Publications by authors named "M Felemban"

Inflammatory myofibroblastic tumor is a rare occurring benign tumor composed of myofibroblastic spindle cells. Lung inflammatory myofibroblastic tumor is difficult to diagnose and may mimic lung cancer or infectious etiology. Surgical intervention with final histopathologic confirmation remains the mainstay of diagnosis.

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A simple and highly effective Schiff-base fluorescent chemosensor (S1) was synthesized and characterized by HNMR and fluorescence spectroscopy. The synthesized chemosensor was applied for the selective and sensitive detection of Hg ions. The chemosensor exhibited a strong 'turn-on' fluorescence response in a CHOH/HO (1:9, v/v) solution due to complex formation (S1-Hg) which block photo induce electron transfer (PET).

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Paraquat (PQ) is a potent and widely utilized herbicide known for its effectiveness in controlling a broad spectrum of weeds. Its chemical properties make it an invaluable tool in agriculture, where it helps maintain crop yields and manage invasive plant species. However, despite its benefits in weed management, PQ poses significant risks due to its severe toxicity, which affects multiple organ systems in both humans and animals.

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  • The study investigated the prevalence and risk factors of extended-spectrum beta-lactamase (ESBL)-producing bacteria in children hospitalized for urinary tract infections (UTIs) at a hospital in Saudi Arabia from 2018 to 2022.
  • Out of 242 urine samples analyzed, 20.7% of the isolates were found to be ESBL producers, with previous antibiotic usage and recurrent UTIs identified as significant risk factors.
  • The ESBL-producing bacteria showed high resistance rates to ampicillin and third-generation cephalosporins, but were universally sensitive to meropenem, highlighting the need for better antibiotic management in high-risk pediatric cases.
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  • Supercritical fluids (SCFs) are a safer, eco-friendly alternative to harmful solvents in drug nanoparticle preparation, enhancing drug solubility.
  • The study focuses on using supercritical carbon dioxide (SCCO) to improve the solubility of the chemotherapeutic drug Letrozole (LET) through machine learning models.
  • The research compares several models, finding the RBF-SVM model to be the best performer with a high degree of accuracy (R-squared = 0.9947) and minimal prediction error (0.1289).
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