance imaging, and fluorodeoxyglucose positron emission tomography. However, there appears to be significant differences between pathologically defined CIA and radiologically defined CIA. Multiple studies have shown that patients with CIA are at increased risk for subsequent aortic events (new aneurysms or dissections) and thus it is recommended to monitor these patients with periodic aortic imaging. While the data is currently limited, there is increasing evidence that at least some patients with CIA may benefit from immunosuppressive therapy.