Post-processing through linear regression

Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred

Trading interactions for topology in scale-free networks

Scale-free networks with topology-dependent interactions are studied. It is shown that the universality classes of critical behavior, which conventionally depend only on topology, can also be explored by tuning the interactions. A mapping, $\gamma' = (\gamma - \mu)/(1-\mu)$, describes how a shift of the standard exponent $\gamma$ of the degree distribution $P(q)$ can absorb the effect of degree-dependent pair interactions $J_{ij} \propto (q_iq_j)^{-\mu}$. Replica technique, cavity method and Monte Carlo simulation support the physical picture suggested by Landau theory for the critical exponents and by the Bethe-Peierls approximation for the critical temperature. The equivalence of topology and interaction holds for equilibrium and non-equilibrium systems, and is illustrated with interdisciplinary applications.Comment: 4 pages, 5 figure

Ising model for distribution networks

An elementary Ising spin model is proposed for demonstrating cascading failures (break-downs, blackouts, collapses, avalanches, ...) that can occur in realistic networks for distribution and delivery by suppliers to consumers. A ferromagnetic Hamiltonian with quenched random fields results from policies that maximize the gap between demand and delivery. Such policies can arise in a competitive market where firms artificially create new demand, or in a solidary environment where too high a demand cannot reasonably be met. Network failure in the context of a policy of solidarity is possible when an initially active state becomes metastable and decays to a stable inactive state. We explore the characteristics of the demand and delivery, as well as the topological properties, which make the distribution network susceptible of failure. An effective temperature is defined, which governs the strength of the activity fluctuations which can induce a collapse. Numerical results, obtained by Monte Carlo simulations of the model on (mainly) scale-free networks, are supplemented with analytic mean-field approximations to the geometrical random field fluctuations and the thermal spin fluctuations. The role of hubs versus poorly connected nodes in initiating the breakdown of network activity is illustrated and related to model parameters

Randomised comparison of initial triple DMARD therapy with methotrexate monotherapy in combination with low-dose glucocorticoid bridging therapy; 1-year data of the tREACH trial

Objectives To compare 1-year clinical efficacy of (1) initial triple disease-modifying antirheumatic drug therapy (iTDT) with initial methotrexate (MTX) monotherapy (iMM) and (2) different glucocorticoid (GC) bridging therapies: oral versus a single intramuscular injection in early rheumatoid arthritis. Methods In a single-blinded randomised clinical trial patients were randomised into three arms: (A) iTDT (methotrexate+sulfasalazine+hydroxychloroquine) with GCs intramuscularly; (B) iTDT with an oral GC tapering scheme and (C) MTX with oral GCs similar to B. Primary outcomes were (1) area under the curve (AUC) of Health Assessment Questionnaire (HAQ) and Disease Activity Score (DAS) and (2) the proportion of patients with radiographic progression. Results 281 patients were randomly assigned to arms A (n=91), B (n=93) or C (n=97). The AUC DAS and HAQ were respectively -2.39 (95% CI -4.77 to -0.00) and -1.67 (95% CI -3.35 to 0.02) lower in patients receiving iTDT than in those receiving iMM. After 3 months, treatment failure occurred less often in the iTDT group, resulting in 40% fewer treatment intensifications. The difference in treatment intensifications between the arms required to maintain the predefined treatment goal remained over time. No differences were seen between the two GC bridging therapies. Respectively 21%, 24% and 23% of patients in arms A, B and C had radiographic progression after 1 year. Patients receiving iTDT had more adjustments of their medication owing to adverse events than those receiving iMM. Conclusions Treatment goals are attained more quickly and maintained with fewer treatment intensifications with iTDT than with iMM. However, no difference in radiographic progression is seen. Both GC bridging therapies are equally effective and, therefore, both can be used

Impacts of climate change and vegetation response on future aridity in a Mediterranean catchment

The climate in the Mediterranean region is expected to become warmer and drier but future projections of precipitation are uncertain, especially in the Northern part. Additionally, the difficulty in determining the plant physiological responses caused by CO2 rising complicates the estimation of future evaporative demand, increasing the uncertainty of future aridity assessments. Vegetation responses to rising CO2 are expected to increase radiation use efficiency and reduce stomatal conductance, hence increasing plant's water use efficiency. These effects are often neglected when estimating future drought and aridity. Hence, the main objective of this study is to estimate the effect of climate change and vegetation stomatal conductance reduction on projected water balance components and the resulting impact on aridity in a medium-sized catchment of Central Italy. We validate and couple a hydrological model with climate projections from five regional climate models and perform simulations considering the vegetation responses or not. Results show that their inclusion significantly affects potential evapotranspiration. The other water balance components, namely actual evapotranspiration, water yield, percolation, and irrigation, are also influenced but with less significant changes. Considering or not the CO2 suppression effect on stomatal conductance, coupled with the uncertainty related to precipitation, highly affects the estimation of future aridity as the future climate classification ranges from “humid” to “semi-arid” depending on the simulation and climate model, even if model outputs need to be evaluated cautiously with CO2 concentration higher than 660 ppm

Immune-derived PD-L1 gene expression defines a subgroup of stage II/III colorectal cancer patients with favorable prognosis that may be harmed by adjuvant chemotherapy

Abstract A recent phase II study of patients with metastatic colorectal carcinoma showed that mismatch repair gene status was predictive of clinical response to PD-1–targeting immune checkpoint blockade. Further examination revealed strong correlation between PD-L1 protein expression and microsatellite instability (MSI) in stage IV colorectal carcinoma, suggesting that the amount of PD-L1 protein expression could identify late-stage patients who might benefit from immunotherapy. To assess whether the clinical associations between PD-L1 gene expression and MSI identified in metastatic colorectal carcinoma are also present in stage II/III colorectal carcinoma, we used in silico analysis to elucidate the cell types expressing the PD-L1 gene. We found a statistically significant association of PD-L1 gene expression with MSI in early-stage colorectal carcinoma (P &amp;lt; 0.001) and show that, unlike in non–colorectal carcinoma tumors, PD-L1 is derived predominantly from the immune infiltrate. We demonstrate that PD-L1 gene expression has positive prognostic value in the adjuvant disease setting (PD-L1low vs. PD-L1high HR = 9.09; CI, 2.11–39.10). PD-L1 gene expression had predictive value, as patients with high PD-L1 expression appear to be harmed by standard-of-care treatment (HR = 4.95; CI, 1.10–22.35). Building on the promising results from the metastatic colorectal carcinoma PD-1–targeting trial, we provide compelling evidence that patients with PD-L1high/MSI/immunehigh stage II/III colorectal carcinoma should not receive standard chemotherapy. This conclusion supports the rationale to clinically evaluate this patient subgroup for PD-1 blockade treatment. Cancer Immunol Res; 4(7); 582–91. ©2016 AACR.</jats:p

Differential affinity of FLIP and procaspase 8 for FADD’s DED binding surfaces regulates DISC assembly

Death receptor activation triggers recruitment of FADD, which via its death effector domain (DED) engages the DEDs of procaspase 8 and its inhibitor FLIP to form death-inducing signalling complexes (DISCs). The DEDs of FADD, FLIP and procaspase 8 interact with one another using two binding surfaces defined by α1/α4 and α2/α5 helices, respectively. Here we report that FLIP has preferential affinity for the α1/α4 surface of FADD, whereas procaspase 8 has preferential affinity for FADD's α2/α5 surface. These relative affinities contribute to FLIP being recruited to the DISC at comparable levels to procaspase 8 despite lower cellular expression. Additional studies, including assessment of DISC stoichiometry and functional assays, suggest that following death receptor recruitment, the FADD DED preferentially engages FLIP using its α1/α4 surface and procaspase 8 using its α2/α5 surface; these tripartite intermediates then interact via the α1/α4 surface of FLIP DED1 and the α2/α5 surface of procaspase 8 DED2

A machine learning platform to optimize the translation of personalized network models to the clinic

PURPOSE Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model inputs, which hampers clinical translation. PATIENTS AND METHODS We applied APOPTO-CELL, a prognostic model of apoptosis signaling, to showcase the establishment of computational platforms that require a reduced set of inputs. We designed two distinct and complementary pipelines: a probabilistic approach to exploit a consistent subpanel of inputs across the whole cohort (Ensemble) and a machine learning approach to identify a reduced protein set tailored for individual patients (Tree). Development was performed on a virtual cohort of 3,200,000 patients, with inputs estimated from clinically relevant protein profiles. Validation was carried out in an in-house stage III colorectal cancer cohort, with inputs profiled in surgical resections by reverse phase protein array (n = 120) and/or immunohistochemistry (n = 117). RESULTS Ensemble and Tree reproduced APOPTO-CELL predictions in the virtual patient cohort with 92% and 99% accuracy while decreasing the number of inputs to a consistent subset of three proteins (40% reduction) or a personalized subset of 2.7 proteins on average (46% reduction), respectively. Ensemble and Tree retained prognostic utility in the in-house colorectal cancer cohort. The association between the Ensemble accuracy and prognostic value (Spearman ρ = 0.43; P = .02) provided a rationale to optimize the input composition for specific clinical settings. Comparison between profiling by reverse phase protein array (gold standard) and immunohistochemistry (clinical routine) revealed that the latter is a suitable technology to quantify model inputs. CONCLUSION This study provides a generalizable framework to optimize the development of network-based prognostic assays and, ultimately, to facilitate their integration in the routine clinical workflow

EGFR-targeting drugs in combination with cytotoxic agents: from bench to bedside, a contrasted reality

The clinical experience recently reported with epidermal growth factor receptor (EGFR)-targeting drugs confirms the synergistic interactions observed between these compounds and conventional cytotoxic agents, which were previously established at the preclinical stage. There are, however, examples of major gaps between the bench and the bedside. Particularly demonstrative is the failure of the tyrosine kinase inhibitors (TKIs) (gefitinib and erlotinib) combined with chemotherapy in pretreated nonsmall cell lung cancer patients. These discrepancies can be due to several factors such as the methodology used to evaluate TKI plus cytotoxic agent combinations in preclinical models and the insufficient consideration given to the importance of the drug sequences for the tested combinations. Recent advances in understanding the biologic basis of acquired resistance to these agents have great potential to improve their clinical effectiveness. The purpose of this review is to critically examine the experimental conditions of the preclinical background for anti-EGFR drug–cytotoxic agent combinations and to attempt to explain the gap between clinical observations and preclinical data

A phase II study to determine the ability of gefitinib to reverse fluoropyrimidine resistance in metastatic colorectal cancer (the INFORM study)

There are data suggesting that inhibition of epidermal growth factor receptor (EGFR) tyrosine kinase signalling may reverse resistance to fluoropyrimidine treatment. To investigate this further, the INFORM study was an open-label, non-comparative phase II study of gefitinib (Iressa, ZD1839; AstraZeneca, Wilmington, DE, USA) 250 mg daily in combination with 5-fluorouracil (5-FU administered as an intravenous 400 mg m−2 bolus injection followed by 2800 mg m−2 infusion over 46 h and folinic acid administered as a 350 mg infusion over 2 h) every 2 weeks for up to 12 cycles in 24 patients with metastatic colorectal cancer refractory to previous fluoropyrimidine treatment. There were no objective responses. The stable disease rate was 37.5% (95% CI: 18.80, 59.41), median progression-free survival measured 116 days and overall survival was 226 days. Quality of life was unchanged compared to baseline values, and the commonest toxicities were diarrhoea, rash and fatigue with 7 out of 24 (29%) patients having a grade 3 or 4 toxicity. Gefitinib does not sensitise patients with fluoropyrimidine refractory metastatic colorectal cancer to 5-FU chemotherapy