Periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1(st) and 2(nd) ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

Clinical and pathological analysis of epidural inflammation in intervertebral disk extrusion in dogs

BACKGROUND Little is known about the pathologic changes in the epidural space after intervertebral disk (IVD) extrusion in the dog. OBJECTIVES To analyze the pathology of the epidural inflammatory response, and to search for correlations between this process and clinical findings. METHODS Clinical data from 105 chondrodystrophic (CD) and nonchondrodystrophic (NCD) dogs with IVD extrusion were recorded. Epidural material from these dogs was examined histopathologically and immunohistochemically. Using statistical analysis, we searched for correlations between severity of epidural inflammation and various clinical and pathologic variables. RESULTS Most dogs exhibited an epidural inflammatory response, ranging from acute invasion of neutrophils to formation of chronic granulation tissue. The mononuclear inflammatory infiltrates consisted mostly of monocytes and macrophages and only few T and B cells. Surprisingly, chronic inflammatory patterns also were found in animals with an acute clinical history. Severity of the epidural inflammation correlated with degree of the epidural hemorrhage and nucleus pulposus calcification (P = .003 and .040), but not with age, chondrodystrophic phenotype, neurologic grade, back pain, pretreatment, or duration. The degree of inflammation was statistically (P = .021) inversely correlated with the ability to regain ambulation. CONCLUSION AND CLINICAL IMPORTANCE Epidural inflammation occurs in the majority of dogs with IVD extrusion and may develop long before the onset of clinical signs. Presence of calcified IVD material and hemorrhage in the epidural space may be the triggers of this lesion rather than an adaptive immune response to the nucleus pulposus as suggested in previous studies. Because epidural inflammation may affect outcome, further research is warranted.

Is complex signal processing for bone conduction hearing aids useful?

OBJECTIVES To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. METHODS Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. RESULTS Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). DISCUSSION Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. CONCLUSIONS When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

Temporal analysis of PI-3kinase and MAPK signal transduction during skeletal muscle overload

Skeletal muscles can adapt to increased mechanical forces (or loading) by increasing the size and strength of the muscle. Knowledge of the molecular mechanisms by which muscle responds to increased loading may lead to the discovery of novel treatment strategies for muscle wasting and frailty. The objective of this research was to examine the temporal associations between the activation of specific signaling pathway intermediates and their potential upstream regulator(s) in response to increased muscle loading. Previous work has demonstrated that focal adhesion kinase (FAK) activity is increased in overloaded hypertrophying skeletal muscle. Thus FAK is a candidate for transducing the loading stimulus in skeletal muscle, potentially by activating phosphatidylinositol 3-kinase (PI3K) and members of the mitogen-activated protein kinase (MAPK) family. However, it was unknown if muscle overload would result in activation of PI3K or the MAPKs. Thus, this work seeks to characterized the temporal response of (1) MAPK phosphorylation (including Erk 2, p38 MAPK and JNK), (2) PI3K activity, and (3) FAK tyrosine phosphorylation in response to 24 hours of compensatory overload in the rat soleus and plantaris muscles. In both muscles, overload resulted in transient Increases in the phosphorylation state of Erk2 and JNK, which peaked within the first hour of overload and returned to baseline thereafter. In contrast, p38 MAPK phosphorylation remained elevated throughout the entire 24-hour overload period. Moreover, overload increased PI3K activity only, in the plantaris and only at 12 hours. Moreover, 24 hours of overload induced a significant increase in total protein content in the plantaris but not the soleus. Thus an increase in total muscle protein content within the 24-hour loading period was observed only in muscle exhibiting increased PI3K activity. Surprisingly, FAK tyrosine phosphorylation was not increased during the overload period in either muscle, indicating that PI3K activation and increased MAPK phosphorylation were independent of increased FAK tyrosine phosphorylation. In summary, increased PI3K activity and sustained elevation of p38 MAPK phosphorylation were associated with muscle overload, identifying these pathways as potential mediators of the early hypertrophic response to skeletal muscle overload. This suggests that stimuli or mechanisms that activate these pathways may reduce/minimize muscle wasting and frailty. ^

A Dynamic Analysis: the Smile and Display of Dentition during Speech

The objective of this retrospective study is to follow up on a previous Dynamic Smile Analysis and videographically analyze and develop averages for soft tissue norms with respect to the display of dentition during speech. These values would then be compared cross-sectionally across different age groups to see whether changes attributable to the aging process could be seen. A secondary objective was to compare averages for soft tissue norms in the display of dentition during speech to averages for soft tissue norms in the display of dentition during the smile. Materials and Method: Records from a previous study in which video equipment was used to capture video for 26 1 subjects were re-evaluated to find appropriate frames to analyze for speech. Two frames for each subject were selected; one frame representing the maximal display of maxillary incisors during speech and the second representing the widest transverse display of dentition during speech. After excluding 40 subjects the data for the remaining 221 subjects was analyzed. These averages were then compared to averages attained in the previous study to compare the display of the dentition during speech to the display of the dentition during smile. Results: On average, a difference in 1.29 mm was seen in the display of the maxillary incisors during speech at maximal display and during the smile. An average of 7.23 mm of maxillary incisors is readily visible during maximum display of maxillary incisors during speech, as compared to 8.52 mm during the smile. The constructed smile index was also smaller when measured during the speech when compared to the smile index by an average of 2.58 units. Conclusion: This study helps to establish age-related dynamic norms for the display of dentition during speech. The dynamic measures indicate that the display of dectition is greater, on average, during the smile than at speech.

Introducing non-linear analysis into sustained speech characterization to improve sleep apnea detection

We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients' voices, and to think about tools which could be used to improve short-time analysis.

Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.

The analysis of the basketball coach speech during the moments of game and pause in relation to the performance in competition

In the area of the professional competition, the coach is a fundamental part in the management of a team and more concretely in the game planning. During the competition, the management of the times of pause and times out as well as the conduct of the coach during the same ones is an aspect to analyze in the sports performance. It is for this that it becomes necessary to know some of the behaviors that turn out to be more frequent by the coach and that are more related to a positive performance of his players. For it there has been realized a study of 7 cases of expert coaches in those that his verbal behavior has observed during 4 games. It has focused on the content of the information only to verbal level, on his meaning. The information that have been obtained in the study shows a major quantity of information elaborated during the pauses of the games and a major tactical content with regard to the moments of game. On the other hand, a relation exists between a major number of questions and a minor number of psychological instructions when the score is adverse, whereas in case of victory, a direct relation does not exist with any category. The rest of categories of the speech do not meet influenced directly for the result, for what it is not possible to consider a direct and immediate relation between the coach verbal behavior during the pauses and the result of the game, except in punctual moments.

Simplified small-signal stability analysis for optimized power system architecture

The optimization of power architectures is a complex problem due to the plethora of different ways to connect various system components. This issue has been addressed by developing a methodology to design and optimize power architectures in terms of the most fundamental system features: size, cost and efficiency. The process assumes various simplifications regarding the utilized DC/DC converter models in order to prevent the simulation time to become excessive and, therefore, stability is not considered. The objective of this paper is to present a simplified method to analyze small-signal stability of a system in order to integrate it into the optimization methodology. A black-box modeling approach, applicable to commercial converters with unknown topology and components, is based on frequency response measurements enabling the system small-signal stability assessment. The applicability of passivity-based stability criterion is assessed. The stability margins are stated utilizing a concept of maximum peak criteria derived from the behavior of the impedance-based sensitivity function that provides a single number to state the robustness of the stability of a well-defined minor-loop gain.

Non uniform embedding based on relevance analysis with reduced computational complexity: application to the detection of pathologies from biosignal recordings

Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study.

Analysis of signal impairment and crosstalk penalty induced by different types of optical filters in 100 Gbps PM-DQPSK based systems

Optical filters are crucial elements in optical communication networks. Their influence toward the optical signal will affect the communication quality seriously. In this paper we will study and simulate the optical signal impairment and crosstalk penalty caused by different kinds of filters, which include Butterworth, Bessel, Fiber Bragg Grating (FBG) and Fabry-Perot (F-P). Signal impairment from filter concatenation effect and crosstalk penalty from out-band and in-band are analyzed from Q-penalty, eye opening penalty (EOP) and optical spectrum. The simulation results show that signal impairment and crosstalk penalty induced by the Butterworth filter is the minimum among these four types of filters. Signal impairment caused by filter concatenation effect shows that when center frequency of all filters is aligned perfectly with the laser's frequency, 12 50-GHz Butterworth filters can be cascaded, with 1-dB EOP. This value is reduced to 9 when the center frequency is misaligned with 5 GHz. In the 50-GHz channel spacing DWDM networks, total Q-penalty induced by a pair of Butterworth filters based demultiplexer and multiplexer is lower than 0.5 dB when the filter bandwidth is in the range of 42-46 GHz.

Descripción de parámetros glóticos basados en el modelado de los pliegues vocales para la detección de patología de la voz

Las patologías de la voz se han transformado en los últimos tiempos en una problemática social con cierto calado. La contaminación de las ciudades, hábitos como el de fumar, el uso de aparatos de aire acondicionado, etcétera, contribuyen a ello. Esto alcanza más relevancia en profesionales que utilizan su voz de manera frecuente, como, por ejemplo, locutores, cantantes, profesores o teleoperadores. Por todo ello resultan de especial interés las técnicas de ayuda al diagnóstico que son capaces de extraer conclusiones clínicas a partir de una muestra de la voz grabada con un micrófono, frente a otras invasivas que implican la exploración utilizando laringoscopios, fibroscopios o videoendoscopios, técnicas en cualquier caso mucho más molestas para los pacientes al exigir la introducción parcial del instrumental citado por la garganta, en actuaciones consideradas de tipo quirúrgico. Dentro de aquellas técnicas se ha avanzado mucho en un período de tiempo relativamente corto. En lo que se refiere al diagnóstico de patologías, hemos pasado en los últimos quince años de trabajar principalmente con parámetros extraídos de la señal de voz –tanto en el dominio del tiempo como en el de la frecuencia– y con escalas elaboradas con valoraciones subjetivas realizadas por expertos a hacerlo también con parámetros procedentes de estimaciones de la fuente glótica. La importancia de utilizar la fuente glótica reside, a grandes rasgos, en que se trata de una señal vinculada directamente al estado de la estructura laríngea del locutor y también en que está generalmente menos influida por el tracto vocal que la señal de voz. Es conocido que el tracto vocal guarda más relación con el mensaje hablado, y su presencia dificulta el proceso de detección de patología vocal. Estas estimaciones de la fuente glótica han sido obtenidas a través de técnicas de filtrado inverso desarrolladas por nuestro grupo de investigación. Hemos conseguido, además, profundizar en la naturaleza de la señal glótica: somos capaces de descomponerla y relacionarla con parámetros biomecánicos de los propios pliegues vocales, obteniendo estimaciones de elementos como la masa, la pérdida de energía o la elasticidad del cuerpo y de la cubierta del pliegue, entre otros. De las componentes de la fuente glótica surgen también los denominados parámetros biométricos, relacionados con la forma de la señal, que constituyen por sí mismos una firma biométrica del individuo. También trabajaremos con parámetros temporales, relacionados con las diferentes etapas que se observan dentro de la señal glótica durante un ciclo de fonación. Por último, consideraremos parámetros clásicos de perturbación y energía de la señal. En definitiva, contamos ahora con una considerable cantidad de parámetros glóticos que conforman una base estadística multidimensional, destinada a ser capaz de discriminar personas con voces patológicas o disfónicas de aquellas que no presentan patología en la voz o con voces sanas o normofónicas. Esta tesis doctoral se ocupa de varias cuestiones: en primer lugar, es necesario analizar cuidadosamente estos nuevos parámetros, por lo que ofreceremos una completa descripción estadística de los mismos. También estudiaremos cuestiones como la distribución de los parámetros atendiendo a criterios como el de normalidad estadística de los mismos, ocupándonos especialmente de la diferencia entre las distribuciones que presentan sujetos sanos y sujetos con patología vocal. Para todo ello emplearemos diferentes técnicas estadísticas: generación de elementos y diagramas descriptivos, pruebas de normalidad y diversos contrastes de hipótesis, tanto paramétricos como no paramétricos, que considerarán la diferencia entre los grupos de personas sanas y los grupos de personas con alguna patología relacionada con la voz. Además, nos interesa encontrar relaciones estadísticas entre los parámetros, de cara a eliminar posibles redundancias presentes en el modelo, a reducir la dimensionalidad del problema y a establecer un criterio de importancia relativa en los parámetros en cuanto a su capacidad discriminante para el criterio patológico/sano. Para ello se aplicarán técnicas estadísticas como la Correlación Lineal Bivariada y el Análisis Factorial basado en Componentes Principales. Por último, utilizaremos la conocida técnica de clasificación Análisis Discriminante, aplicada a diferentes combinaciones de parámetros y de factores, para determinar cuáles de ellas son las que ofrecen tasas de acierto más prometedoras. Para llevar a cabo la experimentación se ha utilizado una base de datos equilibrada y robusta formada por doscientos sujetos, cien de ellos pertenecientes al género femenino y los restantes cien al género masculino, con una proporción también equilibrada entre los sujetos que presentan patología vocal y aquellos que no la presentan. Una de las aplicaciones informáticas diseñada para llevar a cabo la recogida de muestras también es presentada en esta tesis. Los distintos estudios estadísticos realizados nos permitirán identificar aquellos parámetros que tienen una mayor contribución a la hora de detectar la presencia de patología vocal. Alguno de los estudios, además, nos permitirá presentar una ordenación de los parámetros en base a su importancia para realizar la detección. Por otra parte, también concluiremos que en ocasiones es conveniente realizar una reducción de la dimensionalidad de los parámetros para mejorar las tasas de detección. Por fin, las propias tasas de detección constituyen quizá la conclusión más importante del trabajo. Todos los análisis presentes en el trabajo serán realizados para cada uno de los dos géneros, de acuerdo con diversos estudios previos que demuestran que los géneros masculino y femenino deben tratarse de forma independiente debido a las diferencias orgánicas observadas entre ambos. Sin embargo, en lo referente a la detección de patología vocal contemplaremos también la posibilidad de trabajar con la base de datos unificada, comprobando que las tasas de acierto son también elevadas. Abstract Voice pathologies have become recently in a social problem that has reached a certain concern. Pollution in cities, smoking habits, air conditioning, etc. contributes to it. This problem is more relevant for professionals who use their voice frequently: speakers, singers, teachers, actors, telemarketers, etc. Therefore techniques that are capable of drawing conclusions from a sample of the recorded voice are of particular interest for the diagnosis as opposed to other invasive ones, involving exploration by laryngoscopes, fiber scopes or video endoscopes, which are techniques much less comfortable for patients. Voice quality analysis has come a long way in a relatively short period of time. In regard to the diagnosis of diseases, we have gone in the last fifteen years from working primarily with parameters extracted from the voice signal (both in time and frequency domains) and with scales drawn from subjective assessments by experts to produce more accurate evaluations with estimates derived from the glottal source. The importance of using the glottal source resides broadly in that this signal is linked to the state of the speaker's laryngeal structure. Unlike the voice signal (phonated speech) the glottal source, if conveniently reconstructed using adaptive lattices, may be less influenced by the vocal tract. As it is well known the vocal tract is related to the articulation of the spoken message and its influence complicates the process of voice pathology detection, unlike when using the reconstructed glottal source, where vocal tract influence has been almost completely removed. The estimates of the glottal source have been obtained through inverse filtering techniques developed by our research group. We have also deepened into the nature of the glottal signal, dissecting it and relating it to the biomechanical parameters of the vocal folds, obtaining several estimates of items such as mass, loss or elasticity of cover and body of the vocal fold, among others. From the components of the glottal source also arise the so-called biometric parameters, related to the shape of the signal, which are themselves a biometric signature of the individual. We will also work with temporal parameters related to the different stages that are observed in the glottal signal during a cycle of phonation. Finally, we will take into consideration classical perturbation and energy parameters. In short, we have now a considerable amount of glottal parameters in a multidimensional statistical basis, designed to be able to discriminate people with pathologic or dysphonic voices from those who do not show pathology. This thesis addresses several issues: first, a careful analysis of these new parameters is required, so we will offer a complete statistical description of them. We will also discuss issues such as distribution of the parameters, considering criteria such as their statistical normality. We will take special care in the analysis of the difference between distributions from healthy subjects and the distributions from pathological subjects. To reach these goals we will use different statistical techniques such as: generation of descriptive items and diagramas, tests for normality and hypothesis testing, both parametric and nonparametric. These latter techniques consider the difference between the groups of healthy subjects and groups of people with an illness related to voice. In addition, we are interested in finding statistical relationships between parameters. There are various reasons behind that: eliminate possible redundancies in the model, reduce the dimensionality of the problem and establish a criterion of relative importance in the parameters. The latter reason will be done in terms of discriminatory power for the criterion pathological/healthy. To this end, statistical techniques such as Bivariate Linear Correlation and Factor Analysis based on Principal Components will be applied. Finally, we will use the well-known technique of Discriminant Analysis classification applied to different combinations of parameters and factors to determine which of these combinations offers more promising success rates. To perform the experiments we have used a balanced and robust database, consisting of two hundred speakers, one hundred of them males and one hundred females. We have also used a well-balanced proportion where subjects with vocal pathology as well as subjects who don´t have a vocal pathology are equally represented. A computer application designed to carry out the collection of samples is also presented in this thesis. The different statistical analyses performed will allow us to determine which parameters contribute in a more decisive way in the detection of vocal pathology. Therefore, some of the analyses will even allow us to present a ranking of the parameters based on their importance for the detection of vocal pathology. On the other hand, we will also conclude that it is sometimes desirable to perform a dimensionality reduction in order to improve the detection rates. Finally, detection rates themselves are perhaps the most important conclusion of the work. All the analyses presented in this work have been performed for each of the two genders in agreement with previous studies showing that male and female genders should be treated independently, due to the observed functional differences between them. However, with regard to the detection of vocal pathology we will consider the possibility of working with the unified database, ensuring that the success rates obtained are also high.

Identification and analysis of the plant peroxisomal targeting signal 1 receptor NtPEX5

Protein translocation into peroxisomes takes place via recognition of a peroxisomal targeting signal present at either the extreme C termini (PTS1) or N termini (PTS2) of matrix proteins. In mammals and yeast, the peroxisomal targeting signal receptor, Pex5p, recognizes the PTS1 consisting of -SKL or variants thereof. Although many plant peroxisomal matrix proteins are transported through the PTS1 pathway, little is known about the PTS1 receptor or any other peroxisome assembly protein from plants. We cloned tobacco (Nicotiana tabacum) cDNAs encoding Pex5p (NtPEX5) based on the protein’s interaction with a PTS1-containing protein in the yeast two-hybrid system. Nucleotide sequence analysis revealed that the tobacco Pex5p contains seven tetratricopeptide repeats and that NtPEX5 shares greater sequence similarity with its homolog from humans than from yeast. Expression of NtPEX5 fusion proteins, consisting of the N-terminal part of yeast Pex5p and the C-terminal region of NtPEX5, in a Saccharomyces cerevisiae pex5 mutant restored protein translocation into peroxisomes. These experiments confirmed the identity of the tobacco protein as a PTS1 receptor and indicated that components of the peroxisomal translocation apparatus are conserved functionally. Two-hybrid assays showed that NtPEX5 interacts with a wide range of PTS1 variants that also interact with the human Pex5p. Interestingly, the C-terminal residues of some of these peptides deviated from the established plant PTS1 consensus sequence. We conclude that there are significant sequence and functional similarities between the plant and human Pex5ps.

Ultrasensitive detection of pathological prion protein aggregates by dual-color scanning for intensely fluorescent targets

A definite diagnosis of prion diseases such as Creutzfeldt–Jakob disease (CJD) relies on the detection of pathological prion protein (PrPSc). However, no test for PrPSc in cerebrospinal fluid (CSF) has been available thus far. Based on a setup for confocal dual-color fluorescence correlation spectroscopy, a technique suitable for single molecule detection, we developed a highly sensitive detection method for PrPSc. Pathological prion protein aggregates were labeled by specific antibody probes tagged with fluorescent dyes, resulting in intensely fluorescent targets, which were measured by dual-color fluorescence intensity distribution analysis in a confocal scanning setup. In a diagnostic model system, PrPSc aggregates were detected down to a concentration of 2 pM PrPSc, corresponding to an aggregate concentration of approximately 2 fM, which was more than one order of magnitude more sensitive than Western blot analysis. A PrPSc-specific signal could also be detected in a number of CSF samples from patients with CJD but not in control samples, providing the basis for a rapid and specific test for CJD and other prion diseases. Furthermore, this method could be adapted to the sensitive detection of other disease-associated amyloid aggregates such as in Alzheimer's disease.

Analysis of variable (diversity) joining recombination in DNAdependent protein kinase (DNA-PK)-deficient mice reveals DNA-PK-independent pathways for both signal and coding joint formation

Previous studies have suggested that ionizing radiation causes irreparable DNA double-strand breaks in mice and cell lines harboring mutations in any of the three subunits of DNA-dependent protein kinase (DNA-PK) (the catalytic subunit, DNA-PKcs, or one of the DNA-binding subunits, Ku70 or Ku86). In actuality, these mutants vary in their ability to resolve double-strand breaks generated during variable (diversity) joining [V(D)J] recombination. Mutant cell lines and mice with targeted deletions in Ku70 or Ku86 are severely compromised in their ability to form coding and signal joints, the products of V(D)J recombination. It is noteworthy, however, that severe combined immunodeficient (SCID) mice, which bear a nonnull mutation in DNA-PKcs, are substantially less impaired in forming signal joints than coding joints. The current view holds that the defective protein encoded by the murine SCID allele retains enough residual function to support signal joint formation. An alternative hypothesis proposes that DNA-PKcs and Ku perform different roles in V(D)J recombination, with DNA-PKcs required only for coding joint formation. To resolve this issue, we examined V(D)J recombination in DNA-PKcs-deficient (SLIP) mice. We found that the effects of this mutation on coding and signal joint formation are identical to the effects of the SCID mutation. Signal joints are formed at levels 10-fold lower than in wild type, and one-half of these joints are aberrant. These data are incompatible with the notion that signal joint formation in SCID mice results from residual DNA-PKcs function, and suggest a third possibility: that DNA-PKcs normally plays an important but nonessential role in signal joint formation.