A new method to determine mean adult height from incomplete follow-up data

BACKGROUND/AIM: In long-term growth studies with adult height (AH) as outcome, reporting is often required while data are incomplete because some participants have not yet reached AH whereas others might be lost to follow-up. Current practice is to analyze only participants who did reach AH, which can easily give biased results. We introduce a new method into the area of growth research. METHODS: We used the data of patients from a registration database and a growth study. The new method uses growth data in time intervals. The percentage of children still growing and the mean growth at each interval are used to determine mean AH. RESULTS: With the new method, estimated mean AHs had smaller bias and standard error than with commonly used methods. The method is not hampered by a correlation between AH and age at reaching AH, unlike methods merely using patients who have reached AH. CONCLUSION: In contrast to commonly used methods, the new method provides valid results on mean AH when complete actual measurements of AH are not (yet) available, provided that drop-out, if any, is not related to (disappointing) growth. As it also uses observed data of children with incomplete follow-up, the method employs the data more effectively.     

A method for parameter optimization in computational biology

Models in computational biology, such as those used in binding, docking, and folding, are often empirical and have adjustable parameters. Because few of these models are yet fully predictive, the problem may be nonoptimal choices of parameters. We describe an algorithm called ENPOP (energy function parameter optimization) that improves-and sometimes optimizes-the parameters for any given model and for any given search strategy that identifies the stable state of that model. ENPOP iteratively adjusts the parameters simultaneously to move the model global minimum energy conformation for each of m different molecules as close as possible to the true native conformations, based on some appropriate measure of structural error. A proof of principle is given for two very different test problems. The first involves three different two-dimensional model protein molecules having 12 to 37 monomers and four parameters in common. The parameters converge to the values used to design the model native structures. The second problem involves nine bumpy landscapes, each having between 4 and 12 degrees of freedom. For the three adjustable parameters, the globally optimal values are known in advance. ENPOP converges quickly to the correct parameter set.     

A fluorescence ratio-based method to determine microalgal viability and its application to rapid optimization of cryopreservation

The utility of microalgal biomass and bioproducts depends on long-term maintenance of certain physiological or biochemical features of the species. While unique characteristics may not be durably maintained with general subculture, cryopreservation methods better prevent alterations from desired characteristics. Post-thaw viability is critical to establishing microalgal cultures, and there is a critical need to effectively and rapidly evaluate microalgal viability after the post-thawing process. In the present study, we developed a rapid assay based on the change of fluorescence ratio to determine microalgal viability post-thaw. It was shown that the assessment of microalgal viability by the fluorescence ratio method correlated well with that of the FDA-staining (R² = 0.978) and regrowth method (R² = 0.976), demonstrating that the present method could be applied in the high-throughput detection of viability of microalgal strains. Subsequent to establishing this method, we aimed to find out optimal cryopreservation protocol for each strain from a group of 125 microalgal strains. The viability of these strains under different treatments was quickly evaluated by the fluorescence ratio method. Of these strains, 95 attained post-thaw viability over 60%. DMSO was a suitable cryoprotectant for most strains at a concentration ≤10%. Based on the dataset, the relative contribution of 3 variables-genus, cryoprotectants and concentration to post-viability was analyzed with the Random Forest (RF) classification method. All variables together could explain 97.8% of the viability, and type and concentration of cryoprotectant could explain 59.1% in Chlorophyta. This study provided a new approach for viability assay and demonstrated that this method can facilitate to find out the optimal protocols for cryopreservation of microalgal strains.     

A simple iterative approach to parameter optimization.

Various bioinformatics problems require optimizing several different properties simultaneously. For example, in the protein threading problem, a scoring function combines the values for different parameters of possible sequence-to-structure alignments into a single score to allow for unambiguous optimization. In this context, an essential question is how each property should be weighted. As the native structures are known for some sequences, a partial ordering on optimal alignments to other structures, e.g., derived from structural comparisons, may be used to adjust the weights. To resolve the arising interdependence of weights and computed solutions, we propose a heuristic approach: iterating the computation of solutions (here, threading alignments) given the weights and the estimation of optimal weights of the scoring function given these solutions via systematic calibration methods. For our application (i.e., threading), this iterative approach results in structurally meaningful weights that significantly improve performance on both the training and the test data sets. In addition, the optimized parameters show significant improvements on the recognition rate for a grossly enlarged comprehensive benchmark, a modified recognition protocol as well as modified alignment types (local instead of global and profiles instead of single sequences). These results show the general validity of the optimized weights for the given threading program and the associated scoring contributions.     

A graphical method to determine the ordering of moult,illustrated with data from the Blackshouldered Kite Elanus caeruleus

When the order in which feathers moult is not constant and the pattern is complex, it is difficult to discover the usual pattern simply by inspecting the data. This paper illustrates a method, the Gower analysis, that produces a graphical plot from which it is relatively easy to deduce the usual ordering.     

An ultrasound elastography method to determine the local stiffness of arteries with guided circumferential waves

Arterial stiffness is highly correlated with the functions of the artery and may serve as an important diagnostic criterion for some cardiovascular diseases. To date, it remains a challenge to quantitatively assess local arterial stiffness in a non-invasive manner. To address this challenge, we investigated the possibility of determining arterial stiffness using the guided circumferential wave (GCW) induced in the arterial wall by a focused acoustic radiation force. The theoretical model for the dispersion analysis of the GCW is presented, and a finite element model has been established to calculate the dispersion curve. Our results show that under described conditions, the dispersion relations of the GCW are basically independent of the curvature of the arterial wall and can be well-described using the Lamb wave (LW) model. Based on this conclusion, an inverse method is proposed to characterize the elastic modulus of artery. Both numerical experiments and phantom experiments had been performed to validate the proposed method. We show that our method can be applied to the cases in which the artery has local stenosis and/or the geometry of the artery cross-section is irregular; therefore, this method holds great potential for clinical use.     

A finite element based method to determine the properties of planar soft tissue.

A finite element based method to determine the incremental elastic material properties of planar membranes was developed and evaluated. The method is applicable to tissues that exhibit inhomogeneity, geometric and material nonlinearity, and anisotropy. Markers are placed on the tissue to form a four-node quadrilateral element. The specimen is loaded to an initial reference state, then three incremental loading sets are applied and the nodal displacements recorded. One of these loadings must include shear. These data are used to solve an over-determined system of equations for the tangent stiffness matrix. The method was first verified using analytical data. Next, data obtained from a latex rubber sheet were used to evaluate experimental procedures. Finally, experiments conducted on preconditioned rat skin revealed nonlinear orthotropic behavior. The vector norm comparing the applied and calculated nodal force vectors was used to evaluate the accuracy of the solutions.     

A new method to determine DNA sugar conformation from the joint use of 2D and 3D NMR data

The use of sugar restraints has been proven essential for assessing DNAstructures through molecular modeling studies. We present a new methodcombining 2D (COSY and NOESY) and 3D (NOESY-NOESY) experiments, whereconstraints on either the phase angles or the difference between phase anglesof two residues are obtained from comparison of 2D NOE H1-H4intensities and 3D NOE intensities containing the H1-H4transfer. All experiments lead to restraints that match, proving the validityof the method.     

A novel force field parameter optimization method based on LSSVR for ECEPP

In this paper, we propose a novel force field parameter optimization method based on LSSVR and optimize the torsion energy parameters of ECEPP force field. In this method force field parameter optimization problem is turned into a support vector regression problem. Protein samples for regression model training are chosen from Protein Data Bank. The experiments show that the optimized force-field parameters make both α-helix and β-hairpin structures more consistent with the experimental implications than the original parameters.     

A different approach to generating the data for parameter estimation with the heterotrophic activity method

This paper outlines a different approach to generating the data for V_max and T_t estimation with the Wright-Hobbie [1] method of measuring heterotrophic activities in aquatic environments. To be certain that the incubation times chosen are appropriate for all concentrations of substrate tested, and to increase the precision of the kinetic parameter estimates, we have adopted the approach of using kinetic plots derived from independent time-course studies performed at each concentration of substrate and analyzed by non-linear regression analysis. In keeping with our interest in the impact of acidification on aquatic microbial activities, we have applied this approach to the sediments and water column of the acid-stressed Silver Lake.     

An adaptation of the LMS method to determine expression variations in profiling data

One of the major issues in expression profiling analysis still is to outline proper thresholds to determine differential expression, while avoiding false positives. The problem being that the variance is inversely proportional to the log of signal intensities. Aiming to solve this issue, we describe a model, expression variation (EV), based on the LMS method, which allows data normalization and to construct confidence bands of gene expression, fitting cubic spline curves to the Box-Cox transformation. The confidence bands, fitted to the actual variance of the data, include the genes devoid of significant variation, and allow, based on the confidence bandwidth, to calculate EVs. Each outlier is positioned according to the dispersion space (DS) and a P-value is statistically calculated to determine EV. This model results in variance stabilization. Using two Affymetrix-generated datasets, the sets of differentially expressed genes selected using EV and other classical methods were compared. The analysis suggests that EV is more robust on variance stabilization and on selecting differential expression from both rare and strongly expressed genes.     

A rapid method to determine the mammalian cell cycle

A method was developed for determining the duration of the mammalian cell cycle and each of its major phases, mitosis, G1, DNA synthetic period, and G2. Mitotic time was determined by assessment of the mitotic index at intervals after cells collected in mitosis and stored at 4 °C were reincubated at 37 °C. The duration of the three remaining phases was derived from a graphic representation of the uptake of ³H-thymidine by a synchronous population of cells grown directly in scintillation vials. The scintillation counting method for determination of these parameters is advantageous over methods using autoradiography in that the investigator's bias in scoring cells is eliminated. Complex mathematical interpretations are unnecessary, and the data obtained from the scintillation counter are readily processed. Results from scintillation counting and autoradiographic methods are shown to be comparable.     

A new simple method to determine the diffusion coefficient from Active Enzyme Centrifugation experiments

A simple and accurate procedure to determine the diffusion coefficient from Active Enzyme Centrifugation experiments is presented. Using computer-simulated concentration distributions we demonstrate that the procedure, derived by Vinograd for the conventional band sedimentation, is suitable to exploit Active Enzyme Centrifugation experiments when the Cohen's Difference Curves Method is used. This new empirical method avoids all the difficulties of the rigorous method previously proposed by Cohen et al., without any loss of accuracy. Optimal conditions are described which allow the determination of the enzyme diffusion coefficient with a 5% uncertainty. Such an easy determination of the sedimentation and diffusion coefficients by the AEC technique can provide a good and rapid estimation of the active enzyme molecular weight, either with a low amount of material or in very impure preparations.     

A method for the identification of in-vivo segmental stiffness properties of the spine

A numerical algorithm is used to estimate in-vivo segmental stiffness properties of individual spine segments based upon existing load-displacement data. A static nonlinear finite element model stimulates a pathological spine and corrective instrumentation system. A systematic procedure for establishing the model's stiffness parameters is described, in the form of a nonlinear constrained optimal design problem. The numerical method is demonstrated using as an example a case of adolescent idiopathic scoliosis requiring corrective surgery.     

Reliability of parameter estimates from models applied to respiratory impedance data

Many previous studies have fit lumped parameter models to respiratory input (Zin) and transfer (Ztr) impedance data. For frequency ranges higher than 4-32 Hz, a six-element model may be required in which an airway branch (with a resistance and inertance) is separated from a tissue branch (with a resistance, inertance, and compliance) by a shunt compliance. A sensitivity analysis is applied to predict the effects of frequency range on the accuracy of parameter estimates in this model obtained from Zin or Ztr data. Using a parameter set estimated from experimental data between 4 and 64 Hz in dogs, both Zin and Ztr were simulated from 4 to 200 Hz. Impedance sensitivity to each parameter was also calculated over this frequency range. The simulation predicted that for Zin a second resonance occurs near 80 Hz and that the impedance is considerably more sensitive to several of the parameters at frequencies surrounding this resonance than at any other frequencies. Also, unless data is obtained at very high frequencies (where the model is suspect), Zin data provides more accurate estimates than Ztr data. After adding random noise to the simulated Zin data, we attempted to extract the original parameters by using a nonlinear regression applied to three frequency ranges: 4-32, 4-64, and 4-110 Hz. Estimated parameters were substantially incorrect when using only 4- to 32-Hz or 4- to 64-Hz data, but nearly correct when fitting 4- to 110-Hz data. These results indicate that respiratory system parameters can be more accurately extracted from Zin than Ztr, and to make physiological inferences from parameter estimates based on Zin impedance data in dogs, the data must include frequencies surrounding the second resonance.     

Inversion of Markov processes to determine rate constants from single-channel data.

The determination of rate constants from single-channel data can be very difficult, in part because the single-channel lifetime distributions commonly analyzed by experimenters often have a complicated mathematical relation to the channel gating mechanism. The standard treatment of channel gating as a Markov process leads to the prediction that lifetime distributions are exponential functions. As the number of states of a channel gating scheme increases, the number of exponential terms in the lifetime distribution increases, and the weights and decay constants of the lifetime distributions become progressively more complicated functions of the underlying rate constants. In the present study a mathematical strategy for inverting these functions is introduced in order to determine rate constants from single-channel lifetime distributions. This inversion is easy for channel gating schemes with two or fewer states of a given conductance, so the present study focuses on schemes with more states. The procedure is to derive explicit equations relating the parameters of the lifetime distribution to the rate constants of the scheme. Such equations can be derived using the equality between symmetric functions of eigenvalues of a matrix and sums over principle minors, as well as expressions for the moments, derivatives, and weights of a lifetime distribution. The rate constants are then obtained as roots to this system of equations. For a gating scheme with three sequential closed states and a single gateway state, exact analytical expressions were found for each rate constant in terms of the parameters of the three-exponential closed-time distribution. For several other gating schemes, systems of equations were found that could be solved numerically to obtain the rate constants. Lifetime distributions were shown to specify a unique set of real rate constants in sequential gating schemes with up to five closed or five open states. For kinetic schemes with multiple gating pathways, the analysis of simulated data revealed multiple solutions. These multiple solutions could be distinguished by examining two-dimensional probability density functions. The utility of the methods introduced here are demonstrated by analyzing published data on nicotinic acetylcholine receptors, GABA(A) receptors, and NMDA receptors.     

A theoretical experimental method to determine the locus of desensitization

Consider a ligand-gated channel with n agonist binding sites which can undergo desensitization. We present a theoretical experimental procedure for pinpointing the principal receptor state from which there is a transition to the desensitized state. The method is based on the observation that the dependence of the slope of the time constant of desensitization vs agonist concentration, at low concentrations, represents the state from which desensitization occurs. In those receptors where desensitization occurs from the open state (or the one immediately preceding it), the method also enables us to determine the number of binding sites.