The Experts below are selected from a list of 186 Experts worldwide ranked by ideXlab platform
Eckart Meese - One of the best experts on this subject based on the ideXlab platform.
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Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing- Remitting Disease from Healthy Controls
PLOS ONE, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Matthias Scheffler, Hans-peter Lenhof, Julia Lange, Hannah Schroers, Klemens Ruprecht, Eckart MeeseAbstract:Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS.
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miRNAs in lung cancer - studying complex fingerprints in patient's blood cells by microarray experiments.
BMC Cancer, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Anke Wendschlag, Frank Wucherpfennig, Matthias Scheffler, Hanno Huwer, Hans-peter Lenhof, Eckart MeeseAbstract:Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.
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miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments
BMC Cancer, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Anke Wendschlag, Frank Wucherpfennig, Matthias Scheffler, Hanno Huwer, Hans-peter Lenhof, Eckart MeeseAbstract:Background Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. Methods We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Results Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Conclusion Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.
E. Rytkönen - One of the best experts on this subject based on the ideXlab platform.
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Noise level and ultrasound spectra during burring
Clinical Oral Investigations, 2002Co-Authors: E. Sorainen, E. RytkönenAbstract:The aim of this study was to evaluate the noise spectra of current dentistry equipment during normal work at the dental clinic and in the laboratory. In the study, noise was measured during the dental treatment of seven patients at a dental clinic and also in the acoustics laboratory, where working noise was simulated by drilling a polyacetal plate. All samples were analyzed in audible and ultrasonic areas in the one-third octave bands of 20–80,000 Hz. The measuring instruments used were B&K 4135 microphones, B&K 2633 preamplifiers, the B&K 2811 multiplexer, and the B&K 2133 Real-Time Analyzer with the ZT 0318 high-frequency expansion unit. In the in situ measurements, the A-weighted sound pressure level was occasionally over 85 dB(A), and the equivalent continuous A-weighted sound pressure level, L_Aeq, was 76 dB(A). The noise level was most powerful in the one-third octave band of 40,000 Hz, where it was 74 dB. In laboratory measurements, the noise levels of the air-turbine and the micromotor hand pieces ( n =16) were also most powerful in the one-third octave band of 40,000 Hz, where they were 80–89 dB. The L_Aeq of the different micromotor handpieces ( n =6) varied between 76 dB(A) and 77 dB(A), and the L_Aeq of the turbine hand pieces ( n =10) varied between 77 dB(A) and 82 dB(A). The noise of the drills is most powerful in the high frequencies, so using hearing protectors, it is possible that speech communication improves because the protectors attenuate high frequencies more than low frequencies. The very light protectors give sufficient protection against the drilling noise.
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High-Frequency Noise in Dentistry
Aiha Journal, 2002Co-Authors: E. Sorainen, E. RytkönenAbstract:Earlier studies have revealed that dentists have higher hearing thresholds than expected. The aim of this study was to evaluate the noise levels of current dentistry equipment under very controlled conditions. This noise study was carried out in the Acoustics Laboratory of Kuopio Regional Institute of Occupational Health, the background noise of which is about 0 dB(A). Working noise was simulated by drilling a polyacetal plate. During drilling and idling, the noise of the hand pieces was measured over a reflecting plane on the hemisphere surface, the radius of which was 0.3 m, and 10 noise samples were picked for each hand piece. The average sound pressure level and the sound power level of the devices were calculated applying the standard ISO 3744. The measurement and analysis were done in the one-third octave bands of 25–80,000 Hz. The measuring instruments used were the B&K 4135 microphones, the B&K 2633 preamplifiers, the B&K 2811 multiplexer, and the B&K 2133 Real-Time Analyzer with the ZT 0318 high-...
R Keith Mobley - One of the best experts on this subject based on the ideXlab platform.
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Chapter 29 – Zoom Analysis
Vibration Fundamentals, 1999Co-Authors: R Keith MobleyAbstract:Publisher Summary Zoom analysis provides the means to separate quickly machine-train components, such as gear sets, from a complex vibration signature. The technique allows the user to select a specific range of vibration frequencies, which the Real-Time Analyzer converts to a high-resolution, narrowband signature. Reducing the number of active channels and lines of resolution, while using zoom analysis, increases the speed and minimizes the data gaps. The frequency span parameter allows the user to select the frequency span for spectrum and octave acquisition and analysis. Real-Time zoom analysis can be performed with no data gaps up to a range of 10 kHz with most microprocessor-based, Real-Time Analyzers. Above this range, pseudo-Real-Time processing occurs, which means that data required to perform the zoom transform are acquired until the extended recorded memory of the Analyzer is full. The center frequency setting is used to set the center frequency for zoom mode operation.
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Chapter 26 – Analysis Setup
Vibration Fundamentals, 1999Co-Authors: R Keith MobleyAbstract:Publisher Summary Analysis mode can be used in conjunction with acquisition mode to view Real-Time data during the data-acquisition sequence. In this way, the user can monitor the vibration characteristics of the machine-train in real time as well as verify the validity of data as they acquired it. The Real-Time analysis (RTA) program, with the acquisition mode, requests specific inputs to define the user-selected analysis parameters used to condition and display the data. The basic set-up required for a microprocessor-based, Real-Time Analyzer includes the parameters—active channels, reference channel(s), block size, overlap, process weighting, and average group. The final set-up function required to use a microprocessor-based, Real-Time Analyzer for analysis is the display format. The display group is used to set up the type and data source for the Analyzer displays. The Windows-based operating system used by most of the instruments permits multiple simultaneous displays in any combination of formats. However the number of active displays has a direct effect on the speed of both data acquisition and display update. Therefore, caution should be used to limit the number of active displays used in order to limit the reduction of Real-Time functionality.
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Chapter 25 – Data Acquisition
Vibration Fundamentals, 1999Co-Authors: R Keith MobleyAbstract:Publisher Summary This chapter provides the basic information needed to acquire accurate Real-Time data. There are two ways to acquire the data needed to perform a real time analysis (RTA): direct acquisition and tape recording. In direct-acquisition mode, the Real-Time Analyzer can be used to acquire a variety of vibration and nonvibration, process system data, which are stored directly in its onboard memory. The advantage of direct acquisition is that monitoring of machine-train or process system operating conditions can occur as the data are acquired. Tape recorded data permits quicker acquisition of data that can be analyzed quickly in parallel, or an in-depth analysis of the machine-train or process condition can be performed at a later date. Two major types of tape recorders are used to acquire vibration and process parameter data: analog and digital. Storing the data on tape ensures that the raw data will be available for complete, comprehensive analysis. Real-Time data collection does not use preprogrammed acquisition routes, therefore, the acquisition route for obtaining each data set is set up and performed manually. The data acquisition practices that are employed include: hardware setup for transducers, cables, and power supplies; channel integrity; test plans; and field notes for channel data, transducer data, gain, and sequence of events.
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Chapter 25 - Data Acquisition
Vibration Fundamentals, 1999Co-Authors: R Keith MobleyAbstract:Publisher Summary This chapter provides the basic information needed to acquire accurate Real-Time data. There are two ways to acquire the data needed to perform a real time analysis (RTA): direct acquisition and tape recording. In direct-acquisition mode, the Real-Time Analyzer can be used to acquire a variety of vibration and nonvibration, process system data, which are stored directly in its onboard memory. The advantage of direct acquisition is that monitoring of machine-train or process system operating conditions can occur as the data are acquired. Tape recorded data permits quicker acquisition of data that can be analyzed quickly in parallel, or an in-depth analysis of the machine-train or process condition can be performed at a later date. Two major types of tape recorders are used to acquire vibration and process parameter data: analog and digital. Storing the data on tape ensures that the raw data will be available for complete, comprehensive analysis. Real-Time data collection does not use preprogrammed acquisition routes, therefore, the acquisition route for obtaining each data set is set up and performed manually. The data acquisition practices that are employed include: hardware setup for transducers, cables, and power supplies; channel integrity; test plans; and field notes for channel data, transducer data, gain, and sequence of events.
Andreas Keller - One of the best experts on this subject based on the ideXlab platform.
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Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing- Remitting Disease from Healthy Controls
PLOS ONE, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Matthias Scheffler, Hans-peter Lenhof, Julia Lange, Hannah Schroers, Klemens Ruprecht, Eckart MeeseAbstract:Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS.
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miRNAs in lung cancer - studying complex fingerprints in patient's blood cells by microarray experiments.
BMC Cancer, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Anke Wendschlag, Frank Wucherpfennig, Matthias Scheffler, Hanno Huwer, Hans-peter Lenhof, Eckart MeeseAbstract:Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.
-
miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments
BMC Cancer, 2009Co-Authors: Andreas Keller, Petra Leidinger, Anne Borries, Anke Wendschlag, Frank Wucherpfennig, Matthias Scheffler, Hanno Huwer, Hans-peter Lenhof, Eckart MeeseAbstract:Background Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. Methods We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Results Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Conclusion Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.
E. Sorainen - One of the best experts on this subject based on the ideXlab platform.
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Noise level and ultrasound spectra during burring
Clinical Oral Investigations, 2002Co-Authors: E. Sorainen, E. RytkönenAbstract:The aim of this study was to evaluate the noise spectra of current dentistry equipment during normal work at the dental clinic and in the laboratory. In the study, noise was measured during the dental treatment of seven patients at a dental clinic and also in the acoustics laboratory, where working noise was simulated by drilling a polyacetal plate. All samples were analyzed in audible and ultrasonic areas in the one-third octave bands of 20–80,000 Hz. The measuring instruments used were B&K 4135 microphones, B&K 2633 preamplifiers, the B&K 2811 multiplexer, and the B&K 2133 Real-Time Analyzer with the ZT 0318 high-frequency expansion unit. In the in situ measurements, the A-weighted sound pressure level was occasionally over 85 dB(A), and the equivalent continuous A-weighted sound pressure level, L_Aeq, was 76 dB(A). The noise level was most powerful in the one-third octave band of 40,000 Hz, where it was 74 dB. In laboratory measurements, the noise levels of the air-turbine and the micromotor hand pieces ( n =16) were also most powerful in the one-third octave band of 40,000 Hz, where they were 80–89 dB. The L_Aeq of the different micromotor handpieces ( n =6) varied between 76 dB(A) and 77 dB(A), and the L_Aeq of the turbine hand pieces ( n =10) varied between 77 dB(A) and 82 dB(A). The noise of the drills is most powerful in the high frequencies, so using hearing protectors, it is possible that speech communication improves because the protectors attenuate high frequencies more than low frequencies. The very light protectors give sufficient protection against the drilling noise.
-
High-Frequency Noise in Dentistry
Aiha Journal, 2002Co-Authors: E. Sorainen, E. RytkönenAbstract:Earlier studies have revealed that dentists have higher hearing thresholds than expected. The aim of this study was to evaluate the noise levels of current dentistry equipment under very controlled conditions. This noise study was carried out in the Acoustics Laboratory of Kuopio Regional Institute of Occupational Health, the background noise of which is about 0 dB(A). Working noise was simulated by drilling a polyacetal plate. During drilling and idling, the noise of the hand pieces was measured over a reflecting plane on the hemisphere surface, the radius of which was 0.3 m, and 10 noise samples were picked for each hand piece. The average sound pressure level and the sound power level of the devices were calculated applying the standard ISO 3744. The measurement and analysis were done in the one-third octave bands of 25–80,000 Hz. The measuring instruments used were the B&K 4135 microphones, the B&K 2633 preamplifiers, the B&K 2811 multiplexer, and the B&K 2133 Real-Time Analyzer with the ZT 0318 high-...
