Human scotopic dark adaptation: Comparison of recoveries of psychophysical threshold and ERG b-wave sensitivity

We have compared the time course of dark adaptation of the human scotopic visual system, measured psychophysically and from the b-wave of the electroretinogram (ERG), for bleaches ranging from a few percent to near total. We also measured light adaptation, in order to apply a "Crawford transformation" to convert the raw measurements of dark adaptation into equivalent background intensities. For both the "psychophysical threshold equivalent" intensity and the "ERG b-wave sensitivity equivalent" intensity, the equivalent background declined over much of its range with an "S2" component, though with somewhat different slopes of -0.36 (psychophysical) and -0.22 (ERG) log10 unit min-1, respectively. In addition, the magnitude of the equivalent background was approximately 1 log10 unit lower in the psychophysical experiments than in the ERG experiments. Despite these differences, the two approaches extract a common time course for the decline in level of free opsin following moderately large bleaches. We conclude that the recovery of psychophysical scotopic visual threshold over the S2 region reflects events that are present by the stage of the first synapse of rod vision, stemming ultimately from the presence of unregenerated opsin in the rod outer segments

The Impact of a Counseling Techniques Course on Self-efficacy and Stigma

Abstract: Authors analyzed data from counseling trainees in a skills course to examine self-efficacy and stigma. It was hypothesized that self-efficacy would increase, self-stigma would decrease, and that increased self-efficacy would decrease self-stigma in CTs. Increased self-efficacy was statistically significant, but self-efficacy changes did not predict decreased self-stigma. Increased self-efficacy was predictive of self-stigma related to help-seeking. Authors offer implications for counselor educators and counselors. What is the public significance of this article? This study suggests that self-efficacy increases in counseling trainees across a clinical skills course, and that this self-efficacy also predicts the stigma trainees felt about seeking help for a mental health concern. Although it was expected that a skills course would help increase self-efficacy, the study suggests that increased self-efficacy does not relate to the stigma that trainees feel about mental health treatment

Infant-mother attachment and the growth of externalizing problems across the primary-school years

Background:  Some contend that attachment insecurity increases risk for the development of externalizing behavior problems in children. Method:  Latent-growth curve analyses were applied to data on 1,364 children from the NICHD Study of Early Child Care to evaluate the association between early attachment and teacher-rated externalizing problems across the primary-school years. Results:  Findings indicate that (a) both avoidant and disorganized attachment predict higher levels of externalizing problems but (b) that effects of disorganized attachment are moderated by family cumulative contextual risk, child gender and child age, with disorganized boys from risky social contexts manifesting increases in behavior problems over time. Conclusions:  These findings highlight the potentially conditional role of early attachment in children’s externalizing behavior problems and the need for further research evaluating causation and mediating mechanisms

A combination intervention strategy to improve linkage to and retention in HIV care following diagnosis in Mozambique: A cluster-randomized study

Background: Concerning gaps in the HIV care continuum compromise individual and population health. We evaluated a combination intervention strategy (CIS) targeting prevalent barriers to timely linkage and sustained retention in HIV care in Mozambique. Methods and findings: In this cluster-randomized trial, 10 primary health facilities in the city of Maputo and Inhambane Province were randomly assigned to provide the CIS or the standard of care (SOC). The CIS included point-of-care CD4 testing at the time of diagnosis, accelerated ART initiation, and short message service (SMS) health messages and appointment reminders. A pre–post intervention 2-sample design was nested within the CIS arm to assess the effectiveness of CIS+, an enhanced version of the CIS that additionally included conditional non-cash financial incentives for linkage and retention. The primary outcome was a combined outcome of linkage to care within 1 month and retention at 12 months after diagnosis. From April 22, 2013, to June 30, 2015, we enrolled 2,004 out of 5,327 adults ≥18 years of age diagnosed with HIV in the voluntary counseling and testing clinics of participating health facilities: 744 (37%) in the CIS group, 493 (25%) in the CIS+ group, and 767 (38%) in the SOC group. Fifty-seven percent of the CIS group achieved the primary outcome versus 35% in the SOC group (relative risk [RR]CIS vs SOC = 1.58, 95% CI 1.05–2.39). Eighty-nine percent of the CIS group linked to care on the day of diagnosis versus 16% of the SOC group (RRCIS vs SOC = 9.13, 95% CI 1.65–50.40). There was no significant benefit of adding financial incentives to the CIS in terms of the combined outcome (55% of the CIS+ group achieved the primary outcome, RRCIS+ vs CIS = 0.96, 95% CI 0.81–1.16). Key limitations include the use of existing medical records to assess outcomes, the inability to isolate the effect of each component of the CIS, non-concurrent enrollment of the CIS+ group, and exclusion of many patients newly diagnosed with HIV. Conclusions: The CIS showed promise for making much needed gains in the HIV care continuum in our study, particularly in the critical first step of timely linkage to care following diagnosis

Modeling spatiotemporal abundance of mobile wildlife in highly variable environments using boosted GAMLSS hurdle models

Modeling organism distributions from survey data involves numerous statistical challenges, including accounting for zero‐inflation, overdispersion, and selection and incorporation of environmental covariates. In environments with high spatial and temporal variability, addressing these challenges often requires numerous assumptions regarding organism distributions and their relationships to biophysical features. These assumptions may limit the resolution or accuracy of predictions resulting from survey‐based distribution models. We propose an iterative modeling approach that incorporates a negative binomial hurdle, followed by modeling of the relationship of organism distribution and abundance to environmental covariates using generalized additive models (GAM) and generalized additive models for location, scale, and shape (GAMLSS). Our approach accounts for key features of survey data by separating binary (presence‐absence) from count (abundance) data, separately modeling the mean and dispersion of count data, and incorporating selection of appropriate covariates and response functions from a suite of potential covariates while avoiding overfitting. We apply our modeling approach to surveys of sea duck abundance and distribution in Nantucket Sound (Massachusetts, USA), which has been proposed as a location for offshore wind energy development. Our model results highlight the importance of spatiotemporal variation in this system, as well as identifying key habitat features including distance to shore, sediment grain size, and seafloor topographic variation. Our work provides a powerful, flexible, and highly repeatable modeling framework with minimal assumptions that can be broadly applied to the modeling of survey data with high spatiotemporal variability. Applying GAMLSS models to the count portion of survey data allows us to incorporate potential overdispersion, which can dramatically affect model results in highly dynamic systems. Our approach is particularly relevant to systems in which little a priori knowledge is available regarding relationships between organism distributions and biophysical features, since it incorporates simultaneous selection of covariates and their functional relationships with organism responses

The Sparsest Clusters With O Stars

There is much debate on how high-mass star formation varies with environment, and whether the sparsest star-forming environments are capable of forming massive stars. To address this issue, we have observed eight apparently isolated OB stars in the SMC using HST's Advanced Camera for Surveys. Five of these objects appear as isolated stars, two of which are confirmed to be runaways. The remaining three objects are found to exist in sparse clusters, with <10 companion stars revealed, having masses of 1-4 solar mass. Stochastic effects dominate in these sparse clusters, so we perform Monte Carlo simulations to explore how our observations fit within the framework of empirical, galactic cluster properties. We generate clusters using a simplistic -2 power-law distribution for either the number of stars per cluster (N_*) or cluster mass (M_cl). These clusters are then populated with stars randomly chosen from a Kroupa IMF. We find that simulations with cluster lower-mass limits of M_cl,lo >20 solar mass and N_*,lo >40 match best with observations of SMC and Galactic OB star populations. We examine the mass ratio of the second-most massive and most massive stars (m_max,2/m_max), finding that our observations all exist below the 20th percentile of our simulated clusters. However, all of our observed clusters lie within the parameter space spanned by the simulated clusters, although some are in the lowest 5th percentile frequency. These results suggest that clusters are built stochastically by randomly sampling stars from a universal IMF with a fixed stellar upper-mass limit. In particular, we see no evidence to suggest a m_max - M_cl relation. Our results may be more consistent with core accretion models of star formation than with competitive accretion models, and they are inconsistent with the proposed steepening of the integrated galaxy IMF (IGIMF).Comment: 19 pages, 12 figures, accepted for publication in Ap

Massive, wide binaries as tracers of massive star formation

Massive stars can be found in wide (hundreds to thousands AU) binaries with other massive stars. We use N-body simulations to show that any bound cluster should always have approximately one massive wide binary: one will probably form if none are present initially; and probably only one will survive if more than one are present initially. Therefore any region that contains many massive wide binaries must have been composed of many individual subregions. Observations of Cyg OB2 show that the massive wide binary fraction is at least a half (38/74) which suggests that Cyg OB2 had at least 30 distinct massive star formation sites. This is further evidence that Cyg OB2 has always been a large, low-density association. That Cyg OB2 has a normal high-mass IMF for its total mass suggests that however massive stars form they 'randomly sample' the IMF (as the massive stars did not 'know' about each other)

Capturing the Data: Nutrition Risk Screening of Adults in Hospital

This study aims to explore limitations with the Malnutrition Screening Tool in identifyingmalnutrition risk, in a cohort of 3,033 adult Australian medical and surgical hospital inpatients. Seventy-two percent of patients were screened; illness and medical care limited access to others. Malnutrition risk (16.5%; n = 501) was found in all age groups with a trend to higher risk in medical wards; 10% (n = 300) of patients with communication barriers were excluded. Systematic screening increased dietitians’ referrals by 39%. Further research is required to enable screening of all patients, including those with communication issues with an easy to use valid tool

Deciphering coral disease dynamics: integrating host, microbiome, and the changing environment

Diseases of tropical reef organisms is an intensive area of study, but despite significant advances in methodology and the global knowledge base, identifying the proximate causes of disease outbreaks remains difficult. The dynamics of infectious wildlife diseases are known to be influenced by shifting interactions among the host, pathogen, and other members of the microbiome, and a collective body of work clearly demonstrates that this is also the case for the main foundation species on reefs, corals. Yet, among wildlife, outbreaks of coral diseases stand out as being driven largely by a changing environment. These outbreaks contributed not only to significant losses of coral species but also to whole ecosystem regime shifts. Here we suggest that to better decipher the disease dynamics of corals, we must integrate more holistic and modern paradigms that consider multiple and variable interactions among the three major players in epizootics: the host, its associated microbiome, and the environment. In this perspective, we discuss how expanding the pathogen component of the classic host-pathogen-environment disease triad to incorporate shifts in the microbiome leading to dysbiosis provides a better model for understanding coral disease dynamics. We outline and discuss issues arising when evaluating each component of this trio and make suggestions for bridging gaps between them. We further suggest that to best tackle these challenges, researchers must adjust standard paradigms, like the classic one pathogen-one disease model, that, to date, have been ineffectual at uncovering many of the emergent properties of coral reef disease dynamics. Lastly, we make recommendations for ways forward in the fields of marine disease ecology and the future of coral reef conservation and restoration given these observations