Integrating UAV data for assessing the ecological response of Spartina alterniflora towards inundation and salinity gradients in coastal wetland.

The overwhelming spread of Spartina alterniflora (smooth cordgrass) has put many native plant communities and coastal environments at risk. A better understanding of how S. alterniflora responds to inundation and salinity gradients will help manage the invasion of this species. However, current spatial quantitative analyses are insufficient. Thus, unmanned aerial vehicles (UAVs) and field sampling data were integrated to assess the ecological response of S. alterniflora to inundation and salinity gradients. This study aimed to determine the optimum ecological range of flooding and saline for S. alterniflora in Dafeng Milu National Nature Reserve in Jiangsu, China. Our results showed that the optimum ecological amplitude of S. alterniflora to flooding depth was [-0.07 m, 0.82 m] and the optimum mean growing point was 0.38 m. Furthermore, the optimum flooding time was [0 h,11.87 h], and the optimum mean growing point was 4.13 h. Our analyses also showed that soil salinity had significant effects on the growth of S. alterniflora. The optimum ecological amplitude of S. alterniflora to soil salinity was [13.77 g/kg, 22.57 g/kg], and the optimum mean growing point was 18.19 g/kg. This is the first spatially quantitative analysis to study the eco-hydrological mechanism driving both the aboveground biomass and height of S. alterniflora over the intertidal zone to the best of our knowledge. Determining the optimal ecological range for flooding and salt will provide a scientific basis for measures to establish the ecological control of S. alterniflora and to predict the expansion of S. alterniflora in response to rising sea levels.

Development of a Nomogram Model for Predicting the Risk of In-Hospital Death in Patients with Acute Kidney Injury.

OBJECTIVE: To analyze the risk factors of in-hospital death in patients with acute kidney injury (AKI) in the intensive care unit (ICU), and to develop a personalized risk prediction model. METHODS: The clinical data of 137 AKI patients hospitalized in the ICU of Anhui provincial hospital from January 2018 to December 2020 were retrospectively analyzed. Patients were divided into two groups: those that survived to discharge ("survival" group, 100 cases) and those that died while in hospital ("death" group, 37 cases), and risk factors for in-hospital death analyzed. RESULTS: The in-hospital mortality of AKI patients in the ICU was 27.01% (37/137). A multivariate logistic regression analysis indicated age, mechanical ventilation and vasoactive drugs were significant risk factors for in-hospital death in AKI patients, and a nomogram risk prediction model was developed. The Harrell's C-index of the nomogram model was 0.891 (95% CI: 0.837-0.945), and the area under the receiver operating characteristic (ROC) curve was 0.886 (95% CI: 0.823-0.936) after internal validation, indicating that the nomogram model had good discrimination. The Hosmer-Lemeshow goodness of fit test and calibration curve indicated the predicted probability of the nomogram model was consistent with the actual frequency of death in ICU patients with AKI. The decision curve analysis (DCA) showed that the clinical net benefit level of the nomogram model is highest when the probability threshold of AKI is between 0.01 and 0.75. CONCLUSION: Patients in the ICU with AKI had high in-hospital mortality and were affected by a variety of risk factors. The nomogram prediction model based on the risk factors of AKI showed good prediction efficiency and clinical applicability, which could help medical staff in the ICU to identify AKI patients with high-risk, allowing early prevention, detection and intervention, and reducing the risk of in-hospital deaths in ICU patients with AKI.

The effect of folic acid deficiency on Mest/Peg1 in neural tube defects.

OBJECTIVE: Neural tube defects (NTDs) are one of the most common and serious birth defects in human beings caused by genetic and environmental factors. Folate insufficiency is involved in the occurrence of NTDs and folic acid supplementation can prevent NTDs occurrence, however, the underlying mechanism remains poorly understood. METHODS: We established cell and animal models of folic acid deficiency to detect the methylation modification and expression levels of genes by MassARRAY and real-time PCR, respectively. Results and conclusion: In the present study, we found firstly that in human folic acid-insufficient NTDs, the methylation level of imprinted gene Mest/Peg1 was decreased. By using a folic acid-deficient cell model, we demonstrated that Mest/Peg1 methylation was descended. Meanwhile, the mRNA level of Mest/Peg1 was up-regulated via hypomethylation modification under low folic acid conditions. Consistent with the results in cell models, Mest/Peg1 expression was elevated through hypomethylation regulation in folate-deficient animal models. Furthermore, the up-regulation of Mest/Peg1 inhibited the expression of Lrp6 gene, a crucial component of Wnt pathway. Similar results with Lrp6 down-regulation of fetal brain were verified in animal models under folic acid-deficient condition. Taken together, our findings indicated folic acid increased the expression of Mest/Peg1 via hypomethylation modification, and then inhibited Lrp6 expression, which may ultimately impact on the development of nervous system through the inactivation of Wnt pathway.

Relationship between HLA-DPA1 genetic polymorphism and anembryonic pregnancy.

BACKGROUND: Human leukocyte antigen (HLA)-DP is an HLA class II molecule. Overexpression of HLA class II molecules in placental trophoblast cells may induce pregnancy loss. However, the association between HLA-DP and pregnancy loss remains unclear. HLA-DPA1 is an HLA-DP peptide chain. The objective of this study was to assess the association between HLA-DPA1 genetic polymorphism and anembryonic pregnancy, a type of early pregnancy loss, in the Chinese population. METHODS: A case-control study was designed to compare the frequencies of HLA-DPA1 gene polymorphisms in an anembryonic pregnancy group and a control group. Sixty-eight cases and 122 controls were recruited. Statistical analysis was performed to assess the correlation between single-nucleotide polymorphisms (SNPs) and anembryonic pregnancy susceptibility. MassARRAY high-throughput DNA analysis was used to analyze 19 HLA-DPA1 SNPs. To explore how HLA-DPA1 polymorphism could affect anembryonic pregnancy, HLA-DPA1 serum levels were analyzed by ELISA. RESULTS: Homozygous typing of rs1431403 (CC and TT) significantly increased the risk of anembryonic pregnancy in the case group (ORCC  = 3.13, 95% CI: 1.50-6.53; ORTT  = 2.96, 95% CI: 1.31-6.66; ORCC+TT  = 3.06, 95% CI: 1.62-5.78). In samples with high HLA-DPA1 levels (≥1,500 pg/ml), the homozygous rs1431403 genotypes (nCC  = 21, 43.8%; nTT  = 20, 57.1%) were observed more frequently than were heterozygous genotypes. CONCLUSION: HLA-DPA1 rs1431403 may be a risk factor for anembryonic pregnancy in the Chinese population. Homozygous rs1431403 genotypes (CC and TT) may increase the risk of anembryonic pregnancy by aberrantly increasing the HLA-DPA1 levels.

Melatonin receptor 1B gene polymorphism rs10830963 and gestational diabetes mellitus among a Chinese population - a meta-analysis of association studies.

INTRODUCTION: Studies have been conducted to investigate the association between rs10830963 of MTNR1B and the risk of gestational diabetes mellitus (GDM), but with inconclusive results. We aimed to clarify these controversies, especially with regard to the association in the Chinese population. MATERIAL AND METHODS: A systemic literature reference search inclusive to August 12, 2016 yielded 35 articles, from which 11 studies met the inclusion criteria for the final meta-analysis, including 3889 patients with GDM and 6708 controls. RESULTS: We found statistically significant associations between rs10830963 and GDM using odds ratios (ORs) and 95% confidence intervals (CIs) [GG genotype vs. CC genotype: OR = 1.70, 95% CI: 1.38-2.10; G allele vs C allele: OR = 1.27, 95% CI: 1.20-1.36; GG+CG vs. CC (dominant model): OR = 1.31, 95% CI: 1.20-1.44; GG vs CG+CC (recessive model): OR = 1.41, 95% CI: 1.26-1.58]. In subgroup analyses stratified by ethnicity, we also observed rs10830963 to be associated with significantly increased risk of GDM in all genetic models in the Chinese population. CONCLUSIONS: Our meta-analysis indicated that the rs10830963 polymorphism might serve as a risk factor of GDM in the Chinese population.