REQUIREMENT OF THYMUS (T) LYMPHOCYTES FOR RESISTANCE TO LISTERIOSIS

Spleen cells of mice infected with Listeria monocytogenes were adoptively transferred to normal mice. Such lymphocytes conferred resistance to a lethal challenge with Listeria. Hyperimmunization of the donor reduces the number of cells necessary to transfer effective immunity. Such spleen cells if treated with anti-θ serum do not transfer resistance to Listeria. Hence, thymus (T) lymphocytes are involved in the resistance to infection with the facultative intracellular bacteria L. monocytogenes

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition

© 2017 Elsevier Inc. Background Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text “feature engineering” and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word “embeddings”. Objectives (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Methods Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. Results We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. Conclusions We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary

ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems

Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (ReWE) as a new regularization technique in a system that is jointly trained to predict the next word in the translation (categorical value) and its word embedding (continuous value). Such a joint training allows the proposed system to learn the distributional properties represented by the word embeddings, empirically improving the generalization to unseen sentences. Experiments over three translation datasets have showed a consistent improvement over a strong baseline, ranging between 0.91 and 2.54 BLEU points, and also a marked improvement over a state-of-the-art system.Comment: Accepted at NAACL-HLT 201

Diesel Multiple Unit Class 7023 for Regional Passenger Transport

U ovom radu opisan je novi dizel-motorni vlak serije 7023. Obrađena je i proučena prometna potražnja u regionalnom prometu na neelektrificiranim prugama. Također je proučena struktura i stanje dize-motornih vlakova HŽ Putničkog prijevoza iz koje je vidljivo da je bilo potrebno naručiti nove vlakove za regionalni putnički prijevoz. U radu je prikazana osnovna koncepcija dizel-motornih vlakova, te su za kraj prikazani tehnički podaci i kočenje DMV-a 7023.In this piece of work is describes a new diesel multiple unit class 7023. The structure and stte of diesel multiple unit has also been studied and it is apparent that it was necessary to order new trains for regional traffic. In this piece of work is presented concept of diesel motor trains and tehnical data and braking of diesel multiple unit class 7023

The Role of I Region Gene Products in Macrophage - T Lymphocyte Interaction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73965/1/j.1600-065X.1978.tb00400.x.pd

Phagocytosis in the retina promotes local insulin production in the eye

The retina is highly metabolically active, relying on glucose uptake and aerobic glycolysis. Situated in close contact to photoreceptors, a key function of cells in the retinal pigment epithelium (RPE) is phagocytosis of damaged photoreceptor outer segments (POS). Here we identify RPE as a local source of insulin in the eye that is stimulated by POS phagocytosis. We show that Ins2 messenger RNA and insulin protein are produced by RPE cells and that this production correlates with RPE phagocytosis of POS. Genetic deletion of phagocytic receptors (‘loss of function’) reduces Ins2, whereas increasing the levels of the phagocytic receptor MerTK (‘gain of function’) increases Ins2 production in male mice. Contrary to pancreas-derived systemic insulin, RPE-derived local insulin is stimulated during starvation, which also increases RPE phagocytosis. Global or RPE-specific Ins2 gene deletion decreases retinal glucose uptake in starved male mice, dysregulates retinal physiology, causes defects in phototransduction and exacerbates photoreceptor loss in a mouse model of retinitis pigmentosa. Collectively, these data identify RPE cells as a phagocytosis-induced local source of insulin in the retina, with the potential to influence retinal physiology and disease