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Creation of predictive models of aquatic toxicity of environmental pollutants with different mechanisms of action on the basis of molecular similarity and HYBOT descriptors.

Over half of known industrial pollutants have minimal toxic effect, in line with the concept of "baseline toxicity"; such toxicity usually correlates well with lipophilicity. The remainder require additional descriptors in order to model their toxicity by the QSAR approach. Hence, it has not been possible, to date, to develop common stable QSAR models for the toxicity of diverse chemicals with various modes of action on the basis of simple regression relationships. Any new methodology has to take such different modes of action into account. In our work, we used for this purpose an original combination of the similarity concept and physicochemical descriptors calculated by HYBOT, in order to construct stable QSAR models of guppy toxicity. The training set comprised 293 diverse chemicals. Experimental value(s) of one or more nearest related chemicals were used to take structural features and possible modes of toxic action into account. In addition, molecular polarisability and hydrogen bond descriptors for the chemicals of interest and related compounds were used to calculate any additional contribution in toxicity by means of linear regression relationships. Final comparison of calculated and experimental toxicity values gave good results, with standard deviation close to the experimental error.

Animals↗

Large-scale mapping and predictive modeling of submerged aquatic vegetation in a shallow eutrophic lake.

A spatially intensive sampling program was developed for mapping the submerged aquatic vegetation (SAV) over an area of approximately 20,000 ha in a large, shallow lake in Florida, U.S. The sampling program integrates Geographic Information System (GIS) technology with traditional field sampling of SAV and has the capability of producing robust vegetation maps under a wide range of conditions, including high turbidity, variable depth (0 to 2 m), and variable sediment types. Based on sampling carried out in August-September 2000, we measured 1,050 to 4,300 ha of vascular SAV species and approximately 14,000 ha of the macroalga Chara spp. The results were similar to those reported in the early 1990s, when the last large-scale SAV sampling occurred. Occurrence of Chara was strongly associated with peat sediments, and maximal depths of occurrence varied between sediment types (mud, sand, rock, and peat). A simple model of Chara occurrence, based only on water depth, had an accuracy of 55%. It predicted occurrence of Chara over large areas where the plant actually was not found. A model based on sediment type and depth had an accuracy of 75% and produced a spatial map very similar to that based on observations. While this approach needs to be validated with independent data in order to test its general utility, we believe it may have application elsewhere. The simple modeling approach could serve as a coarse-scale tool for evaluating effects of water level management on Chara populations.

Biomass↗

Prognosis of follicular lymphoma: a predictive model based on a retrospective analysis of 987 cases. Intergruppo Italiano Linfomi.

Patients (n-987) with a histologically confirmed diagnosis of follicular lymphoma were studied with the aim of developing a prognostic model specifically devised for this type of lymphoma. We collected information on age, sex, Ann Arbor stage, number of extranodal disease sites, bone marrow (BM) involvement, bulky disease, B symptom criteria (fever, night sweats, and weight loss), performance status (PS), serum lactate dehydrogenase (LDH) level, serum albumin level, hemoglobin level, and erythrocyte sedimentation rate (ESR). In the training sample of 429 patients with complete data, multivariate analysis showed that age, sex, number of extranodal sites, B symptoms, serum LDH level, and ESR were factors predictive for overall survival. Using these 6 variables, a prognostic model was devised to identify 3 groups at different risk. The 5- and 10-year survival rate was 90% and 65% for patients at low risk, respectively; 75% and 54% for patients at intermediate risk; and 38% and 11% for those at high risk (log-rank test, 86.62; P <. 0001). The model was also predictive (P =.0001) in the validation sample of 265 patients with complete data only for the 6 variables used in the development of the model and even in the group of 210 patients from the validation sample uniformly treated with doxorubicin-containing regimens (P =.0001). The prognostic model appears to be very useful in identifying patients with follicular lymphoma at low, intermediate, or high risk.

Adult↗

A predictive model for failure to control bleeding during acute variceal haemorrhage.

BACKGROUND/AIMS: Variceal bleeding is a frequent complication of cirrhosis and is associated with a high risk of early rebleeding. In patients with peptic ulcers, continued bleeding or early rebleeding are risk factors for mortality and can be predicted by statistical models; however, no such models exist for acute variceal bleeding. METHODS: We prospectively evaluated failure to control bleeding in 695 consecutive patients with cirrhosis, admitted for haematemesis and/or melaena. Criteria were defined for failure to control bleeding, which comprised both continued bleeding or early rebleeding within 5 days of admission. There were 2 sequential groups of patients: (i) those with variceal bleeding initially treated with blood transfusion and vasoactive drugs, and if these failed followed by sclerotherapy (n = 385); (ii) those with variceal bleeding treated with injection sclerotherapy at diagnostic endoscopy (n = 144). The third group was those with bleeding from other sources related to portal hypertension (n = 166). RESULTS: Failure to control bleeding was noted in 169 (44%) patients in group 1, 55 (38%) in group 2 and 44 (25%) in group 3. Twenty variables that were evaluable within 6 h of admission, pertaining to severity of bleeding, severity of type of liver disease, mode of admission, and time of diagnostic endoscopy, were entered into a multivariate Cox model. Independent predictors of early rebleeding in group 1 were: active bleeding at endoscopy (irrespective of interval from admission) (p<0.0001), encephalopathy (p = 0.007), platelet count (p = 0.002), history of alcoholism (p = 0.002), presentation with haematemesis (p = 0.02), log urea (p = 0.03) and (shorter) interval to admission (p = 0.007). The variables predictive of 30-day mortality were: early bleeding (p<0.0007), bilirubin (p = 0.0006), encephalopathy (p<0.0001), (shorter) interval to admission (p<0.0001), and log urea (p = 0.004); a model based on these variables was also a good predictor of mortality in the other 2 groups. However, the model derived from group 1 for failure to control variceal bleeding was different in group 2, despite similar patient characteristics and a similar failure rate (following a single injection). This could suggest that sclerotherapy may induce bleeding in some patients independently of the baseline risk for failure to control bleeding. CONCLUSIONS: In cirrhotic patients who present with haematemesis or melaena, active variceal bleeding at diagnostic endoscopy is predictive of failure to control bleeding (continued bleeding or early rebleeding within 5 days of admission), and this failure is predictive of 30-day mortality.

Adolescent↗

A comparison of transient dose model predictions and experimental measurements.

The RADTRAN and RISKIND transportation risk analysis computer codes are the primary tools used to estimate dose consequences and risks associated with the transport of radioactive material. Over the years, some of the mathematical models used within the two computer codes have been updated and the methodologies to calculate input parameters have been improved. In addition, both codes have been evaluated for ease of use and appropriateness of application and verified against other computer codes that perform similar calculations. However, neither code has been validated against experimental data. This report discusses the results of five sets of experimental measurements used to partially validate the specific mathematical models used to predict the dose to an individual due to a passing shipment of radioactive material within the RADTRAN and RISKIND computer codes. Based on the comparisons it was found that RISKIND most closely predicted the measured dose in the majority of the investigated scenarios and that 12 out of 14 cases demonstrate the expected inverse relationship between the measured dose and the distance of closest approach. Only half of the data demonstrated the expected inverse relationship between dose and speed of travel.

Algorithms↗

Clinical validation of a predictive modeling equation for sodium.

Changes in plasma sodium (Na) concentration during hemodialysis were predicted by changes in Na concentration of the dialysate at equilibrium with the plasma, according to the formula C't = CD - (CD - C'0) [(V0 - QFt)/V0]A/QF, where C'0 and C't are the Na concentration of the dialysate at equilibrium with the plasma at times 0 and t, respectively; QF is the ultrafiltration flow rate; V0 is the initial total body water; and CD is the Na dialysate concentration. This modeling involves only one parameter, A, which is the effective sodium dialysance and depends on the dialyzer, the QF, the plasma water flow rate, and the actual Donnan coefficient. Parameter A was evaluated after 1 h of dialysis. Seven routine 4-h dialysis sessions were performed in which the Na concentration of dialysate at equilibrium with the plasma was measured at varying times. The mean (+/- SEM) difference between predicted and measured values was delta C = 0.5 +/- 0.2 mmol/L. These data support the validity of the model that allows the monitoring of Na dialysate concentration to obtain a prescribed Na plasma concentration at the end of a dialysis session.

Humans↗

Applicability of predictive models to the peptide mobility analysis by capillary electrophoresis-electrospray mass spectrometry.

The prediction of peptide mobility by capillary electrophoresis (CE) coupled to electrospray mass spectrometry (MS) is studied in order to verify the validity of the semi-empirical models developed in classical CE. This work relies on the experimental determination of the electrophoretic mobilities of 68 peptides, different in charge and in size. The results indicate that the prediction is possible in CE-MS experiments, in spite of the restraints inherent in the coupling conditions. The best fit of experimental data was obtained with the Offord's model. The efficiency of the model was confirmed by the analysis of a peptide mixture in CE-MS.

Amino Acid Sequence↗

Multi-scale modeling to predict ligand presentation within RGD nanopatterned hydrogels.

The adhesion ligand RGD has been coupled to various materials to be used as tissue culture matrices or cell transplantation vehicles, and recent studies indicate that nanopatterning RGD into high-density islands alters cell adhesion, proliferation, and differentiation. However, elucidating the impact of nanopattern parameters on cellular responses has been stymied by a lack of understanding of the actual ligand presentation within these systems. We have developed a multi-scale predictive modeling approach to characterize the adhesion ligand nanopatterns within an alginate hydrogel matrix. The models predict the distribution of ligand islands, the spacing between ligands within an island and the fraction of ligands accessible for cell binding. These model predictions can be used to select pattern parameter ranges for experiments on the effects of individual parameters on cellular responses. Additionally, our technique could also be applied to other polymer systems presenting peptides or other signaling molecules.

Hydrogels↗

[Identification of caries risk patients 1. An overview of predictive models].

The ability of dentists to select caries risk patients on the basis of what they see and know, varies considerably. There is a need for objective methods. Methods using bacterial counts and salivary tests appeared to be inferior compared to methods based on the caries experience of the patient. There are two models, Nexø and Dentoprog, using the caries experience as caries predictor. The well documented Nexø method does not predict caries increment, but gives the provider a tool to target preventive intervention to those patients in need. The Dentoprog method is accurate, but has only one level of caries risk, which is considered by most providers as too low and thus unpractical.

DMF Index↗

Purging of peripheral blood stem cell transplants in AML: a predictive model based on minimal residual disease burden.

OBJECTIVE: Minimal residual disease (MRD) present in peripheral blood stem cell (PBSC) products of AML patients may contribute to relapse. Our goal was to 1) predict leukemia recurrence based on the frequency of MRD present in PBSC products, 2) establish the efficacy of different purging procedures, and 3) integrate this into a model that enables to predict whether or not to purge. METHODS: Minimal residual disease was measured with flow cytometry using leukemia-associated phenotypes as established at diagnosis. Toxicity of purging procedures was established using clonogenic assays. Purging procedures used were cryopreservation, hyperthermia, ether lipid ET-18-OCH3, and combinations. RESULTS: Minimal residual disease in PBSC products correlated significantly with relapse-free survival (n=24, p=0.003). At a cut-off value of 0.05% MRD the relative risk of relapse was 4.6 times lower in the group with less than 0.05% MRD. As measured in 54 PBSC products, the MRD level was less than 0.05% in 17 of 54 cases, between 0.05% and 0.5% in 19 of 54 cases, and higher than 0.5% in 18 of 54 cases. Based on the MRD cut-off of 0.05%, the log tumor reduction needed to achieve this threshold is zero for the 17 of 54 cases in which MRD was below 0.05%, less than or equal to 1 log in 19 of 54 cases, and greater than 1-2 log in 18 of 54 cases. When applying purging with 25 mug/mL ET-18-OCH3 combined with cryopreservation at 10% DMSO and hyperthermia at 42 degrees C combined with cryopreservation at 10% or 4% DMSO, there was greater than or equal to 1 log depletion of AML blasts. CONCLUSION: This study establishes (1) a threshold level for MRD above which prognosis is worse, (2) that stem cell products from 69% of patients have higher than this "safe" MRD level, and (3) that ET-18-OCH3 and hyperthermia may be used to purge products in part of these patients.

Acute Disease↗

Model predictions and visualization of the particle flux on the surface of Mars.

Model calculations of the particle flux on the surface of Mars due to the Galactic Cosmic Rays (GCR) can provide guidance on radiobiological research and shielding design studies in support of Mars exploration science objectives. Particle flux calculations for protons, helium ions, and heavy ions are reported for solar minimum and solar maximum conditions. These flux calculations include a description of the altitude variations on the Martian surface using the data obtained by the Mars Global Surveyor (MGS) mission with its Mars Orbiter Laser Altimeter (MOLA) instrument. These particle flux calculations are then used to estimate the average particle hits per cell at various organ depths of a human body in a conceptual shelter vehicle. The estimated particle hits by protons for an average location at skin depth on the Martian surface are about 10 to 100 particle-hits/cell/year and the particle hits by heavy ions are estimated to be 0.001 to 0.01 particle-hits/cell/year.

Cosmic Radiation↗

A Bayesian forecasting model: predicting U.S. male mortality.

This article presents a Bayesian approach to forecast mortality rates. This approach formalizes the Lee-Carter method as a statistical model accounting for all sources of variability. Markov chain Monte Carlo methods are used to fit the model and to sample from the posterior predictive distribution. This paper also shows how multiple imputations can be readily incorporated into the model to handle missing data and presents some possible extensions to the model. The methodology is applied to U.S. male mortality data. Mortality rate forecasts are formed for the period 1990-1999 based on data from 1959-1989. These forecasts are compared to the actual observed values. Results from the forecasts show the Bayesian prediction intervals to be appropriately wider than those obtained from the Lee-Carter method, correctly incorporating all known sources of variability. An extension to the model is also presented and the resulting forecast variability appears better suited to the observed data.

Bayes Theorem↗

Computer-assisted modeling, prediction, and multifactor optimization in micellar electrokinetic chromatography of ionizable compounds.

Previously, the use of phenomenological models to describe the migration behavior of acidic solutes in micellar electrokinetic chromatography (MEKC) was reported. In this paper, the phenomenological approach is further extended by including both acidic and basic solutes and simultaneously taking two important experimental factors (pH and micelle concentration) into consideration. In addition, a general method is described to model the migration behavior of ionizable (both acidic and basic) solutes in MEKC with anionic and cationic micelles. The practical implication of the phenomenological approaches is that they will provide quantitative relationships between solute migration and experimental factors such that the migration behavior can be predicted on the basis of a few initial experiments and that physicochemical parameters of solutes can also be estimated from model fitting. Through computer-assisted modeling, migration behavior of several acidic and basic solutes over a pH-micelle concentration factor space was successfully predicted on the basis of only five experiments. Furthermore, this phenomenological approach was used to predict the separation of a group of aromatic amines in MEKC with anionic micelles, which resulted in a successful separation of 18 aromatic amines in less than 15 min.

Chemistry Techniques, Analytical↗

Comparison of in situ and in vitro CT scan-based finite element model predictions of proximal femoral fracture load.

Hip fracture is a serious and common injury that can lead to permanent disability, pneumonia, pulmonary embolism, and death. Research to help prevent these fractures is essential. Computed tomographic (CT) scan-based finite element (FE) modeling is a tool that can predict proximal femoral fracture loads in vitro. Because this tool might be used in vivo, this study examined whether FE models generated from CT scans in situ and in vitro yield comparable predictions of proximal femoral fracture load. CT scans of the left proximal femur of two human cadavers were obtained in situ and in vitro, and three-dimensional FE models employing nonlinear mechanical properties were generated from each CT scan. The models were evaluated under single-limb stance-type loading by applying displacements incrementally to the femoral head. The FE-predicted fracture load (F(FE)) was the maximum femoral head reaction force. F(FE) for the in situ-derived models for the two subjects were 5.2 and 13.3% greater than for the in vitro-derived models. These results demonstrate that using CT scan data obtained in situ instead of in vitro to generate FE models can lead to substantially different predicted fracture loads. This effect must be considered when using this technology in vivo.

Bone Density↗