Comparison of soft tissue and lung parenchyma densities in a micro-CT scan and a human whole lung CT scan.

<p>Distribution of densities in the lung parenchyma (white) and soft tissue (gray) in (A) a mouse micro-CT scan with adaptive threshold of −190 HU and (B) a human whole lung CT scan with no need for adaptive threshold. The mouse micro-CT scan was obtained at 50 µm with 720 projections. The human whole lung CT scan was from the Weill Cornell Medical College Lung CT database. It was obtained using a GE LightSpeed Ultra scanner at 120 kVp and 80 mA, with 0.7×0.7×1.25 mm³ resolution. The peaks in (A) were not as sharp as those in (B), indicating that the mouse micro-CT scans were noisier than human CT scans. Magnified regions of the lung from (C) a micro-CT scan (yellow circle indicates tumor) and (D) a whole-lung CT scan (red arrow points to tumor) are shown to visualize the difference in scan quality. No scaling was done to the images and each image was windowed for viewing. The scale bars represent 5.0 mm (mouse micro-CT image) or 70.3 mm (human CT image). The color bar range is −750 to 849 HU (mouse micro-CT image) or −1400 to 100 HU (human CT image).</p

Tumor volume doubling time and growth index of tumors detected in RNR transgenic mice by micro-CT.

<p>NOTE: mice were first scanned at the indicated age and then subjected to a series of sequential scans to monitor tumor growth. The slope of the growth curve was converted to tumor doubling time and growth index to indicate the rate of tumor growth.</p

Comparison of lung tumor growth measured manually by an observer and by the semi-automated algorithm.

<p>Best linear fit growth curves were plotted for tumors from mouse 2 (left) and mouse 4 tumor A (right) based on measurements by a manual approximation method and by the semi-automated algorithm. The slopes of the best-fit lines for the manual and semi-automated measurements were compared by Student's t-test, and no significant differences were observed between the two slopes (P = 0.62 for mouse 2 and P = 0.57 for mouse 4 tumor A).</p

Flowchart showing the major steps of the semi-automated segmentation algorithm.

<p>Flowchart showing the major steps of the semi-automated segmentation algorithm.</p

Sequential micro-CT scans over time to measure lung tumor growth rate in four RNR transgenic mice.

<p>(A) Images of sequential micro-CT scans of an RNR transgenic mouse (mouse #3 tumor A; red circle generated manually). Images were acquired at 50 µm with 720 projections. The scale bars represent 5.0 mm. The color bar range is −700 to 400 HU. (B) Gross image of the lungs at necropsy showing the tumor (black arrow) after the last scan. (C) H&E stained section from lungs shown in (B). The scale bar represents 1000 µm. Normal and tumor tissues are also shown at a higher magnification. The scale bar represents 40 µm. (D, E) Growth curves of lung tumors from four RNR transgenic mice. Fold change in lung tumor volume was plotted against time from the first micro-CT scan. A best-fit exponential curve was used to model the growth of each tumor. Note that Mouse 1 showed very slow growth, which could be due to inconsistency in tumor volume measurement because different scan parameters were used for mouse 1 time point 3 and this was the first live mouse scanned, when the micro-CT instrument was not calibrated for each scan.</p

Micro-CT and histological analyses of an RNR transgenic mouse lung tumor.

<p>(A) Micro-CT image of lung (sagittal view) from an RNR transgenic mouse with a tumor (red circle generated manually). Image was derived from a scan taken at 50 µm with 220 projections. The scale bar represents 5.0 mm. (B) H&E stained lung tissue from the same mouse. The scale bar represents 1000 µm. Normal and tumor tissues are also shown at a higher magnification. The scale bar represents 40 µm. The tumor diameter was measured to be 1.94 mm by histological analysis. (C) Black and white panels: Several slices (every 4th slice shown) through a small region of interest including the tumor in (A). The scale bar represents 2.5 mm. Color panels: The same tumor separated by the semi-automated segmentation algorithm from other soft tissue structures such as blood vessels and the chest wall. The result is shown with the tumor in red and other soft tissue structures in green. The color bar range is −725 to 625 HU. (D) A 3D visualization of the segmented tumor in (C) showing axial, sagittal, and dorsal views. The volume equivalent diameter of the tumor was calculated by the semi-automated algorithm to be 2.03 mm.</p

Phantoms and tissues show variation in densities across different scans.

<p>(A) Distribution of densities of three phantoms, air, water, and bone (left to right peaks), with mean densities −927.6 HU, 92.2 HU, and 2612.6 HU, respectively, in one scan. (B) Distribution of densities of the same phantoms as in (A) in a repeated scan six weeks later with mean densities −931.8 HU, 66.5 HU, and 2592.0 HU, respectively. (C) Distribution of densities in the lung parenchyma (white) and soft tissue (gray) from one mouse in one scan with an adaptive threshold at −155 HU. (D) Distribution of densities of the same tissues as in (C) of the same mouse in a repeated scan six weeks later with an adaptive threshold at −190 HU. All scans were acquired at 50 µm with 720 projections. Variations in the density distribution of the phantoms and tissues were observed in repeated scans.</p

Cladribine and Fludarabine Nucleotides Induce Distinct Hexamers Defining a Common Mode of Reversible RNR Inhibition

The enzyme ribonucleotide reductase (RNR) is a major target of anticancer drugs. Until recently, suicide inactivation in which synthetic substrate analogs (nucleoside diphosphates) irreversibly inactivate the RNR-α₂β₂ heterodimeric complex was the only clinically proven inhibition pathway. For instance, this mechanism is deployed by the multifactorial anticancer agent gemcitabine diphosphate. Recently reversible targeting of RNR-α-alone coupled with ligand-induced RNR-α-persistent hexamerization has emerged to be of clinical significance. To date, clofarabine nucleotides are the only known example of this mechanism. Herein, chemoenzymatic syntheses of the active forms of two other drugs, phosphorylated cladribine (ClA) and fludarabine (FlU), allow us to establish that reversible inhibition is common to numerous drugs in clinical use. Enzyme inhibition and fluorescence anisotropy assays show that the di- and triphosphates of the two nucleosides function as reversible (i.e., nonmechanism-based) inhibitors of RNR and interact with the catalytic (C site) and the allosteric activity (A site) sites of RNR-α, respectively. Gel filtration, protease digestion, and FRET assays demonstrate that inhibition is coupled with formation of conformationally diverse hexamers. Studies in 293T cells capable of selectively inducing either wild-type or oligomerization-defective mutant RNR-α overexpression delineate the central role of RNR-α oligomerization in drug activity, and highlight a potential resistance mechanism to these drugs. These data set the stage for new interventions targeting RNR oligomeric regulation

Conditional Inactivation of the DNA Damage Response Gene <em>Hus1</em> in Mouse Testis Reveals Separable Roles for Components of the RAD9-RAD1-HUS1 Complex in Meiotic Chromosome Maintenance

<div><p>The RAD9-RAD1-HUS1 (9-1-1) complex is a heterotrimeric PCNA-like clamp that responds to DNA damage in somatic cells by promoting DNA repair as well as ATR-dependent DNA damage checkpoint signaling. In yeast, worms, and flies, the 9-1-1 complex is also required for meiotic checkpoint function and efficient completion of meiotic recombination; however, since <i>Rad9</i>, <i>Rad1</i>, and <i>Hus1</i> are essential genes in mammals, little is known about their functions in mammalian germ cells. In this study, we assessed the meiotic functions of 9-1-1 by analyzing mice with germ cell-specific deletion of <i>Hus1</i> as well as by examining the localization of RAD9 and RAD1 on meiotic chromosomes during prophase I. <i>Hus1</i> loss in testicular germ cells resulted in meiotic defects, germ cell depletion, and severely compromised fertility. <i>Hus1-</i>deficient primary spermatocytes exhibited persistent autosomal γH2AX and RAD51 staining indicative of unrepaired meiotic DSBs, synapsis defects, an extended XY body domain often encompassing partial or whole autosomes, and an increase in structural chromosome abnormalities such as end-to-end X chromosome-autosome fusions and ruptures in the synaptonemal complex. Most of these aberrations persisted in diplotene-stage spermatocytes. Consistent with a role for the 9-1-1 complex in meiotic DSB repair, RAD9 localized to punctate, RAD51-containing foci on meiotic chromosomes in a <i>Hus1</i>-dependent manner. Interestingly, RAD1 had a broader distribution that only partially overlapped with RAD9, and localization of both RAD1 and the ATR activator TOPBP1 to the XY body and to unsynapsed autosomes was intact in <i>Hus1</i> conditional knockouts. We conclude that mammalian HUS1 acts as a component of the canonical 9-1-1 complex during meiotic prophase I to promote DSB repair and further propose that RAD1 and TOPBP1 respond to unsynapsed chromatin through an alternative mechanism that does not require RAD9 or HUS1.</p> </div

Patterns of γH2AX localization in <i>Stra8-Cre</i> and <i>Spo11-Cre Hus1</i> CKO spermatocytes.

*<p>p<0.05,</p>**<p>p<0.01,</p>***<p>p<0.001,</p><p><i>Hus1</i> CKO relative to control; z-test of sample proportions.</p