Myosin conformational states determined by single fluorophore polarization

Muscle contraction is powered by the interaction of the molecular motor myosin with actin. With new techniques for single molecule manipulation and fluorescence detection, it is now possible to correlate, within the same molecule and in real time, conformational states and mechanical function of myosin. A spot-confocal microscope, capable of detecting single fluorophore polarization, was developed to measure orientational states in the smooth muscle myosin light chain domain during the process of motion generation. Fluorescently labeled turkey gizzard smooth muscle myosin was prepared by removal of endogenous regulatory light chain and re-addition of the light chain labeled at cysteine-108 with the 6-isomer of iodoacetamidotetramethylrhodamine (6-IATR). Single myosin molecule fluorescence polarization data, obtained in a motility assay, provide direct evidence that the myosin light chain domain adopts at least two orientational states during the cyclic interaction of myosin with actin, a randomly disordered state, most likely associated with myosin whereas weakly bound to actin, and an ordered state in which the light chain domain adopts a finite angular orientation whereas strongly bound after the powerstroke.     

Gain equalization of EDFA's with Bragg gratings

Flat-gain amplifiers are needed to ensure proper amplification of every channel in wavelength-division-multiplexed communication systems. Such amplifiers can be realized by combining a precisely tailored filter with an erbium-doped fiber amplifier (EDFA). In this letter, we show that Bragg gratings can lead to accurate EDFA gain equalization. Reflection and transmission gratings have been used to demonstrate gain equalization over 32 nm with excursion inferior to ±0.1 and ±0.3 dB, respectively. A maximum 0.04-dB noise-figure penalty results from this process. By extension, Bragg gratings could also equalize the gain of any arbitrary gain profile, over any arbitrary bandwidth     

Proteases involved in mammary tissue damage during endotoxin-induced mastitis in dairy cows

During and after diapedesis, milk polymorphonu-clear neutrophils (PMN) release many proteases that have the potential of degrading extracellular matrix proteins and milk proteins. However, the kinetics of milk proteolysis during inflammation and the underlying mechanisms are poorly defined. The enzymes involved in bovine mammary tissue destruction were investigated in this study using an endotoxin-induced mastitis model. Using zymography techniques, the proteolytic activity of milk and mammary tissue during mastitis was examined. Mastitic milk produced 6 caseolysis bands, 4 of which differed from the ones produced by plasmin. Peak proteolytic activity, bovine serum albumin contents, and mammary tissue damage occurred between 6 and 12 h postchallenge. Mastitic milk proteases hydrolyzed casein, gelatin, collagen, hemoglobin, mammary gland membrane proteins, and lactoferrin. These results confirm that mastitic milk proteases have a broad spectrum of activity. The hydrolytic activity of mastitic milk was partially inhibited by aprotinin, EDTA, 1,10-phenanthroline, leupeptin, and pefabloc. When cocultured with normal mammary tissue, mastitic milk, but not normal milk, caused mammary tissue degradation. In situ zymography of mammary gland showed increased proteolytic activity in mastitic tissue compared with normal tissue. The similarity of zymograms of mastitic milk, blood PMN, milk somatic cells, and PMN strongly suggests that proteases in mastitic milk mainly originate from milk PMN. These results suggest that proteases released by PMN are actively involved in udder tissue damage during mastitis.     

Tracing Listeria monocytogenes isolates from cold-smoked salmon and its processing environment in Iceland using pulsed-field gel electrophoresis

Listeria spp. and Listeria monocytogenes contamination of cold-smoked salmon (n=125) and its processing environment (n=522) were evaluated during surveys conducted in 1997-1998 and 2001 as well as in samples of final products analysed in 2001. The overall frequencies of Listeria spp. and L. monocytogenes in samples from all sources were 15.1% and 11.3%, respectively, but the incidence of L. monocytogenes in cold-smoked salmon final products was only 4%. A total of 201 L. monocytogenes isolates were characterised by Pulsed-Field Gel Electrophoresis (PFGE) in order to trace L. monocytogenes contamination in the processing plants. The combination of AscI and ApaI macrorestriction patterns yielded 24 different pulsotypes in 6 plants. One pulsotype observed by AscI restriction digestion comprised 148 of the 167 typed isolates from two processing plants. Two other pulsotypes predominated in samples from raw material, processing environments and final products. The results indicate that raw material, floors, and drains are potential sources of the L. monocytogenes found on cold-smoked salmon products. This highlights the need to readdress the design and cleaning of processing plants and equipment, and staff behavior. Hindering the introduction into and spread of the organism through the processing environment is necessary to avoid jeopardizing safety of the final product.     

A nonstatistical approach to estimating confidence intervals aboutmodel parameters: application to respiratory mechanics

Estimates of parameters obtained by fitting models to physiologic data are of little use unless accompanied by confidence intervals. The standard methods for estimating confidence intervals are statistical, and make the assumption that the fitted model accounts for all the deterministic variation in the data while the residuals between the fitted model and the data reflect only stochastic noise. In practice, this is frequently not the case, as one often finds the residuals to be systematically distributed about zero. In this paper, we develop an approach for assessing confidence in a parameter estimate when the order of the model is clearly less than that of the system being modeled. Our approach does not require a parameter to have a single value located within a region of confidence. Instead, we let the parameter value vary over the data set in such a way as to provide a good fit to the entire data set. We apply our approach to the estimation of the resistance of the respiratory system in which a simple model is fitted to measurements of tracheal pressure and flow by recursive multiple linear regression. The values of resistance required to achieve a good fit are represented as a modified histogram in which the contribution of a particular resistance value to the histogram is weighted by the amount of information used in its determination. Our approach provides parameter frequency distribution functions that convey the degree of confidence one may have in the parameter, while not being based on erroneous statistical assumptions.     

Influence of storage temperature on microbial spoilage characteristics of haddock fillets (Melanogrammus aeglefinus) evaluated by multivariate quality prediction

The proliferation of specific spoilage organisms (SSO) and quality changes were evaluated in haddock fillets stored in styrofoam boxes at 0, 7 and 15 degrees C and under temperature fluctuations. A rapid electronic nose technique was used to monitor different classes of compounds, representing microbial metabolites that were characteristic for the onset of spoilage odors. Photobacterium phosphoreum predominated among the spoilage bacteria and high levels of TVB-N were observed at sensory rejection. Pseudomonas spp. appeared to be responsible for the development of sweet, fruity spoilage odors in haddock fillets coinciding with increasing response of the electronic nose CO sensor. H(2)S-producing bacteria, most likely Shewanella putrefaciens, were associated with the H(2)S sensor's response at abusive temperature conditions. Partial Least Squares Regression (PLSR) was used as an explorative tool to provide a better understanding of the spoilage potential of SSOs, by evaluating models based on electronic nose responses and counts of specific spoilage organisms to predict sensory quality (Torry scores). The best prediction of the sensory quality was obtained by PLSR models based on five variables: the electronic nose sensors (CO, NH(3) and H(2)S), pseudomonads counts and a time-temperature variable. Good agreement between the predicted and experimental data indicates that these variables characterize the sensory quality of haddock fillets stored under different temperatures.     

Cardiogenic oscillation phase relationships during single-breath tests performed in microgravity

We studied the phase relationships of the cardiogenic oscillations in the phase III portion of single-breath washouts (SBW) in normal gravity (1 G) and in sustained microgravity (microG). The SBW consisted of a vital capacity inspiration of 5% He-1.25% sulfurhexafluoride-balance O2, preceded at residual volume by a 150-ml Ar bolus. Pairs of gas signals, all of which still showed cardiogenic oscillations, were cross-correlated, and their phase difference was expressed as an angle. Phase relationships between inspired gases (e.g., He) and resident gas (n2) showed no change from 1 G (211 +/- 9 degrees) to microG (163 +/- 7 degrees). Ar bolus and He were unaltered between 1 G (173 +/- 15 degrees) and microG (211 +/- 25 degrees), showing that airway closure in microG remains in regions of high specific ventilation and suggesting that airway closure results from lung regions reaching low regional volume near residual volume. In contrast, CO2 reversed phase with He between 1 G (332 +/- 6 degrees) and microG (263 +/- 27 degrees), strongly suggesting that, in microG, areas of high ventilation are associated with high ventilation-perfusion ratio (VA/Q). This widening of the range of VA/Q in microG may explain previous measurements (G.K. Prisk, A.R. Elliott, H.J.B. Guy, J.M. Kosonen, and J.B. West J. Appl. Physiol. 79: 1290-1298, 1995) of an overall unaltered range of VA/Q in microG, despite more homogeneous distributions of both ventilation and perfusion.     

Ambient Vibration Monitoring of a Highway Bridge Undergoing a Destructive Test

Developing a technique to continuously monitor in-service highway bridges is one of the major research focuses at the Connecticut Department of Transportation and the University of Connecticut. The goal has been to use ambient traffic loading as the force to excite a measurable parameter that is sensitive to overall structural integrity. In this study, the dynamic responses of a full-scale steel-girder highway bridge during the passage of a small truck were measured using a number of sensors that could be reasonably implemented on a network of in-service bridges. Measurements were taken before and during the staged introduction of a simulated crack in one of the main supporting girders. The crack was introduced in five stages until it extended through two-thirds of the depth of the girder. Accelerometers were placed at various locations on each girder. Frequency spectra for each stage of the testing were compared to those recorded before the introduction of the crack to determine which aspects of the spectra were sensitive to the change in stiffness. The results indicate that monitoring the amplitudes at the natural frequencies and the frequency response spectrum using the cross signature assurance criterion can be used as an indicator that significant cracks have developed in a multigirder highway bridge.