[DOTA]Somatostatin-14 analogs and their (111)In-radioligands: effects of decreasing ring-size on sst1-5 profile, stability and tumor targeting.

Multiple somatostatin receptor (sst)-subtype expression has been manifested in several human tumors. Hence, the availability of radiopeptides retaining the full pansomatostatin profile of the native hormone (SS14) is expected to increase the sensitivity and broaden the clinical indications of currently applied sst2-preferring cyclic octapeptide radioligands, like OctreoScan(®) ([(111)In-DTPA]octreotide). On the other hand, SS14 has been excluded from clinical use due to its rapid in vivo degradation. We herein present a small library of seven novel cyclic SS14-mimics carrying at their N-terminus the universal chelator DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) for stable binding of medically useful radiometals, like (111)In. By decreasing the number of amino acids composing the ring in their structure from 12 up to 6 AA, we induced important changes in key-biological parameters in vitro and in vivo. In particular, we observed unexpected changes and even total loss of sst1-5-affinity (6AA-ring), as well as weaker sst2-internalization efficacy as the ring size decreased. In contrast, in vivo stability increased with decreasing ring size, reaching its maximum in the 6AA-ring analogs. Interestingly, only the 12AA- and 9AA-ring members of this series showed sst2-specific uptake in AR4-2J tumors in mice revealing the prominent role of ring size on the biological response of tested SS14-derived radioligands.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Cephalometric analysis is an essential clinical and research tool in orthodontics for the orthodontic analysis and treatment planning. This paper presents the evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge, held at the IEEE International Symposium on Biomedical Imaging 2014 with an on-site competition. The challenge was set to explore and compare automatic landmark detection methods in application to cephalometric X-ray images. Methods were evaluated on a common database including cephalograms of 300 patients aged six to 60 years, collected from the Dental Department, Tri-Service General Hospital, Taiwan, and manually marked anatomical landmarks as the ground truth data, generated by two experienced medical doctors. Quantitative evaluation was performed to compare the results of a representative selection of current methods submitted to the challenge. Experimental results show that three methods are able to achieve detection rates greater than 80% using the 4 mm precision range, but only one method achieves a detection rate greater than 70% using the 2 mm precision range, which is the acceptable precision range in clinical practice. The study provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.

GOCE precise orbit determination for the entire Mission – challenges in the final mission phase

The Gravity field and steady-state Ocean Circulation Explorer (GOCE), ESA’s first Earth Explorer core mission, was launched on March 17, 2009 into a sunsynchronous dusk-dawn orbit and eventually re-entered into the Earth’s atmosphere on November 11, 2013. A precise science orbit (PSO) product was provided by the GOCE High-level Processing Facility (HPF) from the GPS high-low Satellite-to-Satellite Tracking (hl-SST) data from the beginning until the very last days of the mission. We recapitulate the PSO procedure and refer to the results achieved until the official end of the GOCE mission on October 21, 2013, where independent validations with Satellite Laser ranging (SLR) measurements confirmed a high quality of the PSO product of about 2 cm 1-D RMS. We then focus on the period after the official end of the mission, where orbits could still be determined thanks to the continuously running GPS receivers delivering high quality data until a few hours before the re-entry into the Earth’s atmosphere. We address the challenges encountered for orbit determination during these last days and report on adaptions in the PSO procedure to also obtain good orbit results at the unprecedented low orbital altitudes below 224 km.

Time Variable Gravity: Contributions of GOCE Satellite Data to Monthly and Bi-monthly GRACE Gravity Estimates

A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

Effect of surface restoring on subsurface variability in a climate model during 1949–2005

Initializing the ocean for decadal predictability studies is a challenge, as it requires reconstructing the little observed subsurface trajectory of ocean variability. In this study we explore to what extent surface nudging using well-observed sea surface temperature (SST) can reconstruct the deeper ocean variations for the 1949–2005 period. An ensemble made with a nudged version of the IPSLCM5A model and compared to ocean reanalyses and reconstructed datasets. The SST is restored to observations using a physically-based relaxation coefficient, in contrast to earlier studies, which use a much larger value. The assessment is restricted to the regions where the ocean reanalyses agree, i.e. in the upper 500 m of the ocean, although this can be latitude and basin dependent. Significant reconstruction of the subsurface is achieved in specific regions, namely region of subduction in the subtropical Atlantic, below the thermocline in the equatorial Pacific and, in some cases, in the North Atlantic deep convection regions. Beyond the mean correlations, ocean integrals are used to explore the time evolution of the correlation over 20-year windows. Classical fixed depth heat content diagnostics do not exhibit any significant reconstruction between the different existing bservation-based references and can therefore not be used to assess global average time-varying correlations in the nudged simulations. Using the physically based average temperature above an isotherm (14°C) alleviates this issue in the tropics and subtropics and shows significant reconstruction of these quantities in the nudged simulations for several decades. This skill is attributed to the wind stress reconstruction in the tropics, as already demonstrated in a perfect model study using the same model. Thus, we also show here the robustness of this result in an historical and observational context.

Detecting dementia in patients with normal neuropsychological screening by Short Smell Test and Palmo-Mental Reflex Test: an observational study

BACKGROUND General practitioners (GPs) are in best position to suspect dementia. Mini-Mental State Examination (MMSE) and Clock Drawing Test (CDT) are widely used. Additional neurological tests may increase the accuracy of diagnosis. We aimed to evaluate diagnostic ability to detect dementia with a Short Smell Test (SST) and Palmo-Mental Reflex (PMR) in patients whose MMSE and CDT are normal, but who show signs of cognitive dysfunction. METHODS This was a 3.5-year cross-sectional observational study in the Memory Clinic of the University Department of Geriatrics in Bern, Switzerland. Participating patients with normal MMSE (>26 points) and CDT (>5 points) were referred by GPs because they suspected dementia. All were examined according to a standardized protocol. Diagnosis of dementia was based on DSM-IV TR criteria. We used SST and PMR to determine if they accurately detected dementia. RESULTS In our cohort, 154 patients suspected of dementia had normal MMSE and CDT test results. Of these, 17 (11 %) were demented. If SST or PMR were abnormal, sensitivity was 71 % (95 % CI 44-90 %), and specificity 64 % (95 % CI 55-72 %) for detecting dementia. If both tests were abnormal, sensitivity was 24 % (95 % CI 7-50 %), but specificity increased to 93 % (95 % CI 88-97 %). CONCLUSION Patients suspected of dementia, but with normal MMSE and CDT results, may benefit if SST and PMR are added as diagnostic tools. If both SST and PMR are abnormal, this is a red flag to investigate these patients further, even though their negative neuropsychological screening results.

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network

Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.

Retention in care of HIV-infected pregnant and lactating women starting art under Option B+ in rural Mozambique.

OBJECTIVE In 2013, Mozambique adopted Option B+, universal lifelong antiretroviral therapy (ART) for all pregnant and lactating women, as national strategy for prevention of mother-to-child transmission of HIV. We analyzed retention in care of pregnant and lactating women starting Option B+ in rural northern Mozambique. METHODS We compared ART outcomes in pregnant ("B+pregnant"), lactating ("B+lactating") and non-pregnant-non-lactating women of childbearing age starting ART after clinical and/or immunological criteria ("own health") between July 2013 and June 2014. Lost to follow-up was defined as no contact >180 days after the last visit. Multivariable competing risk models were adjusted for type of facility (type 1 vs. peripheral type 2 health center), age, WHO stage and time from HIV diagnosis to ART. RESULTS Over 333 person-years of follow-up (of 243 "B+pregnant", 65″B+lactating" and 317 "own health" women), 3.7% of women died and 48.5% were lost to follow-up. "B+pregnant" and "B+lactating" women were more likely to be lost in the first year (57% vs. 56.9% vs. 31.6%; p<0.001) and to have no follow-up after the first visit (42.4% vs. 29.2% vs. 16.4%; p<0.001) than "own health" women. In adjusted analyses, risk of being lost to follow-up was higher in "B+pregnant" (adjusted subhazard ratio [asHR]: 2.77; 95% CI: 2.18-3.50; p<0.001) and "B+lactating" (asHR: 1.94; 95% CI: 1.37-2.74; p<0.001). Type 2 health center was the only additional significant risk factor for loss to follow-up. CONCLUSIONS Retaining pregnant and lactating women in option B+ ART was poor; losses to follow-up were mainly early. The success of Option B+ for prevention of mother-to-child transmission of HIV in rural settings with weak health systems will depend on specific improvements in counseling and retention measures, especially at the beginning of treatment. This article is protected by copyright. All rights reserved.