Reversal of pretreatment hypotension and control of hemorrhage in trauma patients by a simple device

The injection of a suspension of Walker 256 carcinoma cells into the carotid artery of rats produced a model of hematogenously spread cerebral metastases. Most animals died from massive extracerebral tumors of the head and jaw; brain tumors were present in only one-quarter. External carotid artery ligation prior to tumor inoculation did not increase the incidence of fatal brain tumor. When cyclophosphamide, 15 mg/kg, was injected as a single dose on the fourteenth day after tumor inoculation, most of the extracerebral tumor disappeared. Fifty percent of the animals so treated were cured of tumor, but 90% of the remainder died of large intracerebral tumors. Severe cytopathic changes resulting from cyclophosphamide were present in extracerebral or choroid plexus tumors but were mild or nonexistent in intracerebral tumors. These selective effects of cyclophosphamide suggest that water-soluble agents are less effective against tumor in the brain than against extracerebral tumors despite the fact that metastatic tumor breaks down the blood-brain barrier.     

Robust DNA microarray image analysis

DNA microarrays are an increasingly important tool that allow biologists to gain insight into the function of thousands of genes in a single experiment. Common to all array-based approaches is the necessity to analyze digital images of the scanned DNA array. The ultimate image analysis goal is to automatically quantify every individual array element (spot), providing information about the amount of DNA bound to a spot. Irrespective of the quantification strategy, the preliminary information to extract about a spot includes the mapping between its location in the digital image and its possibly distorted position in the spot array (gridding). We present a gridding approach divided into a spot-amplification step (matched filter), a rotation estimation step (Radon transform), and a grid spanning step. Quantification of the spots is performed by robustly fitting of a parametric model to pixel intensities with the help of M-estimators. The main advantage of parametric spot fitting is its ability to cope with overlapping spots. If the goodness-of-fit is too bad, a semiparametric spot fitting is employed. We show that our approach is superior to simple quantification strategies such as averaging of the pixel intensities. The system was extensively tested on 1740 images resulting from two DNA libraries.Received: 15 June 2001, Accepted: 21 July 2002, Published online: 3 June 2003 Correspondence to: Norbert Brändle     

Separation of plutonium and neptunium species by capillary electrophoresis-inductively coupled plasma-mass spectrometry and application to natural groundwater samples

Capillary electrophoresis (CE) was coupled to ICPMS in order to combine the good performance of this separation technique with the high sensitivity of the ICPMS for the analysis of plutonium and neptunium oxidation states. The combination of a fused-silica capillary with a MicroMist AR 30-I-FM02 nebulizer and a Cinnabar small-volume cyclonic spray chamber yielded the best separation results. With this setup, it was possible to separate a model element mixture containing neptunium (NpO2(+)), uranium (UO2(2+)), lanthanum (La3+), and thorium (Th4+) in 1 M acetic acid. The same conditions were also suitable for the separation of various oxidation states of plutonium and neptunium in different aqueous samples. All separations were obtained within less than 15 min. A detection limit of 50 ppb identical with 2 x 10(-7) M (3-fold standard deviation of a blank) was achieved. To prove the negligible disturbance of the plutonium and neptunium redox equilibria during the CE separations, plutonium and neptunium speciation by CE-ICPMS in acidic solutions was compared with the results of UV/visible absorption spectroscopy and was found to be in good agreement. The CE-ICPMS system was also applied to study the reduction of Pu(VI) in a humic acid-containing groundwater at different pH values.     

Synthesis and self-assembly of colloidal nanoparticles

We describe recent developments in the synthesis of semiconductor nanoparticles, which lead to a substantial improvement of the luminescence quantum efficiency. Concerning a theoretical model for the growth of an ensemble of nanoparticles, the highest quantum efficiencies are achieved in particles that grow under conditions of a rapid exchange of monomers at the particle surface, leading to a smooth surface structure. Selective etching, core-shell formation and doping of nanoparticles are also discussed as fluorescence-enhancing preparative techniques. Examples of self-assembly of almost-uniformly-sized nanoparticles are given, which result in two-dimensional and three-dimensional superlattices, colloidal crystals and crystalline structures built-up from particles of different sizes. Finally, the self-assembled oriented attachment of quasi-spherical ZnO nanoparticles onto single-crystalline nanorods is presented.     

Micropositioning and microscopic observation of individual picoliter-sized containers within SU-8 microchannels

We describe the fabrication and application of a bioanalytical chip, made of SU-8 photoresist, comprising integrated, high aspect-ratio microfluidic channels, suitable to manipulate and investigate vesicles, cell fragments and biological cells. A central micrometer-sized aperture allows electrical particle counting and planar membrane experiments, microfluids allow (sub)micrometer-sized objects to be transported and addressed with different chemicals. Here we show how lipid vesicles are positioned with micrometer precision within the micro-channels by means of pressure and electrophoretic movement. Our approach is suited for controlling and investigating (bio)chemical synthesis and cellular signalling processes in ultrasmall individual vesicles by electro-optical techniques.     

Mumford-Shah model for one-to-one edge matching.

This paper presents a new algorithm based on the Mumford-Shah model for simultaneously detecting the edge features of two images and jointly estimating a consistent set of transformations to match them. Compared to the current asymmetric methods in the literature, this fully symmetric method allows one to determine one-to-one correspondences between the edge features of two images. The entire variational model is realized in a multiscale framework of the finite element approximation. The optimization process is guided by an estimation minimization-type algorithm and an adaptive generalized gradient flow to guarantee a fast and smooth relaxation. The algorithm is tested on T1 and T2 magnetic resonance image data to study the parameter setting. We also present promising results of four applications of the proposed algorithm: interobject monomodal registration, retinal image registration, matching digital photographs of neurosurgery with its volume data, and motion estimation for frame interpolation.     

Monitoring post-tsunami vegetation recovery in Phang-Nga province,Thailand, based on IKONOS imagery and field investigations – a contribution to the analysis of tsunami vulnerability of coastal ecosystems

A major tsunami in December 2004 devastated the coastal ecosystems along the Andaman Sea coast of Thailand. Since intact coastal ecosystems provide many important services for local communities at the Andaman Sea, it is crucial to investigate to what extent (in terms of percentage area and speed) the affected ecosystems were capable of recovering after the tsunami. Field measurements and multi-date IKONOS imagery were used to estimate the recovery and succession patterns of coastal vegetation types in the Phang-Nga province of Thailand, three years after the tsunami. Thus, this study contributes to a holistic understanding of the ecological vulnerability of the coastal area to tsunamis. A zone-based change detection approach is applied by comparing two change detection techniques: the first method involves the calculation of a recovery rate based on multi-temporal TNDVI (transformed normalized difference vegetation index) images (TNDVI approach), whereas the second approach is a combined approach of the change vector analysis (CVA). Although these two methods provide different types of information (quantitative for the TNDVI approach, qualitative for the CVA), they are comparable in terms of results and accuracies. The results reveal that recovery processes vary based on the type of the ecosystem and, furthermore, are strongly influenced by human activities. Grasslands, coconut plantations and the mixed vegetation cover could recover faster than the mangroves and casuarina forests. Among the forest ecosystems, recovery rates of casuarina forests were higher than for mangroves, but the recovery area was smaller. This study also discusses the potential and some limitations and inaccuracies of applying high-resolution optical imagery for assessing vegetation recovery at a local scale.     

Brain-computer communication: motivation, aim, and impact of exploring a virtual apartment.

The step away from a synchronized or cue-based brain-computer interface (BCI) and from laboratory conditions towards real world applications is very important and crucial in BCI research. This work shows that ten naive subjects can be trained in a synchronous paradigm within three sessions to navigate freely through a virtual apartment, whereby at every junction the subjects could decide by their own, how they wanted to explore the virtual environment (VE). This virtual apartment was designed similar to a real world application, with a goal-oriented task, a high mental workload, and a variable decision period for the subject. All subjects were able to perform long and stable motor imagery over a minimum time of 2 s. Using only three electroencephalogram (EEG) channels to analyze these imaginations, we were able to convert them into navigation commands. Additionally, it could be demonstrated that motivation is a very crucial factor in BCI research; motivated subjects perform much better than unmotivated ones.