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Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Accurate estimate of the seasonal leaf area index (LAI) in croplands is required for understanding not only intra- and inter-annual crop development, but also crop management. Lack of consideration in different growth phases in the relationship between LAI and vegetation indices (VI) often results in unsatisfactory estimation in the seasonal course of LAI. In this study, we partitioned the growing season into two phases separated by maximum VI ( VI max ) and applied the general regression model to the data gained from two phases. As an alternative method to capture the influence of seasonal phenological development on the LAI-VI relationship, we developed a consistent development curve method and compared its performance with the general regression approaches. We used the Normalized Difference VI (NDVI) and the Enhanced VI (EVI) from the rice paddy sites in Asia (South Korea and Japan) and Europe (Spain) to examine its applicability across different climate conditions and management cycles. When the general regression method was used, separating the season into two phases resulted in no better estimation than the estimation obtained with the entire season observation due to an abrupt change in seasonal LAI occurring during the transition between the before and after VI max . The consistent development curve method reproduced the seasonal patterns of LAI from both NDVI and EVI across all sites better than the general regression method. Despite less than satisfactory estimation of a local LAI max , the consistent development curve method demonstrates improvement in estimating the seasonal course of LAI. The method can aid in providing accurate seasonal LAI as an input into ecological process-based models.

Background Compensation of contralateral kidney function after living-donor kidney donation is well known, and many predictive factors have been proposed. However, no prediction model has been proposed. This study was performed to establish a tool with which to estimate the degree of compensation of the contralateral kidney after living-donor kidney donation. Methods We retrospectively analyzed 133 living donors for renal transplantation in our institution. We defined a favorable compensation as a post-donation estimated glomerular filtration rate (eGFR) at 1 year (calculated by the Chronic Kidney Disease Epidemiology Collaboration equation) of > 60% of the pre-donation eGFR. We analyzed the living donors’ clinical characteristics and outcomes. Results The median (range) donor age was 59 (24–79) years, median (range) body mass index was 22.9 (16.8–32.7) kg/m 2 , and median (range) body surface area was 1.6 (1.3–2.0) m 2 . All donors were Japanese, and 73% of the donors were biologically related. The median (range) donor pre-donation eGFR was 108.7 (82–144) ml/min/1.73 m 2 , and the median (range) post-donation eGFR at 1 year was 86.9 (43–143) ml/min/1.73 m 2 . Eighty-six percent of donors had compensatory hypertrophy. In the univariate analysis, age, female sex, history of hypertension, body surface area, and pre-donation eGFR were significantly associated with hypertrophy ( p  < 0.05). In the multivariate analysis, age, female sex, history of hypertension, and ratio of the remnant kidney volume to body weight were significantly associated with hypertrophy ( p  < 0.05). Based on these results, we created a compensation prediction score (CPS). The median (range) CPS was 8.7 (1.1–17.4). Receiver operating characteristic analysis showed strong diagnostic accuracy for predicting favorable compensation (area under the curve, 0.958; 95% confidence interval, 0.925–0.991, p  < 0.001). The optimal cut-off value of the CPS was 5.0 (sensitivity, 92.0%; specificity, 89.5%). The CPS had a strong positive correlation with the post-donation eGFR (R = 0.797, p  < 0.001). Conclusion The CPS might be useful tool with which to predict a favorable compensation of the contralateral kidney and remnant kidney function. If the CPS is low, careful management and follow-up might be necessary. Further investigations are needed to validate these findings in larger populations.

Non-dispersive infrared CO 2 /H 2 O gas analysers produce erroneous CO 2 outputs when CO 2 is measured in humid air, unless a correction for water vapour cross-sensitivity is applied. Spectroscopic cross-sensitivities arising from direct absorption interference and from the pressure broadening effect are significant in CO 2 flux measurements by the eddy covariance technique using open-path gas analysers over the ocean, as opposed to land-surface measurements, where CO 2 fluxes are orders of magnitude larger. In this study, a widely used analyser with manufacturer-determined correction coefficients for both cross-sensitivities was tested by laboratory experiments. Our results showed that the correction coefficient for direct absorption interference was not optimised to calculate CO 2 flux accurately, and that the correction coefficient for the pressure broadening caused overestimation of the CO 2 mixing ratio flux in the same direction as the water vapour flux. Overestimations of open-path eddy covariance measurements of upward CO 2 fluxes in previous ocean observations probably resulted from inaccuracies in both of these correction coefficients. We also found that slight changes in spectroscopic cross-sensitivities due to contamination of the analyser's optical windows by sea salt caused a low bias in CO 2 outputs with increasing H 2 O; however, this contamination effect was not always observed in repeated tests under different contamination conditions. We suggest that previously proposed methods for correcting the effect of optical window contamination is of limited value and that measurement of small CO 2 fluxes by the open-path eddy covariance technique over the ocean should be performed after confirming the spectroscopic cross-sensitivity and ensuring that the optical windows are as clean as possible.

A prospective randomized clinical trial assessed the efficacy and tolerance of micafungin compared with that of standard fluconazole treatment in patients undergoing hematopoietic stem cell transplantation (HSCT). Adult patients ( n  = 106) were randomly assigned to receive prophylaxis with either micafungin 150 mg ( n  = 52), or fluconazole 400 mg ( n  = 52). Success was defined as the absence of suspected, proven, or probable invasive fungal infection (IFI) through the end of therapy and the absence of proven or probable IFI through the end of the 4-week period following treatment. The overall efficacy of micafungin was comparable to that of fluconazole (94 vs. 88%; difference 6.0%; 95% confidence interval, −5.4 to +17.4%; P  = 0.295). A total of 2 (4.0%) of 50 patients in the micafungin arm and 6 (12.0%) of 50 patients in the fluconazole arm received empirical antifungal therapy ( P  = 0.06). Micafungin treatment did not result in increasing adverse effects and had a safe profile as fluconazole in neutropenic patients. This randomized trial indicates that the efficacy and tolerance of micafungin 150 mg was comparable to that of fluconazole 400 mg, suggesting that micafungin at 150 mg daily represents a valuable new treatment option for antifungal prophylaxis in HSCT recipients.

Methane ( CH 4 ) fluxes observed with the eddy-covariance technique using an open-path CH 4 analyzer and a closed-path CH 4 analyzer in a rice paddy field were evaluated with an emphasis on the flux correction methodology. A comparison of the fluxes obtained by the analyzers revealed that both the open-path and closed-path techniques were reliable, provided that appropriate corrections were applied. For the open-path approach, the influence of fluctuations in air density and the line shape variation in laser absorption spectroscopy (hereafter, spectroscopic effect) was significant, and the relative importance of these corrections would increase when observing small CH 4 fluxes. A new procedure proposed by Li-Cor Inc. enabled us to accurately adjust for these effects. The high-frequency loss of the open-path CH 4 analyzer was relatively large (11 % of the uncorrected covariance) at an observation height of 2.5 m above the canopy owing to its longer physical path length, and this correction should be carefully applied before correcting for the influence of fluctuations in air density and the spectroscopic effect. Uncorrected CH 4 fluxes observed with the closed-path analyzer were substantially underestimated (37 %) due to high-frequency loss because an undersized pump was used in the observation. Both the bandpass and transfer function approaches successfully corrected this flux loss. Careful determination of the bandpass frequency range or the transfer function and the cospectral model is required for the accurate calculation of CH 4 fluxes with the closed-path technique.

Background Preoperative characteristics of living kidney donors are commonly considered during donor selection and postoperative follow-up. However, the impact of preoperative uric acid (UA) levels is poorly documented. The aim of this study was to evaluate the association between preoperative serum UA levels and post-donation long-term events and renal function. Methods This was a single-center retrospective analysis of 183 living kidney donors. The donors were divided into high (≥5.5 mg/dl) and low (< 5.5 mg/dl) UA groups. We analyzed the relationship between preoperative UA levels and postoperative estimated glomerular filtration rate (eGFR), as well as adverse events (cardiovascular events and additional prescriptions for hypertension, gout, dyslipidemia, and diabetes mellitus), over 5 years after donation. Results In total, 44 donors experienced 52 adverse events over 5 years. The incidence of adverse events within 5 years was significantly higher in the high UA group than in the low UA group (50% vs. 24%, p  = 0.003); this was true even after the exclusion of hyperuricemia-related events ( p  = 0.047). UA emerged as an independent risk factor for adverse events ( p  = 0.012). Donors with higher UA levels had lower eGFRs after donation, whereas body mass index, hemoglobin A1c, blood pressure, and low-density lipoprotein cholesterol did not have any impact on the eGFR. Conclusions The findings suggest that preoperative UA levels should be considered during donor selection and postoperative follow-up.

The DNDC (DeNitrification–DeComposition)-Rice model is one of the most advanced process-based models for estimating greenhouse gas emissions from paddy fields, and can be used to simulate the N balance of a paddy field. In this study, we validated DNDC-Rice using field observation data, including N balance data, and revealed problems when using the model to evaluate a paddy field’s N balance. Using a modified process submodel for fixation of ammonium (NH 4 + ) ions by clay, DNDC-Rice simulated the dry weight of roots, stems, and grains well, but overestimated leaf dry weight. The normalized root-mean-square errors (nRMSEs) for the root, stem, grain, and leaf dry weights were 13, 16, 7, and 60 %, respectively. DNDC-Rice also overestimated the leaf area index (LAI) and leaf N content, with nRMSEs of 125 and 37 %, respectively. The overestimation of leaf dry weight and LAI resulted from overestimation of N uptake by rice and of N allocation to leaves. The high N uptake might have been caused by a high available soil N content. At harvesting, the simulated N balance (=N input − N output) was −38.8 kg N ha −1 , which was much lower than the N balance determined by observations and from relevant literature (12.8 kg N ha −1 ). The underestimation of the N balance resulted mostly from the model’s inability to calculate dry N deposition and N fixation as inputs and from overestimation of grain N uptake as outputs.

Aggregating and sharing the metadata of flux observation sites results in a strong collaboration among various fields of study. Such data sharing will also be a part of the future design of a tower flux observation network in Asia. The aim of this review is to comprehend the state of tower flux observation sites in Asia. There are 109 tower flux observation sites in Asia including 51 forest sites. There are more new sites under construction in Asia than in America and Europe. These sites range from the taiga in Siberia to the rainforest in Southeast Asia, and from the equatorial to polar Koeppen climate zones. There are many highly humid areas in Asia, not only at low latitudes but also at middle latitudes. This climate condition has developed unique vegetation such as lucidophyllous (evergreen broadleaf) forest, which is distributed in warm areas with high precipitation in the growing season. However, there are only a few observations taking place in lucidophyllous forest. Rice paddy fields are also unique land cover in Asia. It is important to accumulate long-term data for rice fields with their management records, because plant activity depends highly on both climate conditions and land-use management. Flux data, especially net ecosystem exchange and related elements, are used for widespread studies not only within the flux-research community but also in other fields of study, for example remote sensing. At present, however, both the quantity and quality of the data are not sufficient for these studies. Regarding the quantity, there are many recently established sites that have not published data yet; regarding quality, flux data include uncertainties caused by methodological problems. Flux researchers are required not only to obtain flux data but also to improve their quality. Meanwhile, data users must understand there are still uncertainties in flux data.

We previously reported that allografts from living donors may have pre-existing histopathological damages, defined as the combination of interstitial fibrosis (ci), tubular atrophy (ct), and arteriolar hyalinosis (ah) scores of ≧1, according to the Banff classification. We examined preoperative characteristics to identify whether the degree of these damages was related to metabolic syndrome-related factors of donors. We conducted a single-center cross-sectional analysis including 183 living kidney donors. Donors were divided into two groups: chronic change (ci + ct ≧ 1 ∩ ah ≧ 1, n = 27) and control (n = 156). Preoperative characteristics, including age, sex, blood pressure, hemoglobin A1c (HbA1c), aortic calcification index (ACI), and psoas muscle index (PMI), were analyzed. Comparing the groups, the baseline estimated glomerular filtration rate was not significantly different; however, we observed a significant difference for ACI (p = 0.009). HbA1c (p = 0.016) and ACI (p = 0.006) were independent risk factors to predict pre-existing histopathological damages, whereas PMI was not. HbA1c correlated with ct scores (p = 0.035), and ACI correlated with ci (p = 0.005), ct (p = 0.021), and ah (p = 0.017). HbA1c and ACI may serve as preoperative markers for identifying pre-existing damages on the kidneys of living donors.