MicroRNA expression profile analysis in sperm reveals hsa-mir-191 as an auspicious omen of in vitro fertilization.

BACKGROUND: MicroRNAs (miRNAs) are a class of noncoding small RNAs that play important roles in many physiological processes by regulating gene expression. Previous studies have shown that the expression levels of total miRNAs increase during mouse embryonic development, and some miRNAs control the regulatory network in development progression. However, few studies have focused on the effects of miRNAs on early human embryonic development. The relationship between miRNAs and early human embryogenesis is still unknown. RESULTS: In this study, RNA-seq data collected from sperm samples from 102 patients with a normal sperm index but treated with assisted reproductive technology (ART) were analyzed for the relationships between differentially expressed small RNAs and the fertilization rate (FR), blastocyst rate and high-quality embryo rate (HQER). The sperm samples with high hsa-mir-191 expression had a higher FR, effective embryo rate (EER) and HQER. hsa-mir-191 was used as a single indicator to predict the HQER. The receiver operating characteristic (ROC) curve had an area under the ROC curve (AUC) of 0.686. We also found that hsa-mir-191 expression is correlated with an abnormal sperm rate (cor = 0.29, p < 0.01). We also evaluated the relationship between hsa-mir-34c and early human embryo development in these 102 sperm samples and obtained negative results. CONCLUSIONS: These findings suggest that high hsa-mir-191-5p expression in sperm is associated with early human embryonic quality and that hsa-mir-191-5p could be used as a potential marker to screen high-quality sperm to improve the success rates of in vitro fertilization (IVF).

Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model.

Understanding the effects of thinning on forest productivity under climate change is vital to adaptive forest management. In the present study, the 3-PGmix model was applied to simulate the thinning effects on productivity of Larix olgensis plantations under climate change using 164 sample plots collected from the 6th, 7th and 8th National Forest Inventories in Jilin Province, northeast China. Climate scenarios of RCP 4.5 and RCP 8.5 were adopted from 2011 to 2100 with corresponding reference years (1981-2010). We simulated four cutting intensities: no-thinning, NT; low intensity thinning with 10% stem removal, LT; moderate thinning with 20% stem removal, MT and heavy thinning with 30% stem removal, HT for three times with 5- and 10-year thinning intervals. The results indicated that the mean net primary productivity (NPP) during the simulated 90 years was increased under RCP 4.5 and RCP 8.5. The LT and MT had positive but HT had negative effects on the mean NPP for the same climate scenario. Increased thinning intensity facilitated the positive effects of climate change on NPP but without a significant interaction effect. During the simulation, LT had the highest NPP value and HT had the biggest NPP increase under future climate change. We also discussed the management of larch plantations under climate change and advocated low intensity thinning with 10-year thinning interval to gain maximum NPP for mitigating climate change.

Effects of productivity on biodiversity in forest ecosystems across the United States and China.

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem-wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground-sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump-shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity-biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.

Spatiotemporal patterns and drivers of stem methane flux from two poplar forests with different soil textures.

In forest ecosystems, the majority of methane (CH4) research focuses on soils, whereas tree stem CH4 flux and driving factors remain poorly understood. We measured the in situ stem CH4 flux using the static chamber-gas chromatography method at different heights in two poplar (Populus spp.) forests with separate soil textures. We evaluated the relationship between stem CH4 fluxes and environmental factors with linear mixed models and estimated the tree CH4 emission rate at the stand level. Our results showed that poplar stems were a net source of atmospheric CH4. The mean stem CH4 emission rates were 97.51 ± 6.21 µg·m-2·h-1 in Sihong and 67.04 ± 5.64 µg·m-2·h-1 in Dongtai. The stem CH4 emission rate in Sihong with clay loam soils was significantly higher (P < 0.001) than that in Dongtai with sandy loam soils. The stem CH4 emission rate also showed a seasonal variation, minimum in winter and maximum in summer. The stem CH4 emission rate generally decreased with increasing sampling height. Although the differences in CH4 emission rates between stem heights were significant in the annual averages, these differences were driven by differences observed in the summer. Stem CH4 emission rates were significantly and positively correlated with air temperature (P < 0.001), relative humidity (P < 0.001), soil water content (P < 0.001) and soil CH4 flux (P < 0.001). At these sites, the soil emitted CH4 to the atmosphere in summer (mainly from June to September) but absorbed CH4 from the atmosphere during the other season. At the stand level, tree CH4 emissions accounted for 2-35.4% of soil CH4 uptake. Overall, tree stem CH4 efflux could be an important component of the forest CH4 budget. Therefore, it is necessary to conduct more in situ monitoring of stem CH4 flux to accurately estimate the CH4 budget in the future.

Mass-ratio and complementarity effects simultaneously drive aboveground biomass in temperate Quercus forests through stand structure.

Forests play a key role in regulating the global carbon cycle, a substantial portion of which is stored in aboveground biomass (AGB). It is well understood that biodiversity can increase the biomass through complementarity and mass-ratio effects, and the contribution of environmental factors and stand structure attributes to AGB was also observed. However, the relative influence of these factors in determining the AGB of Quercus forests remains poorly understood. Using a large dataset retrieved from 523 permanent forest inventory plots across Northeast China, we examined the effects of integrated multiple tree species diversity components (i.e., species richness, functional, and phylogenetic diversity), functional traits composition, environmental factors (climate and soil), stand age, and structure attributes (stand density, tree size diversity) on AGB based on structural equation models. We found that species richness and phylogenetic diversity both were not correlated with AGB. However, functional diversity positively affected AGB via an indirect effect in line with the complementarity effect. Moreover, the community-weighted mean of specific leaf area and height increased AGB directly and indirectly, respectively; demonstrating the mass-ratio effect. Furthermore, stand age, density, and tree size diversity were more important modulators of AGB than biodiversity. Our study highlights that biodiversity-AGB interaction is dependent on the regulation of stand structure that can be even more important for maintaining high biomass than biodiversity in temperate Quercus forests.

Biodiversity increased both productivity and its spatial stability in temperate forests in northeastern China.

Although the relationship between biodiversity and ecosystem functioning has been extensively studied, it remains unclear if the relationships of biodiversity with productivity and its spatial stability vary along productivity gradients in natural ecosystems. Based on a large dataset from 2324 permanent forest inventory plots across northeastern China, we examined the intensity of species richness (SR) and tree size diversity (Hd) effects on aboveground wood productivity (AWP) and its spatial stability among different productivity levels. Structural equation modeling was applied, integrating abiotic (climate and soil) and biotic (stand density) factors. Our results demonstrated that both SR and Hd positively affected AWP and its spatial stability, and the intensity of these positive effects decreased with increasing productivity. At low productivity levels, SR and Hd increased spatial stability by reducing spatial variability and increasing mean AWP. At high productivity levels, stability increased only through mean AWP increase. Moreover, temperature and stand density affected the AWP directly and indirectly via biodiversity, and the strength and direction of these effects varied among different productivity levels. We concluded that biodiversity could simultaneously enhance productivity and its spatial stability in temperate forests, and that the effect intensity was uniform along productivity gradients, which provided a new perspective on relationships within biodiversity-ecosystem functioning.

Spatial variability in the amount of forest litter at the local scale in northeastern China: Kriging and cokriging approaches to interpolation.

Litter is essential to promote nutrient cycling and maintain the sustainability of forest resources. However, its variability has not been sufficiently studied at the local scale. The prediction of litter amount using ordinary cokriging with Pearson correlation analysis (COKP) and ordinary cokriging with principal component analysis (COKPCA) was compared with that using ordinary kriging (OK) based on cross-validation at the local scale of a 1-ha plot over natural spruce-fir mixed forest in Jilin Province, China. Litter samples in semidecomposed (F) and complete decomposed (H) horizons were collected using an equidistant grid point sampling of 10 m × 10 m. Pearson correlation analysis and principal component analysis (PCA) were used to confirm auxiliary variables. The results showed that the amount of litter was 19.65 t/ha in the F horizon and 10.37 t/ha in the H horizon. The spatial structure variance ratio in the H horizon was smaller than that in the F horizon, indicative of its stronger spatial autocorrelation. Spatial distributions of litter amount in both horizons exhibited a patchy and heterogeneous pattern. Of the selected stand characteristics and litter properties, litter moisture content indicated the strongest relationship with litter amount. Cross-validation revealed that COKPCA using the comprehensive score as an auxiliary variable produced the most accurate map. The average standard error and root-mean-square error between the predicted and measured values were always smaller, the mean error and mean standardized error were much closer to 0, and the root-mean-square standardized error was closer to 1 than COKP using litter moisture and OK. Therefore, a clear advantage of cokriging based on principal component analysis was observed and COKPCA was found to be a very useful approach for further interpolation prediction.

Genetic and pathogenic characteristics of newly emerging avian reovirus from infected chickens with clinical arthritis in China.

In recent years, emerging avian reovirus (ARV) strains causing viral arthritis have become a challenge to the worldwide chicken industry, and were responsible for significant economic losses. In this study, we characterized emerging variant ARV strains and examined their genetic relationship and pathogenicity variation with reference strains. A total of 18 emerging variant ARV strains were isolated from tendon and capsular synovial fluid of broiler chickens with clinical cases of arthritis/tenosynovitis at commercial farms in China. Comparative analysis based on σC sequence showed that 4/18 isolates were in the same cluster (Cluster 1) as vaccine strains (S1133), whereas 14 of 18 isolates were in Clusters 2, 3, and 6. The field isolates shared a rather low identity (38.1 to 81.9%) with S1133 in Cluster 1, especially for those from Cluster 6 (38.1 to 67.2%). A higher ARV isolation rate was observed in chicken embryos (47/61) compared to cell culture (37/61) through PCR with a detection primer. A total of 3 isolates were selected to infect specific-pathogen-free (SPF) chickens, showing that the tested isolates, especially that from Cluster 6, displayed greater pathogenicity than S1133 strain, characterized by higher incidence. These findings suggest that the virulence of Chinese ARVs has been increasing rapidly in recent years, and the vaccine need to be updated correspondingly.

Feature selection and classification of urinary mRNA microarray data by iterative random forest to diagnose renal fibrosis: a two-stage study.

Renal fibrosis is a common pathological pathway of progressive chronic kidney disease (CKD). However, kidney function parameters are suboptimal for detecting early fibrosis, and therefore, novel biomarkers are urgently needed. We designed a 2-stage study and constructed a targeted microarray to detect urinary mRNAs of CKD patients with renal biopsy and healthy participants. We analysed the microarray data by an iterative random forest method to select candidate biomarkers and produce a more accurate classifier of renal fibrosis. Seventy-six and 49 participants were enrolled into stage I and stage II studies, respectively. By the iterative random forest method, we identified a four-mRNA signature in urinary sediment, including TGFß1, MMP9, TIMP2, and vimentin, as important features of tubulointerstitial fibrosis (TIF). All four mRNAs significantly correlated with TIF scores and discriminated TIF with high sensitivity, which was further validated in the stage-II study. The combined classifiers showed excellent sensitivity and outperformed serum creatinine and estimated glomerular filtration rate measurements in diagnosing TIF. Another four mRNAs significantly correlated with glomerulosclerosis. These findings showed that urinary mRNAs can serve as sensitive biomarkers of renal fibrosis, and the random forest classifier containing urinary mRNAs showed favourable performance in diagnosing early renal fibrosis.

[Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model].

Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.

Positive biodiversity-productivity relationship predominant in global forests.

The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone-US$166 billion to 490 billion per year according to our estimation-is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.

Differential gene expressions of the MAPK signaling pathway in enterovirus 71-infected rhabdomyosarcoma cells.

BACKGROUND: Mitogen-activated protein kinase (MAPK) signaling pathway plays an important role in response to viral infection. The aim of this study was to explore the function and mechanism of MAPK signaling pathway in enterovirus 71 (EV71) infection of human rhabdomyosarcoma (RD) cells. METHODS: Apoptosis of RD cells was observed using annexin V-FITC/PI binding assay under a fluorescence microscope. Cellular RNA was extracted and transcribed to cDNA. The expressions of 56 genes of MAPK signaling pathway in EV71-infected RD cells at 8h and 20h after infection were analyzed by PCR array. The levels of IL-2, IL-4, IL-10, and TNF-α in the supernatant of RD cells infected with EV71 at different time points were measured by ELISA. RESULTS: The viability of RD cells decreased obviously within 48h after EV71 infection. Compared with the control group, EV71 infection resulted in the significantly enhanced releases of IL-2, IL-4, IL-10 and TNF-α from infected RD cells (p<0.05). At 8h after infection, the expressions of c-Jun, c-Fos, IFN-ß, MEKK1, MLK3 and NIK genes in EV71-infected RD cells were up-regulated by 2.08-6.12-fold, whereas other 19 genes (e.g. AKT1, AKT2, E2F1, IKK and NF-κB1) exhibited down-regulation. However, at 20h after infection, those MAPK signaling molecules including MEKK1, ASK1, MLK2, MLK3, NIK, MEK1, MEK2, MEK4, MEK7, ERK1, JNK1 and JNK2 were up-regulated. In addition, the expressions of AKT2, ELK1, c-Jun, c-Fos, NF-κB p65, PI3K and STAT1 were also increased. CONCLUSION: EV71 infection induces the differential gene expressions of MAPK signaling pathway such as ERK, JNK and PI3K/AKT in RD cells, which may be associated with the secretions of inflammatory cytokines and host cell apoptosis.

A pilot trial assessing urinary gene expression profiling with an mRNA array for diabetic nephropathy.

BACKGROUND: The initiation and progression of diabetic nephropathy (DN) is complex. Quantification of mRNA expression in urinary sediment has emerged as a novel strategy for studying renal diseases. Considering the numerous molecules involved in DN development, a high-throughput platform with parallel detection of multiple mRNAs is needed. In this study, we constructed a self-assembling mRNA array to analyze urinary mRNAs in DN patients with aims to reveal its potential in searching novel biomarkers. METHODS: mRNA array containing 88 genes were fabricated and its performance was evaluated. A pilot study with 9 subjects including 6 DN patients and 3 normal controls were studied with the array. DN patients were assigned into two groups according to their estimate glomerular rate (eGFR): DNI group (eGFR>60 ml/min/1.73 m(2), n = 3) and DNII group (eGFR<60 ml/min/1.73 m(2), n = 3). Urinary cell pellet was collected from each study participant. Relative abundance of these target mRNAs from urinary pellet was quantified with the array. RESULTS: The array we fabricated displayed high sensitivity and specificity. Moreover, the Cts of Positive PCR Controls in our experiments were 24±0.5 which indicated high repeatability of the array. A total of 29 mRNAs were significantly increased in DN patients compared with controls (p<0.05). Among these genes, α-actinin4, CDH2, ACE, FAT1, synaptopodin, COL4α, twist, NOTCH3 mRNA expression were 15-fold higher than those in normal controls. In contrast, urinary TIMP-1 mRNA was significantly decreased in DN patients (p<0.05). It was shown that CTGF, MCP-1, PAI-1, ACE, CDH1, CDH2 mRNA varied significantly among the 3 study groups, and their mRNA levels increased with DN progression (p<0.05). CONCLUSION: Our pilot study demonstrated that mRNA array might serve as a high-throughput and sensitive tool for detecting mRNA expression in urinary sediment. Thus, this primary study indicated that mRNA array probably could be a useful tool for searching new biomarkers for DN.

Differential gene expressions of the MAPK signaling pathway in enterovirus 71-infected rhabdomyosarcoma cells

BACKGROUND: Mitogen-activated protein kinase (MAPK) signaling pathway plays an important role in response to viral infection. The aim of this study was to explore the function and mechanism of MAPK signaling pathway in enterovirus 71 (EV71) infection of human rhabdomyosarcoma (RD) cells. METHODS: Apoptosis of RD cells was observed using annexin V-FITC/PI binding assay under a fluorescence microscope. Cellular RNA was extracted and transcribed to cDNA. The expressions of 56 genes of MAPK signaling pathway in EV71-infected RD cells at 8 h and 20 h after infection were analyzed by PCR array. The levels of IL-2, IL-4, IL-10, and TNF-α in the supernatant of RD cells infected with EV71 at different time points were measured by ELISA. RESULTS: The viability of RD cells decreased obviously within 48 h after EV71 infection. Compared with the control group, EV71 infection resulted in the significantly enhanced releases of IL-2, IL-4, IL-10 and TNF-α from infected RD cells (p < 0.05). At 8 h after infection, the expressions of c-Jun, c-Fos, IFN-i, MEKK1, MLK3 and NIK genes in EV71-infected RD cells were up-regulated by 2.08-6.12-fold, whereas other 19 genes (e.g. AKT1, AKT2, E2F1, IKK and NF-κB1) exhibited down-regulation. However, at 20 h after infection, those MAPK signaling molecules including MEKK1, ASK1, MLK2, MLK3, NIK, MEK1, MEK2, MEK4, MEK7, ERK1, JNK1 and JNK2 were up-regulated. In addition, the expressions of AKT2, ELK1, c-Jun, c-Fos, NF-κB p65, PI3K and STAT1 were also increased. CONCLUSION: EV71 infection induces the differential gene expressions of MAPK signaling pathway such as ERK, JNK and PI3K/AKT in RD cells, which may be associated with the secretions of inflammatory cytokines and host cell apoptosis.