What are the determinants of health care expenditure? Empirical results from Asian countries

This paper uses panel data to identify the determinants of health care expenditure in twelve Asian countries (i.e. Cambodia, China, Indonesia, Japan, Laos, Malaysia, Mongolia, the Philippines, South Korea, Singapore, Thailand and Vietnam) for the period of 1995-2008. The empirical results indicated that only two independent variables (GDPit and POP65it) have significant relationship with health care expenditure in these countries. These two variables are positively correlated with the amount of health care expenditure. In other words, when the countries’ income is larger, the amount of health care expenditure is larger. When the share of ageing population in the total population is higher, again the amount of health care expenditure is larger

Stubborn Predictions in Primary Visual Cortex

Perceivers can use past experiences to make sense of ambiguous sensory signals. However, this may be inappropriate when the world changes and past experiences no longer predict what the future holds. Optimal learning models propose that observers decide whether to stick with or update their predictions by tracking the uncertainty or "precision" of their expectations. However, contrasting theories of prediction have argued that we are prone to misestimate uncertainty-leading to stubborn predictions that are difficult to dislodge. To compare these possibilities, we had participants learn novel perceptual predictions before using fMRI to record visual brain activity when predictive contingencies were disrupted-meaning that previously "expected" events become objectively improbable. Multivariate pattern analyses revealed that expected events continued to be decoded with greater fidelity from primary visual cortex, despite marked changes in the statistical structure of the environment, which rendered these expectations no longer valid. These results suggest that our perceptual systems do indeed form stubborn predictions even from short periods of learning-and more generally suggest that top-down expectations have the potential to help or hinder perceptual inference in bounded minds like ours

Fungal and bacterial species in degrading carbamazepine: a metabolite perspective: Mini-review

Carbamazepine (CBZ) is a ubiquitous pharmaceutical pollutant found in various water environments. This is due to the ineffective CBZ removal, despite employing advanced physiochemical treatment technologies in the current conventional wastewater treatment plants. Thus, bioremediation that utilizes enzymes in microorganisms' systems to bio-mineralize CBZ is suggested as an alternative or complementary technique to remove CBZ more effectively. However, information from published research on the biodegradation of CBZ, the toxicity of metabolites, or toxicity testing was rarely evaluated or assessed cohesively. This aspect is important because if bioremediation of CBZ produces toxic metabolites, it will defeat the main purpose of bioremediation. Thus, the focus of this review is to assess the effectiveness of fungi and bacteria in the biodegradation of CBZ, particularly by looking at the type of enzymes expressed, and the metabolites produced. In this review, information related to the fungal and bacterial species that were reported to degrade CBZ was collated from the published literature and analyzed. Results of the analysis showed that cytochrome P450, laccase, and manganese peroxidase were the common enzymes responsible to degrade CBZ. However, such enzymatic activities can sometimes produce epoxy-CBZ, which is a more toxic compound than the parent compound. Only the fungus Pleurotus ostreatus was able to oxidize epoxy-CBZ via the acridine pathway into acridone, the latter a metabolite that is susceptible to further biodegradation into nontoxic metabolites. However, the identity of the end metabolites is not reported nor characterized. Further, Pseudomonas spp. is the most promising bioremediating agent since it can metabolize CBZ into catechol, the latter can enter the carbon central pathways to generate energy for the bacterial cells

Predictions and errors are distinctly represented across V1 layers

Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive.1–6 Under ‘‘predictive processing’’ schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers.7–10 Predictions are compared with input to compute the ‘‘prediction error,’’ which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.11–15 In the primary visual cortex (V1), predictions have thereby been proposed to influence representations in deep layers while error signals may be computed in superficial layers. Despite the framework’s popularity, there is little evidence for these functional distinctions because, to our knowledge, unexpected sensory events have not previously been presented in human laminar paradigms to contrast against expected events. To this end, this 7T fMRI study contrasted V1 responses to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. Although these results are in line with these accounts that have been popular for decades, such distinctions have not previously been demonstrated in humans. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences

The Impact of Different Screening Model Structures on Cervical Cancer Incidence and Mortality Predictions: The Maximum Clinical Incidence Reduction (MCLIR) Methodology

Background. To interpret cervical cancer screening model results, we need to understand the influence of model structure and assumptions on cancer incidence and mortality predictions. Cervical cancer cases and deaths following screening can be attributed to 1) (precancerous or cancerous) disease that occurred after screening, 2) disease that was present but not screen detected, or 3) disease that was screen detected but not successfully treated. We examined the relative contributions of each of these using 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models. Methods. The maximum clinical incidence reduction (MCLIR) method compares changes in the number of clinically detected cervical cancers and mortality among 4 scenarios: 1) no screening, 2) one-time perfect screening at age 45 that detects all existing disease and delivers perfect (i.e., 100% effective) treatment of all screen-detected disease, 3) one-time realistic-sensitivity cytological screening and perfect treatment of all screen-detected disease, and 4) one-time realistic-sensitivity cytological screening and realistic-effectiveness treatment of all screen-detected disease. Results. Predicted incidence reductions ranged from 55% to 74%, and mortality reduction ranged from 56% to 62% within 15 years of follow-up for scenario 4 across models. The proportion of deaths due to disease not detected by screening differed across the models (21%–35%), as did the failure of treatment (8%–16%) and disease occurring after screening (from 1%–6%). Conclusions. The MCLIR approach aids in the interpretation of variability across model results. We showed that the reasons why screening failed to prevent cancers and deaths differed between the models. This likely reflects uncertainty about unobservable model inputs and structures; the impact of this uncertainty on policy conclusions should be examined via comparing findings from different well-calibrated and validated model platforms

Land-use change and propagule pressure promote plant invasions in tropical rainforest remnants

Context: Intact tropical rainforests are considered robust to plant invasions. However, land-use change alters the structure and species composition of native forest, opening up tropical landscapes to invasion. Yet, the relative roles of key drivers on tropical forest invasions remain little investigated. Objectives: We examine factors affecting plant invasion of rainforest remnants in oil-palm dominated landscapes in Sabah, Malaysian Borneo. We hypothesized that invasion is greater in highly fragmented landscapes, and in disturbed forests with lower native plant diversity (cf. old-growth rainforests). Methods: Native and exotic plants were surveyed in 47 plots at 17 forest sites, spanning gradients in landscape-scale fragmentation and local forest disturbance. Using partial least squares path-modelling, we examined correlations between invasion, fragmentation, forest disturbance, propagule pressure, soil characteristics and native plant community. Results: We recorded 6999 individuals from 329 genera in total, including eight exotic species (0–51% of individuals/plot, median = 1.4%) representing shrubs, forbs, graminoids and climbers. The best model (R2 = 0.343) revealed that invasion was correlated with disturbance and propagule pressure (high prevalence of exotic species in plantation matrix), the latter being driven by greater fragmentation of the landscape. Our models revealed a significant negative correlation between invasion and native tree seedlings and sapling community diversity. Conclusions: Increasing landscape fragmentation promotes exotic plant invasion in remnant tropical forests, especially if local disturbance is high. The association between exotic species invasion and young native tree community may have impacts for regeneration given that fragmentation is predicted to increase and so plant invasion may become more prevalent

Mapping genetic determinants of the cell-culture growth phenotype of enterovirus 71

Enterovirus 71 (EV71) is a member of the species Human enterovirus A within the family Picornaviridae and is a major causative agent of epidemics of hand, foot and mouth disease associated with severe neurological disease. Three EV71 genogroups, designated A, B and C, have been identified, with 75–84 % nucleotide sequence similarity between them. Two strains, EV71-26M (genogroup B) and EV71-6F (genogroup C), were found to have distinct cell-culture growth (26M, rapid; 6F, slow) and plaque-formation (26M, large; 6F, small) phenotypes. To identify the genome regions responsible for the growth phenotypes of the two strains, a series of chimeric viruses was constructed by exchanging the 5′ untranslated region (UTR), P1 structural protein or P2/P3 non-structural protein gene regions plus the 3′UTR using infectious cDNA clones of both virus strains. Analysis of reciprocal virus chimeras revealed that the 5′UTRs of both strains were compatible, but not responsible for the observed phenotypes. Introduction of the EV71-6F P1 region into the EV71-26M clone resulted in a small-plaque and slow-growth phenotype similar to that of EV71-6F, whereas the reciprocal chimera displayed intermediate-growth and intermediate-sized plaque phenotypes. Introduction of the EV71-26M P2–P3–3′UTR regions into the EV71-6F clone resulted in a large-plaque and rapid-growth phenotype identical to that of strain EV71-26M, whereas the reciprocal chimera retained the background strain large-plaque phenotype. These results indicate that, although both the P1 and P2–P3–3′UTR genome regions influence the EV71 growth phenotype in cell culture, phenotype expression is dependent on specific genome-segment combinations and is not reciprocal

Supporting decision-making by companies in delivering their climate net-zero and nature recovery commitments: synthesizing current information and identifying research priorities in rainforest restoration

Many companies are making ambitious pledges to achieve positive impacts for climate and nature by financing restoration of carbon- and biodiversity- rich natural habitats. However, companies cannot make evidence-based choices that will deliver successful restoration if the scientific information required to guide investment has not been synthesised in a way that they can use, or there are knowledge gaps. To explore this issue, share information, and identify knowledge gaps and research priorities, we bring together researchers, a conservation NGO and a multinational consumer goods company (Unilever), focusing on Southeast Asian rainforests. These habitats offer significant restoration opportunities for carbon and biodiversity in areas that have been degraded by commercial logging and agriculture. We find that procedures for carbon restoration are much better developed than those for biodiversity, and that new research is urgently needed to deliver evidence-based biodiversity restoration. Companies need to be confident that their actions are fit-for-purpose to meet their environmental pledges. Achieving successful restoration outcomes will require co-designed projects with the potential to deliver positive co-benefits for carbon, biodiversity and local livelihoods

Creating comprehensive, youth-centered culturally appropriate sex education: What do young gay, bisexual and questioning men want?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106604/1/Creating comprehensive, youth-centered culturally appropriate sex education What do young gay, bisexual and questioning men want.pd

Conservation set-asides improve carbon storage and support associated plant diversity in certified sustainable oil palm plantations

Maintaining forest conservation set-asides is a key criterion of sustainability certification of many crops that drive tropical deforestation, but their value for carbon storage and associated biodiversity is unclear. We conducted vegetation measurements to examine the benefits of set-asides for aboveground carbon stocks (AGC) in certified oil palm plantations on Borneo, and whether their AGC is positively associated with plant diversity. The mean estimated AGC of live trees and palms ≥10 cm diameter in set-asides in certified oil palm plantations (52.8 Mg ha−1) was >1.5-times that of oil palm (30.3 Mg ha−1), with some plots supporting similar AGC to primary forest. For lowland Borneo, we estimate that the average AGC of oil palm plantations with 10% coverage of set-asides is up to 20% greater than the average AGC of oil palm plantations without set-asides, newly demonstrating carbon storage as a benefit of conservation set-asides. We found positive relationships between AGC and plant diversity, highlighting the carbon–biodiversity co-benefits of set-asides. However, set-asides had a lower density of tree seedlings than continuous primary forest, indicating potential suppression of future tree regeneration and AGC. Our findings support the application of zero-deforestation during agricultural development, to conserve areas of remaining forest with high AGC and high biodiversity. We recommend management practices that boost regeneration in existing set-asides (e.g. enrichment planting), which would be most effective in larger set-asides, and could substantially increase the AGC of agricultural landscapes without removing land from production, and help conserve forest-dependent biodiversity