Background: Regeneration dentistry demonstrates significant challenges due to the complexity of different dental structures. This study aimed to investigate osteogenic differentiation of human pulp stem cells (hDPSCs) cultured on a 3D-printed poly lactic acid (PLA) scaffold coated with nano-hydroxyapatite (nHA) and naringin (NAR) as a model for a dental regenerative. Methods: PLA scaffolds were 3D printed into circular discs (10 × 1 mm) and coated with nHA, NAR, or both. Scaffolds were cultured with hDPTCs to identify cellular morphological changes and adhesion over incubation periods of 3, 7, and 21 days using SEM. Then, the osteogenic potential of PLA, PLA/nHA/NAR, or PLA scaffolds coated with MTA elutes (PLA/MTA scaffolds) were evaluate

Denture cleansing is an essential step that can stop cross‑contamination and adds to the health of the patient, denture durability, and the general quality of life. A disinfection technique must be practical and devoid of damaging effects on the material's properties used to construct the denture base. The main aim of this study is to evaluate the effect of three concentrations of electrolyzed water denture cleanser on heat cure acrylic and polyamide after immersion in electrolyzed water. The evaluation is based on their efficacy on surface hardness, wettability, and color stability compared with one submerged in distilled water as a control group. The method consists of eighty samples of heat-cured acrylic and polyamide material.

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

Diabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, bloo

Purpose: This study aimed to assess the thickness of alveolar bone of maxillary and mandibular incisors from orthodontics perspective. Materials and Method: A total of 73 Cone beam computed tomography for Iraqi patients (47 females and 26 males) were included in this study. The selected images were captured and imported to AutoCAD database software to perform the measurement. To measure alveolar bone thickness, a reference line was drawn through the long axis of each incisor, from the incisal edge to the root apex. Then, labial and lingual/palatal perpendicular lines were drawn to the reference line at 3, 6, and 9mm apically from the cemento-enamel junction (CEJ). Results: The buccal bone is generally thinner than the lingual/palata

Hydrogen sulfide (H₂S) gas sensor based on cobalt–manganese spinel oxide MnCo₂O₄ thin films that were prepared by chemical precipitation and green synthesis methods. Structural, morphological, and compositional characterizations of MnCo₂O₄ thin films were performed using XRD, FE-SEM, EDS, and AFM. It was found through XRD patterns that MnCo₂O₄ was formed in a cubic spinel structure for both methods; however, the chemically precipitated thin films possessed better crystallinity and larger crystallite sizes, whereas the green-synthesized films exhibited slightly lower crystallinities and smaller sizes, as evidenced by the broader peaks observed. In addition, FE-SEM and AFM images revealed that the MnCo₂O₄ films prepared by

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden