Heterogeneous cancer-associated fibroblast population potentiates neuroendocrine differentiation and castrate resistance in a CD105-dependent manner.

Heterogeneous prostatic carcinoma-associated fibroblasts (CAF) contribute to tumor progression and resistance to androgen signaling deprivation therapy (ADT). CAF subjected to extended passaging, compared to low passage CAF, were found to lose tumor expansion potential and heterogeneity. Cell surface endoglin (CD105), known to be expressed on proliferative endothelia and mesenchymal stem cells, was diminished in high passage CAF. RNA-sequencing revealed SFRP1 to be distinctly expressed by tumor-inductive CAF, which was further demonstrated to occur in a CD105-dependent manner. Moreover, ADT resulted in further expansion of the CD105+ fibroblastic population and downstream SFRP1 in 3-dimensional cultures and patient-derived xenograft tissues. In patients, CD105+ fibroblasts were found to circumscribe epithelia with neuroendocrine differentiation. CAF-derived SFRP1, driven by CD105 signaling, was necessary and sufficient to induce prostate cancer neuroendocrine differentiation in a paracrine manner. A partially humanized CD105 neutralizing antibody, TRC105, inhibited fibroblastic SFRP1 expression and epithelial neuroendocrine differentiation. In a novel synthetic lethality paradigm, we found that simultaneously targeting the epithelia and its microenvironment with ADT and TRC105, respectively, reduced castrate-resistant tumor progression, in a model where either ADT or TRC105 alone had little effect

Evaluating the Impact of Uveitis on Visual Field Progression Using Large Scale Real-World Data

PURPOSE: To compare rates of visual field (VF) loss in uveitis patients with glaucoma against patients with primary open angle glaucoma (POAG) and explores the association between intraocular pressures (IOP) and rate of VF loss. Design; Retrospective cohort study. METHODS: Anonymized VFs and IOP measurements extracted from the EMR of 5 regionally different glaucoma clinics in England. A total of 205 eyes with diagnosis of "uveitis" plus "glaucoma" were compared with 4600 eyes with "POAG" only. Minimum inclusion criteria was ≥4 visits within a 4-year window. Relative risk (RR) of being a "rapid progressor" (mean deviation (MD) loss ≥1.5 dB/year) was calculated. A mixed-effects model (MEM) and a pointwise VF progression analysis of pattern deviation was used to confirm differences between the groups. Longitudinal IOP mean, range and variability were compared with rate of VF progression. RESULTS: Median (IQR) baseline MD in the uveitis and POAG groups was -3.8 (-8.7, -1.5) dB and -3.1 (-6.6, -1.2) dB respectively. The uveitis and POAG groups had 23/205 (11%) and 331/4600 (7%) "rapidly progressing" eyes respectively. Age-adjusted RR for "rapid progression" in uveitic versus POAG eyes was 1.9 (95% CI:1.8-2.0). The MEM confirmed that uveitic eyes (-0.49 dB/year) showed higher rates of VF progression than the POAG group (-0.37 dB/year; p<0.01). IOP range and variability were higher in the "rapidly progressing" uveitic eyes. CONCLUSIONS: Our analysis suggests that VF loss occurs faster in glaucoma patients with uveitis than those without uveitis. The risk of progressing rapidly in glaucoma with uveitis is almost double than in those without uveitis. Early identification of "rapid progressors" may enable targeted intervention to preserve visual function in this high-risk group

Effect of Carbon Dioxide on the Twinkling Artifact in Ultrasound Imaging of Kidney Stones: A Pilot Study

Bone demineralization, dehydration and stasis put astronauts at increased risk of forming kidney stones in space. The color-Doppler ultrasound "twinkling artifact," which highlights kidney stones with color, can make stones readily detectable with ultrasound; however, our previous results suggest twinkling is caused by microbubbles on the stone surface which could be affected by the elevated levels of carbon dioxide found on space vehicles. Four pigs were implanted with kidney stones and imaged with ultrasound while the anesthetic carrier gas oscillated between oxygen and air containing 0.8% carbon dioxide. On exposure of the pigs to 0.8% carbon dioxide, twinkling was significantly reduced after 9-25 min and recovered when the carrier gas returned to oxygen. These trends repeated when pigs were again exposed to 0.8% carbon dioxide followed by oxygen. The reduction of twinkling caused by exposure to elevated carbon dioxide may make kidney stone detection with twinkling difficult in current space vehicles

Rapid glutamate receptor 2 trafficking during retinal degeneration

<p>Abstract</p> <p>Background</p> <p>Retinal degenerations, such as age-related macular degeneration (AMD) and retinitis pigmentosa (RP), are characterized by photoreceptor loss and anomalous remodeling of the surviving retina that corrupts visual processing and poses a barrier to late-stage therapeutic interventions in particular. However, the molecular events associated with retinal remodeling remain largely unknown. Given our prior evidence of ionotropic glutamate receptor (iGluR) reprogramming in retinal degenerations, we hypothesized that the edited glutamate receptor 2 (GluR2) subunit and its trafficking may be modulated in retinal degenerations.</p> <p>Results</p> <p>Adult albino Balb/C mice were exposed to intense light for 24 h to induce light-induced retinal degeneration (LIRD). We found that prior to the onset of photoreceptor loss, protein levels of GluR2 and related trafficking proteins, including glutamate receptor-interacting protein 1 (GRIP1) and postsynaptic density protein 95 (PSD-95), were rapidly increased. LIRD triggered neuritogenesis in photoreceptor survival regions, where GluR2 and its trafficking proteins were expressed in the anomalous dendrites. Immunoprecipitation analysis showed interaction between KIF3A and GRIP1 as well as PSD-95, suggesting that KIF3A may mediate transport of GluR2 and its trafficking proteins to the novel dendrites. However, in areas of photoreceptor loss, GluR2 along with its trafficking proteins nearly vanished in retracted retinal neurites.</p> <p>Conclusions</p> <p>All together, LIRD rapidly triggers GluR2 plasticity, which is a potential mechanism behind functionally phenotypic revisions of retinal neurons and neuritogenesis during retinal degenerations.</p

A priori discretization error metrics for distributed hydrologic modeling applications

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.jhydrol.2016.11.008 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a sub basin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.NSERC Canadian FloodNet gran

DEEPMIR: A DEEP neural network for differential detection of cerebral Microbleeds and IRon deposits in MRI

Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and neurodegenerative disorders. Particularly, CMBs are small lesions and require multiple neuroimaging modalities for accurate detection. Quantitative susceptibility mapping (QSM) derived from in vivo magnetic resonance imaging (MRI) is necessary to differentiate between iron content and mineralization. We set out to develop a deep learning-based segmentation method suitable for segmenting both CMBs and iron deposits. We included a convenience sample of 24 participants from the MESA cohort and used T2-weighted images, susceptibility weighted imaging (SWI), and QSM to segment the two types of lesions. We developed a protocol for simultaneous manual annotation of CMBs and non-hemorrhage iron deposits in the basal ganglia. This manual annotation was then used to train a deep convolution neural network (CNN). Specifically, we adapted the U-Net model with a higher number of resolution layers to be able to detect small lesions such as CMBs from standard resolution MRI. We tested different combinations of the three modalities to determine the most informative data sources for the detection tasks. In the detection of CMBs using single class and multiclass models, we achieved an average sensitivity and precision of between 0.84-0.88 and 0.40-0.59, respectively. The same framework detected non-hemorrhage iron deposits with an average sensitivity and precision of about 0.75-0.81 and 0.62-0.75, respectively. Our results showed that deep learning could automate the detection of small vessel disease lesions and including multimodal MR data (particularly QSM) can improve the detection of CMB and non-hemorrhage iron deposits with sensitivity and precision that is compatible with use in large-scale research studies

Collision-induced C_60 rovibrational relaxation probed by state-resolved nonlinear spectroscopy

Quantum state-resolved spectroscopy was recently achieved for C60 molecules when cooled by buffer gas collisions and probed with a midinfrared frequency comb. This rovibrational quantum state resolution for the largest molecule on record is facilitated by the remarkable symmetry and rigidity of C60, which also present new opportunities and challenges to explore energy transfer between quantum states in this many-atom system. Here we combine state-specific optical pumping, buffer gas collisions, and ultrasensitive intracavity nonlinear spectroscopy to initiate and probe the rotation-vibration energy transfer and relaxation. This approach provides the first detailed characterization of C60 collisional energy transfer for a variety of collision partners, and determines the rotational and vibrational inelastic collision cross sections. These results compare well with our theoretical modeling of the collisions, and establish a route towards quantum state control of a new class of unprecedentedly large molecules

Quantification of Renal Stone Contrast with Ultrasound in Human Subjects

Purpose: Greater visual contrast between calculi and tissue would improve ultrasound (US) imaging of urolithiasis and potentially expand clinical use. The color Doppler twinkling artifact has been suggested to provide enhanced contrast of stones compared with brightness mode (B-mode) imaging, but results are variable. This work provides the first quantitative measure of stone contrast in humans for B-mode and color Doppler mode, forming the basis to improve US for the detection of stones. Materials and Methods: Using a research ultrasound system, B-mode imaging was tuned for detecting stones by applying a single transmit angle and reduced signal compression. Stone twinkling with color Doppler was tuned by using low-frequency transmit pulses, longer pulse durations, and a high-pulse repetition frequency. Data were captured from 32 subjects, with 297 B-mode and Doppler images analyzed from 21 subjects exhibiting twinkling signals. The signal to clutter ratio (i.e., stone to background tissue) (SCR) was used to compare the contrast of a stone on B-mode with color Doppler, and the contrast between stone twinkling and blood-flow signals within the kidney. Results: The stone was the brightest object in only 54% of B-mode images and 100% of Doppler images containing stone twinkling. On average, stones were isoechoic with the tissue clutter on B-mode (SCR = 0 dB). Stone twinkling averaged 37 times greater contrast than B-mode (16 dB, p < 0.0001) and 3.5 times greater contrast than blood-flow signals (5.5 dB, p = 0.088). Conclusions: This study provides the first quantitative measure of US stone to tissue contrast in humans. Stone twinkling contrast is significantly greater than the contrast of a stone on B-mode. There was also a trend of stone twinkling signals having greater contrast than blood-flow signals in the kidney. Dedicated optimization of B-mode and color Doppler stone imaging could improve US detection of stones