青藏高原高寒草甸生物量动态变化及与环境因子的关系——基于模拟增温实验

以青藏高原高寒草甸为研究区,设置模拟增温实验样地,于2010年开始持续增温,2012和2013年调查植被地上-地下生物量,探讨气候变暖背景下高寒草甸生物量的动态变化及其与环境因子的关系。结果表明:(1)增温处理下地上-地下生物量与根冠比的中值和平均值大于对照,其中地下生物量(变异系数为0.30)的增加幅度大于地上生物量(变异系数为0.27),根冠比的变异系数(0.33)大于地上-地下生物量,这表明增温可导致高寒草甸植被生物量分配出现差异。(2)地上-地下生物量呈极显著的幂指数函数关系(R~2=0.147,P0.001),表现为异速生长,但在增温处理下异速生长出现减缓(R~2=0.102,P0.05)。(3)地上生物量受深层土壤水分和浅层土壤温度影响较大,地下生物量受深层土壤水分和深层土壤温度影响较大;土壤温度对地上-地下生物量的影响强于土壤水分,表现为20 cm深度土壤温度对地上生物量(R=0.582,P0.01)和根冠比(R=-0.238,P0.05)影响较大,60 cm深度土壤温度对地下生物量影响较大(R=0.388,P0.01),100 cm深度土壤水分对地上生物量(R=0.423,P0.01)和地下生物量(R=0.245,P0.05)影响较大,这说明增温导致浅层土壤温度对生物量分配产生影响,使生物量更多分配到地上部分,而冻土融化致使深层土壤水分对生物量产生影响。     

PALSAR 50 m Mosaic Data Based National Level Biomass Estimation in Cambodia for Implementation of REDD+ Mechanism

Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σ^o) properties of PALSAR data. The relationship between the PALSAR σ^o HV and HH/HV with field measured biomass was strong with R² = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R² = 0.61 with RMSE  = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level.     

Above- and Belowground Biomass Allocation in Shrub Biomes across the Northeast Tibetan Plateau

Biomass partitioning has been explored across various biomes. However, the strategies of allocation in plants still remain contentious. This study investigated allocation patterns of above- and belowground biomass at the community level, using biomass survey from the Tibetan Plateau. We explored above- and belowground biomass by conducting three consecutive sampling campaigns across shrub biomes on the northeast Tibetan Plateau during 2011–2013. We then documented the above-ground biomass (AGB), below-ground biomass (BGB) and root: shoot ratio (R/S) and the relationships between R/S and environment factors using data from 201 plots surveyed from 67 sites. We further examined relationships between above-ground and below-ground biomass across various shrub types. Our results indicated that the median values of AGB, BGB, and R/S in Tibetan shrub were 1102.55, 874.91 g m^-2, and 0.85, respectively. R/S showed significant trend with mean annual precipitation (MAP), while decreased with mean annual temperature (MAT). Reduced major axis analysis indicated that the slope of the log-log relationship between above- and belowground biomass revealed a significant difference from 1.0 over space, supporting the optimal hypothesis. Interestingly, the slopes of the allometric relationship between log AGB and log BGB differed significantly between alpine and desert shrub. Our findings supported the optimal theory of above- and belowground biomass partitioning in Tibetan shrub, while the isometric hypothesis for alpine shrub at the community level.     

Relationships of Biomass with Environmental Factors in the Grassland Area of Hulunbuir,China

Many studies have focused on the relationship between vegetation biomass and environmental factors in grassland. However, several questions remain to be answered, especially with regards to the spatial pattern of vegetation biomass. Thus, the distributed mechanism will be explored in the present study. Here, plant biomass was measured at 23 sites along a transect survey during the peak growing season in 2006. The data were analyzed with a classification and regression tree (CART) model. The structural equation modeling (SEM) was conducted to explicitly evaluate the both direct and indirect effects of these critical environmental elements on vegetation biomass. The results demonstrated that mean annual temperature (MAT) affected aboveground biomass (AGB) scored at −0.811 (P<0.05). The direct effect of MAT on belowground biomass (BGB) was −0.490 (P<0.05). The results were determined by SEM. Our results indicate that AGB and BGB in semi-arid ecosystems is strongly affected by precipitation and temperature. Future work shall attempt to take into account the integrated effects of precipitation and temperature. Meanwhile, partitioning the influences of environmental variations and vegetation types are helpful in illuminating the internal mechanism of biomass distribution.     

Biomass and Its Allocation in Relation to Temperature,Precipitation, and Soil Nutrients in Inner Mongolia Grasslands,China

Aim

Understanding and predicting ecosystem functioning such as biomass accumulation requires an accurate assessment of large-scale patterns of biomass distribution and partitioning in relation to climatic and soil environments.

Methods

We sampled above- and belowground biomass from 26 sites spanning 1500 km in Inner Mongolian grasslands, compared the difference in aboveground, belowground biomass and below-aboveground biomass ratio (AGB, BGB, and B/A, respectively) among meadow steppe, typical steppe, and desert steppe types. The relationships between AGB, BGB, B/A and climatic and soil environments were then examined.

Results

We found that AGB and BGB differed significantly among three types of grasslands while B/A did not differ. Structural equation model analyses indicated that mean annual precipitation was the strongest positive driver for AGB and BGB. AGB was also positively associated with soil organic carbon, whereas B/A was positively associated with total soil nitrogen.

Conclusions

These results indicated that precipitation positively influence plant production in Inner Mongolian grasslands. Contrary to the prediction from the optimal partitioning hypothesis, biomass allocation to belowground increased with soil total nitrogen, suggesting that more productive sites may increase belowground allocation as an adaptive strategy to potentially high fire frequencies.     

Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City,Northwest China

Crop biomass is an important ecological indicator of growth, light use efficiency, and carbon stocks in agro-ecosystems. Light detection and ranging (LiDAR) or laser scanning has been widely used to estimate forest structural parameters and biomass. However, LiDAR is rarely used to estimate crop parameters because the short, dense canopies of crops limit the accuracy of the results. The objective of this study is to explore the potential of airborne LiDAR data in estimating biomass components of maize, namely aboveground biomass (AGB) and belowground biomass (BGB). Five biomass-related factors were measured during the entire growing season of maize. The field-measured canopy height and leaf area index (LAI) were identified as the factors that most directly affect biomass components through Pearson's correlation analysis and structural equation modeling (SEM). Field-based estimation models were proposed to estimate maize biomass components during the tasseling stage. Subsequently, the maize height and LAI over the entire study area were derived from LiDAR data and were used as input for the estimation models to map the spatial pattern of the biomass components. The results showed that the LiDAR-estimated biomass was comparable to the field-measured biomass, with root mean squared errors (RMSE) of 288.51 g/m² (AGB), and 75.81 g/m² (BGB). In conclusion, airborne LiDAR has great potential for estimating canopy height, LAI, and biomass components of maize during the peak growing season.     

Precipitation and nitrogen addition enhance biomass allocation to aboveground in an alpine steppe

There are two important allocation hypotheses in plant biomass allocation: allometric and isometric. We tested these two hypotheses in an alpine steppe using plant biomass allocation under nitrogen (N) addition and precipitation (Precip) changes at a community level. An in situ field manipulation experiment was conducted to examine the two hypotheses and the responses of the biomass to N addition (10 g N m^?2 y^?1) and altered Precip (±50% precipitation) in an alpine steppe on the Qinghai–Tibetan Plateau from 2013 to 2016. We found that the plant community biomass differed in its response to N addition and reduced Precip such that N addition significantly increased aboveground biomass (AGB), while reduced Precip significantly decreased AGB from 2014 to 2016. Moreover, reduced Precip enhanced deep soil belowground biomass (BGB). In the natural alpine steppe, the allocation between AGB and BGB was consistent with the isometric hypotheses. In contrast, N addition or altered Precip enhanced biomass allocation to aboveground, thus leading to allometric growth. More importantly, reduced Precip enhanced biomass allocation into deep soil. Our study provides insight into the responses of alpine steppes to global climate change by linking AGB and BGB allocation.     

A New Equation to Estimate Glomerular Filtration Rate in Chinese Elderly Population

Background

We sought to develop a new equation to estimate glomerular filtration rate (GFR) in Chinese elderly population.

Methods

A total of 668 Chinese elderly participants, including the development cohort (n = 433), the validation cohort (n = 235) were enrolled. The new equation using the generalized additive model, and age, gender, serum creatinine as predictor variables was developed and the performances was compared with the CKD-EPI equation.

Results

In the validation data set, both bias and precision were improved with the new equation, as compared with the CKD-EPI equation (median difference, −1.5 ml/min/1.73 m² vs. 7.4 ml/min/1.73 m² for the new equation and the CKD-EPI equation, [P<0.001]; interquartile range [IQR] for the difference, 16.2 ml/min/1.73 m² vs. 19.0 ml/min/1.73 m² [P<0.001]), as were accuracies (15% accuracy, 40.4% vs. 30.6% [P = 0.02]; 30% accuracy, 71.1% vs. 47.2%, [P<0.001]; 50% accuracy, 90.2% vs. 75.7%, [P<0.001]), allowing improvement in GFR categorization (GFR category misclassification rate, 37.4% vs. 53.2% [P = <0.001]).

Conclusions

A new equation was developed in Chinese elderly population. In the validation data set, the new equation performed better than the original CKD-EPI equation. The new equation needs further external validations. Calibration of the GFR referent standard to a more accurate one should be an useful way to improve the performance of GFR estimating equations.     

Fusion of airborne LiDAR data and hyperspectral imagery for aboveground and belowground forest biomass estimation

Vegetation biomass is a key biophysical parameter for many ecological and environmental models. The accurate estimation of biomass is essential for improving the accuracy and applicability of these models. Light Detection and Ranging (LiDAR) data have been extensively used to estimate forest biomass. Recently, there has been an increasing interest in fusing LiDAR with other data sources for directly measuring or estimating vegetation characteristics. In this study, the potential of fused LiDAR and hyperspectral data for biomass estimation was tested in the middle Heihe River Basin, northwest China. A series of LiDAR and hyperspectral metrics were calculated to obtain the optimal biomass estimation model. To assess the prediction ability of the fused data, single and fused LiDAR and hyperspectral metrics were regressed against field-observed belowground biomass (BGB), aboveground biomass (AGB) and total forest biomass (TB). The partial least squares (PLS) regression method was used to reduce the multicollinearity problem associated with the input metrics. It was found that the estimation accuracy of forest biomass was affected by LiDAR plot size, and the optimal plot size in this study had a radius of 22 m. The results showed that LiDAR data alone could estimate biomass with a relative high accuracy, and hyperspectral data had lower prediction ability for forest biomass estimation than LiDAR data. The best estimation model was using a fusion of LiDAR and hyperspectral metrics (R² = 0.785, 0.893 and 0.882 for BGB, AGB and TB, respectively, with p < 0.0001). Compared with LiDAR metrics alone, the fused LiDAR and hyperspectral data improved R² by 5.8%, 2.2% and 2.6%, decreased AIC value by 1.9%, 1.1% and 1.2%, and reduced RMSE by 8.6%, 7.9% and 8.3% for BGB, AGB and TB, respectively. These results demonstrated that biomass accuracies could be improved by the use of fused LiDAR and hyperspectral data, although the improvement was slight when compared with LiDAR data alone. This slight improvement could be attributed to the complementary information contained in LiDAR and hyperspectral data. In conclusion, fusion of LiDAR and other remotely sensed data has great potential for improving biomass estimation accuracy.     

Estimation of aboveground biomass and net biomass increment in a cool temperate forest on a landscape scale

I clarified aboveground biomass (AGB), net biomass increment (NBI) and its spatial heterogeneity in a cool temperate forest on a landscape scale (>2,200 ha). The relationships among AGB, NBI, and the size frequency distribution of trees of each stand were examined by combining an analysis of vegetation using aerial photographs, and data from 146 inventory plots (28.8 ha in total). This area included natural broad-leaved stands, harvested broad-leaved stands, and artificial conifer plantations. A –3/2 power distribution density function was applied to the individual mass frequency distribution of each plot. Estimated AGB in carbon (C) equivalent was 480–5,615 g C m^–2 (3,130 g C m^–2 on average), and NBI was –98 to 436 g C m^–2 year^–1 (83.0 g C m^–2 year^–1 on average). NBI had a single significant relationship with the reciprocal of theoretical maximum individual mass, while NBI was not significantly related to AGB. My results showed that, on a landscape scale, AGB and NBI strongly depend on the size structure of forest stands.     

青藏高原草地地上生物量估算

及时准确评估草地产草量对草地资源的科学管理和可持续发展具有重要意义。青藏高原自然环境特殊,气候差异显著,地形复杂,仅依靠遥感信息准确监测草地地上生物量(Aboveground Biomass,AGB)变化有较大限制。基于青藏高原草地AGB野外实测数据与Landsat遥感影像,探索了植被指数表征草地AGB信息的有效性,评估了气象和地形信息对准确估算草地AGB的影响,综合利用气象、地形和遥感信息,在新一代地球科学数据和分析应用平台(Google Earth Engine)上构建了梯度增强回归树草地AGB估算模型,绘制了青藏高原多年草地AGB空间分布图。结果表明:(1)基于单因素遥感因子的线性回归模型仅能解释8%-40%的草地AGB变化情况,其中绿色归一化植被指数(Green Normalized Difference Vegetation Index, GNDVI)对草地AGB解释能力较强(40%)。(2)基于遥感因子构建的梯度增强回归树模型测试集R²为0.57。分别添加气象、地形信息,模型对草地AGB的估测准确性有所提升,测试R²为0.62和0.63。(3)基于气象、地形和遥感因子的多因素估测模型能够提高草地AGB估测精度,经递归特征消除法优选后,基于13个特征变量的梯度增强回归树模型拟合效果最好(训练数据集R²=0.79,RMSE=43.42 g/m²,P<0.01;测试数据集R²=0.66,RMSE=53.64 g/m²,P<0.01),可以解释66%草地AGB变化情况。(4)2010年青藏高原平均AGB为94.58 g/m²,2015年93.63 g/m²,2020年100.78 g/m²。青藏高原西北部草地AGB较低,东南部草地AGB较高,整体呈现自西北向东南逐渐增加的分布格局。研究结果为准确估算青藏高原草地产草量和碳储量等研究提供重要参考。     

Does the effect of flowering time on biomass allocation across latitudes differ between invasive and native salt marsh grass Spartina alterniflora?

1. Parallel latitudinal clines in flowering time have been documented in both the invasive and native ranges of plants. Furthermore, flowering time has been found to affect biomass at maturity. Therefore, understanding how these flowering times affect biomass accumulation across latitudes is essential to understanding plant adaptations and distributions.
2. We investigated and compared trends in first flowering day (FFD), aboveground biomass (AGB), belowground biomass (BGB), and BGB:AGB ratio of the salt marsh grass Spartina alterniflora along latitudinal gradients from the invasive (China, 19–40°N) and native range (United States, 27–43°N) in a greenhouse common garden experiment, and tested whether FFD would drive these divergences between invasive and native ranges.
3. The invasive populations produced more (~20%, ~19%) AGB and BGB than native populations, but there were no significant differences in the FFD and BGB:AGB ratio. We found significant parallel latitudinal clines in FFD in both invasive and native ranges. In addition, the BGB:AGB ratio was negatively correlated with the FFD in both the invasive and native ranges but nonsignificant in invasive populations. In contrast, AGB and BGB increased with latitude in the invasive range, but declined with latitude in the native range. Most interestingly, we found AGB and BGB positively correlated with the FFD in the native range, but no significant relationships in the invasive range.
4. Our results indirectly support the evolution of increased competitive ability hypothesis (EICA) that S. alterniflora has evolved to produce greater AGB and BGB in China, but the flowering and allocation pattern of native populations is maintained in the invasive range. Our results also suggest that invasive S. alterniflora in China is not constrained by the trade‐off of earlier flowering with smaller size, and that flowering time has played an important role in biomass allocation across latitudes.

     

The Association of Growth Differentiation Factor-15 with Left Ventricular Hypertrophy in Hypertensive Patients

Growth differentiation factor-15 (GDF-15) has been identified as an endogenous anti-hypertrophy effect. However, the association of plasma GDF-15 levels with left ventricular hypertrophy (LVH) in hypertension is poorly understood. We investigate the effect of plasma GDF-15 levels on left ventricular hypertrophy (LVH) in hypertension. We measured the plasma levels of GDF-15 in 299 untreated hypertensive patients which consisted of 99 with LVH and 200 without LVH using immunoradiometric assay. All subjects were examined by the ultrasonic cardiograph to determine Left ventricular (LV) internal diameters, septal thickness, and posterior wall thickness. The associations of GDF-15 with left ventricular mass index (LVMI), LV end-systolic and –diastolic diameters, LV wall thickness, and LV ejection fraction were evaluated. We found that plasma GDF-15 levels in hypertensive patients with LVH [median 1101, 25th–75th percentiles (879–1344) ng/L] were higher than that in hypertensive patients without LVH [median 516, 25th–75th percentiles (344–640) ng/L] (P<0.001). After adjustment for traditional covariates, plasma GDF-15 levels were independently related to LVMI (R² = 0.53; β = 0.624, P<0.001), LV interventricular septal thickness (R² = 0.23; β = 0.087, P<0.01) and LV posterior wall thickness (R² = 0.26; β = 0.103, P<0.05). Our cross-sectional data on a hospital-based sample indicate that plasma GDF-15 levels are associated with LVH in hypertensive patients.     

Community species diversity mediates the trade‐off between aboveground and belowground biomass for grasses and forbs in degraded alpine meadow,Tibetan Plateau

Although many empirical experiments have shown that increasing degradation results in lower aboveground biomass (AGB), our knowledge of the magnitude of belowground biomass (BGB) for individual plants is a prerequisite for accurately revealing the biomass trade‐off in degraded grasslands. Here, by linking the AGB and BGB of individual plants, species in the community, and soil properties, we explored the biomass partitioning patterns in different plant functional groups (grasses of Stipa capillacea and forbs of Anaphalis xylorhiza). Our results indicated that 81% and 60% of the biomass trade‐off variations could be explained by environmental factors affecting grasses and forbs, respectively. The change in community species diversity dominated the biomass trade‐off via either direct or indirect effects on soil properties and biomass. However, the community species diversity imparted divergent effects on the biomass trade‐off for grasses (scored at −0.72) and forbs (scored at 0.59). Our findings suggest that plant communities have evolved two contrasting strategies of biomass allocation patterns in degraded grasslands. These are the “conservative” strategy in grasses, in which plants with larger BGB trade‐off depends on gigantic roots for soil resources, and the “opportunistic” strategy in forbs, in which plants can adapt to degraded lands using high variation and optimal biomass allocation.     

Determinants of Posterior Corneal Biometric Measurements in a Multi-Ethnic Asian Population

Purpose

To describe the corneal and anterior segment determinants of posterior corneal arc length (PCAL) and posterior corneal curvature (PCC).

Methods

Cross-sectional, population-based study of 1069 subjects (1069 eyes) aged 40–80 years, from three major Asian ethnic groups. All underwent anterior segment optical coherence tomography imaging and analysis with Zhongshan Angle Assessment Program. Our main outcome measures were determinants of PCAL and PCC using adjusted, multivariate linear regression analysis, adjusted for confounders to obtain the estimated marginal means (EMM) with standard error (SE).

Results

The overall mean (± SD) of PCC was: 6.51±0.39 mm; and PCAL was: 12.52±0.59 mm. Malays had a relatively longer PCAL (EMM = 12.74 mm, SE = 0.04 mm) than Chinese (EMM = 12.48 mm, SE = 0.03 mm, P<0.001), and Indians (EMM = 12.42 mm, SE = 0.03 mm, P<0.001). Anterior segment parameters had weak-moderate correlations with PCAL, which included: anterior chamber depth (ACD) (r = 0.55, P<0.001), PCC (r = 0.27, P<0.001), anterior corneal curvature (ACC) (r = 0.14, P<0.001) and central corneal thickness (CCT) (r = −0.07, P = 0.023). In multivariate analysis, anterior segment parameters explained only 37.6% of the variance of PCAL, with ACD being the most important determinant (partial R²  = 0.300; P<0.001). The determinants of PCC included ACC, PCAL and CCT (explaining 72.1% variation of PCC), with ACC being the most important determinant (partial R²  = 0.683; P<0.001).

Conclusion

There was moderate correlation of PCAL with ACD, but anterior segment parameters accounted for only a small proportion of the variation in PCAL. The significant differences in PCAL and PCC amongst different Asian ethnic groups suggests that there is a need to consider this factor when planning for anterior segment surgeries such as endothelial keratoplasty.     

Estimating net primary productivity of grasslands from field biomass measurements in temperate northern China

Data on field biomass measurements in temperate grasslands of northern China (141 samples from 74 sites) were obtained from 23 Chinese journals, reports and books. Net primary productivity (NPP) of grasslands was estimated using three algorithms (peak live biomass, peak standing crop and maximum minus minimum live biomass), respectively, based on availability of biomass data in sites. 135 samples which have aboveground biomass (AGB) measurements, have peak AGB ranges from 20 to 2021 g m^–2 (mean = 325.3) and the aboveground NPP (ANPP) ranges from 15 to 1647.1 g m^–2 per year (mean = 295.7). 72 samples which have belowground biomass (BGB) measurements, have peak BGB ranges from 226.5 to 12827.5 g m^–2 (mean = 3116) and the belowground NPP (BNPP) ranges from 15.8 to 12827.5 g m^–2 per year (mean = 2425.6). In total 66 samples have the total NPP (TNPP), ranging from 55.3 to 13347.8 g m^–2 per year (mean = 2980.3). Mean peak biomass and NPP varied from different geographical sampling locations, but they had a general rough regularity in ten grasslands. Meadow, mountain and alpine grasslands had high biomass and NPP (sometimes including saline grassland). Forested steppe, saline grassland and desert had median values. Meadowed and typical steppes had low biomass and NPP (sometimes including desert). The lowest biomass and NPP occurred in deserted steppe and stepped desert. Grassland ANPP has significant positive relationships with annual and summer precipitation as well as summer temperature (all p<0.01). However, grassland BNPP and TNPP have more significant negative relationships with summer temperature (p<0.01) than with annual temperature (p<0.05). The analysis of climate – productivity correlations implied that aboveground productivity is more controlled by rainfall, whereas belowground and total productivity is more influenced by temperature in the temperate grasslands of northern China. The present study might underestimate grassland NPP in northern China due to limitation of biomass measurements. Data on relative long-term aboveground and belowground biomass dynamics, as well as data of standing dead matter, litterfall, decomposition and turnover, are required if grassland NPP is to be more accurately estimated and the role of temperate grasslands in the regional to global carbon cycles is to be fully appreciated. This revised version was published online in June 2006 with corrections to the Cover Date.     

三江源国家公园草地地上生物量时空动态及其气候影响

三江源区位于青藏高原腹地,作为长江、黄河、澜沧江三大河流的发源地,是我国重要的生态安全屏障。基于三江源区域草地AGB的野外调查数据,本研究采用多种机器学习算法集成分析的方式构建模型,实现了高精度的三江源国家公园草地AGB时空估算。基于AGB时空模拟结果,分析了近19年(2000—2018年)三江源国家公园区域草地AGB的时空动态变化。研究结果显示：(1)通过多种机器学习结合贝叶斯平均模型,草地AGB模拟值与实测值的r为0.88,RMSE为71.60g/m²,表明多模型集成分析的方式对草地AGB估算获得了较好的模拟效果。(2)三江源国家公园区域草地AGB的空间分布具有明显的空间异质性,呈从东南向西北递减的趋势。(3)2000—2018年长江源国家公园、黄河源国家公园和澜沧江国家公园区域草地AGB多年平均值分别为82.96 g/m²、117.54g/m²和168.39 g/m²。(4)近19年间,在黄河和长江源园区受到温度上升的影响草地AGB呈现出非显著性上升趋势;澜沧江区域,由于2015和2016年的...     

MRI osteitis predicts cartilage damage at the wrist in RA: a three-year prospective 3T MRI study examining cartilage damage

Introduction

Cartilage damage impacts on patient disability in rheumatoid arthritis (RA). The aims of this magnetic resonance imaging (MRI) study were to investigate cartilage damage over three years and determine predictive factors.

Methods

A total of 38 RA patients and 22 controls were enrolled at t = 0 (2009). After 3 years, clinical and MRI data were available in 28 patients and 15 controls. 3T MRI scans were scored for cartilage damage, bone erosion, synovitis and osteitis. A model was developed to predict cartilage damage from baseline parameters.

Results

Inter-reader reliability for the Auckland MRI cartilage score (AMRICS) was high for status scores; intraclass correlation coefficient (ICC), 0.90 (0.81 to 0.95) and moderate for change scores (ICC 0.58 (0.24 to 0.77)). AMRICS scores correlated with the Outcome MEasures in Rheumatoid Arthritis Clinical Trials (OMERACT) MRI joint space narrowing (jsn) and X-Ray (XR) jsn scores (r =0.96, P < 0.0001 and 0.80, P < 0.0001, respectively). AMRICS change scores were greater for RA patients than controls (P = 0.06 and P = 0.04 for the two readers). Using linear regression, baseline MRI cartilage, synovitis and osteitis scores predicted the three-year AMRICS (R² = 0.67, 0.37 and 0.39, respectively). A multiple linear regression model predicted the three-year AMRICS (R² = 0.78). Baseline radial osteitis predicted increased cartilage scores at the radiolunate and radioscaphoid joints, P = 0.0001 and 0.0012, respectively and synovitis at radioulnar, radiocarpal and intercarpal-carpometacarpal joints also influenced three-year cartilage scores (P-values of 0.001, 0.04 and 0.01, respectively).

Conclusions

MRI cartilage damage progression is preceded by osteitis and synovitis but is most influenced by pre-existing cartilage damage suggesting primacy of the cartilage damage pathway in certain patients.     

Niacin Reduces Atherosclerosis Development in APOE*3Leiden.CETP Mice Mainly by Reducing NonHDL-Cholesterol

Objective

Niacin potently lowers triglycerides, mildly decreases LDL-cholesterol, and largely increases HDL-cholesterol. Despite evidence for an atheroprotective effect of niacin from previous small clinical studies, the large outcome trials, AIM-HIGH and HPS2-THRIVE did not reveal additional beneficial effects of niacin (alone or in combination with laropiprant) on top of statin treatment. We aimed to address this apparent discrepancy by investigating the effects of niacin without and with simvastatin on atherosclerosis development and determine the underlying mechanisms, in APOE*3Leiden.CETP mice, a model for familial dysbetalipoproteinemia (FD).

Approach and Results

Mice were fed a western-type diet containing cholesterol without or with niacin (120 mg/kg/day), simvastatin (36 mg/kg/day) or their combination for 18 weeks. Similarly as in FD patients, niacin reduced total cholesterol by -39% and triglycerides by −50%, (both P<0.001). Simvastatin and the combination reduced total cholesterol (−30%; −55%, P<0.001) where the combination revealed a greater reduction compared to simvastatin (−36%, P<0.001). Niacin decreased total cholesterol and triglycerides primarily by increasing VLDL clearance. Niacin increased HDL-cholesterol (+28%, P<0.01) and mildly increased reverse cholesterol transport. All treatments reduced monocyte adhesion to the endothelium (−46%; −47%, P<0.01; −53%, P<0.001), atherosclerotic lesion area (−78%; −49%, P<0.01; −87%, P<0.001) and severity. Compared to simvastatin, the combination increased plaque stability index [(SMC+collagen)/macrophages] (3-fold, P<0.01). Niacin and the combination reduced T cells in the aortic root (−71%, P<0.01; −81%, P<0.001). Lesion area was strongly predicted by nonHDL-cholesterol (R² = 0.69, P<0.001) and to a much lesser extent by HDL-cholesterol (R² = 0.20, P<0.001).

Conclusion

Niacin decreases atherosclerosis development mainly by reducing nonHDL-cholesterol with modest HDL-cholesterol-raising and additional anti-inflammatory effects. The additive effect of niacin on top of simvastatin is mostly dependent on its nonHDL-cholesterol-lowering capacities. These data suggest that clinical beneficial effects of niacin are largely dependent on its ability to lower LDL-cholesterol on top of concomitant lipid-lowering therapy.     

青藏高原草地地下生物量与环境因子的关系

青藏高原草地生物量大部分分布于地下,地下生物量在其碳循环研究中起着重要的作用.基于大规模野外样地调查数据,分析比较了青藏高原南北和东西样带上草地地下生物量与环境因子的相关关系,探讨了环境因子对地下生物量控制作用的区域差异.研究结果表明:对于所有采样点而言,青藏高原草地地下生物量的环境控制因素主要有土壤含水量、表层土壤有机碳和全氮含量.通过比较南北和东西样带研究结果发现,草地地下生物量与土壤含水量、土壤表层有机碳和全氮含量相关的显著性水平,在东西样带上明显高于南北样带.同时,东西样带上草地地下生物量与降水量有显著正相关关系,这种关系在南北样带上不显著,表明水分对东西样带草地地下生物量的控制作用较强.气温与南北样带草地地下生物量呈显著负相关,但与东西样带草地地下生物量相关不显著,由此说明环境因子对青藏高原草地地下生物量的控制存在显著区域差异.