Neonatal rhesus monkey is a potential animal model for studying pathogenesis of EV71 infection

AbstractData from limited autopsies of human patients demonstrate that pathological changes in EV71-infected fatal cases are principally characterized by clear inflammatory lesions in different parts of the CNS; nearly identical changes were found in murine, cynomolgus and rhesus monkey studies which provide evidence of using animal models to investigate the mechanisms of EV71 pathogenesis. Our work uses neonatal rhesus monkeys to investigate a possible model of EV71 pathogenesis and concludes that this model could be applied to provide objective indicators which include clinical manifestations, virus dynamic distribution and pathological changes for observation and evaluation in interpreting the complete process of EV71 infection. This induced systemic infection and other collected indicators in neonatal monkeys could be repeated; the transmission appears to involve infecting new monkeys by contact with feces of infected animals. All data presented suggest that the neonatal rhesus monkey model could shed light on EV71 infection process and pathogenesis

Serum MicroRNA Expression Profile Distinguishes Enterovirus 71 and Coxsackievirus 16 Infections in Patients with Hand-Foot-and-Mouth Disease

Altered circulating microRNA (miRNA) profiles have been noted in patients with microbial infections. We compared host serum miRNA levels in patients with hand-foot-and-mouth disease (HFMD) caused by enterovirus 71 (EV71) and coxsackievirus 16 (CVA16) as well as in other microbial infections and in healthy individuals. Among 664 different miRNAs analyzed using a miRNA array, 102 were up-regulated and 26 were down-regulated in sera of patients with enteroviral infections. Expression levels of ten candidate miRNAs were further evaluated by quantitative real-time PCR assays. A receiver operating characteristic (ROC) curve analysis revealed that six miRNAs (miR-148a, miR-143, miR-324-3p, miR-628-3p, miR-140-5p, and miR-362-3p) were able to discriminate patients with enterovirus infections from healthy controls with area under curve (AUC) values ranged from 0.828 to 0.934. The combined six miRNA using multiple logistic regression analysis provided not only a sensitivity of 97.1% and a specificity of 92.7% but also a unique profile that differentiated enterovirial infections from other microbial infections. Expression levels of five miRNAs (miR-148a, miR-143, miR-324-3p, miR-545, and miR-140-5p) were significantly increased in patients with CVA16 versus those with EV71 (p<0.05). Combination of miR-545, miR-324-3p, and miR-143 possessed a moderate ability to discrimination between CVA16 and EV71 with an AUC value of 0.761. These data indicate that sera from patients with different subtypes of enteroviral infection express unique miRNA profiles. Serum miRNA expression profiles may provide supplemental biomarkers for diagnosing and subtyping enteroviral HFMD infections

Distribution of Natural and Planted Forests in the Yanhe River Catchment: Have We Planted Trees on the Right Sites?

Planting trees on the right sites is the first principle in silviculture, but it is not easy to apply at a large scale, especially in complex terrain such as mountainous regions. In hilly and gully landscapes of China’s Loess Plateau, the environmental heterogeneity is so great that it is very difficult to choose the right sites for planting trees. The long history of vegetation destruction makes it difficult to have a reference for restoration programs. In this paper, we compared the distribution of actual forest to an existing potential natural vegetation (PNV) map to see the mismatch with the sites. The differences in environmental conditions between natural forest and mismatched planted forest were investigated. The results showed that significant differences existed in the environmental conditions between them. The mean rainfall and temperature for natural forest were 512.20 ± 11.42 mm and 8.23 ± 0.55 °C, respectively, but 497.96 ± 14.92 mm and 8.72 ± 0.97 °C, respectively, for the mismatched planted forest. Evaporation was not only different in range (816–953 mm vs. 816–1023 mm), but also significantly different in mean values (888.31 ± 14.35 mm natural forest vs. 895.90 ± 30.55 mm planted forest). The slope gradient of natural forest and mismatched planted forest was also significantly different (22.66° ± 8.82° vs. 24.24° ± 9.86°). The results identified that 58% of the existing forest in the Yanhe River catchment is planted forest that grows on steeper slopes, receives lower rainfall, has higher temperatures and higher evaporation. The average soil water content for sites with planted forest was found to be 5.98% ± 0.32% compared to 7.52% ± 0.33% for natural forest. We conclude that the main cause of dwarfed, slender, low productive and sparse planted forest in the Loess Plateau is planting trees at unsuitable sites. Our results highlight the importance of matching sites with the best potential vegetation types. Instead of using water harvesting techniques, we suggest that more focus should be placed on understanding environmental heterogeneity and its capacity to support particular vegetation types. This study is instructive for vegetation restoration planning and existing planted forest management in the future

Estimating the CSLE Biological Conservation Measures’ B-Factor Using Google Earth’s Engine

The biological conservation measures factor (B) in the Chinese Soil loss Equation (CSLE) model is one of the main components in evaluating soil erosion, and the accurate calculation of the B-factor at the regional scale is fundamental in predicting regional soil erosion and dynamic changes. In this study, we developed an optimal computational procedure for estimating and mapping the B-factor in the Google Earth Engine (GEE) cloud computing environment using multiple data sources through data suitability assessment and image fusion. Taking the Yanhe River Basin in the Loess Plateau of China as an example, we evaluated the availability of daily precipitation data (CHIRPS, ERA5, and PERSIANN-CDR data) against the data at national meteorological stations. We estimated the B-factor from Sentinel-2 data and proposed a new method, namely the trend migration method, to patch the missing values in Sentinel-2 data using three other remote sensing data (MOD09GA, Landsat 7, and Landsat 8). We then calculated and mapped the B-factor in the Yanhe River Basin based on rainfall erosivity, vegetation coverage, and land use types. The results show that the ERA5 precipitation dataset outperforms the CHIRPS and PERSIANN-CDR data in estimating rainfall and rainfall erosivity, and it can be utilized as an alternative data source for meteorological stations in soil erosion modeling. Compared to the harmonic analysis of time series (HANTS), the trend migration method proposed in this study is more suitable for patching the missing parts of Sentinel-2 data. The restored high-resolution Sentinel-2 data fit nicely with the 10 m resolution land use data, enhancing the B-factor calculation accuracy at local and region scales. The B-factor computation procedure developed in this study is applicable to various river basin and regional scales for soil erosion monitoring

Leaf Trait Variation with Environmental Factors at Different Spatial Scales: A Multilevel Analysis Across a Forest-Steppe Transition

In mountain areas, the distribution of plant communities is affected by both regional and microhabitat conditions. The degree to which these different spatial factors contribute to plant communities is not well understood, because few studies have used a uniform sampling methodology to measure trait variation across the range of ecological scales. In this study, a stratified sampling method was used to study community weighted leaf traits and environment factors at different spatial (transect and plot) scales. We measured 6 leaf traits (specific leaf area, leaf tissue density, leaf thickness, leaf carbon, nitrogen and phosphorus content) in 258 communities from 57 sites in 9 transects nested within 3 vegetation zones. These communities are located in the loess hilly and gully area of the Yanhe river watershed. We coupled climatic factors at the transect scale with topographic and edaphic factors at the plot scale using multilevel regression modeling to analyze the trait variation associated with spatial scales. At the transect scale, the mean annual rainfall showed a highly significant positive effect on the leaf nitrogen concentration (LNC) (p &lt; 0.01), while it had a highly significant negative effect on leaf thickness (LT) and leaf tissue density (LTD) (p &lt; 0.001) and a significant negative effect on leaf carbon concentration (LCC) (p &lt; 0.05), explaining 10.91%, 36.08%, 57.25% and 66.01% of LTD, LT, LCC and LNC variation at transect scale respectively. At a plot scale, the slope aspect showed a highly significant positive effect on specific leaf area (SLA) and LNC but a highly significant negative effect on LT and LTD. The soil water content had a significant negative effect on LT (p &lt; 0.05) and LTD (p &lt; 0.001) while soil organic matter showed a positive effect on SLA (p &lt; 0.001) and LNC (p &lt; 0.01). Totally, plot scale variables explained 7.28%, 43.60%, 46.43%, 75.39% and 81.17% of LCC, LT, LNC, LTD and SLA variation. The elevation showed positive effect only on LCC (p &lt; 0.05). The results confirmed the existence of consistent trait–environment relationships at both transect and plot scales. These trait–environment relationships at different spatial scales will provide mechanistic understanding on the vegetation community assembly in the study area. Practically, ignoring trait variation within transects will underestimate roles of microhabitat filters in community assembly, and leads to the homogenization of restoration species. This will be like the past restoration plans and programs, causing serious environmental problems such as dwarf trees and soil desiccation

Spatial heterogeneity of temperature across alpine boulder fields in New South Wales, Australia: multilevel modelling of drivers of microhabitat climate

Understanding the spatial heterogeneity of temperatures across a region is significant for identification and protection of potential microhabitats for species conservation. However, this task is proving difficult because multiple factors drive the temperatures of microhabitats and their effect differs at different scales. In the Australian alpine region, boulder field habitats have been identified as important refugia for a range of small mammals. Vegetation cover and elevation have been found to drive thermal buffering at the level of single sampling sites within boulder fields, whereas the aspect and inclination of slopes have been found to affect thermal buffering at the level of clusters of boulder fields. But how the rock structure (number of rock layers, rock size and cavity of boulders) influences microclimate of boulder fields remains an open question. We used a multilevel modelling approach to detect the factors driving microhabitat temperatures in different seasons at different spatial scales in an Australian alpine region. We found that significant temperature differences existed within and between clusters of boulder fields in different seasons. Besides elevation and vegetation cover, the number of rock layers and rock cavity size also exerts important influences on extreme temperatures at the site (i.e. single boulder field) scale. Topographical variables such as slope gradient and elevation influenced minimum temperatures at the boulder field cluster scale. Variations in boulder field temperatures were significant at fine scales, with variations in minimum temperatures exceeding those of maximum temperatures. We suggest that variations in slope gradient and elevation, interacting with vegetation cover, the number of rock layers and rock cavity size can lead to fine-grained thermal variability, which potentially provides refugia for species at microsites, even when regional climatic conditions become less suitable for their survival

Thermal properties of alpine boulder fields: The potential to provide refuge for the endangered mountain pygmy-possum (Burramys parvus)

This thesis investigates the microclimate of Australian alpine boulder fields inhabited by the endangered mountain pygmy-possum Burramys parvus. This endemic specialist is highly sensitive to extreme temperatures and therefore threatened by global warming. In the Australian alpine region, B. parvus survives by living deep within boulder fields. Extreme high and low temperatures within boulder fields are known to be critical factors that determine its survival. Whether alpine boulder fields can offer a stable, long-term microhabitat that effectively buffers extreme temperatures is an open question.This study made detailed investigations of the thermal properties of boulder fields to indentify where refuges for B. parvus may occur in the future. By deploying 273 temperature data loggers in 38 boulder fields for more than 12 months and logging hourly temperatures, it was demonstrated that some boulder fields are better than others at buffering extreme temperatures. Specifically, temperatures become more stable at increasing depths within boulder fields, so the number of available rock layers is important. Vegetation cover, rock cavity size and topographic position of the boulder fields are also significant factors in buffering extreme temperatures. Light intensity meters deployed concurrently with the temperature sensors demonstrated that boulder fields at high elevation, on gentle slopes with south facing aspect accumulated snow for the longest duration. It was also found that the snow depth threshold for achieving effective insulation was 70 cm, therefore hibernating B. parvus are likely to be influenced by extremely cold temperatures when a snow depth <70 cm exists. Moreover, the most dangerous temperatures for B. parvus do not occur during mid-winter when persistent snow covers the boulder fields, but happen before and after the persistent snow cover is established.Significant relationships existed between environmental variables and temperatures in the boulder fields. Statistical modelling showed that elevation was a powerful predictor of several crucial temperatures for B. parvus, such as night-time and minimum temperatures during all seasons at all three depths measured at the point level. Vegetation cover, insolar, rock layer and rock cavity size were also important in predicting extreme temperatures at the point level. Topographic environmental variables such as slope and elevation influenced minimum temperatures at the cluster level. Importantly, this study reported diminished maximum and minimum temperatures in boulder fields covered with vegetation and possessing small cavities. Deep boulder fields were found to provide a more reliable microclimate for B. parvus than shallow ones. A major outcome of this study was the definition and calculation of both the internal and absolute thermal buffering capacities of alpine boulder fields. The internal thermal buffering capacity of alpine boulder field habitat was defined as the differences in temperature ranges between different depths, which express the ability of a boulder field to buffer against outside air temperature changes. The results revealed why certain boulder fields provide potential refuge from extreme temperatures and others do not. Burramys parvus naturally selects boulder fields with the most favourable available microclimate. Deep boulder fields provide the best microclimate in all seasons and, therefore, were identified as the prime potential thermal refuge for B. parvus. Shallow boulder fields at high elevation or deep boulder fields at low elevation might provide thermal refuge for B. parvus if covered by reasonable vegetation and possessing good rock structure. During winter, snow cover moderated the microclimate, so boulder fields with better conditions for snow preservation such as high elevation, on gentle slopes with a south facing aspect were identified as important thermal refuges for B. parvus.Understanding how the buffering capacity of alpine boulder fields varies at a landscape scale and identifying potential refuge conditions crucial to the survival of B. parvus will provide important information for improving assessment of the vulnerability of the species, identifying refuge habitat, identifying suitable translocation sites and constructing artificial habitat in future conservation planning. This is globally relevant for oligostenothermic alpine species in the face of habitat loss due to climate change

A compact and low-cost laser induced fluorescence detector with silicon based photodetector assembly for capillary flow systems

A compact and low-cost laser induced fluorescence (LIF) detector based on confocal structure for capillary flow systems was developed and applied for analysis of Her2 protein on single Hela cells. A low-power and low-cost 450 nm laser diode (LD) instead of a high quality laser was used as excitation light source. A compact optical design together with shortened optical path length improved the optical efficiency and detection sensitivity. A superior silicon based photodetector assembly was used for fluorescence detection instead of a photomultiplier (PMT). The limit of detection (LOD) for fluorescein sodium was 3 x 10(-12) M or 165 fluorescein molecules in detection volume measured on a homemade capillary electroosmotic driven (EOD)-LIF system, which was similar to commercial LIFs. Compared to commercial LIFs, the whole volume of our LIF was reduced to 1/2-1/3, and the cost was less than 1/3 of them