Dietary fructose can disturb hepatic lipid metabolism in a way that leads to lipid accumulation and steatosis, which is often accompanied with low-grade inflammation. The macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine with important role not only in the regulation of inflammation, but also in the modulation of energy metabolism in the liver.

Background and Objectives: FK506 binding protein like (FKBPL) is a member of the immunophilin family, with anti-angiogenic effects capable of inhibiting the migration of endothelial cells and blood vessel formation. Its role as an inhibitor of tumor growth and angiogenesis has previously been shown in studies with breast and ovarian cancer. The role of FKBPL in angiogenesis, growth, and carcinogenesis of endometrioid endometrial carcinoma (EEC) is still largely unknown. The aim of this study was to examine the expression of FKBPL in EEC and benign endometrial hyperplasia (BEH) and its correlation with the expression of vascular endothelial factor-A (VEGF-A) and estrogen receptor alpha (ERα). Materials and Methods: Specimens from 89 patients with EEC and 40 patients with BEH, as well as histological, clinical, and demographic data, were obtained from the Clinical Hospital Centre Zemun, Belgrade, Serbia over a 10-year period (2010–2020). Immunohistochemical staining of the tissue was performed for FKBPL, VEGF-A, and ERα. Slides were analyzed blind by two pathologists, who measured the intensity of FKBPL and VEGF-A expression and used the Allred score to determine the level of ERα expression. Results: Immunohistochemical analysis showed moderate to high intensity of FKBPL expression in 97.5% (n = 39) of samples of BEH, and low or no expression in 93.3% (n = 83) of cases of EEC. FKBPL staining showed a high positive predictive value (98.8%) and a high negative predictive value for malignant diagnosis (86.7%). The difference in FKBPL expression between EEC and BEH was statistically significant (p < 0.001), showing a decrease in intensity and loss of expression in malignant tissues of the endometrium. FKBPL expression was positively correlated with ERα expression (intensity, percentage and high Allred score values) and negatively correlated with the expression of VEGF-A (p < 0.05 for all). Conclusions: FKBPL protein expression demonstrated a significant decrease in FKBPL in EEC in comparison to BEH tissue, with a high predictive value for malignancy. FKBPL might be emerging as a significant protein with antiangiogenic and antineoplastic effects, showing great promise for the diagnostic and therapeutic applications of its therapeutic derivatives in gynecological oncology.

Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify discrete changes in cell and tissue textural features. Previous research has indicated that these methods may be applicable in the pathology for identification and classification of various types of cancers. In this study, we present findings that squamous epithelial cells in laryngeal carcinoma, which appear morphologically intact during conventional pathohistological evaluation, have distinct nuclear GLCM and DWT features. The average values of nuclear GLCM indicators of these cells, such as angular second moment, inverse difference moment, and textural contrast, substantially differ when compared to those in noncancerous tissue. In this work, we also propose machine learning models based on random forests and support vector machine that can be successfully trained to separate the cells using GLCM and DWT quantifiers as input data. We show that, based on a limited cell sample, these models have relatively good classification accuracy and discriminatory power, which makes them suitable candidates for future development of AI-based sensors potentially applicable in laryngeal carcinoma diagnostic protocols.