Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.

New methodology for the integration of biometric features in speaker recognition systems applied to security environments

La cuestión principal abordada en esta tesis doctoral es la mejora de los sistemas biométricos de reconocimiento de personas a partir de la voz, proponiendo el uso de una nueva parametrización, que hemos denominado parametrización biométrica extendida dependiente de género (GDEBP en sus siglas en inglés). No se propone una ruptura completa respecto a los parámetros clásicos sino una nueva forma de utilizarlos y complementarlos. En concreto, proponemos el uso de parámetros diferentes dependiendo del género del locutor, ya que como es bien sabido, la voz masculina y femenina presentan características diferentes que deberán modelarse, por tanto, de diferente manera. Además complementamos los parámetros clásicos utilizados (MFFC extraídos de la señal de voz), con un nuevo conjunto de parámetros extraídos a partir de la deconstrucción de la señal de voz en sus componentes de fuente glótica (más relacionada con el proceso y órganos de fonación y por tanto con características físicas del locutor) y de tracto vocal (más relacionada con la articulación acústica y por tanto con el mensaje emitido). Para verificar la validez de esta propuesta se plantean diversos escenarios, utilizando diferentes bases de datos, para validar que la GDEBP permite generar una descripción más precisa de los locutores que los parámetros MFCC clásicos independientes del género. En concreto se plantean diferentes escenarios de identificación sobre texto restringido y texto independiente utilizando las bases de datos de HESPERIA y ALBAYZIN. El trabajo también se completa con la participación en dos competiciones internacionales de reconocimiento de locutor, NIST SRE (2010 y 2012) y MOBIO 2013. En el primer caso debido a la naturaleza de las bases de datos utilizadas se obtuvieron resultados cercanos al estado del arte, mientras que en el segundo de los casos el sistema presentado obtuvo la mejor tasa de reconocimiento para locutores femeninos. A pesar de que el objetivo principal de esta tesis no es el estudio de sistemas de clasificación, sí ha sido necesario analizar el rendimiento de diferentes sistemas de clasificación, para ver el rendimiento de la parametrización propuesta. En concreto, se ha abordado el uso de sistemas de reconocimiento basados en el paradigma GMM-UBM, supervectores e i-vectors. Los resultados que se presentan confirman que la utilización de características que permitan describir los locutores de manera más precisa es en cierto modo más importante que la elección del sistema de clasificación utilizado por el sistema. En este sentido la parametrización propuesta supone un paso adelante en la mejora de los sistemas de reconocimiento biométrico de personas por la voz, ya que incluso con sistemas de clasificación relativamente simples se consiguen tasas de reconocimiento realmente competitivas. ABSTRACT The main question addressed in this thesis is the improvement of automatic speaker recognition systems, by the introduction of a new front-end module that we have called Gender Dependent Extended Biometric Parameterisation (GDEBP). This front-end do not constitute a complete break with respect to classical parameterisation techniques used in speaker recognition but a new way to obtain these parameters while introducing some complementary ones. Specifically, we propose a gender-dependent parameterisation, since as it is well known male and female voices have different characteristic, and therefore the use of different parameters to model these distinguishing characteristics should provide a better characterisation of speakers. Additionally, we propose the introduction of a new set of biometric parameters extracted from the components which result from the deconstruction of the voice into its glottal source estimate (close related to the phonation process and the involved organs, and therefore the physical characteristics of the speaker) and vocal tract estimate (close related to acoustic articulation and therefore to the spoken message). These biometric parameters constitute a complement to the classical MFCC extracted from the power spectral density of speech as a whole. In order to check the validity of this proposal we establish different practical scenarios, using different databases, so we can conclude that a GDEBP generates a more accurate description of speakers than classical approaches based on gender-independent MFCC. Specifically, we propose scenarios based on text-constrain and text-independent test using HESPERIA and ALBAYZIN databases. This work is also completed with the participation in two international speaker recognition evaluations: NIST SRE (2010 and 2012) and MOBIO 2013, with diverse results. In the first case, due to the nature of the NIST databases, we obtain results closed to state-of-the-art although confirming our hypothesis, whereas in the MOBIO SRE we obtain the best simple system performance for female speakers. Although the study of classification systems is beyond the scope of this thesis, we found it necessary to analise the performance of different classification systems, in order to verify the effect of them on the propose parameterisation. In particular, we have addressed the use of speaker recognition systems based on the GMM-UBM paradigm, supervectors and i-vectors. The presented results confirm that the selection of a set of parameters that allows for a more accurate description of the speakers is as important as the selection of the classification method used by the biometric system. In this sense, the proposed parameterisation constitutes a step forward in improving speaker recognition systems, since even when using relatively simple classification systems, really competitive recognition rates are achieved.

Cepstral peak prominence: a comprehensive analysis

An analytical study of cepstral peak prominence (CPP) is presented, intended to provide an insight into its meaning and relation with voice perturbation parameters. To carry out this analysis, a parametric approach is adopted in which voice production is modelled using the traditional source-filter model and the first cepstral peak is assumed to have Gaussian shape. It is concluded that the meaning of CPP is very similar to that of the first rahmonic and some insights are provided on its dependence with fundamental frequency and vocal tract resonances. It is further shown that CPP integrates measures of voice waveform and periodicity perturbations, be them either amplitude, frequency or noise.

Analysis of measured and simulated supraglottal acoustic waves

To date, although much attention has been paid to the estimation and modeling of the voice source (ie, the glottal airflow volume velocity), the measurement and characterization of the supraglottal pressure wave have been much less studied. Some previous results have unveiled that the supraglottal pressure wave has some spectral resonances similar to those of the voice pressure wave. This makes the supraglottal wave partially intelligible. Although the explanation for such effect seems to be clearly related to the reflected pressure wave traveling upstream along the vocal tract, the influence that nonlinear source-filter interaction has on it is not as clear. This article provides an insight into this issue by comparing the acoustic analyses of measured and simulated supraglottal and voice waves. Simulations have been performed using a high-dimensional discrete vocal fold model. Results of such comparative analysis indicate that spectral resonances in the supraglottal wave are mainly caused by the regressive pressure wave that travels upstream along the vocal tract and not by source-tract interaction. On the contrary and according to simulation results, source-tract interaction has a role in the loss of intelligibility that happens in the supraglottal wave with respect to the voice wave. This loss of intelligibility mainly corresponds to spectral differences for frequencies above 1500 Hz.

Modeling of GRBAS perceptual evaluation using spectral features obtained from an auditory-based filterbank.

Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained.

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.

Modelado de fuente glotal para extraer características de la identidad del locutor

La producción de la voz humana se lleva a cabo en el tracto vocal. Los sintetizadores consiguen emular a las distintas partes del tracto vocal, y gracias a ellos se pueden modificar características propias del hablante. Una de estas modificaciones consiste variar el tono de un locutor inicial, mezclando parámetros de éste con los de un locutor deseado. En este proyecto se ha desarrollado un modelo propuesto para este cambio de identidad. Partiendo de las señales de voz originales se han extraído parámetros para crear una base de datos para cada locutor. Las voces se sintetizarán mezclando estas bases de datos y otros parámetros correspondientes a distintos locutores dando como resultado una señal de voz con características de dos locutores diferentes. Finalmente se realizarán pruebas auditivas para comprobar la identidad del locutor de la voz sintetizada. ABSTRACT. Human voice production is carried out in the vocal tract. Each part of the vocal tract is emulated in synthesizers, and for that, speaker features can be modified. One of these modifications is to change the initial speaker tone, mixing parameters of this speaker with the parameters of a desired speaker. In this project it has been developed a proposed model for this identity change. Starting from the originals voice signals its parameters have been extracted to built a database for each speaker. Voices will be synthesized mixing these databases with parameters of the others speakers giving as result a voice signal with features of two different speakers. Finally, hearing tests will be made to check the speaker identity of the synthesized voice.

Molecular basis for the recognition of two structurally different major histocompatibility complex/peptide complexes by a single T-cell receptor

2C is a typical alloreactive cytotoxic T lymphocyte clone that recognizes two different ligands. These ligands are adducts of the allo-major histocompatibility complex (MHC) molecule H-2Ld and an endogenous octapeptide, and of the self-MHC molecule H-2Kb and another peptide. MHC-binding and T-cell assays with synthetic peptides in combination with molecular modeling studies were employed to analyze the structural basis for this crossreactivity. The molecular surfaces of the two complexes differ greatly in densities and distributions of positive and negative charges. However, modifications of the peptides that increase similarity decrease the capacities of the resulting MHC peptide complexes to induce T-cell responses. Moreover, the roles of the peptides in ligand recognition are different for self- and allo-MHC-restricted T-cell responses. The self-MHC-restricted T-cell responses were finely tuned to recognition of the peptide. The allo-MHC-restricted responses, on the other hand, largely ignore modifications of the peptide. The results strongly suggest that adaptation of the T-cell receptor to the different ligand structures, rather than molecular mimicry by the ligands, is the basis for the crossreactivity of 2C. This conclusion has important implications for T-cell immunology and for the understanding of immunological disorders.

Acoustic and neural bases for innate recognition of song

In behavior reminiscent of the responsiveness of human infants to speech, young songbirds innately recognize and prefer to learn the songs of their own species. The acoustic and physiological bases for innate recognition were investigated in fledgling white-crowned sparrows lacking song experience. A behavioral test revealed that the complete conspecific song was not essential for innate recognition: songs composed of single white-crowned sparrow phrases and songs played in reverse elicited vocal responses as strongly as did normal song. In all cases, these responses surpassed those to other species’ songs. Although auditory neurons in the song nucleus HVc and the underlying neostriatum of fledglings did not prefer conspecific song over foreign song, some neurons responded strongly to particular phrase types characteristic of white-crowned sparrows and, thus, could contribute to innate song recognition.

A new mechanism of sound generation in songbirds

Our current understanding of the sound-generating mechanism in the songbird vocal organ, the syrinx, is based on indirect evidence and theoretical treatments. The classical avian model of sound production postulates that the medial tympaniform membranes (MTM) are the principal sound generators. We tested the role of the MTM in sound generation and studied the songbird syrinx more directly by filming it endoscopically. After we surgically incapacitated the MTM as a vibratory source, zebra finches and cardinals were not only able to vocalize, but sang nearly normal song. This result shows clearly that the MTM are not the principal sound source. The endoscopic images of the intact songbird syrinx during spontaneous and brain stimulation-induced vocalizations illustrate the dynamics of syringeal reconfiguration before phonation and suggest a different model for sound production. Phonation is initiated by rostrad movement and stretching of the syrinx. At the same time, the syrinx is closed through movement of two soft tissue masses, the medial and lateral labia, into the bronchial lumen. Sound production always is accompanied by vibratory motions of both labia, indicating that these vibrations may be the sound source. However, because of the low temporal resolution of the imaging system, the frequency and phase of labial vibrations could not be assessed in relation to that of the generated sound. Nevertheless, in contrast to the previous model, these observations show that both labia contribute to aperture control and strongly suggest that they play an important role as principal sound generators.

A relationship between behavior, neurotrophin expression, and new neuron survival

The high vocal center (HVC) controls song production in songbirds and sends a projection to the robust nucleus of the archistriatum (RA) of the descending vocal pathway. HVC receives new neurons in adulthood. Most of the new neurons project to RA and replace other neurons of the same kind. We show here that singing enhances mRNA and protein expression of brain-derived neurotrophic factor (BDNF) in the HVC of adult male canaries, Serinus canaria. The increased BDNF expression is proportional to the number of songs produced per unit time. Singing-induced BDNF expression in HVC occurs mainly in the RA-projecting neurons. Neuronal survival was compared among birds that did or did not sing during days 31–38 after BrdUrd injection. Survival of new HVC neurons is greater in the singing birds than in the nonsinging birds. A positive causal link between pathway use, neurotrophin expression, and new neuron survival may be common among systems that recruit new neurons in adulthood.

Resected RNA pseudoknots and their recognition by histidyl-tRNA synthetase

Duplexes constituted by closed or open RNA circles paired to single-stranded oligonucleotides terminating with 3′-CCAOH form resected pseudoknots that are substrates of yeast histidyl-tRNA synthetase. Design of this RNA fold is linked to the mimicry of the pseudoknotted amino acid accepting branch of the tRNA-like domain from brome mosaic virus, known to be charged by tyrosyl-tRNA synthetases, with RNA minihelices recapitulating accepting branches of canonical tRNAs. Prediction of the histidylation function of the new family of minimalist tRNA-like structures relates to the geometry of resected pseudoknots that allows proper presentation to histidyl-tRNA synthetase of analogues of the histidine identity determinants N-1 and N73 present in tRNAs. This geometry is such that the analogue of the major N-1 histidine determinant in the RNA circles faces the analogue of the discriminator N73 nucleotide in the accepting oligonucleotides. The combination of identity elements found in tRNAHis species from archaea, eubacteria, and organelles (G-1/C73) is the most efficient for determining histidylation of the duplexes. The inverse combination (C-1/G73) leads to the worst histidine acceptors with charging efficiencies reduced by 2–3 orders of magnitude. Altogether, these findings open new perspectives for understanding evolution of tRNA identity and serendipitous RNA functions.

Cytomegalovirus in autoimmunity: T cell crossreactivity to viral antigen and autoantigen glutamic acid decarboxylase

Antigens of pathogenic microbes that mimic autoantigens are thought to be responsible for the activation of autoreactive T cells. Viral infections have been associated with the development of the neuroendocrine autoimmune diseases type 1 diabetes and stiff-man syndrome, but the mechanism is unknown. These diseases share glutamic acid decarboxylase (GAD65) as a major autoantigen. We screened synthetic peptide libraries dedicated to bind to HLA-DR3, which predisposes to both diseases, using clonal CD4+ T cells reactive to GAD65 isolated from a prediabetic stiff-man syndrome patient. Here we show that these GAD65-specific T cells crossreact with a peptide of the human cytomegalovirus (hCMV) major DNA-binding protein. This peptide was identified after database searching with a recognition pattern that had been deduced from the library studies. Furthermore, we showed that hCMV-derived epitope can be naturally processed by dendritic cells and recognized by GAD65 reactive T cells. Thus, hCMV may be involved in the loss of T cell tolerance to autoantigen GAD65 by a mechanism of molecular mimicry leading to autoimmunity.

Complete genome sequence of an M1 strain of Streptococcus pyogenes

The 1,852,442-bp sequence of an M1 strain of Streptococcus pyogenes, a Gram-positive pathogen, has been determined and contains 1,752 predicted protein-encoding genes. Approximately one-third of these genes have no identifiable function, with the remainder falling into previously characterized categories of known microbial function. Consistent with the observation that S. pyogenes is responsible for a wider variety of human disease than any other bacterial species, more than 40 putative virulence-associated genes have been identified. Additional genes have been identified that encode proteins likely associated with microbial “molecular mimicry” of host characteristics and involved in rheumatic fever or acute glomerulonephritis. The complete or partial sequence of four different bacteriophage genomes is also present, with each containing genes for one or more previously undiscovered superantigen-like proteins. These prophage-associated genes encode at least six potential virulence factors, emphasizing the importance of bacteriophages in horizontal gene transfer and a possible mechanism for generating new strains with increased pathogenic potential.

Viruses, cytokines, antigens, and autoimmunity.

To explain the pathogenesis of autoimmunity, we hypothesize that following an infection the immune response spreads to tissue-specific autoantigens in genetically predisposed individuals eventually determining progression to disease. Molecular mimicry between viral and self antigens could, in some instances, initiate autoimmunity. Local elicitation of inflammatory cytokines following infection probably plays a pivotal role in determining loss of functional tolerance to self autoantigens and the destructive activation of autoreactive cells. We also describe the potential role of interleukin 10, a powerful B-cell activator, in increasing the efficiency of epitope recognition, that could well be crucial to the progression toward disease.