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• A large multi-model study predicting wheat phenology in Australia was performed. • Calibration and evaluation datasets were independently drawn from the same population. • Mean absolute prediction error ranged from 6 to 20 days (median 9 days). • Two thirds of modeling groups predicted better than a simple temperature sum. • Variability between groups using the same model structure was substantial. Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fields in the major wheat growing regions of Australia under current climatic conditions and with current local management practices. The environments used for calibration and for evaluation were both sampled from this same target population. The calibration and evaluation environments had neither sites nor years in common, so this is a rigorous evaluation of the ability of modeling groups to predict phenology for new sites and weather conditions. Mean absolute error (MAE) for the evaluation environments, averaged over predictions of three phenological stages and over modeling groups, was 9 days, with a range from 6 to 20 days. Predictions using the multi-modeling group mean and median had prediction errors nearly as small as the best modeling group. About two thirds of the modeling groups performed better than a simple but relevant benchmark, which predicts phenology by assuming a constant temperature sum for each development stage. The added complexity of crop models beyond just the effect of temperature was thus justified in most cases. There was substantial variability between modeling groups using the same model structure, which implies that model improvement could be achieved not only by improving model structure, but also by improving parameter values, and in particular by improving calibration techniques. [ABSTRACT FROM AUTHOR]

Background: Prevalence of hepatocellular carcinoma (HCC) is increasing, especially in patients with metabolic dysfunction-associated steatotic liver disease (MASLD)., Aim: To investigate rifaximin (RIF) effects on epigenetic/autophagy markers in animals., Methods: Adult Sprague-Dawley rats were randomly assigned ( n = 8, each) and treated from 5-16 wk: Control [standard diet, water plus gavage with vehicle (Veh)], HCC [high-fat choline deficient diet (HFCD), diethylnitrosamine (DEN) in drinking water and Veh gavage], and RIF [HFCD, DEN and RIF (50 mg/kg/d) gavage]. Gene expression of epigenetic/autophagy markers and circulating miRNAs were obtained., Results: All HCC and RIF animals developed metabolic-dysfunction associated steatohepatitis fibrosis, and cirrhosis, but three RIF-group did not develop HCC. Comparing animals who developed HCC with those who did not, miR-122, miR-34a, tubulin alpha-1c (Tuba-1c) , metalloproteinases - 2 (Mmp2) , and metalloproteinases - 9 (Mmp9) were significantly higher in the HCC-group. The opposite occurred with Becn1 , coactivator associated arginine methyltransferase-1 ( Carm1 ), enhancer of zeste homolog-2 ( Ezh2 ), autophagy-related factor LC3A/B (Map1 Lc3b) , and p62/ sequestosome-1 ( p62/ SQSTM1 )- protein . Comparing with controls, Map1 Lc3b , Becn1 and Ezh2 were lower in HCC and RIF-groups ( P < 0.05). Carm1 was lower in HCC compared to RIF ( P < 0.05). Hepatic expression of Mmp9 was higher in HCC in relation to the control; the opposite was observed for p62/Sqstm1 ( P < 0.05). Expression of p62/SQSTM1 protein was lower in the RIF-group compared to the control ( P = 0.024). There was no difference among groups for Tuba-1c , Aldolase-B, alpha-fetoprotein, and Mmp2 ( P > 0.05). miR-122 was higher in HCC, and miR-34a in RIF compared to controls ( P < 0.05). miR-26b was lower in HCC compared to RIF, and the inverse was observed for miR-224 ( P < 0.05). There was no difference among groups regarding miR-33a, miR-143, miR-155, miR-375 and miR-21 ( P > 0.05)., Conclusion: RIF might have a possible beneficial effect on preventing/delaying liver carcinogenesis through epigenetic modulation in a rat model of MASLD-HCC., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers' fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ., (© 2024. The Author(s).)

Baccharis anomala DC. (BA) is a plant species found in the tropical regions of South America and is widely used for its hepatoprotective effects, as well as for the treatment of gastrointestinal diseases. Studies have recently reported its antioxidant and anti-inflammatory potential. BA extract can reverse the activated phenotype of hepatic stellate cells (HSC), which plays a central role in extracellular matrix (ECM) deposition in the development of liver fibrosis. Thus, this study aimed to evaluate the effects of the treatment with BA extract on liver fibrosis in a CCl 4 -induced liver fibrosis model in BALB/c mice. Methanolic extract was obtained from BA leaves, a gas chromatography/mass spectrometry (GC/MS) to detect the compounds present was performed, and then administered by intraperitoneal injection in Balb/C mice at a concentration of 50 and 100 mg/kg together with the administration of CCl 4 for inducing liver fibrosis. After 10 weeks, blood analysis, histopathology, oxidative stress, as well as protein and gene expression in the hepatic tissue were performed. Treatment with BA extract was able to reduce profibrotic markers by reducing the expression of α-SMA and Col-1 proteins, as well as reducing the formation of free radicals and lipid peroxidation. (BA extract showed anti-inflammatory effects in the liver by suppressing NF-kB activation and reducing gene expression of signaling targets (IL-6 and iNOS). The data obtained showed that BA extract has antifibrotic and anti-inflammatory effects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In pulmonary fibrosis, the proliferation of fibroblasts and their differentiation into myofibroblasts is often caused by tissue damage, such as oxidative damage caused by reactive oxygen species, which leads to progressive rupture and thus destruction of the alveolar architecture, resulting in cell proliferation and tissue remodeling. Bezafibrate (BZF) is an important member of the peroxisome proliferator-activated receptor (PPARs) family agonists, used in clinical practice as antihyperlipidemic. However, the antifibrotic effects of BZF are still poorly studied. The objective of this study was to evaluate the effects of BZF on pulmonary oxidative damage in lung fibroblast cells. MRC-5 cells were treated with hydrogen peroxide (H 2 O 2 ) to induce oxidative stress activation and BZF treatment was administered at the same moment as H 2 O 2 induction. The outcomes evaluated were cell proliferation and cell viability; oxidative stress markers such as reactive oxygen species (ROS), catalase (CAT) levels and thiobarbituric acid reactive substances (TBARS); col-1 and α-SMA mRNA expression and cellular elasticity through Young's modulus analysis evaluated by atomic force microscopy (AFM). The H 2 O 2 -induced oxidative damage decreased the cell viability and increased ROS levels and decreased CAT activity in MRC-5 cells. The expression of α-SMA and the cell stiffness increased in response to H 2 O 2 treatment. Treatment with BZF decreased the MRC-5 cell proliferation, ROS levels, reestablished CAT levels, decreased the mRNA expression of type I collagen protein (col-1) and α-smooth muscle actin (α-SMA), and cellular elasticity even with H 2 O 2 induction. Our results suggest that BZF has a potential protective effect on H2O2-induced oxidative stress. These results are based on an in vitro experiment, derived from a fetal lung cell line and may emerge as a possible new therapy for the treatment of pulmonary fibrosis., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background & Aims: Portal hypertension (PH) is a frequent and severe clinical syndrome associated with chronic liver disease. Considering the mechanobiological effects of hydrostatic pressure and shear stress on endothelial cells, we hypothesised that PH might influence the phenotype of liver sinusoidal endothelial cells (LSECs) during disease progression. The aim of this study was to investigate the effects of increased hydrodynamic pressure on LSECs and to identify endothelial-derived biomarkers of PH., Methods: Primary LSECs were cultured under normal or increased hydrodynamic pressure within a pathophysiological range (1 vs . 12 mmHg) using a microfluidic liver-on-a-chip device. RNA sequencing was used to identify pressure-sensitive genes, which were validated in liver biopsies from two independent cohorts of patients with chronic liver disease with PH (n = 73) and participants without PH (n = 23). Biomarker discovery was performed in two additional independent cohorts of 104 patients with PH and 18 patients without PH., Results: Transcriptomic analysis revealed marked deleterious effect of pathological pressure in LSECs and identified chromobox 7 ( CBX7 ) as a key transcription factor diminished by pressure. Hepatic CBX7 downregulation was validated in patients with PH and significantly correlated with hepatic venous pressure gradient. MicroRNA 181a-5p was identified as pressure-induced upstream regulator of CBX7. Two downstream targets inhibited by CBX7, namely, E-cadherin (ECAD) and serine protease inhibitor Kazal-type 1 (SPINK1), were found increased in the bloodstream of patients with PH and were highly predictive of PH and clinically significant PH., Conclusions: We characterise the detrimental effects of increased hydrodynamic pressure on the sinusoidal endothelium, identify CBX7 as a pressure-sensitive transcription factor, and propose the combination of two of its reported products as biomarkers of PH., Impact and Implications: Increased pressure in the portal venous system that typically occurs during chronic liver disease (called portal hypertension) is one of the main drivers of related clinical complications, which are linked to a higher risk of death. In this study, we found that pathological pressure has a harmful effect on liver sinusoidal endothelial cells and identified CBX7 as a key protein involved in this process. CBX7 regulates the expression of E-cadherin and SPINK1, and consequently, measuring these proteins in the blood of patients with chronic liver disease allows the prediction of portal hypertension and clinically significant portal hypertension., Competing Interests: The authors declare no competing financial interests. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2023 The Author(s).)

Agricultural soils can act as a sink for large quantities of soil organic carbon (SOC) but can also be sources of carbon to the atmosphere. The international standard for assessing SOC stock and measuring stock change stipulates fixed depth sampling to at least 30 cm. The tendency of bulk density (BD) to decrease with decreasing disturbance and increasing SOC concentration and the assumption of constant SOC and BD within this depth profile promotes error in the estimates of SOC stock. A hypothetical but realistic change in BD from 1.5 to 1.1 g cm -3 from successive fixed depth sampling to 30 cm underestimates SOC stock change by 17%. Significant effort has been made to evaluate and reduce this fixed depth error by using the equivalent soil mass (ESM) approach, but with limited adoption. We evaluate the error in SOC stock assessment and change generated from fixed depth measurements over time relative to the ESM approach and propose a correction that can be readily adopted under current sampling and analytical methods. Our approach provides a more accurate estimate of SOC stock accumulation or loss that will help incentivize management practice changes that reduce the environmental impacts of agriculture and further legitimize the accounting practices used by the emerging carbon market and organizations that have pledged to reduce their supply chain greenhouse gas (GHG) footprints., (© 2023. The Author(s).)

Plants remove carbon dioxide from the atmosphere through photosynthesis. Because agriculture's productivity is based on this process, a combination of technologies to reduce emissions and enhance soil carbon storage can allow this sector to achieve net negative emissions while maintaining high productivity. Unfortunately, current row-crop agricultural practice generates about 5% of greenhouse gas emissions in the United States and European Union. To reduce these emissions, significant effort has been focused on changing farm management practices to maximize soil carbon. In contrast, the potential to reduce emissions has largely been neglected. Through a combination of innovations in digital agriculture, crop and microbial genetics, and electrification, we estimate that a 71% (1,744 kg CO 2 e/ha) reduction in greenhouse gas emissions from row crop agriculture is possible within the next 15 y. Importantly, emission reduction can lower the barrier to broad adoption by proceeding through multiple stages with meaningful improvements that gradually facilitate the transition to net negative practices. Emerging voluntary and regulatory ecosystems services markets will incentivize progress along this transition pathway and guide public and private investments toward technology development. In the difficult quest for net negative emissions, all tools, including emission reduction and soil carbon storage, must be developed to allow agriculture to maintain its critical societal function of provisioning society while, at the same time, generating environmental benefits., Competing Interests: Competing interest statement: D.L.N. is an employee of Benson Hill, a seed company that aims to produce sustainable and nutritious agricultural products. P.N.B. is cofounder and chair of the Scientific Advisory Board of High Fidelity Genetics, a technology company that aims to improve crop root traits. B.B. is a cofounder of CiBO Technologies, a crop modeling and agronomy company with digital agriculture solutions.

The Experimental Zooprophylactic Institute of Southern Italy (Istitituto Zooprofilattico Sperimentale del Mezzogiorno, IZSM) is a public health institution operating within the Italian National Health Service. Over the past 5 years [IZSM] has promoted several research studies and interventions in an effort to tackle the 'Land of Fires' phenomenon, caused by the continued trafficking and uncontrolled incineration of waste that has affected some areas of Campania for decades. In this article, a mathematical model that generates a municipality index of environmental pressure is presented. The model was developed by a multidisciplinary team led by an environmental engineer and included researchers in the fields of veterinary and human medicine, biology and computer science. This model may serve as a geostratification tool useful for the design of human biomonitoring studies, although it may also be employed for strategic planning of remediation programs and public health interventions., Competing Interests: Financial & competing interests disclosure Translation services were supplied by Translated S.r.l., funding of which was supported by Istituto Zooprofilattico Sperimentale del Mezzogiorno. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No further writing assistance was utilized in the production of this manuscript., (© 2021 Carlo Buonerba.)

Warming generally leads to increased evaporative demand, altering the amount of water needed for growing crops. For the Midwest, some studies have suggested that reaching yield targets by 2050 will not be possible without additional precipitation or large expansion of irrigation. Here, we show that this claim is not supported by the historical summer climate trends, which indicate that the warming of daily average temperatures is largely driven by increases in minimum temperatures, while maximum temperatures have decreased. This has translated into a net decrease in vapor pressure deficit (VPD) and potential evapotranspiration (PET). With the increasing rainfall, this suggests that crop water deficits have likely become less frequent in the region despite the warming climate. By projecting these trends into 2050 and ancillary use of a crop model, we estimate minor changes in PET that would have minimal effects on corn yields (<6%) under persistence of these trends.

Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dataset composed of 5520 yield maps from 768 fields provided by farmers was used to investigate the influence of subfield yield distribution skewness on temporal variability. The data are used to test two intuitive algorithms for mapping stability: one based on standard deviation and the second based on pixel ranking and percentiles. The analysis of yield monitor data indicates that yield distribution is asymmetric, and it tends to be negatively skewed (p < 0.05) for all of the four crops analyzed, meaning that low yielding areas are lower in frequency but cover a larger range of low values. The mean yield difference between the pixels classified as high-and-stable and the pixels classified as low-and-stable was 1.04 Mg ha -1 for maize, 0.39 Mg ha -1 for cotton, 0.34 Mg ha -1 for soybean, and 0.59 Mg ha -1 for wheat. The yield of the unstable zones was similar to the pixels classified as low-and-stable by the standard deviation algorithm, whereas the two-way outlier algorithm did not exhibit this bias. Furthermore, the increase in the number years of yield maps available induced a modest but significant increase in the certainty of stability classifications, and the proportion of unstable pixels increased with the precipitation heterogeneity between the years comprising the yield maps., Supplementary Information: The online version contains supplementary material available at 10.1007/s11119-021-09810-1., (© The Author(s) 2021.)

Hepatocellular carcinoma (HCC) is the most prevalent type of tumor among primary liver tumors and is the second highest cause of cancer-related deaths worldwide. Current therapies are controversial, and more research is needed to identify effective treatments. A new synthetic compound, potassium 5-cyano-4-methyl-6-oxo-1,6-dihydropyridine-2-olate (CPBMF65), is a potent inhibitor of the human uridine phosphorylase-1 (hUP1) enzyme, which controls the cell concentration of uridine (Urd). Urd is a natural pyrimidine nucleoside involved in cellular processes, such as RNA synthesis. In addition, it is considered a promising biochemical modulator, as it may reduce the toxicity caused by chemotherapeutics without impairing its anti-tumor activity. Thus, the objective of this study is to evaluate the effects of CPBMF65 on the proliferation of the human hepatocellular carcinoma cell line (HepG2). Cell proliferation, cytotoxicity, apoptosis, senescence, autophagy, intracellular Urd levels, cell cycle arrest, and drug resistance were analyzed. Results demonstrate that, after incubation with CPBMF65, HepG2 cell proliferation decreased, mainly through cell cycle arrest and senescence, increasing the levels of intracellular Urd and maintaining cell proliferation reduced during chronic treatment. In conclusion, results show, for the first time, the ability of a hUP1 inhibitor (CPBMF65) to reduce HepG2 cell proliferation through cell cycle arrest and senescence.

Water deficit and water excess constitute severe stresses that limit crop yield and are likely to intensify as climate becomes more variable. Regional crop production aggregates for the US Midwest indicate widespread yield losses in past decades due to both extreme rainfall and water limited conditions, though the degree to which these weather impacts are related to site-specific factors such as landscape position and soils has not been examined in a systematic manner. This study offers observational evidence from a large sample of commercial crop fields to support the hypothesis that landscape position is the primary mediator of crop yield responses to weather within unstable field zones (i.e., zones where yields tend to fluctuate between high and low, depending on the year). Results indicate that yield losses in unstable zones driven by water excess and deficits occur throughout a wide range of seasonal rainfall, even simultaneously under normal weather. Field areas prone to water stress are shown to lag as much as 23-33% below the field average during drought years and 26-33% during deluge years. By combining large-scale spatial datasets, we identify 2.65 million hectares of water-stress prone cropland, and estimate an aggregated economic loss impact of $536M USD yr -1 , 4.0 million tons yr -1 of less CO 2 fixed in crop biomass, and 52.6 Gg yr -1 of more reactive N in the environment. Yield stability maps can be used to spatially implement adaptation practices to mitigate weather-induced stresses in the most vulnerable cropland.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed., (© 2017 John Wiley & Sons Ltd.)

Background and Objectives: As the population ages, osteometabolic diseases and osteoporotic fractures emerge, resulting in substantial healthcare resource utilization and impaired quality of life. Many types of mechanical stimulation have the potential of being recognized by bone cells after a mechanical sign is transformed into a biological one (a process called mechanotransduction). The therapeutic ultrasound (TU) is one of several resources capable of promoting bone cell mechanical stimulation. Therefore, the main purpose of present study was to evaluate the effect of TU on the proliferation of pre-osteoblasts using in vitro bioassays., Study Design/materials and Methods: We used MC3T3-E1 pre-osteoblast lineage cells kept in Alpha medium. Cells were treated using pulsed mode therapeutic ultrasound, with frequency of 1 MHz, intensity of 0.2 W/cm(2) (SATA), duty cycle of 20%, for 30 minutes. Nifedipine and rapamycin were used to further investigate the role of L-type Ca(2+) channels and mTOR pathway. Intracellular calcium, TGF-β1, magnesium, and the mRNA levels of osteopontin, osteonectin, NF-κB1, p38α were evaluated., Results: The results show that TU stimulates the growth of MC3T3-E1 cells and decreases the supernatant calcium and magnesium content. Also, it increases intracellular calcium, activates NF-κB1 and mTOR complex via p38α. Moreover, TU promoted a decrease in the TGF-β1 synthesis, which is a cell growth inhibitor., Conclusions: Therapeutic ultrasound, with frequency of 1 MHz, intensity of 0.2 W/cm(2) (SATA) and pulsed mode, for 30 minutes, was able to increase the proliferation of preosteoblast-like bone cells. This effect was mediated by a calcium influx, with a consequent activation of the mTOR pathway, through increased NF-κB1 and p38α., (© 2015 Wiley Periodicals, Inc.)

The response of wheat crops to elevated CO 2 (eCO 2 ) was measured and modelled with the Australian Grains Free-Air CO 2 Enrichment experiment, located at Horsham, Australia. Treatments included CO 2 by water, N and temperature. The location represents a semi-arid environment with a seasonal VPD of around 0.5 kPa. Over 3 years, the observed mean biomass at anthesis and grain yield ranged from 4200 to 10 200 kg ha -1 and 1600 to 3900 kg ha -1 , respectively, over various sowing times and irrigation regimes. The mean observed response to daytime eCO 2 (from 365 to 550 μmol mol -1 CO 2 ) was relatively consistent for biomass at stem elongation and at anthesis and LAI at anthesis and grain yield with 21%, 23%, 21% and 26%, respectively. Seasonal water use was decreased from 320 to 301 mm (P = 0.10) by eCO 2 , increasing water use efficiency for biomass and yield, 36% and 31%, respectively. The performance of six models (APSIM-Wheat, APSIM-Nwheat, CAT-Wheat, CROPSYST, OLEARY-CONNOR and SALUS) in simulating crop responses to eCO 2 was similar and within or close to the experimental error for accumulated biomass, yield and water use response, despite some variations in early growth and LAI. The primary mechanism of biomass accumulation via radiation use efficiency (RUE) or transpiration efficiency (TE) was not critical to define the overall response to eCO 2 . However, under irrigation, the effect of late sowing on response to eCO 2 to biomass accumulation at DC65 was substantial in the observed data (~40%), but the simulated response was smaller, ranging from 17% to 28%. Simulated response from all six models under no water or nitrogen stress showed similar response to eCO 2 under irrigation, but the differences compared to the dryland treatment were small. Further experimental work on the interactive effects of eCO 2 , water and temperature is required to resolve these model discrepancies., (© 2014 John Wiley & Sons Ltd.)

Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models., (© 2014 John Wiley & Sons Ltd.)

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information., (© 2014 John Wiley & Sons Ltd.)

(+)-Catechin is a type of catechin present in large amounts in açaí fruits and cocoa seeds. Besides its antioxidant and anti-inflammatory activities, little is known about its effects in the liver, especially during hepatic fibrosis. We report here the effects of (+)-catechin on hepatic stellate cells. (+)-Catechin induced quiescent phenotype in GRX cells, along with an increase in lipid droplets. Proliferator-activated receptor γ mRNA expression was upregulated, whereas type I collagen mRNA expression was downregulated. Pro-inflammatory cytokines were not influenced by (+)-catechin, whereas the levels of interleukin 10 were significantly increased. The data provide evidence that (+)-catechin can reduce hepatic stellate cell activation., (© 2013 International Federation for Cell Biology.)

Capsaicin, the active component of chili pepper, has been reported to have antiproliferative and anti-inflammatory effects on a variety of cell lines. In the current study, we aimed to investigate the effects of capsaicin during HSC activation and maintenance. Activated and freshly isolated HSCs were treated with capsaicin. Proliferation was measured by incorporation of EdU. Cell cycle arrest and apoptosis were investigated using flow cytometry. The migratory response to chemotactic stimuli was evaluated by a modified Boyden chamber assay. Activation markers and inflammatory cytokines were determined by qPCR, immunocytochemistry, and flow cytometry. Our results show that capsaicin reduces HSC proliferation, migration, and expression of profibrogenic markers of activated and primary mouse HSCs. In conclusion, the present study shows that capsaicin modulates proliferation, migration, and activation of HSC in vitro.

Hepatic stellate cells (HSC) play a key role in liver fibrogenesis. Activation of PPARγ and inhibition of fibrogenic molecules are potential strategies to block HSC activation and differentiation. Aware that the process of hepatic fibrosis involves inflammatory mediators, various anti-inflammatory substances have been studied in an attempt to revert fibrosis. The purpose of this study was to investigate the in vitro effects of fructose-1,6-bisphosphate (FBP) on HSC phenotype reversion. The results demonstrated that FBP induced quiescent phenotype in GRX cells via PPARγ activation. Significant decrease in type I collagen mRNA expression was observed in the first 24h of treatment. These events preceded the reduction of TGF-β1 and total collagen secretion. Thus, FBP promoted downregulation of HSC activation by its antifibrotic action. These findings demonstrate that FBP may have potential as a novel therapeutic agent for the treatment of liver fibrosis., (© 2013 Elsevier B.V. All rights reserved.)

Hepatic stellate cells (HSC) play a key role in liver fibrogenesis. Activation of PPARγ and inhibition of fibrogenic molecules are potential strategies to block HSC activation and differentiation. A number of natural products have been suggested to have antifibrotic effects for the de-activation and de-differentiation of HSCs. The purpose of this study was to investigate the in vitro effects of capsaicin on HSC de-activation and de-differentiation. The results demonstrated that capsaicin induced quiescent phenotype in GRX via PPARγ activation. Significant decrease in COX-2 and type I collagen mRNA expression was observed in the first 24 h of treatment. These events preceded the reduction of TGF-β1 and total collagen secretion. Thus, capsaicin promoted down-regulation of HSC activation by its antifibrotic and anti-inflammatory actions. These findings demonstrate that capsaicin may have potential as a novel therapeutic agent for the treatment of liver fibrosis.

Traditional methods for studying tree roots are destructive and labor intensive, but available nondestructive techniques are applicable only to small scale studies or are strongly limited by soil conditions and root size. Soil electrical resistivity measured by geoelectrical methods has the potential to detect belowground plant structures, but quantitative relationships of these measurements with root traits have not been assessed. We tested the ability of two-dimensional (2-D) DC resistivity tomography to detect the spatial variability of roots and to quantify their biomass in a tree stand. A high-resolution resistivity tomogram was generated along a 11.75 m transect under an Alnus glutinosa (L.) Gaertn. stand based on an alpha-Wenner configuration with 48 electrodes spaced 0.25 m apart. Data were processed by a 2-D finite-element inversion algorithm, and corrected for soil temperature. Data acquisition, inversion and imaging were completed in the field within 60 min. Root dry mass per unit soil volume (root mass density, RMD) was measured destructively on soil samples collected to a depth of 1.05 m. Soil sand, silt, clay and organic matter contents, electrical conductivity, water content and pH were measured on a subset of samples. The spatial pattern of soil resistivity closely matched the spatial distribution of RMD. Multiple linear regression showed that only RMD and soil water content were related to soil resistivity along the transect. Regression analysis of RMD against soil resistivity revealed a highly significant logistic relationship (n = 97), which was confirmed on a separate dataset (n = 67), showing that soil resistivity was quantitatively related to belowground tree root biomass. This relationship provides a basis for developing quick nondestructive methods for detecting root distribution and quantifying root biomass, as well as for optimizing sampling strategies for studying root-driven phenomena.