Smooth Muscle Hyperplasia due to ACTA2/MYH11 Mutations: Identification of Novel Pathology and Pathways Leading to Aneurysms and Diverse Vascular Occlusive Diseases

Missense mutations in smooth muscle cell (SMC) specific ACTA2 (á-actin) and MYH11 (â-myosin heavy chain) cause diffuse and diverse vascular diseases, including thoracic aortic aneurysms and dissections (TAAD) and early onset coronary artery disease and stroke. The mechanism by which these mutations lead to dilatation of some arteries but occlusion of others is unknown. We hypothesized that the mutations act through two distinct mechanisms to cause varied vascular diseases: a loss of function, leading to decreased SMC contraction and aneurysms, and a gain of function, leading to increased SMC proliferation and occlusive disease. To test this hypothesis, ACTA2 mutant SMCs and myofibroblasts were assessed and found to not form á-actin filaments whereas control cells did, suggesting a dominant negative effect of ACTA2 mutations on filament formation. A loss of á-actin filaments would be predicted to cause decreased SMC contractility. Histological examination of vascular tissues from patients revealed SMC hyperplasia leading to arterial stenosis and occlusion, supporting a gain of function associated with the mutant gene. Furthermore, ACTA2 mutant SMCs and myofibroblasts proliferated more rapidly in static culture than control cells (p<0.05). We also determined that Acta2-/- mice have ascending aortic aneurysms. Histological examination revealed aortic medial SMC hyperplasia, but minimal features of medial degeneration. Acta2-/- SMCs proliferated more rapidly in culture than wildtype (p<0.05), and microarray analysis of Acta2-/- SMCs revealed increased expression of Actg2, 15 collagen genes, and multiple focal adhesion genes. Acta2-/- SMCs showed altered localization of vinculin and zyxin and increased phosphorylated focal adhesion kinase (FAK) in focal adhesions. A specific FAK inhibitor decreased Acta2-/- SMC proliferation to levels equal to wildtype SMCs (p<0.05), suggesting that FAK activation leads to the increased proliferation. We have described a unique pathology associated with ACTA2 and MYH11 mutations, as well as an aneurysm phenotype in Acta2-/- mice. Additionally, we identified a novel pathogenic pathway for vascular occlusive disease due to loss of SMC contractile filaments, alterations in focal adhesions, and activation of FAK signaling in SMCs with ACTA2 mutations.

Canine mast cell tumours: a review of the pathogenesis, clinical features, pathology and treatment

Mast cells (MCs) are well known for their neoplastic transformation in solitary and multiple cutaneous mast cell tumours (MCTs), as well as visceral and systemic mastocytosis. Dogs have a unique risk of developing cutaneous MCTs, and they account for 7% to 21% of all canine skin tumours. The aetiology of canine MCTs is unknown but is probably multifactorial. This article reviews up-to-date knowledge on the pathogenesis, the clinical presentation, the clinical prognostic factors, the diagnostic workup including clinical staging, cytological findings, histological findings and the various grading systems which have been evaluated based on morphology, the assessment of proliferation markers and other factors such as vessel density. Furthermore, detailed information about current treatment protocols for canine cutaneous MCTs is provided.

Proliferative kidney disease in brown trout – infection level, pathology and mortality under field conditions

Proliferative kidney disease (PKD) is an emerging disease threatening wild salmonid populations. In temperature-controlled aquaria, PKD can cause mortality rates of up to 85% in rainbow trout. So far, no data about PKD-related mortality in wild brown trout Salmo trutta fario are available. The aim of this study was to investigate mortality rates and pathology in brown trout kept in a cage within a natural river habitat known to harbor Tetracapsuloides bryosalmonae. Young-of-the-year (YOY) brown trout, free of T. bryosalmonae, were exposed in the River Wutach, in the northeast of Switzerland, during 3 summer months. Samples of wild brown trout caught by electrofishing near the cage location were examined in parallel. The incidence of PKD in cage-exposed animals (69%) was not significantly different to the disease prevalence of wild fish (82 and 80% in the upstream and downstream locations, respectively). The mortality in cageexposed animals, however, was as low as 15%. At the termination of the exposure experiment, surviving fish showed histological lesions typical for PKD regression, suggesting that many YOY brown trout survive the initial infection. Our results at the River Wutach suggest that PKD in brown trout does not always result in high mortality under natural conditions.

Waddlia chondrophila induces systemic infection, organ pathology, and elicits Th1-associated humoral immunity in a murine model of genital infection

Waddlia chondrophila is a known bovine abortigenic Chlamydia-related bacterium that has been associated with adverse pregnancy outcomes in human. However, there is a lack of knowledge regarding how W. chondrophila infection spreads, its ability to elicit an immune response and induce pathology. A murine model of genital infection was developed to investigate the pathogenicity and immune response associated with a W. chondrophila infection. Genital inoculation of the bacterial agent resulted in a dose-dependent infection that spread to lumbar lymph nodes and successively to spleen and liver. Bacterial-induced pathology peaked on day 14, characterized by leukocyte infiltration (uterine horn, liver, and spleen), necrosis (liver) and extramedullary hematopoiesis (spleen). Immunohistochemistry demonstrated the presence of a large number of W. chondrophila in the spleen on day 14. Robust IgG titers were detected by day 14 and remained high until day 52. IgG isotypes consisted of high IgG2a, moderate IgG3 and no detectable IgG1, indicating a Th1-associated immune response. This study provides the first evidence that W. chondrophila genital infection is capable of inducing a systemic infection that spreads to major organs, induces uterus, spleen, and liver pathology and elicits a Th1-skewed humoral response. This new animal model will help our understanding of the mechanisms related to intracellular bacteria-induced miscarriages, the most frequent complication of pregnancy that affects one in four women.

Report on the practice based culminating experience as teaching assistant for "Pathology and Public Health" class taught at University of Texas School of Public Health, Houston

Objectives. The objectives of this report were to describe current best standards in online education, class competencies, class objectives, class activities and to compare the class competencies, objectives and activities undertaken with the current best practices in online teaching and to provide a list of recommendations based on the most efficacious practices. ^ Methods. Utilizing the key words- online teaching, national standards, quality, online courses, I: (1) conducted a search on Google to find the best standard for quality online courses; the search yielded National Standards for Quality Online Teaching as the gold standard in online course quality; (2) specified class objectives and competencies as well as major activities undertaken as a part of the class. Utilizing the Southern Regional Education Board evaluation checklist for online courses, I: (1) performed an analysis comparing the class activities, objectives, and competencies with the current best standards; (2) utilized the information obtained from the analysis and class experiences to develop recommendations for the most efficacious online teaching practices. ^ Results. The class met the criteria set by the Southern Regional Education Board for evaluating online classes completely in 75%, partially in 16% and did not meet the criteria in 9% cases. The majority of the parameters in which the class did not meet the standards (4 of 5) were due to technological reasons beyond the scope of the class instructor, teaching assistant and instructional design. ^ Discussion. Successful online teaching requires awareness of technology, good communication, methods, collaboration, reflection and flexibility. Creation of an online community, engaging online learners and utilizing different learning styles and assessment methods promote learning. My report proposes that online teaching should actively engage the students and teachers with multiple interactive strategies as evidenced from current best standards of online education and my “hands-on” work experience. ^ Conclusion. The report and the ideas presented are intended to create a foundation for efficacious practice on the online teaching platform. By following many of the efficacious online practices described in the report and adding from their own experiences, online instructors and teaching assistants can contribute to effective online learning. ^

Contributions to Speech Analytics based on Speech Recognition and Topic Identification

La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.

Targeted disruption of the cyclin-dependent kinase 5 gene results in abnormal corticogenesis, neuronal pathology and perinatal death.

Although cyclin-dependent kinase 5 (Cdk5) is closely related to other cyclin-dependent kinases, its kinase activity is detected only in the postmitotic neurons. Cdk5 expression and kinase activity are correlated with the extent of differentiation of neuronal cells in developing brain. Cdk5 purified from nervous tissue phosphorylates neuronal cytoskeletal proteins including neurofilament proteins and microtubule-associated protein tau in vitro. These findings indicate that Cdk5 may have unique functions in neuronal cells, especially in the regulation of phosphorylation of cytoskeletal molecules. We report here generation of Cdk5(-/-) mice through gene targeting and their phenotypic analysis. Cdk5(-/-) mice exhibit unique lesions in the central nervous system associated with perinatal mortality. The brains of Cdk5(-/-) mice lack cortical laminar structure and cerebellar foliation. In addition, the large neurons in the brain stem and in the spinal cord show chromatolytic changes with accumulation of neurofilament immunoreactivity. These findings indicate that Cdk5 is an important molecule for brain development and neuronal differentiation and also suggest that Cdk5 may play critical roles in neuronal cytoskeleton structure and organization.

Preserved speech abilities and compensation following prefrontal damage.

Lesions to left frontal cortex in humans produce speech production impairments (nonfluent aphasia). These impairments vary from subject to subject and performance on certain speech production tasks can be relatively preserved in some patients. A possible explanation for preservation of function under these circumstances is that areas outside left prefrontal cortex are used to compensate for the injured brain area. We report here a direct demonstration of preserved language function in a stroke patient (LF1) apparently due to the activation of a compensatory brain pathway. We used functional brain imaging with positron emission tomography (PET) as a basis for this study.

The speech, spatial and qualities of hearing scale: tradução e adaptação cultural para o português europeu

A deficiência auditiva afecta milhões de pessoas em todo o mundo, originando vários problemas, nomeadamente a nível psicossocial, que comprometem a qualidade de vida do indivíduo. A deficiência auditiva influencia o comportamento, particularmente ao dificultar a comunicação. Com o avanço tecnológico, os produtos de apoio, em particular os aparelhos auditivos e o implante coclear, melhoram essa qualidade de vida, através da melhoria da comunicação. Com as escalas de avaliação determinamos o modo como a deficiência auditiva influencia a vida diária, com ou sem amplificação, e de que forma afecta o desempenho psicossocial, emocional ou profissional do indivíduo, sendo esta informação importante para determinar a necessidade e o sucesso de amplificação, independentemente do tipo e grau da deficiência auditiva. O objectivo do presente estudo foi a tradução e adaptação para a cultura portuguesa da escala The Speech, Spatial and Qualities of Hearing Scale (SSQ), desenvolvida por Stuart Gatehouse e William Noble em 2004. Este trabalho foi realizado nos centros auditivos da Widex Portugal. Após os procedimentos de tradução e retroversão, a versão portuguesa foi testada em 12 indivíduos, com idades compreendidas entre os 36 anos e os 80 anos, dos quais 6 utilizavam prótese auditiva há mais de um ano, um utilizava prótese há menos de um ano e 5 nunca tinham utilizado. Com a tradução e adaptação cultural para o Português Europeu do “Questionário sobre as Qualidades Espaciais do Discurso – SSQ”, contribuímos para uma melhor avaliação dos indivíduos que estejam, ou venham a estar, a cumprir programas de reabilitação auditiva.

MicroRNAs in pathology and as therapeutic target in gene therapy?

Dissertação para obtenção do grau de Mestre no Instituto Superior de Ciências da Saúde Egas Moniz

Clinical pathology and transfusion medicine guide /

"February 1997"--p. [4] of cover.

A manual for the student of anatomy ; containing rules for displaying the structure of the body, so as to exhibit the elementary views of anatomy, and their application to pathology and surgery.

Original edition, London, 1821.

Excessive venery, masturbation and continence. The etiology, pathology and treatment of the diseases resulting from venereal excesses, masturbation and continence.

"The substance of a course of lectures delivered in the Medical department of the University of New York"--Pref.

Soviet publications in plant pathology and closely related fields; titles published from 1925 through early 1953 and available in the Library of the U.S. Department of Agriculture.

Mode of access: Internet.

Prolapsus, fistula in ano, and other diseases of the rectum: their pathology and treatment

Mode of access: Internet.