Green synthesis, characterization and optimization of silver nanoparticles from Carica papaya using Box Behnken design and its activity against dental caries causing Streptococcus sp

IF 2.218 Q2 Chemistry Chemical Data Collections Pub Date : 2024-04-26 DOI:10.1016/j.cdc.2024.101139
T. Subha , M. Srilatha , P. Naveen , R. Thirumalaisamy
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Abstract

In current scenario, Oral diseases are the most prevalent and challenging diseases globally and it causes serious health and economic burdens for those who are affected. Carica papaya is used to treat oral diseases in Ayurvedic medicines from very long time. In current study aqueous leaf extract of C. papaya utilize to green synthesize silver nanoparticles for oral pathogen treatment. Green synthesized silver nanoparticles from C. papaya characterized using UV–Visible, FTIR, XRD and SEM analysis. Green synthesis of silver nanoparticles from C. papaya optimized by utilizing Box–Behnken based response surface methodology software. Characterization of green synthesized silver nanoparticles from C. papaya reveals that has maximal absorbance at 510 nm shown strong vibrational band at 3490 cm−1 in IR analysis indicate silver nanoparticle formation. SEM analysis reveals 30–55 nm sized spherical shaped nanoparticles which was further affirmed by XRD analysis. Further green synthesized silver nanoparticles synthesized from C. papaya leaf extract shown anti-microbial activity against dental caries causing microorganism with zone of inhibition values 10, 14, 15 mm diameter respectively against S. mutans (ATCC25175), S. gordonii (ATCC10558), S. anginosus (ATCC33397) dental caries pathogen at 10 µg nanoparticle concentration. The functional groups of bioactive compounds from C. papaya responsible for effective reduction of silver ions and its inhibitory activity against tooth decay causing bacteria were assayed in this current research study. The current study proven that the green synthesized silver nanoparticles from C. papaya leaf extract possess significant applications in dental applications and we recommend this silver nanoparticle found suitable applications in biomaterial applications in dental industry.

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利用 Box Behnken 设计从木瓜中提取银纳米粒子的绿色合成、表征和优化及其抗龋齿链球菌的活性
在当前形势下,口腔疾病是全球最普遍、最具挑战性的疾病,给患者造成严重的健康和经济负担。在阿育吠陀医学中,木瓜很早就被用来治疗口腔疾病。本研究利用木瓜的水性叶提取物来绿色合成银纳米粒子,用于治疗口腔病原体。利用紫外可见光、傅立叶变换红外光谱、X射线衍射和扫描电镜分析对从木瓜中绿色合成的银纳米粒子进行了表征。利用基于 Box-Behnken 的响应面方法软件优化木瓜银纳米粒子的绿色合成。从木瓜中绿色合成的银纳米粒子的特征显示,其最大吸光度在 510 纳米处,红外分析显示在 3490 cm-1 处有强烈的振动带,表明银纳米粒子的形成。扫描电子显微镜分析显示出 30-55 纳米大小的球形纳米粒子,XRD 分析进一步证实了这一点。此外,从木瓜叶提取物中合成的绿色银纳米粒子对龋齿病微生物具有抗微生物活性,在 10 µg 纳米粒子浓度下,对突变酵母菌(ATCC25175)、戈登酵母菌(ATCC10558)和盎格鲁酵母菌(ATCC33397)龋齿病原体的抑制区直径分别为 10、14 和 15 mm。本研究分析了木瓜中有效还原银离子的生物活性化合物官能团及其对蛀牙致病菌的抑制活性。目前的研究证明,从木瓜叶提取物中绿色合成的银纳米粒子在牙科应用中具有重要的应用价值,我们建议这种银纳米粒子在牙科行业的生物材料应用中找到合适的应用。
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来源期刊
Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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