Neurotrophins and their receptors in the pigeon caecal tonsil. An immunohistochemical study

Neurotrophins are growth factors which bind to signal-transducing receptors called Trk proteins. The neurotrophins and their receptor proteins are present in the mammalian and avian lymphoid organs, thus suggesting that these factors could act upon cells of the immune system. Nevertheless, little is known about the cellular distribution of neurotrophins and their receptor proteins in avian lymphoid tissues. In this study we use immunohistochemistry to detect the cellular localisation of neurotrophins and their receptor proteins in the pigeon caecal tonsil, used as a model for avian secondary lymphoid organs. Rabbit polyclonal antibodies against neurotrophins (nerve growth factor -NGF-, brain-derived neurotrophic factor -BDNF- and neurotrophin -3 NT-3-) and against specific epitopes of TrkA, TrkB and TrkC proteins were used. Cytokeratins, vimentin, S-100 protein and chromogranin A were studied in parallel to identify cells which seemed to express neurotrophins and Trk proteins. TrkA-like protein was seen in the intestinal epithelium, whereas TrkB-like and TrkC-like proteins was found in cells which we identified as dendritic cells and macrophages. BDNF-like and NT-3-like reactivity was localised in intestinal epithelial cells, especially endocrine cells. Present results add further evidence to the presumptive immune role of neurotrophins and their receptors and the possible functions of these peptides in the caecal tonsil are discussed.     

TiO2 thin films from titanium butoxide: Synthesis, Pt addition, structural stability, microelectronic processing and gas-sensing properties

TiO₂ thin films were prepared by spin-coating of a Ti butoxide-derived sol onto oxidized silicon wafers, followed by a heat-treatment at temperatures ranging from 500 to 800 °C. The film thickness after heat-treatment at 500 °C was 50 nm. Pt addition, with a Pt:Ti nominal atomic ratio ranging from 0.01 to 0.1, was achieved by adding solutions of Pt(II) acetylacetonate to the TiO₂ sols. The thin films were investigated by X-ray diffraction, evidencing that Pt promoted the structural transformation of the starting anatase phase of TiO₂ to rutile, with a more enhanced effect with increasing the Pt concentration and/or the heat-treatment temperature. High-resolution transmission electron microscopy evidenced that, when a Pt:Ti atomic ratio of 0.05 and a heat treatment at 500 °C were used, the TiO₂ contained both anatase and rutile phases and interspersed Pt nanocrystals (2–3 nm). This result allowed attributing the structural transformation in TiO₂ to the strain created by the Pt nanocrystals—a conclusion which was further corroborated by the observation that Pd-modified films, prepared under similar conditions, were only composed of anatase TiO₂ and did not contain any Pd nanocrystals. The films heat-treated at 500 °C were able to withstand a full microelectronic processing sequence, including dry etching for gas sensors sensitive area definition, Ti/Pt contact formation, and heater processing on the backside of the sensor substrates. H₂ gas-sensing tests evidenced that the anatase TiO₂ phase was much more sensitive than the rutile one. The presence of Pt further enhanced the gas-sensing properties, lowering the optimum sensor operation temperature to about 330 °C and allowing for the detection of a minimum H₂ concentration of about 1000 ppm.     

Automated discrimination of dicentric and monocentric chromosomes by machine learning‐based image processing

Dose from radiation exposure can be estimated from dicentric chromosome (DC) frequencies in metaphase cells of peripheral blood lymphocytes. We automated DC detection by extracting features in Giemsa‐stained metaphase chromosome images and classifying objects by machine learning (ML). DC detection involves (i) intensity thresholded segmentation of metaphase objects, (ii) chromosome separation by watershed transformation and elimination of inseparable chromosome clusters, fragments and staining debris using a morphological decision tree filter, (iii) determination of chromosome width and centreline, (iv) derivation of centromere candidates, and (v) distinction of DCs from monocentric chromosomes (MC) by ML. Centromere candidates are inferred from 14 image features input to a Support Vector Machine (SVM). Sixteen features derived from these candidates are then supplied to a Boosting classifier and a second SVM which determines whether a chromosome is either a DC or MC. The SVM was trained with 292 DCs and 3135 MCs, and then tested with cells exposed to either low (1 Gy) or high (2‐4 Gy) radiation dose. Results were then compared with those of 3 experts. True positive rates (TPR) and positive predictive values (PPV) were determined for the tuning parameter, σ. At larger σ, PPV decreases and TPR increases. At high dose, for σ = 1.3, TPR = 0.52 and PPV = 0.83, while at σ = 1.6, the TPR = 0.65 and PPV = 0.72. At low dose and σ = 1.3, TPR = 0.67 and PPV = 0.26. The algorithm differentiates DCs from MCs, overlapped chromosomes and other objects with acceptable accuracy over a wide range of radiation exposures. Microsc. Res. Tech. 79:393–402, 2016. © 2016 Wiley Periodicals, Inc.     

Concept Formation in WWTP by Means of Classification Techniques: A Compared Study

Although activated sludge process is a very widely used biologicalprocess in wastewater treatment plants (WWTP), and there areproperly functioning control loops such as that of dissolved oxygen,in practice, this type of plant requires a major time investment onthe part of the operator, involving many manual operations.Treatment plants work well most of the time, as long as there are not unforeseen occurrences. Normal operatingsituations (generally similar to design conditions) can be treatedmathematically by using efficient control algorithms. However, there aresituations in which the control system cannot properlymanage the plant, and in which the process can only be efficiently managedthanks to the operators experience. This is a case in which aknowledge-based system may be useful. One of the difficulties inherent tothe development of a knowledge-based system is to obtain the knowledge base(i.e., knowledge acquisition), specially whendealing with a wide, complicated and ill-structured)field.Among the aims of this work arethose to show how semi-automatic knowledge acquisition tools could helphuman experts to organize their knowledge about their domain and also, tocompare the power of different approaches of knowledge acquisition) to the same database.In this paper are presented the results obtained fromapplying two different classification techniques to the development of knowledge-bases for the management of an activated sludge process.