Exposure-Focused CBT Outperforms Relaxation-Based Control in an RCT of Treatment for Child and Adolescent Anxiety.

OBJECTIVE: The relative contribution of individual cognitive behavioral therapy (CBT) components to treatment outcomes for child anxiety disorders (CADs) is unclear. Recent meta-analyses suggest that exposure may be the primary active ingredient in CBT for CADs, and that relaxation may be relatively less effective. This brief report tests the hypothesis that exposure-focused CBT (EF-CBT) would outperform a relaxation-based active therapy control (Relaxation Mentorship Training; RMT) for the treatment of CADs. METHOD: Participants were 102 youth with CADs (mean age = 11.91, 26 males; 76.4% White, 14.7% Multiracial, 3.9% Black, 3.9% Asian, 0.9% other/do not wish to identify) as part of an ongoing neuroimaging randomized controlled trial. Participants were randomly assigned (ratio 2:1) to receive 12 sessions of EF-CBT (n = 70) or RMT (n = 32). Clinical improvement was measured at Week 12 (Clinical Global Impression - Improvement scale; CGI-I); treatment response was defined as receiving a rating of "very much" or "much improved" on the CGI-I. Anxiety severity was measured at Weeks 1, 6, 9, 12 (Pediatric Anxiety Rating Scale; PARS). Outcome measures were completed by an independent evaluator unaware of condition. RESULTS: EF-CBT exhibited 2.98 times higher odds of treatment completion than RMT; 13 treatment non-completers were included in analyses. Estimated treatment response rates were higher for EF-CBT (57.3%) than for RMT (19.2%). Longitudinal analyses indicated that EF-CBT was associated with faster and more pronounced anxiety reductions than RMT on the PARS (Hedges' g = .77). CONCLUSIONS: Results suggest that EF-CBT without relaxation is effective for CADs, and more effective than a relaxation-based intervention.

Deceased donors as nondirected donors in kidney paired donation.

As proof of concept, we simulate a revised kidney allocation system that includes deceased donor (DD) kidneys as chain-initiating kidneys (DD-CIK) in a kidney paired donation pool (KPDP), and estimate potential increases in number of transplants. We consider chains of length 2 in which the DD-CIK gives to a candidate in the KPDP, and that candidate's incompatible donor donates to theDD waitlist. In simulations, we vary initial pool size, arrival rates of candidate/donor pairs and (living) nondirected donors (NDDs), and delay time from entry to the KPDP until a candidate is eligible to receive a DD-CIK. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Kidney Donation, and the actual DDs from the Scientific Registry of Transplant Recipients (SRTR) data, simulations extend over 2 years. With an initial pool of 400, respective candidate and NDD arrival rates of 2 per day and 3 per month, and delay times for access to DD-CIK of 6 months or less, including DD-CIKs increases the number of transplants by at least 447 over 2 years, and greatly reduces waiting times of KPDP candidates. Potential effects on waitlist candidates are discussed as are policy and ethical issues.

The nine development bands: A conceptual framework and global theory for waste and development.

Solid waste management (SWM) is an essential utility service. More than two to three billion people worldwide still lack basic services, whereas some countries are already moving beyond SWM towards waste and resource management (WaRM) and a circular economy. This paper sets out a novel conceptual framework and global theory of waste and development, providing a road map, allowing a country or city to locate their current position and plot their way ahead. We identify nine development bands (9DBs) with significant commonalities in terms of critical challenges and developmental pressure points. DB1-DB4 reflect stepwise improvement towards the new baseline of meeting the SDG 11.6.1 indicators of universal collection and management in controlled facilities (DB5). Countries can then choose to move towards environmentally sound management and the 'reduce, reuse, recycle' (3Rs) (DB6-9), with an ultimate aspiration of 'zero waste'. We test the 9DBs conceptual framework against historical journeys of higher income countries. The main application will be in low- and middle-income countries striving towards SDG 11.6.1, where it fills a key gap in the practitioners' toolkit by enabling initial framing/scoping of the problem and smarter interventions to be designed and sense checked. Key insights include targeted governance/institutional reforms, appropriate and affordable systems/technology and adapting solutions to a diversity of local needs and realities.

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

Operator models for delivering municipal solid waste management services in developing countries. Part A: The evidence base.

This article presents the evidence base for 'operator models' - that is, how to deliver a sustainable service through the interaction of the 'client', 'revenue collector' and 'operator' functions - for municipal solid waste management in emerging and developing countries. The companion article addresses a selection of locally appropriate operator models. The evidence shows that no 'standard' operator model is effective in all developing countries and circumstances. Each city uses a mix of different operator models; 134 cases showed on average 2.5 models per city, each applying to different elements of municipal solid waste management - that is, street sweeping, primary collection, secondary collection, transfer, recycling, resource recovery and disposal or a combination. Operator models were analysed in detail for 28 case studies; the article summarises evidence across all elements and in more detail for waste collection. Operators fall into three main groups: The public sector, formal private sector, and micro-service providers including micro-, community-based and informal enterprises. Micro-service providers emerge as a common group; they are effective in expanding primary collection service coverage into poor- or peri-urban neighbourhoods and in delivering recycling. Both public and private sector operators can deliver effective services in the appropriate situation; what matters more is a strong client organisation responsible for municipal solid waste management within the municipality, with stable political and financial backing and capacity to manage service delivery. Revenue collection is also integral to operator models: Generally the municipality pays the operator from direct charges and/or indirect taxes, rather than the operator collecting fees directly from the service user.

Entorhinal volume, aerobic fitness, and recognition memory in healthy young adults: A voxel-based morphometry study.

Converging evidence supports the hypothesis effects of aerobic exercise and environmental enrichment are beneficial for cognition, in particular for hippocampus-supported learning and memory. Recent work in humans suggests that exercise training induces changes in hippocampal volume, but it is not known if aerobic exercise and fitness also impact the entorhinal cortex. In animal models, aerobic exercise increases expression of growth factors, including brain derived neurotrophic factor (BDNF). This exercise-enhanced expression of growth hormones may boost synaptic plasticity, and neuronal survival and differentiation, potentially supporting function and structure in brain areas including but not limited to the hippocampus. Here, using voxel based morphometry and a standard graded treadmill test to determine cardio-respiratory fitness (Bruce protocol; ·VO2 max), we examined if entorhinal and hippocampal volumes were associated with cardio-respiratory fitness in healthy young adults (N=33). In addition, we examined if volumes were modulated by recognition memory performance and by serum BDNF, a putative marker of synaptic plasticity. Our results show a positive association between volume in right entorhinal cortex and cardio-respiratory fitness. In addition, average gray matter volume in the entorhinal cortex, bilaterally, was positively associated with memory performance. These data extend prior work on the cerebral effects of aerobic exercise and fitness to the entorhinal cortex in healthy young adults thus providing compelling evidence for a relationship between aerobic fitness and structure of the medial temporal lobe memory system.

Structural differences in hippocampal and prefrontal gray matter volume support flexible context-dependent navigation ability.

Spatial navigation is a fundamental part of daily life. Humans differ in their individual abilities to flexibly navigate their world, and a critical question is how this variability relates to differences in underlying brain structure. Our experiment examined individual differences in the ability to flexibly navigate routes that overlap with, and must be distinguished from, previously learned trajectories. We related differences in flexible navigation performance to differences in brain morphology in healthy young adults using voxel-based morphometry. Our findings provide novel evidence that individual differences in gray matter volume in the hippocampus and dorsolateral prefrontal cortex correlate with our ability rapidly to learn and flexibly navigate routes through our world.

Socio-economic development drives solid waste management performance in cities: A global analysis using machine learning.

Mismanaged municipal solid waste (MSW), the major source of plastics pollution and a key contributor to climate forcing, in Global South cities poses public health and environmental problems. This study analyses the first consistent and quality assured dataset available for cities distributed worldwide, featuring a comprehensive set of solid waste management performance indicators (Wasteaware Cities Benchmark Indicators - WABI). Machine learning (multivariate random forest) and univariate non-linear regression are applied, identifying best-fit converging models for a broad range of explanatory socioeconomic variables. These proxies describe in a variety of ways generic levels of progress, such as Gross Domestic Product - Purchasing Power per capita, Social Progress Index (SPI) and Corruption Perceptions Index. Specifically, the research tests and quantitatively confirms a long-standing, yet unverified, hypothesis: that variability in cities' performance on MSW can be accounted for by socioeconomic development indices. The results provide a baseline for measuring progress as cities report MSW performance for the sustainable development goal SDG11.6.1 indicator: median rates of controlled recovery and disposal are approximately at 45 % for cities in low-income countries, 75 % in lower-middle, and 100 % for both upper-middle and high-income. Casting light on aspects beyond the SDG metric, on the quality of MSW-related services, show that improvements in service quality often lag improvements in service coverage. Overall, the findings suggest that progress in collection coverage, and controlled recovery and disposal has already taken place in low- and middle-income cities. However, if cities aspire to perform better on MSW management than would have been anticipated by the average socioeconomic development in their country, they should identify ways to overcome systemic underlying failures associated with that socioeconomic level. Most alarmingly, 'business as usual' development would substantially increase their waste generation per capita unless new policies are found to promote decoupling.

Bayesian Inference for Brain Activity from Functional Magnetic Resonance Imaging Collected at Two Spatial Resolutions.

Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application requires a high degree of spatial accuracy, but the fMRI signal-to-noise ratio (SNR) decreases as spatial resolution increases. In practice, fMRI scans can be collected at multiple spatial resolutions, and it is of interest to make more accurate inference on brain activity by combining data with different resolutions. To this end, we develop a new Bayesian model to leverage both better anatomical precision in high resolution fMRI and higher SNR in standard resolution fMRI. We assign a Gaussian process prior to the mean intensity function and develop an efficient, scalable posterior computation algorithm to integrate both sources of data. We draw posterior samples using an algorithm analogous to Riemann manifold Hamiltonian Monte Carlo in an expanded parameter space. We illustrate our method in analysis of presurgical fMRI data, and show in simulation that it infers the mean intensity more accurately than alternatives that use either the high or standard resolution fMRI data alone.

Hippocampal subfield and medial temporal cortical persistent activity during working memory reflects ongoing encoding.

Previous neuroimaging studies support a role for the medial temporal lobes in maintaining novel stimuli over brief working memory (WM) delays, and suggest delay period activity predicts subsequent memory. Additionally, slice recording studies have demonstrated neuronal persistent spiking in entorhinal cortex, perirhinal cortex (PrC), and hippocampus (CA1, CA3, subiculum). These data have led to computational models that suggest persistent spiking in parahippocampal regions could sustain neuronal representations of sensory information over many seconds. This mechanism may support both WM maintenance and encoding of information into long term episodic memory. The goal of the current study was to use high-resolution fMRI to elucidate the contributions of the MTL cortices and hippocampal subfields to WM maintenance as it relates to later episodic recognition memory. We scanned participants while they performed a delayed match to sample task with novel scene stimuli, and assessed their memory for these scenes post-scan. We hypothesized stimulus-driven activation that persists into the delay period-a putative correlate of persistent spiking-would predict later recognition memory. Our results suggest sample and delay period activation in the parahippocampal cortex (PHC), PrC, and subiculum (extending into DG/CA3 and CA1) was linearly related to increases in subsequent memory strength. These data extend previous neuroimaging studies that have constrained their analysis to either the sample or delay period by modeling these together as one continuous ongoing encoding process, and support computational frameworks that predict persistent activity underlies both WM and episodic encoding.

'Wasteaware' benchmark indicators for integrated sustainable waste management in cities.

This paper addresses a major problem in international solid waste management, which is twofold: a lack of data, and a lack of consistent data to allow comparison between cities. The paper presents an indicator set for integrated sustainable waste management (ISWM) in cities both North and South, to allow benchmarking of a city's performance, comparing cities and monitoring developments over time. It builds on pioneering work for UN-Habitat's solid waste management in the World's cities. The comprehensive analytical framework of a city's solid waste management system is divided into two overlapping 'triangles' - one comprising the three physical components, i.e. collection, recycling, and disposal, and the other comprising three governance aspects, i.e. inclusivity; financial sustainability; and sound institutions and proactive policies. The indicator set includes essential quantitative indicators as well as qualitative composite indicators. This updated and revised 'Wasteaware' set of ISWM benchmark indicators is the cumulative result of testing various prototypes in more than 50 cities around the world. This experience confirms the utility of indicators in allowing comprehensive performance measurement and comparison of both 'hard' physical components and 'soft' governance aspects; and in prioritising 'next steps' in developing a city's solid waste management system, by identifying both local strengths that can be built on and weak points to be addressed. The Wasteaware ISWM indicators are applicable to a broad range of cities with very different levels of income and solid waste management practices. Their wide application as a standard methodology will help to fill the historical data gap.

Interaction between serum BDNF and aerobic fitness predicts recognition memory in healthy young adults.

Convergent evidence from human and non-human animal studies suggests aerobic exercise and increased aerobic capacity may be beneficial for brain health and cognition. It is thought growth factors may mediate this putative relationship, particularly by augmenting plasticity mechanisms in the hippocampus, a brain region critical for learning and memory. Among these factors, glucocorticoids, brain derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), and vascular endothelial growth factor (VEGF), hormones that have considerable and diverse physiological importance, are thought to effect normal and exercise-induced hippocampal plasticity. Despite these predictions, relatively few published human studies have tested hypotheses that relate exercise and fitness to the hippocampus, and none have considered the potential links to all of these hormonal components. Here we present cross-sectional data from a study of recognition memory; serum BDNF, cortisol, IGF-1, and VEGF levels; and aerobic capacity in healthy young adults. We measured circulating levels of these hormones together with performance on a recognition memory task, and a standard graded treadmill test of aerobic fitness. Regression analyses demonstrated BDNF and aerobic fitness predict recognition memory in an interactive manner. In addition, IGF-1 was positively associated with aerobic fitness, but not with recognition memory. Our results may suggest an exercise adaptation-related change in the BDNF dose-response curve that relates to hippocampal memory.

8-Chloroadenine: a novel product formed from hypochlorous acid-induced damage to calf thymus DNA.

Hypochlorous acid (HOCl) is formed by the action of the enzyme myeloperoxidase on hydrogen peroxide and chloride ions. It has been shown to be highly bactericidal and cytotoxic by a variety of mechanisms, one of which, may be the modification of DNA. Previously we have demonstrated by GC-MS analysis that exposure of calf thymus DNA to HOCl causes extensive pyrimidine modification, including 5-chlorocytosine formation. Using GC-MS analysis, we now demonstrate the formation of an additional chlorinated base product, 8-Cl adenine. The addition of 50 µM HOCl was sufficient to produce a significant increase in this product. The reaction of HOCl with adenine in calf thymus DNA was shown to be rapid with the reaction complete after 1 min. pH-dependence studies suggest HOCl rather than its conjugate base (OCl-) to be responsible for 8-Cl adenine formation. Other commercially available chlorinated base products, 6-Cl guanine or 2-Cl adenine were not detected. Therefore, 8-Cl adenine might prove a useful biomarker for studying the role of reactive chlorine species (RCS) during inflammatory processes.