Omental and pleural milky spots: different reactivity patterns in mice infected with Schistosoma mansoni reveals coelomic compartmentalisation

In vertebrate animals, pleural and peritoneal cavities are repositories of milky spots (MS), which constitute an organised coelom-associated lymphomyeloid tissue that is intensively activated by Schistosoma mansoni infection. This study compared the reactive patterns of peritoneal MS to pleural MS and concluded from histological analysis that they represent independent responsive compartments. Whole omentum, lungs and the entire mediastinum of 54 S. mansoni-infected mice were studied morphologically. The omental MS of infected animals were highly activated, modulating from myeloid-lymphocytic (60 days of infection) to lymphomyeloid (90 days of infection) and lymphocytic or lymphoplasmacytic (160 days of infection) types. The non-lymphoid component predominated in the acute phase of infection and was expressed by monocytopoietic, eosinopoietic and neutropoietic foci, with isolated megakaryocytes and small foci of late normoblasts and mast cells. Nevertheless, pleural or thoracic MS of infected mice were monotonous, consisting of small and medium lymphocytes with few mast and plasma cells and no myeloid component. Our data indicate that compartmentalisation of the MS response is dependent on the lymphatic vascularisation of each coelomic cavity, limiting the effects or consequences of any stimulating or aggressive agents, as is the case with S. mansoni infection.

Open access and connectedness: stimulating unexpected innovation through the use of institutional open archives

The author reviews past work with Ibict and the global progress made by the Open Access Movement. He postulates a theory of open access being an example of a complex adaptive system created by Internet-based scholarly publishing. Open access could be the cause of a cascade of increasing complexity and opportunities that will reshape this system. He has chosen the pervasive and global "Connectedness" created by the internet and the content spaces it provides for open access collections as a "simple disruptive agent". He discusses how connectedness influences infinite variety, creativity, work, change, knowledge, and the information economy. Case studies from the University of New Mexico Libraries are used where appropriate.

ETDs, NDLTD, and open access: a 5S perspective

Worldwide initiatives toward digital library (DL) support for electronic theses and dissertations (ETDs), facilitated by the work of the Networked Digital Library of Theses and Dissertations (NDLTD), are a key part of the move toward open access. When all graduate students learn to use openly available ETDs, and have experience with authoring and submission in connection with their own research results, it will be easy for them to continue these efforts through other contributions to open access. When all universities support ETD activities, they will be key participants in institutional repositories and open access, and will have engaged in discussion and infrastructure development supportive of further open access activities. Understanding of open access also can be facilitated through modeling of all of these efforts using the 5S framework, considering the key aspects of DL development: Societies, Scenarios, Spaces, Structures, and Streams.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.