Linear prediction application for modelling the relationships between a large number of stand characteristics of Norway spruce stands

Abstract

The INTERMED questionnaire for predicting return to work after a multidisciplinary rehabilitation program for chronic low back pain.

OBJECTIVES: To evaluate the performance of the INTERMED questionnaire score, alone or combined with other criteria, in predicting return to work after a multidisciplinary rehabilitation program in patients with non-specific chronic low back pain. METHODS: The INTERMED questionnaire is a biopsychosocial assessment and clinical classification tool that separates heterogeneous populations into subgroups according to case complexity. We studied 88 patients with chronic low back pain who followed an intensive multidisciplinary rehabilitation program on an outpatient basis. Before the program, we recorded the INTERMED score, radiological abnormalities, subjective pain severity, and sick leave duration. Associations between these variables and return to full-time work within 3 months after the end of the program were evaluated using one-sided Fisher tests and univariate logistic regression followed by multivariate logistic regression. RESULTS: The univariate analysis showed a significant association between the INTERMED score and return to work (P<0.001; odds ratio, 0.90; 95% confidence interval, 0.86-0.96). In the multivariate analysis, prediction was best when the INTERMED score and sick leave duration were used in combination (P=0.03; odds ratio, 0.48; 95% confidence interval, 0.25-0.93). CONCLUSION: The INTERMED questionnaire is useful for evaluating patients with chronic low back pain. It could be used to improve the selection of patients for intensive multidisciplinary programs, thereby improving the quality of care, while reducing healthcare costs.

Prediction of plant species distributions across six millennia.

The usefulness of species distribution models (SDMs) in predicting impacts of climate change on biodiversity is difficult to assess because changes in species ranges may take decades or centuries to occur. One alternative way to evaluate the predictive ability of SDMs across time is to compare their predictions with data on past species distributions. We use data on plant distributions, fossil pollen and current and mid-Holocene climate to test the ability of SDMs to predict past climate-change impacts. We find that species showing little change in the estimated position of their realized niche, with resulting good model performance, tend to be dominant competitors for light. Different mechanisms appear to be responsible for among-species differences in model performance. Confidence in predictions of the impacts of climate change could be improved by selecting species with characteristics that suggest little change is expected in the relationships between species occurrence and climate patterns.

Treatment deviating from guidelines does not influence status epilepticus prognosis.

Status epilepticus (SE) prognosis is related to nonmodifiable factors (age, etiology), but the exact role of drug treatment is unclear. This study was undertaken to address the prognostic role of treatment adherence to guidelines (TAG). We prospectively studied over 26 months a cohort of adults with incident SE (excluding postanoxic). TAG was assessed in terms of drug doses (± 30 % of recommendations) and medication sequence; its prognostic impact on mortality and return to baseline conditions was adjusted for etiology, SE severity [Status Epilepticus Severity Score (STESS)], and comorbidities. Of 225 patients, 26 (12 %) died and 82 (36 %) were discharged with a new handicap; TAG was observed in 142 (63 %). On univariate analysis, age, etiology, SE severity, and comorbidities were significantly related to outcome, while TAG was associated with neither outcome nor likelihood of SE control. Logistic regression for mortality identified etiology [odds ratio (OR) 18.8, 95 % confidence interval (CI) 4.3-82.8] and SE severity (STESS ≥ 3; OR 1.7, 95 % CI 1.2-2.4) as independent predictors, and for lack of return to baseline, again etiology (OR 7.4, 95 % CI 3.9-14.0) and STESS ≥ 3 (OR 1.7, 95 % CI 1.4-2.2). Similar results were found for the subgroup of 116 patients with generalized-convulsive SE. Receiver operator characteristic (ROC) analyses confirmed that TAG did not improve outcome prediction. This study of a large SE cohort suggests that treatment adherence to recommendations using current medications seems to play a negligible prognostic role (class III), confirming the importance of the biological background. Awaiting further treatment trials, it appears mandatory to apply resources towards identification of new therapeutic approaches.

Field data and prediction models of pesticide spray drift on coffee crop

The objective of this work was to generate drift curves from pesticide applications on coffee plants and to compare them with two European drift-prediction models. The used methodology is based on the ISO 22866 standard. The experimental design was a randomized complete block with ten replicates in a 2x20 split-plot arrangement. The evaluated factors were: two types of nozzles (hollow cone with and without air induction) and 20 parallel distances to the crop line outside of the target area, spaced at 2.5 m. Blotting papers were used as a target and placed in each of the evaluated distances. The spray solution was composed of water+rhodamine B fluorescent tracer at a concentration of 100 mg L-1, for detection by fluorimetry. A spray volume of 400 L ha-1 was applied using a hydropneumatic sprayer. The air-induction nozzle reduces the drift up to 20 m from the treated area. The application with the hollow cone nozzle results in 6.68% maximum drift in the nearest collector of the treated area. The German and Dutch models overestimate the drift at distances closest to the crop, although the Dutch model more closely approximates the drift curves generated by both spray nozzles.

Premenopausal serum androgens and breast cancer risk: a nested case-control study.

ABSTRACT: INTRODUCTION: Prospective epidemiologic studies have consistently shown that levels of circulating androgens in postmenopausal women are positively associated with breast cancer risk. However, data in premenopausal women are limited. METHODS: A case-control study nested within the New York University Women's Health Study was conducted. A total of 356 cases (276 invasive and 80 in situ) and 683 individually-matched controls were included. Matching variables included age and date, phase, and day of menstrual cycle at blood donation. Testosterone, androstenedione, dehydroandrosterone sulfate (DHEAS) and sex hormone-binding globulin (SHBG) were measured using direct immunoassays. Free testosterone was calculated. RESULTS: Premenopausal serum testosterone and free testosterone concentrations were positively associated with breast cancer risk. In models adjusted for known risk factors of breast cancer, the odds ratios for increasing quintiles of testosterone were 1.0 (reference), 1.5 (95% confidence interval (CI), 0.9 to 2.3), 1.2 (95% CI, 0.7 to 1.9), 1.4 (95% CI, 0.9 to 2.3) and 1.8 (95% CI, 1.1 to 2.9; Ptrend = 0.04), and for free testosterone were 1.0 (reference), 1.2 (95% CI, 0.7 to 1.8), 1.5 (95% CI, 0.9 to 2.3), 1.5 (95% CI, 0.9 to 2.3), and 1.8 (95% CI, 1.1 to 2.8, Ptrend = 0.01). A marginally significant positive association was observed with androstenedione (P = 0.07), but no association with DHEAS or SHBG. Results were consistent in analyses stratified by tumor type (invasive, in situ), estrogen receptor status, age at blood donation, and menopausal status at diagnosis. Intra-class correlation coefficients for samples collected from 0.8 to 5.3 years apart (median 2 years) in 138 cases and 268 controls were greater than 0.7 for all biomarkers except for androstenedione (0.57 in controls). CONCLUSIONS: Premenopausal concentrations of testosterone and free testosterone are associated with breast cancer risk. Testosterone and free testosterone measurements are also highly reliable (that is, a single measurement is reflective of a woman's average level over time). Results from other prospective studies are consistent with our results. The impact of including testosterone or free testosterone in breast cancer risk prediction models for women between the ages of 40 and 50 years should be assessed. Improving risk prediction models for this age group could help decision making regarding both screening and chemoprevention of breast cancer.

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

The objective of this work was to develop uni- and multivariate models to predict maximum soil shear strength (τmax) under different normal stresses (σn), water contents (U), and soil managements. The study was carried out in a Rhodic Haplustox under Cerrado (control area) and under no-tillage and conventional tillage systems. Undisturbed soil samples were taken in the 0.00-0.05 m layer and subjected to increasing U and σn, in shear strength tests. The uni- and multivariate models - respectively τmax=10(a+bU) and τmax=10(a+bU+cσn) - were significant in all three soil management systems evaluated and they satisfactorily explain the relationship between U, σn, and τmax. The soil under Cerrado has the highest shear strength (τ) estimated with the univariate model, regardless of the soil water content, whereas the soil under conventional tillage shows the highest values with the multivariate model, which were associated to the lowest water contents at the soil consistency limits in this management system.

Prediction of hip fracture risk by quantitative ultrasound in more than 7000 Swiss women > or =70 years of age: comparison of three technologically different bone ultrasound devices in the SEMOF study.

To compare the prediction of hip fracture risk of several bone ultrasounds (QUS), 7062 Swiss women > or =70 years of age were measured with three QUSs (two of the heel, one of the phalanges). Heel QUSs were both predictive of hip fracture risk, whereas the phalanges QUS was not. INTRODUCTION: As the number of hip fracture is expected to increase during these next decades, it is important to develop strategies to detect subjects at risk. Quantitative bone ultrasound (QUS), an ionizing radiation-free method, which is transportable, could be interesting for this purpose. MATERIALS AND METHODS: The Swiss Evaluation of the Methods of Measurement of Osteoporotic Fracture Risk (SEMOF) study is a multicenter cohort study, which compared three QUSs for the assessment of hip fracture risk in a sample of 7609 elderly ambulatory women > or =70 years of age. Two QUSs measured the heel (Achilles+; GE-Lunar and Sahara; Hologic), and one measured the heel (DBM Sonic 1200; IGEA). The Cox proportional hazards regression was used to estimate the hazard of the first hip fracture, adjusted for age, BMI, and center, and the area under the ROC curves were calculated to compare the devices and their parameters. RESULTS: From the 7609 women who were included in the study, 7062 women 75.2 +/- 3.1 (SD) years of age were prospectively followed for 2.9 +/- 0.8 years. Eighty women reported a hip fracture. A decrease by 1 SD of the QUS variables corresponded to an increase of the hip fracture risk from 2.3 (95% CI, 1.7, 3.1) to 2.6 (95% CI, 1.9, 3.4) for the three variables of Achilles+ and from 2.2 (95% CI, 1.7, 3.0) to 2.4 (95% CI, 1.8, 3.2) for the three variables of Sahara. Risk gradients did not differ significantly among the variables of the two heel QUS devices. On the other hand, the phalanges QUS (DBM Sonic 1200) was not predictive of hip fracture risk, with an adjusted hazard risk of 1.2 (95% CI, 0.9, 1.5), even after reanalysis of the digitalized data and using different cut-off levels (1700 or 1570 m/s). CONCLUSIONS: In this elderly women population, heel QUS devices were both predictive of hip fracture risk, whereas the phalanges QUS device was not.

What makes one person paranoid and another person anxious? The differential prediction of social anxiety and persecutory ideation in an experimental situation

The study shows that social anxiety and persecutory ideation share many of the same predictive factors. Non-clinical paranoia may be a type of anxious fear. However, perceptual anomalies are a distinct predictor of paranoia. In the context of an individual feeling anxious, the occurrence of odd internal feelings in social situations may lead to delusional ideas through a sense of" things not seeming right". The study illustrates the approach of focusing on experiences such as paranoid thinking rather than diagnoses such as schizophrenia.

Genome-wide prediction of matrix attachment regions that increase gene expression in mammalian cells.

Gene transfer in eukaryotic cells and organisms suffers from epigenetic effects that result in low or unstable transgene expression and high clonal variability. Use of epigenetic regulators such as matrix attachment regions (MARs) is a promising approach to alleviate such unwanted effects. Dissection of a known MAR allowed the identification of sequence motifs that mediate elevated transgene expression. Bioinformatics analysis implied that these motifs adopt a curved DNA structure that positions nucleosomes and binds specific transcription factors. From these observations, we computed putative MARs from the human genome. Cloning of several predicted MARs indicated that they are much more potent than the previously known element, boosting the expression of recombinant proteins from cultured cells as well as mediating high and sustained expression in mice. Thus we computationally identified potent epigenetic regulators, opening new strategies toward high and stable transgene expression for research, therapeutic production or gene-based therapies.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.