Chirurgische und interventionelle Behandlung der chronisch-kritischen Beinischämie

Zusammenfassung: Die chronisch-kritische Beinischämie (CLI) ist die schwerste Form der peripher-arteriellen Verschlusskrankheit und geht mit einem erhöhten Risiko für letale kardiovaskuläre Ereignisse einher. Die meisten Patienten überleben aber die ersten Jahre nach Diagnosestellung und sind für den Erhalt ihrer Selbständigkeit auf eine nachhaltige Verbesserung der Beindurchblutung angewiesen. Dieser CME-Artikel fasst die chirurgischen und endovaskulären Optionen zur Revaskularisierung zusammen und geht auf deren Nachhaltigkeit bei CLI ein. Grenzen der verfügbaren Evidenz werden aufgezeigt. Sie beruhen vor allem auf dem Fehlen einer einheitlichen Definition des Behandlungserfolges. Ein klinisch orientierter Lösungsvorschlag wird diskutiert, der helfen könnte, die verschiedenen Behandlungsindikationen zu schärfen. Da sich aber nur die wenigsten Patienten gleich gut für verschiedene Verfahren eignen, werden CLI-Patienten auch in Zukunft am besten in einem interdisziplinär arbeitenden Team betreut sei

Valley splitting in strained silicon quantum wells

A theory based on localized-orbital approaches is developed to describe the valley splitting observed in silicon quantum wells. The theory is appropriate in the limit of low electron density and relevant for proposed quantum computing architectures. The valley splitting is computed for realistic devices using the quantitative nanoelectronic modeling tool NEMO. A simple, analytically solvable tight-binding model is developed, it yields much physical insight, and it reproduces the behavior of the splitting in the NEMO results. The splitting is in general nonzero even in the absence of electric field in contrast to previous works. The splitting in a square well oscillates as a function of S, the number of layers in the quantum well, with a period that is determined by the location of the valley minimum in the Brillouin zone. The envelope of the splitting decays as $S^3$. Finally the feasibility of observing such oscillations experimentally in modern Si/SiGe heterostructures is discussed.Comment: 19 pages, including 4 figure

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

Kinetics of exciton photoluminescence in type-II semiconductor superlattices

The exciton decay rate at a rough interface in type-II semiconductor superlattices is investigated. It is shown that the possibility of recombination of indirect excitons at a plane interface essentially affects kinetics of the exciton photoluminescence at a rough interface. This happens because of strong correlation between the exciton recombination at the plane interface and at the roughness. Expressions that relate the parameters of the luminescence kinetics with statistical characteristics of the rough interface are obtained. The mean height and length of roughnesses in GaAs/AlAs superlattices are estimated from the experimental data.Comment: 3 PostScript figure

Transformation and analysis of tobacco plant var Petit havana with T-urf13 gene under anther-specific TA29 promoter

T-urf13, a well-documented cms-associated gene from maize, has been shown to render methomyl sensitivity to heterologous systems like rice, yeast and bacteria when expressed constitutively. Since these transgenic plants were fertile, it was hypothesized that T-urf13 gene if expressed in anthers may result in male sterility that could be used for hybrid seed production. Hence, this work was aimed at analysing whether T-urf13 gene when expressed in anthers can result in male sterile plants or requires methomyl treatment to cause male sterility (controllable). This is the first report of transformation of tobacco with T-urf13 gene under anther-specific promoter (TA29) with or without mitochondrial targeting sequence. Most of the transgenic plants obtained were fertile; this was surprising as many male sterile plants were expected as T-urf13 gene is a cms associated gene. Our results suggest that it may not be possible to obtain male sterility by expressing URF13 in the anther by itself or by methomyl application