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Research Paper | Biological Engineering | India | Volume 8 Issue 12, December 2019 | Popularity: 6.4 / 10
Combining Studies on Preparation of Metal Nanoparticles from Plant Extracts as Nano-Antibiotic
Shivani Kushwaha, Dr. Jaya Singh Bisen, Pragya Srivastava
Abstract: Nano antibiotics are an arising antibiotics particularly arranged for the multidrug resistance, the infection basically occurred by the medically valuable strains that have genetically altered and become unaffected to the antibiotics. The application of ions of metals and salts being unchanged but precisely a affect the bacterial resistance mechanisms. The plants contain antimicrobial activity can be employed for the complementary therapies as stuff for the nanoparticle creation. The naoparticles have powerfuldestination action on the pathogen as its working efficiency can be altered as per requirement. The naoparticles can be used as tablets and also in suspensions. The multi drug resistantpathogens would be hindered and its strain could be altered for our aim. The employment of alteredspecimen with the salts can be grouped as per the wanted dosage for the bacterial pathogens.
Keywords: Nanoparticles, Nanoantibiotics, Phytocompounds, Phytochemicals, Plantshifts
Edition: Volume 8 Issue 12, December 2019
Pages: 26 - 31
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Biological Engineering, Uzbekistan, Volume 8 Issue 12, December 2019
Pages: 32 - 38Distributed Species of Family Liliaceae and Iridaceae in Tarkapchigai Botanical-Geographical Region (Uzbekistan)
Azizbek S. Abduraimov, Sultankul A. Daniyarov
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Biological Engineering, India, Volume 6 Issue 3, March 2017
Pages: 204 - 207Effect of Immersion (2D vs. 3D) on Attention through Virtual Reality
Rajesh Kumar, Greeshma Sharma, Lokesh Kumar, Sushil Chandra
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Biological Engineering, Iraq, Volume 6 Issue 8, August 2017
Pages: 18 - 23Mathematical Modeling of Delayed Release Dosage Form Dissolution Test and Bioavailability
Auns Hashem, Fadhil Abid, Khawla Rasheed
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Biological Engineering, India, Volume 7 Issue 8, August 2018
Pages: 10 - 13A Comprehensive Study of Machine Learning Models in Radiogenomics
Eash Sharma, Ashwin Garg