Open Access
Add to BibSonomy
Abstract
Abnormalities within cells result in intracellular structural alterations ranging from nano to submicron scales. Accidental or deliberate exposure to total body irradiation has adverse effects on the nuclear DNAs of cells. Here, we study the molecular specific DNA spatial mass density fluctuations of chromatin of mice gut cell nuclei caused by the exposure to standard doses of 4-Gy total body irradiation, using the light localization technique called inverse participation ratio via confocal imaging. Results show radiation suppresses DNA spatial mass density fluctuations. And hence, the reduction and saturation in DNA mass density fluctuations are observed on different durations of post-irradiation.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
It is now reported that abnormalities in a cell are associated with the structural alterations of its basic building blocks, such as DNA, RNA, proteins, etc. The nanoscale structural changes in a cell may range from the molecular specific spatial mass density changes to total mass density changes in a cell. However, these structural alternations which are initially at the nanoscale level in cells provide a plethora of information that can help us to predict the physiological state of cells. It is shown that the structural changes in cells/tissue can be quantified at the nano to submicron scale level using light localization techniques via confocal imaging [1,2]. Most often the prominent structural changes happen in the cells especially in the DNA/chromatin, which is highly susceptible to damage in the abnormalities. These structural abnormalities in cells could be due to diseases, or radiation exposure from sources such as ultraviolet light, mutagenic chemicals, heavy reactive processes, and ionizing radiation (IR) [3,4]. In this paper, we will study the molecular specific structural abnormalities in mice gut cell nuclei due to the exposure to a standard dose of total body irradiation (TBI), 4-Gy gamma-ray.
Humans are vulnerable to both deliberate and accidental radiation exposure. Radiation therapy or varieties of the synchrotron and laser radiations are commonly used methods of treatment for different types of diseases including treatment for controlling different types of progressive cancers. In radiation therapy treatment, we target specific organs or parts of the body and destroy the diseased cells/tissues or tumors to prevent further growth or expansion [5,6]. On the other hand, accidental exposition to TBI may happen due to environmental hazards such as radiation disasters. Besides the tremendous advancement in technologies and treatment modalities in radiation therapy, the adverse effects of radiation on healthy adjacent cells/tissues are still inevitable. Therefore, in radiation treatment or therapy, normal cells/tissues are unintentionally exposed to radiation and the structural alterations may have resulted in the cell nuclei. These alterations may vary with the progression of time, and the intensity of radiation dose. At this point, it was observed that in each proceeding hour of ionizing post-irradiation, different effects such as disruption of the intestinal epithelial tight junction and barrier dysfunction are observed within the gastrointestinal system [7]. Only cells/tissues of the organs that are exposed to radiation can explain the role in determining the radiation-tolerance levels of the irradiated tissues. The nanoscale changes in the irradiated normal cells could have long-term effects on the patients, due to the radiation related damages. It is reported that patients may experience radiation damage symptoms soon after the radiation therapy or it may take several years to be revealed [8]. However, the pathological processes of radiation damage in cells that begin soon after the normal tissues are exposed need to be explored.
Damage due to irradiation is divided into two categories based on the duration of time for the symptoms to become noticeable. The categories are acute (or severe) and consequential. Acute effects are noticeable within a few weeks after the radiation therapy treatment; sometimes even at the time of therapy. However, this damage is initially at the nanoscale level and is hardly distinguishable by conventional imaging techniques. On the other hand, the consequential effects become prominent very late, and come with severe health issues. Interestingly, both of these categories of radiation effects are initially at the nanoscale level in cells/tissue structures and have not been studied or understood well before. In reality, these processes are very complex, and the radiation can trigger a range of phenomena that may go unnoticed. In some cases, late or consequential effects have been reported up to 34 years after the radiation exposure [9].
Whole organ damage is one of many side-effects of post-irradiation of gamma-ray TBI. When an organ is exposed to radiation, its cells/tissues may react in different ways based on the type of radiation dose and their level of radiation tolerance. Radiation results in ionization and the production of free radicals within the irradiated organs. This causes severe damage to different cellular components resulting in the rearrangement of the cytoskeleton, occluding, zona occludes-1, claudin-3, E-cadherin, and β-catenin, etc. When cells are in their first cell division or the process of their first cell division after being exposed to radiation, their DNA molecules are likely to get damaged partially to severely, resulting in abnormalities in cell functioning [10,11]. Chromosomal damage that is either unrepaired or improperly repaired causes mitosis or mitotic death [12]. Double-strand break (DSB) damage due to irradiation causes the DNA double helix to break in such a way that it is nearly impossible to keep broken ends together. Besides, as there is less chance of repairing itself, this damage can even cause unsuitable recombination of the DNA genome. Such inappropriate repair of a DSB may lead to massive instability in the genome that runs through generations of chromosomal fragments [13]. A single DSB event on irradiation cells can sometimes cause apoptosis or the cell self-death [14]. Consequently, the DNA damage of irradiated cells carries long-term effects such as genetic abnormalities [15].
The gastrointestinal system is the major target of TBI. During the post gamma-ray TBI period, the tight junction and barrier dysfunction in the gut tissue gets destroyed and produces endotoxin flux in the mucosa that triggers diarrhea, malabsorption, and electrolyte imbalance in the body [16]. The radiation effect in gut tissue includes induction of oxidative stress and apoptosis in the intestinal tissues [17]. Also, the effects on post gamma-ray TBI result in the activation of cellular signaling pathways, which ultimately leads to the expression and activation of proinflammatory and profibrotic cytokines, vascular injury, and coagulation cascade [18,19]. Radiation exposure can have a more damaging effect on patients with pre-existing conditions/diseases. The irradiated cells that hinder the restoration of DNA, patients with ataxia-telangiectasia (genetic abnormality) will experience serious radiation reactions [20]. Other genetic factors can also play a role in the radiosensitivity of cells as suggested by studies on various strains of mice [21]. However, it is not completely reliable to depend on the experiments of radiosensitivity on cells that were isolated from the patient except when there is a case of extremity. No significant late damages have been found in patients who showed early responses to radiation effects [22].
Treatment of irradiated cells/tissues is difficult or sometimes impossible since radiation targets the chromatin of the cell. Recently, several publications have been reported on the technological development to increase the efficacy of conventional radiotherapy methodologies, where the reduction of the effect of radiation near to the targeted cells/tissues, or proximal damage in radiation have been addressed. The 3-dimensional conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT) are examples of scientific technology that can distribute necessary doses to cancer tissues or tumors and avoid unnecessary exposure of radiation to normal tissues by proximal damage [23]. Also, different forms of chemical treatment are in practice before the irradiation to protect normal tissues from acute as well as chronic damages [24].
In a recent paper [7], the effects of total body irradiation (TBI) on gut tissue were studied systematically. The gastrointestinal tract, a radiation sensitive organ whose radiation complications are collectively known as gastrointestinal acute radiation syndrome (GI-ARS) [25]. At the same point, the Center for Disease Control statistics reveals the threshold for GI-ARS is 5-10 Gy. In this paper, allowable radiation dose 4-Gy was applied for TBI. Also, endotoxemia and bacteremia are important pathogenesis of ARS and colonic tissues get injured in the pathogenesis of GI-ARS. Confocal microscopy results presented in [7], showed that radiation causes rapid disruption of tight junctions (TJ), adherens junctions (AJ), and the actin cytoskeleton by an oxidative stress-dependent mechanism as early as 2 hours post-irradiation, and the effect was sustained for at least 24 hours of post-irradiation. Although there is an indication of TJ, AJ, and actin cytoskeleton disruption by radiation in gut tissues due to post-irradiation, DNA molecular specific structural alterations in nuclei of cells in these tissues were poorly explored. DNA molecules are one that gets affected severely by TBI. Therefore, quantifying the spatial structural disruption of irradiated cells’ DNA will provide quantitative access to the radiation damage. Recent reports show that DNA damage in low-dose TBI [26–28], however, the DNA molecular specific spatial structural changes have not been addressed.
In this paper, using a novel approach, called the inverse participation ratio via confocal imaging (Confocal-IPR) technique, we report a quantitative analysis of the DNA molecular specific spatial mass density fluctuations in cell nuclei in gut tissues due to the exposure to post 4-Gy gamma-ray TBI using a mouse model. The DNA molecular specific mass density fluctuations can be probed by using a mesoscopic physics-based spectroscopic technique, the inverse participation ratio (IPR), on DAPI stained (i.e. chromatin) confocal imaging. The light localization properties of nuclear DNA that represent the mass density fluctuation exposed to different hours of post 4-Gy gamma-ray TBI are quantified as the measures of standard deviation (std) of < IPR(L)> or (σ<IPR(L)>), represented by the degree of disorder strength (Ld) and compared with the control. This mesoscopic physics-based spectroscopic analysis consequently represents the structural change in terms of the degree of disorder strength at the nano to submicron scales. This powerful diagnostic tool, the confocal-IPR technique has shown promising success to probe the molecular specific nanoscale structural abnormalities in cells/tissue using a confocal image to distinguish the cancer stages and drug-effect in cancer treatment as well as quantify any types of abnormalities in cells [29,30].
2. Method
2.1. Confocal microscopy imaging
For confocal microscopy imaging, ileum cryosections of thickness 12 microns were fixed in an acetone-methanol mixture (1:1 ratio) for two minutes (temperature -20°C). Rehydration was performed on the sections using phosphate-buffered saline (PBS). 0.5% Triton X-100 was used to permeabilize the sections in saline for 15 minutes. The tissue sections were permeabilized with 0.2% Triton X-100 in PBS for 10 min and blocked in 4% nonfat milk in Triton-Tris buffer (150 mM sodium chloride containing 10% Tween 20 mM and 20 mM Tris, pH 7.4). It was then incubated for 10 minutes with the DAPI (Hoechst 33342). A Zeiss 710 confocal microscope was used to examine the fluorescence and to collect the confocal images. We have recorded the x-y images (size 1 micron) using ZEN (Zeiss Efficient Navigation) software. These images were stacked using ImageJ software (National Institutes of Health, Bethesda, MD) and further processed using Adobe Photoshop Software (Adobe Systems, San Jose, CA).
2.2. Inverse participation ratio (IPR) technique for the structural disorder analysis from confocal imaging or micrographs
The mesoscopic physics-based molecular specific imaging method, inverse participation ratio (IPR) using confocal imaging or “confocal-IPR” technique, has been proven to be useful in quantifying the molecular specific structural changes in biological cells/tissues [31,32]. The IPR technique quantifies the structural changes at the nanoscales level by evaluating the localization properties of the optical lattice that are formed from the molecular specific spatial mass density distribution using confocal imaging. Based on the light localization strength of the medium, the degree of disorder strength is calculated. The average and std of the IPR are proportional to the mass density fluctuation at a point of the weakly disordered optical media such as cells. The detail of the IPR method is described in the earlier publications [33,34]; however, in the following, we describe the method in short for the completeness of this paper.
Consider dV = dxdydz is a small finite volume of the cell slice at a point (x,y) with thickness dz, and ρ is the DNA molecular mass density in the voxel dV of the sample. In the confocal image, if I(x,y) is the pixel intensity at position (x,y), then I(x,y) can be denoted as [1]. The local refractive index of the cell slice at a point (x,y) i.e. n(x,y) is directly proportional to the local mass density of the cell $n({x,y} )= \; {n_0} + dn({x,y} )$. Here, ${\textrm{n}_0}$ is the average refractive index and dn(x,y) is the refractive index fluctuations of the $I({x,y} )\propto dV(\rho )$ voxel dV at position (x,y) [32]. The refractive index fluctuations are less than the average refractive index n0(dn<< n0). We can represent the pixel intensity I(x,y) of a voxel area dxdy at position (x,y) of the confocal image which is linearly proportional to the refractive index n(x,y) of the voxel [33,34], i.e.:
In the same way, the optical parameter refractive index n(x,y) of the scattering substance is directly proportional to the mass density of the thin cell at that point [32]. Therefore, the intensities of a confocal image are linearly proportional to the mass, M, and refractive index, n of the voxel: From this, we obtained the optical potential as εi(x,y) at the pixel position (x, y) of the two-dimensional plane of the confocal image. Then the optical potential of the voxel point, εi(x,y) is generated as: The Tight Binding Model (TBM) is commonly used to calculate the disorder properties of electrical and optical systems. The spatial structural disorder strength of an optical lattice can be analyzed by the Hamiltonian approach of the Anderson Tight Binding Model (TBM), which can be written as [35,36]:2.3. Sample preparation
All the experiments on animals strictly followed the guidelines provided by the Institutional Animal Care and Use Committee (IACUC) at the University of Tennessee Health Science Center. Mice were housed in an institutional animal care facility. The animal care facility replicated the regular living atmosphere of the animals by providing 12/12 hours of light-dark cycles and access to regular laboratory food and water until the experiments were conducted. For the experiments, 12-14 weeks old C57BL/6 mice were used and collected from Harlan Laboratories, Houston, TX. Calibration and radiation field mapping of ion chamber dosimetry was performed by the manufacturer during installation while the validation and quality control measures of radiation exposure rates in the ion chamber were conducted by a certified Health Physicist using a calibrate RadCal 0.6-ml therapy grade ion chamber system as described previously [7]. In the experiment, a Mark I, model 25, 137Cs source irradiator (JL Shepherd and Associates, San Fernando, CA) was used for TBI. The 4-Gy gamma-ray TBI at a dose rate of 76 cGy/min was treated for all mice except the control. Then each group of 5 mice was euthanized at different hours (2, 6, 8, and 24) after exposed to gamma-ray TBI, as described in [7]. The mice ileum tissue sections were removed and cryofixed and stained with DAPI for the confocal imaging.
3. Results
In this experiment, mice were exposed to 4-Gy gamma-ray TBI to evaluate the effects of post ionizing radiation (postIR) on DNA molecular spatial mass density fluctuations of gut nuclei. For this, mice divide into 5 groups were fed with a regular Lieber DeCarli liquid diet. The mice were then sacrificed after post-irradiation (postIR) time points: 2, 6, 8, and 24 hours, and then the 12 µm thin gut tissues were prepared for DAPI staining as described in the Method section to target the DNA/chromatin fluorescent. In particular, using confocal microscopy, the images of DAPI stained 4-Gy ionizing gamma radiation treated gut tissue were recorded as follows: Control, 2hr-postIR, 6hr-postIR, 8hr-postIR, and 24hr-postIR. And, hence, the confocal micrographs were analyzed using the IPR technique at the sample length, L = 0.8 µm to quantify the molecular specific light localization properties of irradiated DNA molecular structure.
Fig. 1 (a)-(e), represent confocal images of DAPI stained of the mice gut tissues for control and TBI mice for different hours of post-irradiation (a) Control, (b) 2hr-postIR, (c) 6hr-postIR, (d) 8hr-postIR, and (e) 24hr-postIR; and their corresponding < IPR(L)> or Ld images are shown in (a’)-(e’), respectively. In the confocal images, brighter spots represent the DNA molecular mass density spots. The Ld images represent the mass density fluctuations expressed in terms of structural abnormalities of the chromatin in cell nuclei of gut tissues. In the Ld images, the red color represents higher DNA spatial mass density fluctuations while the blue color represents the lower spatial mass density fluctuations for every pixel of IPR images. Therefore, the Ld images show that red spots or the higher mass density fluctuations decrease with the increase in the duration of post-irradiation indicating the adverse effect of ionizing radiation in the DNA with the increase of time duration after being exposed. Further, the standard deviation of < IPR(L)> or σ(<IPR(L)>) at the sample length L = 0.8 µm for post-irradiated times are calculated.
Fig. 1. (a)-(e) represent the confocal images of gut tissue sections stained with DAPI for: (a) Control, (b) 2hr-postIR, (c) 6hr-postIR, (d) 8hr-postIR, and (e) 24hr-postIR, and their corresponding $L_d$ images at sample length L = 0.8µm are shown in (a’)-(e’), respectively. The Ld images show the structural abnormalities or mass density fluctuations decrease in the irradiated gut cell nuclei due to the ionizing effect of 4-Gy gamma-ray TBI.
Confocal DNA mass density intensities are calculated and shown in the bar graph in Fig. 2. The molecular specific DNA mass density fluctuations of the gut cell nuclei were then calculated using the IPR technique and represented in the bar graphs as shown in Fig. 3. Each of 5 groups has 5 mice, on average 8-10 tissue sections for each mouse were analyzed from the corresponding confocal and IPR images. Hence the σ(Intensity) and σ(<IPR(L)>) values were quantified. Then the σ(Intensity) and σ(<IPR(L)>) values were compared to observe the effect of post-irradiation on irradiated DNA/chromatin structure at the nano to submicron levels. Since the standard deviation is a more reliable statistical marker that depends only on the width of the distribution, irrespective of the mean position. And the Student’s t-test p-value was calculated to compare the significance of the statistical difference on an average in reference to the control for all the post-irradiated gut tissues.
Fig. 2. Bar graphs of the standard deviation of the ensemble confocal intensities of DAPI stained mice gut cell nuclei targeting DNA molecular intensities (in gray scale mean intensity): (a) Control, (b) 2hr-postIR, (c) 6hr-postIR, (d) 8hr-postIR, and (e) 24hr-postIR. In average 8-10 confocal gut micrographs from each mouse, and 5 mice per group was considered. The decrease in intensities are 31.33%, 22.74%,46.88% for 2hr-, 6hr-, 8hr- and 24hr-postIR. Student’s t-test (two-tailed) p-values relative to control: 0.018 for 2hr-postIR, 0.00035 for 6hr-postIR, 0.0004 for 8hr-postIR, 0.00003 for 24hr-postIR. For all the treated cases, p-value <0.05 relative to the control, implies changes are statistically significant.
Fig. 3. Bar graphs of the standard deviation of the ensemble averaged IPR or σ(<IPR(L)>) at sample length L = 0.8µm of DAPI stained mice gut cell nuclei for: (a) Control, (b) 2hr-postIR, (c) 6hr-postIR, (d) 8hr-postIR, and (e) 24hr-postIR. The confocal-IPR analysis illustrates that the σ(<IPR(L)>) or the degree of disorder strength (Ld) of 4-Gy TBI mice gut nuclei DNA decreases by 47% after 2 hours post-irradiation, 96% after 6 hours post-irradiation, 90% after 8 hours post-irradiation and 97% after 24 hours post-irradiation relative to the Control. On average 8-10 confocal micrographs from each mouse and 5 mice per group were considered. Student’s t-test (two-tailed) p-values relative to control: 0.036 for 2hr-postIR, 0.001 for 6hr-postIR, 0.0006 for 8hr-postIR, 0.001 for 24hr-postIR. For all the treated cases, p-value <0.05 relative to the control, implies changes are statistically significant.
In Fig. 2, the bar graphs for ensemble averaged DNA molecular intensity standard deviation σ(Intensity) is presented. The bar graphs clearly show the decrease in the standard deviation in the intensity, with an increase in the post-irradiation hours, relative to the control. The decrease in intensities are 12.44%, 31.33%, 22.74%,46.88% for 2hr-postIR, 6hr-postIR, 8hr-postIR, and 24hr-postIR, respectively, relative to the control with all p-values <0.05. These intensity variations are due to the onsite variations of the intensities, without any spatial correlation information of the intensity distribution.
In Fig. 3, the bar graph shows a significant decrease in the σ(<IPR(L)>) value or disorder strength Ld (∼dn×lc) of mice cells nuclei with the increasing time duration after 4-Gy gamma-ray TBI exposure compared to the control. In this IPR analysis technique, a combined parameter ∼dn×lc values are calculated. On average, both the dn and lc values are decreased. This statistical result shows that the molecular mass density fluctuations of DNA expressed in term of structural disorder (Ld) of TBI exposed gut tissues’ chromatin structure decreases by 47% after 2 hours post-irradiation, 96% after 6 hours post-irradiation, 90% after 8 hours post-irradiation, and 97% after 24 hours post-irradiation compare to the control. We perform the Student’s t-test (two-tailed) statistical analyses, and the results show that for all the treated cases p-value <0.05, relative to the control, implies changes are statistically significant. The results show that after TBI exposer, the DNA spatial structural disorder strength was decreased, in general. This suppression is the decrease in the DNA spatial mass density fluctuations with the increasing elapsed duration after TBI. Hence, the gradual decrease in the degree of DNA molecular specific spatial disorder strength of 4-Gy gamma-ray TBI DNA structure after different durations of irradiation i.e. postIR suggests that TBI has adverse effects on cell nuclei which are found prominent at the DNA molecular mass density in chromatin.
The results further illustrate that the effects of standard 4-Gy gamma-ray TBI effect on the chromatin of nuclei may vary with time duration and worsen with increasing elapsed hours after being exposed and eventually the density fluctuations saturate to a lower value. That means, the DNA spatial structural change in the nucleus due to irradiation is very prominent during the first hours and reaches the maximum structural disorder changes within the next 24 hours of post-irradiation. Since the tight junction (TJ), adherens junctions (AJ), and actin cytoskeleton are destroyed in irradiated gut tissue where time course correlates with functional changes such as tight junction disruption [7]. This result strongly supports the mesoscopic physics-based molecular specific light localization technique, that confocal-IPR can quantify the degree of mass density fluctuations which acts as a potential biomarker for measuring the nanoscales’ spatial structural alteration of DNA in the irradiated gut tissues by TBI. In particular, the degree of structural disorder strength (${L_d}$) or σ(<IPR(L)>) of the nuclei, chromatin/DNA is reduced significantly compared to the control. Although, the radiation destroys the different components of cells/tissue in different quantities; it is known that the mitochondria, cytoskeleton, chromatin, etc. are found more sensitive towards radiation and get affected, and the molecular structural changes in these organelles are yet to study. This variation of the disorder strength is not prominently visible in the confocal intensity onsite fluctuations, but visible in Ld statistics, although they have a similar decreasing trend with the increase in the post-irradiation time, relative to the control. As mentioned, intensity fluctuations only probe the onsite refractive index fluctuations (dn) without any spatial correlation information; in contrast Ld parameter probe a combined parameter dn×lc.
4. Conclusions
In this study, a newly developed mesoscopic physics-based confocal-IPR technique has been used to quantify the effect of post-irradiation on DNA molecular specific mass density spatial fluctuations. We have successfully applied a light localization technique to quantify the mass density fluctuations of 4-Gy gamma-ray TBI mice gut cell nuclei chromatin/DNA for different duration of post-irradiation and represent it in terms of σ(<IPR(L)>) or structural disorder (Ld). 4-Gy gamma-ray TBI is the approved lower threshold on animal medical doses. Radiation destroys the tight junctions (TJ), adherens junctions (AJ), and barrier dysfunction in the gut and produces endotoxin flux in the mucosa. This endotoxin flux in the gastrointestinal system may trigger diarrhea, malabsorption, and electrolyte imbalance which later eventually leading to endotoxemia and bacteremia as severe outcomes [16]. Further, DNA in chromatin easily gets exposed to radiation, and hence, we focus to study spatial structural abnormalities in DNA/chromatin for gut tissues via the confocal-IPR technique. Interestingly, both the results confocal intensities σ(Intensity) and the degree of DNA disorder strength (Ld) decreases gradually for 4-Gy gamma-ray TBI exposed mice gut DNA with the increase in the duration of post-irradiation and gets almost saturated to a lower value within 24 hours, however, the changes are more prominent in the IPR analysis. In the IPR study, the < IPR(L)> value of confocal images of control and 4-Gy gamma-ray irradiated mice gut tissues are calculated which is directly proportional to the DNA spatial mass density fluctuations within the tissue. Then, the statistical measure of σ(<IPR(L)>) was computed which acts as a potential biomarker for the measurement of the structural alteration of the DNA molecular mass density fluctuations in irradiated tissues. It has been reported that gamma radiation effects in cells/tissue vary with the post-irradiation duration time and have adverse effects on the DNA mass density spatial structural arrangements. However, there was a slight increase in σ(<IPR(L)>) of the gut tissues’ DNA structural disorder after 6 hours and at 8 hours of post-irradiation time, then the value decreases again and gets almost saturated. This sudden increase in the σ(<IPR(L)>) may be due to the irradiated tissues trying to retain their initial structural properties, which demand more experimental investigations. The radiation suppresses the DNA mass density fluctuations and it eventually gets saturated with the increase of the post-irradiation time. Suppression of the DNA mass density fluctuations affect various activities of the chromatin including the daily nuclear transcriptions and eventually resulting in DNA replication which may result in genetic alterations. Hence, the nano to submicron scale quantification of molecular specific structural abnormalities in the irradiation cells/tissues could explain their physical states and helps to increase the efficacy of radiation therapy or radiation related treatment modalities in the future which inevitably involve irradiation of normal cells/tissues.
Funding
National Institute of Diabetes and Digestive and Kidney Diseases, NIH (NIH DK55532).
Acknowledgment
Funding from MSU and NIH are acknowledged.
Disclosures
The authors have no conflict of interest.
References
1. P. Sahay, H. M. Almabadi, H. M. Ghimire, O. Skalli, and P. Pradhan, “Light localization properties of weakly disordered optical media using confocal microscopy: application to cancer detection,” Opt. Express 25(13), 15428–15440 (2017). [CrossRef]
2. P. Sahay, A. Ganju, H. M. Almabadi, H. M. Ghimire, M. M. Yallapu, O. Skalli, M. Jaggi, S. C. Chauhan, and P. Pradhan, “Quantification of photonic localization properties of targeted nuclear mass density variations: Application in cancer-stage detection,” J. Biophotonics 11(5), e201700257 (2018). [CrossRef]
3. E. C. Friedberg, G. C. Walker, W. Siede, and R. D. Wood, DNA Repair and Mutagenesis (American Society for Microbiology Press, 2005).
4. J. H. Hoeijmakers, “Genome maintenance mechanisms for preventing cancer,” Nature 411(6835), 366–374 (2001). [CrossRef]
5. S. Demaria, E. B. Golden, and S. C. Formenti, “Role of Local Radiation Therapy in Cancer Immunotherapy,” JAMA Oncol 1(9), 1325–1332 (2015). [CrossRef]
6. R. Baskar, K. A. Lee, R. Yeo, and K.-W. Yeoh, “Cancer and Radiation Therapy: Current Advances and Future Directions,” Int. J. Med. Sci. 9(3), 193–199 (2012). [CrossRef]
7. P. K. Shukla, R. Gangwar, B. Manda, A. S. Meena, N. Yadav, E. Szabo, A. Balogh, S. C. Lee, G. Tigyi, and R. Rao, “Rapid disruption of intestinal epithelial tight junction and barrier dysfunction by ionizing radiation in mouse colon in vivo: protection by N-acetyl-l-cysteine,” Am. J. Physiol. Gastrointest. Liver Physiol. 310(9), G705–715 (2016). [CrossRef]
8. H. B. Stone, C. N. Coleman, M. S. Anscher, and W. H. McBride, “Effects of radiation on normal tissue: consequences and mechanisms,” Lancet Oncol. 4(9), 529–536 (2003). [CrossRef]
9. W. Dörr and J. H. Hendry, “Consequential late effects in normal tissues,” Radiother. Oncol. 61(3), 223–231 (2001). [CrossRef]
10. G. Şener, N. Jahovic, O. Tosun, B. M. Atasoy, and BÇ Yeğen, “Melatonin ameliorates ionizing radiation-induced oxidative organ damage in rats,” Life Sci. 74(5), 563–572 (2003). [CrossRef]
11. L. H. Thompson and H. D. Suit, “Proliferation kinetics of X-irradiated mouse L cells studied with time-lapse photography. II,” Int. J. Radiat. Biol. Relat. Stud. Phys., Chem. Med. 15(4), 347–362 (1969). [CrossRef]
12. W. C. Dewey, S. C. Furman, and H. H. Miller, “Comparison of lethality and chromosomal damage induced by X-rays in synchronized Chinese hamster cells in vitro,” Radiat. Res. 43(3), 561–581 (1970). [CrossRef]
13. S. P. Jackson, “Sensing and repairing DNA double-strand breaks,” Carcinogenesis 23(5), 687–696 (2002). [CrossRef]
14. T. Rich, R. L. Allen, and A. H. Wyllie, “Defying death after DNA damage,” Nature 407(6805), 777–783 (2000). [CrossRef]
15. K. K. Khanna, “Jac son SP. DNA double-strand brea s: signaling, repair and the cancer connection,” Nat. Genet. 27(3), 247–254 (2001). [CrossRef]
16. A. Wang, Z. Ling, Z. Yang, P. R. Kiela, T. Wang, C. Wang, L. Cao, F. Geng, M. Shen, and X. Ran, “Gut microbial dysbiosis may predict diarrhea and fatigue in patients undergoing pelvic cancer radiotherapy: a pilot study,” PLoS One 10(5), e0126312 (2015). [CrossRef]
17. A. Kunwar, P. P. Bag, S. Chattopadhyay, V. K. Jain, and K. I. Priyadarsini, “Anti-apoptotic, anti-inflammatory, and immunomodulatory activities of 3, 3′-diselenodipropionic acid in mice exposed to whole body γ-radiation,” Arch. Toxicol. 85(11), 1395–1405 (2011). [CrossRef]
18. Y. Chen, J. Williams, I. Ding, E. Hernady, W. Liu, T. Smudzin, J. N. Finkelstein, P. Rubin, and P. Okunieff, “Radiation pneumonitis and early circulatory cytokine markers,” Seminars in Radiation Oncology 12(1), 26–33 (2002). [CrossRef]
19. F. Paris, Z. Fuks, A. Kang, P. Capodieci, G. Juan, D. Ehleiter, A. Haimovitz-Friedman, C. Cordon-Cardo, and R. Kolesnick, “Endothelial apoptosis as the primary lesion initiating intestinal radiation damage in mice,” science 293(5528), 293–297 (2001). [CrossRef]
20. R. Cox, W. K. Masson, R. R. Weichselbaum, J. Nove, and J. B. Little, “The repair of potentially lethal damage in X-irradiated cultures of normal and ataxia telangiectasia human fibroblasts,” Int. J. Radiat. Biol. Relat. Stud. Phys., Chem. Med. 39(4), 357–365 (1981). [CrossRef]
21. W. Budach, J. Classen, C. Belka, and M. Bamberg, “Clinical impact of predictive assays for acute and late radiation morbidity,” Strahlentherapie und Onkologie: Organ der Deutschen Rontgengesellschaft…[et al 174, 20–24 (1998).
22. F. C. Chu, A. S. Glicksman, and J. J. Nickson, “Late consequences of early skin reactions,” Radiology 94(3), 669–672 (1970). [CrossRef]
23. I. M. R. T. C. Working, “Group: Intensity-modulated radiotherapy: current status and issues of interest,” Int. J. Radiat. Oncol., Biol., Phys. 51(4), 880–914 (2001). [CrossRef]
24. J. E. Moulder, “Report on an Interagency Workshop on the Radiobiology of Nuclear Terrorism: Molecular and Cellular Biology of Moderate Dose (1–10 Sv) Radiation and Potential Mechanisms of Radiation Protection (Bethesda, Maryland, December 17–18, 2001),” Radiation research 158(1), 118–124 (2002). [CrossRef]
25. M. M. i Garau, A. L. Calduch, and E. C. López, “Radiobiology of the acute radiation syndrome,” Reports of Practical Oncology & Radiotherapy 16(4), 123–130 (2011). [CrossRef]
26. N. Ruprecht, M. N. Hungerbühler, I. B. Böhm, and J. T. Heverhagen, “Improved identification of DNA double strand breaks: γ-H2AX-epitope visualization by confocal microscopy and 3D reconstructed images,” Radiat. Environ. Biophys. 58(2), 295–302 (2019). [CrossRef]
27. W. Sudprasert, P. Navasumrit, and M. Ruchirawat, “Effects of low-dose gamma radiation on DNA damage, chromosomal aberration and expression of repair genes in human blood cells,” Int. J. Hyg. Environ. Health 209(6), 503–511 (2006). [CrossRef]
28. Y.-K. Kwon, I. J. Ha, H.-W. Bae, W. G. Jang, H. J. Yun, S. R. Kim, E. K. Lee, C.-M. Kang, and G.-S. Hwang, “Dose-dependent metabolic alterations in human cells exposed to gamma irradiation,” PLoS One 9(11), e113573 (2014). [CrossRef]
29. P. Adhikari, M. Hasan, V. Sridhar, D. Roy, and P. Pradhan, “Studying nanoscale structural alterations in cancer cells to evaluate ovarian cancer drug treatment, using transmission electron microscopy imaging,” Phys. Biol. 17(3), 036005 (2020). [CrossRef]
30. P. Adhikari, P. K. Shukla, M. Hasan, F. Alharthi, B. Regmi, R. Rao, and P. Pradhan, “Photonics study of probiotic treatment on brain cells exposed to chronic alcoholism using molecular specific nuclear light localization properties via confocal imaging,” arXiv preprint arXiv:1912.11777 (2019).
31. P. Adhikari, P. K. Shukla, S. Bhandari, A. S. Meena, B. Regmi, F. Alharthi, P. Sahay, R. Rao, and P. Pradhan, “Optical probing of pups brain tissue and molecular specific nuclear nano-structural alterations due to fetal alcoholism via dual spectroscopic approach,” arXiv preprint arXiv:1912.11593 (2019).
32. J. Beuthan, O. Minet, J. Helfmann, M. Herrig, and G. Müller, “The spatial variation of the refractive index in biological cells,” Phys. Med. Biol. 41(3), 369–382 (1996). [CrossRef]
33. P. Pradhan, D. Damania, H. M. Joshi, V. Turzhitsky, H. Subramanian, H. K. Roy, A. Taflove, V. P. Dravid, and V. Backman, “Quantification of nanoscale density fluctuations using electron microscopy: Light-localization properties of biological cells,” Appl. Phys. Lett. 97(24), 243704 (2010). [CrossRef]
34. P. Pradhan, D. Damania, H. M. Joshi, V. Turzhitsky, H. Subramanian, H. K. Roy, A. Taflove, V. P. Dravid, and V. Backman, “Quantification of nanoscale density fluctuations by electron microscopy: probing cellular alterations in early carcinogenesis,” Phys. Biol. 8(2), 026012 (2011). [CrossRef]
35. P. A. Lee and T. V. Ramakrishnan, “Disordered electronic systems,” Rev. Mod. Phys. 57(2), 287–337 (1985). [CrossRef]
36. E. Abrahams, P. W. Anderson, D. C. Licciardello, and T. V. Ramakrishnan, “Scaling theory of localization: Absence of quantum diffusion in two dimensions,” Phys. Rev. Lett. 42(10), 673–676 (1979). [CrossRef]
37. B. Kramer and A. MacKinnon, “Localization: theory and experiment,” Rep. Prog. Phys. 56(12), 1469–1564 (1993). [CrossRef]
38. V. N. Prigodin and B. L. Altshuler, “Long-range spatial correlations of eigenfunctions in quantum disordered systems,” Phys. Rev. Lett. 80(9), 1944–1947 (1998). [CrossRef]
