SUMMARY
Elaborate cell‐cycle control must be adopted to ensure the continuity of the meiotic second division and termination after that. Despite its importance, however, the genetic controls ...underlying the meiotic cell cycle have not been reported in maize. Here, we characterized a meiotic cell‐cycle controller ZmTDM1, which is a homolog of Arabidopsis TDM1 and encodes a canonical tetratricopeptide repeat domain protein in maize. The Zmtdm1 homozygous plants exhibited complete male sterility and severe female abortion. In Zmtdm1 mutants, cell‐cycle progression was almost identical to that of wild type from leptotene to anaphase II. However, chromosomes in the tetrad failed meiotic termination at the end of the second division and underwent additional divisions in succession without DNA replication, reducing the ploidy to less than haploid in the product. In addition, two ZmTDM1‐like homologs (ZmTDML1 and ZmTDML2) were not functional in meiotic cell‐cycle control. Moreover, ZmTDM1 interacted with RING‐type E3 ubiquitin ligase, revealing that it acts as a subunit of the APC/C E3 ubiquitin ligase complex. Overall, our results identified a regulator of meiotic cell cycle in maize and demonstrated that ZmTDM1 is essential for meiotic exit after meiosis II.
Significance Statement
In this study, we identified that ZmTDM1 is a regulator of meiotic cell‐cycle control in maize. It encodes a protein harboring four tetratricopeptide repeats (TPR) and is required for determining meiosis exit after the second meiotic division.
Tobacco is a significant product providing considerable economic benefits to countries worldwide, while its increased consumption causes health and socio-economic losses for smokers and non-smokers. ...This paper constructs a decomposition system of tobacco taxation: the population aging factor is included in the influencing factors of personal tax, and personal tax revenue is regarded as the product of tax structure, macro tax burden, regional economy, reciprocal aging, and the elderly population. This article conducts an empirical study on the relationship between taxation and economic growth. The estimated coefficients of business tax and corporate income tax are significant at the significance level of 0.1, with a consumption tax and time-variable coefficients reporting a 0.02 level of significance. The T statistic value and the explanatory degree of the variables involved in the model to the explained variables are also very high, reaching more than 95%. We find that increasing the macro tax burden negatively impacts economic growth. Therefore, the study suggests that for fostering the industry's economic growth, the country needs to ensure the optimal macro tax burden of 17.5%, with different types of taxes influencing economic growth. Personal tax reform should pay attention to the phenomenon of aging, adjust the tax structure to increase personal tax income, provide policy support and guarantee for the elderly labor force, and encourage the re-employment of silver-haired people to alleviate the adverse impact of aging on taxation.
The rapid economic growth has not only created more opportunities for the development of colleges and universities, but also presented many challenges. In this paper, by analyzing the construction of ...university budget implementation system, based on 5 stages, the recursive hierarchy of university performance budget is established by using hierarchical analysis method, and the hierarchy is solved by using recursive hierarchy matrix. A combination of balanced scorecard and key performance indicators is used. The performance budget evaluation index system for colleges and universities is constructed from the four levels of financial performance, business performance, budget performance and social performance. The equity realization method is used to study the financial fund performance of universities in the current period in the form of dividends, emptying behavior and selling shares. Based on the budget model, the impact of various factors on the shareholders’ dividend decision-making behavior is calculated according to the paradigm of “decision analysis framework - parameter change - decision change”. After the effective implementation of the performance project, the income of university A increased by 28.6% compared to the previous year, which laid a solid foundation for the development of the university.
The international capital flows between the financial markets of state-owned enterprises are frequent and closely linked, and the difficulty of assessing and managing risks is deepening day by day. ...In order to be able to provide some useful references for corporate financial institutions in theory and practice, this paper is oriented to cloud accounting SOEs, modeling and calculating SOE returns and volatilities to obtain corporate financial spillover indices. The calculated spillover index is introduced into the basic assessment system to establish the financial risk assessment system. Based on the expert scoring results of the assessment indexes, a judgment matrix is constructed to obtain the fuzzy assessment weights of each index. Combined with the system assessment results, the risk matrix is used to classify risk levels and develop corresponding management strategies. It is experimentally verified that the intensity of the total risk spillover index and the probability of risk occurrence between different submarkets of corporate finance are higher during the unpracticed period, 76% and 83.48%, respectively. In contrast, the spillover index intensity and the probability of risk occurrence in the practice period are only 50% and 61.15%. This shows that the proposed method can carry out effective risk assessment management based on the spillover index, which meets the needs of the times and realistic needs of cloud accounting SOEs for financial risk assessment management and promotes the financial business development of SOEs.
Abstract
This study proposes a new model in explicit form to predict the diameter of the jet grouting column of three popular jet grouting systems (i.e., single, double, and triple). The proposed ...model can quantify the uncertainty associated with the prediction. Bayesian model selection was used to determine the optimal models and, the bootstrap sampling method was adopted to avoid bias in the collected database. The predictions agree well with the measured data, and the 95% credible intervals can cover almost all the measured data on the testing dataset, which indicates the robustness of the proposed model. A simple formula combined with a table was established to facilitate the engineers in applying the proposed model. The results reveal that soil type has a significant impact on diameter prediction. Uncertainty quantification can reveal possible fluctuations in column diameter and is vital to get a cost‐efficient design.
Early 2020 witnessed the coronavirus disease 2019 (COVID-19) pandemic followed by a nationwide lockdown in the whole history for the first time. In this raising dilemma, multiple countries had a ...serious impact on their international trade, especially during the lockdown. It is also widely accepted that the lives of individuals had been changing ever since the spread of COVID-19. Several other sectors were badly affected during the pandemic. For the above reasons, service industries had a significant impact before and after the pandemic. Based on the data collected, it was identified that the pandemic affected the service industries, enterprises, and other organizations that contribute to the economic growth of the nation. It was also found that the pandemic has adversely impacted private and public enterprises. In addition, the study examined the impact of COVID-19 on China's international trade using artificial intelligence and blockchain technology. Another objective of the article is to examine the impact of big data on China's international trade. The study suggests upgrading the trading policies of China to deal with the challenges being faced in the trading industry.
Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) is a powerful technique for in-depth metabolome analysis with high quantification accuracy. Unlike conventional LC-MS, ...it analyzes chemical-group-based submetabolomes and uses the combined results to represent the whole metabolome. Due to analysis time and cost constraint, not all submetabolomes can be profiled and thus knowledge of chemical group classification is important in guiding submetabolome selection. Herein we report a study of determining the distribution of functional groups of compounds in a database and then examine how well we can experimentally analyze the major chemical groups in two representative samples (i.e., human plasma and yeast). We developed a computer algorithm to classify chemical structures according to their functional groups. After removing lipids which are targeted molecules in lipidomic analysis, inorganic species and other molecules that are unique to drug, food, plant, and environmental origins, five groups (i.e., amine, phenol, hydroxyl, carboxyl, and carbonyl) are found to be the dominant classes. In the databases of MCID (2683 filtered metabolites), HMDB (5506), KEGG (11598), YMDB (1107), and ECMDB (1462), 94.7%, 85.7%, 86.4%, 85.7%, and 95.8% of the filtered metabolites belong to one or more of the five groups, respectively. These groups can be analyzed in four-channel CIL LC-MS where hydroxyls (H), amines and phenols (A), carboxyls (C), and carbonyls or ketones/aldehydes (K) are separately profiled as individual channels using dansyl and DmPA labeling reagents. A total of 7431 peak pairs were detected with 6109 unique-mass pairs from plasma, while 5629 pairs with 4955 unique-mass pairs were detected in yeast. Compared to group distributions of database compounds, hydroxyl-containing metabolites were severely underdetected, which might indicate that the current method is less than optimal for analyzing this group of metabolites. As a result, the overall experimental coverage is likely significantly lower than the database-derived coverage. In short, this study has shown that high metabolome coverage is theoretically attainable by analyzing only the H, A, C, and K submetabolomes and the group classification information should be helpful in guiding future analytical method development and choices of submetabolomes to be analyzed.
Summary
Potassium transporters and channels play crucial roles in K+ uptake and translocation in plant cells. These roles are essential for plant growth and development. AKT1 is an important K+ ...channel in Arabidopsis roots that is involved in K+ uptake. It is known that AKT1 is activated by a protein kinase CIPK23 interacting with two calcineurin B‐like proteins CBL1/CBL9. The present study showed that another calcineurin B‐like protein (CBL10) may also regulate AKT1 activity. The CBL10‐over‐expressing lines showed a phenotype as sensitive as that of the akt1 mutant under low‐K+ conditions. In addition, the K+ content of both CBL10‐over‐expressing lines and akt1 mutant plants were significantly reduced compared with wild‐type plants. Moreover, CBL10 directly interacted with AKT1, as verified in yeast two‐hybrid, BiFC and co‐immunoprecipitation experiments. The results of electrophysiological analysis in both Xenopus oocytes and Arabidopsis root cell protoplasts demonstrated that CBL10 impairs AKT1‐mediated inward K+ currents. Furthermore, the results from the yeast two‐hybrid competition assay indicated that CBL10 may compete with CIPK23 for binding to AKT1 and negatively modulate AKT1 activity. The present study revealed a CBL‐interacting protein kinase‐independent regulatory mechanism of calcineurin B‐like proteins in which CBL10 directly regulates AKT1 activity and affects ion homeostasis in plant cells.
Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance ...chemical isotope labeling (CIL) LC–MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential 12C- and 13C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with 12C-labeling and spiked with a 13C-labeled pooled sample, followed by LC–MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 12C-/13C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org. Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that 12C-/13C-DnsHz labeling LC–MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.
Driving solutions for power semiconductor devices are experiencing new challenges since the emerging wide bandgap power devices, such as silicon carbide (SiC), with superior performance become ...commercially available. Generally, high switching speed is desired due to the lower switching loss, yet high <inline-formula> <tex-math notation="LaTeX">dv/dt </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">di/dt </tex-math></inline-formula> can result in elevated electromagnetic interference (EMI) emission, false-triggering, and other detrimental effects during switching transients. Active gate drivers (AGDs) have been proposed to balance the switching losses and the switching speed of each switching transient. The review of the in-existence AGD methodologies for SiC devices has not been reported yet. This review starts with the essence of the slew rate control and its significance. Then, a comprehensive review categorizing the state-of-the-art AGD methodologies is presented. It is followed by a summary of the AGDs control and timing strategies. In this work, using AGD to reduce the EMI noise of a 10-kV SiC MOSFET system is reported. This work also highlights other capabilities of AGDs, including reliability enhancement of power devices and rebalancing the mismatched electrical parameters of parallel- and series-connected devices. These application scenarios of AGDs are validated via simulation and experimental results.
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