An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Predicting residue-wise contact orders in proteins by support vector regression

Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Stochastic analysis of the VEGF receptor response curve

Recently, an analysis of the response curve of the vascular endothelial growth factor (VEGF) receptor and its application to cancer therapy was described in [T. Alarcón, and K. Page, J. R. Soc. Lond. Interface 4, 283–304 (2007)]. The analysis is significantly extended here by demonstrating that an alternative computational strategy, namely the Krylov FSP algorithm for the direct solution of the chemical master equation, is feasible for the study of the receptor model. The new method allows us to further investigate the hypothesis of symmetry in the stochastic fluctuations of the response. Also, by augmenting the original model with a single reversible reaction we formulate a plausible mechanism capable of realizing a bimodal response, which is reported experimentally but which is not exhibited by the original model. The significance of these findings for mechanisms of tumour resistance to antiangiogenic therapy is discussed.

Quantile regression without the curse of unsmoothness

We consider quantile regression models and investigate the induced smoothing method for obtaining the covariance matrix of the regression parameter estimates. We show that the difference between the smoothed and unsmoothed estimating functions in quantile regression is negligible. The detailed and simple computational algorithms for calculating the asymptotic covariance are provided. Intensive simulation studies indicate that the proposed method performs very well. We also illustrate the algorithm by analyzing the rainfall–runoff data from Murray Upland, Australia.

An envirogenomic signature is associated with risk of IBD-related surgery in a population-based Crohn’s Disease cohort

BACKGROUND AND AIMS: Crohn's disease (CD) is an inflammatory bowel disease (IBD) caused by a combination of genetic, clinical, and environmental factors. Identification of CD patients at high risk of requiring surgery may assist clinicians to decide on a top-down or step-up treatment approach. METHODS: We conducted a retrospective case-control analysis of a population-based cohort of 503 CD patients. A regression-based data reduction approach was used to systematically analyse 63 genomic, clinical and environmental factors for association with IBD-related surgery as the primary outcome variable. RESULTS: A multi-factor model was identified that yielded the highest predictive accuracy for need for surgery. The factors included in the model were the NOD2 genotype (OR = 1.607, P = 2.3 × 10(-5)), having ever had perianal disease (OR = 2.847, P = 4 × 10(-6)), being post-diagnosis smokers (OR = 6.312, P = 7.4 × 10(-3)), being an ex-smoker at diagnosis (OR = 2.405, P = 1.1 × 10(-3)) and age (OR = 1.012, P = 4.4 × 10(-3)). Diagnostic testing for this multi-factor model produced an area under the curve of 0.681 (P = 1 × 10(-4)) and an odds ratio of 3.169, (95 % CI P = 1 × 10(-4)) which was higher than any factor considered independently. CONCLUSIONS: The results of this study require validation in other populations but represent a step forward in the development of more accurate prognostic tests for clinicians to prescribe the most optimal treatment approach for complicated CD patients.

Epstein-Barr virus-positive diffuse large B-cell lymphoma of the elderly expresses EBNA3A with conserved CD8+ T-cell epitopes

Post-transplantation lymphoproliferative disorders (PTLD) arise in the immunosuppressed and are frequently Epstein-Barr virus (EBV) associated. The most common PTLD histological sub-type is diffuse large B-cell lymphoma (EBV+DLBCL-PTLD). Restoration of EBV-specific T-cell immunity can induce EBV+DLBCL-PTLD regression. The most frequent B-cell lymphoma in the immunocompetent is also DLBCL. ‘EBV-positive DLBCL of the elderly’ (EBV+DLBCL) is a rare but well-recognized DLBCL entity that occurs in the overtly immunocompetent, that has an adverse outcome relative to EBV-negative DLBCL. Unlike PTLD (which is classified as viral latency III), literature suggests EBV+DLBCL is typically latency II, i.e. expression is limited to the immuno-subdominant EBNA1, LMP1 and LMP2 EBV-proteins. If correct, this would be a major impediment for T-cell immunotherapeutic strategies. Unexpectedly we observed EBV+DLBCL-PTLD and EBV+DLBCL both shared features consistent with type III EBV-latency, including expression of the immuno-dominant EBNA3A protein. Extensive analysis showed frequent polymorphisms in EBNA1 and LMP1 functionally defined CD8+ T-cell epitope encoding regions, whereas EBNA3A polymorphisms were very rare making this an attractive immunotherapy target. As with EBV+DLBCL-PTLD, the antigen presenting machinery within lymphomatous nodes was intact. EBV+DLBCL express EBNA3A suggesting it is amenable to immunotherapeutic strategies.

Epidemiological trend of hepatitis B, liver cirrhosis and liver cancer during 1990 - 2007 in Shandong province, China [山东省乙型肝炎、肝硬化及肝癌流行趋势分析]

Objective To analyze the epidemiological trend of hepatitis B, liver cirrhosis and liver cancer during 1990 to 2007 in Shandong province, and to evaluate the effectiveness of hepatitis B prevention and control measures, so as to provide evidence for policy-making. Methods Based on the routine incidence data of hepatitis B, mortality data of hepatitis B, liver cirrhosis, liver cancer and demographic data, the incidence rate, mortality rate and age-specific mortality rate were calculated and analyzed with simple linear regression model. Results A total of 437094 cases of hepatitis B were reported during 1990 - 2007 with an average yearly morbidity of 27.32 per 100 000 persons and a decreased trend for the 0-9 years old children. At the same time, the adjusted mortality rate for hepatitis B and liver cirrhosis showed a decreased trend and the combined mortality rate decreased from 17.55 /100 000 in 1990 to 4.01 /100 000 in 2007. The mortality of liver cancer was stable during this time (P = 0. 9998). Conclusion Immunization of hepatitis B vaccine may have lowered the incidence of hepatitis B in the target population and the overall mortality rates of liver cirrhosis and liver cancer. Abstract in Chinese 目的 了解山东省1990～2007年乙肝、肝硬化和肝癌的流行状况及变化趋势,初步评价乙肝预防控制措施的效果,为今后防治决策制定提供参考. 方法 根据报告的乙肝发病资料和乙肝、肝硬化、肝癌死亡资料以及历年人口资料,利用发病率、死亡率、年龄别死亡率等指标对上述3种疾病进行流行趋势的分析,并建立简单线性回归模型进行统计分析. 结果 1990～2007年山东省共报告乙肝病例437 094例,年均总发病率为27.32/10万,并呈上升趋势,而0～9岁年龄组的发病率呈显著下降趋势.乙肝和肝硬化调整死亡率下降趋势明显,两者合并死亡率由1990年的17.55/10万下降到2007年的4.01/10万.肝癌调整死亡率基本稳定(P=0.999 8). 结论 做好乙肝疫苗的免疫接种不仅可降低目标人群乙肝的发病,并将最终降低与此相关的肝硬化和肝癌的死亡率.

Epidemiological Trend of Hepatitis B in Shandong Province of China, 1990 - 2007 []

Objective To analyze the epidemiological trend of hepatitis B from 1990 to 2007 in Shandong province, and to find the high risk population so as to explore the further control strategy. Methods Based on the routine reporting incidence data of hepatitis B and demographic data of Shandong province, the incidence rates and sex - specific, age - specific incidence rates of hepatitis B were calculated and statistically analyzed in the simple linear regression model. Results The total number of hepatitis B was 437 094, the annual average morbidity was 27132 per 100 000 population during 1990 to 2007. The incidence of men (38142 per 100 000) was higher than that for women (15183 per 100 000) 1The annual incidence rate of hepatitis B indicated an increasing trend for the whole population, while a decreased trend for the 0～9 year - old children p resented in the past 18 years. It showed that the average age of onset moved to the older. Conclusion Young adult men are the high-risk groups for the onset of hepatitis B. For the prevention of hepatitis B, the immunization of hepatitis B vaccine should be enhanced for other groups, especially for the high - risk population on the basis of imp roving the immunization coverage rate for newborns.

Bioequivalence of two tablet formulations of capecitabine and exploration of age, gender, body surface area, and creatinine clearance as factors influencing systemic exposure in cancer patients

Purpose: The objective of the study was to assess the bioequivalence of two tablet formulations of capecitabine and to explore the effect of age, gender, body surface area and creatinine clearance on the systemic exposure to capecitabine and its metabolites. Methods: The study was designed as an open, randomized two-way crossover trial. A single oral dose of 2000 mg capecitabine was administered on two separate days to 25 patients with solid tumors. On one day, the patients received four 500-mg tablets of formulation B (test formulation) and on the other day, four 500-mg tablets of formulation A (reference formulation). The washout period between the two administrations was between 2 and 8 days. After each administration, serial blood and urine samples were collected for up to 12 and 24 h, respectively. Unchanged capecitabine and its metabolites were determined in plasma using LC/MS-MS and in urine by NMRS. Results: Based on the primary pharmacokinetic parameter, AUC(0-∞) of 5'-DFUR, equivalence was concluded for the two formulations, since the 90% confidence interval of the estimate of formulation B relative to formulation A of 97% to 107% was within the acceptance region 80% to 125%. There was no clinically significant difference between the t(max) for the two formulations (median 2.1 versus 2.0 h). The estimate for C(max) was 111% for formulation B compared to formulation A and the 90% confidence interval of 95% to 136% was within the reference region 70% to 143%. Overall, these results suggest no relevant difference between the two formulations regarding the extent to which 5'-DFUR reached the systemic circulation and the rate at which 5'-DFUR appeared in the systemic circulation. The overall urinary excretions were 86.0% and 86.5% of the dose, respectively, and the proportion recovered as each metabolite was similar for the two formulations. The majority of the dose was excreted as FBAL (61.5% and 60.3%), all other chemical species making a minor contribution. Univariate and multivariate regression analysis to explore the influence of age, gender, body surface area and creatinine clearance on the log-transformed pharmacokinetic parameters AUC(0-∞) and C(max) of capecitabine and its metabolites revealed no clinically significant effects. The only statistically significant results were obtained for AUC(0-∞) and C(max) of intact drug and for C(max) of FBAL, which were higher in females than in males. Conclusion: The bioavailability of 5'-DFUR in the systemic circulation was practically identical after administration of the two tablet formulations. Therefore, the two formulations can be regarded as bioequivalent. The variables investigated (age, gender, body surface area, and creatinine clearance) had no clinically significant effect on the pharmacokinetics of capecitabine or its metabolites.

Platinum-based chemotherapy in metastatic breast cancer : current status

Cisplatin and carboplatin are active in previously untreated patients with metastatic breast cancer (MBC) with mean response rates (RRs) of 50 and 32%, respectively. In pretreated patients the RR to cisplatin/carboplatin monotherapy declines markedly to <10%. Cisplatin and carboplatin have been combined with many other cytotoxics. In first-line setting high activity has been observed in combination with taxanes or vinorelbine (RRs consistently ∼60%). It appears that these newer combinations are superior to older regimens with etoposide (RRs 30 to 50%) or 5-fluorouracil (RRs 40 to 60%). Cisplatin-/carboplatin-based regimens with infusional 5-FU and epirubicin/paclitaxel/vinorelbine achieve high RRs of around 60 to 80%. However these regimens are difficult to administer in all patients because they require central venous access for continuous 5-FU infusion. In pretreated MBC the combinations of cisplatin-taxane/vinorelbine/gemcitabine or carboplatin-docetaxel/vinorelbine yield RRs of 40 to 50%, which are higher than those achieved with platinum-etoposide/5-FU. In locally advanced disease cisplatin-based regimens achieve very high RRs (>80%). This would suggest that in chemotherapy-naïve patients platinum-based therapy might have an important role to play. Additionally the synergy demonstrated between platinum compounds, taxanes and herceptin, in preclinical and clinical studies is of immense importance and the results of the two ongoing Breast Cancer International Research Group randomized phase III studies are eagerly awaited. These studies may help clarify the role of platinum compounds in the treatment of metastatic and possibly early breast cancer. © 2003 Elsevier Ltd. All rights reserved.

Single-agent versus combination chemotherapy in patients with advanced non-small cell lung cancer and a performance status of 2 : prognostic factors and treatment selection based on two large randomized clinical trials

Purpose: Data from two randomized phase III trials were analyzed to evaluate prognostic factors and treatment selection in the first-line management of advanced non-small cell lung cancer patients with performance status (PS) 2. Patients and Methods: Patients randomized to combination chemotherapy (carboplatin and paclitaxel) in one trial and single-agent therapy (gemcitabine or vinorelbine) in the second were included in these analyses. Both studies had identical eligibility criteria and were conducted simultaneously. Comparison of efficacy and safety was performed between the two cohorts. A regression analysis identified prognostic factors and subgroups of patients that may benefit from combination or single-agent therapy. Results: Two hundred one patients were treated with combination and 190 with single-agent therapy. Objective responses were 37 and 15%, respectively. Median time to progression was 4.6 months in the combination arm and 3.5 months in the single-agent arm (p < 0.001). Median survival imes were 8.0 and 6.6 months, and 1-year survival rates were 31 and 26%, respectively. Albumin <3.5 g, extrathoracic metastases, lactate dehydrogenase ≥200 IU, and 2 comorbid conditions predicted outcome. Patients with 0-2 risk factors had similar outcomes independent of treatment, whereas patients with 3-4 factors had a nonsignificant improvement in median survival with combination chemotherapy. Conclusion: Our results show that PS2 non-small cell lung cancer patients are a heterogeneous group who have significantly different outcomes. Patients treated with first-line combination chemotherapy had a higher response and longer time to progression, whereas overall survival did not appear significantly different. A prognostic model may be helpful in selecting PS 2 patients for either treatment strategy. © 2009 by the International Association for the Study of Lung Cancer.

Serum HE4 as a prognostic marker in endometrial cancer : a population based study

Objective HE4 has emerged as a promising biomarker in gynaecological oncology. The purpose of this study was to evaluate serum HE4 as a biomarker for high-risk phenotypes in a population-based endometrial cancer cohort. Methods Peri-operative serum HE4 and CA125 were measured in 373 patients identified from the prospective Australian National Endometrial Cancer Study (ANECS). HE4 and CA125 were quantified on the ARCHITECT instrument in a clinically accredited laboratory. Receiver operator curves (ROC), Spearman rank correlation coefficient, and chi-squared and Mann–Whitney tests were used for statistical analysis. Survival analysis was performed using Kaplan–Meier and Cox multivariate regression analyses. Results Median CA125 and HE4 levels were higher in stage III and IV tumours (p < 0.001) and in tumours with outer-half myometrial invasion (p < 0.001). ROC analysis demonstrated that HE4 (area under the curve (AUC) = 0.76) was a better predictor of outer-half myometrial invasion than CA125 (AUC = 0.65), particularly in patients with low-grade endometrioid tumours (AUC 0.77 vs 0.64 for CA125). Cox multivariate analysis demonstrated that elevated HE4 was an independent predictor of recurrence-free survival (HR = 2.40, 95% CI 1.19–4.83, p = 0.014) after adjusting for stage and grade of disease, particularly in the endometrioid subtype (HR = 2.86, 95% CI 1.25–6.51, p = 0.012). Conclusion These findings demonstrate the utility of serum HE4 as a prognostic biomarker in endometrial cancer in a large, population-based study. In particular they highlight the utility of HE4 for pre-operative risk stratification to identify high-risk patients within low-grade endometrioid endometrial cancer patients who might benefit from lymphadenectomy.

A Bayesian regression approach to assess uncertainty in pollutant wash-off modelling

Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

Environmental productivity and Kuznets curve in India

As a result of India's extremely rapid economic growth, the scale and seriousness of environmental problems are no longer in doubt. Whether pollution abatement technologies are utilized more efficiently is crucial in the analysis of environmental management because it influences the cost of alternative production and pollution abatement technologies. In this study, we use state-level industry data of sulfur dioxide, nitrogen dioxide, and suspended particular matter over the period 1991-2003. Employing recently developed productivity measurement technique, we show that overall environmental productivities decrease over time in India. Furthermore, we analyze the determinants of environmental productivities and find environmental Kuznets curve type relationship existences between environmental productivity and income. Panel analysis results show that the scale effect dominates over the technique effect. Therefore, a combined effect of income on environmental productivity is negative.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression