General Background: Breast cancer is the most prevalent cancer affecting women, with increasing incidence worldwide. Specific Background: Recent research has focused on the role of epigenetic changes in DNA damage, repair mechanisms, and the potential therapeutic effects of probiotics. Probiotics have shown promise in promoting tissue regeneration and DNA repair. Knowledge Gap: However, the precise impact of probiotics on DNA repair in cancer cells, specifically breast cancer cells, remains underexplored. Aims: This study aimed to evaluate the effects of probiotics on DNA damage repair in AMJ13 Iraqi breast cancer cells and assess the cytotoxic effects of probiotics on these cells. Results: Using the comet assay, we found significant increases in DNA damage repair in AMJ13 cells treated with Lactobacillus plantarum (T1) and a combination of eight probiotic strains (T2). Exposure to T1 for 48 hours resulted in significant increases in tail DNA (P≤0.001), head DNA (P≤0.001), and tail moment (P<0.001), while T2 showed similar significant increases at 72 hours (P<0.05). Image analysis further supported the DNA repair potential of probiotics, as indicated by a small tail curve for treated cells. Novelty: This study provides novel insights into the therapeutic potential of probiotics in breast cancer treatment by demonstrating their capacity to enhance DNA repair mechanisms in cancer cells. Implications: The findings suggest that probiotic therapy may be a promising adjunct treatment in breast cancer, offering a new avenue for cancer management through the enhancement of DNA repair and reduction of DNA damage. Highlights: Probiotics significantly repaired DNA damage in breast cancer cells. T1 and T2 enhanced DNA repair within 48-72 hours. Probiotics offer potential as breast cancer adjunct therapy. Keywords: Breast cancer, probiotics, DNA repair, AMJ13 cells, cytotoxicity
Photodynamic Action (PDA) by using appropriate wavelength of irradiation conjugated with porphyrin derivatives is a powerful mechanism of tumor destruction. Hematoporphyrin derivative has been shown to selectively localize in neoplastic cells and then cause destruction of them by generation of singlet oxygen when activated by low power He-Ne laser. Light which used in this study has been emitting from this laser has a wavelength equal to 632.8 nm (red light). Doses of laser had been varied from 3.6 J/cm2 to 14.4 J/cm2 . The beam of laser adjusted with a modified tissue culture plate. Cell lines had exposed to Hematoporphyrin D (HpD) for 24 hours before Laser exposure, their concentrations were varied from 5 µg/ml to 80 µg/ml. Resu
... Show MoreEffective management of advanced cancer requires systemic treatment including small molecules that target unique features of aggressive tumor cells. At the same time, tumors are heterogeneous and current evidence suggests that a subpopulation of tumor cells, called tumor initiating or cancer stem cells, are responsible for metastatic dissemination, tumor relapse and possibly drug resistance. Classical apoptotic drugs are less effective against this critical subpopulation. In the course of generating a library of open-chain epothilones, we discovered a new class of small molecule anticancer agents that has no effect on tubulin but instead kills selected cancer cell lines by harnessing reactive oxygen
The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ
The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
... Show MoreIn this research, carbon nanotubes (CNTs) is prepared through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the
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