Machine learning prediction of above-ground biomass in pure Calabrian pine (Pinus brutia Ten.) stands of the Mediterranean region,Türkiye

Above-ground biomass (AGB) is an important component for identifying carbon stocks, monitoring the impacts of climate change, and evaluating merchantable timber. Accurate prediction of forest AGB is central to the correct interpretation of these components and to produce usable data for planners and researchers. In this study, remotely sensed time-series data derived from Landsat 8 (reflectance (R) and vegetation indices (VI)), topographic (T) and climate (C) data were used as independent variables to predict AGB of pure Calabrian pine (Pinus brutia Ten.) stands using multiple regression analysis (MLR) and support vector machines (SVM) methods. The AGB modeling was done by using independent variables individually and by combining variables, and the AGB maps of the most successful models obtained from MLR and SVM methods were produced. It was determined that the most successful variable group was the VI when the independent variables were used one by one (MLR Training R² = 0.50, SVM Training R² = 0.67). The most successful predictions in AGB modeling were obtained with combining all independent variables and using the SVM method (Training R² = 0.85, Validation R² = 0.69). In the combination of independent variables, VI and C data made the greatest contribution to the success of the AGB prediction. The ‘green leaf index’ vegetation indices had the most significant effect on the modeling AGB. In this study, T and C in addition to spectral data has increased the AGB estimation performance. It has been found that the SVM method yielded higher model accuracy than MLR method in predicting AGB. Overall, the spectral data and the SVM method can contribute to improving the accuracy of AGB estimates and provide an effective approach towards the capability for forest ecosystem monitoring.     

Relationship of Glycogen Synthase and Glycogen Phosphorylase to Protein Phosphatase 2C and cAMP-Dependent Protein Kinase in Liver of Obese Rhesus Monkeys

ORTMEYER HK. Relationship of glycogen synthase and glycogen phosphorylase to protein phosphatase 2C and cAMP-dependent protein kinase in liver of obese rhesus monkeys. The regulation of glycogen synthase (GS) and glycogen phosphorylase (GP) activity by phosphorylation/ dephosphorylation has been proposed to be via changes in activities of several different protein (serine/ threonine) phosphatases and kinases, including protein phosphatase (PP) 1/2A, PP2C, and cAMP-dependent protein kinase (PKA). In order to determine whether PP1/2A, PP2C, and/or PKA activities are related to GS and/or GP activities, these enzymes were measured in freeze-clamped liver biopsies obtained under basal fasting conditions from 16 obese monkeys. Four monkeys were normoglycemic and normoinsulinemic, five were hyperinsulinemic, and seven had type 2 diabetes (NIDDM). Liver glycogen and glucose 6-phosphate (G6P) contents were also determined. Basal enzyme activities and basal substrate concentrations were not significantly different between the three groups of obese monkeys; however, there were several significant linear relationships observed when the monkeys were treated as one group. Therefore, multiple regression was used to determine the correlation between key variables. GS fractional activity was correlated to GP fractional activity (p<0. 05) and to PP2C activity (p=0. 005) (adjusted R²,53%). GP independent activity was correlated to GS independent activity (p<0. 07) and to PKA fractional activity (p=0. 005) (adjusted R²,64%). PP2C activity was correlated to GS fractional activity (p<0. 0005) and to PP1/2A activity G7<0. 0001) (adjusted R²,83%). PKA fractional activity was correlated to GP total activity (p<0. 0005) and to age (p=0. 001) (adjusted R282%). G6P content was correlated to glycogen content (p<0. 05) and to PP2C activity (p=0. 0005) (adjusted R²,73%). In conclusion, PP2C and PKA are involved in the regulation of GS and GP activity in the basal state in liver of obese monkeys with a wide range of glucose tolerance.     

Discriminating and mapping the C3 and C4 composition of grasslands in the northern Great Plains,USA

There is uncertainty about the extent and distribution of grasslands following the C3 and C4 photosynthetic pathways. Since these grasses have an asynchronous seasonal profile it should be possible to estimate and map the C3–C4 composition of grasslands from multi-temporal remote sensing imagery. This potential was evaluated using 30 weekly composite MERIS MTCI images for South Dakota, USA. Derived relationships between the remotely sensed response and composition of grasslands were significant, with R² ∼ 0.6. It also appears possible to map broad classes of grassland composition, with a three class (high, medium and low C3 cover) classification having an accuracy of 77.8%.     

Demographic and growth patterns of Pentaclethra macroloba (Willd.) Kuntze,a hyperdominant tree in the Amazon River estuary

Little is known about the life history and environmental factors that regulate the growth rate of hyperdominant trees in flooded Amazonian forests. Pentaclethra macroloba is a hyperdominant tree, and it is widely explored in the Amazon, because its seed oil is a powerful herbal medicine. We evaluated the demographic structure and growth patterns of P. macroloba and tested the effect of the Amazon River flood pulse on its growth. We modeled the growth and determined the age of P. macroloba by analyzing the growth rings of 30 monitored trees in relation to hydroclimatic variables. We also inventoried 240 juvenile and 2072 adult trees arranged in a clustered pattern. The diametric distribution pattern of the juvenile and adult trees was exponential and log-normal, respectively. The trees were found to be up to 102 years old, and 47% of them grew freely toward the canopy. Peak growth in height and diameter occurred at 24 (61.7 cm year^-1) and 46 (9.38 mm year^-1) years, respectively. Pentaclethra macroloba showed cambial dormancy during the seasonal peak of rainfall (R² = 0.41; t = −2.62; p < 0.01) and flooding of the Amazon River (R² = 0.47; t = −3.01; p < 0.01). Increases in rainfall and flood level of the river in the rainy season control the growth rate of P. macroloba, making it a seasonal process. The demographic and growth patterns of P. macroloba respond to the environmental heterogeneity of the estuarine floodplain forest and also reflect its life history over time.     

Soil is the main predictor of secondary rain forest estimated aboveground biomass across a Neotropical landscape

We studied the relative effects of landscape configuration, environmental variables, forest age, and spatial variables on estimated aboveground biomass (AGB) in Costa Rican secondary rain forests patches. We measured trees ≥5 cm dbh in 24, 0.25 ha plots and estimated AGB for trees 5–24.9 cm dbh and for trees >25 cm dbh using two allometric equations based on multispecies models using tree dbh and wood‐specific gravity. AGB averaged 87.3 Mg/ha for the 24 plots (not including remnant trees) and 123.4 Mg/ha including remnant trees (20 plots). There was no effect of forest age on AGB. Variation partitioning analysis showed that soils, climate, landscape configuration, and space together explained 61% of tree AGB variance. When controlling for the effects of the other three variables, only soils remained significant. Soil properties, specifically K and Cu, had the strongest independent effect on AGB (variation partitioning, R² = 0.17, p = 0.0310), indicating that in this landscape, AGB variation in secondary forest patches is influenced by soil chemical properties. Elucidating the relative influence of soils in AGB variation is critical for understanding changes associated with land cover modification across Neotropical landscapes, as it could have important consequences for land use planning since secondary forests are considered carbon sinks. Abstract in Spanish is available with online material.     

An accessible scheme for monitoring free‐roaming cat population trends

Free‐roaming cats (FRCs) form nondomiciliary population groups that might lead to adverse environmental effects, as well as to welfare impairment of the cats themselves. Though criticized by ecologists, for the last two decades, the trap–neuter–return (TNR) programs were often employed aiming to manage these populations. At present, no accepted and accessible monitoring scheme exists to determine the effectiveness of those programs. In the current study, we present the reliability and validity of an applicable monitoring scheme, as an adjunct tool for a TNR program of FRC in an urban environment. The monitoring scheme is based on cat observation counts along randomly chosen transects. Fifty‐four transects were repeatedly walked for three years, between 2012‐2014, in 27 neighborhoods within an urban area of 19.3 Km². Cat numbers counted in the 2014 observations were significantly higher than cat numbers found in the 2012 observations (prevalence ratio = 1.258, CI_95%= 1.198–1.322, p < 0.001). The method revealed high reliability when different observers and different transects in the same neighborhood were compared (R² = 0.548 and R² = 0.391, respectively, for measuring cat counts per km, p < 0.001; and R² = 0.5 and R² = 0.74, respectively, for measuring neutering percentage, p < 0.001). This scheme was constructively validated by measurements of municipal data on the number of neutered cats and demonstrated high correlation (R² = 0.59, p < 0.001). Conducting cat observations using friendly calling and feeding resulted in an increased number of FRC observed per km walk (by 79% and 22%–30%, respectively). However, these manipulations did not alter the recorded percentage of neutered cats. The proposed scheme provides spatio‐temporal data that can contribute to the management programs of such cat metapopulations in an urban environment.     

A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest

Mangroves are well-recognized for their very high carbon sequestration potential. However, studies on their role in global carbon cycling and climate change are hindered due to lack of operational methodologies to model and map their biophysical properties. This study establishes a robust methodological protocol for aboveground biomass (AGB) estimation using i) field measurements, ii) a generic (in the absence of species-specific) allometric equation, iii) multi-sensor/polarization SAR data and derived variables thereof, and iv) machine learning models; that demonstrated high prediction accuracy (R² = 0.93) and low uncertainty (mean ≤ 3% and median ≤ 1.5%) for a mangrove forest. Following stratified random sampling and on-field accessibility criteria, we laid out 314 elementary sampling points of 0.04 ha each at Bhitarkanika wildlife sanctuary (BWS), India and measured circumference at breast height (CBH) and canopy tree height for 18 species. The estimated AGB range of a generic allometric equation was 9–474 Mg/ha for BWS, with a major representation of 9–347 Mg/ha. We utilized Sentinel-1 and ALOS-2/PALSAR-2 and derived their variables for AGB prediction. Compared to single sensor-based model, we observed higher prediction accuracy for combined sensor data (R² = 0.63, 0.87, 0.93; RMSE = 66.75, 39.95, 28.35 Mg/ha; MAE = 52.63, 24.21, 19.55 Mg/ha; and Bias = 3.42, 0.22, 2.15 Mg/ha for C, L and C & L bands respectively using a Generalized Additive Model (GAM) over Random Forest (RF), Gradient Boosting Machines (GBM) and Support Vector Regression (SVR). The higher uncertainty pixels represented seasonal grassland and scrubs in the swampy areas and along the fringes of the creeks that experience diurnal tidal fluctuations. This robust methodology can be replicated for AGB estimates in other mangrove ecosystems to meet the operational carbon accounting requirements of various entities.     

The role of environmental, root, and microbial biomass characteristics in soil respiration in temperate secondary forests of Northeast China

For secondary forests, the major forest resources in China (accounting for more than 50% of the national total), soil respiration (R _S) and the relationship between R _S and various biotic/abiotic factors are poorly understood. The objectives of the present study were to examine seasonal variations in soil respiration during the growing season, and to explore the factors affecting the variation in soil respiration rates for three forest types (Mongolian oak, Manchurian walnut and mixed forests) of temperate secondary forest in Northeast China. The results showed that (1) the maximum total R _S rate occurred in July, following a bell-shaped curve with season, (2) for all forest types, the total R _S was significantly influenced by soil temperature (P < 0.01), and did not significantly correlate with soil moisture, (3) compared with fine root biomass, coarse root biomass was more closely related with the root respiration in mixed forest (R ² = 0.711, P = 0.017) and in Manchurian walnut forest (R ² = 0.768, P = 0.010), and (4) microbial biomass carbon (MBC) and nitrogen were significantly correlated with heterotrophic R _S in Mongolian oak forest (R ² = 0.664, P = 0.026; R ² = 0.784, P = 0.008, respectively) and in mixed forest (R ² = 0.918, P = 0.001; R ² = 0.967, P = 0.001, respectively). We can conclude that in temperate secondary forests: (1) the R _S rate and the relationships between R _S and abiotic/biotic factors change greatly with forest types, and (2) R _S is strongly influenced by soil temperature, MBC, microbial biomass nitrogen and coarse root biomass in temperate secondary forests.     

Development of a macrophyte-based index of biotic integrity for Minnesota lakes

Traditional approaches for managing aquatic resources have often failed to account for effects of anthropogenic disturbances on biota that are not directly reflected by chemical and physical proxies of environmental condition. The index of biotic integrity (IBI) is a potentially effective assessment method to integrate ecological, functional, and structural aspects of aquatic systems. A macrophyte-based IBI was developed for Minnesota lakes to assess the ability of aquatic plant communities to indicate environmental condition. The index was developed using quantitative point intercept vegetation surveys for 97 lakes that represent a range of limnological and watershed characteristics. We followed an approach similar to that used in Wisconsin to develop the aquatic macrophyte community index (AMCI). Regional adaptation of the AMCI required the identification of species representative of macrophyte communities in Minnesota. Metrics and scaling methods were also substantially modified to produce a more empirically robust index. Regression analyses indicated that IBI scores reflected statewide differences in lake trophic state (R² = 0.57, F = 130.3, df = 1, 95, p < 0.005), agricultural (R² = 0.51, F = 83.0, df = 1, 79, p < 0.005), urban (R² = 0.22, F = 23.0, df = 1, 79, p < 0.005), and forested land uses (R² = 0.51, F = 84.7, df = 1, 79, p < 0.005), and county population density (R² = 0.14, F = 16.6, df = 1, 95, p < 0.005). Variance partitioning analyses using multiple regression models indicated a unique response of the IBI to human-induced stress separate from a response to natural lake characteristics. The IBI was minimally affected by differences in sample point density as indicated by Monte Carlo analyses of reduced sampling effort. Our analysis indicates that a macrophyte IBI calibrated for Minnesota lakes could be useful for identifying differences in environmental condition attributed to human-induced stress gradients.     

Seasonal Variation in Onset of Myocardial Infarction—A 7‐year single‐center study in Italy

Like many other serious acute cardiovascular and cerebrovascular events, acute myocardial infarction (AMI) shows seasonal variation, being most frequent in the winter. We sought to investigate whether age, gender, and hypertension influence this pattern. We studied 4014 (2259 male and 1755 female) consecutive patients with AMI presenting to St. Anna Hospital of Ferrara, Italy between January 1998 and December 2004. Some 1131 (28.2%) of the AMI occurred in persons <65 yrs of age, and 2883 (71.8%) in those ≥65 yrs of age. AMI was over‐represented in males (82% in the <65 yr group vs. 56.6% in the ≥65 yr group (χ²=13.99; p<0.001). Hypertension had been previously documented in 964 (24%) of the cases. There were 691 (17.2%) fatal case outcomes; fatal outcomes were significantly higher among the 3054 normotensive (n=614 or 20.1%) than the 964 hypertensive cases (n=77 or 8%; χ²=74.94, p<0.001). AMIs were most frequent in the winter (n=1076 or 26.8% of all the events) and least in the summer (n=924 or 23.0% of all the events; χ²=12.36, p=0.007). The greatest number of AMIs occurred in December (n=379 or 9.44%), and the lowest number in September (n=293 or 7.3%; χ²=11.1, p=0.001). Inferential chronobiological (Cosinor) analysis identified a significant annual pattern in AMI in those ≥65 yrs of age, with a peak between December and February—January for the total sample (p<0.005), January for the sample of males (p=0.014), February for fatal infarctions (p=0.017), and December for non‐fatal infarctions (p=0.006). No such temporal variations were detected in any of these categories in those <65 yrs of age. The annual pattern in AMI was also verified by Cosinor analysis in the following hypertensive subgroups: hypertensive males (n=552: January, p=0.014), non‐fatal infarctions in hypertensive patients (n=887: January, p=0.018), and elderly normotensives (n=1556: November, p=0.007).     

Effect of water temperature on activity of wintering age‐0 Acipenser transmontanus and A. brevirostrum: An artificial stream study

The effect of water temperature on behaviour and life history of wintering age‐0 = young‐of‐the‐year (YOY) northern sturgeons (populations using winter refuge habitat) is poorly understood. Using artificial stream tanks, we observed the effect of water temperature on 1) day‐time activity of cultured YOY Kootenai River white sturgeon, Acipenser transmontanus, during two winters (2008 and 2009–2010), and 2) observed day‐time activity of cultured YOY Connecticut River shortnose sturgeon, A. brevirostrum, in the winter, 2009–2010. Activity of YOY was measured every 2 to 7 days by visual or video observations on each fish to determine the mean number of 10 cm² square gridlines on the tank bottom crossed by all fish in each replicate tank (two replicate tanks, 10 fish in each tank). Daily water temperature was recorded by a logger in one tank every 20 min, 24 hr per day. In 2008, YOY A. transmontanus activity was positively related to decreasing mean daily temperature (R² = 0.96, p < 0.01) with 0 to 5 gridlines (range) crossed by all fish during observation periods at the coldest temperature (≤3°C). During the winter of 2009–2010, activity of both species was significantly related to decreasing temperature, and again, a mean of 0 to 5 gridlines (range) were crossed by fish at ≤3°C. We accept the hypothesis that YOY of both species are mostly inactive in the day when winter water temperature decreases to ≤3°C. Using the daytime inactivity temperature threshold of 3°C for YOY, and recent temperatures in river reaches where wild wintering YOY likely occur, we predict (a) wild wintering YOY A. transmontanus are moderately active in the day, may be energy challenged due to elevated temperatures from the warm river discharge by Libby Dam, and have poor survival in the regulated Kootenay River, and (b) wintering YOY Connecticut River A. brevirostrum are moderately active most winter months due to elevated natural river temperatures and may be energy challenged. More research is needed on YOY wintering activity and energetics relative to temperature to insure management of river temperature includes conservation of sturgeons.     

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R² = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower‐based measurement of SIF and leaf‐level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R² = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F_q’/F_m’, the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R² = 0.79; P < 0.0001). We also found that canopy SIF and SIF‐derived GPP (GPP_SIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R² = 0.65 for canopy GPP_SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R² = 0.35 for canopy GPP_SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R² = 0.36 for canopy GPP_SIF and NDVI; P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales.     

Emperipolesis mediated by CD8+ T cells correlates with biliary epithelia cell injury in primary biliary cholangitis

Primary biliary cholangitis (PBC) is an autoimmune disease characterized by chronic destruction of the bile ducts. A major unanswered question regarding the pathogenesis of PBC is the precise mechanisms of small bile duct injury. Emperipolesis is one of cell‐in‐cell structures that is a potential histological hallmark associated with chronic hepatitis B. This study aimed to clarify the pathogenesis and characteristics of emperipolesis in PBC liver injury. Sixty‐six PBC patients, diagnosed by liver biopsy combined with laboratory test, were divided into early‐stage PBC (stages I and II, n = 39) and late‐stage PBC (stages III and IV, n = 27). Emperipolesis was measured in liver sections stained with haematoxylin‐eosin. The expressions of CK19, CD3, CD4, CD8, CD20, Ki67 and apoptosis of BECs were evaluated by immunohistochemistry or immunofluorescence double labelling. Emperipolesis was observed in 62.1% of patients with PBC, and BECs were predominantly host cells. The number of infiltrating CD3⁺ and CD8⁺ T cells correlated with the advancement of emperipolesis (R² = 0.318, P < .001; R² = 0.060, P < .05). The cell numbers of TUNEL‐positive BECs and double staining for CK19 and Ki67 showed a significant positive correlation with emperipolesis degree (R² = 0.236, P < .001; R² = 0.267, P < .001). We conclude that emperipolesis mediated by CD8⁺ T cells appears to be relevant to apoptosis of BEC and thus may aggravate the further injury of interlobular bile ducts.     

Climatic dependency of soil organic carbon isotopic composition along the S–N Transect from 34°N to 52°N in central-east Asia

We explored the relationships between surface-soil (1–20 cm) organic carbon isotopic signatures and associated climatic factors in central-east Asia in an attempt to develop transfer functions that can be used to retrieve the paleoclimatic information stored in the thick eolian–paleosol sequences within the area. Our analysis shows that the negative correlation between the surface-soil organic δ¹³C values and the mean annual precipitation is robust (R² = 0.453; n = 196; p < 0.05) and the negative correlation with the growing-season (April–September) precipitation is more significant (R² = 0.4966; n = 196; p < 0.05). Our study further shows that the positive correlation between the surface-soil organic δ¹³C values and mean growing-season aridity is most significant (R² = 0.5805; n = 196; p < 0.05). We have smoothed both the organic δ¹³C values and the mean growing-season aridity values using a 3-point moving-window average-filter method in an attempt to remove some of random errors and found that the positive correlation between the two is further increased (R² =  0.7784; n =  192; p < 0.05). These robust linear relationships demonstrate their value in reconstructing paleoclimate changes in the study area. The documented climatic dependency of the surface-soil carbon isotopic composition in the study area might have resulted both from the humidity-related isotopic enrichment processes of the dominant C₃ plants (stomatal conductance and photosynthetic discrimination) and from the aridity-related abundance of C₄ plants (mainly Chenopodiaceae species) along the S–N bioclimatic gradient.     

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。     

Melanin quantification by in vitro and in vivo analysis of near‐infrared fluorescence

Objective measurements of melanin can provide important information for differentiating melanoma from benign pigmented lesions and in assessing pigmentary diseases. Herein, we evaluate near‐infrared (NIR) fluorescence as a possible tool to quantify melanin. Various concentrations of in vitro Sepia melanin in tissue phantoms were measured with NIR fluorescence and diffuse reflectance spectroscopy. Similar optic measurements were conducted in vivo on 161 normal human skin sites. Diffuse reflectance spectroscopy was used to quantify the melanin content via Stamatas–Kollias algorithm. At physiologic concentrations, increasing in vitro melanin concentrations demonstrated higher fluorescence that was linearly correlated (R² = 0.99, p < .001). At higher concentrations, the fluorescence signal plateaued. A linear relationship was also observed with melanin content in human skin (R² = 0.59, p < .001). Comparing the fluorescence and reflectance signals with in vitro and in vivo samples, the estimated melanin concentration in human skin ranged between 0 and 1.25 mg/ml, consistent with previous quantitative studies involving invasive methods.     

Solar‐induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO‐2 and flux tower observations

Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R² = 0.72, p < 0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R² = 0.57–0.79, p < 0.0001) except evergreen broadleaf forests (R² = 0.16, p < 0.05) at the daily timescale. A higher slope was found for C₄ grasslands and croplands than for C₃ ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies.     

Water-use efficiency of one C3 and two C4 grasses in response to varying soil moisture and herbage-removal levels in a seasonally dry tropical region

In a seasonally dry tropical region the water use efficiency (WUE) of three grasses (C₃ winter annualPolypogon monspeliensis, C₄ perennialDichanthium annulatum and C₄ warm seasonal annualEchinochloa colonum) was evaluated during summer and winter under nine experimental conditions (3 soil moisture×3 herbage removal). Generally leaf water status and transpiration rate decreased with soil moisture stress and increased with clipping intensity. During winter the transpiration rate of Dichanthium was much lower than that of Polypogon and its own rate in summer. Both soil moisture stress and clipping intensity increased the WUE in all instances. Despite differences in photosynthetic type, growing season and life form, these grasses exhibited broadly similar positive relationships, across nine treatments for WUE: soil moisture stress, and water consumption: production. The range of WUE (g. mm^–1) calculated on TNP through the nine treatments was: summer—Dichanthium 2.9–10.0, Echinochloa 2.0–6.7; winter—Dichanthium 4.3–36.3, Polypogon 1.9–12.0.     

Characteristics of circulating CD31+ cells from patients with coronary artery disease

Recently, we reported the properties of CD31‐expressing cells in healthy individuals. However, the characteristics of CD31‐expressing cells derived from coronary artery disease (CAD) patients remain unknown. This study aimed to investigate the relationship between circulating CD31⁺ cells and CAD as well as their biological characteristics. Analysis with flow cytometry revealed that CD31⁺ cells (C‐CD31) from the peripheral blood (PB) of CAD patients exhibited low levels of T‐cell marker and high levels of macrophage marker compared with the PB‐CD31⁺ cells from healthy individuals (H‐CD31). In addition, the expression levels of multiple pro‐angiogenic and chemokine genes were significantly down‐regulated in C‐CD31. However, inflammatory gene IL‐1α was highly up‐regulated in C‐CD31. Patients with unstable angina (UA) had significantly more CD31⁺ cells in the PB than healthy control group (P < 0.001). Moreover, there were significant correlations between the number of CD31⁺ cells and cardiovascular (CV) disease activity (R = 0.318, P = 0.006) and the number of diseased coronaries (R = 0.312, P = 0.005). For the diagnostic category of UA, the area under curve was 0.803 (P < 0.001). In conclusion, C‐CD31 have impaired angiogenic potential and the number of circulating CD31⁺ cells were correlated with CV risk. These findings may contribute to the understanding of the pathogenesis of CAD.     

Inline Real-Time Near-Infrared Granule Moisture Measurements of a Continuous Granulation–Drying–Milling Process

The purpose of this research was to use inline real-time near-infrared (NIR) to measure the moisture content of granules manufactured using a commercial production scale continuous twin-screw granulator fluid-bed dryer milling process. A central composite response surface statistical design was used to study the effect of inlet air temperature and dew point on granule moisture content. The NIR moisture content was compared to Karl Fischer (KF) and loss on drying (LOD) moisture determinations. Using multivariate analysis, the data showed a statistically significant correlation between the conventional methods and NIR. The R ² values for predicted moisture content by NIR versus KF and predicted moisture values by NIR versus LOD were 0.94 (p < 0.00001) and 0.85 (p < 0.0002), respectively. The adjusted R ² for KF versus LOD correlation was 0.85 (p < 0.0001). Analysis of the response surface design data showed that inlet air temperature over a range of 35–55°C had a significant linear impact on granule moisture content as measured by predicted NIR (adjusted R ² = 0.84, p < 0.02), KF (adjusted R ² = 0.91, p < 0.0001), and LOD (adjusted R ² = 0.85, p < 0.0006). The inlet air dew point range of 10–20°C did not have a significant impact on any of the moisture measurements.