Boron is absorbed by the digestive and respiratory system, and it was considered that it is converted to boric acid (BA), which was distributed to all tissues above 90 %. The biochemical essentiality of boron element is caused by boric acid because it affects the activity of several enzymes involved in the metabolism. DNA damage repair mechanisms and oxidative stress regulation is quite important in the transition stage from normal to cancerous cells; thus, this study was conducted to investigate the protective effect of boric acid on DNA damage and wound healing in human epithelial cell line. For this purpose, the amount of DNA damage occurred with irinotecan (CPT-11), etoposide (ETP), doxorubicin (Doxo), and HO was determined by immunofluorescence through phosphorylation of H2AX and pATM in the absence and presence of BA. Moreover, the effect of BA on wound healing has been investigated in epithelial cells treated with these agents. Our results demonstrated that H2AX foci numbers were significantly decreased in the presence of BA while wound healing was accelerated by BA compared to that in the control and only drug-treated cells. Eventually, the results indicate that BA reduced the formation of DNA double strand breaks caused by agents as well as improving the wound healing process. Therefore, we suggest that boric acid has important therapeutical effectiveness and may be used in the treatment of inflammatory diseases where oxidative stress and wound healing process plays an important role.

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Evidences about the preventive and therapeutic effects of boron compounds on cancer have been increasing in the last years. Although calcium fructoborate (CaFB) is used as a nutritional supplement, data about its preventive and therapeutic effects on neoplastic transformations are limited. In the present study, the various concentrations of CaFB were applied to the MDA-MB-231 metastatic breast cancer cell line. First, we examined the cytotoxic effect and IC value of CaFB by MTT assay. For the evaluation of the DNA damage, apoptosis and metastatic potential, expression levels of ATM, pATM, PARP, p53, p-p53, caspase-3, caspase-9, and VEGF were investigated by using immunoblotting and immunohistochemical methods. Cell viability was significantly reduced at 50 μM CaFB treatment. pATM, p-p53, and caspase-9 levels increased significantly in all groups; furthermore, there was approximately 12.5-, 2.4-, and 10.7-fold increase, respectively, for 100 μM CaFB treatment. ATM and p53 levels did not change with CaFB treatment, but PARP levels significantly 2.5-fold decreased. While VEGF immunoreactivity decreased in all groups, significant increase in caspase-3 immunoreactivity was observed only in the group treated with 50 μM CaFB (p < 0,001). Our results imply that CaFB may have therapeutic potential as well as preventive benefits in cancer.

Objectives: Computed tomography (CT) plays a complementary role in the diagnosis of the pneumonia-burden of COVID-19 disease. However, the low contrast of areas of inflammation on CT images, areas of infection are difficult to identify. The purpose of this study is to develop a post-image-processing method for quantitative analysis of COVID-19 pneumonia-related changes in CT attenuation values using a pixel-based analysis rather than more commonly used clustered focal pneumonia volumes. The COVID-19 pneumonia burden is determined by experienced radiologists in the clinic. Previous AI software was developed for the measurement of COVID-19 lesions based on the extraction of local pneumonia features. In this respect, changes in the pixel levels beyond the clusters may be overlooked by deep learning algorithms. The proposed technique focuses on the quantitative measurement of COVID-19 related pneumonia over the entire lung in pixel-by-pixel fashion rather than only clustered focal pneumonia volumes. Material and Methods: Fifty COVID-19 and 50 age-matched negative control patients were analyzed using the proposed technique and commercially available artificial intelligence (AI) software. The %pneumonia was calculated using the relative volume of parenchymal pixels within an empirically defined CT density range, excluding pulmonary airways, vessels, and fissures. One-way ANOVA analysis was used to investigate the statistical difference between lobar and whole lung %pneumonia in the negative control and COVID-19 cohorts. Results: The threshold of high-and-low CT attenuation values related to pneumonia caused by COVID-19 were found to be between ₋642.4 HU and 143 HU. The %pneumonia of the whole lung, left upper, and lower lobes were 8.1 ± 4.4%, 6.1 ± 4.5, and 11.3 ± 7.3% for the COVID-19 cohort, respectively, and statistically different (P < 0.01). Additionally, the pixel-based methods correlate well with existing AI methods and are approximately four times more sensitive to pneumonia particularly at the upper lobes compared with commercial software in COVID-19 patients (P < 0.01). Conclusion: Pixel-by-pixel analysis can accurately assess pneumonia in COVID-19 patients with CT. Pixel-based techniques produce more sensitive results than AI techniques. Using the proposed novel technique, %pneumonia could be quantitatively calculated not only in the clusters but also in the whole lung with an improved sensitivity by a factor of four compared to AI-based analysis. More significantly, pixel-by-pixel analysis was more sensitive to the upper lobe pneumonia, while AI-based analysis overlooked the upper lung pneumonia region. In the future, this technique can be used to investigate the efficiency of vaccines and drugs and post COVID-19 effects.

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