Cryopreservation technology has developed into a fundamental and important supporting method for biomedical applications such as cell‐based therapeutics, tissue engineering, assisted reproduction, ...and vaccine storage. The formation, growth, and recrystallization of ice crystals are the major limitations in cell/tissue/organ cryopreservation, and cause fatal cryoinjury to cryopreserved biological samples. Flourishing anti‐icing materials and strategies can effectively regulate and suppress ice crystals, thus reducing ice damage and promoting cryopreservation efficiency. This review first describes the basic ice cryodamage mechanisms in the cryopreservation process. The recent development of chemical ice‐inhibition molecules, including cryoprotectant, antifreeze protein, synthetic polymer, nanomaterial, and hydrogel, and their applications in cryopreservation are summarized. The advanced engineering strategies, including trehalose delivery, cell encapsulation, and bioinspired structure design for ice inhibition, are further discussed. Furthermore, external physical field technologies used for inhibiting ice crystals in both the cooling and thawing processes are systematically reviewed. Finally, the current challenges and future perspectives in the field of ice inhibition for high‐efficiency cryopreservation are proposed.
This work describes the fundamental mechanisms of ice injury during cryopreservation, and introduces the state‐of‐the‐art ice‐inhibition materials and strategies, both in the cooling and thawing processes, for high‐efficiency cryopreservation. Future perspectives and challenges are also proposed to motivate the development of cell, tissue, and organ cryopreservation and offer bright new inspiration for cryobiology.
The potential of using Landsat for assessing long‐term water surface dynamics of individual reservoirs at a global scale has been significantly hindered by contaminations from clouds, cloud shadows, ...and terrain shadows. A novel algorithm was developed toward the automatic correction of these contaminated image classifications. By applying this algorithm to the data set by Pekel et al. (2016, https://doi.org/10.1038/nature20584), time series of area values for 6,817 global reservoirs (with an integrated capacity of 6,099 km3) were generated from 1984 to 2015. The number of effective images that can be used in each time series has been improved by 81% on average. The long‐term average area for these global reservoirs was corrected from 1.73 × 105 km2 to 3.94 × 105 km2. The results were proven to be robust through validation using observations, synthetic data, and visual inspection. This continuous reservoir surface area data set can provide benefit to various applications (both at continental and local scales).
Plain Language Summary
Understanding of water surface area dynamics is important for modern water resources management. Due to the difficulties collecting data from ground, remote sensing images from satellites have been widely used to map the water coverage and then to analyze the dynamics. However, one typical problem when using satellite images is that they are frequently contaminated by clouds, cloud shadows, and terrain shadows, which result in the underestimation of the water area. Thus, we developed a novel algorithm to remove the impacts of these contaminations for monitoring water area accurately. After comprehensive evaluations, the algorithm was proved to be able to effectively enhance the Landsat‐based water area results. A data set containing monthly surface area time series for 6,817 global reservoirs from 1984 to 2015 was subsequently generated using the algorithm. This work (both the data set and the algorithm) can support many applications on both global and local scales to benefit the water management, hydrology, and remote sensing communities.
Key Points
Image contamination significantly hinders the continuous and accurate assessment of water dynamics using Landsat imagery
A novel algorithm is developed to automatically repair contaminated Landsat images for generating more reliable surface area time series
The number of effective images that can be used in the time series is improved by 81% on average for 6,817 global reservoirs
As subsidies continue to fall, the technology and cost performance of distributed photovoltaic (PV) determines the progress of its grid parity. Based on the discussion of technology and cost, this ...paper analyzed the economic performance of China's distributed PV industry by utilizing the two indicators of levelized cost of energy (LCOE) and internal rate of return (IRR). The results show that: firstly, the current external environment is generally conducive to the development of distributed PV, but there are still some constraints. Secondly, with the decrease of unit investment cost, distributed PV can achieve the goal of parity before 2025. Thirdly, distributed PV projects in the three types of solar energy resources all have high IRR, and the economic performance is better for the projects with high proportion of spontaneous self-use. At the end of the paper, policy recommendations are offered as references for the government.
•We comprehensively analyzed the technology and cost performance of China's distributed PV.•We focused on the trend and decline path of China's distributed PV costs.•The LCOE of distributed PV in China is expected to achieve full parity in 2025.•Except 100% grid-connected mode, the IRR of distributed PV power plants in three areas is higher than 8% which has shown good economic benefits.
Abstract
The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water ...bodies—from the spatial distribution to the long-term trend—is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km
3
year
−1
and it has increased at a rate of 3.12 km
3
year
−1
. The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems.
With the economic transformation and regional economic restructuring of China, there is a significant inter-regional transfer trend of industries among the eastern, central, western and northeastern ...regions. The industrial transfer is able to change the spatial distribution of regional energy intensity by affecting the regional industrial structure, thus impacting the convergence of energy intensity. This paper established a spatial Durbin panel model, and used the relevant data of thirty administrative regions of China from 2004 to 2017 to empirically study the impacts of industrial transfer on regional energy intensity. The results showed that: (1) As a whole, the energy intensity of China's regions was low in the southeast region and high in the northwest region, and there was a significant positive spatial autocorrelation among the energy intensity of different regions. (2) There was β-convergence in the regional energy intensity. It indicated that, on the one hand, the differences in the energy intensity of China's different regions were being gradually narrowed; on the other hand, the energy intensity of each region would converge to its own steady state. (3) The industrial transfer and economic development could promote the convergence of the regional energy intensity.
•China's economic transition and regional economic restructuring promoted industrial transfer.•The regional energy intensity showed a decreasing trend from northwest to southeast.•Industrial transfer could promote the convergence of energy intensity.•A spatial Durbin panel model was used to prove the regional energy intensity convergence of China.
•The flood susceptibility of mountain areas in China was mapped and validated, for the first time, based on RF model.•The model was calibrated and validated with over 50years of historical flooding ...data.•Twelve geographic, meteorological, and hydrological factors were used and the individual contribution was assessed.
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Mountainous terrain covers nearly half of China and is susceptible to floods, which can lead to substantial losses of human life and property. Historical flooding records from government bulletins and newspapers, the only available information regarding floods that have occurred in some mountainous areas, are valuable for understanding flood disaster mechanisms in these regions. In this study, the flood susceptibility in mountainous regions in China was mapped based on historical flooding records from 1949 to 2000. A Random Forest (RF) model, which can handle large datasets through factor contribution analysis, was chosen to characterize the relationships between flooding occurrences and twelve geographic, meteorological, and hydrological explanatory factors. The results indicate that the RF model can effectively identify flood-prone areas and has advantages over artificial neural network (ANN) and support vector machine (SVM) methods. Among these explanatory factors, the geographic factors (elevation, longitude and drainage density) are the most important predictors of flooding in China's mountainous areas, whereas the hydrological factors (relative elevation and curve number) are the least important. Two independent datasets of historical flooding events from the Bulletin of Flood and Drought Disasters in China (2006–2014) alongside news reports and yearbooks (2008–2014) were collected and chosen to validate the capability of the RF model. The validation results confirm that the RF model can identify the flood susceptibility with satisfactory accuracy. This study proposes a preliminary flood susceptibility map of mountainous areas in China and provides a reference for predicting and mitigating potentially disastrous flooding events.
Promoting wind power is a long-term strategy of China to respond to both energy shortage and environmental pollution. Stimulated by various incentive policies, wind power generation in China has ...achieved tremendous growth. However, the China's wind power industry is still in its early development stage and various problems have emerged, seriously challenging the healthy functioning of the industry. Based on micro-data on wind power listed companies, the four-stage Data Envelopment Analysis (DEA) model is used to measure the technical efficiency of China's wind power enterprises and sketch the development of the wind power industry at the micro level. The results show that there exist non-efficiency problems arising from the diseconomies of scale in China's wind power industry during 2011–2015. The average value of the efficiency of wind power enterprises is 32.5%. According to the subsample analysis, large-scale enterprises, private-owned enterprises and enterprises taking wind farm conduction and operation as their main business, as well as enterprises located in the three northern area, have the highest efficiency in their respective categories. Drawn on this analysis, conclusions and policy implications are provided at the end of the paper.
•Reviewed literature on the efficiency of China's wind power industry systematically.•Used the four-stage DEA method to analyze micro-data on wind power listed companies with the goal of delineating the efficiency of the development of China's wind power industry.•Analyzed wind power enterprises from the following four aspects: the scale of enterprises, their regions, nature, and the upstream and downstream of their industrial chain.•Made policy recommendations for the development of China's wind power industry.
As one of the most frequent chemical modifications in eukaryotic mRNAs, N6-methyladenosine (m6A) modification exerts important effects on mRNA stability, splicing, and translation. Recently, the ...regulatory role of m6A in tumorigenesis has been increasingly recognized. However, dysregulation of m6A and its functions in tumor epithelial-mesenchymal transition (EMT) and metastasis remain obscure.
qRT-PCR and immunohistochemistry were used to evaluate the expression of methyltransferase-like 3 (METTL3) in gastric cancer (GC). The effects of METTL3 on GC metastasis were investigated through in vitro and in vivo assays. The mechanism of METTL3 action was explored through transcriptome-sequencing, m6A-sequencing, m6A methylated RNA immunoprecipitation quantitative reverse transcription polymerase chain reaction (MeRIP qRT-PCR), confocal immunofluorescent assay, luciferase reporter assay, co-immunoprecipitation, RNA immunoprecipitation and chromatin immunoprecipitation assay.
Here, we show that METTL3, a major RNA N6-adenosine methyltransferase, was upregulated in GC. Clinically, elevated METTL3 level was predictive of poor prognosis. Functionally, we found that METTL3 was required for the EMT process in vitro and for metastasis in vivo. Mechanistically, we unveiled the METTL3-mediated m6A modification profile in GC cells for the first time and identified zinc finger MYM-type containing 1 (ZMYM1) as a bona fide m6A target of METTL3. The m6A modification of ZMYM1 mRNA by METTL3 enhanced its stability relying on the "reader" protein HuR (also known as ELAVL1) dependent pathway. In addition, ZMYM1 bound to and mediated the repression of E-cadherin promoter by recruiting the CtBP/LSD1/CoREST complex, thus facilitating the EMT program and metastasis.
Collectively, our findings indicate the critical role of m6A modification in GC and uncover METTL3/ZMYM1/E-cadherin signaling as a potential therapeutic target in anti-metastatic strategy against GC.
We present the result of a search for very metal-poor (VMP, ) stars in the Milky Way based on low-resolution spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) DR3, ...significantly enlarging the current candidate sample of these low-metallicity objects. The selection procedure results in a sample of 10,008 VMP stars covering a large area of sky in the Northern Hemisphere, and includes over 6800 targets brighter than V ∼ 16. This LAMOST DR3 VMP sample provides the largest number of VMP candidates to date that are sufficiently bright for follow-up high-resolution observation with 4-10 m telescopes, greatly expanding the VMP stars discovered in the northern sky, and can be used to balance the spatial distribution of VMP stars with high-resolution spectroscopic analyses. Comparison with stars having existing high-resolution analyses and Tycho Gaia Astrometric Solution parallaxes indicates that the derived stellar parameters and distance estimates are reliable. The sample reaches beyond 40 kpc in the halo, and contains over 670 candidates of extremely metal-poor ( ) and ultra-metal-poor ( ) stars. The distribution of Vφ indicates that the sample consists of two halo components, with the retrograde component likely to be associated with the outer-halo population. A new criterion is proposed to select carbon-enhanced metal-poor (CEMP) star candidates, using line indices G1 and EGP over the range 4000 K < < 7000 K, resulting in 636 CEMP candidates from the LAMOST DR3 VMP sample.
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