The role of urodynamics in the evaluation of voiding dysfunction in men after cerebrovascular accident

PURPOSE: The etiology of voiding dysfunction was determined in men after a cerebrovascular accident who were at risk for obstructive uropathy to evaluate whether the cause of voiding dysfunction could be predicted by the type (obstructive or irritative) or onset of symptoms. MATERIALS AND METHODS: We evaluated 38 men with complaints of voiding dysfunction following a cerebrovascular accident. All patients were of the age when bladder outlet obstruction secondary to benign prostatic hyperplasia would otherwise be prevalent. After a comprehensive history and physical examination, all patients underwent multichannel urodynamic studies at a medium fill rate (20 to 50 ml. per minute). Findings were classified by the Abrams-Griffiths nomogram as obstruction, no obstruction or equivocal. RESULTS: Mean patient age was 70 years (range 54 to 87). Patients were grouped according to the presenting voiding complaints (purely irritative in 42%, purely obstructive in 34% or mixed in 24%). In 34 patients (89%) the onset of symptoms paralleled the occurrence of the cerebrovascular accident. Detrusor hyperreflexia was noted in 82% of the patients. There was no statistically significant difference in the occurrence of detrusor hyperreflexia among the 3 symptom groups (Fisher's exact test). Pressure-flow analysis clearly showed obstruction in 24 patients (63%), no obstruction in 9 (24%) and equivocal results in 5 (13%) according to the nomogram. There was no statistically significant difference in the incidence of obstruction among the 3 symptom groups (Fisher's exact test). CONCLUSIONS: Presenting symptoms did not predict the urodynamic findings of bladder outlet obstruction or detrusor hyperreflexia. The significant incidence of onset of symptoms after stroke suggests that the cerebrovascular accident induced voiding dysfunction in the face of preexisting bladder outlet obstruction may exacerbate the symptoms of the latter condition or vice versa.     

Fast full‐color reflective display via photoluminescent enhancement

Reflective displays are advantageous in applications requiring low power or daylight readability. However, there are no low‐cost reflective technologies capable of displaying bright colors. By employing photoluminescence to more efficiently use ambient light, we created a prototype display that provides bright, full color in a simple, low‐cost architecture. This prototype includes a novel electrokinetic shutter, a layer that incorporates patterned luminescent red, green, and blue sub‐pixel elements, and a novel optical out‐coupling scheme. The luminescent elements convert otherwise‐wasted portions of the incident spectrum to light in the desired color band, resulting in improved color saturation and lightness. This prototype provides a color gamut that is superior to competing reflective display technologies that utilize color filters in single‐layer side‐by‐side sub‐pixel architectures. The current prototype is capable of switching in <0.5 s; future displays based on an alternative electro‐optic shutter technology should achieve video rate operation. A transflective version of this technology has also been prototyped. The transflective version utilizes its backlight with a power efficiency that is at least three times that of a conventional liquid crystal display. These photoluminescence‐based technologies enable a host of applications ranging from low‐power mobile products and retail pricing signage to daylight readable signage for outdoor advertising segments.     

Five-year experience with setup and implementation of an integrated database system for clinical documentation and research

In radiation oncology, where treatment concepts are elaborated in interdisciplinary collaborations, handling distributed, large heterogeneous amounts of data efficiently is very important, yet challenging, for an optimal treatment of the patient as well as for research itself. This becomes a strong focus, as we step into the era of modern personalized medicine, relying on various quantitative data information, thus involving the active contribution of multiple medical specialties. Hence, combining patient data from all involved information systems is inevitable for analyses. Therefore, we introduced a documentation and data management system integrated in the clinical environment for electronic data capture. We discuss our concept and five-year experience of a precise electronic documentation system, with special focus on the challenges we encountered. We specify how such a system can be designed and implemented to plan, tailor and conduct (multicenter) clinical trials, ultimately reaching the best clinical performance, and enhancing interdisciplinary and clinical research.     

Identification of microglial signal transduction pathways mediating a neurotoxic response to amyloidogenic fragments of beta-amyloid and prion proteins

Microglial interaction with amyloid fibrils in the brains of Alzheimer's and prion disease patients results in the inflammatory activation of these cells. We observed that primary microglial cultures and the THP-1 monocytic cell line are stimulated by fibrillar beta-amyloid and prion peptides to activate identical tyrosine kinase-dependent inflammatory signal transduction cascades. The tyrosine kinases Lyn and Syk are activated by the fibrillar peptides and initiate a signaling cascade resulting in a transient release of intracellular calcium that results in the activation of classical PKC and the recently described calcium-sensitive tyrosine kinase PYK2. Activation of the MAP kinases ERK1 and ERK2 follows as a subsequent downstream signaling event. We demonstrate that PYK2 is positioned downstream of Lyn, Syk, and PKC. PKC is a necessary intermediate required for ERK activation. Importantly, the signaling response elicited by beta-amyloid and prion fibrils leads to the production of neurotoxic products. We have demonstrated in a tissue culture model that conditioned media from beta-amyloid- and prion-stimulated microglia or from THP-1 monocytes are neurotoxic to mouse cortical neurons. This toxicity can be ameliorated by treating THP-1 cells with specific enzyme inhibitors that target various components of the signal transduction pathway linked to the inflammatory responses.     

Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry

Artificial neural networks are applied to the automated classification of trichloroethylene (TCE) signatures from passive Fourier transform infrared remote sensing interferogram data. Through the use of three data collection methods, a combination of laboratory and field data is acquired that allows the methodology to be evaluated under a variety of infrared background conditions and in the presence of potentially interfering compounds such as sulfur hexafluoride, methyl ethyl ketone, acetone, carbon tetrachloride, and ammonia. To maximize the computational efficiency of the network optimization, experimental design techniques are employed to develop a training protocol for the network that takes into account the relationships among five variables that are related either to the network architecture or to the training process. This protocol is implemented for the case of a back-propagation neural network (BNN) and is used to develop an optimized network for the detection of TCE. The classification performance of the network is assessed by comparing both TCE detection capabilities and false detection rates to similar classification results obtained with the technique of piecewise linear discriminant analysis (PLDA). When applied to prediction data withheld from the optimization of both the BNN and PLDA algorithms, the BNN method is observed to outperform PLDA overall, with TCE detection rates in excess of 99% and false detection rates less than 0.5%.     

Calibration transfer algorithm for automated qualitative analysis by passive Fourier transform infrared spectrometry

The automated qualitative analysis of passive Fourier transform infrared (FT-IR) remote sensing data is made difficult by the presence in the data of background and instrument-specific variation. For data collected with a single instrument, variation in the data arises from changes in the infrared background radiance, changes in the atmospheric composition within the field-of-view of the spectrometer, and changes in the instrument response function arising from temperature variation in the spectrometer. When more than one spectrometer is used, the variation in detector responses and phase signatures between instruments serves to complicate further the task of implementing an automated processing algorithm for detecting the signature of a target compound. In this work, a combination of signal processing and pattern recognition methodology is applied directly to the interferogram data collected by the FT-IR spectrometer to implement an automated compound detection procedure that is independent of background and instrument-specific variation. The key to this algorithm is the use of highly attenuating digital filters to isolate in the interferogram the frequencies associated with an analyte absorption or emission band while suppressing information at other frequencies. For the test compounds, acetone and sulfur hexafluoride, it is demonstrated that when this digital filtering procedure is coupled with either piecewise linear discriminant analysis or a back-propagation neural network, an automated detection algorithm can be developed with data from a primary instrument and then subsequently used to predict the presence of analyte signatures in data collected with a secondary spectrometer. Correct classification rates in excess of 92% are obtained for both compounds when the algorithm is applied to data collected with the secondary instrument.     

Effects of increasing levels of grain supplementation on rumen environment and lactation performance of dairy cows grazing grass-legume pasture

The impact of supplemental energy on nutrient utilization, fiber digestion, rumen fermentation, and lactation performance was evaluated in dairy cows grazing pastures composed of brome, orchardgrass, red clover, and alfalfa. Three amounts [0, 5, and 10 kg dry matter (DM)/d] of ground dry shelled corn-based concentrate were supplemented to nine rumen cannulated Holstein cows in a 3 x 3 Latin square replicated three times. Cows were on average 84+/-13 d in milk and producing 41.6+/-5.9 kg of milk/d at the beginning of the study. An increase in amounts of concentrate in the diets was associated with an increase in milk production, solids-corrected milk, and concentrations of milk protein and SNF. Milk fat percentage and milk urea nitrogen concentration decreased linearly with supplementation. Milk production and protein percentage were 21.8, 26.8, and 30.4 kg/d, and 2.85, 2.95, and 3.05% for the increasing levels of concentrate, respectively. Intake and digestibility of DM and organic matter (OM) increased as grain supplementation increased. Ruminal pH and total volatile fatty acid concentration (VFA) were not affected by supplementation or the amount of concentrate. Ruminal ammonia concentration was reduced by supplementation, presumably due to a decrease in N intake and greater use of ammonia-N for rumen microbial protein synthesis. Rumen fermentation varied throughout the day, with lower mean pH and higher VFA concentrations at night. Supplementation increased total OM intake, decreased forage OM intake, and increased the proportion of OM that was digested in the intestines. Total DM intake by grazing dairy cows can be increased using ground dry shelled corn-based concentrate without causing negative effects on forage digestion.     

Predicting the effect of proteolysis on ruminal crude protein degradation of legume and grass silages using near-infrared reflectance spectroscopy

Two studies were conducted to assess whether routine applications of near infrared reflectance spectroscopy could predict the effects of silage proteolysis on ruminal crude protein (CP) degradation of legume and grass silages. A preliminary study was conducted to assess the effect of laboratory drying method on ruminal CP degradation of silages. Thirty legume and grass silages were freeze-, oven-, or microwave-dried and incubated in situ in the ventral rumen of three ruminally cannulated cows for 24 h. Freeze-drying was considered least likely to alter ruminal CP degradation of the silages; therefore, oven- and microwave-drying were compared using first-order regression with freeze-drying. Oven-drying for 48 h at 55 degrees C compared favorably (R2 = 0.84) with freeze-drying. Microwave-drying resulted in a large bias (2.84 g/10(-1) kg of CP) and was poorly related (R2 = 0.48) to freeze-drying. In a second study, alfalfa and timothy were cut at three maturities and allowed to wilt for 0, 10, 24, 32, 48, and 54 h. Forages were ensiled in triplicate cylindrical mini silos and allowed to ferment for 120 d. After fermentation, silages were oven-dried, ground, and scanned on a near-infrared reflectance spectrophotometer. Duplicate, dried, 2-mm ground silage samples were incubated in the ventral rumen of three ruminally cannulated cows for 24 h. Forage species, maturity, and wilting time significantly affected 24-h ruminal CP degradation of the silages. Near-infrared reflectance spectroscopy accurately predicted (R2 = 0.91) 24-h ruminal CP degradation of silages. Data suggest near-infrared reflectance spectroscopy can accurately assess the effects of forage species, maturity, and wilting time (proteolysis) on 24-h ruminal CP degradation of legume and grass silages.     

A comparative study of activity and dual sensor: activity and minute ventilation pacing responses to ascending and descending stairs

Previous studies with activity-based rate adaptive pacemakers have shown a somewhat paradoxical response when comparing ascending stairs to descending stairs. The objective of this investigation was to measure dual-sensor rate response provided by activity and minute ventilation (MV) compared with activity alone, and with a control group, during ascending and descending stairs. For dual sensor mode, measured mean peak pacing rate with 72 (92) steps per minute was 111 +/- 13 beats/min (124 +/- 14 beats/min) ascending stairs and 81 +/- 7 beats/min (97 +/- 13 beats/min) for descending. For activity mode alone, mean peak pacing rate was 90 +/- 12 beats/min (108 +/- 19 beats/min) ascending stairs and 97 +/- 12 beats/min (123 +/- 17 beats/min) descending. The mean peak control group heart rate ascending stairs for a step rate of 72 (92) steps/min were 116 +/- 11 beats/min (127 +/- 14 beats/min) ascending stairs and for descending 89 +/- 12 beats/min (95 +/- 11 beats/min). While for dual sensor controlled pacing there was a significant difference for ascending and descending stairs at both step rates, there was no difference between going upstairs and downstairs for activity mode alone. Rates with dual sensor did not significantly differ from respective rates of the control group. The mean correlation coefficient between MV and paced rate was 0.85. Pacing heart rates delivered by the dual sensor mode were appropriate for ascending and descending stairs. In contrast to activity mode alone, the peak heart rates for dual sensor mode are higher during ascending than during descending stairs.