A new G-quadruplex-specific photosensitizer inducing genome instability in cancer cells by triggering oxidative DNA damage and impeding replication fork progression.

Photodynamic therapy (PDT) ideally relies on the administration, selective accumulation and photoactivation of a photosensitizer (PS) into diseased tissues. In this context, we report a new heavy-atom-free fluorescent G-quadruplex (G4) DNA-binding PS, named DBI. We reveal by fluorescence microscopy that DBI preferentially localizes in intraluminal vesicles (ILVs), precursors of exosomes, which are key components of cancer cell proliferation. Moreover, purified exosomal DNA was recognized by a G4-specific antibody, thus highlighting the presence of such G4-forming sequences in the vesicles. Despite the absence of fluorescence signal from DBI in nuclei, light-irradiated DBI-treated cells generated reactive oxygen species (ROS), triggering a 3-fold increase of nuclear G4 foci, slowing fork progression and elevated levels of both DNA base damage, 8-oxoguanine, and double-stranded DNA breaks. Consequently, DBI was found to exert significant phototoxic effects (at nanomolar scale) toward cancer cell lines and tumor organoids. Furthermore, in vivo testing reveals that photoactivation of DBI induces not only G4 formation and DNA damage but also apoptosis in zebrafish, specifically in the area where DBI had accumulated. Collectively, this approach shows significant promise for image-guided PDT.

Measuring glomerular blood transfer rate in kidney using diffusion-weighted arterial spin labeling.

PURPOSE: To propose a two-compartment renal perfusion model for calculating glomerular blood transfer rate ( k G $$ {k}_G $$ ) as a new measure of renal function. THEORY: The renal perfusion signal was divided into preglomerular and postglomerular flows according to flow velocity. By analyzing perfusion signals acquired with and without diffusion gradients, we estimated k G $$ {k}_G $$ , the blood transfer rate from the afferent arterioles into the glomerulus. METHODS: A multislice multidelay diffusion-weighted arterial spin labeling sequence was applied to subjects with no history of renal dysfunctions. In the multiple b-value experiment, images were acquired with seven b-values to validate the bi-exponential decays of the renal perfusion signal and to determine the appropriate b-value for suppressing preglomerular flow. In the caffeine challenge, six subjects were scanned twice on the caffeine day and the control day. The k G $$ {k}_G $$ values of the two dates were compared. RESULTS: The perfusion signal showed a bi-exponential decay with b-values. There was no significant difference in renal blood flow and arterial transit time between caffeine and control days. In contrast, cortical k G $$ {k}_G $$ was significantly higher on the caffeine day (caffeine day: 106 . 0 ± 20 . 3 $$ 106.0\pm 20.3 $$ min - 1 $$ {}^{-1} $$ control day: 78 . 8 ± 22 . 9 $$ 78.8\pm 22.9 $$ min - 1 $$ {}^{-1} $$ ). These results were consistent with those from the literature. CONCLUSION: We showed that the perfusion signal consists of two compartments of preglomerular flow and postglomerular flow. The proposed diffusion-weighted arterial spin labeling could measure the glomerular blood transfer rate ( k G $$ {k}_G $$ ), which was sensitive enough to noninvasively monitor the caffeine-induced vasodilation of afferent arterioles.

Unsupervised resolution-agnostic quantitative susceptibility mapping using adaptive instance normalization.

Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging (MRI) technique that provides the spatial distribution of magnetic susceptibility values of tissues. QSMs can be obtained by deconvolving the dipole kernel from phase images, but the spectral nulls in the dipole kernel make the inversion ill-posed. In recent years, deep learning approaches have shown a comparable QSM reconstruction performance to the classic approaches, in addition to the fast reconstruction time. Most of the existing deep learning methods are, however, based on supervised learning, so matched pairs of input phase images and ground-truth maps are needed. Moreover, it was reported that the deep learning-based methods fail to reconstruct QSM when the resolution of test data is different from the trained resolution. To address this, here we propose an unsupervised resolution-agnostic QSM deep learning method. The proposed method does not require QSM labels for training and reconstructs QSM with various resolutions by using adaptive instance normalization. Experimental results and clinical validation confirm that the proposed method provides accurate QSM with various resolutions compared to other deep learning approaches, and shows competitive performance to the best classical approaches in addition to the ultra-fast reconstruction.

Assessment of Renal Perfusion in Transplanted Kidney Patients Using Pseudo-Continuous Arterial Spin Labeling with Multiple Post-Labeling Delays.

PURPOSE: To investigate technical issues for implementing pseudo-continuous arterial spin labeling (pCASL) for renal perfusion measurements in transplanted kidney patients (TK) in the early postoperative recovery phase. METHODS: Eleven subjects were scanned: TK (N = 4, 42 ±â€¯8.1Y) and normal volunteers (NV) (N = 7, 25 ±â€¯3Y). In 3.0 T clinical MRI, pCASL with a 2D balanced steady-state free precession readout was applied with four different post-labeling delays: 0.5/1.0/1.5/2.0 s. Perfusion images were acquired with and without background suppression and processed with and without registration for comparison. Renal blood flow (RBF) and arterial transit time (ATT) values were calculated from each pixel of images. The F-test, Wilcoxon signed-rank test, and Wilcoxon rank-sum test were used for statistical analyses. RESULTS: Background suppression decreased signal variations for both NV and TK. Registration suppressed effects of kidney motion for NV, which was not critical for TK. The renal cortex showed greater perfusion than the renal medulla in both NV and TK(p < 0.01). TK showed greater renal perfusion than NV(p < 0.05). Cortical and medullary RBF values were 271.8 ±â€¯43.5, 119.1 ±â€¯15.1 ml/100 g/min for NV and 358.3 ±â€¯36.4, 141.0 ±â€¯11.5 ml/100 g/min for TK. TK showed longer ATT values than NV(p < 0.01). ATT values in the cortex and medulla were 641 ±â€¯141 and 746 ±â€¯150 ms for NV and 919 ±â€¯49 and 935 ±â€¯81 ms for TK. CONCLUSIONS: We demonstrated that although there is no discernible motion of the transplanted kidney, background suppression is necessary to suppress signal fluctuations in renal perfusion measurements. Also, relatively high RBF and long ATT values were observed in the transplanted kidneys in the early postoperative recovery phase, which requires further longitudinal studies.

Quantitative susceptibility map reconstruction using annihilating filter-based low-rank Hankel matrix approach.

PURPOSE: Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on k-space low-rank Hankel matrix constraint, avoiding the over-smoothing problem and streaking artifacts. THEORY AND METHODS: Based on the recent theory of annihilating filter-based low-rank Hankel matrix approach (ALOHA), QSM is formulated as deconvolution under low-rank Hankel matrix constraint in the k-space. The computational complexity and the high memory burden were reduced by successive reconstruction of 2-D planes along 3 independent axes of the 3-D phase image in Fourier domain. Feasibility of the proposed method was tested on a simulated phantom and human data and were compared with existing QSM reconstruction methods. RESULTS: The proposed ALOHA-QSM effectively reduced streaking artifacts and accurately estimated susceptibility values in deep gray matter structures, compared to the existing QSM methods. CONCLUSIONS: The suggested ALOHA-QSM algorithm successfully solves the 3-dimensional QSM dipole inversion problem using k-space low rank property with no anatomical constraint. ALOHA-QSM can provide detailed brain structures and accurate susceptibility values with no streaking artifacts.