Background: Periodontitis is an infection attributable to multiple infectious; it causes an interrelated cellular and humoral host immune responses. Recent reports have indicated that human cytomegalovirus (HCMV) may contribute to pathogenesis of periodontitis. The HCMV can stimulate the release of cytokines from inflammatory and non-inflammatory cells and weaken the periodontal immune defense. This study aimed to reveal the presence of anti-CMV IgG, and determine the levels of IL‐6 and TNF-α and to correlate the presence of cytomegalovirus (CMV) with cytokines levels. Materials and Methods: Forty patients with chronic periodontitis and 40 healthy control subjects (their age and sex were matched with the patients) were involved

Three new hydrazone derivatives of Etodolac were synthesized and evaluated for their anti-inflammatory activity by using egg white induced paw edema method. All the synthesized target compounds were characterized by CHN- microanalysis, FT-IR spectroscopy, and ¹HNMR analysis. The synthesis of the target (P1-P3) compounds was accomplished following multistep reaction procedures. The synthesized target compounds were found to be active in reducing paw edema thickness and their anti-inflammatory effect was comparable to that of the standard (Etodolac).

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

There is a correlation between the occurrence of anxiety and the production of inflammatory mediators, and red ginger rhizome is a well-known herbal product with a high content of phenolic and flavonoid compounds that can be used as anti-inflammatories and antioxidants. The aim of study to evaluate the effect of red ginger as antianxiety in mice (Mus musculus) BALB/c strain by measuring levels of TNF-α, IL-6 and IL-10.  Anxiety model mice were carried out by giving treatment with the Forced Swimming Test (FST) for 7 days then assessed by carrying out the Elevated Plus Maze for Mice (EPM) test for one day. After the treatment, the anxiety mice model was made, followed by administration of red ginger ethanol extract therapy for 14 days.

The prostaglandins inside inflamed tissues are produced by cyclooxygenase-2 (COX-2), making it an important target for improving anti-inflammatory medications over a long period. Adverse effects have been related to the traditional usage of non-steroidal anti-inflammatory drugs (NSAIDs) for the treatment of inflammation, mainly centered around gastrointestinal (GI) complications. The current research involves the creation of a virtual library of innovative molecules showing similar drug properties via a structure-based drug design. A library that includes five novel derivatives of Diclofenac was designed. Subsequently, molecular docking through the Glide module and determining the binding free energy implementing the P

Helminthiasis is a significant economic burden on grazing cattle. Increased resistance to currently available synthetic anthelmintics used to treat helminthiasis, and anthelmintic residues in meat and dairy products pose a significant worldwide health threat. These obstacles require the development of new anthelmintics capable of combating drug resistance while also exhibiting improved safety profiles. Rhynchosia cana (Fabaceae) is a herb that has historically been used as a worm expeller. To evaluate the phytochemical profile and explore the anti-oxidant and anthelmintic effects of different extracts of Rhynchosia cana (R. cana) by In silico and In vitro methods. Using standardised chemical t

Background: Crohn's disease (CD) is an immunological disorder associated with chronic inflammatory process of several unspecific regions of gastrointestinal tract but frequently detected in the terminal Ilium and proximal colon or both. This disease frequently presented with various oral manifestations as a consequence of inflammatory process of the disease, nutritional deficiency or medications side effects. Several therapeutic approaches have been developed for CD management that are targeting the inflammatory process and directed at controlling the host immune response. Immunosuppressants such as Azathioprine and anti-TNF α agents as well as the combination of them have been widely used as an effective therapeutic modality with a bett

Background: Decontamination of gutta percha cones was important factor for success of root canal treatment. The aim of the present in vitro study was to identify and to compare the antimicrobial effect of following disinfection solutions: 0.2% chlorhexidine gluconate, Iodine, tetracycline hydrochloride solution, EDTA & formocresol mixed with zinc oxide eugenol, on E faecalis, E coli and Candida albicans using sensitivity test Materials and Methods: Three types of microorganisms were isolated from infected root canals (E faecalis, E coli and Candida albicans) and cultured on Mueller Hinton agar petri-dishes. Disinfection of gutta percha cones done by immersion in six disinfection solutions (six groups), the groups are: distill water (used a

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20