The cyanobacterial neurotoxinβ-N-methylamino-L-alanine (BMAA) is considered to be an “excitotoxin,” and its suggested mechanism of action is killing neurons. Long-term exposure to L-BMAA is believed to lead to neurodegenerative diseases including Parkinson’s and Alzheimer’s diseases and amyotrophic lateral sclerosis (Lou Gehrig’s disease). Objectives of this study were to determine the presumptive median lethal dose (LD₅₀), the Lowest-Observed-Adverse-Effect Level (LOAEL), and histopathologic lesions caused by the naturally occurring BMAA isomer, L-BMAA, in mice. Seventy NIH Swiss Outbred mice (35 male and 35 female) were used. Treatment group mice

Platinum nanoparticles (PtNPs) exhibit promising biomedical properties, but concerns about biocompatibility and synthesis-related toxicity remain. This study aimed to develop eco-friendly PtNPs using aqueous broccoli extract as a natural reducing and stabilizing agent, and to assess their multifunctional biomedical potential. PtNPs were synthesized through sonochemical reduction of K₂PtCl₆ in broccoli extract, followed by purification and comprehensive physicochemical characterization. UV–Vis confirmed nanoparticle formation at 253 nm, while XRD and FTIR analyses verified the crystalline FCC structure and phytochemical capping. TEM revealed mainly spherical PtNPs with an average core size of 14.83 ± 7.67 nm. Conversely, DLS showe

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Background: Potentially malignant oral disorders (PMODs) are common precursors of oral squamous cell carcinoma (OSCC). Neoangiogenesis and signalling are important intermediate biomarkers that may govern the progression of dysplastic mucosa into carcinoma. Aims: Evaluate the importance of CD34 and Wnt3 expression in PMODs and OSCCs in relation to their clinicopathological parameters. Settings and Design: Prospective cross-sectional study. Materials and Methods: Immunohistochemical staining for CD34 and Wnt3 was performed for 41 samples. These included 27 PMODs, six OSCCs and eight normal gingival and alveolar mucosa. Analysis of variance (ANOVA) and post-hoc tests were applied. P<0.05 was considered statistically significant. Results: CD34

Background: Abdominoplasty is one of the commonest surgical procedures that performed for those patients who had skin laxity, strive and muscle rectur diastasis. Combined using of liposuction and abdominoplasty it can give better result than traditional abdominoplasty with fear complications. Patient and Method: A total number of 25 female patients with age ranging between 27-55 years were underwent lipoabdominoplasty. With extensive liposuction of abdominal wall and selective undermining together with muscle plication. All of our patients had body mass index more than 30. Patients satisfaction and complication were documented postoperatively. Result: All of our patients had no Major complications and the postoperative period passed unevent