A new ovarian response prediction index (ORPI): implications for individualised controlled ovarian stimulation

Background: The objective was to present a new ovarian response prediction index (ORPI), which was based on anti-Mullerian hormone (AMH) levels, antral follicle count (AFC) and age, and to verify whether it could be a reliable predictor of the ovarian stimulation response.Methods: A total of 101 patients enrolled in the ICSI programme were included. The ORPI values were calculated by multiplying the AMH level (ng/ml) by the number of antral follicles (2-9 mm), and the result was divided by the age (years) of the patient (ORPI=(AMH x AFC)/Patient age).Results: The regression analysis demonstrated significant (P<0.0001) positive correlations between the ORPI and the total number of oocytes and of MII oocytes collected. The logistic regression revealed that the ORPI values were significantly associated with the likelihood of pregnancy (odds ratio (OR): 1.86; P=0.006) and collecting greater than or equal to 4 oocytes (OR: 49.25; P<0.0001), greater than or equal to 4 MII oocytes (OR: 6.26; P<0.0001) and greater than or equal to 15 oocytes (OR: 6.10; P<0.0001). Regarding the probability of collecting greater than or equal to 4 oocytes according to the ORPI value, the ROC curve showed an area under the curve (AUC) of 0.91 and an efficacy of 88% at a cut-off of 0.2. In relation to the probability of collecting greater than or equal to 4 MII oocytes according to the ORPI value, the ROC curve had an AUC of 0.84 and an efficacy of 81% at a cut-off of 0.3. The ROC curve for the probability of collecting greater than or equal to 15 oocytes resulted in an AUC of 0.89 and an efficacy of 82% at a cut-off of 0.9. Finally, regarding the probability of pregnancy occurrence according to the ORPI value, the ROC curve showed an AUC of 0.74 and an efficacy of 62% at a cut-off of 0.3.Conclusions: The ORPI exhibited an excellent ability to predict a low ovarian response and a good ability to predict a collection of greater than or equal to 4 MII oocytes, an excessive ovarian response and the occurrence of pregnancy in infertile women. The ORPI might be used to improve the cost-benefit ratio of ovarian stimulation regimens by guiding the selection of medications and by modulating the doses and regimens according to the actual needs of the patients.

Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

Pushover analysis for the seismic response prediction of cable-stayed bridges under multi-directional excitation

Cable-stayed bridges represent nowadays key points in transport networks and their seismic behavior needs to be fully understood, even beyond the elastic range of materials. Both nonlinear dynamic (NL-RHA) and static (pushover) procedures are currently available to face this challenge, each with intrinsic advantages and disadvantages, and their applicability in the study of the nonlinear seismic behavior of cable-stayed bridges is discussed here. The seismic response of a large number of finite element models with different span lengths, tower shapes and class of foundation soil is obtained with different procedures and compared. Several features of the original Modal Pushover Analysis (MPA) are modified in light of cable-stayed bridge characteristics, furthermore, an extension of MPA and a new coupled pushover analysis (CNSP) are suggested to estimate the complex inelastic response of such outstanding structures subjected to multi-axial strong ground motions.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Background: There is growing evidence that individual EEG differences may aid in classifying patients with major depressive disorder (MDD) and also help predict clinical response to antidepressant treatment. This study aims to compare the effectiveness of EEG frequency band power, alpha asymmetry and prefrontal theta cordance towards escitalopram response prediction and MDD diagnosis, in a multi-site initiative. Methods: Resting EEG (eyes open and closed) was recorded from 64 electrodes in 44 depressed patients and 20 healthy controls at baseline, 2 weeks post-treatment and 8 weeks post-treatment. Clinical response was measured as change from baseline MADRS of 50% or more. EEG measures were analyzed (1) at baseline (2) at 2 weeks post-treatment and (3) as an ‘‘early change” variable defined as change in EEG from baseline to 2 weeks post-treatment. Results: At baseline, responders exhibited greater absolute alpha power in the left hemisphere versus the right while non-responders showed the opposite. Responders further exhibited a cortical asymmetry of greater right relative to left activity in parietal areas. Groups also differed in baseline relative delta power with responders showing greater power in the right hemisphere versus the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to right and the opposite was noted for non-responders. The opposite pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reduction in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance. Absolute delta power helped distinguish MDD patients from healthy controls. Conclusions: Hemispheric asymmetries in the alpha and delta bands at pre-treatment baseline and at 2 weeks post-treatment have moderate to moderately strong predictive utility towards antidepressant treatment response. These findings have significant potential for improving clinical practice in psychiatry by eventually guiding clinical choice of treatments. This would greatly benefit patients awaiting relief from depressive symptoms as treatment optimization would help overcome problems associated with delayed recovery. Our results also indicate that resting EEG activity may have clinical utility in predicting MDD diagnosis.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Thesis (Ph.D, Neuroscience Studies) -- Queen's University, 2016-08-27 00:55:35.782

Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

IMPROVING QUANTITATIVE TREATMENT RESPONSE MONITORING WITH DEFORMABLE IMAGE REGISTRATION

Quantitative imaging with 18F-FDG PET/CT has the potential to provide an in vivo assessment of response to radiotherapy (RT). However, comparing tissue tracer uptake in longitudinal studies is often confounded by variations in patient setup and potential treatment induced gross anatomic changes. These variations make true response monitoring for the same anatomic volume a challenge, not only for tumors, but also for normal organs-at-risk (OAR). The central hypothesis of this study is that more accurate image registration will lead to improved quantitation of tissue response to RT with 18F-FDG PET/CT. Employing an in-house developed “demons” based deformable image registration algorithm, pre-RT tumor and parotid gland volumes can be more accurately mapped to serial functional images. To test the hypothesis, specific aim 1 was designed to analyze whether deformably mapping tumor volumes rather than aligning to bony structures leads to superior tumor response assessment. We found that deformable mapping of the most metabolically avid regions improved response prediction (P<0.05). The positive predictive power for residual disease was 63% compared to 50% for contrast enhanced post-RT CT. Specific aim 2 was designed to use parotid gland standardized uptake value (SUV) as an objective imaging biomarker for salivary toxicity. We found that relative change in parotid gland SUV correlated strongly with salivary toxicity as defined by the RTOG/EORTC late effects analytic scale (Spearman’s ρ = -0.96, P<0.01). Finally, the goal of specific aim 3 was to create a phenomenological dose-SUV response model for the human parotid glands. Utilizing only baseline metabolic function and the planned dose distribution, predicting parotid SUV change or salivary toxicity, based upon specific aim 2, became possible. We found that the predicted and observed parotid SUV relative changes were significantly correlated (Spearman’s ρ = 0.94, P<0.01). The application of deformable image registration to quantitative treatment response monitoring with 18F-FDG PET/CT could have a profound impact on patient management. Accurate and early identification of residual disease may allow for more timely intervention, while the ability to quantify and predict toxicity of normal OAR might permit individualized refinement of radiation treatment plan designs.

Advances in the analysis and design of concrete structures, metal containments and liner plate for extreme loads

The material presented in this paper summarizes the progress that has been made in the analysis, design, and testing of concrete structures. The material is summarized in the following documents: 1. Part I - Containment Design Criteria and Loading Combinations - J.D. Stevenson (Stevenson and Associates, Cleveland, Ohio, USA) 2. Part II - Reinforced and Prestressed Concrete Behavior - J. Eibl and M. Curbach (Karlsruhe University, Karlsruhe, Germany) 3. Part III - Concrete Containment Analysis, Design and Related Testing - T.E. Johnson and M.A. Daye (Bechtel Power Corporation, Gaithersburg, Maryland USA) 4. Part IV - Impact and Impulse Loading and Response Prediction - J.D. Riera (School of Engineering - UFRGS, Porto Alegre, RS, Brazil) 5. Part V - Metal Containments and Liner Plate Systems - N.J. Krutzik (Siemens AG, Offenbach Am Main, Germany) 6. Part VI - Prestressed Reactor Vessel Design, Testing and Analysis - J. Nemet (Austrian Research Center, Seibersdorf, Austria) and K.T.S. Iyengar (Indian Institute of Science, Bangalore, India).

An invariant subspace-based approach to the random eigenvalue problem of systems with clustered spectrum

The repeated or closely spaced eigenvalues and corresponding eigenvectors of a matrix are usually very sensitive to a perturbation of the matrix, which makes capturing the behavior of these eigenpairs very difficult. Similar difficulty is encountered in solving the random eigenvalue problem when a matrix with random elements has a set of clustered eigenvalues in its mean. In addition, the methods to solve the random eigenvalue problem often differ in characterizing the problem, which leads to different interpretations of the solution. Thus, the solutions obtained from different methods become mathematically incomparable. These two issues, the difficulty of solving and the non-unique characterization, are addressed here. A different approach is used where instead of tracking a few individual eigenpairs, the corresponding invariant subspace is tracked. The spectral stochastic finite element method is used for analysis, where the polynomial chaos expansion is used to represent the random eigenvalues and eigenvectors. However, the main concept of tracking the invariant subspace remains mostly independent of any such representation. The approach is successfully implemented in response prediction of a system with repeated natural frequencies. It is found that tracking only an invariant subspace could be sufficient to build a modal-based reduced-order model of the system. Copyright (C) 2012 John Wiley & Sons, Ltd.

CFD结合降阶模型预测阵风响应

传统的阵风响应主要在频域内进行分析，气动载荷基于线性方法计算，不能考虑黏性和跨声速流动影响．飞机设计需考虑不同频率和不同形状阵风的响应，基于CFD的阵风响应预测由于计算工况太多，工作量巨大．本文发展了一种CFD结合非定常气动力ARMA（autoregressive—moving—averagemodel）降阶模型的阵风响应分析方法，CFD只要针对给定频率和形状的一种阵风响应进行计算，对获得的气动力时间历程运用线性最小二乘法参数辨识ARMA降阶模型的系数，则对任意频率和形状的阵风，代入降阶模型即可确定该阵风的响应，大大提高了计算效率．为效验发展的方法，先计算NACA0012翼型在低马赫数0．11的阵风响应，通过对比CFD、ARMA降阶模型及早期发展的不可压阵风响应预测方法的结果，验证了方法的有效性．再对比CFD、ARMA在跨声速马赫数0．8的阵风响应预测结果，证实所发展的方法对跨声速阵风响应预测亦是有效的．

A comparison of methods for the coupled analysis of floating structures

The dynamic analysis of a deepwater floating platform and the associated mooring/riser system should ideally be fully coupled to ensure a reliable response prediction. It is generally held that a time domain analysis is the only means of capturing the various coupling and nonlinear effects accurately. However, in recent work it has been found that for an ultra-deepwater floating system (2000m water depth), the highly efficient frequency domain approach can provide highly accurate response predictions. One reason for this is the accuracy of the drag linearization procedure over both first and second order motions, another reason is the minimal geometric nonlinearity displayed by the mooring lines in deepwater. In this paper, the aim is to develop an efficient analysis method for intermediate water depths, where both mooring/vessel coupling and geometric nonlinearity are of importance. It is found that the standard frequency domain approach is not so accurate for this case and two alternative methods are investigated. In the first, an enhanced frequency domain approach is adopted, in which line nonlinearities are linearized in a systematic way. In the second, a hybrid approach is adopted in which the low frequency motion is solved in the time domain while the high frequency motion is solved in the frequency domain; the two analyses are coupled by the fact that (i) the low frequency motion affects the mooring line geometry for the high frequency motion, and (ii) the high frequency motion affects the drag forces which damp the low frequency motion. The accuracy and efficiency of each of the methods are systematically compared. Copyright © 2007 by ASME.

Lovastatin production by Aspergillus terreus using lignocellulose biomass in large scale packed bed reactor

The effect of superficial air velocity on lovastatin production by Aspergillus terreus PL10 using wheat bran and wheat straw was investigated in a 7 l and a 1200 l packed bed reactor. Mass transfer and reaction limitations on bioconversion in the 1200 l reactor was studied based on a central composite design of experiments constructed using the superficial air velocity and solid substrate composition as variables and lovastatin production as response.
The surface response prediction showed a maximum lovastatin production of 1.86 mg g-1 dry substrate on day 5 of the bioconversion process when the reactor was operated using 0.19 vvm airflow rate (23.37 cm min-1 superficial air velocity) and 54% substrate composition (wC). Lovastatin production did not increase significantly with superficial air velocity in the 7 l reactor. Variation in temperature and exit CO2 composition was recorded, and the Damköhler number was calculated for lovastatin production at these two scales. The results showed that in larger reactors mass transfer limitation controlled bioconversion while in smaller reactors bioconversion was controlled by reaction rate limitations. In addition, mass transfer limitations in larger reactors reduced the rate of metabolic heat removal, resulting in hot spots within the substrate bed.