Search

Lake Qinghai has shrunk and then expanded over the past few decades. Quantifying the contributions of climate change and human activities to lake variation is important for water resource management and adaptation to climate change. In this study, we calculated the water volume change of Lake Qinghai, analyzed the climate and land use changes in Lake Qinghai catchment, and distinguished the contributions of climate change and local human activities to water volume change. The results showed that lake water volume decreased by 9.48 km3 from 1975 to 2004 and increased by 15.18 km3 from 2005 to 2020. The climate in Lake Qinghai catchment is becoming warmer and more pluvial, and the changes in land use have been minimal. Based on the Soil and Water Assessment Tool (SWAT), land use change, climate change and interaction effect of them contributed to 7.46%, 93.13% and −0.59%, respectively, on the variation in surface runoff into the lake. From the perspective of the water balance, we calculated the proportion of each component flowing into and out of the lake and found that the contribution of climate change to lake water volume change was 97.55%, while the local human activities contribution was only 2.45%. Thus, climate change had the dominant impact on water volume change in Lake Qinghai. [ABSTRACT FROM AUTHOR]

[Display omitted] • Alpine meadow degradation significantly changed soil microbial community composite. • Soil microbial diversity showed hump-shaped patterns with increasing degradation. • The changes in soil microbial diversity were greatly correlated with plant production. In recent decades, alpine meadows have experienced severe degradation owing to external disturbances. Although soil microorganisms are critical for ecosystem services, little is known about their responses to soil degradation and the potential patterns in alpine meadows. To solve this question, we collected and analyzed soil samples from three degraded alpine meadows situated on the Qinghai-Tibet Plateau. We aimed to examine the effects of degradation on soil microbial diversity and identify the ecological predictors for the diversity of bacteria and fungi. Our results showed that alpine meadow degradation significantly changed soil bacterial and fungal diversity and community composition. Specifically, the relationship between bacterial and fungal diversity and degradation intensity was a hump-shaped, with the highest diversity observed at a moderate degradation level. Additionally, alpine meadow degradation-induced changes in microbial diversity were strongly correlated with decreased plant production, with fungal diversity showing a closer link with below-ground biomass (BGB) than with bacterial diversity. Our findings offer empirical evidence that intermediate disturbance (i.e., moderate degradation) may be beneficial for supporting soil biodiversity. This has important implications for informing policy and management strategies meant to conserve soil biodiversity and ecosystem services when facing anthropogenic change. [ABSTRACT FROM AUTHOR]

The terrestrial methane budget varies between different vegetation types and soil conditions and is highly uncertain for alpine grasslands. This work used eddy covariance techniques to continuously measure CH4 flux (NEEm) over a semiarid alpine meadow on the northeastern Qinghai-Tibetan Plateau from January 2017 to August 2019. The diel NEEm averaged 0.14 ± 0.98 nmol CH4 m−2 s−1 (mean ± S.D.), with a rough pattern of daytime release and nocturnal uptake. The 8-day NEEm exhibited a similar sinusoid variation, with a peak of 6.8 mg CH4 m−2 d−1 at the end of April and a minimum of −1.5 mg CH4 m−2 d−1 at the end of August. The maximum release probably coincided with the thawing of frozen soil in the root zone, and the peak uptake may be related to high soil temperature. Monthly CH4 uptake was highest from June to September and consumed 51.7 mg CH4 m−2 from the atmosphere. CH4 production in the other months totaled 647.6 mg CH4 m−2. The semiarid alpine meadow thus acted as a weak net CH4 source, releasing ca 0.6 g CH4 m−2 year−1 to the atmosphere. The boosted regression trees analysis shows that the sensible heat flux (H) is positively related to half-hour NEEm and accounted for 34% of its variability. The piecewise structural equation models reveal that the magnitude of the effects from soil temperature and vapor pressure deficit on 8-day and monthly NEEm were almost equal, but acted in opposite directions. Vegetation growth and soil moisture exerted little direct influence on NEEm variability at half-hour, 8-day, or monthly scales. Our results show that CH4 emissions of the nongrowing season dominate the annual methane budget for this alpine meadow area. Methane consumption during the growing season was significantly constrained by low soil temperature and high soil water content. These findings imply that semiarid alpine meadows may consume more methane during the growing season if soil temperatures increase and soil moisture levels decrease as projected by future warming scenarios, thus constituting a climate change negative feedback. [ABSTRACT FROM AUTHOR]

Gross primary production (GPP) plays a crucial part in the carbon cycle of terrestrial ecosystems. A set of validated monthly GPP data from 1957 to 2010 in 0.5° × 0.5° grids of China was weighted from the Multi-scale Terrestrial Model Intercomparison Project using Bayesian model averaging (BMA). The spatial anomalies of detrended BMA GPP during the growing seasons of typical El Niño years indicated that GPP response to El Niño varies with Pacific Decadal Oscillation (PDO) phases: when the PDO was in the cool phase, it was likely that GPP was greater in northern China (32°–38°N, 111°–122°E) and less in the Yangtze River valley (28°–32°N, 111°–122°E); in contrast, when PDO was in the warm phase, the GPP anomalies were usually reversed in these two regions. The consistent spatiotemporal pattern and high partial correlation revealed that rainfall dominated this phenomenon. The previously published findings on how El Niño during different phases of PDO affecting rainfall in eastern China make the statistical relationship between GPP and El Niño in this study theoretically credible. This paper not only introduces an effective way to use BMA in grids that have mixed plant function types, but also makes it possible to evaluate the carbon cycle in eastern China based on the prediction of El Niño and PDO. [ABSTRACT FROM AUTHOR]

• The PRI as an indicator of NPQ to characterize the change in heat dissipation. • SIF is strongly affected by radiation, while PRI is sensitive to soil moisture. • PRI can be used to improve the relationship between GPP and SIF. The sun-induced chlorophyll fluorescence (SIF) is directly related to the photosynthesis of winter wheat and has a good linear relationship with the gross primary production (GPP). However, the relationship of SIF and GPP is still uncertain under different soil water content conditions. The sun-induced chlorophyll fluorescence, GPP and non-photochemical quenching (NPQ) are the three ways of photosynthetically active radiation in plants. The photochemical reflectance index (PRI) can be used as a proxy indicator of NPQ to characterize the change in heat dissipation during photosynthesis process of winter wheat. To detect the impact of soil water content on winter wheat photosynthesis and SIF and GPP relationship, based on the ground measurement data at Zhaoxian Experimental Station in northern China during the growing season in 2018 and the simulated data by the SCOPE model, we use PRI to improve the GPP model estimated by SIF. The results indicate that: (1) PRI is sensitive to soil water content (R2 = 0.64), so it can be used to improve the estimation of GPP based on SIF under different soil water conditions; (2) For the ground measurement data, PRI obv can improve the estimation accuracy of GPP obv by SIF obv. Under different soil water content (SWC) conditions, the relationship between GPP obv and SIF obv is significantly correlated (R2 = 0.33–0.45, p < 0.01), and PRI obv can be used to improve the estimation between GPP obv and SIF obv (R2 = 0.57–0.62, p < 0.01); (3) The simulation results of the SCOPE model show that the simulation effect of the model can be better optimized by adding PRI under the condition of relatively dry soil (△R2 = 0.13–0.17). Our research suggests that PRI can be added when estimating GPP using SIF information, especially when winter wheat is under low soil water content conditions. [ABSTRACT FROM AUTHOR]

• Compare the performances of SIF and three VIs in predicting wheat yield. • SIF CSIF performs better than SIF GOME2 and VIs in predicting wheat yield. • Adapt six machine/deep learning methods to predict wheat yield over large areas. • SVR achieved the best prediction (R2 = 0.87) using SIF CSIF and climate data. Reliable forecasts of large-scale wheat yield are very important for global food security. Although solar-induced chlorophyll fluorescence (SIF) is more sensitive than traditional remotely sensed vegetation indices to photosynthetic capacity, the performance of SIF in wheat yield prediction should be further explored. In this study, five satellite variables (i.e., Global Ozone Monitoring Experiment-2 (GOME-2) SIF at 0.5° spatial resolution, global spatially contiguous SIF (CSIF) at 0.05° resolution, and three vegetation indices at 1 km resolution) from 2007 to 2018 were used to predict wheat yield using two linear regression methods (least absolute shrinkage and selection operator regression (LASSO) and ridge regression (RIDGE)), three machine learning methods (support vector regression (SVR), random forest regression (RF), and extreme gradient boosting (XGBoost)), and one deep learning method (long short-term memory (LSTM)) to predict wheat yield across the Indo-Gangetic Plains. The results showed that machine learning and deep learning methods outperformed the two linear regression methods in predicting wheat yield, while the LSTM did not perform better than SVR. The prediction using the high-resolution SIF product had better performance than that using the coarse-resolution SIF product among all years. Moreover, the high-resolution SIF had better performance than the three vegetation indices in yield prediction in 2010, which indicated that the SIF data had great superiority in predicting wheat yield under extreme weather events. Our findings highlight that developing high-quality SIF products in the future has the potential to improve crop yield predictions, and our method can predict wheat yield simply and effectively in cropping areas with limited data. [ABSTRACT FROM AUTHOR]

• Spatial and seasonal heterogeneity of rice T opt GPP was detected by satellite NIR V. • Rice NIR V - T opt GPP is lower in the regions with more drought stress. • ORYZA model modified by NIR V - T opt GPP shows better simulation in rice yield. • More reduction of rice yield was predicted in the study area under global warming. Tropical rice production is at risk from rising temperature. Understanding regional and seasonal heterogeneity of optimum temperatures for rice production is important for model simulation to predict rice yield change under climate change. However, studies or tools for widely observation of crop responses to temperature over broad spatial scales with long time spans are limited. In this study, we detected optimum temperature range for rice gross primary production (T opt GPP) in the lower Gangetic plains and delta region using the near-infrared reflectance of vegetation (NIR V), which is a new photosynthetic proxy, to improve ORYZA model performance in high-temperature season and assessed how tropical rice would respond to temperature increase in the study area. According to satellite observations of NIR V from 2001 to 2015, current ambient air temperature has exceeded the mean T opt GPP of Boro rice (24.8 ± 1.8 °C) and Aman rice (26.7 ± 1.2 °C) in the lower Gangetic plains and delta region, suggesting a downtrend of rice production under future warming. The detection results show that rice has lower T opt GPP in the regions with more drought stress and lower background temperature under water-limited conditions. Furthermore, the model modified by NIRv- T opt GPP shows better performance in potential yields, especially in high-temperature seasons on the region scale. Without CO 2 fertilization effect, each degree-Celsius increase is expected to reduce rice potential yields by 4.9 ± 1.6% based on the default T opt GPP range in ORYZA model and by 7.0 ± 1.2% based on the detected NIRv- T opt GPP range in the study area. This study implies that global grid-based model simulation may underestimate sensitivity of tropical rice yield to temperature rise due to the neglect of regional and seasonal heterogeneity of T opt GPP. NIR V makes it possible to determine local optimal temperatures for crop production, and to improve grid-based modelling across various agricultural systems in different growing seasons at the regional scale. [ABSTRACT FROM AUTHOR]

As the biggest carbon flux of terrestrial ecosystems from photosynthesis, gross primary productivity (GPP) is an important indicator in understanding the carbon cycle and biogeochemical process of terrestrial ecosystems. Despite advances in remote sensing-based GPP modeling, spatial and temporal variations of GPP are still uncertain especially under extreme climate conditions such as droughts. As the only official products of global spatially explicit GPP, MOD17A2H (GPPMOD) has been widely used to assess the variations of carbon uptake of terrestrial ecosystems. However, systematic assessment of its performance has rarely been conducted especially for the grassland ecosystems where inter-annual variability is high. Based on a collection of GPP datasets (GPPEC) from a global network of eddy covariance towers (FluxNet), we compared GPPMOD and GPPEC at all FluxNet grassland sites with more than five years of observations. We evaluated the performance and robustness of GPPMOD in different grassland biomes (tropical, temperate, and alpine) by using a bootstrapping method for calculating 95% confident intervals (CI) for the linear regression slope, coefficients of determination (R2), and root mean square errors (RMSE). We found that GPPMOD generally underestimated GPP by about 34% across all biomes despite a significant relationship (R2 = 0.66 (CI, 0.63–0.69), RMSE = 2.46 (2.33–2.58) g Cm−2 day−1) for the three grassland biomes. GPPMOD had varied performances with R2 values of 0.72 (0.68–0.75) (temperate), 0.64 (0.59–0.68) (alpine), and 0.40 (0.27–0.52) (tropical). Thus, GPPMOD performed better in low GPP situations (e.g., temperate grassland type), which further indicated that GPPMOD underestimated GPP. The underestimation of GPP could be partly attributed to the biased maximum light use efficiency (εmax) values of different grassland biomes. The uncertainty of the fraction of absorbed photosynthetically active radiation (FPAR) and the water scalar based on the vapor pressure deficit (VPD) could have other reasons for the underestimation. Therefore, more accurate estimates of GPP for different grassland biomes should consider improvements in εmax, FPAR, and the VPD scalar. Our results suggest that the community should be cautious when using MODIS GPP products to examine spatial and temporal variations of carbon fluxes. [ABSTRACT FROM AUTHOR]

Soil contamination with heavy metals has emerged as a global environmental threat, compromising agricultural productivity, ecosystem integrity, and human health. Conventional remediation techniques often fall short due to high costs, operational complexities, and environmental drawbacks. Plant-based disposal technologies, including biochar, phytometallurgy, and phrolysis, have emerged as promising solutions in this regard. Grounded in a novel experimental framework, biochar is studied for its dual role as soil amendment and metal adsorbent, while phytometallurgy is explored for its potential in resource recovery and economic benefits derived from harvested metal-rich plant biomass. Pyrolysis, in turn, is assessed for transforming contaminated biomass into value-added products, thereby minimizing waste. These plant disposal technologies create a circular model of remediation and resource utilization that holds the potential for application in large-scale soil recovery projects, development of environmentally friendly agro-industries, and advancement in sustainable waste management practices. This review mainly discussed cutting-edge plant disposal technologies-biochar application, phytometallurgy, and pyrolysis-as revolutionary approaches to soil heavy metal remediation. The efficacy, cost-effectiveness, and environmental impact of these innovative technologies are especially evaluated in comparison with traditional methods. The success of these applications could signal a paradigm shift in how we approach both environmental remediation and resource recovery, with profound implications for sustainable development and circular economy strategies., 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 © 2024 Elsevier B.V. All rights reserved.)

Widespread concern about ecological degradation has prompted development of concepts and exploration of methods to quantify ecological quality with the aim of measuring ecosystem changes to contribute to future policy-making. This paper proposes a conceptual framework for ecological quality measurement based on current ecosystem functions and biodiverse habitat, compared with pixel-scale historical baselines. The framework was applied to evaluate the changes and driving factors of ecological quality for Chinese terrestrial ecosystems through remote sensing-based and ecosystem process modeled data at 1 km spatial resolution from 2000 to 2018. The results demonstrated the ecological quality index (EQI) had a very different spatial pattern based upon vegetation distribution. An upward trend in EQI was found over most areas, and variability of 46.95% in EQI can be explained well by change in climate, with an additional 10.64% explained by changing human activities, quantified by population density. This study demonstrated a practical and objective approach for quantifying and assessing ecological quality, which has application potential in ecosystem assessments on scales from local to region and nation, yet would provide a new scientific concept and paradigm for macro ecosystems management and decision-making by governments., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Damaged hyaline cartilage has no capacity for self-healing, making osteoarthritis (OA) "difficult-to-treat". Cartilage destruction is central to OA patho-etiology and is mediated by matrix degrading enzymes. Here we report decreased expression of miR-17 in osteoarthritic chondrocytes and its deficiency contributes to OA progression. Supplementation of exogenous miR-17 or its endogenous induction by growth differentiation factor 5, effectively prevented OA by simultaneously targeting pathological catabolic factors including matrix metallopeptidase-3/13 (MMP3/13), aggrecanase-2 (ADAMTS5), and nitric oxide synthase-2 (NOS2). Single-cell RNA sequencing of hyaline cartilage revealed two distinct superficial chondrocyte populations (C1/C2). C1 expressed physiological catabolic factors including MMP2, and C2 carries synovial features, together with C3 in the middle zone. MiR-17 is highly expressed in both superficial and middle chondrocytes under physiological conditions, and maintains the physiological catabolic and anabolic balance potentially by restricting HIF-1α signaling. Together, this study identified dual functions of miR-17 in maintaining cartilage homeostasis and prevention of OA., (© 2022. The Author(s).)

Large-scale COVID-19 vaccinations are currently underway in many countries in response to the COVID-19 pandemic. Here, we report, besides generation of neutralizing antibodies, consistent alterations in hemoglobin A1c, serum sodium and potassium levels, coagulation profiles, and renal functions in healthy volunteers after vaccination with an inactivated SARS-CoV-2 vaccine. Similar changes had also been reported in COVID-19 patients, suggesting that vaccination mimicked an infection. Single-cell mRNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) before and 28 days after the first inoculation also revealed consistent alterations in gene expression of many different immune cell types. Reduction of CD8 + T cells and increase in classic monocyte contents were exemplary. Moreover, scRNA-seq revealed increased NF-κB signaling and reduced type I interferon responses, which were confirmed by biological assays and also had been reported to occur after SARS-CoV-2 infection with aggravating symptoms. Altogether, our study recommends additional caution when vaccinating people with pre-existing clinical conditions, including diabetes, electrolyte imbalances, renal dysfunction, and coagulation disorders., (© 2021. The Author(s).)

Mantle cell lymphoma (MCL) is a distinct histological type of B-cell lymphoma with a poor prognosis. Several agents, such as proteasome inhibitors, immunomodulatory drugs, and inhibitors of B cell lymphoma-2 and Bruton's tyrosine kinase have shown efficacy for relapsed or refractory (r/r) MCL but often have short-term responses. Chimeric antigen receptor (CAR) T-cell therapy has emerged as a novel treatment modality for r/r non-Hodgkin's lymphoma. However, long-term safety and tolerability associated with CAR T-cell therapy are not defined well, especially in MCL. In this report, we described a 70-year-old patient with r/r MCL with 48-month duration of follow-up who achieved long-term remission after CAR T-cell therapy. CAR T-cell-related toxicities were also mild and tolerated well even in this elderly patient. This report suggested that CAR T-cell therapy is a promising treatment modality for patients with MCL, who are generally elderly and have comorbid conditions.

Factors associated with complete and durable remissions after anti-CD19 chimeric antigen receptor T (CAR-T) cell immunotherapy for relapsed or refractory non-Hodgkin lymphoma (r/r NHL) have not been well characterized. In this study, we found that the different sites of extranodal involvement may affect response, overall survival (OS), and progression-free survival (PFS) in patients with r/r NHL treated with anti-CD19 CAR-T cells. In a cohort of 32 treated patients, 12 (37.5%) and 8 (25%) patients exhibited soft tissue lymphoma and bone marrow (BM) infiltrations, respectively, and 13 (41%) patients exhibited infiltration at other sites. The factors that may affect prognosis were identified through multivariable analysis. As an independent risk factor, soft tissue infiltration was the only factor significantly correlated with adverse prognosis (P < 0.05), whereas other factors did not reach statistical significance. Furthermore, the site of extranodal tumor infiltration significantly and negatively affected OS and PFS in patients with r/r NHL treated with anti-CD19 CAR-T cell therapy. PFS and OS in patients with BM involvement were not significantly different from those of patients with lymph node involvement alone. Thus, anti-CD19 CAR-T cell therapy may improve the prognosis of patients with BM infiltration.

The CreER/LoxP system is widely accepted to track neural lineages and study gene functions upon tamoxifen (TAM) administration. We have observed that prenatal TAM treatment caused high rates of delayed delivery and fetal mortality. This substance could produce undesired results, leading to data misinterpretation. Here, we report that administration of TAM during early stages of cortical neurogenesis promoted precocious neural differentiation, while it inhibited neural progenitor cell (NPC) proliferation. The TAM-induced inhibition of NPC proliferation led to deficits in cortical neurogenesis, dendritic morphogenesis, synaptic formation, and cortical patterning in neonatal and postnatal offspring. Mechanistically, by employing single-cell RNA-sequencing (scRNA-seq) analysis combined with in vivo and in vitro assays, we show TAM could exert these drastic effects mainly through dysregulating the Wnt - Dmrta2 signaling pathway. In adult mice, administration of TAM significantly attenuated NPC proliferation in both the subventricular zone and the dentate gyrus. This study revealed the cellular and molecular mechanisms for the adverse effects of TAM on corticogenesis, suggesting that care must be taken when using the TAM-induced CreER/LoxP system for neural lineage tracing and genetic manipulation studies in both embryonic and adult brains., Competing Interests: The authors declare no competing interest.