There is increasing evidence that the natural environment provides substantial benefits to human emotional well-being. The current study synthesized this body of research using the meta-analysis and assessed the positive and negative effects of exposure to both the natural and built environments. We searched four databases and 20 studies were included in the review. The meta-analysis results showed the most convincing evidence that exposure to the natural environment could increase positive affect (standardized mean difference, SMD = 0.61, 95% CI 0.41, 0.81) and decreased negative affect (SMD = −0.47, 95% CI −0.71, −0.24). However, there was extreme heterogeneity between the studies, and the risk of bias was high. According to the subgroup analysis, study region, study design, mean age of the sample, sample size, and type of natural and built environment were found to be important factors during exposure to the natural environment. The implications of these findings for the existing theory and research are discussed. These findings will help convince the health professionals and policymakers to encourage the residents to increase their time spent in the natural environment. These findings of this systematic review also suggested that the creation, maintenance, and enhancement of accessible greenspaces or existing natural environments may form part of a multidimensional approach to increasing emotional well-being of the local populations.

Background Tetrapyrroles play indispensable roles in various biological processes. In higher plants, glutamate 1-semialdehyde 2,1-aminomutase (GSAM) converts glutamate 1-semialdehyde (GSA) to 5-aminolevulinic acid (ALA), which is the rate-limiting step of tetrapyrrole biosynthesis. Up to now, GSAM genes have been successively identified from many species. Besides, it was found that GSAM could form a dimeric protein with itself by x-ray crystallography. However, no mutant of GSAM has been identified in monocotyledonous plants, and no experiment on interaction of GSAM protein with itself has been reported so far. Result We isolated a yellow leaf mutant, ys53, in rice (Oryza sativa). The mutant showed decreased photosynthetic pigment contents, suppressed chloroplast development, and reduced photosynthetic capacity. In consequence, its major agronomic traits were significantly affected. Map-based cloning revealed that the candidate gene was LOC_Os08g41990 encoding GSAM protein. In ys53 mutant, a single nucleotide substitution in this gene caused an amino acid change in the encoded protein, so its ALA-synthesis ability was significantly reduced and GSA was massively accumulated. Complementation assays suggested the mutant phenotype of ys53 could be rescued by introducing wild-type OsGSAM gene, confirming that the point mutation in OsGSAM is the cause of the mutant phenotype. OsGSAM is mainly expressed in green tissues, and its encoded protein is localized to chloroplast. qRT-PCR analysis indicated that the mutation of OsGSAM not only affected the expressions of tetrapyrrole biosynthetic genes, but also influenced those of photosynthetic genes in rice. In addition, the yeast two-hybrid experiment showed that OsGSAM protein could interact with itself, which could largely depend on the two specific regions containing the 81th–160th and the 321th–400th amino acid residues at its N- and C-terminals, respectively. Conclusions We successfully characterized rice GSAM gene by a yellow leaf mutant and map-based cloning approach. Meanwhile, we verified that OsGSAM protein could interact with itself mainly by means of the two specific regions of amino acid residues at its N- and C-terminals, respectively.

The Sichuan province is a key area for forest and grassland fire prevention in China. Forest resources contribute significantly not only to the biological gene pool in the mid latitudes but also in reducing the concentration of greenhouse gases and slowing down global warming. To study and forecast forest fire change trends in a grade I forest fire danger zone in the Sichuan province under climate change, the dynamic impacts of meteorological factors on forest fires in different climatic regions were explored and a model between them was established by using an integral regression in this study. The results showed that the dominant factor behind the area burned was wind speed in three climatic regions, particularly in Ganzi and A’ba with plateau climates. In Ganzi and A’ba, precipitation was mainly responsible for controlling the number of forest fires while it was mainly affected by temperature in Panzhihua and Liangshan with semi-humid subtropical mountain climates. Moreover, the synergistic effect of temperature, precipitation and wind speed was responsible in basin mid-subtropical humid climates with Chengdu as the center and the influence of temperature was slightly higher. The differential forest fire response to meteorological factors was observed in different climatic regions but there was some regularity. The influence of monthly precipitation in the autumn on the area burned in each climatic region was more significant than in other seasons, which verified the hypothesis of a precipitation lag effect. Climate warming and the combined impact of warming effects may lead to more frequent and severe fires.