Life expectancy can reflect both health benefit and implementation cost of climate policy. Nevertheless, little research has quantified the relation between life expectancy and climate policy in literature. In this paper, we attempt to narrow the research gap by studying how life expectancy is related to the Chinese nationwide emission trading scheme (CNETS). To achieve this research target, a Computable General Equilibrium (CGE) model is employed to simulate the operation of the economic system and the policy shock from emission abatement. The CGE model results show that life expectancy is prolonged by GDP but shortened by emissions, and the GDP impact on life expectancy is larger than the emission impact. Climate policy has dual effects on life expectancy because it relieves both negative emission impacts and positive GDP impacts on lifespan; its net effect on life expectancy is positive. Life expectancy positively impacts GDP, and this impact is moderated by climate policy; specifically, climate policy reinforces the positive impact of life expectancy on GDP. Life expectancy minimally affects carbon emissions during climate policy implementation; in other words, it has minimal impacts on emission abatement. These findings imply that climate policy and life expectancy complement each other; the government could implement climate policy to increase lifespan or prolong life expectancy to facilitate policy implementation.

With the development of economic and technologies, the trend of annual Gross Domestic Product (GDP) and carbon dioxide (CO2) emission changes with time passes. The relationship between economic growth and carbon dioxide emissions is considered as one of the most important empirical relationships. In this study, we focus on the member of Shanghai Cooperation Organization, including China, Russia, India, and Pakistan and collect CO2 emission and annual GDP from 1969 to 2014. The statistical methods and tests are used to find the relationship between annual GDP and CO2 emission in these countries. Based on relationship between annual and CO2 emission, a novel multi-step prediction algorithm called Extreme Learning Machine with Artificial Bee Colony (ELM-ABC) is proposed for forecasting annual GDP based on CO2 emission and historical GDP features. According to the experimental results, it proved that the proposed model had a super forecasting ability in GDP prediction and it could predict ten-year future annual GDP for the corresponding countries. Moreover, the forecasting results showed that the annual GDP of China and Pakistan will continue to grow but growth will slow after 2025. The annual GDP in India will exhibit unstable growth. The trend of Russia will follow the pattern between 2010 and 2016.

BACKGROUND: Growing public and private expenditure on healthcare results i.a. from the spreading of chronic diseases. Diabetes belongs to the most frequent ones, beyond neoplasms and cardiological diseases, and hence generates a significant burden for the public finance in terms of the direct costs. However, the economy suffers also from the indirect cost of diabetes that manifests itself in the loss in Gross Domestic Product (GDP) and general government revenues.
METHODS: This paper aims to measure this indirect cost, both in terms of GDP drop (social perspective) and public revenue drop (public finance perspective), in the case of Poland in 2012-2014. We use a modified human capital approach and unique dataset provided by the Social Security institution in Poland and the Polish Central Statistical Office.
RESULTS: Diabetes is a substantial and growing burden for the Polish economy. In the years 2012, 2013 and 2014 the indirect cost (output loss) amounted to 1.85 bn USD, 1.94 bn USD and 2.00 bn USD respectively.
CONCLUSIONS: Estimated indirect cost of diabetes can be a useful input for health technology analyses of drugs or economic impact assessments of public health programmes.

Congenital disorders of glycosylation (CDG) are a growing group of inherited metabolic disorders where enzymatic defects in the formation or processing of glycolipids and/or glycoproteins lead to variety of different diseases. The deficiency of GDP-Man:GlcNAc2-PP-dolichol mannosyltransferase, encoded by the human ortholog of ALG1 from yeast, is known as ALG1-CDG (CDG-Ik). The phenotypical, molecular and biochemical analysis of a severely affected ALG1-CDG patient is the focus of this paper. The patient\'s main symptoms were feeding problems and diarrhea, profound hypoproteinemia with massive ascites, muscular hypertonia, seizures refractory to treatment, recurrent episodes of apnoea, cardiac and hepatic involvement and coagulation anomalies. Compound heterozygosity for the mutations c.1145T>C (M382T) and c.1312C>T (R438W) was detected in the patient\'s ALG1-coding sequence. In contrast to a previously reported speculation on R438W we confirmed both mutations as disease-causing in ALG1-CDG.