Potential biological application of silver nanoparticles synthesized from Citrus paradisi leaves.
Developing sustainable and eco-friendly methods for nanoparticle (NP) production in an era of environmental consciousness is crucial. This study introduces a novel approach to synthesizing silver (Ag) NPs using Citrus paradisi leaves extract (CPLE) as a green precursor at optimum conditions of the AgNO3 (2 mM) with CPLE in 1:3 ratio, at pH 14 and 80 °C temperature for reaction time of 4 h. The CP@AgNPs were formed and stabilized by Naringen, a major Citrus paradisi component. CP@AgNPs were thoroughly characterized through ultraviolet-visible (UV-vis) and Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) analysis, and field emission scanning electron microscopy (FE-SEM) imaging techniques. CP@AgNPs demonstrated SPR peak at 450 nm, face cubic crystal structure, the average size of 8 nm, rod-shaped particle adsorbed on quasi-spherical shaped agglomerated NPs, significantly impacting both environmental and biomedical fields. In the catalytic degradation experiment, an application for environment pollutant reducer, CP@AgNPs, achieved an impressive 85% degradation efficiency of the methyl orange (MO) dye, showcasing their potential as a sustainable solution for wastewater treatment. Additionally, CP@AgNPs exhibited potent anti-biofilm properties, with half maximal inhibitory concentration (IC50) values of 0.13 and 0.12 mg/ml against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), respectively, indicating their promise in addressing biofilm-related issues in healthcare and industrial settings. CP@AgNPs also displayed exceptional antioxidant potential with IC50 values of 2.02, 0.07, and 0.035 mg/ml for CPLE, CP@AgNPs, and ascorbic acid, respectively, in scavenging DPPH radical, suggesting their utility in biomedical applications for mitigating oxidative stress. Notably, the bio-activity results of CP@AgNPs surpassed those of CP leaf extract, highlighting the enhanced properties achieved through this green synthesis approach. This study provides a sustainable and environmental remediation to biomedical science.
Akhter N
，Batool M
，Yaqoob A
，Shahid M
，Muhammad F
，Khan J
，Mudassir MA
，Rasheed M
，Javed S
，Al Farraj DA
，Alzaidi I
，Iqbal R
，Malaga-Toboła U
，Gancarz M
... -
《Scientific Reports》
Cytotoxic activity of silver nanoparticles prepared by eco-friendly synthesis using Lythrum salicaria extract on breast cancer cells.
Metal nanoparticles (NPs) have widely been investigated due to their several applications in therapeutic activities. The current investigation highlights the cytotoxic effects of the eco-friendly phytosynthesis route for silver nanoparticles using Lythrum salicaria (L. salicaria) extract (AgNPs-LS).
The change in color from colorless to brown confirmed the reduction of silver ions to AgNPs. x-ray diffraction (XRD) analysis demonstrated high crystallinity. The surface morphology of AgNPs-LS was spherical, and their average sizes were 50 nm. energy-dispersive x-ray analysis (EDAX) confirmed that silver was the predominant component, indicating the involvement of L. salicaria plant extract in the green synthesis process. In vitro dimethyl thiazolyl tetrazolium bromide (MTT) assay showed significant cytotoxicity of AgNPs-LS against MCF7 cells, with an IC50 of 113 µg mL- 1. In contrast, AgNPs-LS showed minimal cytotoxicity to HEK293 cells (IC50: 254 µg mL- 1), demonstrating a higher sensitivity of cancer cells to AgNPs-LS. Moreover, AgNPs-LS resulted in MCF7 cells producing reactive oxygen species (ROS) and undergoing cell cycle arrest at the G2/M phase, serving as barriers to the proliferation of cancer cells. Annexin V fluorescein isothiocyanate (FITC) assays and fluorescence microscopy confirmed the induction of apoptosis in MCF7 cells by AgNPs-LS. Gene expression analysis revealed upregulated pro-apoptotic genes (Bax, p53, caspase-3, and caspase-9) and downregulated an anti-apoptotic gene (Bcl2) in michigan cancer foundation7 (MCF7) cells treated with AgNPs-LS.
These results indicate that AgNPs-LS induced apoptosis via the intrinsic pathway (mitochondrial-mediated mechanism) and involved p53-dependent regulation. The current study results implied that AgNPs-LS fabricated by a bio-green approach could be helpful to the future of nanomedicine.
Shandiz SAS
，Hashemi A
，Rezaei N
，Haghani B
，Baghbani-Arani F
... -
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Green-synthesized silver nanoparticles induced apoptotic cell death in CACO2 cancer cells by activating MLH1 gene expression.
MLH1 (Mult homolog1) gene is the main element of Multlα heterodimer and plays a role in the repair of base-base mismatches and deletion and addition loops. When the MLH1 protein is not present, the number of errors that remain unrepaired increases, and this can lead to the formation of tumors in the body. Colorectal cancer is the third most common type of cancer in terms of incidence and the third type of cancer in terms of mortality worldwide. In this regard, the present study was conducted with the aim of investigating the effect of biological silver nanoparticles with anticancer properties and MLH1 gene expression on cancer cell samples of people with colorectal cancer. In this study, the green synthesis of silver nanoparticles was carried out by precipitation method with reduction of silver ions by leaf and flower extract of Moringa oleifera plant. Then, silver nanoparticles were confirmed using UV-visible spectroscopy, transmission and scanning electron microscopy. The cytotoxic effects of nanoparticles on cells were evaluated by MTT colorimetric method within 42 h. After RNA extraction of treated cells, cDNA synthesis and primers were designed by the Exon-Exon Junction method and the Real-time Polymerase test for MLH1 and Beta-actin genes was repeated three times. The final analysis of the results was done using Graphpad Prism and Rest 2009 software. The presence of a peak at the wavelength of 234 nm for the synthesized silver nanoparticles was confirmed by ultraviolet-visible spectroscopic analysis. The morphological study on the size and shape of the silver nanoparticles showed that the nanoparticles are spherical and have a size between 40 and 34 nanometers in diameter. The leaf extract typically produces smaller, more uniform particles than the flower extract. The Green-Synthesized Silver Nanoparticles of leaf extract were used to evaluation of induced Apoptotic Cell Death in CACO2 Cancer Cells by Activating MLH1 Gene Expression. MTT results showed that the anti-proliferative effect of nanoparticles depends on the concentration of synthesized silver nanoparticles. The treatment of MLH1 cancer cell line and normal with synthesized nanoparticles at a concentration of 0.44 micrograms per ml for 42 h showed the effects of cell toxicity. The percentage of cancer cell death under the influence of quercetin present in Moringa green bio-particles depends on the concentration and time, and this difference is statistically significant compared to the control group (P < 0.05). So that the lethal dose of the extract for 50% survival IC50 in a period of 48 h for intestinal cancer cells was equal to 21 μg/ml, and the expression ratio of the MLH1 gene in the tumor tissue to the adjacent healthy tissue has increased (P ≤ 0.05).
Khajeh H
，Fazeli-Nasab B
，Pourshahdad A
，Mirzaei AR
，Ghorbanpour M
... -
《Scientific Reports》
Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
... -
《-》
ResearchGate
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钛学术
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