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In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying “photosynthetic phenology” from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a “chlorophyll/carotenoid index” (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA’s Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology.

There is an increasing necessity in reducing CO2 emissions and implementing clean energy technologies, and over the years the marine environment has shown a huge potential in terms of renewable energy. From this perspective, extracting marine renewable energy represents one of the most important technological challenges of the 21st century. In this context, the objective of the present work is to provide a new and comprehensive understanding concerning the global wave energy resources based on the most recent results coming from two different databases, ERA5 and the European Space Agency Climate Change Initiative for Sea State. In this study, an analysis was first made based only on the ERA5 data and concerns the 30-year period of 1989–2018. The mean wave power, defined as the energy flux per unit of wave-crest length, was evaluated at this step. Besides the spatial distribution of this parameter, its seasonal, inter, and mean annual variability was also assessed on a global scale. As a second step, the mean wave energy density per unit horizontal area was analyzed for a 27-year period (1992–2018) with both ERA5 and the satellite data from the European Space Agency being considered. The comparison indicates a relatively good concordance between the results provided by the two databases in terms of mean wave energy density, although the satellite data indicate slightly higher energy values.

A good knowledge of the quality of the satellite soil moisture products is of great importance for their application and improvement. This paper examines the performance of eight satellite-based soil moisture products, including the Soil Moisture Active Passive (SMAP) passive Level 3 (L3), the Soil Moisture and Ocean Salinity (SMOS) Centre Aval de Traitement des Données SMOS (CATDS) L3, the Japan Aerospace Exploration Agency (JAXA) Advanced Microwave Scanning Radiometer 2 (AMSR2) L3, the Land Parameter Retrieval Model (LPRM) AMSR2 L3, the European Space Agency (ESA) Climate Change Initiative (CCI) L3, the Chinese Fengyun-3B (FY3B) L2 soil moisture products at a coarse resolution of ~0.25°, and the newly released SMAP enhanced passive L3 and JAXA AMSR2 L3 soil moisture products at a medium resolution of ~0.1°. The ground soil moisture used for validation were collected from two well-calibrated and dense networks, including the Little Washita Watershed (LWW) network in the United States and the REMEDHUS network in Spain, each with different land cover. The results show that the SMAP passive soil moisture product outperformed the other products in the LWW network region, with an unbiased root mean square (ubRMSE) of 0.027 m3 m−3, whereas the FY3B soil moisture performed the best in the REMEDHUS network region, with an ubRMSE of 0.025 m3 m−3. The JAXA product performed much better at 0.25° than at 0.1°, but at both resolutions it underestimated soil moisture most of the time (bias < −0.05 m3 m−3). The SMAP-enhanced passive soil moisture product captured the temporal variation of ground measurements well, with a correlation coefficient larger than 0.8, and was generally superior to the JAXA product. The LPRM showed much larger amplitude and temporal variation than the ground soil moisture, with a wet bias larger than 0.09 m3 m−3. The underestimation of surface temperature may have contributed to the general dry bias found in the SMAP (−0.018 m3 m−3 for LWW and 0.016 m3 m−3 for REMEDHUS) and SMOS (−0.004 m3 m−3 for LWW and −0.012 m3 m−3 for REMEDHUS) soil moisture products. The ESA CCI product showed satisfactory performance with acceptable error metrics (ubRMSE < 0.045 m3 m−3), revealing the effectiveness of merging active and passive soil moisture products. The good performance of SMAP and FY3B demonstrates the potential in integrating them into the existing long-term ESA CCI product, in order to form a more reliable and useful product.

Microglia have a variety of functions in the brain, including synaptic pruning, CNS repair and mediating the immune response against peripheral infection. Microglia rapidly become activated in response to CNS damage. Depending on the nature of the stimulus, microglia can take a number of activation states, which correspond to altered microglia morphology, gene expression and function. It has been reported that early microglia activation following traumatic brain injury (TBI) may contribute to the restoration of homeostasis in the brain. On the other hand, if they remain chronically activated, such cells display a classically activated phenotype, releasing pro-inflammatory molecules, resulting in further tissue damage and contributing potentially to neurodegeneration. However, new evidence suggests that this classification is over-simplistic and the balance of activation states can vary at different points. In this article, we review the role of microglia in TBI, analyzing their distribution, morphology and functional phenotype over time in animal models and in humans. Animal studies have allowed genetic and pharmacological manipulations of microglia activation, in order to define their role. In addition, we describe investigations on the imaging of microglia using translocator protein (TSPO) PET and autoradiography, showing that microglial activation can occur in regions far remote from sites of focal injuries, in humans and animal models of TBI. Finally, we outline some novel potential therapeutic approaches that prime microglia/macrophages toward the beneficial restorative microglial phenotype after TBI.

The Construction Cost Index (CCI) is an important tool that is widely used in construction cost management to monitor cost fluctuations over time. Numerous studies have been conducted on CCI development and forecasting models, including time series, artificial intelligence, machine learning, and hybrid models. Therefore, this study seeks to reveal the complexity of CCI forecasting and identify the leading indicators, trends, and techniques for CCI prediction. A bibliometric analysis was conducted to explore the landscape in the CCI literature, focusing on co-occurrence, co-authorship, and citation analysis. These analyses revealed the frequent keywords, the most cited authors and documents, and the most productive countries. The research topics and clusters in the CCI forecasting process were presented, and directions for future research were suggested to enhance the prediction models. A case study was conducted to demonstrate the practical application of a forecasting model to validate its prediction reliability. Furthermore, this study emphasizes the need to integrate advanced technologies and sustainable practices into future CCI forecasting models. The findings are useful in enhancing the knowledge of CCI prediction techniques and serve as a base for future research in construction cost estimation.

Background This study aimed to investigate the potential mechanism of paeonol in the treatment of neuropathic pain. Methods Relevant mechanisms were explored through microglial pseudotime analysis and the use of specific inhibitors in cell experiments. In animal experiments, 32 SD rats were randomly divided into the sham operation group, the chronic constrictive injury (CCI) group, the ibuprofen group, and the paeonol group. We performed behavioral testing, ELISA, PCR, Western blotting, immunohistochemistry, and immunofluorescence analysis. Results The pseudotime analysis of microglia found that RhoA, Rock1, and p38MAPK were highly expressed in activated microglia, and the expression patterns of these genes were consistent with the expression trends of the M1 markers CD32 and CD86. Paeonol decreased the levels of M1 markers (IL1β, iNOS, CD32, IL6) and increased the levels of M2 markers (IL10, CD206, ARG‐1) in LPS‐induced microglia. The expression of iNOS, IL1β, RhoA, and Rock1 was significantly increased in LPS‐treated microglia, while paeonol decreased the expression of these proteins. Thermal hyperalgesia occurred after CCI surgery, and paeonol provided relief. In addition, paeonol decreased the levels of IL1β and IL8 and increased the levels of IL4 and TGF‐β in the serum of CCI rats. Paeonol decreased expression levels of M1 markers and increased expression levels of M2 markers in the spinal cord. Paeonol decreased IBA‐1, IL1β, RhoA, RhoA‐GTP, COX2, Rock1, and p‐p38MAPK levels in the spinal dorsal horn. Conclusion Paeonol relieves neuropathic pain by modulating microglial M1 and M2 phenotypes through the RhoA/p38 MAPK pathway. Experiment flow chart.

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

Introduction Sciatica causes intense pain. No satisfactory therapeutic drugs exist to treat sciatica. This study aimed to probe the potential mechanism of ferulic acid in sciatica treatment. Methods Thirty‐two SD rats were randomly divided into 4 groups: sham operation, chronic constriction injury (CCI), mecobalamin, and ferulic acid. We conducted RNA sequencing, behavioral tests, ELISA, PCR, western blotting, and immunofluorescence analysis. TAK‐242 and JSH23 were administered to RSC96 and GMI‐R1 cells to explore whether ferulic acid can inhibit apoptosis and alleviate inflammation. Results RNA sequencing showed that TLR4/NF‐κB pathway is involved in the mechanism of sciatica. CCI induced cold and mechanical hyperalgesia; destroyed the sciatic nerve structure; increased IL‐1β, IL‐6, TNF‐α, IL‐8, and TGF‐β protein levels and IL‐1β, IL‐6, TNF‐α, TGF‐β, TLR4, and IBA‐1 mRNA levels; and decreased IL‐10 and INF‐γ protein levels and IL‐4 mRNA levels. Immunohistochemistry showed that IBA‐1, CD32, IL‐1β, iNOS, nNOS, COX2, and TLR4 expression was increased while S100β and Arg‐1 decreased. CCI increased TLR4, IBA‐1, IL‐1β, iNOS, Myd88, p‐NF‐κB, and p‐p38MAPK protein levels. Treatment with mecobalamin and ferulic acid reversed these trends. Lipopolysaccharide (LPS) induced RSC96 cell apoptosis by reducing Bcl‐2 and Bcl‐xl protein and mRNA levels and increasing Bax and Bad mRNA and IL‐1β, TLR4, Myd88, p‐NF‐κB, and p‐p38MAPK protein levels, while ferulic acid inhibited cell apoptosis by decreasing IL‐1β, TLR4, Myd88, p‐NF‐κB, and p‐p38MAPK levels and increasing Bcl‐2 and Bcl‐xl levels. In GMI‐R1 cells, Ferulic acid attenuated LPS‐induced M1 polarization by decreasing the M1 polarization markers IL‐1β, IL‐6, iNOS, and CD32 and increasing the M2 polarization markers CD206, IL‐4, IL‐10 and Arg‐1. After LPS treatment, IL‐1β, iNOS, TLR4, Myd88, p‐p38MAPK, and p‐NF‐κB levels were obviously increased, and Arg‐1 expression was reduced, while ferulic acid reversed these changes. Conclusion Ferulic acid can promote injured sciatic nerve repair by reducing neuronal cell apoptosis and inflammatory infiltration though the TLR4/NF‐κB pathway. Ferulic acid promotes sciatic nerve repair by inhibiting Schwann cell apoptosis and promoted the transformation of M1 GMI‐R1 microglia to M2 microglia to relieve inflammatory infiltration though the TLR4/NF‐κB pathway.

• Phenology is an important indicator of environmental variation and climate change impacts on tree responses. In conifers, monitoring phenology of photosynthesis through remote sensing has been unreliable, because needle foliage varies little throughout the year. This is challenging for modelling ecosystem carbon uptake and monitoring phenology for enhanced breeding (genomic selection) and forest health. • Here, we demonstrate that drone-based carotenoid-sensitive spectral indices, such as the Chl/carotenoid index (CCI), can be used to track phenology in conifers by taking advantage of the close relationship between seasonally changing carotenoid levels and the variation of photosynthetic activity. • Physiological ground measurements, including photosynthetic pigments and maximum quantum yield of Chl fluorescence, indicated that CCI tracked the variation of photosynthetic activity better than other vegetation indices for 30 white spruce seedlings measured over 1 yr. A machine-learning approach, using CCI derived from drone-based multispectral imagery, was used to model phenology of photosynthesis for the entire pedigree population (6000 seedlings). • This high-throughput drone-based phenotyping approach is suitable for studying climate change impacts and environmental variation on the physiological status of thousands of field-grown conifers at unprecedented speed and scale.

Earth Observation data are uniquely positioned to estimate forest aboveground biomass density (AGBD) in accordance with the United Nations Framework Convention on Climate Change (UNFCCC) principles of ‘transparency, accuracy, completeness, consistency and comparability’. However, the use of space-based AGBD maps for national-level reporting to the UNFCCC is nearly non-existent as of 2023, the end of the first global stocktake (GST). We conduct an evidence-based comparison of AGBD estimates from the NASA Global Ecosystem Dynamics Investigation and ESA Climate Change Initiative, describing differences between the products and National Forest Inventories (NFIs), and suggesting how science teams must align efforts to inform the next GST. Between the products, in the tropics, the largest differences in estimated AGBD are primarily in the Congolese lowlands and east/southeast Asia. Where NFI data were acquired (Peru, Mexico, Lao PDR and 30 regions of Spain), both products show strong correlation to NFI-estimated AGBD, with no systematic deviations. The AGBD-richest stratum of these, the Peruvian Amazon, is accurately estimated in both. These results are remarkably promising, and to support the operational use of AGB map products for policy reporting, we describe targeted ways to align products with Intergovernmental Panel on Climate Change (IPCC) guidelines. We recommend moving towards consistent statistical terminology, and aligning on a rigorous framework for uncertainty estimation, supported by the provision of open-science codes for large-area assessments that comprehensively report uncertainty. Further, we suggest the provision of objective and open-source guidance to integrate NFIs with multiple AGBD products, aiming to enhance the precision of national estimates. Finally, we describe and encourage the release of user-friendly product documentation, with tools that produce AGBD estimates directly applicable to the IPCC guideline methodologies. With these steps, space agencies can convey a comparable, reliable and consistent message on global biomass estimates to have actionable policy impact.