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Aim: To investigate the relationship of fibroblast growth factor receptor 4 (FGFR4) gene polymorphisms with the response of Chinese patients with non-small cell lung cancer (NSCLC) to chemotherapy. Methods: A total of 629 patients with Stage III (A+B) or IV NSCLC, as well as 729 age-and gender-matched healthy controls were recruited. All the patients received platinum-based chemotherapy, and the therapeutic effects were evaluated. Three polymorphisms in the FGFR4 gene (rs351855G/A, rs145302848C/G, and rs147603016G/A) were genotyped, and the association between the 3 polymorphisms and the chemotherapy effect was analyzed using SPSS software, version 16.0. Results: The genotype frequencies of rs145302848C/G and rs147603016G/A were not significantly different between NSCLC patients and healthy controls on one hand, and between the responders and non-responders to the chemotherapy on the other hand. The distribution of AA genotype and A-allele of rs351855G/A was significantly lower in NSCLC patients than in healthy controls. Using patients with the GG genotype as a reference, the AA carrier had a significantly reduced risk for the development of NSCLC after normalizing to age, sex and smoking habits. In NSCLC patients, this genotype occurred more frequently in the responders to the chemotherapy than in non-responders. The chance of being a responder was significantly increased with the AA genotype as compared to G genotype. The AA genotype of rs351855G/A had a better prognosis compared with GA and GG genotype carriers: the overall survival of patients with the AA genotype of rs351855G/A was significantly longer than those with the GG+GA genotype (21.1 vs 16.5 months). Conclusion:The rs351855G/A polymorphisms of FGFR4 gene can be used to predict the occurrence, chemotherapy response and prognosis of NSCLC.

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This paper presents the results of airborne pollen and spore trapping in Nanjing city, eastern China, using a Burkard pollen trap during two consecutive years (2013)(2014). A total of 103 pollen and spore taxa were identified. Two concentration peaks are observed in the annual cycle, a spring peak dominated by arboreal pollen types (Morus, Cupressaceae, Pinus, Pterocarya, and Quercus) and a fall peak dominated by upland herbs (Compositae, Poaceae, Humulus, and Cruciferae). Wetland herbs and ferns dominate summer assemblages and winter assemblages are characterized by sporadic records of Artemisia, Chenopodiaceae, and Pinus. Strong year-to-year differences in measured pollen concentration are seen, probably in response to interyear differences in weather. Compared to long-term means, 2013 was comparatively hot and dry and 2014 had a higher than average number of rain days during the flowering periods. Rising temperatures in early spring are connected with the timing of flowering and therefore pollen release, while rainfall during the flowering period appeared to remove pollen from the air, leading to lower recorded pollen concentration values. Four taxa, Cupressaceae, Quercus, Pinus, and Humulus, were considered in more detail. Each has a different pattern of variation in pollen concentration between the studied years. Cross correlation between pollen concentration and daily temperature, relative humidity, and precipitation at lags from 0 to À30 days also showed different responses for each taxon, suggesting that pollen signal responses to weather conditions have to be considered at a taxon level rather than at the assemblage level.FANG ET AL.

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Reconstructing land cover from pollen data using mathematical models of the relationship between them has the potential to translate the many thousand pollen records produced over the last 100 years (over 2300 radiocarbon-dated pollen records exist for the UK alone) into formats relevant to ecologists, archaeologists and climate scientists. However, the reliability of these reconstructions depends on model parameters. A key parameter is Relative Pollen Productivity (RPP), usually estimated from empirical data using ‘Extended R Value analysis’ (ERV analysis). Lack of RPP estimates for many regions is currently a major limitation on reconstructing global land cover. We present two alternatives to ERV analysis, the Modified Davis Method and an iteration method, which use the same underlying model of the relationship between pollen and vegetation to estimate RPP from empirical data, but with different assumptions. We test them in simulation against ERV analysis, and use a case study of a problematic empirical dataset to determine whether they have the potential to increase the speed and geographic range of RPP estimation. The two alternative methods are shown to perform at least as well as ERV analysis in simulation. We also present new RPP estimates from southeastern sub-tropical China for nine taxa estimated using the Modified Davis Method. Adding these two methods to the ‘toolkit’ for land cover reconstruction from pollen records opens up the possibility to estimate a key parameter from existing datasets with less field time than using current methods. This can both speed up the inclusion of more of the globe in past land cover mapping exercises such as the PAGES Landcover6k working group and improve our understanding of how this parameter varies within a single taxon and the factors control that variation.

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