Evaluating the Experience of Teen-to-Teen Crisis Line Volunteers: A Pilot Study.

Teen-to-teen (t2t) crisis lines are a special type of crisis service where youth volunteers help their peers. Although prior research has examined the experience of adult crisis line responders, no research has examined the experience of adolescents who do this work. In collaboration with two of the largest t2t lines in the U.S., this pilot study is the first examination of t2t crisis line work. Volunteers (ages 14-20) reported: their primary motivation for joining the crisis lines was to help others and give back to the community; responding to a range of peers' problems on the t2t crisis line, including high-risk suicide contacts; and a range of ways the crisis line work impacted their lives. Findings provide preliminary information about the experience of adolescents engaging in t2t crisis line work. Additional research is needed in larger and more diverse samples to understand the impact of crisis line work for youth.

Enzyme leaps fuel antichemotaxis.

There is mounting evidence that enzyme diffusivity is enhanced when the enzyme is catalytically active. Here, using superresolution microscopy [stimulated emission-depletion fluorescence correlation spectroscopy (STED-FCS)], we show that active enzymes migrate spontaneously in the direction of lower substrate concentration ("antichemotaxis") by a process analogous to the run-and-tumble foraging strategy of swimming microorganisms and our theory quantifies the mechanism. The two enzymes studied, urease and acetylcholinesterase, display two families of transit times through subdiffraction-sized focus spots, a diffusive mode and a ballistic mode, and the latter transit time is close to the inverse rate of catalytic turnover. This biochemical information-processing algorithm may be useful to design synthetic self-propelled swimmers and nanoparticles relevant to active materials. Executed by molecules lacking the decision-making circuitry of microorganisms, antichemotaxis by this run-and-tumble process offers the biological function to homogenize product concentration, which could be significant in situations when the reactant concentration varies from spot to spot.

Green function of correlated genes in a minimal mechanical model of protein evolution.

The function of proteins arises from cooperative interactions and rearrangements of their amino acids, which exhibit large-scale dynamical modes. Long-range correlations have also been revealed in protein sequences, and this has motivated the search for physical links between the observed genetic and dynamic cooperativity. We outline here a simplified theory of protein, which relates sequence correlations to physical interactions and to the emergence of mechanical function. Our protein is modeled as a strongly coupled amino acid network with interactions and motions that are captured by the mechanical propagator, the Green function. The propagator describes how the gene determines the connectivity of the amino acids and thereby, the transmission of forces. Mutations introduce localized perturbations to the propagator that scatter the force field. The emergence of function is manifested by a topological transition when a band of such perturbations divides the protein into subdomains. We find that epistasis-the interaction among mutations in the gene-is related to the nonlinearity of the Green function, which can be interpreted as a sum over multiple scattering paths. We apply this mechanical framework to simulations of protein evolution and observe long-range epistasis, which facilitates collective functional modes.

A semiparametric modeling approach for analyzing clinical biomarkers restricted to limits of detection.

Before biomarkers can be used in clinical trials or patients' management, the laboratory assays that measure their levels have to go through development and analytical validation. One of the most critical performance metrics for validation of any assay is related to the minimum amount of values that can be detected and any value below this limit is referred to as below the limit of detection (LOD). Most of the existing approaches that model such biomarkers, restricted by LOD, are parametric in nature. These parametric models, however, heavily depend on the distributional assumptions, and can result in loss of precision under the model or the distributional misspecifications. Using an example from a prostate cancer clinical trial, we show how a critical relationship between serum androgen biomarker and a prognostic factor of overall survival is completely missed by the widely used parametric Tobit model. Motivated by this example, we implement a semiparametric approach, through a pseudo-value technique, that effectively captures the important relationship between the LOD restricted serum androgen and the prognostic factor. Our simulations show that the pseudo-value based semiparametric model outperforms a commonly used parametric model for modeling below LOD biomarkers by having lower mean square errors of estimation.

Statistical ensemble inequivalence for flexible polymers under confinement in various geometries.

The problem of statistical ensemble inequivalence for single polymers has been the subject of intense research. In a recent publication, we show that even though the force-extension relation of a free Gaussian chain exhibits ensemble equivalence, confinement to half-space due to tethering to a planar substrate induces significant inequivalence [S. Dutta and P. Benetatos, Soft Matter, 2018, 14, 6857-6866]. In the present article, we extend that work to the conformational response to confining forces distributed over surfaces. We analyze in both the Helmholtz and the Gibbs ensemble the pressure-volume equation of state of a chain in rectangular, spherical, and cylindrical confinement. We especially consider the case of a directed polymer in a cylinder. We also analyze the case of a tethered chain inside a rectangular box, a sphere, and outside a sphere. In general, confinement causes significant ensemble inequivalence. Remarkably, we recover ensemble equivalence in the limit of squashing confinement. We trace the ensemble inequivalence to the persistence of strong fluctuations. Our work may be useful in the interpretation of single molecule experiments and caging phenomena.

Score and deviance residuals based on the full likelihood approach in survival analysis.

Assuming the proportional hazards model and non-informative censoring, the full likelihood approach is used to obtain two new residuals. The first residual is based on the ideas used in obtaining score-type residuals similar to the partial likelihood approach. The second type of residual is based on the concept of deviance residuals. Extensive simulations are conducted to compare the performance of the residuals from the full likelihood-based approach with those of the partial likelihood method. We demonstrate through simulation studies that the full likelihood-based residuals are more efficient than their partial likelihood counterpart in identifying potential outliers when the censoring proportion is high. The graphical techniques are used to illustrate the applications of these residuals using some examples.

Complexation and coacervation of like-charged polyelectrolytes inspired by mussels.

It is well known that polyelectrolyte complexes and coacervates can form on mixing oppositely charged polyelectrolytes in aqueous solutions, due to mainly electrostatic attraction between the oppositely charged polymers. Here, we report the first (to the best of our knowledge) complexation and coacervation of two positively charged polyelectrolytes, which provides a new paradigm for engineering strong, self-healing interactions between polyelectrolytes underwater and a new marine mussel-inspired underwater adhesion mechanism. Unlike the conventional complex coacervate, the like-charged coacervate is aggregated by strong short-range cation-π interactions by overcoming repulsive electrostatic interactions. The resultant phase of the like-charged coacervate comprises a thin and fragile polyelectrolyte framework and round and regular pores, implying a strong electrostatic correlation among the polyelectrolyte frameworks. The like-charged coacervate possesses a very low interfacial tension, which enables this highly positively charged coacervate to be applied to capture, carry, or encapsulate anionic biomolecules and particles with a broad range of applications.

Rank-based inference for covariate and group effects in clustered data in presence of informative intra-cluster group size.

There have been numerous attempts to extend the Wilcoxon rank-sum test to clustered data. Recently, one such rank-sum test (Dutta & Datta, 2016, Biometrics 72, 432-440) was developed to compare the group-specific marginal distributions of outcomes in clustered data where the conditional distributions of outcomes depend on the number of observations from that group in a given cluster, a phenomenon referred to as informative intra-cluster group (ICG) size. However, comparison of group-specific marginal distributions may not be sufficient in presence of some potentially useful covariables that are observed in the study. In addition, not accounting for the effect of these covariates can lead to biased and misleading inference for the group comparisons. Thus, the purpose of this article is twofold. First, we develop a method to estimate the covariate effects using rank-based weighted estimating equations that are appropriate when the ICG size is informative. Second, we construct an aligned rank-sum test based on the covariate adjusted outcomes. Asymptotic distributions of the R-estimators and the test statistic are provided. Through simulation studies, we show the importance of selecting proper weights in constructing the estimating equations when informativeness is present through the cluster or ICG sizes. We also demonstrate the superiority and the robustness of our method in comparison to regular parametric linear mixed models in clustered data. We apply our method to analyze different real-life data sets including a data on birthweights of rat pups in different litters and a dental data on tooth attachment loss.

Inequivalence of fixed-force and fixed-extension statistical ensembles for a flexible polymer tethered to a planar substrate.

Recent advances in single macromolecule experiments have sparked interest in the ensemble dependence of force-extension relations. The thermodynamic limit may not be attainable for such systems, which leads to inequivalence of the fixed-force and the fixed-extension ensembles. We consider an ideal Gaussian chain described by the Edwards Hamiltonian with one end tethered to a rigid planar substrate. We analytically calculate the force-extension relation in the two ensembles and we show their inequivalence, which is caused by the confinement of the polymer to half space. The inequivalence is quite remarkable for strong compressional forces. We also perform Monte-Carlo simulations of a tethered wormlike chain with contour length 20 times its persistence length, which corresponds to experiments measuring the conformations of DNA tethered to a wall. The simulations confirm the ensemble inequivalence and qualitatively agree with the analytical predictions of the Gaussian model. Our analysis shows that confinement due to tethering causes ensemble inequivalence, irrespective of the polymer model.

Temporal Prediction of Future State Occupation in a Multistate Model from High-Dimensional Baseline Covariates via Pseudo-Value Regression.

In many complex diseases such as cancer, a patient undergoes various disease stages before reaching a terminal state (say disease free or death). This fits a multistate model framework where a prognosis may be equivalent to predicting the state occupation at a future time t. With the advent of high throughput genomic and proteomic assays, a clinician may intent to use such high dimensional covariates in making better prediction of state occupation. In this article, we offer a practical solution to this problem by combining a useful technique, called pseudo value regression, with a latent factor or a penalized regression method such as the partial least squares (PLS) or the least absolute shrinkage and selection operator (LASSO), or their variants. We explore the predictive performances of these combinations in various high dimensional settings via extensive simulation studies. Overall, this strategy works fairly well provided the models are tuned properly. Overall, the PLS turns out to be slightly better than LASSO in most settings investigated by us, for the purpose of temporal prediction of future state occupation. We illustrate the utility of these pseudo-value based high dimensional regression methods using a lung cancer data set where we use the patients' baseline gene expression values.

A rank-sum test for clustered data when the number of subjects in a group within a cluster is informative.

The Wilcoxon rank-sum test is a popular nonparametric test for comparing two independent populations (groups). In recent years, there have been renewed attempts in extending the Wilcoxon rank sum test for clustered data, one of which (Datta and Satten, 2005, Journal of the American Statistical Association 100, 908-915) addresses the issue of informative cluster size, i.e., when the outcomes and the cluster size are correlated. We are faced with a situation where the group specific marginal distribution in a cluster depends on the number of observations in that group (i.e., the intra-cluster group size). We develop a novel extension of the rank-sum test for handling this situation. We compare the performance of our test with the Datta-Satten test, as well as the naive Wilcoxon rank sum test. Using a naturally occurring simulation model of informative intra-cluster group size, we show that only our test maintains the correct size. We also compare our test with a classical signed rank test based on averages of the outcome values in each group paired by the cluster membership. While this test maintains the size, it has lower power than our test. Extensions to multiple group comparisons and the case of clusters not having samples from all groups are also discussed. We apply our test to determine whether there are differences in the attachment loss between the upper and lower teeth and between mesial and buccal sites of periodontal patients.

Adsorption of highly charged Gaussian polyelectrolytes onto oppositely charged surfaces.

In many biological processes highly charged biopolymers are adsorbed onto oppositely charged surfaces of macroions and membranes. They form strongly correlated structures close to the surface which cannot be explained by the conventional Poisson-Boltzmann theory. In this work strong coupling theory is used to study the adsorption of highly charged Gaussian polyelectrolytes. Two cases of adsorptions are considered, when the Gaussian polyelectrolytes are confined (a) by one charged wall, and (b) between two charged walls. The effects of salt and the geometry of the polymers on their adsorption-depletion transitions in the strong coupling regime are discussed.

Entangled polymer complexes as Higgs phenomena.

We derive an effective Maxwell-London equation for entangled polymer complexes under topological constraints, borrowing the theoretical framework from topological field theory. We find that the transverse current flux of a test polymer chain, surrounded by entangled chains, decays exponentially from its centerline position with a finite penetration depth, which is analogous to the magnetic-field decay in a superconductor (SC), referred to as the Meissner effect. Just as the mass acquirement of photons in a SC is the origin of the magnetic-field decay, the polymer obtains uncrossable intersections along the chain due to the preservation of the linking number, which restricts the deviation of the transverse polymer current in the normal direction. The underlying physics is as follows: less flexible polymers have stronger current-current correlations, giving rise to a heavier effective mass of the gauge fields and resulting in a shorter decay length. Interestingly, this picture is well incorporated within the most successful phenomenological theory of the, so called, tube model, the microscopic origins of which researchers have long pursued. The correspondence of our equation of motion to the tube model claims that the confining tube potential is a consequence of the topological constraint (linking number). The tube radius is attributed to the decay length. On increasing the effective mass (by strengthening the interaction at an uncrossable intersection or a number of intersections), the tube becomes narrower. Using this argument, the exponential decay of the chain leakage out of the tube is well understood.

Most probable paths for active Ornstein-Uhlenbeck particles.

Fluctuations play an important role in the dynamics of stochastic systems. In particular, for small systems, the most probable thermodynamic quantities differ from their averages because of the fluctuations. Using the Onsager Machlup variational formalism we analyze the most probable paths for nonequilibrium systems, in particular, active Ornstein-Uhlenbeck particles, and investigate how the entropy production along these paths differs from the average entropy production. We investigate how much information about their nonequilibrium nature can be obtained from their extremum paths and how these paths depend on the persistence time and their swim velocities. We also look at how the entropy production along the most probable paths varies with the active noise and how it differs from the average entropy production. This study would be useful to design artificial active systems with certain target trajectories.

Machine learning for lumbar and pelvis kinematics clustering.

Clustering algorithms such as k-means and agglomerative hierarchical clustering (HCA) may provide a unique opportunity to analyze time-series kinematic data. Here we present an approach for determining number of clusters and which clustering algorithm to use on time-series lumbar and pelvis kinematic data. Cluster evaluation measures such as silhouette coefficient, elbow method, Dunn Index, and gap statistic were used to evaluate the quality of decision making. The result show that multiple clustering evaluation methods should be used to determine the ideal number of clusters and algorithm suitable for clustering time-series data for each dataset being analyzed.

Colossal Power Extraction from Active Cyclic Brownian Information Engines.

Brownian information engines can extract work from thermal fluctuations by utilizing information. To date, the studies on Brownian information engines consider the system in a thermal bath; however, many processes in nature occur in a nonequilibrium setting, such as the suspensions of self-propelled microorganisms or cellular environments called an active bath. Here, we introduce an archetypal model for a Maxwell-demon type cyclic Brownian information engine operating in a Gaussian correlated active bath capable of extracting more work than its thermal counterpart. We obtain a general integral fluctuation theorem for the active engine that includes additional mutual information gained from the active bath with a unique effective temperature. This effective description modifies the generalized second law and provides a new upper bound for the extracted work. Unlike the passive information engine operating in a thermal bath, the active information engine extracts colossal power that peaks at the finite cycle period. Our study provides fundamental insights into the design and functioning of synthetic and biological submicrometer motors in active baths under measurement and feedback control.

Reaching and violating thermodynamic uncertainty bounds in information engines.

Thermodynamic uncertainty relations (TURs) set fundamental bounds on the fluctuation and dissipation of stochastic systems. Here, we examine these bounds, in experiment and theory, by exploring the entire phase space of a cyclic information engine operating in a nonequilibrium steady state. Close to its maximal efficiency, we find that the engine violates the original TUR. This experimental demonstration of TUR violation agrees with recently proposed softer bounds: The engine satisfies two generalized TUR bounds derived from the detailed fluctuation theorem with feedback control and another bound linking fluctuation and dissipation to mutual information and Renyi divergence. We examine how the interplay of work fluctuation and dissipation shapes the information conversion efficiency of the engine, and find that dissipation is minimal at a finite noise level, where the original TUR is violated.

Efficiency fluctuations and noise induced refrigerator-to-heater transition in information engines.

Understanding noisy information engines is a fundamental problem of non-equilibrium physics, particularly in biomolecular systems agitated by thermal and active fluctuations in the cell. By the generalized second law of thermodynamics, the efficiency of these engines is bounded by the mutual information passing through their noisy feedback loop. Yet, direct measurement of the interplay between mutual information and energy has so far been elusive. To allow such examination, we explore here the entire phase-space of a noisy colloidal information engine, and study efficiency fluctuations due to the stochasticity of the mutual information and extracted work. We find that the average efficiency is maximal for non-zero noise level, at which the distribution of efficiency switches from bimodal to unimodal, and the stochastic efficiency often exceeds unity. We identify a line of anomalous, noise-driven equilibrium states that defines a refrigerator-to-heater transition, and test the generalized integral fluctuation theorem for continuous engines.

Androgen decline and survival during docetaxel therapy in metastatic castration resistant prostate cancer (mCRPC).

BACKGROUND: Multiple androgens drive prostate cancer progression and higher pre-treatment levels of androgens, even within the castrate range, have been previously shown to be associated with an improved overall survival (OS) in mCRPC. Docetaxel impairs microtubules, has androgen receptor (AR) inhibitory effects and is used in both the castration resistant and sensitive settings, where androgen dynamics may impact outcome. The present analysis evaluates the association of decline in serum androgen levels (Testosterone (T), Androstenedione (A) and DHEA in docetaxel-treated mCRPC patients with OS. METHODS: Data from 1050 men treated on CALGB 90401 with docetaxel, prednisone and either bevacizumab or placebo were evaluated. Eligibility required progressive mCRPC and no prior chemotherapy. Pre-treatment, 6 week and progression serum assays for T, A and DHEA were performed via tandem Liquid Chromatography-Mass Spectrometry (LC-MS/MS). Changes in T, A and DHEA levels from baseline to 6 weeks were calculated as the ratio of 6-week over baseline. The proportional hazards model was used to assess the prognostic significance of changes in T, A, and DHEA from baseline to 6 weeks in predicting OS adjusting for known prognostic factors. RESULTS: Median baseline values for T, A, and, DHEA were 1.0, 13.5, and 8.1 ng/dL respectively while 6 week levels were 0.64, 7.0, and 6.8 ng/dL respectively. Median OS for low testosterone decline is 20.9 months vs 26.3 months for high testosterone decline. In multivariable analysis including known prognostic variables, change in testosterone levels was independently associated with greater OS; the hazard ratio for death with each unit increase in the 6-week/baseline ratio is 1.02 (95% CI = 1.01-1.03, p = 0.001). Decline in A and DHEA were not significant predictors of OS. In multivariable analysis change in the serum changes did not predict PFS however the ratio of T at 6-weeks over baseline was prognostic of ≥50% decline in PSA with an odds ratio of 0.93 (95% CI = 0.85-0.98, p-value = 0.039). CONCLUSIONS: Declines in testosterone during docetaxel treatment is associated with a longer survival, consistent with a favorable prognostic significance of higher serum androgens in the CRPC.

Androgens and Overall Survival in Patients With Metastatic Castration-resistant Prostate Cancer Treated With Docetaxel.

BACKGROUND: Pre-treatment androgen levels are associated with overall survival (OS) in patients with metastatic castration-resistant prostate cancer (CRPC) treated with androgen synthesis inhibitors. The current study sought to determine whether pre-treatment serum androgens predict clinical outcome among patients with metastatic CRPC treated with docetaxel chemotherapy. MATERIALS AND METHODS: Data were obtained from 1050 men who were chemotherapy-naive prior to treatment with docetaxel, prednisone, and either bevacizumab or placebo (CALGB 90401). Pretreatment serum assays for testosterone, androstenedione, and dehydroepiandrosterone (DHEA) were performed with tandem liquid chromatography-mass spectrometry. RESULTS: Median values for testosterone, androstenedione, and DHEA were 1.00, 13.50, and 8.12 ng/dL, respectively. The median was used to define the midpoint between low and high values. In univariate analysis, median OS for low versus high levels was 21.4 and 24.2 months for testosterone, 23.8 and 21.9 months for androstenedione, and 20.2 and 25.2 months for DHEA (P = NS). In multivariable analysis of all androgens, baseline DHEA was prognostic of ≥ 50% PSA decline from baseline (P = .008). In multivariable analysis adjusting for 10 known prognostic values and prior ketoconazole use for metastatic CRPC, a 10-unit increase in baseline testosterone increased risk of death (hazard ratio, 1.11; 95% confidence interval, 1.01-1.23; P = .039), whereas a 10-unit increase in androstenedione lowered risk of death (hazard ratio, 0.92; 95% confidence interval, 0.88-0.97; P = .001). CONCLUSION: Consistent with prior studies, higher androstenedione levels in patients with metastatic CRPC treated with docetaxel are associated with improved survival. However pretreatment levels of other androgen levels are associated with varied effects on clinical outcome in chemotherapy-treated patients.