Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal Narra J Malacca Pharmaceutics Infolitika Journal of Data Science
El-Shazly, Mohamed
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
The race for clinical trials on Omicron-based COVID-19 vaccine candidates: Updates from global databases Viveiros-Rosa, Sandro G.; Mendes, Cristina DS.; Farfán-Cano, Galo G; El-Shazly, Mohamed
Narra J Vol. 2 No. 3 (2022): December 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i3.88

Abstract

The coronavirus disease 2019 (COVID-19) has caused more than 6.5 million deaths globally as of June 10, 2022. The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) Omicron variant (B.1.1.529) has the greatest transmission rate and can cause hospitalization in vaccinated individuals. It has been the most distinct SARS-CoV-2 variant of concern to date. The existing inactivated vaccines made with the wild-type strain are less efficient to prevent disease and/or hospitalization associated with the Omicron variant, even after a booster dose. Hence, it is crucial to develop new vaccines that are effective against this variant. The objective of this study was to summarize the data on existing clinical trials for new COVID-19 vaccines formulated against Omicron variant. Clinical trials from the international clinical trials registry platforms were searched and analyzed. As of June 10, 2022, a total of 15 clinical trials are available consisting of six and nine clinical trials of inactivated and messenger RNA (mRNA)-based vaccine candidates containing the Omicron variant, respectively. Those trials are evaluating four inactivated and four mRNA-based vaccine candidates. Although Omicron-specific vaccines are highly desired, their development is challenging since the SARS-CoV-2 variant formation is still unpredictable. Although two vaccines from Pfizer and Moderna have been approved for emergency use in the US and the UK for Omicron variant, the Asian pharmaceutical companies such as CNBG (Sinopharm), Sinovac, and Shifa Pharmed also have Phase 3 clinical trials under development and almost all clinical trials are expected to be completed in 2023. These results should help guide academics and policymakers in the COVID-19 vaccine field regarding investments in updated booster doses against the SARS-CoV-2 Omicron variant.
Machine Learning Approach for Diabetes Detection Using Fine-Tuned XGBoost Algorithm Maulana, Aga; Faisal, Farassa Rani; Noviandy, Teuku Rizky; Rizkia, Tatsa; Idroes, Ghazi Mauer; Tallei, Trina Ekawati; El-Shazly, Mohamed; Idroes, Rinaldi
Infolitika Journal of Data Science Vol. 1 No. 1 (2023): September 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i1.72

Abstract

Diabetes is a chronic condition characterized by elevated blood glucose levels which leads to organ dysfunction and an increased risk of premature death. The global prevalence of diabetes has been rising, necessitating an accurate and timely diagnosis to achieve the most effective management. Recent advancements in the field of machine learning have opened new possibilities for improving diabetes detection and management. In this study, we propose a fine-tuned XGBoost model for diabetes detection. We use the Pima Indian Diabetes dataset and employ a random search for hyperparameter tuning. The fine-tuned XGBoost model is compared with six other popular machine learning models and achieves the highest performance in accuracy, precision, sensitivity, and F1-score. This study demonstrates the potential of the fine-tuned XGBoost model as a robust and efficient tool for diabetes detection. The insights of this study advance medical diagnostics for efficient and personalized management of diabetes.
Hybrid Handwash with Silver Nanoparticles from Calotropis gigantea Leaves and Patchouli Oil: Development and Properties Salsabila, Indah; Khairan, Khairan; Kemala, Pati; Idroes, Ghifari Maulana; Isnaini, Nadia; Maulydia, Nur Balqis; El-Shazly, Mohamed; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.206

Abstract

When washing hands, handwashing is one way to prevent diseases caused by bacteria such as Staphylococcus aureus and Escherichia coli, the most common bacteria that can cause infections. The production of handwash utilizing silver nanoparticles as an active antibacterial agent remains a relatively infrequent practice. The synthesis of silver nanoparticles from the leaves of Calotropis gigantea, which grows in the geothermal area of Ie Seu-um Aceh Besar, has been carried out using the green synthesis method and hybrid green synthesis with patchouli oil. Handwash with active ingredients such as silver nanoparticles was successfully formulated, evaluated, and tested against S. aureus and E. coli. The organoleptic characteristics, pH, viscosity, foam height measurements, density, irritation, and antibacterial activity against S. aureus and E. coli were evaluated. The results showed that the organoleptic properties of the handwash with silver nanoparticles were not changed during a 30-day storage period, with pH values in the range of 9.7-10.3, and did not cause irritation upon using silver nanoparticle handwash. The best formula for handwashing with silver nanoparticles in inhibiting the growth of S. aureus and E. coli bacteria was F2, with inhibition zones of 12.9 ± 2.85 mm and 10.95 ± 0.8 mm, respectively. The formulated handwash with silver nanoparticles met the requirements of good liquid soap according to the Indonesian National Standard (SNI) with potent antibacterial activity.
Co-Authors Faisal, Farassa Rani Farfán-Cano, Galo G Ghazi Mauer Idroes Idroes, Ghifari Maulana Isnaini, Nadia Kemala, Pati Khairan Khairan Maulana, Aga Maulydia, Nur Balqis Mendes, Cristina DS. Rinaldi Idroes Rizkia, Tatsa Salsabila, Indah Teuku Rizky Noviandy TRINA EKAWATI TALLEI Viveiros-Rosa, Sandro G.