Effects of abdominal and vaginal hysterectomy on anorectal functions along with quality of life of the patient

Objectives and background:Hysterectomy is the most commonly performed major gynecological operation for both benign and malign gynecologic conditions. After hysterectomy, although some investigators have declared an increased incidence of urinary and anorectal dysfunction, some others could not show any connection. Methods: The voluntary patients were divided in two groups: abdominal hysterectomy (Group 1) and vaginal hysterectomy (Group 2). Anal manometry and all the other examinations of the patients were performed at the Department of General Surgery Endoscopy Unit of Ankara University, Faculty of Medicine. Results: When the quality of life of the patients was assessed before the operation and on the 12 th post-operative month via the SF-36 form; it can be seen that body pain parameters of the patients in Group 1 had significantly improved and there is no statistical difference in other parameters. When the effect of hysterectomy on the quality of life of the patients was evaluated by the “Cleveland Clinic Global Quality of Life” form, the statistically significant improvement in the quality of life of the patients in Group 2 was observed. Conclusion: If the type of operation (vaginal or abdominal) is performed due to benign causes, it does not affect the urinary and anorectal functions of the patients. Depending on the decrease of complaints of the patients, it has a positive effect on the quality of life. © 2018 Birsen et al

Derived vascular endothelial cells induced by mucoepidermoid carcinoma cells: 3-dimensional collagen matrix model*

Mucoepidermoid carcinoma undergoes uniquely vigorous angiogenic and neovascularization processes, possibly due to proliferation of vascular endothelial cells (ECs) induced by mucoepidermoid carcinoma cells (MCCs) in their three-dimensional (3D) microenvironment. To date, no studies have dealt with tumor cells and vascular ECs from the same origin of mucoepidermoid carcinoma using the in vitro 3D microenvironment model. In this context, the current research aims to observe neovascularization with mucoepidermoid carcinoma microvascular ECs (MCMECs) conditioned by the microenvironment in the 3D collagen matrix model. We observed the growth of MCMECs purified by immunomagnetic beads and induced by MCCs, and characteristics of tubule-like structures (TLSs) formed by induced MCMECs or non-induced MCMECs. The assessment parameters involved the growth curve, the length, the outer and inner diameters, and the wall thickness of the TLSs, and the cell cycle. Results showed that MCCs induced formation of the TLSs in the 3D collagen matrix model. A statistically significant difference was noted regarding the count of TLSs between the control group and the induction group on the 4th day of culture (t=5.00, P=0.001). The outer and inner diameters (t 1=5.549, P 1=0.000; t 2=10.663, P 2=0.000) and lengths (t=18.035, P=0.000) of the TLSs in the induction group were statistically significant larger than those in the control group. The TLSs were formed at the earlier time in the induction group compared with the control group. It is concluded that MCCs promote growth and migration of MCMECs, and formation of the TLSs. The 3D collagen matrix model with MCMECs induced by MCCs in the current research may be a favorable choice for research on pro-angiogenic factors in progression of mucoepidermoid carcinoma

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies