Inhibition of breast cancer MDA cells line with gold nanoparticles irradiated with beta particles

Inhibition of breast cancer MDA cells line with gold nanoparticles irradiated with beta particles | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Inhibition of breast cancer MDA cells line with gold nanoparticles irradiated with beta particles Sala Sami Hamza, Ruwiadah Tarek Mahdi, Ban H. Adil, Ban Sabah Hameed, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6797293/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Dec, 2025 Read the published version in BioNanoScience → Version 1 posted 12 You are reading this latest preprint version Abstract Amid the ongoing challenges faced by traditional cancer therapies, the use of nanomaterials as smart carriers for beta-minus-emitting radionuclides has emerged as a promising approach for targeted cancer treatment, In this study, gold nanoparticles (Au NPs) were fabricated by a plasma jet system using gold salts at a concentration of 0.6 mM and loading them with negative beta particles at doses of 1.2 KGy و14.4 KGy and 15.6 KGy The following tests were performed: FE-SEM, XRD, and UV.The UV peaks were located between 680 and 720 nm, and the XRD values for Au were 38.76 (111), 44.4 (200), and 77.5 (311), along with the impact on the MDA cell line for breast cancer.After 48 hours, the maximal growth inhibition of AuNPs irradiated 15.6 KGy was 60%. After 48 hours of exposure to 14.4 KGy of AuNPs, the normal cell line (REF) showed the highest toxicity of 15.3%. AuNPs β-particles plasma jet MDA cells line REF cells line Adriamycin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Abstract image Introduction The modern age faces cancer as one of its most severe health challenges. This disease manifests as cells multiply uncontrollably which causes them to form tumors and spread throughout the body. The World Health Organization reports that cancer stands as one of the primary global causes of death while emphasizing the growing number of cases attributed to environmental and genetic influences combined with contemporary lifestyle habits [ 1 ][ 2 ]. The medical community continues searching for cancer treatments that work better while causing less harm to healthy tissues despite significant progress being made in this field. Doctors commonly use radiotherapy against cancer because radiation helps destroy cancer cells or inhibit their development. Traditional radiotherapy with X-rays and gamma rays proves effective against tumors but frequently harms surrounding healthy tissues [ 3 ][ 4 ]. Beta particle therapy stands out as an innovative cancer treatment because it allows for precise targeting of malignant cells while preserving surrounding healthy tissues. The radioactive decay of isotopes Strontium-90 and Yttrium-90 produces beta-minus radiation which provides a treatment option for different cancer types such as bone and liver cancer. Research demonstrates that radioactive particles achieve penetration into cancerous tissues where they inflict DNA damage that results in either stopping cancer cell growth or eliminating them entirely [ 5 ][ 6 ]. A research project [ 7 ] executed study demonstrated that Strontium-90 effectively decreased bone tumor size and relieved pain in advanced bone cancer patients. A study demonstrated that liver tumor sizes decreased by 60% with Yttrium-90 SIRT application and showed significant survival rate enhancements [ 8 ]. New studies demonstrate that beta radiation shows increased effectiveness alongside immunotherapy because it enhances the immune system's ability to target cancer cells [ 9 ][ 10 ]. The emerging research indicates beta radiation will play a central role in developing sophisticated therapies which deliver superior results with reduced adverse effects. As medical science progresses, now have cancer treatment options that go beyond just chemotherapy and radiotherapy. The focus of modern medical advancements has shifted towards accurate technological developments with nanotechnology emerging as the primary driver. Gold nanoparticles represent a primary application in medical technology because they utilize their unique physical and chemical properties to serve as intelligent instruments for diagnostic and therapeutic uses. Gold nanoparticles enhance radiation treatment by precisely focusing on cancer cells while protecting adjacent healthy tissues from radiation exposure [ 11 ][ 12 ][ 13 ][ 14 ]. Medical treatment has undergone a significant transformation by combining nanotechnology with radiation therapy to enhance patients' quality of life and reduce their suffering. The significance of this research lies in its development of treatment methods designed to destroy cancer cells without producing harmful side effects. Studies on gold nanoparticles combined with radiotherapy introduce essential solutions to medical issues through innovative therapeutic methods. This study investigates how beta-minus radiation impacts cancer cells by examining its therapeutic mechanism and outcomes and reducing damage. techniques and safer effective therapies for patients within the rapidly progressing area of radiation medicine. Material and method In this study, the work method was carried out in several steps there are 1. Gold nanoparticle (AuNP) synthesis A plasma jet device was used to synthesize Au NPs.Aqueous tetrachloride salts (HAuCl4.4H2O), produced by Glentham in the United Kingdom, were utilized; they weighed 411.8476 g in part and were 99% pure.Eq. (1) [ 15 ] was used to get the necessary concentration (mol/L) from a volume of 100 mL of 0.6 mM. $$\:Concentration\left(mole\right)=\frac{mass\left(g\right)}{Molecular\:weight\left(\frac{g}{mol}\right)\times\:volume\left(liter\right)}\:\:\:\:\:\dots\:.1$$ Using the gas argon (Ar). included a gas flowmeter with a 3 L/min calibrator, were connected to the power supply's cathode, and could withstand DC voltages of up to 25 kV. The glass beaker containing the aqueous tetrachloride is poured into a tiny beaker (about 25 mm in size), which is then set on a moving holder beneath the metal tube.The anode, which is made of stainless steel, is 7 cm long, 5 mm wide, and has a 1x1 cm strip end, as seen in the figure.1 2- Loading negative beta particles on AuNPs Gold nanoparticles were irradiated using the strontium radioactive source Sr-90, is a strong and pure radiation source for negative beta particles, and the doses for each sample were as follows: 1.2 KGy, 14.4 KGy and 15.6 KGy the equivalent dose to the radioactive source was calculated as 50 Gy/hr. the irradiation time for each sample was calculated, and its value was as follows: 0.024 (hr.), 0.288 (hr.) and 0.312 (hr). 3- MDA and REF, two cell lines, were used to culture both normal and breast cancer cells. For my organizations, the Al-Nahrain University Biotechnology Centre donated cells. Trypsin EDTA was used in this instance to extract the cells, followed by the addition of PRMI 10% culture media and the distribution of 10,000 cells per well using a microplate 96 well. Following a 24-hour incubation period at 37 degrees Celsius, the cells were examined to see whether a monolayer had developed [ 16 ]. There were groups created on the 96-well Lear microplate.groups were given diluted concentrations in the following order: 100%, 50%, 25%, of AuNPs loaded negative beta particle and three set exposed chemotherapy(Adriamycin)15µl,25µland 35µl and exposed 9set combination between three diluted of AuNPs and dose of Adrimycin, The cells were exposed 24and 48 hours after being dyed with 50 µg of Crystal Violet for twenty minutes to an inspection at 37° C for dye and put in an incubator. Finally calculated of growth inhibition using Eq. 2[ 16 ] $$\:Growth\:inhibition\:\left(GI\right)\%=\frac{control-treated}{control\:}\times\:100\%\:\:\:\:\:\:\dots\:\dots\:2$$ Result and discussion The UV-Vis spectral analysis of gold nanoparticles (AuNPs) synthesize using plasma jet exhibited a well-defined surface plasmon resonance (SPR) peak centered at 545 nm, which is consistent with the typical optical signature of colloidal AuNPs in the size range of 30–50 nm as shown in Fig. 2 . This SPR peak, which is extremely sensitive to variations in particle size, shape, dielectric environment, and interparticle spacing, results from the collective oscillation of conduction band electrons in response to incoming light.Following irradiated of negative bata particles, a noticeable blue-shift in the SPR peak to 530 nm was observed, accompanied by a decrease in absorbance intensity. This spectral shift can be attributed to several interrelated effects. Particle Size Reduction or Reshaping,Beta irradiation may induce fragmentation or reshaping of the nanoparticles, leading to smaller or more spherical particles. Since smaller AuNPs exhibit SPR peaks at shorter wavelengths, this morphological modification can account for the observed shift [ 17 ].The findings demonstrate the presence of spherically shaped Au nanoparticles and are consistent with those found in previous studies that used Mie theory to model the light scattering spectra of Au nanoparticles [ 18 ]. Figure.The Xray diffraction (XRD) patterns of dried gold particles Au NPs were prepared using a plasma jet system, and their positions are consistent with the values in the standard card (JCPDS file No. 040784), as shown in Fig. 3 . The peak intensity (111) at 38.8° is indexed for the facecentered cubic (FCC) structure of Au NPs, and 2θ = 38° (1 1 1), 45° (2 0 0), 64° (2 2 0), and 78° (3 1 1) [ 19 ]. The structural effects of beta particle irradiation on noble metal nanoparticles such as gold (AuNPs) were evaluated using X-ray diffraction (XRD) analysis. Post-irradiation, the XRD patterns revealed clear peak broadening, indicative of reduced crystallite size due to lattice fragmentation or disorder. Moreover, a notable decrease in peak intensity was observed, suggesting the introduction of crystalline defects such as vacancies and dislocations. In some cases, slight shifts in peak position (2θ) were detected, which can be attributed to internal microstrain and lattice distortion caused by the high-energy impact of β-particles [ 20 ]. These shifts reflect subtle changes in interplanar spacing and crystal symmetry. Such irradiation-induced modifications—including decreased crystallinity, enhanced microstrain, and possible amorphization—have critical implications for the physicochemical properties of nanoparticles, potentially altering their optical, catalytic, and biological behaviors [ 21 ]. Therefore, understanding these structural changes is essential when designing nanoparticle-based systems for applications in radiation environments, such as medical diagnostics, biosensing, or radiation shielding. When MDA cell line is exposed to Au NPs combination with Adrimycin chemotherapy in different concentration (10µg,25 µg and35 µg) there is a synergism effect after 24, 48 hrs of incubation, present synergism effect and the growth inhibition increase with increasing dose of radiation of bata particles combination with Adrimycin chemotherapy and also no synergismeffect after 24, 48 hrs of incubation in REF cell line. Shown Fig. 4 , 5 , 6 , 7 We notce the highest rate of inhibition of cancer cells 55.3% at 24 hours and 74.3% at 48 hours, as shown in Figs. 4 and 5 , respectively. While the highest rate of inhibition of normal cells 23% at 24 hours and 27.6% at 48 hours, as shown in Figs. 6 and 7 , respectively. Conclusion The results obtained in this study highlight the significant possible of using radiation-loaded nanomaterials in the treatment of cancerous tumors. These radiation-carrying nanomaterials have demonstrated a high capacity to selectively target cancer cells while minimizing damage to healthy tissues, representing a substantial advancement toward improving therapeutic safety. Furthermore, it was observed that combining this approach with chemotherapy leads to a synergistic effect that enhances therapeutic efficacy and more effectively inhibits tumor cell growth. The functional interaction between the physical and chemical properties of nanomaterials and the biological environment of the targeted tissues opens promising research avenues for the development of multifunctional therapeutic platforms. Therefore, employing nanomaterials as smart carriers for radiation represents an innovative and promising direction in the development of targeted and safer treatments, aligning with contemporary trends in precision medicine and personalized therapy. the combining these radionuclide-loaded nanocarriers with chemotherapy results in a synergistic effect, improving tumor inhibition efficiency. The tunability of the physicochemical properties of nanomaterials, coupled with their interaction with the unique tumor microenvironment, provides a foundation for the development of multifunctional theranostic platforms. This research aims to explore the therapeutic potential of beta-minus-emitting nanomaterial-based carriers within a combined therapy framework, highlighting their role in advancing precision medicine and personalized cancer treatment. Declarations Declaration of Interest Statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding: The authors declare that no funding was received from any organization or agency in support of this research . Ethics Approval and Consent to Participate : Not applicable. This study did not involve human participants or animals. Consent to Publish : Not applicable. Author Contributions Statement: Sala Sami Hamza : Conceptualization, Methodology, Investigation, Data Curation, Formal Analysis, Writing – Original Draft. Ruwiadah Tarek Mahdi : Methodology, Investigation, Data Curation Ban H. Adil : Supervision, Project Administration, Methodology, Validation, Data Analysis, Visualization, Writing – Review & Editing. Ban Sabah Hameed : Formal Analysis, Writing – Original Draft. A.S. Obaid : Resources, Writing – Review & Editing, Funding Acquisition. All authors have read and approved the final manuscript References Ferlay, Jacques, Colombet, M., Soerjomataram, I., Mathers, C., Parkin, D. M., Piñeros, M., Znaor, A., & Bray, F. (2020). Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2018. International Journal of Cancer , 147(6), 2020–2029. Sung, Hyuna, Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians , 71(3), 209–249. Bentzen, Søren M. (2006). 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Journal of Nanobiotechnology, 19(1), 1–24. https://doi.org/10.1186/s12951-021-00838-4 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Dec, 2025 Read the published version in BioNanoScience → Version 1 posted Editorial decision: Revision requested 18 Jul, 2025 Reviews received at journal 11 Jul, 2025 Reviewers agreed at journal 07 Jul, 2025 Reviews received at journal 04 Jul, 2025 Reviewers agreed at journal 03 Jul, 2025 Reviews received at journal 01 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers invited by journal 01 Jul, 2025 Editor assigned by journal 01 Jul, 2025 Submission checks completed at journal 30 Jun, 2025 First submitted to journal 01 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6797293","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479201101,"identity":"bf029132-4e25-421e-9400-9b74a048d7d6","order_by":0,"name":"Sala Sami Hamza","email":"","orcid":"","institution":"University of Baghdad","correspondingAuthor":false,"prefix":"","firstName":"Sala","middleName":"Sami","lastName":"Hamza","suffix":""},{"id":479201104,"identity":"53a9d5e3-75e6-4b7d-89cd-b0e42b080f49","order_by":1,"name":"Ruwiadah Tarek Mahdi","email":"","orcid":"","institution":"University of Baghdad","correspondingAuthor":false,"prefix":"","firstName":"Ruwiadah","middleName":"Tarek","lastName":"Mahdi","suffix":""},{"id":479201106,"identity":"2318778f-91c0-409a-82cc-8f569969a0b1","order_by":2,"name":"Ban H. 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\"\u003e\u003c/p\u003e\n"},{"header":"Introduction","content":"\u003cp\u003eThe modern age faces cancer as one of its most severe health challenges. This disease manifests as cells multiply uncontrollably which causes them to form tumors and spread throughout the body. The World Health Organization reports that cancer stands as one of the primary global causes of death while emphasizing the growing number of cases attributed to environmental and genetic influences combined with contemporary lifestyle habits [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The medical community continues searching for cancer treatments that work better while causing less harm to healthy tissues despite significant progress being made in this field.\u003c/p\u003e \u003cp\u003eDoctors commonly use radiotherapy against cancer because radiation helps destroy cancer cells or inhibit their development. Traditional radiotherapy with X-rays and gamma rays proves effective against tumors but frequently harms surrounding healthy tissues [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Beta particle therapy stands out as an innovative cancer treatment because it allows for precise targeting of malignant cells while preserving surrounding healthy tissues.\u003c/p\u003e \u003cp\u003eThe radioactive decay of isotopes Strontium-90 and Yttrium-90 produces beta-minus radiation which provides a treatment option for different cancer types such as bone and liver cancer. Research demonstrates that radioactive particles achieve penetration into cancerous tissues where they inflict DNA damage that results in either stopping cancer cell growth or eliminating them entirely [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A research project [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] executed study demonstrated that Strontium-90 effectively decreased bone tumor size and relieved pain in advanced bone cancer patients. A study demonstrated that liver tumor sizes decreased by 60% with Yttrium-90 SIRT application and showed significant survival rate enhancements [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNew studies demonstrate that beta radiation shows increased effectiveness alongside immunotherapy because it enhances the immune system's ability to target cancer cells [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The emerging research indicates beta radiation will play a central role in developing sophisticated therapies which deliver superior results with reduced adverse effects.\u003c/p\u003e \u003cp\u003eAs medical science progresses, now have cancer treatment options that go beyond just chemotherapy and radiotherapy. The focus of modern medical advancements has shifted towards accurate technological developments with nanotechnology emerging as the primary driver.\u003c/p\u003e \u003cp\u003eGold nanoparticles represent a primary application in medical technology because they utilize their unique physical and chemical properties to serve as intelligent instruments for diagnostic and therapeutic uses. Gold nanoparticles enhance radiation treatment by precisely focusing on cancer cells while protecting adjacent healthy tissues from radiation exposure [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Medical treatment has undergone a significant transformation by combining nanotechnology with radiation therapy to enhance patients' quality of life and reduce their suffering.\u003c/p\u003e \u003cp\u003eThe significance of this research lies in its development of treatment methods designed to destroy cancer cells without producing harmful side effects. Studies on gold nanoparticles combined with radiotherapy introduce essential solutions to medical issues through innovative therapeutic methods.\u003c/p\u003e \u003cp\u003eThis study investigates how beta-minus radiation impacts cancer cells by examining its therapeutic mechanism and outcomes and reducing damage. techniques and safer effective therapies for patients within the rapidly progressing area of radiation medicine.\u003c/p\u003e"},{"header":"Material and method","content":"\u003cp\u003eIn this study, the work method was carried out in several steps there are\u003c/p\u003e \u003cp\u003e1. Gold nanoparticle (AuNP) synthesis A plasma jet device was used to synthesize Au NPs.Aqueous tetrachloride salts (HAuCl4.4H2O), produced by Glentham in the United Kingdom, were utilized; they weighed 411.8476 g in part and were 99% pure.Eq.\u0026nbsp;(1) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] was used to get the necessary concentration (mol/L) from a volume of 100 mL of 0.6 mM.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Concentration\\left(mole\\right)=\\frac{mass\\left(g\\right)}{Molecular\\:weight\\left(\\frac{g}{mol}\\right)\\times\\:volume\\left(liter\\right)}\\:\\:\\:\\:\\:\\dots\\:.1$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eUsing the gas argon (Ar). included a gas flowmeter with a 3 L/min calibrator, were connected to the power supply's cathode, and could withstand DC voltages of up to 25 kV. \u003c/p\u003e\u003cp\u003eThe glass beaker containing the aqueous tetrachloride is poured into a tiny beaker (about 25 mm in size), which is then set on a moving holder beneath the metal tube.The anode, which is made of stainless steel, is 7 cm long, 5 mm wide, and has a 1x1 cm strip end, as seen in the figure.1\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e2- Loading negative beta particles on AuNPs\u003c/p\u003e \u003cp\u003eGold nanoparticles were irradiated using the strontium radioactive source Sr-90, is a strong and pure radiation source for negative beta particles, and the doses for each sample were as follows: 1.2 KGy, 14.4 KGy and 15.6 KGy the equivalent dose to the radioactive source was calculated as 50 Gy/hr. the irradiation time for each sample was calculated, and its value was as follows: 0.024 (hr.), 0.288 (hr.) and 0.312 (hr).\u003c/p\u003e \u003cp\u003e3- MDA and REF, two cell lines, were used to culture both normal and breast cancer cells. For my organizations, the Al-Nahrain University Biotechnology Centre donated cells. Trypsin EDTA was used in this instance to extract the cells, followed by the addition of PRMI 10% culture media and the distribution of 10,000 cells per well using a microplate 96 well. Following a 24-hour incubation period at 37 degrees\u003c/p\u003e \u003cp\u003eCelsius, the cells were examined to see whether a monolayer had developed [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere were groups created on the 96-well Lear microplate.groups were given diluted concentrations in the following order: 100%, 50%, 25%, of AuNPs loaded negative beta particle and three set exposed chemotherapy(Adriamycin)15\u0026micro;l,25\u0026micro;land 35\u0026micro;l and exposed 9set combination between three diluted of AuNPs and dose of Adrimycin, The cells were exposed 24and 48 hours after being dyed with 50 \u0026micro;g of Crystal Violet for twenty minutes to an inspection at 37\u0026deg; C for dye and put in an incubator. Finally calculated of growth inhibition using Eq.\u0026nbsp;2[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Growth\\:inhibition\\:\\left(GI\\right)\\%=\\frac{control-treated}{control\\:}\\times\\:100\\%\\:\\:\\:\\:\\:\\:\\dots\\:\\dots\\:2$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Result and discussion","content":"\u003cp\u003eThe UV-Vis spectral analysis of gold nanoparticles (AuNPs) synthesize using plasma jet exhibited a well-defined surface plasmon resonance (SPR) peak centered at 545 nm, which is consistent with the typical optical signature of colloidal AuNPs in the size range of 30\u0026ndash;50 nm as shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. This SPR peak, which is extremely sensitive to variations in particle size, shape, dielectric environment, and interparticle spacing, results from the collective oscillation of conduction band electrons in response to incoming light.Following irradiated of negative bata particles, a noticeable blue-shift in the SPR peak to 530 nm was observed, accompanied by a decrease in absorbance intensity. This spectral shift can be attributed to several interrelated effects. Particle Size Reduction or Reshaping,Beta irradiation may induce fragmentation or reshaping of the nanoparticles, leading to smaller or more spherical particles. Since smaller AuNPs exhibit SPR peaks at shorter wavelengths, this morphological modification can account for the observed shift [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].The findings demonstrate the presence of spherically shaped Au nanoparticles and are consistent with those found in previous studies that used Mie theory to model the light scattering spectra of Au nanoparticles [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eFigure.The Xray diffraction (XRD) patterns of dried gold particles Au NPs were prepared using a plasma jet system, and their positions are consistent with the values in the standard card (JCPDS file No. 040784), as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The peak intensity (111) at 38.8\u0026deg; is indexed for the facecentered cubic (FCC) structure of Au NPs, and 2\u0026theta;\u0026thinsp;=\u0026thinsp;38\u0026deg; (1 1 1), 45\u0026deg; (2 0 0), 64\u0026deg; (2 2 0), and 78\u0026deg; (3 1 1) [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThe structural effects of beta particle irradiation on noble metal nanoparticles such as gold (AuNPs) were evaluated using X-ray diffraction (XRD) analysis. Post-irradiation, the XRD patterns revealed clear peak broadening, indicative of reduced crystallite size due to lattice fragmentation or disorder. Moreover, a notable decrease in peak intensity was observed, suggesting the introduction of crystalline defects such as vacancies and dislocations. In some cases, slight shifts in peak position (2\u0026theta;) were detected, which can be attributed to internal microstrain and lattice distortion caused by the high-energy impact of \u0026beta;-particles [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. These shifts reflect subtle changes in interplanar spacing and crystal symmetry.\u003c/p\u003e\n\u003cp\u003eSuch irradiation-induced modifications\u0026mdash;including decreased crystallinity, enhanced microstrain, and possible amorphization\u0026mdash;have critical implications for the physicochemical properties of nanoparticles, potentially altering their optical, catalytic, and biological behaviors [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, understanding these structural changes is essential when designing nanoparticle-based systems for applications in radiation environments, such as medical diagnostics, biosensing, or radiation shielding.\u003c/p\u003e\n\u003cp\u003eWhen MDA cell line is exposed to Au NPs combination with Adrimycin chemotherapy in different concentration (10\u0026micro;g,25 \u0026micro;g and35 \u0026micro;g) there is a synergism effect after 24, 48 hrs of incubation, present synergism effect and the growth inhibition increase with increasing dose of radiation of bata particles combination with Adrimycin chemotherapy and also no synergismeffect after 24, 48 hrs of incubation in REF cell line. Shown Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e,\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e,\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e,\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWe notce the highest rate of inhibition of cancer cells 55.3% at 24 hours and 74.3% at 48 hours, as shown in Figs. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, respectively.\u003c/p\u003e\n\u003cp\u003eWhile the highest rate of inhibition of normal cells 23% at 24 hours and 27.6% at 48 hours, as shown in Figs. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, respectively.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results obtained in this study highlight the significant possible of using radiation-loaded nanomaterials in the treatment of cancerous tumors. These radiation-carrying nanomaterials have demonstrated a high capacity to selectively target cancer cells while minimizing damage to healthy tissues, representing a substantial advancement toward improving therapeutic safety. Furthermore, it was observed that combining this approach with chemotherapy leads to a synergistic effect that enhances therapeutic efficacy and more effectively inhibits tumor cell growth. The functional interaction between the physical and chemical properties of nanomaterials and the biological environment of the targeted tissues opens promising research avenues for the development of multifunctional therapeutic platforms. Therefore, employing nanomaterials as smart carriers for radiation represents an innovative and promising direction in the development of targeted and safer treatments, aligning with contemporary trends in precision medicine and personalized therapy.\u003c/p\u003e \u003cp\u003ethe combining these radionuclide-loaded nanocarriers with chemotherapy results in a synergistic effect, improving tumor inhibition efficiency. The tunability of the physicochemical properties of nanomaterials, coupled with their interaction with the unique tumor microenvironment, provides a foundation for the development of multifunctional theranostic platforms. This research aims to explore the therapeutic potential of beta-minus-emitting nanomaterial-based carriers within a combined therapy framework, highlighting their role in advancing precision medicine and personalized cancer treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The authors declare that no funding was received from any organization or agency in support of this research\u003cspan dir=\"RTL\"\u003e.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e:\u003cbr\u003e\u0026nbsp;Not applicable. This study did not involve human participants or animals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e:\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSala Sami Hamza\u003c/strong\u003e: Conceptualization, Methodology, Investigation, Data Curation, Formal Analysis, Writing \u0026ndash; Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRuwiadah Tarek Mahdi\u003c/strong\u003e : Methodology, Investigation, Data Curation\u003cbr\u003e \u003cstrong\u003eBan H. Adil\u003c/strong\u003e: Supervision, Project Administration, Methodology, Validation, Data Analysis, Visualization, Writing \u0026ndash; Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBan Sabah Hameed\u003c/strong\u003e : Formal Analysis, Writing \u0026ndash; Original Draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.S. Obaid\u003c/strong\u003e: Resources, Writing \u0026ndash; Review \u0026amp; Editing, Funding Acquisition.\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFerlay, Jacques, Colombet, M., Soerjomataram, I., Mathers, C., Parkin, D. M., Pi\u0026ntilde;eros, M., Znaor, A., \u0026amp; Bray, F. (2020). Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2018. \u003cem\u003eInternational Journal of Cancer\u003c/em\u003e, 147(6), 2020\u0026ndash;2029.\u003c/li\u003e\n\u003cli\u003eSung, Hyuna, Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., \u0026amp; Bray, F. (2021). Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. \u003cem\u003eCA: A Cancer Journal for Clinicians\u003c/em\u003e, 71(3), 209\u0026ndash;249.\u003c/li\u003e\n\u003cli\u003eBentzen, S\u0026oslash;ren M. (2006). Preventing or reducing late side effects of radiation therapy: radiobiology meets molecular pathology. \u003cem\u003eNature Reviews Cancer\u003c/em\u003e, 6(9), 702\u0026ndash;713.\u003c/li\u003e\n\u003cli\u003eJoiner, Michael, \u0026amp; van der Kogel, Albert. (2018). \u003cem\u003eBasic Clinical Radiobiology\u003c/em\u003e (5th ed.). 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Y-90 radioembolization for hepatocellular carcinoma: impact on tumor response and patient survival. \u003cem\u003eHepatology\u003c/em\u003e, 73(3), 1123\u0026ndash;1137.\u003c/li\u003e\n\u003cli\u003eLee, Hyeon, \u0026amp; Chang, Kyung. (2022). Beta radiation therapy combined with immunotherapy: A new approach in cancer treatment. \u003cem\u003eCancer Therapy Journal\u003c/em\u003e, 30(2), 105\u0026ndash;122.\u003c/li\u003e\n\u003cli\u003eDemaria, Sandra, Golden, E. B., Formenti, S. C., \u0026amp; Barcellos-Hoff, M. H. (2015). Radiation dose and fraction in immunotherapy: one-size regimen does not fit all settings, so how does one choose? \u003cem\u003eJournal for ImmunoTherapy of Cancer\u003c/em\u003e, 3(1), 1\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eHainfeld, James F., Slatkin, D. N., \u0026amp; Smilowitz, H. M. (2004). Radiation dose enhancement with gold nanoparticles. \u003cem\u003eJournal of Radiation Oncology\u003c/em\u003e, 43(1), 129\u0026ndash;137.\u003c/li\u003e\n\u003cli\u003eButterworth, Kevin T., Coulter, J. A., Jain, S., Forker, J., McMahon, S. J., Schettino, G., Prise, K. M., \u0026amp; Currell, F. J. (2010). The effect of gold nanoparticle size on the enhancement of radiotherapy in human cancer cells. \u003cem\u003eNanotechnology\u003c/em\u003e, 21(13), 135101.\u003c/li\u003e\n\u003cli\u003eHer, Suzy, Jaffray, D. A., \u0026amp; Allen, C. (2017). Nanoparticle-based drug delivery systems in cancer treatment: Focus on gold nanoparticles. \u003cem\u003eNature Nanotechnology Reviews\u003c/em\u003e, 12(7), 435\u0026ndash;444.\u003c/li\u003e\n\u003cli\u003eArvizo, R. Rudraraju, Miranda, O. R., Moyano, D. F., Walden, C. A., Giri, K., Bhattacharya, R., \u0026amp; Mukherjee, P. (2012). 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In \u003cem\u003eMaterials Science Forum\u003c/em\u003e (Vol. 1050, pp. 51-63). Trans Tech Publications Ltd.\u003c/li\u003e\n\u003cli\u003eObaid, A. S., Naeemah, M. R., Harb, N. H., Adil, B. H., \u0026amp; Hasan, F. F. (2023, November). The effect between combination of cold plasma and gold nano material on blood components. In \u003cem\u003eAIP Conference Proceedings\u003c/em\u003e (Vol. 3018, No. 1). AIP Publishing.\u003c/li\u003e\n\u003cli\u003eAli Thamer, N., Adil, B.H., Obaid, A.S.Gold Nanoparticles Synthesis Using Environmentally Friendly Approach for Inhibition Human Breast Cancer (2020) International Journal of Nanoscience, 19 (5), art. no. 1950040. doi: 10.1142/S0219581X19500406\u003c/li\u003e\n\u003cli\u003ePatel, P. R., \u0026amp; Chauhan, D. S. (2020). Structural and optical evaluation of \u0026beta;-irradiated silver nanoparticles. Radiation Physics and Chemistry, 173, 108864. https://doi.org/10.1016/j.radphyschem.2020.108864\u003c/li\u003e\n\u003cli\u003eSingh, J., Dutta, T., Kim, K. H., Rawat, M., Samddar, P., \u0026amp; Kumar, P. (2021). Green synthesis of metals and their oxide nanoparticles: Applications for environmental remediation. Journal of Nanobiotechnology, 19(1), 1\u0026ndash;24. https://doi.org/10.1186/s12951-021-00838-4 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bionanoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnsc","sideBox":"Learn more about [BioNanoScience](http://link.springer.com/journal/12668)","snPcode":"12668","submissionUrl":"https://submission.nature.com/new-submission/12668/3","title":"BioNanoScience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"AuNPs, β-particles, plasma jet, MDA cells line, REF cells line, Adriamycin","lastPublishedDoi":"10.21203/rs.3.rs-6797293/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6797293/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmid the ongoing challenges faced by traditional cancer therapies, the use of nanomaterials as smart carriers for beta-minus-emitting radionuclides has emerged as a promising approach for targeted cancer treatment, In this study, gold nanoparticles (Au NPs) were \u0026nbsp;fabricated by a plasma jet system using gold salts at a concentration of 0.6 mM and loading them with negative beta particles at doses of 1.2 KGy و14.4 \u0026nbsp;KGy and 15.6 KGy The following tests were performed: FE-SEM, XRD, and UV.The UV peaks were located between 680 and 720 nm, \u0026nbsp;and the XRD values for Au were 38.76 (111), 44.4 (200), and 77.5 (311), along with the \u0026nbsp;impact on the MDA cell line for breast cancer.After 48 hours, the maximal growth inhibition of AuNPs irradiated 15.6 KGy was 60%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter 48 hours of exposure to 14.4 KGy of AuNPs, the normal cell line (REF) showed the highest toxicity of 15.3%.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Inhibition of breast cancer MDA cells line with gold nanoparticles irradiated with beta particles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-03 12:13:41","doi":"10.21203/rs.3.rs-6797293/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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