A Generalized Estimator of the Attributable Benefit of an Optimal Treatment Regime

Summary For many diseases where there are several treatment options often there is no consensus on the best treatment to give individual patients. In such cases, it may be necessary to define a strategy for treatment assignment; that is, an algorithm that dictates the treatment an individual should receive based on their measured characteristics. Such a strategy or algorithm is also referred to as a treatment regime. The optimal treatment regime is the strategy that would provide the most public health benefit by minimizing as many poor outcomes as possible. Using a measure that is a generalization of attributable risk (AR) and notions of potential outcomes, we derive an estimator for the proportion of events that could have been prevented had the optimal treatment regime been implemented. Traditional AR studies look at the added risk that can be attributed to exposure of some contaminant; here we will instead study the benefit that can be attributed to using the optimal treatment strategy. We will show how regression models can be used to estimate the optimal treatment strategy and the attributable benefit of that strategy. We also derive the large sample properties of this estimator. As a motivating example, we will apply our methods to an observational study of 3856 patients treated at the Duke University Medical Center with prior coronary artery bypass graft surgery and further heart‐related problems requiring a catheterization. The patients may be treated with either medical therapy alone or a combination of medical therapy and percutaneous coronary intervention without a general consensus on which is the best treatment for individual patients.     

浅水湖泊生态系统稳态转换的阈值判定方法

浅水湖泊生态系统对人类干扰的反应会随着干扰力度的改变或增强而出现突然的变化,即发生稳态转换;对其机理和驱动机制的揭示将有助于对湖泊富营养化的控制及恢复.基于“多稳态”理论的稳态转换研究已广泛开展,但对浅水湖泊生态系统稳态转换的驱动机制结论各异,采用的阈值判定方法相差很大,主要有实验观测、模型模拟和统计分析3种.实验观测多关注少数特定指标,指标筛选过程复杂且工作量大;模型模拟虽能从较为全面的尺度上理解生态系统稳态变化的特征和主要机理过程,但在模型误差和不确定性的处理等问题上尚存在不足;统计分析方法基于对长时间序列数据的统计变化规律分析,用以判断或者预警稳态转换现象的发生,是目前最为常用的方法.目前稳态转换领域的研究大都是对已发生的稳态转换进行机制分析或过程反演,对未来预测与预警的问题仍然亟需加强.     

Identification of regime shifts in time series using neighborhood statistics

Sudden and significant changes in biotic and abiotic variables have been observed across a variety of systems. The identification of such regime shifts in time series includes both model-fitting and statistical approaches. We introduce two methods that use state- or measurement-space neighborhood statistics to pick out regime shifts. Analysis of simulated and real data sets shows that these methods can be an effective means of identifying regime shifts for single variable as well as multivariable time series. In addition, these methods can be used on systems with non-equilibrium steady states. However, care must be taken in interpreting results as these methods do respond to changes in time series that are not consistent with the regime shift concept.     

Guiding the self-organization of random Boolean networks

Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews eight different methods for guiding the self-organization of RBNs. In particular, the article is focused on guiding RBNs toward the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases. The properties and advantages of the critical regime for life, computation, adaptability, evolvability, and robustness are reviewed. The guidance methods of RBNs can be used for engineering systems with the features of the critical regime, as well as for studying how natural selection evolved living systems, which are also critical.     

Interaction of human serum albumin with membranes containing polymer-grafted lipids: spin-label ESR studies in the mushroom and brush regimes

The adsorption of human serum albumin (HSA) to dipalmitoyl phosphatidylcholine (DPPC) bilayer membranes containing poly(ethylene glycol)-grafted dipalmitoyl phosphatidylethanolamine (PEG-DPPE) was studied as a function of content and headgroup size of the polymer lipid. In the absence of protein, conversion from the low-density mushroom regime to the high-density brush regime of polymer-lipid content is detected by the change in ESR outer hyperfine splitting, 2A(max), of chain spin-labelled phosphatidylcholine in gel-phase membranes. The values of 2A(max) remain constant in the mushroom regime, but decrease on entering the brush regime. Conversion between the two regimes occurs at mole fractions X(PEG)(m-->b) approximately 0.04, 0.01-0.02 and 0.005-0.01 for PEG-DPPE with mean PEG molecular masses of 350, 2000 and 5000 Da, respectively, as expected theoretically. Adsorption of HSA to DPPC membranes is detected as a decrease of the spin label 2A(max) hyperfine splitting in the gel phase. Saturation is obtained at a protein/lipid ratio of ca. 1:1 w/w. In the presence of polymer-grafted lipids, HSA adsorbs to DPPC membranes only in the mushroom regime, irrespective of polymer length. In the brush regime, the spin-label values of 2A(max) are unchanged in the presence of protein. Even in the mushroom regime, protein adsorption progressively becomes strongly attenuated as a result of the steric stabilization exerted by the polymer lipid. These results are in agreement with theoretical estimates of the lateral pressure exerted by the grafted polymer in the brush and mushroom regimes, respectively.     

A new determination of the shear modulus of the human erythrocyte membrane using optical tweezers.

Optical tweezers are used to apply calibrated forces to human erythrocytes, via small silica beads bound to their membrane. The shear modulus mu of the membrane is inferred from measurements of the cell deformation in the small strain linear regime. We find the same result mu = 2.5 +/- 0.4 microN/m for both discotic and nearly spherical swollen cells. This value is smaller than the one deduced from micropipettes experiments. However the two methods do not operate in the same deformation regime and are not expected to lead to the same result.     

Thermal characteristics of Spirulina platensis cells under nongrowing conditions at various values of pH medium

The total value of heat (-Q) evolved by green-blue microalgae Spirulina platensis cells in a dark and stationary regime in the range of pH values 8.0-11.6 was determined. It was established that (-Q) reaches its maximum value at 360 +/- 40 J/g of dry biomass in the pH range 9.3-10.3 and then sharply dropped relative to these values and reached zero at pH 7.5 +/- 0.2 and 11.8 +/- 0.2. It is affirmed that an optimum regime for preservation of Spirulina platensis cell viability in a dark and stationary regime is pH range 9.3-10.3. It was also shown that the peak of heat evolution with maximum about 45 degrees C, reflecting mainly the respiration of cells (oxygen absorption rate), did not displace along the temperature scale at a change of pH from 9.3 to 10.4 and slightly displaced lower and higher of these values of pH. It is supposed that the thermostability of biomacromolecules and their complexes responsible for cell respiration does not depend on pH medium in pH range 9.3-10.3.     

Boll weevil (Coleoptera: Curculionidae) damage to cotton bolls under standard and proactive spraying

In some parts of the boll weevil's, Anthonomus grandis grandis (Boheman) (Coleoptera: Curculionidae), distribution from the United States to Argentina, insecticides are applied after cut-out (end of square production) when bolls are the predominant stage of fruiting body. This study demonstrates that the standard spray regime in southern Texas, which involves insecticide applications after cut-out, did not result in more bolls than a nonsprayed control. An alternative "proactive" spray regime focusing on protecting large squares before cut-out resulted in 1.9- to 2.5-fold more bolls in the lower half of the canopies than the control. At one of two experimental field locations, the percentage of damaged boll carpels was 3-fold greater in the standard spray regime's lower canopy than in the proactive spray regime, and the percentage in the control was 1.6-fold greater than in the standard regime. At both experimental field locations, the upper canopy control had 2.1- to 2.3-fold greater percentages of carpel damage than the proactive spray regime. The standard spray regime resulted in 2.3-fold greater percentage of carpel damage than the proactive regime. In the control and the standard spray regime, percentages of upper canopy nondamaged bolls were mostly lower than or not different from percentages of bolls with one, two, three, or all four carpels damaged, but in the proactive regime, percentage of nondamaged bolls in the upper canopy was greater than percentages of bolls with one or more damaged carpels. Reasons for the ineffectiveness of the standard spray regime and the benefits observed in the proactive approach are discussed.     

Flexible search tactics and efficient foraging in saltatory searching animals

Summary Foraging is one of the most important endeavors undertaken by animals, and it has been studied intensively from both mechanistic-empirical and optimal foraging perspectives. Planktivorous fish make excellent study organisms for foraging studies because they feed frequently and in a relatively simple environment. Most optimal foraging studies of planktivorous fish have focused, either on diet choice or habitat selection and have assumed that these animals used a cruise search foraging strategy. We have recently recognized that white crappie do not use a cruise search strategy (swimming continuously and searching constantly) while foraging on zooplankton but move in a stop and go pattern, searching only while paused. We have termed thissaltatory search. Many other animals move in a stop and go pattern while foraging, but none have been shown to search only while paused. Not only do white crappie search in a saltatory manner but the components of the search cycle change when feeding on prey of different size. When feeding on large prey these fish move further and faster after an unsuccessful search than when feeding on small prey. The fish also pause for a shorter period to search when feeding on large prey. To evaluate the efficiency of these alterations in the search cycle, a net energy gain simulation model was developed. The model computes the likelihood of locating 1 or 2 different size classes of zooplankton prey as a function of the volume of water scanned. The volume of new water searched is dependent upon the dimensions of the search volume and the length of the run. Energy costs for each component of the search cycle, and energy gained from the different sized prey, were assessed. The model predicts that short runs produce maximum net energy gains when crappie feed on small prey but predicts net energy gains will be maximized with longer runs when crappie feed on large prey or a mixed assemblage of large and small prey. There is an optimal run length due to high energy costs of unsuccessful search when runs are short and reveal little new water, and high energy costs of long runs when runs are lengthy. The model predicts that if the greater search times observed when crappie feed on small prey are assessed when they feed on a mixed diet of small and large prey, net energy gained is less than if small prey are deleted from the diet. We believe the model has considerable generality. Many animals are observed to move in a saltatory manner while foraging and some are thought to search only while stationary. Some birds and lizards are, known to modify the search cycle in a manner similar to white crappie.Components of the search cycle and dimensions of the location space SST (sec) Successful search time — the average time stationary prior to a pursuit - USST (sec) Unsuccessful search time — the average time stationary prior to a run - PT (sec) Pursuit time-PL/SS — the time to pursue prey at a given distance away. It is calculated by dividing the pursuit distance by swim speed - RT (sec) Run time-RL/SS — the time to complete a run of a given length. It is calculated by dividing the run length, by swim speed - PL (cm) Pursuit length-distance moved to attack prey - RL (cm) Run length-distance moved between consecutive searches - SS (cm/sec) Swim speed — the speed of movement during a pursuit or run - LS (l) Location space — the area or volume within which prey are located. In the case of white crappie the search space is shaped like a pie wedge with the fish positioned at the apex of the wedge - LA (^o) Location angle—the angle of the wedge-shaped search space - LH (cm) Location height—the height of the wedge-shaped search space - LD (cm) Location distance—the length of long axis of the wedge-shaped search space. Components of the location probability model RND Random number-random number generated through BASICA - SV (l) Search volume—the volume of water actually searched after one run of given length - SV_MAX (l) Maximum search volume—the greatest search volume that can be based upon LA, LH, LD and unaffected by the previous search - SV_R (l) Search volume researched—that volume of SV_MAX that is researched where RLo Search volume unsearched—that volume of SV_MAX not previously searched - AD (#/1) Absolute density—the density of zooplankton prey in numbers per liter - VD (#) Visual density—the number of zooplankton prey in the search volume - LP (%) Location probability—the probability that one or more prey are in the search volume Components of the net energy gain model NEG (cal/sec) Net energy gain-total calories ingested, less total calories used, divided by total time. - E _e (cal) Energy expended on the search cycle - E _i (cal) Energy intake - e _p (cal) Energy content of a given individual prey - P _i Total number of prey ingested - e _r (cal) Energy expended while searching - e _s (cal) Energy expended while swimming - T _t (sec) Total time-time expended to eat a given number of prey     

Marine ecosystem regime shifts: challenges and opportunities for ecosystem-based management

Regime shifts have been observed in marine ecosystems around the globe. These phenomena can result in dramatic changes in the provision of ecosystem services to coastal communities. Accounting for regime shifts in management clearly requires integrative, ecosystem-based management (EBM) approaches. EBM has emerged as an accepted paradigm for ocean management worldwide, yet, despite the rapid and intense development of EBM theory, implementation has languished, and many implemented or proposed EBM schemes largely ignore the special characteristics of regime shifts. Here, we first explore key aspects of regime shifts that are of critical importance to EBM, and then suggest how regime shifts can be better incorporated into EBM using the concept of integrated ecosystem assessment (IEA). An IEA uses approaches that determine the likelihood that ecological or socio-economic properties of systems will move beyond or return to acceptable bounds as defined by resource managers and policy makers. We suggest an approach for implementing IEAs for cases of regime shifts where the objectives are either avoiding an undesired state or returning to a desired condition. We discuss the suitability and short-comings of methods summarizing the status of ecosystem components, screening and prioritizing potential risks, and evaluating alternative management strategies. IEAs are evolving as an EBM approach that can address regime shifts; however, advances in statistical, analytical and simulation modelling are needed before IEAs can robustly inform tactical management in systems characterized by regime shifts.     

Analysis of the flow field induced by the sessile peritrichous ciliate Opercularia asymmetrica

The feeding mechanism of the sessile protozoon Opercularia asymmetrica (Oligohymenophorea, Peritrichia) relies on the cilia beat generating a flow field that convectively transports suspended particles and dissolved substances to the oral cavity of the organism. By use of optical micro-flow measurement and theoretical methods the flow environment of two neighbouring peritrichous ciliate cells is studied. Both, yeast cells (Saccharomyces cerevisiae) and artificial flow tracers are used for the visualisation of the flow field. Artificial tracers are rejected by the protozoa and deviate from the fluid path lines, while yeast cells follow the flow almost perfectly. This is shown through a dimensional analysis of the involved hydrodynamic forces on the tracers. The measured flow field exhibits maximum velocities of 25 microm/s at around 20 microm distance ahead of an individual ciliate. The flow field extends 200 microm from the location of the ciliate. A nicking motion of the protozoon is observed and found not to obey any periodic law. Multiples of protozoa exhibit most commonly an alternating cilia beat regime generating a non-stationary flow field. It can be shown through theoretical methods that fluid exchange is enhanced in this alternating regime compared to a flow field generated by a single ciliate. Fluid exchange depends on the distance of the ciliates from each other and on the alteration frequency of the cilia beat. The comparison of an analytical Stokes' flow solution with the observed fluid flow serves to determine the force required to maintain the flow field against viscous dissipation. The force magnitude is in the order of magnitude of 10-100 pN.     

利用泽兰实蝇控制紫茎泽兰的生防策略研究

本文根据野外泽兰实蝇种群15个世代的调查资料,利用契贝谢夫正交多项式拟合了泽兰实蝇、紫茎泽兰的空间格局。阐明了泽兰实蝇空间格局的序列变化及紫茎泽兰空间格局的特点;揭示了泽兰实蝇空间格局的特点受当地主风及寄主紫茎泽兰空间格局特点的影响;并从最优控制系统的角度对泽兰实蝇-紫茎泽兰系统作了初步探讨。首次提出了最佳释放虫量指标为每条虫占有10条枝条。这些结果为多点释放及定点多次释放泽兰实蝇防治紫茎泽兰这一生防策略提供了理论基础。     

带扩散的Logistic单种群模型及其最优收获

在一些合理的假设条件下,就空间分布非均匀的Ｌｏｇｉｓｔｉｃ型收获模型 得到了与空间分布均匀的Ｌｏｇｉｓｔｉｃ型收获模型［１,２,３］完全平行的结论,其中包括种群持续生存和灭绝时收获努力量 Ｅ（ｘ）须满足的充要条件、种群持续生存时趋于正平衡状态的速度估计、种群灭绝时其密度趋于０的速度估计以及在种群持续生存条件下的最优收获努力量 Ｅ、最优平衡解 ｐ（ｘ）和最大收获量 ｈ＊     

Changes in composition of membrane proteins accompanying the regulation of PS I/PS II stoichiometry observed with Synechocystis PCC 6803

Changes in composition of membrane proteins in Synechocystis PCC 6803 induced by the shift of light regime for photosynthetic growth were studied in relation to the regulation of PS I/PS II stoichiometry. Special attention was paid to the changes in abundance of proteins of PS I and PS II complexes. Composition was examined using a LDS-PAGE and a quantitative enzyme immunoassay. Abundance of PsaA/B polypeptides and the PsaC polypeptide of the PS I complex, on a per cell basis, increased under the light regime exciting preferentially PS II and decreased under the light regime exciting mainly PS I. Similar changes were observed with polypeptides of 18.5, 10 and 8.5 kDa. The abundance of other proteins associated with membranes, including PsbA polypeptide of the PS II complex, was fairly constant irrespective of light regime. These results are consistent with our previous observations with other strains of cyanophytes (Anabaena variabilis M2 and Synechocystis PCC 6714) that PS I is the variable component in changes in PS I/PS II stoichiometry in response to changing light regimes for photosynthesis.Abbreviations CBB Coomassie brilliant blue - Chl chlorophyll - EIA enzyme immunoassay - LDS lithium dodecyl sulfate - PAGE polyacrylamide gel electrophoresis - PS photosystem - PVDF polyvinylidene difluoride     

Water in keratin. Piezoelectric, dielectric, and elastic experiments.

To investigate actions of water in keratin, the piezoelectric, dielectric, and elastic constants are measured at 10 Hz, at temperatures between -160 and 150 degrees C, and at various hydration levels. From changes in the piezoelectric, dielectric, and dynamic mechanical parameters with moisture content (m.c.), we have identified three regimes (I, II, and III) in the hydration of water for keratin. At high hydration (21% m.c.) around 0 degree C, the piezoelectric constants for keratin steeply decrease with increasing temperature. This may be attributed to interfacial polarization which is strongly related to self-associated water molecules (particularly regime III water) just around crystalline helical regions which can exhibit the stress-induced, i.e., piezoelectric, polarization and may be attributed to electrode polarization induced by the increase of mobile ions in the amorphous matrix region, some of which would be released from their trapped states just around the piezoelectric phase by the regime III water. With increasing hydration, the elastic constants for keratin are found to increase below -70 degrees C and decrease above -70 degrees C. This suggests a viscoelastic transition of the keratin structure due to bound water (regime II water). The piezoelectric, dielectric, and elastic loss peaks are found at around -120 degrees C for hydrated keratin, believed to be due to tightly bound water (regime I water), which acts only to stiffen the keratin structure. The adsorption regions of water in keratin are discussed by a piezoelectric two-phase model, which consists of piezoelectric and nonpiezoelectric phases. It is proposed that water molecule would at least adsorb in the nonpiezoelectric phase.     

Prestressing in finite deformation abdominal aortic aneurysm simulation

In abdominal aortic aneurysm (AAA) simulation the patient-specific geometry of the object of interest is very often reconstructed from in vivo medical imaging such as CT scans. Such geometries represent a deformed configuration stressed by typical in vivo conditions. However, commonly, such structures are considered stress-free in simulation. In this contribution we sketch and compare two methods to introduce a physically meaningful stress/strain state to the obtained geometry for simulations in the finite strain regime and demonstrate the necessity of such prestressing techniques. One method is based on an inverse design analysis to calculate a stress-free reference configuration. The other method developed here is based on a modified updated Lagrangian formulation. Formulation of both methods is provided. Applicability and accurateness of both approaches are compared and evaluated utilizing fully three-dimensional patient-specific AAA structures in the finite strain regime.     

Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection

The receiver operating characteristic (ROC) curve is used to evaluate a biomarker's ability for classifying disease status. The Youden Index (J), the maximum potential effectiveness of a biomarker, is a common summary measure of the ROC curve. In biomarker development, levels may be unquantifiable below a limit of detection (LOD) and missing from the overall dataset. Disregarding these observations may negatively bias the ROC curve and thus J. Several correction methods have been suggested for mean estimation and testing; however, little has been written about the ROC curve or its summary measures. We adapt non-parametric (empirical) and semi-parametric (ROC-GLM [generalized linear model]) methods and propose parametric methods (maximum likelihood (ML)) to estimate J and the optimal cut-point (c *) for a biomarker affected by a LOD. We develop unbiased estimators of J and c * via ML for normally and gamma distributed biomarkers. Alpha level confidence intervals are proposed using delta and bootstrap methods for the ML, semi-parametric, and non-parametric approaches respectively. Simulation studies are conducted over a range of distributional scenarios and sample sizes evaluating estimators' bias, root-mean square error, and coverage probability; the average bias was less than one percent for ML and GLM methods across scenarios and decreases with increased sample size. An example using polychlorinated biphenyl levels to classify women with and without endometriosis illustrates the potential benefits of these methods. We address the limitations and usefulness of each method in order to give researchers guidance in constructing appropriate estimates of biomarkers' true discriminating capabilities.     

Consistent probabilistic outputs for protein function prediction

In predicting hierarchical protein function annotations, such as terms in the Gene Ontology (GO), the simplest approach makes predictions for each term independently. However, this approach has the unfortunate consequence that the predictor may assign to a single protein a set of terms that are inconsistent with one another; for example, the predictor may assign a specific GO term to a given protein ('purine nucleotide binding') but not assign the parent term ('nucleotide binding'). Such predictions are difficult to interpret. In this work, we focus on methods for calibrating and combining independent predictions to obtain a set of probabilistic predictions that are consistent with the topology of the ontology. We call this procedure 'reconciliation'. We begin with a baseline method for predicting GO terms from a collection of data types using an ensemble of discriminative classifiers. We apply the method to a previously described benchmark data set, and we demonstrate that the resulting predictions are frequently inconsistent with the topology of the GO. We then consider 11 distinct reconciliation methods: three heuristic methods; four variants of a Bayesian network; an extension of logistic regression to the structured case; and three novel projection methods - isotonic regression and two variants of a Kullback-Leibler projection method. We evaluate each method in three different modes - per term, per protein and joint - corresponding to three types of prediction tasks. Although the principal goal of reconciliation is interpretability, it is important to assess whether interpretability comes at a cost in terms of precision and recall. Indeed, we find that many apparently reasonable reconciliation methods yield reconciled probabilities with significantly lower precision than the original, unreconciled estimates. On the other hand, we find that isotonic regression usually performs better than the underlying, unreconciled method, and almost never performs worse; isotonic regression appears to be able to use the constraints from the GO network to its advantage. An exception to this rule is the high precision regime for joint evaluation, where Kullback-Leibler projection yields the best performance.