Das Problem der verantworteten Therapieentscheidung in der Neonatologie

Definition of the problem: Physicians and nurses who work in neonatology—as in intensive care at all—are often forced to decide whether to stop or to continue with the treatment of a severely ill patient. The literature provides several decision making instruments, which are meant to help and to rationalize such decisions. Method and conclusion: Two of these instruments (“Schema zur ethischen Urteilsbildung nach dem Muster der aristotelischen Ethik”, Honnefelder 1994; “Nimwegener Methode für ethische Fallbesprechung”, Gordijn 1998) were tested by retrospectively examining two cases of our NICU. Results of our study show that the use of a decision making instrument is basically helpful. But the above mentioned instruments showed also shortcomings when used in the framework of neonatology. Therefore we developed the “Kölner Arbeitsbogen zur ethischen Entscheidungsfindung in der Neonatologie”, which is adapted to the specific needs of neonatology.     

Opposing Effects of D? and D? Receptor Activation on Odor Discrimination Learning.

Dopaminergic modulation of cortical activity has been implicated in the formation of reward associations. There is abundant evidence for dopaminergic effects on olfactory processing. Using an olfactory discrimination task, the authors show that D? and D? dopamine receptors can regulate rats' olfactory discrimination capacities and that the effects of receptor activation functionally oppose one another. Injection of either the D? agonist SKF 38393 (10 mg/kg) or the D? antagonist spiperone (0.62 mg/kg) facilitated the discrimination of similar odorants but had no effect on the discrimination of dissimilar odorants, whereas both the D, antagonist SCH 23390 (0.025 mg/kg) and the D? agonist quinpirole (0.2 mg/kg) significantly impaired rats' ability to discriminate similar and dissimilar odorants. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluation of a new computer-assisted surgical planning and navigation system based on two-dimensional fluoroscopy for insertion of a proximal femoral nail: an experimental study

Pertrochanteric femoral fractures are common and intramedullary nailing is an accepted method for their surgical treatment. Accurate placement of the implant is essential to ensure fixation. The conventional technique can require multiple guide wire passes, and relies heavily on fluoroscopy. A computer-assisted planning and navigation system based on two-dimensional fluoroscopy for guide wire placement in the femoral neck has been developed, in order to perform intramedullary pertrochanteric fracture fixation using the proximal femoral nail (PFNA). The planning process was supported by a 'zero-dose C-arm navigation' system. The PFNA was inserted into 12, intact, femoral sawbones guided by the computer-based navigation, and into 12, intact, femoral sawbones using a conventional fluoroscopic-assisted technique. Guide wire and subsequent blade placement in the femoral neck was evaluated. The computer-assisted technique achieved a significant decrease in the number of required fluoroscopic images and in the number of guide wire passes. The obtained average blade placement accuracy in the femoral neck was equivalent to the conventional technique. The operation time was significantly longer in the navigation-assisted group. The addition of computer-assisted planning and surgical guidance to the intramedullary nailing of pertrochanteric femoral fractures offers a number of clinical benefits based on the results of this sawbone study. Further studies including fractured sawbones and cadaver models with extension of the navigation process to all steps of PFNA introduction and with the goal of reducing operation time are indispensable before integration of this navigation system into clinical practice.     

Neuropsychological function in adults with attention-deficit hyperactivity disorder

Pacemaker therapy in patients with atrial fibrillation means the best current pacemaker therapy for patients with bradycardias with the aim to avoid the onset of atrial fibrillation and to establish DDD pacing despite of a history of atrial tachyarrhythmias. The newer application of pacing is the suppression of atrial arrhythmias in patients with medical refractory atrial tachyarrhythmias. Patients with slow ventricular rates and permanent atrial fibrillation should receive a VVI-pacemaker, if the bradycardias causes syncope, dizziness or a decrease of their exercise tolerance. In case of chronotropic incompetence the pacemaker should provide rate responsive pacing. Patients with sick sinus syndrome should receive an atrial (AAI) or dual-chamber (DDD) pacemaker, because patients with these in contrast to VVI-pacemakers develop less often atrial fibrillation and subsequent complications such as atrial thromboembolism. A dual-chamber or VDD-pacemaker--the latter connected to a VDD-single-lead--is indicated in patients with advanced AV-block. Atrial fibrillation occurs in 3 to 6% of the patients with no history of arrythmia and is, if pacemakers have no automatic mode switch, an often reason to program the devices to the VVI-pacing mode. Nowadays, most DDD(R)-pacemakers provide an automatic mode switch: During an atrial tachycardia the pacemaker switches to a VVI/VVIR mode and restores the initial DDD(R)-pacing mode with termination of the arrhythmia. In respect to the newer applications, one approach to prevent atrial tachyarrhythmias is permanent atrial pacing. As lower pacing rates of 80 to 90 ppm are usually needed and many patients hardly tolerate these pacing rates, new algorithms are under clinical investigation. Another approach is the simultaneous depolarization of the right and left atrium. Biatrial pacing is performed with one lead in the high right atrium and another lead in the coronary sinus. Another solution is bifocal atrial pacing with leads placed in the high right atrium and in the coronary sinus ostium. One effect of the new pacing techniques is to shorten interatrial conduction times. Therefore, biatrial pacing has become a therapy to prevent atrial arrhythmias deriving from delayed interatrial conduction times. As atrial reentry circuits seem to be important in atrial fibrillation, multisite atrial pacing is also performed in patients with medical refractory paroxysmal atrial fibrillation. Preliminary results suggest a more effective prevention of atrial fibrillation; nevertheless, these techniques should be still restricted to patients enrolled in clinical studies.     

Engineering metal-impurity nanodefects for low-cost solar cells

As the demand for high-quality solar-cell feedstock exceeds supply and drives prices upwards, cheaper but dirtier alternative feedstock materials are being developed. Successful use of these alternative feedstocks requires that one rigorously control the deleterious effects of the more abundant metallic impurities. In this study, we demonstrate how metal nanodefect engineering can be used to reduce the electrical activity of metallic impurities, resulting in dramatic enhancements of performance even in heavily contaminated solar-cell material. Highly sensitive synchrotron-based measurements directly confirm that the spatial and size distributions of metal nanodefects regulate the minority-carrier diffusion length, a key parameter for determining the actual performance of solar-cell devices. By engineering the distributions of metal-impurity nanodefects in a controlled fashion, the minority-carrier diffusion length can be increased by up to a factor of four, indicating that the use of lower-quality feedstocks with proper controls may be a viable alternative to producing cost-effective solar cells.     

An Adaptive Role for DNA Double-Strand Breaks in Hippocampus-Dependent Learning and Memory

DNA double-strand breaks (DSBs), classified as the most harmful type of DNA damage based on the complexity of repair, lead to apoptosis or tumorigenesis. In aging, DNA damage increases and DNA repair decreases. This is exacerbated in disease, as post-mortem tissue from patients diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) show increased DSBs. A novel role for DSBs in immediate early gene (IEG) expression, learning, and memory has been suggested. Inducing neuronal activity leads to increases in DSBs and upregulation of IEGs, while increasing DSBs and inhibiting DSB repair impairs long-term memory and alters IEG expression. Consistent with this pattern, mice carrying dominant AD mutations have increased baseline DSBs, and impaired DSB repair is observed. These data suggest an adaptive role for DSBs in the central nervous system and dysregulation of DSBs and/or repair might drive age-related cognitive decline (ACD), MCI, and AD. In this review, we discuss the adaptive role of DSBs in hippocampus-dependent learning, memory, and IEG expression. We summarize IEGs, the history of DSBs, and DSBs in synaptic plasticity, aging, and AD. DSBs likely have adaptive functions in the brain, and even subtle alterations in their formation and repair could alter IEGs, learning, and memory.     

Protein–Protein Interaction Prediction for Targeted Protein Degradation

Protein–protein interactions (PPIs) play a fundamental role in various biological functions; thus, detecting PPI sites is essential for understanding diseases and developing new drugs. PPI prediction is of particular relevance for the development of drugs employing targeted protein degradation, as their efficacy relies on the formation of a stable ternary complex involving two proteins. However, experimental methods to detect PPI sites are both costly and time-intensive. In recent years, machine learning-based methods have been developed as screening tools. While they are computationally more efficient than traditional docking methods and thus allow rapid execution, these tools have so far primarily been based on sequence information, and they are therefore limited in their ability to address spatial requirements. In addition, they have to date not been applied to targeted protein degradation. Here, we present a new deep learning architecture based on the concept of graph representation learning that can predict interaction sites and interactions of proteins based on their surface representations. We demonstrate that our model reaches state-of-the-art performance using AUROC scores on the established MaSIF dataset. We furthermore introduce a new dataset with more diverse protein interactions and show that our model generalizes well to this new data. These generalization capabilities allow our model to predict the PPIs relevant for targeted protein degradation, which we show by demonstrating the high accuracy of our model for PPI prediction on the available ternary complex data. Our results suggest that PPI prediction models can be a valuable tool for screening protein pairs while developing new drugs for targeted protein degradation.