Earthquake forecasting from paleoseismic records.

Forecasting large earthquakes along active faults is of critical importance for seismic hazard assessment. Statistical models of recurrence intervals based on compilations of paleoseismic data provide a forecasting tool. Here we compare five models and use Bayesian model-averaging to produce time-dependent, probabilistic forecasts of large earthquakes along 93 fault segments worldwide. This approach allows better use of the measurement errors associated with paleoseismic records and accounts for the uncertainty around model choice. Our results indicate that although the majority of fault segments (65/93) in the catalogue favour a single best model, 28 benefit from a model-averaging approach. We provide earthquake rupture probabilities for the next 50 years and forecast the occurrence times of the next rupture for all the fault segments. Our findings suggest that there is no universal model for large earthquake recurrence, and an ensemble forecasting approach is desirable when dealing with paleoseismic records with few data points and large measurement errors.

Dual-Lifetime Referencing (t-DLR) Optical Fiber Fluorescent pH Sensor for Microenvironments.

The pH behavior in the µm to cm thick diffusion boundary layer (DBL) surrounding many aquatic species is dependent on light-controlled metabolic activities. This DBL microenvironment exhibits different pH behavior to bulk seawater, which can reduce the exposure of calcifying species to ocean acidification conditions. A low-cost time-domain dual-lifetime referencing (t-DLR) interrogation system and an optical fiber fluorescent pH sensor were developed for pH measurements in the DBL interface. The pH sensor utilized dual-layer sol-gel coatings of pH-sensitive iminocoumarin and pH-insensitive Ru(dpp)3-PAN. The sensor has a dynamic range of 7.41 (±0.20) to 9.42 ± 0.23 pH units (95% CI, T = 20 °C, S = 35), a response time (t90) of 29 to 100 s, and minimal salinity dependency. The pH sensor has a precision of approximately 0.02 pHT units, which meets the Global Ocean Acidification Observing Network (GOA-ON) "weather" measurement quality guideline. The suitability of the t-DLR optical fiber pH sensor was demonstrated through real-time measurements in the DBL of green seaweed Ulva sp. This research highlights the practicability of optical fiber pH sensors by demonstrating real-time pH measurements of metabolic-induced pH changes.

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders.

BACKGROUND: The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time. METHODS: We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms - Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale - Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis. DISCUSSION: This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures. TRIAL REGISTRATION: Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.

Proteolytic activation of anti-Müllerian hormone is suppressed in adolescent girls.

PURPOSE: The ratio of the anti-Müllerian hormone (AMH) precursor (proAMH) to active AMH (AMHN,C) is higher in childhood than in adulthood but has never been quantified during adolescence. The ratio of proAMH to total AMH (AMH prohormone index, API) was examined during the puberty in healthy girls. The API was also compared between girls with and without polycystic ovary syndrome (PCOS) to determine if there were differences that could assist in PCOS diagnosis during adolescence. METHODS: Total AMH and proAMH were measured by immunoassay in a single-centre, cross-sectional observational study; 61 controls and 29 girls with PCOS were included in the study (age range 8-21 years). The API was calculated as proAMH as a percentage of total AMH. Differences in API between control and PCOS subjects and across age-groups were examined by Welch's ANOVA. The relationship between API and a range of metabolic parameters was examined by Pearson correlation. RESULTS: The API in healthy females increased between the ages of 10~15 years and declined from 15~20 years (p < 0.001). The API was negatively correlated with body mass index in the control (p = 0.04) and PCOS groups (p = 0.007). The API was associated with factors related to adiposity and lipid metabolism. The API was not significantly different in control girls and girls with PCOS. CONCLUSIONS: Higher API during adolescence suggests that proteolytic activation of proAMH is suppressed during this life stage. API was not different between control girls and girls with PCOS indicating that it is not useful in diagnosis of PCOS during adolescence.

Concurrent measurement of nitrate and ammonium in water and soil samples using ion-selective electrodes: Tackling sensitivity and precision issues.

In this paper, we demonstrate the suitability, sensitivity, and precision of low-cost and easy-to-use ion-selective electrodes (ISEs) for concurrent detection of NH4 + and NO3 - in soil and water by technical and non-technical end-users to enable efficient soil and water management exposed to chronic reactive nitrogen loading. We developed a simplified methodology for sample preparation followed by the demonstration of an analytical methodology resulting in improvements of sensitivity and precision of ISEs. Herein, we compared and contrasted ISEs with traditional laboratory-based technique such as Flow Injection Analysis (FIA) and portable colorimetric assay followed by comparisons of linear regression and Bayesian nonlinear calibration approaches applied on both direct potentiometry and standard addition modes of analysis in terms of in-field applications and improvement of sensitivity and precision. The ISEs were validated for sensing on a range of ambient soil and water samples representing a range of NH4 + and NO3 - concentrations from pristine to excessive saturation conditions. Herein developed methodology showed excellent agreement with lab-based and portable analytical techniques while demonstrating improvements in precision and sensitivity analysis illustrated by a decrease in confidence intervals by 50-60%. We also demonstrated the utilization of the entire ISE response curve thus removing the biases originating from linear approximation which is often currently employed. Therefore, we show that ISEs are robust yet low cost and an easy to use technology that can enable high-frequency measurement of mineral N and help to improve our understanding of N transformation processes as influenced by soil management, fertilization, land use, and climate change.

Separating the effects of climate, bycatch, predation and harvesting on titi (Ardenna grisea) population dynamics in New Zealand: A model-based assessment.

A suite of factors may have contributed to declines in the titi (sooty shearwater; Ardenna grisea) population in the New Zealand region since at least the 1960s. Recent estimation of the magnitude of most sources of non-natural mortality has presented the opportunity to quantitatively assess the relative importance of these factors. We fit a range of population dynamics models to a time-series of relative abundance data from 1976 until 2005, with the various sources of mortality being modelled at the appropriate part of the life-cycle. We present estimates of effects obtained from the best-fitting model and using model averaging. The best-fitting models explained much of the variation in the abundance index when survival and fecundity were linked to the Southern Oscillation Index, with strong decreases in adult survival, juvenile survival and fecundity being related to El Niño-Southern Oscillation (ENSO) events. Predation by introduced animals, harvesting by humans, and bycatch in fisheries also appear to have contributed to the population decline. It is envisioned that the best-fitting models will form the basis for quantitative assessments of competing management strategies. Our analysis suggests that sustainability of the New Zealand titi population will be most influenced by climate, in particular by how climate change will affect the frequency and intensity of ENSO events in the future. Removal of the effects of both depredation by introduced predators and harvesting by humans is likely to have fewer benefits for the population than alleviating climate effects.

Establishing Meaningful Limits of Detection for Ion-Selective Electrodes and Other Nonlinear Sensors.

Although IUPAC has recommended a probabilistic approach to determining limit of detection (LOD) based on false-positive and false-negative rates for more than 20 years, the LOD definition for ion-selective electrodes (ISEs) long predates these recommendations and conflicts substantively with them. Although it is well known that the ISE LOD definition does not follow best practice, it continues to be used due to simplicity and a lack of available methods for estimating LOD for nonlinear sensors. Here, we use ISEs as a model system for estimation of LOD for nonlinear sensors that is consistent with broad IUPAC recommendations and justified using statistical theory. Using freely available software, the new approach and updated definition is demonstrated through theory, simulation, and an environmental application. The results show that the current LOD definition for ISEs performs substantially worse than the proposed definition when assessed against IUPAC recommendations, including ignoring sensor noise and LOD uncertainty, leading to bias of an order of magnitude or more. Further, the environmental application shows that the new definition, which includes estimates of LOD uncertainty, allows more objective assessment of sensor response and fitness for purpose. The growing demand for ultrasensitive sensors that operate in complex matrices has pushed the boundaries of traditional calibration approaches. These sensors often operate near their limit of detection (LOD), with additional challenges created if their response is nonlinear. These challenges are amplified when assessing new sensors, since they may be less reproducible and noisier than benchmark techniques.

Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools.

A new software package, ISEtools, is introduced for use within the popular open-source programming language R that allows Bayesian statistical data analysis techniques to be implemented in a straightforward manner. Incorporating all collected data simultaneously, this Bayesian approach naturally accommodates sensor arrays and provides improved limit of detection estimates, including providing appropriate uncertainty estimates. Utilising >1500 lines of code, ISEtools provides a set of three core functions-loadISEdata, describeISE, and analyseISE- for analysing ion-selective electrode data using the Nikolskii-Eisenman equation. The functions call, fit, and extract results from Bayesian models, automatically determining data structures, applying appropriate models, and returning results in an easily interpretable manner and with publication-ready figures. Importantly, while advanced statistical and computationally intensive methods are employed, the functions are designed to be accessible to non-specialists. Here we describe basic features of the package, demonstrated through a worked environmental application.

Studentized bootstrap model-averaged tail area intervals.

In many scientific studies, the underlying data-generating process is unknown and multiple statistical models are considered to describe it. For example, in a factorial experiment we might consider models involving just main effects, as well as those that include interactions. Model-averaging is a commonly-used statistical technique to allow for model uncertainty in parameter estimation. In the frequentist setting, the model-averaged estimate of a parameter is a weighted mean of the estimates from the individual models, with the weights typically being based on an information criterion, cross-validation, or bootstrapping. One approach to building a model-averaged confidence interval is to use a Wald interval, based on the model-averaged estimate and its standard error. This has been the default method in many application areas, particularly those in the life sciences. The MA-Wald interval, however, assumes that the studentized model-averaged estimate has a normal distribution, which can be far from true in practice due to the random, data-driven model weights. Recently, the model-averaged tail area Wald interval (MATA-Wald) has been proposed as an alternative to the MA-Wald interval, which only assumes that the studentized estimate from each model has a N(0, 1) or t-distribution, when that model is true. This alternative to the MA-Wald interval has been shown to have better coverage in simulation studies. However, when we have a response variable that is skewed, even these relaxed assumptions may not be valid, and use of these intervals might therefore result in poor coverage. We propose a new interval (MATA-SBoot) which uses a parametric bootstrap approach to estimate the distribution of the studentized estimate for each model, when that model is true. This method only requires that the studentized estimate from each model is approximately pivotal, an assumption that will often be true in practice, even for skewed data. We illustrate use of this new interval in the analysis of a three-factor marine global change experiment in which the response variable is assumed to have a lognormal distribution. We also perform a simulation study, based on the example, to compare the lower and upper error rates of this interval with those for existing methods. The results suggest that the MATA-SBoot interval can provide better error rates than existing intervals when we have skewed data, particularly for the upper error rate when the sample size is small.

The effects of external cues on individual and collective behavior of shoaling fish.

Collective animal behavior is an emergent phenomenon arising from the local interactions of the members of animal groups. Considerable progress has been made in characterizing these interactions, particularly inferring rules that shape and guide the responses of animals to their near neighbors. To date, experimental work has focused on collective behavior within a single, stable context. We examine the individual and collective behavior of a schooling fish species, the x-ray tetra (Pristella maxillaris), identifying their response to changes in context produced by food cues or conspecific alarm cues. Fish exposed to alarm cues show pronounced, broad-ranging changes of behavior, including reducing speed and predictability in their movements. Alarmed fish also alter their responses to other group members, including enacting a smaller zone of repulsion and increasing their frequency of observation of, and responsiveness to, near neighbors. Fish subject to food cues increased speed as a function of neighbor positions and reduced encounter frequency with near neighbors. Overall, changes in individual behavior and the interactions among individuals in response to external cues coincide with changes in group-level patterns, providing insight into the adaptability of behavior to changes in context and interrelationship between local interactions and global patterns in collective behavior.

Improved estimation of intrinsic growth r(max) for long-lived species: integrating matrix models and allometry.

Intrinsic population growth rate (r(max)) is an important parameter for many ecological applications, such as population risk assessment and harvest management. However, r(max) can be a difficult parameter to estimate, particularly for long-lived species, for which appropriate life table data or abundance time series are typically not obtainable. We describe a method for improving estimates of r(max) for long-lived species by integrating life-history theory (allometric models) and population-specific demographic data (life table models). Broad allometric relationships, such as those between life history traits and body size, have long been recognized by ecologists. These relationships are useful for deriving theoretical expectations for r(max), but r(max) for real populations may vary from simple allometric estimators for "archetypical" species of a given taxa or body mass. Meanwhile, life table approaches can provide population-specific estimates of r(max) from empirical data, but these may have poor precision from imprecise and missing vital rate parameter estimates. Our method borrows strength from both approaches to provide estimates that are consistent with both life-history theory and population-specific empirical data, and are likely to be more robust than estimates provided by either method alone. Our method uses an' allometric constant: the product of r(max) and the associated generation time for a stable-age population growing at this rate. We conducted a meta-analysis to estimate the mean and variance of this allometric constant across well-studied populations from three vertebrate taxa (birds, mammals, and elasmobranchs) and found that the mean was approximately 1.0 for each taxon. We used these as informative Bayesian priors that determine how much to "shrink" imprecise vital rate estimates for a data-limited population toward the allometric expectation. The approach ultimately provides estimates of r(max) (and other vital rates) that reflect a balance of information from the individual studied population, theoretical expectation, and meta-analysis of other populations. We applied the method specifically to an archetypical petrel (representing the genus Procellaria) and to white sharks (Carcharodon carcharias) in the context of estimating sustainable-fishery bycatch limits.

An update on the interaction between the serotonin transporter promoter variant (5-HTTLPR), stress and depression, plus an exploration of non-confirming findings.

In the three years since the most recent meta-analysis of the association between the serotonin transported promoter polymorphism (5-HTTLPR), stress and the development of depression, another 27 studies have been published on this issue, which is an increase of 50% more studies than were previously reviewed. In addition, previous findings of inconsistency of results across studies argued for further exploration of this relationship. From the 81 studies identified to June 2013, the significant relationship between the short form of the 5-HTTLPR was confirmed (p=.0000009), which is stronger than the relationship reported in the most recent meta-analysis in 2011. However, nearly 26% of the 81 studies reviewed failed to show any significant association between the 5-HTTLPR, stress and depression, and four studies found opposite results to those expected. Examination of the methodologies of all studies failed to indicate any flaws in the opposite or unequivocal studies, and the latter had larger sample sizes than those studies which supported the expected association, arguing that the null results were not an outcome of insufficient statistical power. The need to consider aspects of samples and measures of depression, particularly the presence of subtypes of depression in future research is discussed.

Using trace elements in particulate matter to identify the sources of semivolatile organic contaminants in air at an alpine site.

An approach using trace elements in particulate matter (PM) to identify the geographic sources of atmospherically transported semivolatile organic contaminants (SOCs) was investigated. Daily samples of PM and SOCs were collected with high-volume air samplers from 16 January to 16 February 2009 at Temple Basin, a remote alpine site in New Zealand's Southern Alps. The most commonly detected pesticides were dieldrin, trans-chlordane, endosulfan I, and chlorpyrifos. Polycyclic aromatic hydrocarbons and polychlorinated biphenyls were also detected. For each sampling day, the relative contribution of PM from regional New Zealand versus long-range Australian sources was determined using trace element profiles and a binary mixing model. The PM approach indicated that endosulfan I, indeno[1,2,3-c,d]pyrene, and benzo[g,h,i]perylene found at Temple Basin were largely of Australian origin. Local wind observations indicated that the chlorpyrifos found at Temple Basin primarily came from the Canterbury Plains in New Zealand.

A single-item measure of health-related quality-of-life for HIV-infected patients in routine clinical care.

Measurement of health-related quality-of-life (HRQL) captures dimensions of health not otherwise assessed. However, HRQL measurement is time-consuming and difficult to incorporate into a routine clinical care setting. The purpose of this study was to assess the construct validity, discriminative ability, and feasibility of administering a single-item health status measure (EVGGFP) of HRQL rating health as excellent, very good, good, fair, or poor among HIV-infected patients in routine clinical care. Patients attending an urban HIV specialty clinic completed a survey assessing their current symptom burden, HRQL as measured by EVGGFP and by a 7-domain, 21-item HRQL instrument (HRQL-21), and sociodemographic factors (n = 269). Patients were predominantly men (91%), 27% reported a history of intravenous drug use, and over half had some college education. We used multiple regression analysis to examine the association between HRQL assessed by EVGGFP and the HRQL-21. We compared the discriminative ability of EVGGFP and the HRQL-21 to detect differences in CD4 cell count, plasma HIV-1 RNA level, and symptom burden. We found that HRQL scores determined by EVGGFP were significantly associated with domain scores from the HRQL-21 (adjusted R2 0.42-0.69). The discriminative ability of EVGGFP was equivalent to that of the HRQL-21. EVGGFP had high sensitivity and low to moderate specificity in identifying patients with poor overall HRQL who might benefit from more comprehensive evaluation of multiple HRQL domains. EVGGFP can be used to assess health status among HIV-infected patients in routine clinical care and may be useful in settings in which comprehensive HRQL assessment is not practical.

Pharmacy-based assessment of adherence to HAART predicts virologic and immunologic treatment response and clinical progression to AIDS and death.

Although adherence to HAART at a level above 95% has been associated with optimal viral suppression, the impact of different levels of adherence on long-term clinical outcomes has not been determined. We used an objective pharmacy-based measure to examine the association between three levels of adherence to HAART and disease progression among a population-based cohort of HIV-infected patients attending an urban HIV specialty clinic. Higher levels of adherence to HAART were significantly associated with longer time to virologic failure (P < 0.001), greater increase in CD4 cell count (P = 0.04), and lower risk of progression to clinical AIDS or death (P < 0.007). After controlling for other factors, patients with low adherence had over five times the risk of disease progression than patients with moderate adherence (P = 0.007) or patients with high adherence (P = 0.001). There was no significant difference in the risk of progression between patients with moderate and high levels of adherence (P > 0.2). Patients who progressed to AIDS or death had significantly higher viral loads (P = 0.01) and lower CD4 cell counts (P = 0.03) than patients who experienced virologic failure, but did not progress.

A Bayesian approach to aid in formulary decision making: incorporating institution-specific cost-effectiveness data with clinical trial results.

Pharmacy and therapeutics committees commonly cite a lack of generalizability as a reason for not incorporating cost-effectiveness information into decision making. To address this concern, many committees undertake site-specific economic evaluations, which are often limited by small sample sizes and nonrandomized designs. We show how 2 complementary approaches were used to minimize these limitations in an economic evaluation of abciximab at 1 institution. Using a propensity score methodology, we selected patients who did not receive abciximab for the comparison cohort. Then, we adopted a Bayesian, hierarchical, random-effects model to integrate site-specific and clinical trial data. We applied the posterior distributions of effectiveness with local cost data in a traditional decision-analytic model. In 74% of the simulations, abciximab was cost-effective at 1 institution at the $50,000 per life year saved threshold, assuming a 50:50 split of patients undergoing coronary stenting and angioplasty. Among patients undergoing coronary stenting, the cost-effectiveness ratio of the addition of abciximab was at or below the $50,000 per life year saved threshold in 66.0% of the simulations.

Electronic human immunodeficiency virus (HIV) clinical reminder system improves adherence to practice guidelines among the University of Washington HIV Study Cohort.

We conducted a prospective study of an electronic clinical reminder system in an academic medical center-based human immunodeficiency virus (HIV) specialty clinic. Published performance indicators were used to examine adherence to HIV practice guidelines before and after its implementation for 1204 patients. More than 90% of patients received CD4 cell count and HIV type 1 (HIV-1) RNA level monitoring every 3-6 months during both time periods, and approximately 80% of patients with a CD4 cell count nadir of <350 cells/mm(3) received highly active antiretroviral therapy. Patients were significantly more likely to receive prophylaxis against Mycobacterium avium complex (hazard ratio, 3.84; 95% confidence interval [CI], 1.58-9.31; P=.003), to undergo annual cervical carcinoma screening (OR, 2.09; 95% CI, 1.04-4.16; P=.04), and to undergo serological screening for Toxoplasma gondii (odds ratio [OR], 1.86; 95% CI, 1.05-3.27; P=.03) and syphilis infection (OR, 3.71; 95% CI, 2.37-5.81; P<.0001). HIV clinical reminders delivered at the time that HIV care is provided were associated with more timely initiation of recommended practices.

Primary care delivery is associated with greater physician experience and improved survival among persons with AIDS.

OBJECTIVE: It has been shown that greater physician experience in the care of persons with AIDS prolongs survival, but how more experienced primary care physicians achieve better outcomes is not known. DESIGN/SETTING/PATIENTS: Retrospective cohort study of HIV-infected patients enrolled in a large staff-model health maintenance organization from 1990 through 1999. MEASUREMENTS: Adjusted odds of medical service delivery and adjusted hazard ratio of death by physician experience level (least, moderate, most) and service utilization. MAIN RESULTS: Primary care delivery by physicians with greater AIDS experience was associated with improved survival. After controlling for disease severity, patients cared for by the most experienced physicians were twice as likely to receive a primary care visit in a given month compared with patients of the least and moderately experienced physicians (P <.01). Patients of the least experienced physicians received the lowest level of outpatient pharmacy and laboratory services (P <.001) and were half as likely to have a specialty care visit compared with patients of the most and moderately experienced physicians (P <.05). Patients who received infrequent primary care visits by the least experienced physicians were 15.3 times more likely to die than patients of the most experienced physicians (P =.02). There was a significant increase in primary care services delivered to the population of HIV-infected patients receiving care in 1999, when highly active antiretroviral therapy (HAART) was in general use, compared with the time period prior to the introduction of HAART. CONCLUSIONS: Primary care delivery by physicians with greater HIV experience contributes to improved patient outcomes.