Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was us

The cost-effective removal of heavy metal ions represents a significant challenge in environmental science. In this study, we developed a straightforward and efficient reusable adsorbent by amalgamating chitosan and vermiculite (forming the CSVT composite), and comprehensively investigated its selective adsorption mechanism. Different techniques, such as Fourier-transform infrared spectroscopy (FTIR), zeta potential analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer, Emmett, Teller (BET) analysis were employed for this purpose. The prepared CSVT composite exhibited a larger surface area and higher mesoporosity increasing from 1.9 to 17.24 m2/g compared to pristine chitosan. The adsorption capabilities of the

The aim of our study was to investigate the antiviral activity of the Corchorus olitorius family Tiliaceae cultivated in Iraq against measles virus, and to demonstrate an overview about chemical constituents and pharmacological activity of Corchorus olitorius L.

About150 gm Leaves of Corchorus. olitorius were defatted by maceration in hexane for 24 hrs. The defatted plant materials were subjected for extraction after filtration using Soxhlet apparatus, with aqueous methanol 85% as a solvent extraction for 24 hours, the extract was filtered, and the solvent was evaporated under reduced pressure using a rotary evaporator to get a dry extract of about 12 gm. About 4 gm from the residue was suspended in 100

High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

Here we determined the structure of a cold active family IV esterase (EstN7) cloned from Bacillus cohnii strain N1. EstN7 is a dimer with a classical α/β hydrolase fold. It has an acidic surface that is thought to play a role in cold-adaption by retaining solvation under changed water solvent entropy at lower temperatures. The conformation of the functionally important cap region is significantly different to EstN7's closest relatives, forming a bridge-like structure with reduced helical content providing greater access to the active site through more than one substrate access tunnel. However, dynamics do not appear to play a major role in cold adaption. Molecular dyn

Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health