Validation of Urban NO2NO_2 Concentrations and Their Diurnal and Seasonal Variations Observed from the SCIAMACHY and OMI Sensors Using In Situ Surface Measurements in Israeli Cities

We compare a full-year (2006) record of surface air $NO_2$ concentrations measured in Israeli cities to coinciding retrievals of tropospheric $NO_2$ columns from satellite sensors (SCIAMACHY aboard ENVISAT and OMI aboard Aura). This provides a large statistical data set for validation of $NO_2$ satellite measurements in urban air, where validation is difficult yet crucial for using these measurements to infer $NO_x$ emissions by inverse modeling. Assuming that $NO_2$ is well-mixed throughout the boundary layer (BL), and using observed average seasonal boundary layer heights, near-surface $NO_2$ concentrations are converted into BL $NO_2$ columns. The agreement between OMI and (13:45) BL $NO_2$ columns (slope=0.93, n=542), and the comparable results at 10:00 h for SCIAMACHY, allow a validation of the seasonal, weekly, and diurnal cycles in satellite-derived $NO_2$. OMI and BL $NO_2$ columns show consistent seasonal cycles (winter $NO_2$ 1.6–2.7× higher than summer). BL and coinciding OMI columns both show a strong weekly cycle with 45–50% smaller $NO_2$ columns on Saturday relative to the weekday mean, reflecting the reduced weekend activity, and validating the weekly cycle observed from space. The diurnal difference between SCIAMACHY (10:00) and OMI (13:45) $NO_2$ is maximum in summer when SCIAMACHY is up to 40% higher than OMI, and minimum in winter when OMI slightly exceeds SCIAMACHY. A similar seasonal variation in the diurnal difference is found in the source region of Cairo. The surface measurements in Israel cities confirm this seasonal variation in the diurnal cycle. Using simulations from a global 3-D chemical transport model (GEOS-Chem), we show that this seasonal cycle can be explained by a much stronger photochemical loss of $NO_2$ in summer than in winter.Engineering and Applied Science

Liquid Phase Direct Synthesis of H2O2 : Activity and Selectivity of Pd-Dispersed Phase on Acidic Niobia-Silica Supports

In this work, acidic niobia-silica (NbS, 4 1214 wt % Nb) materials used as supports of dispersed Pd particles (1.0 122.0 wt % Pd) have been prepared from different Nb-precursors (niobium ethoxide, NBE, and ammonium niobium oxalate, ANBO) and techniques (coprecipitation and deposition), characterized, and tested in the direct synthesis of H2O2 in water and methanol solvents. In particular, on a typical NbS sample, the evolution of morphology (by N2-adsorption 12desorption), crystalline-phase (by XRD), electronic structure (by UV 12vis-DRS), and surface acidity with time/temperature of treatment (350 12800 \ub0C for 4 12100 h) has been investigated. Surface acidity was measured by titrations with 2-phenylethylamine adsorption in various liquids: cyclohexane, for the intrinsic acidity, and water, methanol, and water 12methanol mixtures for the ef fective acidities. Direct H2O2 synthesis reaction was performed in semibatch slurry reactor with continuous feeding of the gaseous mixture (H2, O2, and N2), under pressure (5 7 103 kPa or 104 kPa) at 5 \ub0C in methanol or in water. In both solvents, reaction rates only little decreased with time on stream (ca. 5% of rate decrease after 4 h of reaction from initial rate of ca. 0.5 gH2O2\ub7(kgsolution\ub7min) 121, according with the slight Pd sintering observed by TEM images. Catalysts prepared by deposition of NBE on silica gave better performances than those prepared from ANBO. In general, selectivity to H2O2 in water and in methanol was observed to be similar; the unexpected good selectivity in water was due to the higher ef fective acid strengths of the catalytic surfaces in water than in methanol, as experimentally proven

Lower Bounds for Leakage-Resilient Secret Sharing

Threshold secret sharing allows a dealer to split a secret into $n$ shares such that any authorized subset of cardinality at least $t$ of those shares efficiently reveals the secret, while at the same time any unauthorized subset of cardinality less than $t$ contains no information about the secret. Leakage-resilience additionally requires that the secret remains hidden even if one is given a bounded amount of additional leakage from every share. In this work, we study leakage-resilient secret sharing schemes and prove a lower bound on the share size and the required amount of randomness of any information-theoretically secure scheme. We prove that for any information-theoretically secure leakage-resilient secret sharing scheme either the amount of randomness across all shares or the share size has to be linear in $n$. More concretely, for a secret sharing scheme with $p$-bit long shares, $\ell$-bit leakage per share, where $\widehat{t}$ shares uniquely define the remaining $n - \widehat{t}$ shares, it has to hold that $$p \ge \frac{\ell (n - t)}{\widehat{t}}\ .$$ We use this lower bound to gain further insights into a question that was recently posed by Benhamouda et al. (CRYPTO\u2718), who ask to what extend existing regular secret sharing schemes already provide protection against leakage. The authors proved that Shamir\u27s secret sharing is $1$-bit leakage-resilient for reconstruction thresholds $t \geq 0.85n$ and conjectured that it is also $1$-bit leakage-resilient for any other threshold that is a constant fraction of the total number of shares. We do not disprove their conjecture, but show that it is the best one could possibly hope for. Concretely, we show that for large enough $n$ and any constant $0< c < 1$ it holds that Shamir\u27s secret sharing scheme is \emph{not} leakage-resilient for $t \leq \frac{cn}{\log n}$. In contrast to the setting with information-theoretic security, we show that our lower bound does not hold in the computational setting. That is, we show how to construct a leakage-resilient secret sharing scheme in the random oracle model that is secure against computationally bounded adversaries and violates the lower bound stated above

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

Respective Prognostic Value of Genomic Grade and Histological Proliferation Markers in Early Stage (pN0) Breast Carcinoma

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score.A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R).GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02).In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma

Tumor-infiltrating lymphocytes in patients receiving trastuzumab/pertuzumab-based chemotherapy : a TRYPHAENA Substudy

Background: There is an urgent requirement to identify biomarkers to tailor treatment in human epidermal growth factor receptor 2 (HER2)-amplified early breast cancer treated with trastuzumab/pertuzumab-based chemotherapy. Methods: Among the 225 patients randomly assigned to trastuzumab/pertuzumab concurrently or sequentially with an anthracycline-containing regimen or concurrently with an anthracycline-free regimen in the Tryphaena trial, we determined the percentage of tumor-infiltrating lymphocytes (TILs) at baseline in 213 patients, of which 126 demonstrated a pathological complete response (pCR; ypT0/is ypN0), with 28 demonstrating event-free survival (EFS) events. We investigated associations between baseline TIL percentage and either pCR or EFS after adjusting for clinicopathological characteristics using logistic and Cox regression models, respectively. To understand TIL biology, we evaluated associations between baseline TILs and baseline tumor gene expression data (800 gene set by NanoString) in a subset of 173 patients. All statistical tests were two-sided. Results: Among the patients with measurable TILs at baseline, the median level was 14.1% (interquartile range = 7.1%-32.4%). After adjusting for clinicopathological characteristics, baseline percentage TIL was not associated with pCR (adjusted odds ratio [aOR] for every 10-percentage unit increase in TILs = 1.12, 95% confidence interval [CI] = 0.95 to 1.31, P = .17). At a median follow-up of 4.7 years, for every increase in baseline TILs of 10%, there was a 25% reduction in the hazard for an EFS event (aOR = 0.75, 95% CI = 0.56 to 1.00, P = .05) after adjusting for baseline clinicopathological characteristics and pCR. Additionally, genes associated with epithelial-mesenchymal transition, angiogenesis, and T-cell inhibition such as SNAIL1, ZEB1, NOTCH3, and B7-H3 were statistically significantly inversely correlated with percentage TIL. Conclusions: Baseline TIL percentage provides independent prognostic information in patients treated with trastuzumab/pertuzumab-based neoadjuvant chemotherapy. However, further validation is required

The effect of water immersion on short-latency somatosensory evoked potentials in human

<p>Abstract</p> <p>Background</p> <p>Water immersion therapy is used to treat a variety of cardiovascular, respiratory, and orthopedic conditions. It can also benefit some neurological patients, although little is known about the effects of water immersion on neural activity, including somatosensory processing. To this end, we examined the effect of water immersion on short-latency somatosensory evoked potentials (SEPs) elicited by median nerve stimuli. Short-latency SEP recordings were obtained for ten healthy male volunteers at rest in or out of water at 30°C. Recordings were obtained from nine scalp electrodes according to the 10-20 system. The right median nerve at the wrist was electrically stimulated with the stimulus duration of 0.2 ms at 3 Hz. The intensity of the stimulus was fixed at approximately three times the sensory threshold.</p> <p>Results</p> <p>Water immersion significantly reduced the amplitudes of the short-latency SEP components P25 and P45 measured from electrodes over the parietal region and the P45 measured by central region.</p> <p>Conclusions</p> <p>Water immersion reduced short-latency SEP components known to originate in several cortical areas. Attenuation of short-latency SEPs suggests that water immersion influences the cortical processing of somatosensory inputs. Modulation of cortical processing may contribute to the beneficial effects of aquatic therapy.</p> <p>Trial Registration</p> <p>UMIN-CTR (UMIN000006492)</p

Stromal Genes Add Prognostic Information to Proliferation and Histoclinical Markers: A Basis for the Next Generation of Breast Cancer Gene Signatures

BACKGROUND: First-generation gene signatures that identify breast cancer patients at risk of recurrence are confined to estrogen-positive cases and are driven by genes involved in the cell cycle and proliferation. Previously we induced sets of stromal genes that are prognostic for both estrogen-positive and estrogen-negative samples. Creating risk-management tools that incorporate these stromal signatures, along with existing proliferation-based signatures and established clinicopathological measures such as lymph node status and tumor size, should better identify women at greatest risk for metastasis and death. METHODOLOGY/PRINCIPAL FINDINGS: To investigate the strength and independence of the stromal and proliferation factors in estrogen-positive and estrogen-negative patients we constructed multivariate Cox proportional hazards models along with tree-based partitions of cancer cases for four breast cancer cohorts. Two sets of stromal genes, one consisting of DCN and FBLN1, and the other containing LAMA2, add substantial prognostic value to the proliferation signal and to clinical measures. For estrogen receptor-positive patients, the stromal-decorin set adds prognostic value independent of proliferation for three of the four datasets. For estrogen receptor-negative patients, the stromal-laminin set significantly adds prognostic value in two datasets, and marginally in a third. The stromal sets are most prognostic for the unselected population studies and may depend on the age distribution of the cohorts. CONCLUSION: The addition of stromal genes would measurably improve the performance of proliferation-based first-generation gene signatures, especially for older women. Incorporating indicators of the state of stromal cell types would mark a conceptual shift from epithelial-centric risk assessment to assessment based on the multiple cell types in the cancer-altered tissue