miR-552 promotes the proliferation and metastasis of intrahepatic cholangiocarcinoma by targeting FOXO1.

Intrahepatic cholangiocarcinoma (ICC) is a relatively rare but highly malignant cancer. Few effective systemic targeted therapies are available for patients with unresectable ICC, but there exists an urgent need to explore mechanisms underlying the initiation and progression of ICC. MicroRNA (miRNA) plays vital roles in the initiation, progression, and drug resistance of different cancers. Recently, the biological function of a novel miRNA, miR-552, has been widely analyzed in hepatocellular carcinoma and colorectal, cervical, gastric, and other cancers. However, its role in ICC has not yet been elucidated. In this study, we found that miR-552 expression was upregulated in ICC and that miR-552 predicted poor prognosis. Using functional studies, we found that miR-552 enhanced the proliferation and invasion ability of ICC cells. Mechanistic research identified that forkhead box O1 (FOXO1) is the target of miR-552 in ICC. Moreover, the combined panels of miR-552 and FOXO1 exhibited a better prognostic value for ICC patients than did miR-552 alone. In conclusion, these findings demonstrated that the miR-552/FOXO1 axis drove ICC progression, further suggesting that targeting this axis could be a novel therapeutic strategy for ICC.

Genome evolution of the psammophyte Pugionium for desert adaptation and further speciation.

Deserts exert strong selection pressures on plants, but the underlying genomic drivers of ecological adaptation and subsequent speciation remain largely unknown. Here, we generated de novo genome assemblies and conducted population genomic analyses of the psammophytic genus Pugionium (Brassicaceae). Our results indicated that this bispecific genus had undergone an allopolyploid event, and the two parental genomes were derived from two ancestral lineages with different chromosome numbers and structures. The postpolyploid expansion of gene families related to abiotic stress responses and lignin biosynthesis facilitated environmental adaptations of the genus to desert habitats. Population genomic analyses of both species further revealed their recent divergence with continuous gene flow, and the most divergent regions were found to be centered on three highly structurally reshuffled chromosomes. Genes under selection in these regions, which were mainly located in one of the two subgenomes, contributed greatly to the interspecific divergence in microhabitat adaptation.

In Situ Root Dataset Expansion Strategy Based on an Improved CycleGAN Generator.

The root system plays a vital role in plants' ability to absorb water and nutrients. In situ root research offers an intuitive approach to exploring root phenotypes and their dynamics. Deep-learning-based root segmentation methods have gained popularity, but they require large labeled datasets for training. This paper presents an expansion method for in situ root datasets using an improved CycleGAN generator. In addition, spatial-coordinate-based target background separation method is proposed, which solves the issue of background pixel variations caused by generator errors. Compared to traditional threshold segmentation methods, this approach demonstrates superior speed, accuracy, and stability. Moreover, through time-division soil image acquisition, diverse culture medium can be replaced in in situ root images, thereby enhancing dataset versatility. After validating the performance of the Improved_UNet network on the augmented dataset, the optimal results show a 0.63% increase in mean intersection over union, 0.41% in F1, and 0.04% in accuracy. In terms of generalization performance, the optimal results show a 33.6% increase in mean intersection over union, 28.11% in F1, and 2.62% in accuracy. The experimental results confirm the feasibility and practicality of the proposed dataset augmentation strategy. In the future, we plan to combine normal mapping with rendering software to achieve more accurate shading simulations of in situ roots. In addition, we aim to create a broader range of images that encompass various crop varieties and soil types.

Improved Transformer for Time Series Senescence Root Recognition.

The root is an important organ for plants to obtain nutrients and water, and its phenotypic characteristics are closely related to its functions. Deep-learning-based high-throughput in situ root senescence feature extraction has not yet been published. In light of this, this paper suggests a technique based on the transformer neural network for retrieving cotton's in situ root senescence properties. High-resolution in situ root pictures with various levels of senescence are the main subject of the investigation. By comparing the semantic segmentation of the root system by general convolutional neural networks and transformer neural networks, SegFormer-UN (large) achieves the optimal evaluation metrics with mIoU, mRecall, mPrecision, and mF1 metric values of 81.52%, 86.87%, 90.98%, and 88.81%, respectively. The segmentation results indicate more accurate predictions at the connections of root systems in the segmented images. In contrast to 2 algorithms for cotton root senescence extraction based on deep learning and image processing, the in situ root senescence recognition algorithm using the SegFormer-UN model has a parameter count of 5.81 million and operates at a fast speed, approximately 4 min per image. It can accurately identify senescence roots in the image. We propose that the SegFormer-UN model can rapidly and nondestructively identify senescence root in in situ root images, providing important methodological support for efficient crop senescence research.

Demographic patterns of two related desert shrubs with overlapping distributions in response to past climate changes.

Numerous studies have revealed that past geological events and climatic fluctuations had profoundly affected the genetic structure and demographic patterns of species. However, related species with overlapping ranges may have responded to such environmental changes in different ways. In this study, we compared the genetic structure and population dynamics of two typical desert shrubs with overlapping distributions in northern China, Nitraria tangutorum and Nitraria sphaerocarpa, based on chloroplast DNA (cpDNA) variations and species distribution models. We sequenced two cpDNA fragments (trnH-trnA and atpH-atpI) in 633 individuals sampled from 52 natural populations. Twenty-four chlorotypes, including eight rare chlorotypes, were identified, and a single dominant haplotype (H4) widely occurred in the entire geographical ranges of the two species. There were also a few distinctive chlorotypes fixed in different geographical regions. Population structure analyses suggested that the two species had significantly different levels of total genetic diversity and interpopulation differentiation, which was highly likely correlated with the special habitat preferences of the two species. A clear phylogeographic structure was identified to exist among populations of N. sphaerocarpa, but not exist for N. tangutorum. The neutral tests, together with the distribution of pairwise differences revealed that N. tangutorum experienced a sudden demographic expansion, and its expansion approximately occurred between 21 and 7 Kya before present, while a rapid range expansion was not identified for N. sphaerocarpa. The ecological niche modeling (ENM) analysis indicated that the potential ranges of two species apparently fluctuated during the past and present periods, with obvious contraction in the Last Glacial Maximum (LGM) and recolonization in the present, respectively, comparing to the Last Interglacial (LIG). These findings suggest that the two species extensively occurred in the Northwest of China before the Quaternary, and the current populations of them originated from a few separated glacial refugia following their habitat fragmentation in the Quarternary. Our results provide new insights on the impact of past geological and climatic fluctuations on the population dynamics of desert plants in northwestern China, and further enforce the hypothesis that there were several independent glacial refugia for these species during the Quaternary glaciations.

Pleistocene climate change and the origin of two desert plant species, Pugionium cornutum and Pugionium dolabratum (Brassicaceae), in northwest China.

Pleistocene climate change has had an important effect in shaping intraspecific genetic variation in many species; however, its role in driving speciation is less clear. We examined the possibility of a Pleistocene origin of the only two representatives of the genus Pugionium (Brassicaceae), Pugionium cornutum and Pugionium dolabratum, which occupy different desert habitats in northwest China. We surveyed sequence variation for internal transcribed spacer (ITS), three chloroplast (cp) DNA fragments, and eight low-copy nuclear genes among individuals sampled from 11 populations of each species across their geographic ranges. One ITS mutation distinguished the two species, whereas mutations in cpDNA and the eight low-copy nuclear gene sequences were not species-specific. Although interspecific divergence varied greatly among nuclear gene sequences, in each case divergence was estimated to have occurred within the Pleistocene when deserts expanded in northwest China. Our findings point to the importance of Pleistocene climate change, in this case an increase in aridity, as a cause of speciation in Pugionium as a result of divergence in different habitats that formed in association with the expansion of deserts in China.

A method of cotton root segmentation based on edge devices.

The root is an important organ for plants to absorb water and nutrients. In situ root research method is an intuitive method to explore root phenotype and its change dynamics. At present, in situ root research, roots can be accurately extracted from in situ root images, but there are still problems such as low analysis efficiency, high acquisition cost, and difficult deployment of image acquisition devices outdoors. Therefore, this study designed a precise extraction method of in situ roots based on semantic segmentation model and edge device deployment. It initially proposes two data expansion methods, pixel by pixel and equal proportion, expand 100 original images to 1600 and 53193 respectively. It then presents an improved DeeplabV3+ root segmentation model based on CBAM and ASPP in series is designed, and the segmentation accuracy is 93.01%. The root phenotype parameters were verified through the Rhizo Vision Explorers platform, and the root length error was 0.669%, and the root diameter error was 1.003%. It afterwards designs a time-saving Fast prediction strategy. Compared with the Normal prediction strategy, the time consumption is reduced by 22.71% on GPU and 36.85% in raspberry pie. It ultimately deploys the model to Raspberry Pie, realizing the low-cost and portable root image acquisition and segmentation, which is conducive to outdoor deployment. In addition, the cost accounting is only $247. It takes 8 hours to perform image acquisition and segmentation tasks, and the power consumption is as low as 0.051kWh. In conclusion, the method proposed in this study has good performance in model accuracy, economic cost, energy consumption, etc. This paper realizes low-cost and high-precision segmentation of in-situ root based on edge equipment, which provides new insights for high-throughput field research and application of in-situ root.

Identification and expression analysis of the small auxin-up RNA (SAUR) gene family in Lycium ruthenicum.

The plant hormone auxin regulates numerous aspects of plant growth and development, and small auxin-up RNA (SAUR) is the largest family of early auxin response genes in higher plants. SAUR has been implicated in the regulation of multiple biological processes. However, no comprehensive analysis of SAUR genes has been reported in Lycium ruthenicum. L. ruthenicum is a thorny shrub with very pronounced salt and drought tolerance, and studies have shown that stem thorns are related to drought tolerance in L. ruthenicum. In this study, the identification, phylogenetic analysis, and conserved motif prediction of SAUR genes were extensively explored. Furthermore, the tissue expression patterns of selected SAUR genes were assayed with quantitative real-time polymerase chain reaction (RT-qPCR). A total of 33 putative LrSAURs were identified and divided into three clusters in a phylogenetic tree of L. ruthenicum. MEME analysis identified 10 motifs in L. ruthenicum, and the results suggested that motif 1 and motif 3 were widely distributed. Analyzing the transcriptome data of stem thorns at four developmental stages indicated that LrSAURs were differentially expressed in L. ruthenicum, and could be divided into six expression patterns. The RT-qPCR analysis of 21 genes showed that LrSAUR2, LrSAUR8, LrSAUR9, LrSAUR11, LrSAUR12, and LrSAUR19 were mainly expressed in stems and stem thorns, and may be related to stem thorn development.

Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots.

The root is an important organ for crops to absorb water and nutrients. Complete and accurate acquisition of root phenotype information is important in root phenomics research. The in situ root research method can obtain root images without destroying the roots. In the image, some of the roots are vulnerable to soil shading, which severely fractures the root system and diminishes its structural integrity. The methods of ensuring the integrity of in situ root identification and establishing in situ root image phenotypic restoration remain to be explored. Therefore, based on the in situ root image of cotton, this study proposes a root segmentation and reconstruction strategy, improves the UNet model, and achieves precise segmentation. It also adjusts the weight parameters of EnlightenGAN to achieve complete reconstruction and employs transfer learning to implement enhanced segmentation using the results of the former two. The research results show that the improved UNet model has an accuracy of 99.2%, mIOU of 87.03%, and F1 of 92.63%. The root reconstructed by EnlightenGAN after direct segmentation has an effective reconstruction ratio of 92.46%. This study enables a transition from supervised to unsupervised training of root system reconstruction by designing a combination strategy of segmentation and reconstruction network. It achieves the integrity restoration of in situ root system pictures and offers a fresh approach to studying the phenotypic of in situ root systems, also realizes the restoration of the integrity of the in situ root image, and provides a new method for in situ root phenotype study.

Postoperative Prognosis of Non-alcoholic Fatty Liver Disease-Associated Intrahepatic Cholangiocarcinoma: a Multi-center Propensity Score Matching Analysis.

BACKGROUND AND AIMS: The incidence of intrahepatic cholangiocarcinoma (ICC) in non-alcoholic fatty liver disease (NAFLD) is increasing gradually. The prognosis of NAFLD-ICC has not been well studied. We aim to investigate the prognosis of patients with NAFLD-ICC after curative-intent partial hepatectomy (PH). METHODS: Multi-center data from January 2003 to January 2014 were retrospectively analyzed. The prognosis of ICC was analyzed using PSM and compared with hepatitis B virus (HBV)-related ICC. RESULTS: A total of 898 patients with ICC were included in this study. Of them, 199 (22.2%) were NAFLD-ICC, and 699 (77.8%) were HBV-ICC. Multivariate analysis showed that CA19-9 ≥ 37 U/mL, microvascular invasion, tumor size > 5 cm, multiple tumors, and lymph node (LN) metastasis were independent risk factors for early recurrence (ER) in ICC patients. After a 1:1 PSM, NAFLD-ICC has worse 5-year overall survival (OS) (24.0% vs. 48.9%), 5-year recurrence (80.9% vs. 55.0%), and ER (58.5% vs. 30.0%) than that of HBV-ICC (all P < 0.01). Multivariable analysis showed NAFLD was an independent risk factor for OS (hazard ratio [HR] 2.26, 95% CI 1.63-3.13, P < 0.001), tumor recurrence (HR 2.24, 95%CI 1.61-3.10, P < 0.001) and ER (HR 2.23, 95%CI 1.60-3.09, P < 0.001) in patients with ICC after PH. The sensitivity analysis indicated that NAFLD-ICC patients were more likely to experience ER. CONCLUSION: Compared with HBV-ICC, NAFLD-ICC has a worse prognosis and was more likely to relapse early. More frequent surveillance should be considered.

Effect of different PD-1 inhibitor combination therapies for unresectable intrahepatic cholangiocarcinoma.

BACKGROUND: Immune checkpoint inhibitor (ICI) combination therapy offers a new option for treatment of unresectable intrahepatic cholangiocarcinoma (uICC). AIM: To compare the effect of different anti-PD-1 combination therapies as the first-line treatments for uICC. METHODS: This study included 318 patients who received chemotherapy alone (Chemo), anti-PD-1 plus chemotherapy (ICI-chemo), anti-PD-1 plus targeted therapy (ICI-target) or anti-PD-1 plus targeted therapy and chemotherapy (ICI-target-chemo) as first line for uICC from 22 centres in China. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR) and safety. RESULTS: Patients with ICI-chemo (median PFS [mPFS], 6.3 months; HR: 0.61, 95% CI: 0.42-0.88; p = 0.008; median OS [mOS], 10.7 months; HR: 0.61, 95% CI: 0.39-0.94; p = 0.026), ICI-target (7.2 months; HR: 0.54, 95% CI: 0.36-0.80; p = 0.002; 15.8 months; HR: 0.54, 95% CI: 0.35-0.84; p = 0.006) or ICI-target-chemo (6.9 months; HR: 0.65, 95% CI: 0.47-0.90; p = 0.009; 14.4 months; HR: 0.47, 95% CI: 0.31-0.70; p < 0.001) achieved better clinical outcomes than those with Chemo (3.8 months; 9.3 months). ICI-target was not inferior to ICI-chemo in survival outcomes (HR for PFS: 0.88, 95% CI: 0.55-1.42; p = 0.614; HR for OS: 0.89, 95% CI: 0.51-1.55; p = 0.680). ICI-target-chemo yielded similar prognoses as ICI-chemo (HR for PFS: 1.07, 95% CI: 0.70-1.62; p = 0.764; HR for OS: 0.77, 95% CI: 0.45-1.31; p = 0.328) and ICI-target (HR for PFS: 1.20, 95% CI: 0.77-1.88; p = 0.413; HR for OS: 0.86, 95% CI: 0.51-1.47; p = 0.583) but resulted in more adverse events (p < 0.001; p = 0.010). Multivariable and propensity score analyses supported these findings. CONCLUSIONS: Among patients with uICC, ICI-chemo or ICI-target provided more survival benefits than Chemo while achieving comparable prognoses and fewer adverse events than ICI-target-chemo.

Dynamic Dirichlet process mixture model for identifying voting coalitions in the United Nations General Assembly human rights roll call votes.

Scholars have been interested in the politicization of humans rights within the United Nations for some time. However, previous research typically looks at simple associations between voting coalitions and observable variables, such as geographic location or membership in international organizations. Our study is the first attempt at estimating the latent coalition structure based on the voting data. We propose a Bayesian Dynamic Dirichlet Process Mixture (DDPM) model to identify voting coalitions based on roll call vote data across multiple time periods. We also propose post-processing methods for analyzing the outputs of the DDPM model. We apply these methods to the United Nations General Assembly (UNGA) human rights roll call vote data from 1992 to 2017. We identify human rights voting coalitions in the UNGA after the Cold War, and polarizing resolutions that divide countries into different coalitions.

A multidimensional pairwise comparison model for heterogeneous perceptions with an application to modelling the perceived truthfulness of public statements on COVID-19.

Pairwise comparison models are an important type of latent attribute measurement model with broad applications in the social and behavioural sciences. Current pairwise comparison models are typically unidimensional. The existing multidimensional pairwise comparison models tend to be difficult to interpret and they are unable to identify groups of raters that share the same rater-specific parameters. To fill this gap, we propose a new multidimensional pairwise comparison model with enhanced interpretability which explicitly models how object attributes on different dimensions are differentially perceived by raters. Moreover, we add a Dirichlet process prior on rater-specific parameters which allows us to flexibly cluster raters into groups with similar perceptual orientations. We conduct simulation studies to show that the new model is able to recover the true latent variable values from the observed binary choice data. We use the new model to analyse original survey data regarding the perceived truthfulness of statements on COVID-19 collected in the summer of 2020. By leveraging the strengths of the new model, we find that the partisanship of the speaker and the partisanship of the respondent account for the majority of the variation in perceived truthfulness, with statements made by co-partisans being viewed as more truthful.

Serum prealbumin as a predictor of adverse outcomes in patients with heart failure: a systematic review and meta-analysis.

Aim: To evaluate the association of serum prealbumin level with adverse outcomes in heart failure (HF) patients by conducting a meta-analysis. Methods: A comprehensive literature search was conducted in both international and Chinese databases to identify the cohort studies that reported the association of serum prealbumin level with all-cause mortality and composite endpoints of death/heart failure readmission in HF patients. Results: Eight studies involving 2439 patients were eligible. Low prealbumin level was associated with higher risk of all-cause mortality (adjusted risk ratio [RR] 1.89; 95% CI: 1.35-2.65) and composite endpoints (adjusted RR 3.08; 95% CI: 1.43-6.64). Conclusions: Low serum prealbumin level may be an independent predictor of all-cause mortality/heart failure readmission in HF patients.

A Novel Nomogram for Predicting Postoperative Liver Failure After Major Hepatectomy for Hepatocellular Carcinoma.

Background: Post-hepatectomy liver failure (PHLF) is the most common cause of mortality after major hepatectomy in hepatocellular carcinoma (HCC) patients. We aim to develop a nomogram to preoperatively predict grade B/C PHLF defined by the International Study Group on Liver Surgery Grading (ISGLS) in HCC patients undergoing major hepatectomy. Study Design: The consecutive HCC patients who underwent major hepatectomy at the Eastern Hepatobiliary Surgery Hospital between 2008 and 2013 served as a training cohort to develop a preoperative nomogram, and patients from 2 other hospitals comprised an external validation cohort. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to identify preoperative predictors of grade B/C PHLF. Multivariable logistic regression was utilized to establish a nomogram model. Internal and external validations were used to verify the performance of the nomogram. The accuracy of the nomogram was also compared with the conventional scoring models, including MELD and ALBI score. Results: A total of 880 patients who underwent major hepatectomy (668 in the training cohort and 192 in the validation cohort) were enrolled in this study. The independent risk factors of grade B/C PHLF were age, gender, prothrombin time, total bilirubin, and CSPH, which were incorporated into the nomogram. Good prediction discrimination was achieved in the training (AUROC: 0.73) and validation (AUROC: 0.72) cohorts. The calibration curve also showed good agreement in both training and validation cohorts. The nomogram has a better performance than MELD and ALBI score models. Conclusion: The proposed nomogram showed more accurate ability to individually predict grade B/C PHLF after major hepatectomy in HCC patients than MELD and ALBI scores.

Comparison of Metallization Schemes on Glass Dielectrics for X-Band Glass Antennas and Energy Harvesting.

We prepare and test four types of glass antennas for X-band applications and energy harvesting. These antennas are made of three different glass metallization schemes, including conductive copper foil (CCF), conductive silver paste (CSP) and indium tin oxide (ITO) thin film. Compared with conventional microstrip patch antennas, the dielectric substrate materials of these designs are replaced with silicon-boron glass (εr = 6, tangent δ = 0.002). The antenna with CCF as a radiator and ground plane (case one) is compared with the antenna with ITO replacing the radiator (case two) and ground plane (case three), respectively, and the glass antenna made of CSP (case four) is also presented. In this paper, these four types of glass antennas are measured and analyzed, and a comparison of the fabrication process and performance of these antennas is demonstrated. This study could contribute to the development of human-machine interactivity (HMI) systems with glass dielectric substrates.

Anti-Vibrio dibutyl phthalate from marine-derived Streptomyces sp. S073.

Marine Streptomyces S073 was previously shown to have strong anti-Vibrio activity, and its antibacterial mechanism was proposed to be associated with siderophore-mediated iron competition and other antagonistic agents. In this study, anti-Vibrio compounds produced by S073 were isolated by bioassay-guided fractionation using column chromatography and HPLC, and the target compound in the most active fraction was identified as dibutyl phthalate (DBP) by various spectroscopic analyses, including EI-MS, 1H NMR and 13C NMR. The DBP-producing capacity of S073 was 2.39 mg/L in ISP1 culture media. Pure DBP was demonstrated to have strong inhibitory activity on Vibiro parahaemolyticus growth with an MIC of 31.25 mg/L. When standard DBP was supplemented into the S073 fermentation broth in a gradient method, an additive inhibitory effect on V. parahaemolyticus was observed, indicating the important role of DBP in driving anti-Vibrio activity in S073 metabolites pool. A synergistic additive effect between DBP and florfenicol was observed in the Vibrio inhibition. These results indicate that, to achieve Vibrio-inhibition, S073 exerted multifaceted strategies, which included DBP-mediated antagonism and siderophore-governed iron competition. The application potential of S073 as an aquaculture probiotic was evaluated, and the safety risks associated with the endocrine disruptor attributes of DBP were discussed.

The Bet-Hedging Strategies for Seedling Emergence of Calligonum mongolicum to Adapt to the Extreme Desert Environments in Northwestern China.

Calligonum mongolicum is a dominant native perennial shrub on sand dunes in arid deserts of northwestern China, and is therefore widely used in sand dune stabilization in these regions. However, it remains largely unknown how seedling emergence of C. mongolicum has adapted to unpredictable sand movement and extreme drought. Here we examined effects of seed burial depth, light intensity, and seed age on seedling emergence, and considered seed germination and seedling emergence strategies for the shrub's adaption to the desert environment. In our pot experiment, the optimum seeding depth for emergence of C. mongolicum was 2 cm, indicating that for germination and seedling emergence only moderate sand burial is required. Light intensity at the surface soil (0 cm) was important for seedling emergence, while there was no significant difference between 50 and 20% light flux density, at burial depths of 1 and 2 cm, indicating that C. mongolicum seeds had adapted to sand burial, while not exposure from sand erosion. We also found C. mongolicum seedlings emerged in spring and in late summer to early autumn. Meanwhile, seedling emergence percentage for 3-year-old seeds was similar to that of 1-year-old seeds, which meant that C. mongolicum seeds were well preserved under normal sand dune conditions, thus were capable of developing a persistent, but shallow soil seed-bank. These results indicated that germination and seedling emergence take a bet-hedging strategies to adapt to variable desert environments. Our study confirmed that C. mongolicum desert shrubs combine strategies in its adaption to arid and variable sand environments.

Factors influencing the natural regeneration of the pioneering shrub Calligonum mongolicum in sand dune stabilization plantations in arid deserts of northwest China.

Calligonum mongolicum is a successful pioneer shrub to combat desertification, which is widely used for vegetation restoration in the desert regions of northwest China. In order to reveal the limitations to natural regeneration of C. mongolicum by asexual and sexual reproduction, following the process of sand dune stabilization, we assessed clonal shoots, seedling emergence, soil seed bank density, and soil physical characteristics in mobile and stabilized sand dunes. Controlled field and pot experiments were also conducted to assess germination and seedling emergence in different dune soil types and seed burial depths. The population density of mature C. mongolicum was significantly different after sand dune stabilization. Juvenile density of C. mongolicm was much lower in stabilized sand dunes than mobile sand dune. There was no significant difference in soil seed bank density at three soil depths between mobile and stabilized sand dunes, while the emergence of seedlings in stabilized dunes was much lower than emergence in mobile dunes. There was no clonal propagation found in stabilized dunes, and very few C. mongolicum seedlings were established on stabilized sand dunes. Soil clay and silt content, air-filled porosity, and soil surface compaction were significantly changed from mobile sand dune to stabilized dunes. Seedling emergence of C. mongolicm was highly dependent on soil physical condition. These results indicated that changes in soil physical condition limited clonal propagation and seedling emergence of C. mongolicum in stabilized sand dunes. Seed bank density was not a limiting factor; however, poor seedling establishment limited C. mongolicum's further natural regeneration in stabilized sand dunes. Therefore, clonal propagation may be the most important mode for population expansion in mobile sand dunes. As a pioneer species C. mongolicum is well adapted to propagate in mobile sand dune conditions, it appears unlikely to survive naturally in stabilized sand dune plantations.

Interaction between peroxisome proliferator-activated receptor gamma and smoking on cardiovascular disease.

The aim of this study was to investigate the association between peroxisome proliferator-activator receptor-γ (PPAR-γ) genotype and additional gene-smoking interaction on cardiovascular disease (CVD) based on a Chinese population. A total of 1248 subjects (613 men, 635 women), with a mean age of 55.5±11.8 years old, were selected, including 620 CVD patients and 628 normal controls. Logistic regression was performed to investigate association between single nucleotide polymorphism (SNP) and CVD. Generalized MDR (GMDR) was used to analysis the gene-environment interaction, cross-validation consistency, the testing balanced accuracy, and the sign test, to assess each selected interaction were calculated. The carriers of homozygous mutant of two SNP revealed increased CVD risk than those with wild-type homozygotes, OR (95% CI) were 1.31 (1.16-1.95) and 1.68 (1.29-2.06), respectively. GMDR analysis for one- to three-locus models indicated that there was a significant two-locus model (p=0.0107) involving rs1805192 and smoking, indicating a potential gene-gene interaction between rs1805192 and smoking. Overall, the two- locus models had a cross-validation consistency of 10 of 10, and had the testing accuracy of 62.17%. We found that smokers with Pro/Ala or Ala/Ala genotype have highest CVD risk, compared to non-smokers with Pro/Pro genotype, OR (95% CI) was 3.46 (1.31-3.42), after covariates adjustment. We found a significant association between genotypes of variants in rs10865710 and rs1805192 with increased CVD risk and a potential gene-gene interaction between rs1805192 and smoking.