95th Percentile Values Research Articles

Reproxalap Activity and Estimation of Clinically Relevant Thresholds for Ocular Itching and Redness in a Randomized Allergic Conjunctivitis Field Trial.

IntroductionThis clinical trial assessed the activity of reproxalap, a novel reactive aldehyde species modulator, and estimated clinically relevant thresholds for changes in ocular itching and redness in an allergic conjunctivitis field trial.MethodsThis was a randomized, double-masked, vehicle-controlled phase 2 trial. Patients with ragweed-associated allergic conjunctivitis were assessed over 28 days in an environmental setting with approximately four doses per day of either 0.25% reproxalap, 0.5% reproxalap, or vehicle. Patients recorded ocular itching, redness, tearing, and eyelid swelling scores (each with a 0–4 scale, except for a 0–3 scale for swelling), and completed the Allergic Conjunctivitis Quality of Life Questionnaire at the beginning and end of the trial.ResultsMixed model of repeated measures analysis demonstrated statistically lower itching and tearing scores (pooled P = 0.026 and P < 0.001, respectively) and numerically lower redness and eyelid swelling scores than vehicle on days when pollen exceeded the 95th percentile value. Using three anchor-based and three distribution-based approaches, the meaningful within-patient change and the between-group meaningful difference for patient-reported ocular itching and redness was estimated to be approximately 0.5. The most common treatment-emergent adverse event associated with reproxalap was transient irritation upon instillation.ConclusionIn a field clinical trial, reproxalap was well tolerated and superior to vehicle in reducing ocular itching on high-pollen days. The clinical meaningfulness threshold estimates of 0.5 units are among the first such calculations generated for the standard ocular itching and redness scores, providing important context for the clinical interpretation of clinical trials in allergic conjunctivitis.

Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models.

The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change. To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype. Prospective. A total of 62 participants (37 males, 25 females; mean age, 52 ± 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas. APT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3T. The ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus. T-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant. Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT5 ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95th-percentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT5 was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 ± 0.75 vs. 2.09 ± 0.93 vs. 2.71 ± 0.81). APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT5 can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification. 1 TECHNICAL EFFICACY: Stage 2.

Exposure assessment and risk-based limit levels evaluation of ochratoxin A in Astragali Radix in China

Ochratoxin A (OTA) is a mycotoxin found in a variety of foods and herbal medicines, and several governmental bodies around the world have set maximum allowable levels of OTA in different foods and herbal medicines. This study aims to evaluate the health risk of OTA in Astragali Radix (AR) in China, and to evaluate the effects of different limit levels on the risk control of OTA in AR. The concentrations of OTA in 187 samples of AR were investigated, and 61 (32.6%) samples were positive. The mean, 50th and 95th percentile values of OTA in positive samples were 56.2, 5.1 and 304.5 μg/kg, respectively. A margin of exposure (MOE) approach was applied to assess the risk. Considering other food sources, long-term consumers have a relatively high risk of OTA exposure due to the ingestion of AR. Theoretical limit levels of OTA in AR were evaluated from two dimensions by weighing the costs and the benefits. The results indicated that the limit levels that might be applied to the management of OTA contamination in AR in China could be screened out through risk-based evaluation of limit levels.

Volatile Organic Compounds in Finnish Office Environments in 2010-2019 and Their Relevance to Adverse Health Effects.

We gathered recent (2010–2019) data on the VOC and formaldehyde levels in Finnish non-industrial indoor work environments. The data comprised 9789 VOC and 1711 formaldehyde samples collected from the indoor air of offices, schools, kindergartens, and healthcare offices. We assessed the health risks by comparing the measured concentrations to the health-based RW I/II and EU-LCI reference values. The concentrations of individual VOCs and formaldehyde in these work environments were generally very low and posed no health risks. Total VOC concentration (TVOC) as well as concentrations of several individual compounds, including aromatic compounds, alkanes, 2-ethyl-1-hexanol, and formaldehyde, showed clearly decreasing trends. In contrast, several aldehydes, acids, and a few other compounds showed increasing trends. However, the increasing trends did not seem to affect the higher ends of the distributions, as the 95th percentile values remained fairly stable or decreased over the years. The VOC patterns in the environments of the offices, schools, kindergartens, and healthcare offices varied, probably reflecting the differences in typical activities and the use of materials. However, we do not expect these differences to be relevant to health outcomes.

T-shirt size as a classification for body habitus in computed tomography (CT) and development of size-based dose reference levels for different indications

PurposeTo examine the impact of patient size on dose indices and develop size-based reference levels (50th and 75th percentiles) for 20 body CT exams for routine and organ-specific clinical indications. MethodsBased on effective diameter estimated from adult body CT, each acquisition was classified into T-shirt size as XXS, XS, S, M, L, XL, and XXL. Radiation dose indices for each size and each exam type were correlated. ResultsAbout 0.93 million CT exams from 256 CT facilities in the United States were analysed. Taking T-shirt size M as a reference, the CTDIvol for other sizes were: XXS (∼60%), XS (∼65%), S (∼75%), L (∼130%), XL (∼165%), XXL (∼210%), or grossly small patients received about 60% of the dose as compared to M sized patients and XXL required doubling the dose. Taking ratio of the dose indices of the largest to smallest size, it was evident that SSDE variation was much less (about 50%) than that in CTDIvol, but there was still nearly 40 to 220% variation in SSDE across the range of t-shirt sizes. The 50th and 75th percentile values are presented for CTDIvol, SSDE and DLP for each of the 20 CT exams and for each of the seven T-shirt sizes. ConclusionsA novel approach expressing body habitus in terms of T-shirt size is not only simple and intuitive, but it also provides a tool to have a perception of differences in dose metrices among patients of different body build.

Comparing Four Indexing Approaches to Define Soil Quality in an Intensively Cropped Region of Northern India

The usefulness of the soil quality index (SQI) as a tool to evaluate management options has mostly been studied within the boundaries of a crop or experimental field, calling for the need to enhance its utility in regional-scale soil health assessment. Thus, four quantitative approaches for computing the SQI were evaluated with samples collected from 0 to 15 and 15 to 30 cm depths at 156 points from the Trans-Gangetic Plains of North India. Principal component analysis (PCA) and soil function (SF)-based approaches were used to select the minimum dataset from 18 soil parameters and assign weights to key indicators. In both approaches, two different data transformation methods were followed: 1) routine method with maximum or minimum values of indicator parameters and 2) percentile method with the 90th or 10th percentile value as the denominator or numerator for “more is better” and “less is better” scoring functions, respectively. The PCA output with factor loadings from the varimax rotation showed six principal components accounting for 75% of the total variance, with PC1 explaining the highest variance (26.8%) followed by PC2 (16%). The SF-based approach was better than PCA in terms of a higher correlation of SQI with rice and wheat yields. The percentile method showed a higher correlation in both PCA and SF methods. The SQI computed from 0 to 30 cm soil data did not show any superiority over that from 0 to 15 cm soil. Thus, the soil function–based approach with the percentile method of data transformation proved better to compute the SQI and establish a relationship with production function.

Association of Metals and Metalloids With Urinary Albumin/Creatinine Ratio: Evidence From a Cross-Sectional Study Among Elderly in Beijing.

BackgroundEnvironmental exposure to toxic elements contributes to the pathogenesis of chronic kidney disease (CKD). Few studies focus on the association of urinary metals and metalloids concentrations with the urinary albumin/creatinine ratio (UACR) among elderly, especially in areas and seasons with severe air pollution.ObjectiveWe aimed to evaluate the associations of urinary metals and metalloids concentration with UACR, which is an early and sensitive indicator of CKD.MethodWe conducted a cross-sectional study among 275 elderly people in Beijing from November to December 2016, which has experienced the most severe air pollution in China. We measured 15 urinary metals and metalloids concentration and estimated their association with UACR using a generalized linear model (GLM). Bayesian kernel machine regression (BKMR) and quantile g-computation (qgcomp) models were also conducted to evaluate the combined effect of metal and metalloid mixtures concentration.ResultsOf the 275 elderly people included in the analysis, we found that higher urinary Cu concentration was positively associated with UACR using GLM (β = 0.36, 95% CI: 0.25, 0.46). Using the BKMR model, we found that the change in UACR was positively associated with a change in urinary Cu concentration from its 25th to 75th percentile value with all other metals and metalloids concentration fixed at their 25th, 50th, or 75th percentile levels. Urinary Cu concentration had the most significant positive contribution (59.15%) in the qgcomp model. Our finding was largely robust in three mixture modeling approaches: GLM, qgcomp, and BKMR.ConclusionThis finding suggests that urinary Cu concentration was strongly positively associated with UACR. Further analyses in cohort studies are required to corroborate this finding.

Comparative study of conventional ROI-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors.

To quantitatively compare the diagnostic values of conventional region of interest (ROI)-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors. A total of 230 patients with pathologically confirmed renal tumors who had undergone CT enhancement were classified into clear cell renal cell carcinoma (ccRCC) (n = 133), non-ccRCC (n = 56), and benign renal tumor(n = 41) group. Parametric CT enhancement of each tumor from volumetric histogram were obtained using in-house software, including 10th percentile, 25th percentile, median, 75th percentile, 90th percentile, mean, standard deviation, as well as skewness, kurtosis and entropy, and histogram metrics among these groups were analyzed. ROI-based enhancement density was also analyzed. The entropy and SD values of ccRCCs were higher than those of non-ccRCCs and benign renal tumors (p < 0.05). The 10th percentile, 25th percentile, median, 75th percentile, 90th percentile and mean values of ccRCCs were lower than those of benign renal tumors, however, higher than those of non-ccRCCs (p < 0.05). The ROI-based enhancement density of non-ccRCCs were lower than those of ccRCCs and benign renal tumors(p < 0.05). Receiver operating characteristic (ROC) curve analyses showed that entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs and benign renal tumors. ROC curve analyses showed that mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs. In terms of pairwise comparisons of ROC curves and diagnostic efficacy, ROI-based CT enhancement density was worse than volumetric histogram analysis (p < 0.05). Volumetric histogram analysis parameters can effectively distinguish malignant and benign renal tumors. 1. Entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/ non-ccRCCs and benign renal tumors.2. Mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs.3.Volumetric histogram analysis had better performance than ROI-based enhancement density.

Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI.

ObjectivesTo investigate the application of apparent diffusion coefficient (ADC) histogram analysis in differentiating between benign and malignant breast lesions detected as non-mass enhancement on MRI.Materials and MethodsA retrospective study was conducted for 25 malignant and 26 benign breast lesions showing non-mass enhancement on breast MRI. An experienced radiologist without prior knowledge of the pathological results drew a region of interest (ROI) outlining the periphery of each lesion on the ADC map. A histogram was then made for each lesion. Following a univariate analysis of 18 summary statistics values, we conducted statistical discrimination after hierarchical clustering using Ward’s method. A comparison between the malignant and the benign groups was made using multiple logistic regression analysis and the Mann-Whitney U test. A P -value of less than 0.05 was considered statistically significant.ResultsUnivariate analysis for the 18 summary statistics values showed the malignant group had greater entropy (P < 0.001) and lower uniformity (P < 0.001). While there was no significant difference in mean and skewness values, the malignant group tended to show a lower mean (P = 0.090) and a higher skewness (P = 0.065). Hierarchical clustering of the 18 summary statistics values identified four values (10th percentile, entropy, skewness, and uniformity) of which the 10th percentile values were significantly lower for the malignant group (P = 0.035).ConclusionsWhole-lesion ADC histogram analysis may be useful for differentiating malignant from benign lesions which show non-mass enhancement on breast MRI.

Fetal Ventricular Dilation; prelude to Dandy-Walker Syndrome and Hydrocephalus: Synopsis of Two Case Reports

Accurate measurement of the 3rd and 4th ventricles is important in cases of prenatal and postnatal diagnosis of suspected cranial anomalies. Ventricular dilation occurs with excess fluid in the embryologic ventricles during brain development, we make a comparative analysis of two case reports on a 23rd-week fetus and a 10-month-old neonate. Ultrasound findings related to horns and ventricular system through transfontanelle ultrasound (excluding any &gt; 95th error margin and &lt; 5th percentile) can be utilized for a specific diagnosis of ventricular dilation. Hydrocephalus is defined as the accumulation of excessive CSF resulting in dilation of the cerebrospinal compartment in the calvaria; which can be acquired or congenital in origin. Hydrocephalus can also be seen due to obstructed flow, faulty absorption, and overproduction of CSF (in the subarachnoid space) by a choroid plexus papilloma. The diameter of the anterior horn of the RT and LT (hydrocephalic) lateral ventricles measured 15.3mm and 14.1mm respectively, far above the threshold for normal (control) neonates / RT and LT (anterior) lateral ventricles averaging 2.40mm and 2.51mm. These documented findings indicate the excellent agreement between fetal brain sonography in the diagnosis of fetal ventriculomegaly (anterior horn/ 10.4mm) and dilation (combined 40.8mm). Mean Head Circumference (MHC) for neonatal hydrocephalus was 44.2cm far above the normal average of 36.7cm. When we assessed the clinical benchmark of 10mm or (&gt;19mm) for the neonate ventricle, it was far above the normal range (greater than &gt; 95th percentile value).

Is simultaneous multi-slice readout-segmented echo-planar imaging valuable for predicting molecular subtypes of breast cancer?

PurposeTo investigate the feasibility of simultaneous multi-slice readout-segmented diffusion-weighted echo-planar imaging (SMS rs-EPI DWI) in predicting invasive breast cancer molecular subtypes using whole-tumor histogram and texture analyses. MethodsIn our retrospective study, 125 patients (mean age, 52.81 ± 12.01 years; range, 24–84 years) with single invasive breast cancer who underwent preoperative MRI with SMS rs-EPI DWI and surgery at our institution were included. Two radiologists independently performed whole-tumor histogram and texture analyses on the apparentdiffusioncoefficient (ADC) map of SMS rs-EPI DWI (TR, 3800.0 ms; TE 90.0 ms; field of view, 340 mm × 206 mm; in-plane matrix, 244 × 148; section thickness, 5 mm; readout segments, 5, b = 0, 800 s/mm2; scan time, 3 mins; slice acceleration factor, 2). The Mann–Whitney U test or Kruskal-Wallis test were used to compare histogram and texture parameters to assess their potential in differentiating molecular subtypes of breast cancer and predicting axillary lymph node status. Receiver operating characteristic (ROC) curves were generated for parameters with significant differences, and the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. ResultsCompared to luminal A breast cancer, the HER2-positive breast cancer subtype showed higher ADC_95th percentile values (p = 0.016). In addition, HER2-positive breast cancer yielded significantly higher ADC_mean (p = 0.025), ADC_median (p = 0.025), and ADC_5th percentile (p = 0.041) values than luminal B breast cancer. The ADC_skewness value was higher for triple-negative breast cancer (TNBC) than Luminal A breast cancer (p = 0.021). The difference in ADC_mean, ADC_median, ADC_5th percentile and ADC_95th percentile values between the HER2-positive breast cancer and luminal types was statistically significant, with a combined AUC for these parameters of 0.762 (sensitivity 72.41%, specificity 75.00%, PPV 27.27 %, and NPV 95.45 %). The ADC_skewness value for TNBC was higher than for luminal types (p = 0.012) and yielded an AUC value of 0.688 (sensitivity 96.15%, specificity 36.78%, PPV 31.25%, and NPV 96.97 %). Additionally, significantly higher ADC_skewness and ADC_95th percentile values (p = 0.003, 0.002, respectively) were reported for non-luminal types than luminal types yielding a combined AUC value of 0.712 (sensitivity 92.11%, and specificity 50.23%, PPV 41.18%, and NPV 92.50%). The AUC value for ADC_5th percentile for axillary lymph node status prediction was 0.659 (sensitivity 65.38%, specificity of 64.86%). ConclusionsThe whole-tumor histogram and texture analyses parameters based on SMS rs-EPI DWI may provide biological information on aggressive molecular subtypes of breast cancer. In addition, ADC_5th percentile values were significantly different between lymph node-positive and lymph node-negative breast cancer.

Wide-Area Grid-Based Slant Ionospheric Delay Corrections for Precise Point Positioning

Introducing ionospheric information into a precise point positioning (PPP) solution enables faster ambiguity resolution and significantly improves positioning accuracy. To compute such corrections over wide areas, sparse networks with potentially irregular station distributions are often used. This aspect brings a new level of complexity as ionospheric corrections should be weighted appropriately in the PPP filter. This paper presents a possible implementation of grid-based wide-area slant ionospheric delay corrections, with a focus on the reported uncertainties. A balance is obtained between obtaining corrections with formal errors small enough to enable fast convergence, while large enough to overbound most errors. Based on least-squares collocation, the method uses satellite-specific variograms based on the 99th percentile values in each distance bin. Tested in southern Canada over a 53-week period in 2020, ionospheric grids allowed dual-frequency receivers to obtain around 5 cm accuracy in each horizontal component within 5 min of static data collection. For single-frequency solutions using data from geodetic receivers, positioning errors were reduced by over 60% for both static and kinematic processing.

Relationship between Apparent Diffusion Coefficient Distribution and Cancer Grade in Prostate Cancer and Benign Prostatic Hyperplasia.

The aim of this paper was to assess the associations between prostate cancer aggressiveness and histogram-derived apparent diffusion coefficient (ADC) parameters and determine which ADC parameters may help distinguish among stromal hyperplasia (SH), glandular hyperplasia (GH), and low-grade, intermediate-grade, and high-grade prostate cancers. The mean, median, minimum, maximum, and 10th and 25th percentile ADC values were determined from the ADC histogram and compared among two benign prostate hyperplasia (BPH) groups and three Gleason score (GS) groups. Seventy lesions were identified in 58 patients who had undergone proctectomy. Thirty-nine lesions were prostate cancers (GS 6 = 7 lesions, GS 7 = 19 lesions, GS 8 = 11 lesions, GS 9 = 2 lesions), and thirty-one lesions were BPH (SH = 15 lesions, GH = 16 lesions). There were statistically significant differences in 10th percentile and 25th percentile ADC values when comparing GS 6 to GS 7 (p < 0.05). The 10th percentile ADC values yielded the highest area under the curve (AUC). Tenth and 25th percentile ADCs can be used to more accurately differentiate lesions with GS 6 from those with GS 7 than other ADC parameters. Our data indicate that the major challenge with ADC mapping is to differentiate between SH and GS 6, and SH and GS 7.

Concentration of smoke marker compounds in non‐smoke‐exposed grapes and wine in Australia

Background and Aims An elevated concentration of several volatile phenols and their glycosides in grapes and wines is associated with exposure of grapes to forest fire smoke. Interpretation of phenol compositional data from grapes or wines, however, is complicated by the fact that traces of these compounds can be detected in non-smoke-exposed samples. Hence, the concentration of smoke marker compounds was investigated with the aim of providing a reference data set to help determine smoke exposure. Methods and Results Thirteen phenolic compounds were measured in non-smoke-exposed grape berries and unoaked wines made from 12 cultivars collected from multiple regions across Australia over four vintages. The grapes and wines contained a low concentration of several volatile phenols and their glycosides. These varied in concentration between cultivars but showed little variation between regions and vintages. The maximum concentration observed for any analyte was below 15 μg/kg in grapes and approximately 15 μg/L in wine. Conclusions The results for smoke marker compounds should be considered on a per-cultivar basis when determining smoke exposure. Interpretation of results for a potentially smoke-exposed sample can be achieved based on comparison with the 99th percentile values reported here. Use of the interpretation system described should be limited to determining smoke exposure and not smoke taint. Significance of the Study This study provides a comprehensive set of data that defines the upper limits of smoke marker compounds expected in Australian grapes and wines from non-smoke-exposed vineyards that can be used for determining the likelihood of smoke exposure.

Regional patterns of dry spell durations in Croatia

AbstractThe spatiotemporal characteristics of mean and maximum dry spells (DSs) in Croatia were analysed through general climatology and the return values associated with different return periods. An analysis was performed across seven regions with different precipitation regimes comprising data from 131 meteorological stations for 1961–2015. Daily precipitation limits of 1, 5, and 10 mm were used to define dry days, and DSs were defined as consecutive series of dry days. Generalized extreme value (GEV) and generalized Pareto (GP) distributions were applied to the DS annual maxima (AM) and the peak over threshold (POT) series, respectively. The respective distribution parameter methodology and interpretation combined both frequentist and Bayesian approaches. The regional mean DS lengths clearly indicated a dominance of DS durations in easternmost Croatia during the cold season (mainly winter) and in the southern Adriatic during the warm season (mainly summer). Elsewhere, combined climatic influences were reflected, with the shortest DSs found in the highlands. This spatial pattern was more pronounced for DS5 and DS10, whereas differences in DS1 durations were not evident. Spatial DS distribution return values associated with various return periods obtained by the GEV and GP distributions followed the general DS climatology. The visual inspection of an appropriate threshold for GP‐POT modelling, using the GP parameter stability graphs and L‐moment ratio diagrams, indicated that the 75th percentile value was best for all three DS categories. Although the estimates obtained by the two methods could not be directly compared, the GP model generally found longer DS return values than those obtained by the GEV, particularly in the regions with long DS. This study provides a climatological basis for drought parameters and drought risk assessment in Croatia. Moreover, the results are relevant for adjacent regions, complementing and enriching the current DS characteristics knowledge in southeastern Europe.

Tephra Fallout Probabilistic Hazard Maps for Cotopaxi and Guagua Pichincha Volcanoes (Ecuador) With Uncertainty Quantification

AbstractTephra fallout hazard assessment is undertaken with probabilistic maps that rely on numerical models. Regarding maps production, the input parameters of the model (including atmospheric conditions), the physical approximations of the numerical simulations, and the probabilities of occurrence of different eruption types in specific time frames are among the most critical sources of uncertainty. We therefore present a tephra fallout hazard assessment study for two active volcanoes (Cotopaxi and Guagua Pichincha) in Ecuador. We utilize PLUME‐MoM/HYSPLIT models, and a procedure for uncertainty quantification where: (a) the uncertainty on eruptive source parameters and eruption type occurrence is quantified through expert elicitation; (b) we implement a new procedure for correlations between the different parameters, and (c) we use correction coefficients to take into account the uncertainty of the numerical model. Maps of exceedance probability given a deposit thickness threshold, and thickness maps given a probability of exceedance, are produced (a) for two eruptive scenarios (sub‐Plinian and Plinian) and (b) as a combination of these scenarios in case the next eruption will be sub‐Plinian or Plinian. These maps are described according to the uncertainty distribution of eruption type occurrence probabilities, considering their 5th percentile, mean, and 95th percentile values. We finally present hazard curves describing exceeding probabilities in 10 sensitive sites within the city of Quito. Additional information includes the areal extent and the population potentially affected by different isolines of tephra accumulation. This work indicates that full uncertainty quantification helps in providing more robust scientific information, improving the hazard assessment reliability.

The Content of Cobalt, Silver and Vanadium in Raw Cow’s Milk in Croatia and Risk Assessment for Consumers

Concentrations of selected trace elements Ag, Co and V in raw milk sampled from four geographical regions in Croatia were measured. Silver, Co and V were detected above the limit of detection within the range of 9.52%-30.8%, 1.6%-12.1% and 12.4%-30.8%. Silver concentrations were not detected in milk samples from the Croatian Littoral and Mountainous Croatia (CL-MC) region. Similar Ag content was found in Southern, Eastern and Central Croatia. The lowest mean of Co and V of 33.2 and 83.8µg kg-1 were found in the CL-MC region while the highest of 49.8 and 136.9µg kg-1 was found in Central Croatia. There were no statistically significant differences in Ag, Co and V contents between the four regions. The estimated daily dietary intakes (EDI) of total mean and total 95th percentile values of Ag, Co and V showed lower values in comparison with available EFSA health-based limits.

Appraisal of groundwater arsenic on opposite banks of River Ganges, West Bengal, India, and quantification of cancer risk using Monte Carlo simulations.

This study was conducted to inspect the spatial distribution, source identification, and risk assessment of groundwater arsenic (As) in different blocks that lie on the opposite banks of river Bhagirathi (a distributary of river Ganges), Murshidabad, West Bengal, India. It has been observed that the blocks that lie towards the eastern bank of river Bhagirathi have elevated arsenic and comparatively more reducing groundwater (lower oxidation-reduction potential and high iron). About 66% of groundwater samples across the district have arsenic concentration higher than the World Health Organization (WHO) permissible limit. Speciation of groundwater arsenic reveals that about 90% of arsenic species were present as arsenic (III). Further, principal component analysis (PCA) was employed to identify the controlling factors that favor the release of arsenic. PC1 comprises EC, TDS, As, Fe, TOC, and HCO3- with moderate loadings, which suggests microbially mediated degradation of organic matter (OM), helps in reductive dissolution of arsenic-bearing Fe-Mn oxyhydroxides. Results pointed out severe groundwater arsenic poisoning; hence, a health risk assessment was performed for the exposure of arsenic in groundwater, using incremental lifetime cancer risk (ILCR) models coupled with Monte Carlo simulations. On the eastern bank of river Bhagirathi, incremental lifetime cancer risk (ILCR) due to oral exposure (5th to 95th percentile values) ranged from 1.30538E - 04 to 9.31398E - 03 with a mean of 2.84194E - 03 for adults, which is 2841 times higher than the USEPA high safety risk guidelines of one in 1 million. The outcomes of the results will be useful for the policymakers and regulatory boards in defining the actual impact and deciding the pre-remediation goals.

Simulation and Evaluation of Statistical Downscaling of Regional Daily Precipitation over North China Based on Self-Organizing Maps

A statistical downscaling method based on Self-Organizing Maps (SOM), of which the SOM Precipitation Statistical Downscaling Method (SOM-SD) is named, has received increasing attention. Herein, its applicability of downscaling daily precipitation over North China is evaluated. Six indices (total season precipitation, daily precipitation intensity, mean number of precipitation days, percentage of rainfall from events beyond the 95th percentile value of overall precipitation, maximum consecutive wet days, and maximum consecutive dry days) are selected, which represent the statistics of daily precipitation with regards to both precipitation amount and frequency, as well as extreme event. The large-scale predictors were extracted from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) daily reanalysis data, while the prediction was the high resolution gridded daily observed precipitation. The results show that the method can establish certain conditional transformation relationships between large-scale atmospheric circulation and local-scale surface precipitation in a relatively simple way. This method exhibited a high skill in reproducing the climatologic statistical properties of the observed precipitation. The simulated daily precipitation probability distribution characteristics can be well matched with the observations. The values of Brier scores are between 0 and 1.5 × 10−4 and the significance scores are between 0.8 and 1 for all stations. The SOM-SD method, which is evaluated with the six selected indicators, shows a strong simulation capability. The deviations of the simulated daily precipitation are as follows: Total season precipitation (−7.4%), daily precipitation intensity (−11.6%), mean number of rainy days (−3.1 days), percentage of rainfall from events beyond the 95th percentile value of overall precipitation (+3.4%), maximum consecutive wet days (−1.1 days), and maximum consecutive dry days (+3.5 days). In addition, the frequency difference of wet-dry nodes is defined in the evaluation. It is confirmed that there was a significant positive correlation between frequency difference and precipitation. The findings of this paper imply that the SOM-SD method has a good ability to simulate the probability distribution of daily precipitation, especially the tail of the probability distribution curve. It is more capable of simulating extreme precipitation fields. Furthermore, it can provide some guidance for future climate projections over North China.

Correlation Between the Incidence of Breast Cancer and the Human Development Index

Introduction: Breast cancer is the second most frequent type in the world and is the most common among women. The increase in its incidence has been a cause of constant and growing concern, as the incidence rates vary greatly according to the degree of socio-economic development. Currently, the genesis of breast cancer and its risk factors have been receiving an important consideration, since these factors are crucial when thinking about its prevention. As developing countries are constantly growing, there is a change in their lifestyle habits, such as fat and alcohol intake, smoking, exposure to oral contraceptives, changes in procreation and breastfeeding patterns, birth profile. With this change, they also accumulate more diseases associated with this culture, among them breast cancer. Objective: to analyze a possible relationship between HDI and the incidence of breast cancer worldwide. Methods: The incidence of breast cancer in 164 countries was obtained from GLOBOCAN, derived from population-based cancer records. A list of human development index of the same 164 countries was obtained from the United Nations Human Development Report. Nonlinear regression models were obtained using the Levenberg-Marquardt estimation method. Results and Conclusions: Of the 164 countries evaluated, 146 were in the range between 10 and -10 of predicted variation, which were between the fifth and 95th percentile values. The 18 countries whose incidences of CM were found to deviate outside this range (nine above and below, respectively) were considered as discrepant observations. Once the data from countries with discrepant observations were removed, nonlinear regression analysis of the group of 146 remaining countries was obtained using the Levenberg-Marquardt estimation method, identifying a value of “R2” at 0.8343, confirming the high reliability of the proposed mathematical model. This result suggests the hypothesis that the factors included in the calculation of the Human Development Index are strongly related to those involved in the population incidence of breast cancer. The application of this model also suggested the existence of a group of countries that apparently present protective factors or that favor the onset of breast cancer