Background: Odontogenisis is a complex process controlled by dynamic and reciprocal interactions that regulated by various molecules. Thymosin β4 is a small bioactive peptide with wide spectrum biological effects on much cell types. The present study was designed to highlight the effect of synthetic exogenous Tβ4 on developing dental tissue of the upper central teeth of rats, by histological examination and immunohistochemical evaluation of TGFβ1. Materials and method: Thirty six Albino Wister pregnant rat 18control group received intraperitoneal injection of normal saline and the others are experimental group received 50µg/300µl of Tβ4 injection. The animals were sacrificed at periods 16th and 18th day I.U.L and one day post natal, as six animals for each period. Histological and immunohistochemical evaluation for expression of TGF β1 in dental tissue of upper central teeth of the rat were done Results: In-vivo results showed that experimental group had accelerated stages of tooth development with acceleration in deposition of dental hard tissue (enamel and dentin) with high positive expression of TGF β1by enamel organ, dental papilla and dental sac cells. Conclusion: these data suggest synthetic exogenous Tβ4 act as bioactive initiator enhances tooth development by stimulating proliferation and differentiation of both epithelial and mesenchymal cells.
The purpose of this study was to measure serum levels of insulin-like growth factor-binding protein (IGFBP7), Insulin-like Growth Factor 1 (IGF-1), Growth Hormone (GH), Interleukin 6 (IL-6) and insulin in acromegaly patients and healthy controls. The acromegaly group had 60 patients, while the population group had 30 people who had never had acromegaly before. The concentration of IGFBP7, IGF-1, GH, IL-6, and insulin were determined. The results of the present study indicate that IGFBP7 level in the acromegaly group was significantly lower (1.690.07 ng/mL vs. 2.740.12 ng/mL, respectively, p = 0.001). IGF-1, GH, IL-6, and insulin concentrations were also significantly higher in acromegaly patients. The diagnostic accuracy (2.194) was exce
... Show MoreBackground: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach
... Show MoreWe aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show More