Structural analysis and molecular model of a self-incompatibility RNase from wild tomato

Self-incompatibility RNases (S-RNases) are an allelic series of style glycoproteins associated with rejection of self-pollen in solanaceous plants. The nucleotide sequences of S-RNase alleles from several genera have been determined, but the structure of the gene products has only been described for those from Nicotiana alata. We report on the N-glycan structures and the disulfide bonding of the S-3-RNase from wild tomato (Lycopersicon peruvianum) and use this and other information to construct a model of this molecule. The S-3-RNase has a single N-glycosylation site (Asn-28) to which one of three N-glycans is attached. S-3-RNase has seven Cys residues; six are involved in disulfide linkages (Cys-16-Cys-21, Cys-46-Cys-91, and Cys-166-Cys-177), and one has a free thiol group (Cys-150). The disulfide-bonding pattern is consistent with that observed in RNase Rh, a related RNase for which radiographic-crystallographic information is available. A molecular model of the S-3-RNase shows that four of the most variable regions of the S-RNases are clustered on one surface of the molecule. This is discussed in the context of recent experiments that set out to determine the regions of the S-RNase important for recognition during the self-incompatibility response.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

Prediction of the chemical composition of lamb carcasses from multi-frequency impedance data

Multi-frequency bioimpedance analysis (MFBIA) was used to determine the impedance, reactance and resistance of 103 lamb carcasses (17.1-34.2 kg) immediately after slaughter and evisceration. Carcasses were halved, frozen and one half subsequently homogenized and analysed for water, crude protein and fat content. Three measures of carcass length were obtained. Diagonal length between the electrodes (right side biceps femoris to left side of neck) explained a greater proportion of the variance in water mass than did estimates of spinal length and was selected for use in the index L-2/Z to predict the mass of chemical components in the carcass. Use of impedance (Z) measured at the characteristic frequency (Z(c)) instead of 50 kHz (Z(50)) did not improve the power of the model to predict the mass of water, protein or fat in the carcass. While L-2/Z(50) explained a significant proportion of variation in the masses of body water (r(2) 0.64), protein (r(2) 0.34) and fat (r(2) 0.35), its inclusion in multi-variate indices offered small or no increases in predictive capacity when hot carcass weight (HCW) and a measure of rib fat-depth (GR) were present in the model. Optimized equations were able to account for 65-90 % of the variance observed in the weight of chemical components in the carcass. It is concluded that single frequency impedance data do not provide better prediction of carcass composition than can be obtained from measures of HCW and GR. Indices of intracellular water mass derived from impedance at zero frequency and the characteristic frequency explained a similar proportion of the variance in carcass protein mass as did the index L-2/Z(50).

Analysis and application of an equilibrium model for in vitro bioassay systems with three components: Receptor, hormone and hormone-binding-protein

A simple theoretical framework is presented for bioassay studies using three component in vitro systems. An equilibrium model is used to derive equations useful for predicting changes in biological response after addition of hormone-binding-protein or as a consequence of increased hormone affinity. Sets of possible solutions for receptor occupancy and binding protein occupancy are found for typical values of receptor and binding protein affinity constants. Unique equilibrium solutions are dictated by the initial condition of total hormone concentration. According to the occupancy theory of drug action, increasing the affinity of a hormone for its receptor will result in a proportional increase in biological potency. However, the three component model predicts that the magnitude of increase in biological potency will be a small fraction of the proportional increase in affinity. With typical initial conditions a two-fold increase in hormone affinity for its receptor is predicted to result in only a 33% increase in biological response. Under the same conditions an Ii-fold increase in hormone affinity for receptor would be needed to produce a two-fold increase in biological potency. Some currently used bioassay systems may be unrecognized three component systems and gross errors in biopotency estimates will result if the effect of binding protein is not calculated. An algorithm derived from the three component model is used to predict changes in biological response after addition of binding protein to in vitro systems. The algorithm is tested by application to a published data set from an experimental study in an in vitro system (Lim et al., 1990, Endocrinology 127, 1287-1291). Predicted changes show good agreement (within 8%) with experimental observations. (C) 1998 Academic Press Limited.

Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

A mathematical model of HIV transmission in NSW prisons

A mathematical model was developed to estimate HIV incidence in NSW prisons. Data included: duration of imprisonment; number of inmates using each needle; lower and higher number of shared injections per IDU per week; proportion of IDUs using bleach; efficacy of bleach; HIV prevalence and probability of infection. HIV prevalence in IDUs in prison was estimated to have risen from 0.8 to 5.7% (12.2%) over 180 weeks when using lower (and higher) values for frequency of shared injections. The estimated minimum (and maximum) number of IDU inmates infected with HIV in NSW prisons was 38 (and 152) in 1993 according to the model. These figures require confirmation by seroincidence studies. (C) 1998 Published by Elsevier Science Ireland Ltd. All rights reserved.

Th2-type CD4(+) cells neither enhance nor suppress antitumor CTL activity in a mouse tumor model

Many cervical cancers express the E7 protein of human papillomavirus 16 as a tumor-specific Ag (TSA). To establish the role of E7-specific T cell help in CD8(+) CTL-mediated tumor regression, C57BL/6J mice were immunized with E7 protein or with a peptide (GF001) comprising a minimal CTL epitope of E7, together with different adjuvants, Immunized mice were challenged with an E7-expressing tumor cell line, EL4.E7. Growth of EL4.E7 was reduced following immunization with E7 and Quil-A (an adjuvant that induced a Th1-type response to E7) or with GF001 and Quil-A, Depletion of CD8(+) cells, but not CD4(+) cells, from an immunized animal abrogated protection, confirming that E7-specific CTL are necessary and sufficient for TSA-specific protection in this model. Immunization with E7 and Algammulin (an alum-based adjuvant) induced a Th2-like response and provided; no tumor protection. To investigate whether a Th2 T helper response to E7 could prevent the development of an E7-specific CTL-mediated protection, mice were simultaneously immunized with E7/Algammulin and GF001/Quil-A or, alternatively, were immunized with GF011/Quil-A 8 wk after immunization with E7/Algammulin, Tumor protection was observed in each case. We conclude that an established Th2 response to a TSA does not prevent the development of TSA-specific tumor protective CTL.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Dendritic cells in rheumatoid arthritis - A model autoimmune inflammatory site

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease in which unknown arthrogenic autoantigen is presented to CD4+ T cells. The strong association of the disease with an epitope within the HLA-DR chain shared between various alleles of HLA-DR4 and DR1 emphasizes the importance of antigen presentation. This immune response predominantly occurs in the synovial tissue and fluid of the joints and autoreactive T cells are readily demonstrable in both the synovial compartment and blood. Circulating dendritic cells (DC) are phenotypically and functionally identical with normal peripheral blood (PB) DC. In the synovial tissue, fully differentiated perivascular DC are found in close association with T cells and with B cell follicles, sometimes containing follicular DC. These perivascular DC migrate across the activated endothelium from blood and receive differentiative signals within the joint from monocyte-derived cytokines and CD40-ligand+ T cells. In the SF, DC manifest an intermediate phenotype, similar to that of monocyte-derived DC in vitro. Like a delayed-type hypersensitivity response, the rheumatoid synovium represents an effector site. DC at many effector sites have a characteristic pattern of infiltration and differentiation. It is important to note that the effector response is not self-limiting in RA autoimmune inflammation. In this article, we argue that the presentation of self-antigen by DC and by autoantibody-producing B cells is critical for the perpetuation of the autoimmune response. Permanently arresting this ongoing immune response with either pharmaceutical agents or immunotherapy is a major challenge for immunology.

Response of a two-level atom to a narrow-bandwidth squeezed-vacuum excitation

Using the coupled-system approach we calculate the optical spectra of the fluorescence and transmitted fields of a two-level atom driven by a squeezed vacuum of bandwidths smaller than the natural atomic linewidth. We find that in this regime of squeezing bandwidths the spectra exhibit unique features, such as a hole burning and a three-peak structure, which do not appear for a broadband excitation. We show that the features are unique to the quantum nature of the driving squeezed vacuum field and donor appear when the atom is driven by a classically squeezed field. We find that a quantum squeezed-vacuum field produces squeezing in the emitted fluorescence field which appears only in the squeezing spectrum while there is no squeezing in the total field. We also discuss a nonresonant excitation and find that depending on the squeezing bandwidth there is a peak or a hole in the spectrum at a frequency corresponding to a three-wave-mixing process. The hole appears only for a broadband excitation and results from the strong correlations between squeezed-vacuum photons.

Response to price and production risk: The case of Australian wheat

A model of Australian wheat grower supply response was specified under the constraints of price and yield uncertainty, risk aversion, partial adjustment, and quadratic costs. The model was solved to obtain area planted. The results of estimation indicate that risk arising from prices and climate have had a significant influence on producer decision making. The coefficient of relative risk aversion and short-run and long-run elasticities of supply with respect to price were calculated. Wheat growers' risk premium, expected at the start of the season for exposed price and yield risk, was 2.8 percent of revenue or 10.4 percent of profit as measured by producer surplus. (C) 2000 John Wiley & Sons, Inc.

The anti-tumor activity of IL-12: Mechanisms of innate immunity that are model and dose dependent

IL-12 has been demonstrated to have potent anti-tumor activities in a variety of mouse tumor models, but the relative roles of NK, NKT, and T cells and their effector mechanisms in these responses have not been fully addressed. Using a spectrum of gene-targeted or Ab-treated mice we have shown that for any particular tumor model the effector mechanisms downstream of IL-12 often mimic the natural immune response to that tumor. For example, metastasis of the MHC class I-deficient lymphoma, EL4-S3, was strictly controlled by NK cells using perforin either naturally or following therapy with high-dose IL-12. Intriguingly, in B16F10 and RM-1 tumor models both NK and NKT cells contribute to natural protection from tumor metastasis, In these models, a lower dose of IL-12 or delayed administration of IL-12 dictated a greater relative role of NKT cells in immune protection from tumor metastasis. Overall, both NK and NKT cells can contribute to natural and IL-12-induced immunity against tumors, and the relative role of each population is turner and therapy dependent.

A context noise model of episodic word recognition

Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.

On the theory of mixing-frequency electron spin-echo envelope modulation spectroscopy

It has recently been stated that the parametrization of the time variables in the one-dimensional (I-D) mixing-frequency electron spin-echo envelope modulation (MIF-ESEEM) experiment is incorrect and hence the wrong frequencies for correlated nuclear transitions are predicted. This paper is a direct response to such a claim, its purpose being to show that the parametrization in land 2-D MIF-ESEEM experiments possesses the same form as that used in other 4-pulse incrementation schemes and predicts the same correlation frequencies. We show that the parametrization represents a shearing transformation of the 2-D time-domain and relate the resulting frequency domain spectrum to the HYSCORE spectrum in terms of a skew-projection. It is emphasized that the parametrization of the time-domain variables may be chosen arbitrarily and affects neither the computation of the correct nuclear frequencies nor the resulting resolution. The usefulness or otherwise of the MIF parameters \gamma\ > 1 is addressed, together with the validity of the original claims of the authors with respect to resolution enhancement in cases of purely homogeneous and inhomogeneous broadening. Numerical simulations are provided to illustrate the main points.

ERP 'old/new' effects: memory strength and decisional factor(s)

Event-related potentials (ERPs) were recorded while subjects made old/new recognition judgments on new unstudied words and old words which had been presented at study either once ('weak') or three times ('strong'). The probability of an 'old' response was significantly higher for strong than weak words and significantly higher for weak than new words. Comparisons were made initially between ERPs to new, weak and strong words, and subsequently between ERPs associated with six strength-by-response conditions. The N400 component was found to be modulated by memory trace strength in a graded manner. Its amplitude was most negative in new word ERPs and most positive in strong word ERPs. This 'N400 strength effect' was largest at the left parietal electrode (in ear-referenced ERPs). The amplitude of the late positive complex (LPC) effect was sensitive to decision accuracy (and perhaps confidence). Its amplitude was larger in ERPs evoked by words attracting correct versus incorrect recognition decisions. The LPC effect had a left > right, centro-parietal scalp topography (in ear-referenced ERPs). Hence, whereas, the majority of previous ERP studies of episodic recognition have interpreted results from the perspective of dual-process models, we provide alternative interpretations of N400 and LPC old/new effects in terms of memory strength and decisional factor(s). (C) 2002 Elsevier Science Ltd. All rights reserved.