Identification of a novel serum protein secreted by lung carcinoma cells

The murine anti-human lung tumor monoclonal antibody L3 recognizes antigens found both in the medium of cultured carcinoma cells and in normal human serum. Sequential immunoprecipitation experiments indicate that the L3 antigen is also recognized by a previously described monoclonal antibody directed against a melanoma-associated antigen [Natali, P. G., Wilson, B. S., Imai, K., Bigotti, A., & Ferrone, S. (1982) Cancer Res. 42, 583-589]. This antibody precipitated a Mr 76000 glycoprotein from metabolically labeled extracts of the lung carcinoma cell line Calu-1 and a Mr 94 000 glycoprotein from labeled culture medium. Pulse-chase experiments suggested a precursor-product relationship between these molecules. Analysis of glycosidase sensitivities of the two forms indicated that maturation of carbohydrate side chains correlated with the apparent increase in molecular weights. L3 antigenic activity, measured in a competitive radiometric cell binding assay, was purified more than 90-fold from serum-free medium of Calu-1 cells and more than 3000-fold from normal human serum. The major immunoreactive components purified from culture medium and serum were identical with respect to apparent molecular weight, electrophoretic mobility, pI, glycosidase sensitivity, and V8 protease fingerprints. In addition, the sequence of the amino-terminal 16 N-terminal amino acid residues of the major immunoreactive species from both sources was identical. The properties of the L3 antigen did not correspond to those of any known protein, suggesting that this serum protein has not been previously characterized.     

B7 costimulates proliferation of CD4-8+ T lymphocytes but is not required for the deletion of immature CD4+8+ thymocytes.

In addition to TCR-derived signals, costimulatory signals derived from stimulation of the CD28 molecule by its natural ligand, B7, have been shown to be required for CD4+8- T cell activation. We investigate the ability of B7 to provide costimulatory signals necessary to drive proliferation and differentiation of virgin CD4-8+ T-cells that express a transgenic TCR specific for the male (H-Y) Ag presented by H-2Db class I MHC molecules. Virgin male-specific CD4-8+ T cells can be activated either with B7 transfected chinese hamster ovary (CHO) cells and T3.70, a mAb specific for the transgenic TCR-alpha chain that is associated with male-reactivity, or by male dendritic cells (DC). Activated CD4-8+ T cells proliferated in the absence of exogenously added IL-2. IL-2 activity was detected in supernatants of CD4-8+T3.70+ cells that were stimulated with T3.70 and B7+CHO cells. The response of CD4-8+T3.70+ cells to T3.70/B7+CHO or to male DC stimulation were inhibited by CTLA4Ig, a fusion protein comprising the extracellular portion of CTLA4 and human IgG C gamma 1. It has been previously shown that CTLA4Ig binds B7 with high affinity. Staining with CTLA4Ig revealed that DC express about 50 times more B7 than CD4-8+ T cells. CTLA4Ig also specifically blocked the proliferation of male-reactive cells in vivo. We have also used an in vitro deletion assay whereby immature CD4+8+ thymocytes expressing the transgenic male-specific TCR are deleted by overnight incubation with either immobilized T3.70 or male DC to investigate the participation of the CD28/B7 pathway in the negative selection of immature thymocytes. Staining with B7Ig established that both immature murine CD4+8+ and mature CD4-8+ thymocytes express a high level of CD28. However, despite the high expression of CD28 on CD4+8+ thymocytes, it was found that deletion of CD4+8+ thymocytes expressing the male-specific TCR by the T3.70 mAb was not inhibited by B7+CHO cells. Furthermore, the deletion of these thymocytes by DC also was not inhibited by CTLA4Ig. These findings provide evidence that although signaling through CD28 can costimulate a primary anti-male response in mature CD4-8+ T cells, the CD28/B7 pathway does not appear to participate in the negative selection of immature CD4+8+ thymocytes.     

Last‐century changes of alpine grassland water‐use efficiency: a reconstruction through carbon isotope analysis of a time‐series of Capra ibex horns

The ecophysiological response of an alpine grassland to recent climate change and increasing atmospheric CO₂ concentration was investigated with a new strategy to go back in time: using a time‐series of Capra ibex horns as archives of the alpine grasslands' carbon isotope discrimination (¹³Δ). From the collection of the Natural History Museum of Bern, horns of 24 males from the population of the Augstmatthorn–Brienzer Rothorn mountains, Switzerland, were sampled covering the period from 1938 to 2006. Samples were taken from the beginning of each year‐ring of the horns, representing the beginning of the horn growth period, the spring. The horns' carbon ¹³C content (Δ¹³C) declined together with that of atmospheric CO₂ over the 69‐year period, but ¹³Δ increased slightly (+0.4‰), though significantly (P<0.05), over the observation period. Estimated intercellular CO₂ concentration increased (+56 μmol mol^?1) less than the atmospheric CO₂ concentration (+81 μmol mol^?1), so that intrinsic water‐use efficiency increased by 17.8% during the 69‐year period. However, the atmospheric evaporative demand at the site increased by approximately 0.1 kPa between 1955 and 2006, thus counteracting the improvement of intrinsic water‐use efficiency. As a result, instantaneous water‐use efficiency did not change. The observed changes in intrinsic water‐use efficiency were in the same range as those of trees (as reported by others), indicating that leaf‐level control of water‐use efficiency of grassland and forests followed the same principles. This is the first reconstruction of the water‐use efficiency response of a natural grassland ecosystem to last century CO₂ and climatic changes. The results indicate that the alpine grassland community has responded to climate change by improving the physiological control of carbon gain to water loss, following the increases in atmospheric CO₂ and evaporative demand. But, effective leaf‐level water‐use efficiency has remained unchanged.     

Machine learning techniques in disease forecasting: a case study on rice blast prediction

Background  

Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases.     

Median absolute deviation to improve hit selection for genome-scale RNAi screens

High-throughput screening (HTS) of large-scale RNA interference (RNAi) libraries has become an increasingly popular method of functional genomics in recent years. Cell-based assays used for RNAi screening often produce small dynamic ranges and significant variability because of the combination of cellular heterogeneity, transfection efficiency, and the intrinsic nature of the genes being targeted. These properties make reliable hit selection in the RNAi screen a difficult task. The use of robust methods based on median and median absolute deviation (MAD) has been suggested to improve hit selection in such cases, but mean and standard deviation (SD)-based methods are still predominantly used in many RNAi HTS. In an experimental approach to compare these 2 methods, a genome-scale small interfering RNA (siRNA) screen was performed, in which the identification of novel targets increasing the therapeutic index of the chemotherapeutic agent mitomycin C (MMC) was sought. MAD values were resistant to the presence of outliers, and the hits selected by the MAD-based method included all the hits that would be selected by SD-based method as well as a significant number of additional hits. When retested in triplicate, a similar percentage of these siRNAs were shown to genuinely sensitize cells to MMC compared with the hits shared between SD- and MAD-based methods. Confirmed hits were enriched with the genes involved in the DNA damage response and cell cycle regulation, validating the overall hit selection strategy. Finally, computer simulations showed the superiority and generality of the MAD-based method in various RNAi HTS data models. In conclusion, the authors demonstrate that the MAD-based hit selection method rescued physiologically relevant false negatives that would have been missed in the SD-based method, and they believe it to be the desirable 1st-choice hit selection method for RNAi screen results.