Association of a large lateral extension of the acromion with rotator cuff tears

BACKGROUND: Factors predisposing to tearing of the rotator cuff are poorly understood. We have observed that the acromion of patients with a rotator cuff tear very often appears large on anteroposterior radiographs or during surgery. The purpose of this study was to quantify the lateral extension of the acromion in patients with a full-thickness rotator cuff tear and in patients with an intact rotator cuff. METHODS: The lateral extension of the acromion was assessed on true anteroposterior radiographs made with the arm in neutral rotation. The distance from the glenoid plane to the lateral border of the acromion was divided by the distance from the glenoid plane to the lateral aspect of the humeral head to calculate the acromion index. This index was determined in a group of 102 patients (average age, 65.0 years) with a proven full-thickness rotator cuff tear, in an age and gender-matched group of forty-seven patients (average age, 63.7 years) with osteoarthritis of the shoulder and an intact rotator cuff, and in an age and gender-matched control group of seventy volunteers (average age, 64.4 years) with an intact rotator cuff as demonstrated by ultrasonography. RESULTS: The average acromion index (and standard deviation) was 0.73 +/- 0.06 in the shoulders with a full-thickness tear, 0.60 +/- 0.08 in those with osteoarthritis and an intact rotator cuff, and 0.64 +/- 0.06 in the asymptomatic, normal shoulders with an intact rotator cuff. The difference between the index in the shoulders with a full-thickness supraspinatus tear and the index in those with an intact rotator cuff was highly significant (p < 0.0001). CONCLUSIONS: A large lateral extension of the acromion appears to be associated with full-thickness tearing of the rotator cuff.

Designed Extension of Survival Studies: Application to Clinical Trials with Unrecognized Heterogeneity

It is well known that unrecognized heterogeneity among patients, such as is conferred by genetic subtype, can undermine the power of randomized trial, designed under the assumption of homogeneity, to detect a truly beneficial treatment. We consider the conditional power approach to allow for recovery of power under unexplained heterogeneity. While Proschan and Hunsberger (1995) confined the application of conditional power design to normally distributed observations, we consider more general and difficult settings in which the data are in the framework of continuous time and are subject to censoring. In particular, we derive a procedure appropriate for the analysis of the weighted log rank test under the assumption of a proportional hazards frailty model. The proposed method is illustrated through application to a brain tumor trial.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

Stochastic Models Based on Molecular Hybridization Theory for Short Oligonucleotide Microarrays

High density oligonucleotide expression arrays are a widely used tool for the measurement of gene expression on a large scale. Affymetrix GeneChip arrays appear to dominate this market. These arrays use short oligonucleotides to probe for genes in an RNA sample. Due to optical noise, non-specific hybridization, probe-specific effects, and measurement error, ad-hoc measures of expression, that summarize probe intensities, can lead to imprecise and inaccurate results. Various researchers have demonstrated that expression measures based on simple statistical models can provide great improvements over the ad-hoc procedure offered by Affymetrix. Recently, physical models based on molecular hybridization theory, have been proposed as useful tools for prediction of, for example, non-specific hybridization. These physical models show great potential in terms of improving existing expression measures. In this paper we demonstrate that the system producing the measured intensities is too complex to be fully described with these relatively simple physical models and we propose empirically motivated stochastic models that compliment the above mentioned molecular hybridization theory to provide a comprehensive description of the data. We discuss how the proposed model can be used to obtain improved measures of expression useful for the data analysts.

Magnetic resonance imaging features of orbital inflammation with intracranial extension in four dogs

This retrospective study describes the clinical and magnetic resonance (MR) imaging features of chronic orbital inflammation with intracranial extension in four dogs (two Dachshunds, one Labrador, one Swiss Mountain). Intracranial extension was observed through the optic canal (n=1), the orbital fissure (n=4), and the alar canal (n=1). On T1-weighted images structures within the affected skull foramina could not be clearly differentiated, but were all collectively isointense to hypointense compared with the contralateral, unaffected side, or compared with gray matter. On T2-, short tau inversion recovery (STIR)-, or fluid-attenuated inversion recovery (FLAIR)-weighted images structures within the affected skull foramina appeared hyperintense compared with gray matter, and extended with increased signal into the rostral cranial fossa (n=1) and middle cranial fossa (n=4). Contrast enhancement at the level of the affected skul foramina as well as at the skull base in continuity with the orbital fissure was observed in all patients. Brain edema or definite meningeal enhancement could not be observed, but a close anatomic relationship of the abnormal tissue to the cavernous sinus was seen in two patients. Diagnosis was confirmed in three dogs (one cytology, two biopsy, one necropsy) and was presumptive in one based on clinical improvement after treatment. This study is limited by its small sample size, but provides evidence for a potential risk of intracranial extension of chronic orbital inflammation. This condition can be identified best by abnormal signal increase at the orbital fissure on transverse T2-weighted images, on dorsal STIR images, or on postcontrast transverse or dorsal images.

Prognostic factors in lymph node metastases of prostatic cancer patients: the size of the metastases but not extranodal extension independently predicts survival

AIMS: To analyse tumour characteristics and the prognostic significance of prostatic cancers with extranodal extension of lymph node metastases (ENE) in 102 node-positive, hormone treatment-naive patients undergoing radical prostatectomy and extended lymphadenectomy. METHODS AND RESULTS: The median number of nodes examined per patient was 21 (range 9-68), and the median follow-up time was 92 months (range 12-191). ENE was observed in 71 patients (70%). They had significantly more, larger and less differentiated nodal metastases, paralleled by significantly larger primary tumours at more advanced stages and with higher Gleason scores than patients without ENE. ENE defined a subgroup with significantly decreased biochemical recurrence-free (P = 0.038) and overall survival (P = 0.037). In multivariate analyses the diameter of the largest metastasis and Gleason score of the primary tumour were independent predictors of survival. CONCLUSIONS: ENE in prostatic cancer is an indicator lesion for advanced/aggressive tumours with poor outcome. However, the strong correlation with larger metastases suggests that ENE may result from their size, which was the only independent risk factor in the metastasizing component. Consequently, histopathological reports should specify the true indicator of poor survival in the lymphadenectomy specimens, which is the size of the largest metastasis in each patient.

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

Low-grade endometrial stromal sarcoma with inferior vena cava tumor thrombus and intracardiac extension: radical resection may improve recurrence free survival

BACKGROUND: Endometrial stromal sarcoma (ESS) represents 0.2% of all uterine malignancies. Based on the mitotic activity, a distinction is made between low and high-grade ESS. Although the overall five-year survival rate for low-grade ESS exceeds 80%, about 50% of the patients show tumor recurrence, mostly after a long latency period. Tumor invasion of the great vessels is extremely rare. We describe a patient with advanced low-grade ESS with tumor invasion of the infrarenal aorta and the inferior vena cava. The patient presented with a large tumor thrombus extending from the inferior vena cava into the right atrium. METHODS: Review of literature and identification of 19 patients, including our own case report, with advanced low-grade ESS with invasion of the great vessels and formation of an inferior vena cava tumor thrombus. RESULTS: All 19 patients presented with an abdominal tumor mass and a tumor thrombus protruding into the inferior vena cava. The tumor thrombus extended into the right heart cavities in nine patients reaching the right atrium in four, the right ventricle in three and the pulmonary artery in two patients. There were 5 patients with an advanced primary tumor and 14 patients with an advanced recurrent tumor. Seven patients presented with synchronous metastatic disease and six patients with a pelvic tumor infiltrating the bladder, the rectosigmoid colon or the infrarenal aorta. Mean age at surgery was 45.9+/-12.3 years (median 47, range 25-65 years). Tumor thrombectomy was accomplished by cavatomy or by right atriotomy after installation of a cardiopulmonary bypass. There was no peri-operative mortality and a very low morbidity. Radical tumor resections were achieved in 10 patients. The follow-up for these 10 patients was 2+/-1.3 years (median 2, range 0.3-4.5 years). Nine patients remained recurrence free whereas one patient suffered an asymptomatic local recurrence. CONCLUSIONS: Low-grade ESS is a rare angioinvasive tumor with a high recurrence rate. Resection of an inferior vena cava tumor thrombus, even with extension into the right heart cavities, can be performed safely. Extensive radical surgery is therefore justified in the treatment of advanced tumor manifestations of a low-grade ESS potentially improving recurrence free survival.

STOCHASTIC CHARGE TRANSPORT IN MULTI-ISLAND SINGLE-ELECTRON TUNNELING DEVICES

The physics of the operation of singe-electron tunneling devices (SEDs) and singe-electron tunneling transistors (SETs), especially of those with multiple nanometer-sized islands, has remained poorly understood in spite of some intensive experimental and theoretical research. This computational study examines the current-voltage (IV) characteristics of multi-island single-electron devices using a newly developed multi-island transport simulator (MITS) that is based on semi-classical tunneling theory and kinetic Monte Carlo simulation. The dependence of device characteristics on physical device parameters is explored, and the physical mechanisms that lead to the Coulomb blockade (CB) and Coulomb staircase (CS) characteristics are proposed. Simulations using MITS demonstrate that the overall IV characteristics in a device with a random distribution of islands are a result of a complex interplay among those factors that affect the tunneling rates that are fixed a priori (e.g. island sizes, island separations, temperature, gate bias, etc.), and the evolving charge state of the system, which changes as the source-drain bias (VSD) is changed. With increasing VSD, a multi-island device has to overcome multiple discrete energy barriers (up-steps) before it reaches the threshold voltage (Vth). Beyond Vth, current flow is rate-limited by slow junctions, which leads to the CS structures in the IV characteristic. Each step in the CS is characterized by a unique distribution of island charges with an associated distribution of tunneling probabilities. MITS simulation studies done on one-dimensional (1D) disordered chains show that longer chains are better suited for switching applications as Vth increases with increasing chain length. They are also able to retain CS structures at higher temperatures better than shorter chains. In sufficiently disordered 2D systems, we demonstrate that there may exist a dominant conducting path (DCP) for conduction, which makes the 2D device behave as a quasi-1D device. The existence of a DCP is sensitive to the device structure, but is robust with respect to changes in temperature, gate bias, and VSD. A side gate in 1D and 2D systems can effectively control Vth. We argue that devices with smaller island sizes and narrower junctions may be better suited for practical applications, especially at room temperature.