Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Computer-simulation study of magnetic relaxation in anisotropic magnetic systems

We present a computer-simulation study of the effect of the distribution of energy barriers in an anisotropic magnetic system on the relaxation behavior of the magnetization. While the relaxation law for the magnetization can be approximated in all cases by a time logarithmic decay, the law for the dependence of the magnetic viscosity with temperature is found to be quite sensitive to the shape of the distribution of barriers. The low-temperature region for the magnetic viscosity never extrapolates to a positive no-null value. Moreover our computer simulation results agree reasonably well with some recent relaxation experiments on highly anisotropic single-domain particles.

Concurrent or sequential adjuvant letrozole and radiotherapy after conservative surgery for early-stage breast cancer (CO-HO-RT): a phase 2 randomised trial.

BACKGROUND: Letrozole radiosensitises breast cancer cells in vitro. In clinical settings, no data exist for the combination of letrozole and radiotherapy. We assessed concurrent and sequential radiotherapy and letrozole in the adjuvant setting. METHODS: This phase 2 randomised trial was undertaken in two centres in France and one in Switzerland between Jan 12, 2005, and Feb 21, 2007. 150 postmenopausal women with early-stage breast cancer were randomly assigned after conserving surgery to either concurrent radiotherapy and letrozole (n=75) or sequential radiotherapy and letrozole (n=75). Randomisation was open label with a minimisation technique, stratified by investigational centres, chemotherapy (yes vs no), radiation boost (yes vs no), and value of radiation-induced lymphocyte apoptosis (< or = 16% vs >16%). Whole breast was irradiated to a total dose of 50 Gy in 25 fractions over 5 weeks. In the case of supraclavicular and internal mammary node irradiation, the dose was 44-50 Gy. Letrozole was administered orally once daily at a dose of 2.5 mg for 5 years (beginning 3 weeks pre-radiotherapy in the concomitant group, and 3 weeks post-radiotherapy in the sequential group). The primary endpoint was the occurrence of acute (during and within 6 weeks of radiotherapy) and late (within 2 years) radiation-induced grade 2 or worse toxic effects of the skin. Analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00208273. FINDINGS: All patients were analysed apart from one in the concurrent group who withdrew consent before any treatment. During radiotherapy and within the first 12 weeks after radiotherapy, 31 patients in the concurrent group and 31 in the sequential group had any grade 2 or worse skin-related toxicity. The most common skin-related adverse event was dermatitis: four patients in the concurrent group and six in the sequential group had grade 3 acute skin dermatitis during radiotherapy. At a median follow-up of 26 months (range 3-40), two patients in each group had grade 2 or worse late effects (both radiation-induced subcutaneous fibrosis). INTERPRETATION: Letrozole can be safely delivered shortly after surgery and concomitantly with radiotherapy. Long-term follow-up is needed to investigate cardiac side-effects and cancer-specific outcomes. FUNDING: Novartis Oncology France.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Concurrent or Sequential Adjuvant Letrozole and Radiotherapy after Conservative Surgery for Early-stage Breast Cancer: Long-term Results of the Cohort Phase 2 Randomized Trial

Purpose/Objective(s): Letrozole radiosensitizes breast cancer cells in vitro. In clinical settings, no data exist for the combination of letrozole and radiotherapy. We assessed concurrent and sequential radiotherapy and letrozole in the adjuvant setting.Materials/Methods: The present study is registered with ClinicalTrials.gov, number NCT00208273. This Phase 2 randomized trial was undertaken in two centers in France and one in Switzerland between January 12, 2005, and February 21, 2007. One hundred fifty postmenopausal women with early-stage breast cancer were randomly assigned after conserving surgery to either concurrent radiotherapy and letrozole (n = 75) or sequential radiotherapy and letrozole (n = 75). Randomization was open label with a minimization technique, stratified by investigational centers, chemotherapy (yes vs. no), radiation boost (yes vs. no), and value of radiation-induced lymphocyte apoptosis (#16% vs. .16%). The whole breast was irradiated to a total dose of 50 Gy in 25 fractions over 5 weeks. In the case of supraclavicular and internal mammary node irradiation, the dose was 44 - 50 Gy. Letrozole was administered orally once daily at a dose of 2 - 5 mg for 5 years (beginning 3 weeks pre-radiotherapy in the concomitant group, and 3 weeks postradiotherapy in the sequential group). The primary endpoint was the occurrence of acute (during and within 6 weeks of radiotherapy) and late (within 2 years) radiation-induced Grade 2 or worse toxic effects of the skin and lung (functional pulmonary test and lung CT-scan). Analyses were by intention-to-treat. The long-term follow-up after 2 years was only performed in Montpellier (n = 121) and evaluated skin toxicity (clinical examination every 6 months), lung fibrosis (one CT-scan yearly), cosmetic outcome.Results: All patients were analyzed apart from 1 in the concurrent group who withdrew consent before any treatment.Within the first 2 years (n = 149), no lung toxicity was identified by CT scan and no modification from baseline was noted by the lung diffusion capacity test. Two patients in each group had Grade 2 or worse late effects (both radiation-induced subcutaneous fibrosis [RISF]). After 2 years (n = 121), and with a median follow-up of 50 months (38-62), 2 patients (1 in each arm) presented a Grade 3 RISF. No lung toxicity was identified by CT scan. Cosmetic results (photographies) and quality of life was good to excellent. All patients who had Grade 3 subcutaneous fibrosis had an RILA value of 16% or less, irrespective of the sequence with letrozole.Conclusions:With long-term follow-up, letrozole can be safely delivered shortly after surgery and concomitantly with radiotherapy.

Individual-based modelling and simulation: towards a better understanding of growth dynamics from small inocula

Postprint (published version)

Energy-based modelling and simulation of the interconnection of a back-to-back converter and a doubly-fed induction machine

This paper describes the port interconnection of two subsystems: a power electronics subsystem (a back-to-back AC/CA converter (B2B), coupled to a phase of the power grid), and an electromechanical subsystem (a doubly-fed induction machine (DFIM). The B2B is a variable structure system (VSS), due to presence of control-actuated switches: however, from a modelling simulation, as well as a control-design, point of view, it is sensible to consider modulated transformers (MTF in the bond graph language) instead of the pairs of complementary switches. The port-Hamiltonian models of both subsystems are presented and, using a power-preserving interconnection, the Hamiltonian description of the whole system is obtained; detailed bond graphs of all subsystems and the complete system are also provided. Using passivity-based controllers computed in the Hamiltonian formalism for both subsystems, the whole model is simulated; simulations are run to rest the correctness and efficiency of the Hamiltonian network modelling approach used in this work.

General electromagnetic simulation tool to predict the microwave nonlinear response of planar, arbitrarily-shaped HTS structures

This work describes a simulation tool being developed at UPC to predict the microwave nonlinear behavior of planar superconducting structures with very few restrictions on the geometry of the planar layout. The software is intended to be applicable to most structures used in planar HTS circuits, including line, patch, and quasi-lumped microstrip resonators. The tool combines Method of Moments (MoM) algorithms for general electromagnetic simulation with Harmonic Balance algorithms to take into account the nonlinearities in the HTS material. The Method of Moments code is based on discretization of the Electric Field Integral Equation in Rao, Wilton and Glisson Basis Functions. The multilayer dyadic Green's function is used with Sommerfeld integral formulation. The Harmonic Balance algorithm has been adapted to this application where the nonlinearity is distributed and where compatibility with the MoM algorithm is required. Tests of the algorithm in TM010 disk resonators agree with closed-form equations for both the fundamental and third-order intermodulation currents. Simulations of hairpin resonators show good qualitative agreement with previously published results, but it is found that a finer meshing would be necessary to get correct quantitative results. Possible improvements are suggested.

The Gaussian assumption in second-order estimation problems in digital communications

This paper deals with the goodness of the Gaussian assumption when designing second-order blind estimationmethods in the context of digital communications. The low- andhigh-signal-to-noise ratio (SNR) asymptotic performance of the maximum likelihood estimator—derived assuming Gaussiantransmitted symbols—is compared with the performance of the optimal second-order estimator, which exploits the actualdistribution of the discrete constellation. The asymptotic study concludes that the Gaussian assumption leads to the optimalsecond-order solution if the SNR is very low or if the symbols belong to a multilevel constellation such as quadrature-amplitudemodulation (QAM) or amplitude-phase-shift keying (APSK). On the other hand, the Gaussian assumption can yield importantlosses at high SNR if the transmitted symbols are drawn from a constant modulus constellation such as phase-shift keying (PSK)or continuous-phase modulations (CPM). These conclusions are illustrated for the problem of direction-of-arrival (DOA) estimation of multiple digitally-modulated signals.

Joint array combining and MLSE for single-user receivers in multipath Gaussian multiuser channels

The well-known structure of an array combiner along with a maximum likelihood sequence estimator (MLSE) receiveris the basis for the derivation of a space-time processor presentinggood properties in terms of co-channel and intersymbol interferencerejection. The use of spatial diversity at the receiver front-endtogether with a scalar MLSE implies a joint design of the spatialcombiner and the impulse response for the sequence detector. Thisis faced using the MMSE criterion under the constraint that thedesired user signal power is not cancelled, yielding an impulse responsefor the sequence detector that is matched to the channel andcombiner response. The procedure maximizes the signal-to-noiseratio at the input of the detector and exhibits excellent performancein realistic multipath channels.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

Effects of preset sequential administrations of sunitinib and everolimus on tumour differentiation in Caki-1 renal cell carcinoma.

BACKGROUND: Sunitinib (VEGFR/PDGFR inhibitor) and everolimus (mTOR inhibitor) are both approved for advanced renal cell carcinoma (RCC) as first-line and second-line therapy, respectively. In the clinics, sunitinib treatment is limited by the emergence of acquired resistance, leading to a switch to second-line treatment at progression, often based on everolimus. No data have been yet generated on programmed alternating sequential strategies combining alternative use of sunitinib and everolimus before progression. Such strategy is expected to delay the emergence of acquired resistance and improve tumour control. The aim of our study was to assess the changes in tumours induced by three different sequences administration of sunitinib and everolimus. METHODS: In human Caki-1 RCC xenograft model, sunitinib was alternated with everolimus every week, every 2 weeks, or every 3 weeks. Effects on necrosis, hypoxia, angiogenesis, and EMT status were assessed by immunohisochemistry and immunofluorescence. RESULTS: Sunitinib and everolimus programmed sequential regimens before progression yielded longer median time to tumour progression than sunitinib and everolimus monotherapies. In each group of treatment, tumour growth control was associated with inhibition of mTOR pathway and changes from a mesenchymal towards an epithelial phenotype, with a decrease in vimentin and an increase in E-cadherin expression. The sequential combinations of these two agents in a RCC mouse clinical trial induced antiangiogenic effects, leading to tumour necrosis. CONCLUSIONS: In summary, our study showed that alternate sequence of sunitinib and everolimus mitigated the development of mesenchymal phenotype compared with sunitinib as single agent.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.