scholarly journals The use of high–sensitivity sapphire cells in high pressure NMR spectroscopy and its application to proteins

2004 ◽  
Vol 18 (2) ◽  
pp. 271-278 ◽  
Author(s):  
W. Kremer ◽  
M. R. Arnold ◽  
N. Kachel ◽  
H. R. Kalbitzer
Keyword(s):  
High Pressure ◽  
Nmr Spectroscopy ◽  
Prion Protein ◽  
Pressure Dependence ◽  
Structural Changes ◽  
Chemical Shifts ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Human Prion Protein ◽  
Noise Ratio

The application of high pressure in bioscience and biotechnology has become an intriguing field in un/refolding and misfolding processes of proteins. NMR spectroscopy is the only generally applicable method to monitor pressure–induced structural changes at the atomic level in solution. Up to now the application of most of the multidimensional NMR experiments is impossible due to the restricted volume of the high pressure glass cells which causes a poor signal–to–noise ratio. Here we present high strength single crystal sapphire cells which double the signal–to–noise ratio. This increased signal–to–noise ratio is necessary to perform, for example, phophorus NMR spectroscopy under variable pressures. To understand the effect of pressure on proteins, we need to know the pressure dependence of1H chemical shifts in random coil model tetrapeptides. The results allow distinguishing structural changes from the pressure dependence of the chemical shifts. In addition, the influence of pressure on the buffer system was investigated. Since high pressure was shown to populate intermediate amyloidogenic states of proteins the investigation of pressure effects on proteins involved in protein conformational disorders like Alzheimer's Disease (AD) and Transmissible Spongiform Encephalopathies (TSE) is of keen interest.1H–15N–TROSY–spectra were acquired to study the effects of pressure and temperature on chemical shifts and signal volumes of the human prion protein. These measurements show identical pressure sensitivity ofhuPrP(23–230) andhuPrP(121–230). First results suggest a folding intermediate for the human prion protein which can be populated by high hydrostatic pressure.

Novel Electron Tomographic Methods to Study the Morphology of Keratin Filament Networks

2010 ◽  
Vol 16 (4) ◽  
pp. 462-471 ◽  
Author(s):  
Michaela Sailer ◽  
Katharina Höhn ◽  
Sebastian Lück ◽  
Volker Schmidt ◽  
Michael Beil ◽  
...  
Keyword(s):  
High Pressure ◽  
Low Voltage ◽  
Signal To Noise Ratio ◽  
3D Structure ◽  
Signal To Noise ◽  
Freeze Dried ◽  
Keratin Filaments ◽  
Keratin Filament ◽  
Noise Ratio ◽  
Filament Network

AbstractThe three-dimensional (3D) keratin filament network of pancreatic carcinoma cells was investigated with different electron microscopical approaches. Semithin sections of high-pressure frozen and freeze substituted cells were analyzed with scanning transmission electron microscope (STEM) tomography. Preservation of subcellular structures was excellent, and keratin filaments could be observed; however, it was impossible to three-dimensionally track the individual filaments. To obtain a better signal-to-noise ratio in transmission mode, we observed ultrathin sections of high-pressure frozen and freeze substituted samples with low-voltage (30 kV) STEM. Contrast was improved compared to 300 kV, and individual filaments could be observed. The filament network of samples prepared by detergent extraction was imaged by high-resolution scanning electron microscopy (SEM) with very good signal-to-noise ratio using the secondary electron signal and the 3D structure could be elucidated by SEM tomography. In freeze-dried samples it was possible to discern between keratin filaments and actin filaments because the helical arrangement of actin subunits in the F-actin could be resolved. When comparing the network structures of the differently prepared samples, we found no obvious differences in filament length and branching, indicating that the intermediate filament network is less susceptible to preparation artifacts than the actin network.

NMR spectroscopy threshold signal-to-noise ratio

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Petar Kolar ◽  
Lovro Blažok ◽  
Dario Bojanjac
Keyword(s):  
Nmr Spectroscopy ◽  
Communication Channel ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Standard Procedure ◽  
Threshold Value ◽  
Signal To Noise ◽  
Online Questionnaire ◽  
Spectroscopy System ◽  
Noise Ratio

Abstract Ever since noise was spotted and proven to cause problems for the transmission and detection of information through a communication channel, a standard procedure in the process of characterizing a detection system of the communication channel is to determine the level of the lowest detectable signal. In signal processing, this is usually done by determining the so-called threshold signal-to-noise ratio (SNR). This determination is especially important for the communication channels and systems that constantly operate with low-level signals. A good example of such a system is definitely the NMR spectroscopy system. However, to the authors’ knowledge, the threshold SNR value of NMR spectroscopy systems has not been determined yet. That is why the experts in the field of NMR spectroscopy were asked to assess, using an online questionnaire, which SNR level they considered to be the NMR threshold SNR level. Afterwards, the threshold value was calculated from the obtained data. Finally, it was compared to the existing rule of thumb and thus, a conclusion about its legitimacy was made. The described questionnaire is still available online (https://forms.gle/Y9hyDZ1v1iJoEbk27). This enables everyone to form their own opinion about the threshold SNR level, which the authors encourage the readers to do.

Localized NMR Spectroscopy with a 1.5 T Whole- Body Imager Using CODEX

1991 ◽  
Vol 46 (5) ◽  
pp. 401-404 ◽  
Author(s):  
Wulf-Ingo Jung ◽  
Otto Lutz ◽  
Markus Pfeffer
Keyword(s):  
Bone Marrow ◽  
Nmr Spectroscopy ◽  
Signal To Noise Ratio ◽  
Whole Body ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Good Signal

AbstractWith a whole-body NMR imager working at 1.5 T localized 1H and 31P spectra were obtained using the CODEX sequence. Examples are presented: With ethanol 'H spectra the resolution, stability, and sensitivity are documented. Human in vivo investigations of the yellow bone marrow of (13 mm)3 volume elements show well resolved spectra with a good signal-to-noise ratio. An example for 31P spectroscopy is also given

Miniature diamond anvils for X-ray Raman scattering spectroscopy experiments at high pressure

2017 ◽  
Vol 24 (1) ◽  
pp. 276-282 ◽  
Author(s):  
Sylvain Petitgirard ◽  
Georg Spiekermann ◽  
Christopher Weis ◽  
Christoph Sahle ◽  
Christian Sternemann ◽  
...  
Keyword(s):  
High Pressure ◽  
Raman Scattering ◽  
Signal To Noise Ratio ◽  
High Energy ◽  
X Rays ◽  
Signal To Noise ◽  
X Ray ◽  
Custom Made ◽  
Diamond Anvils ◽  
Noise Ratio

X-ray Raman scattering (XRS) spectroscopy is an inelastic scattering method that uses hard X-rays of the order of 10 keV to measure energy-loss spectra at absorption edges of light elements (Si, Mg, Oetc.), with an energy resolution below 1 eV. The high-energy X-rays employed with this technique can penetrate thick or dense sample containers such as the diamond anvils employed in high-pressure cells. Here, we describe the use of custom-made conical miniature diamond anvils of less than 500 µm thickness which allow pressure generation of up to 70 GPa. This set-up overcomes the limitations of the XRS technique in very high-pressure measurements (>10 GPa) by drastically improving the signal-to-noise ratio. The conical shape of the base of the diamonds gives a 70° opening angle, enabling measurements in both low- and high-angle scattering geometry. This reduction of the diamond thickness to one-third of the classical diamond anvils considerably lowers the attenuation of the incoming and the scattered beams and thus enhances the signal-to-noise ratio significantly. A further improvement of the signal-to-background ratio is obtained by a recess of ∼20 µm that is milled in the culet of the miniature anvils. This recess increases the sample scattering volume by a factor of three at a pressure of 60 GPa. Examples of X-ray Raman spectra collected at the OK-edge and SiL-edge in SiO2glass at high pressures up to 47 GPa demonstrate the significant improvement and potential for spectroscopic studies of low-Zelements at high pressure.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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