Background: Many studies suggest that the small ubiquitin-like modifier 4 (SUMO4) M55V gene polymorphism (rs237025) may be associated with an increased risk of type 2 diabetes mellitus (T2DM). However, due to other conflicting results, a clear consensus is lacking in the matter. Objective and methods: A meta-analysis consisting of 6,823 subjects from 10 studies was conducted to elucidate relationship between the SUMO4 M55V gene polymorphism and T2DM. Depending on the heterogeneity of the data, either a fixed or random-effects model would be used to assess the combined odds ratio (ORs) and their corresponding 95% confidence interval (CI). Results: SUMO4 gene M55V polymorphism was significantly associated with T2DM in the whole population under allelic (OR: 1.18, 95% CI: 1.10 - 1.28, P = 1.63×10-5), recessive (OR: 1.59, 95% CI: 1.14-2.23, P = 0.006), dominant (OR: 0.815, 95% CI: 0.737 - 0.901, P = 6.89×10-5), homozygous (OR: 1.415, 95% CI: 1.170 - 1.710, P = 0.0003), heterozygous (OR: 1.191, 95% CI: 1.072 - 1.323, P = 0.001), and additive genetic models (OR: 1.184, 95% CI: 1.097 - 1.279, P = 1.63×10-5). In our subgroup analysis, a significant association was found again in the Chinese population, but not in Japanese or Iranian population. Conclusion: SUMO4 gene M55V polymorphism may correlate with increased T2DM risk. Chinese carriers of the V allele of the SUMO4 gene M55V polymorphism may be predisposed to developing T2DM.

The distribution shift of forest species due to the fact of climate change may negatively affect ecosystem services including the production of medicinal resources. Climate change impact assessments of habitat range changes are essential to sustainably manage forest resources. A change in the habitat suitability due to the fact of climate change was predicted for Angelica gigas, which has high economic value among forest medicinal resources in South Korea. The habitat suitability was predicted by an ensemble species distribution model that combined the results of nine single algorithm models using the committee averaging method. A total 168 occurrence data and 10 environmental variables were used for the single algorithm models. The area under the receiver operation characteristic curve (AUC) and true skill statistic (TSS) were applied to evaluate the models’ performance, and the contribution of the environmental variables was calculated as an important value for each single algorithm model. Climate change scenarios were projected to predict future habitat suitability. The future suitable habitat for A. gigas was gradually reduced to the high mountain regions of the eastern part of South Korea regardless of the climate change scenarios. The main environmental variable was the annual mean temperature, and the rise in temperature due to the fact of climate change was found to have a negative effect on the habitat suitability for A. gigas. The decline in the habitat suitability for A. gigas, a major forest medicinal resource, is expected to result in the reduction in its production. Therefore, it is required to establish adaptation measures to mitigate the negative impact of this decrease, such as protecting the natural habitats of A. gigas.

Cudrania tricuspidata is a traditional medicinal herb in East Asia. The compounds of plants vary depending on environmental factors, such as soil, temperature, drainage, and so on. However, few to no studies have been done on the correlation among environment, growth, and compounds in C. tricuspidata. Thus, we aimed to investigate their relationship. Samples of C. tricuspidata fruit and cultivation soil were collected from 28 cultivation sites in October 2021. Six growth characteristics, eleven soil physicochemical properties, seven meteorological data points, and three active compounds were investigated in this study. We developed and validated an optimized method for quantifying active compounds using UPLC and performed correlation analysis of the environment, growth characteristics, and active compounds. The UPLC-UV method for determining active compounds was validated by measuring the linearity, LOD, LOQ, precision, and accuracy using UPLC. The LOD and LOQ were 0.01–0.03 µg/mL and 0.04–0.09 µg/mL, respectively. The precision was acceptable with RSD% values less than 2%. The recoveries ranged from 97.25 to 104.98% with RSD values <2%, within the acceptable limits. The active compounds were negatively correlated with the size of the fruit, and the growth characteristics were negatively correlated with some environmental factors. The results of this study can be used as basic data for the standard cultural practices and quality control of C. tricuspidata fruits.

The growth characteristics and active compounds of plants are influenced by various environmental factors, including light, temperature, soil, and precipitation. These factors interact with each plant in a unique way. In this study, we collected fruit and soil samples from 17 cultivation sites in October 2020 to investigate the relationship among environmental factors, growth characteristics, and active compounds of H. dulcis seed and fruit. We developed an optimized method for quantifying active compounds using ultra-performance liquid chromatography and performed correlation analyses with the surveyed environmental factors. Results showed that the size and fresh weight of H. dulcis fruits were positively correlated with exchangeable Mg, Na, and silt texture proportion in the soil. The temperature was positively correlated with sugar content in the fruits but negatively correlated with fruit weight, and precipitation was negatively correlated with fruit size. Results also showed a positive correlation between the active compounds and growth characteristics such as fruit length, seed number per fruit, and fresh weight. The results of this study can be used as basic data for the cultivation and quality control of H. dulcis fruits.