Tectonic evolution of the Southern Ocean between Antarctica, South America and Africa over the past 84Ma

An improved method has been developed for carrying out 2-plate reconstructions, in which fracture zone locations are fitted to synthetic flowlines and magnetic anomaly picks are rotated and fitted to great circles representing other, not necessarily conjugate, anomaly isochrons. This enables the determination of finite rotation poles for regions with sparse data coverage, or where much of one or both plates has been subducted. Misfits and partial derivatives are calculated for each type of data, and combined in a single iterative inversion, allowing the direct calculation of confidence intervals. This method is then extended to a 3-plate reconstruction, taking closure into consideration. The South American - African - Antarctic plate system is then studied. Fracture zone locations are identified from a gravity map constructed from GEOSAT altimeter data, and magnetic anomalies are identified from ship profiles. Two-plate reconstructions are carried out for each plate pair, giving good fits to the observed data, and then all three datasets are combined in a 3-plate reconstruction. Comparison of the results reveals a discontinuity in spreading in the Weddell Sea, believed to be related to pseudo-asymmetric spreading caused by ridge re-organisation in the Paleocene and early Eocene. A revised 3-plate inversion, taking this discontinuity into account, produces an internally consistent set of poles, indicating a closed 3-plate system since anomaly 34 (83Ma), with no evidence for a Malvinas Plate extending into the Weddell Sea in the Late Cretaceous. Disruption to the system from anomaly 32 (71Ma) until anomaly 24 (52Ma), appears to be related to the collision of Africa with Eurasia. A study of the past motion, configuration and stability of the Bouvet Triple junction suggests that for the majority of the past 50Ma it has been in a RFF configuration, in theory considerably less stable than RRR, the other possible configuration

Antilymphoid antibody preconditioning and tacrolimus monotherapy for pediatric kidney transplantation

Objective: Heavy post-transplant immunosuppression may contribute to long-term immunosuppression dependence by subverting tolerogenic mechanisms; thus, we sought to determine if this undesirable consequence could be mitigated by pretransplant lymphoid depletion and minimalistic post-transplant monotherapy. Study design: Lymphoid depletion in 17 unselected pediatric recipients of live (n = 14) or deceased donor kidneys (n = 3) was accomplished with antithymocyte globulin (ATG) (n = 8) or alemtuzumab (n = 9). Tacrolimus was begun post-transplantation with subsequent lengthening of intervals between doses (spaced weaning). Maintenance immunosuppression, morbidity, graft function, and patient/graft survival were collated. Results: Steroids were added temporarily to treat rejection in two patients (both ATG subgroup) or to treat hemolytic anemia in two others. After 16 to 31 months (mean 22), patient and graft survival was 100% and 94%, respectively. The only graft loss was in a nonweaned noncompliant recipient. In the other 16, serum creatinine was 0.85 ± 0.35 mg/dL and creatinine clearance was 90.8 ± 22.1 mL/1.73 m2. All 16 patients are on monotherapy (15 tacrolimus, one sirolimus), and 14 receive every other day or 3 times per week doses. There were no wound or other infections. Two patients developed insulin-dependent diabetes. Conclusion: The strategy of lymphoid depletion and minimum post-transplant immunosuppression appears safe and effective for pediatric kidney recipients. © 2006 Elsevier Inc. All rights reserved

On Planetary Companions to the MACHO-98-BLG-35 Microlens Star

We present observations of microlensing event MACHO-98-BLG-35 which reached a peak magnification factor of almost 80. These observations by the Microlensing Planet Search (MPS) and the MOA Collaborations place strong constraints on the possible planetary system of the lens star and show intriguing evidence for a low mass planet with a mass fraction $4\times 10^{-5} \leq \epsilon \leq 2\times 10^{-4}$. A giant planet with $\epsilon = 10^{-3}$ is excluded from 95% of the region between 0.4 and 2.5 $R_E$ from the lens star, where $R_E$ is the Einstein ring radius of the lens. This exclusion region is more extensive than the generic "lensing zone" which is $0.6 - 1.6 R_E$. For smaller mass planets, we can exclude 57% of the "lensing zone" for $\epsilon = 10^{-4}$ and 14% of the lensing zone for $\epsilon = 10^{-5}$. The mass fraction $\epsilon = 10^{-5}$ corresponds to an Earth mass planet for a lensing star of mass \sim 0.3 \msun. A number of similar events will provide statistically significant constraints on the prevalence of Earth mass planets. In order to put our limits in more familiar terms, we have compared our results to those expected for a Solar System clone averaging over possible lens system distances and orientations. We find that such a system is ruled out at the 90% confidence level. A copy of the Solar System with Jupiter replaced by a second Saturn mass planet can be ruled out at 70% confidence. Our low mass planetary signal (few Earth masses to Neptune mass) is significant at the $4.5\sigma$ confidence level. If this planetary interpretation is correct, the MACHO-98-BLG-35 lens system constitutes the first detection of a low mass planet orbiting an ordinary star without gas giant planets.Comment: ApJ, April 1, 2000; 27 pages including 8 color postscript figure

Chronic allograft nephropathy

Chronic allograft nephropathy (CAN) is the leading cause of renal allograft loss in paediatric renal transplant recipients. CAN is the result of immunological and nonimmunological injury, including acute rejection episodes, hypoperfusion, ischaemia reperfusion, calcineurin toxicity, infection and recurrent disease. The development of CAN is often insidious and may be preceded by subclinical rejection in a well-functioning allograft. Classification of CAN is histological using the Banff classification of renal allograft pathology with classic findings of interstitial fibrosis, tubular atrophy, glomerulosclerosis, fibrointimal hyperplasia and arteriolar hyalinosis. Although improvement in immunosuppression has led to greater 1-year graft survival rates, chronic graft loss remains relatively unchanged and opportunistic infectious complications remain a problem. Protocol biopsy monitoring is not current practice in paediatric transplantation for CAN monitoring but may have a place if new treatment options become available. Newer immunosuppression regimens, closer monitoring of the renal allograft and management of subclinical rejection may lead to reduced immune injury leading to CAN in the paediatric population but must be weighed against the risk of increased immunosuppression and calcineurin inhibitor nephrotoxicity

Automated detection and delineation of lymph nodes in haematoxylin & eosin stained digitised slides

Treatment of patients with oesophageal and gastric cancer (OeGC) is guided by disease stage, patient performance status and preferences. Lymph node (LN) status is one of the strongest prognostic factors for OeGC patients. However, survival varies between patients with the same disease stage and LN status. We recently showed that LN size from patients with OeGC might also have prognostic value, thus making delineations of LNs essential for size estimation and the extraction of other imaging biomarkers. We hypothesized that a machine learning workflow is able to: (1) find digital H&E stained slides containing LNs, (2) create a scoring system providing degrees of certainty for the results, and (3) delineate LNs in those images. To train and validate the pipeline, we used 1695 H&E slides from the OE02 trial. The dataset was divided into training (80%) and validation (20%). The model was tested on an external dataset of 826 H&E slides from the OE05 trial. U-Net architecture was used to generate prediction maps from which predefined features were extracted. These features were subsequently used to train an XGBoost model to determine if a region truly contained a LN. With our innovative method, the balanced accuracies of the LN detection were 0.93 on the validation dataset (0.83 on the test dataset) compared to 0.81 (0.81) on the validation (test) datasets when using the standard method of thresholding U-Net predictions to arrive at a binary mask. Our method allowed for the creation of an “uncertain” category, and partly limited false-positive predictions on the external dataset. The mean Dice score was 0.73 (0.60) per-image and 0.66 (0.48) per-LN for the validation (test) datasets. Our pipeline detects images with LNs more accurately than conventional methods, and high-throughput delineation of LNs can facilitate future LN content analyses of large datasets

Automated detection and delineation of lymph nodes in haematoxylin & eosin stained digitised slides.

Treatment of patients with oesophageal and gastric cancer (OeGC) is guided by disease stage, patient performance status and preferences. Lymph node (LN) status is one of the strongest prognostic factors for OeGC patients. However, survival varies between patients with the same disease stage and LN status. We recently showed that LN size from patients with OeGC might also have prognostic value, thus making delineations of LNs essential for size estimation and the extraction of other imaging biomarkers. We hypothesized that a machine learning workflow is able to: (1) find digital H&E stained slides containing LNs, (2) create a scoring system providing degrees of certainty for the results, and (3) delineate LNs in those images. To train and validate the pipeline, we used 1695 H&E slides from the OE02 trial. The dataset was divided into training (80%) and validation (20%). The model was tested on an external dataset of 826 H&E slides from the OE05 trial. U-Net architecture was used to generate prediction maps from which predefined features were extracted. These features were subsequently used to train an XGBoost model to determine if a region truly contained a LN. With our innovative method, the balanced accuracies of the LN detection were 0.93 on the validation dataset (0.83 on the test dataset) compared to 0.81 (0.81) on the validation (test) datasets when using the standard method of thresholding U-Net predictions to arrive at a binary mask. Our method allowed for the creation of an "uncertain" category, and partly limited false-positive predictions on the external dataset. The mean Dice score was 0.73 (0.60) per-image and 0.66 (0.48) per-LN for the validation (test) datasets. Our pipeline detects images with LNs more accurately than conventional methods, and high-throughput delineation of LNs can facilitate future LN content analyses of large datasets