Search

Abstract Climate mitigation policies have broad environmental and socioeconomic impacts and thus underpin progress towards the United Nations Sustainable Development Goals (SDGs). Through national-scale integrated modeling, we explore the spillover effects of China’s long-term climate mitigation pathways (CMPs) on achieving all 17 SDGs, and then identify a cost-effective CMP for China with co-benefits for sustainability. Our analysis indicates that the 9 original CMPs and 180 bundled CMPs can both substantially boost the SDGs, resulting in an increase of 6.33–8.86 and 5.90–9.33 points in overall SDG score (0=no progress, 100=full achievement) by 2060, compared to the Reference pathway of 70.75 points, respectively. The identified cost-effective CMP deals with the trade-offs among sustainability, CO2 emissions and mitigation cost, and maximizes the synergies between them. This CMP can inform future directions for China’s policy-makers to maximize the potential synergies between carbon neutrality and long-term sustainable development.

Abstract Investors are often affected by emotion, cognition, and other psychological factors in stock trading when making decisions. At present, people can use machine learning and other technologies to obtain a massive amount of text data from the Internet to mine information related to investor behavior and sentiment. Building intelligent online portfolio trading strategies that consider investor sentiment has become an important topic and key challenge in the financial field. Therefore, this paper explores how to use text data to depict investor sentiment, fuzzifies historical stock price data, designs a new weight transfer equation, and finally obtains a novel fuzzy mean regression strategy that considers investor sentiment based on text data. We conduct empirical tests on this strategy by using the stock price data selected from CSI300 constituent stocks, as well as the text data of investors’ opinions on the internet. The results show that the strategy proposed in this study has a higher Calmar ratio than other mean regression strategies previously studied.

Abstract As an emerging cancer treatment strategy, reactive oxygen species-based tumor catalytic therapies face enormous challenges due to hypoxia and the overexpression of glutathione (GSH) in the tumor microenvironment. Herein, a self-assembled copper-based nanoplatform, TCCHA, was designed for enzyme-like catalysis-enhanced chemodynamic/photodynamic/antiangiogenic tritherapy against hepatocellular carcinoma. TCCHA was fabricated from Cu2+, 3,3′-dithiobis (propionohydrazide), and photosensitizer chlorine e6 via a facile one-pot self-assembly strategy, after which an aldehyde hyaluronic acid was coated, followed by loading of the antivascular drug AL3818. The obtained TCCHA nanoparticles exhibited pH/GSH dual-responsive drug release behaviors and multienzymatic activities, including Fenton, glutathione peroxidase-, and catalase-like activities. TCCHA, a redox homeostasis disruptor, promotes ⋅OH generation and GSH depletion, thus increasing the efficacy of chemodynamic therapy. TCCHA, which has catalase-like activity, can also reinforce the efficacy of photodynamic therapy by amplifying O2 production. In vivo, TCCHA efficiently inhibited tumor angiogenesis and suppressed tumor growth without apparent systemic toxicity. Overall, this study presents a facile strategy for the preparation of multienzyme-like nanoparticles, and TCCHA nanoparticles display great potential for enzyme catalysis-enhanced chemodynamic/photodynamic/antiangiogenic triple therapy against cancer. Graphical Abstract

Summary: Wnts are lipid-modified glycoproteins that play key roles in both embryonic development and adult homeostasis. Wnt signaling is dysregulated in many cancers and preclinical data shows that targeting Wnt biosynthesis and secretion can be effective in Wnt-addicted cancers. An integral membrane protein known as Wntless (WLS/Evi) is essential for Wnt secretion. However, WLS remains undrugged thus far. The cryo-EM structure of WLS in complex with WNT8A shows that WLS has a druggable G-protein coupled receptor (GPCR) domain. Using Active Learning/Glide, we performed an ultra-large scale virtual screening from Enamine’s REAL 350/3 Lead-Like library containing nearly 500 million compounds. 68 hits were examined after on-demand synthesis in cell-based Wnt reporter and other functional assays. ETC-451 emerged as a potential first-in-class WLS inhibitor. ETC-451 blocked WLS-WNT3A interaction and decreased Wnt-addicted pancreatic cancer cell line proliferation. The current hit provides a starting chemical scaffold for further structure or ligand-based drug discovery targeting WLS.

Abstract Drug-induced liver injury (DILI) is the leading cause of acute liver failure (ALF). Continuous and prolonged hepatic cellular oxidative stress and liver inflammatory stimuli are key signatures of DILI. DEAD-box helicase 3, X-linked (DDX3X) is a central regulator in pro-survival stress granule (SG) assembly in response to stress signals. However, the role of DDX3X in DILI remains unknown. Herein, we characterized the hepatocyte-specific role of DDX3X in DILI. Human liver tissues of DILI patients and control subjects were used to evaluate DDX3X expression. APAP, CCl4 and TAA models of DILI were established and compared between hepatocyte-specific DDX3X knockout (DDX3XΔhep) and wild-type control (DDX3Xfl/fl) mice. Hepatic expression of DDX3X was significantly decreased in the pathogenesis of DILI compared with controls in human and mice. Compared to DDX3Xfl/fl mice, DDX3XΔhep mice developed significant liver injury in multiple DILI models. DDX3X deficiency aggravates APAP induced oxidative stress and hepatocyte death by affecting the pro-survival stress granule (SG) assembly. Moreover, DDX3X deficiency induces inflammatory responses and causes pronounced macrophage infiltration. The use of targeted DDX3X drug maybe promising for the treatment of DILI in human.

Abstract How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell’s activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

A dynamic model of herd behaviour with delay time and media is established and analysed to discover the latent mechanism that represents how capital flows in the stock market. We prove that solutions of the model are uniformly bounded, and the contagion threshold [Formula: see text] is obtained. The stability of positive equilibrium points of the model with zero and nonzero delay is discussed. An optimal control problem with media is formulated, and Pontryagin's maximum principle is applied to find an optimal strategy to control herding. Several numerical simulations show the effect of media and delay on herd behaviour. Finally, the practical meaning of the presented model is briefly discussed.

ObjectiveIn order to improve the calculation accuracy of the influence of slamming load on ship fatigue damage, and evaluate ship fatigue life more effectively, a direct calculation method of ship fatigue damage which accounts for slamming load is proposed. MethodsFirst, the time domain calculation of nonlinear load is combined with the spectral analysis method of linear frequency domain, and the stress time history of the ship in a short-term sea state is obtained based on beam theory. Second, the damage of the check points is calculated using the rain flow counting method and S-N curve, the contribution and influence coefficients of nonlinear slamming load on fatigue damage are calculated with reference to the CCS guidelines, and the corresponding stress response transfer function is corrected by combining the spectral analysis method. Finally, the stress spectrum is calculated and fatigue damage accounting for nonlinear slamming is obtained. ResultsThe results show that compared with traditional spectral analysis method, it is found that the ship fatigue damage obtained by the direct calculation method accounting for slamming load is about 10%–50%. ConclusionThe proposed method can improve the accuracy of load calculation when evaluating the fatigue strength of ships sailing in harsh sea states.

Abstract This study investigates the predictability of a fixed uncertainty index (UI) for realized variances (volatility) in the international stock markets from a high-frequency perspective. We construct a composite UI based on the scaled principal component analysis (s-PCA) method and demonstrate that it exhibits significant in- and out-of-sample predictabilities for realized variances in global stock markets. This predictive power is more powerful than those of two commonly employed competing methods, namely, PCA and the partial least squares (PLS) methods. The result is robust in several checks. Further, we explain that s-PCA outperforms other dimension-reduction methods since it can effectively increase the impacts of strong predictors and decrease those of weak factors. The implications of this research are significant for investors who allocate assets globally.

Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combined with our mix-and-inject technology enables the initial phase of ceftriaxone binding to the Mycobacterium tuberculosis β-lactamase to be followed using time-resolved crystallography in real time. It is shown how a diffusion coefficient in enzyme crystals can be derived directly from the X-ray data, enabling the determination of ligand and enzyme–ligand concentrations at any position in the crystal volume as a function of time. In addition, the structure of the irreversible inhibitor sulbactam bound to the enzyme at a 66 ms time delay after mixing is described. This demonstrates that the EuXFEL can be used as an important tool for biomedically relevant research.

Insect metabolites play vital roles in regulating the physiology, behavior, and numerous adaptations of insects, which has contributed to them becoming the largest class of Animalia. However, systematic metabolomics within the insects is still unclear. The present study performed a widely targeted metabolomics analysis based on the HPLC-MS/MS technology to construct a novel integrated metabolic database presenting comprehensive multimetabolite profiles from nine insect species across three metamorphosis types. A total of 1442 metabolites were identified, including amino acids and their metabolites, organic acids and their derivatives, fatty acids (FAs), glycerophospholipids (GPs), nucleotides and their metabolites, and benzene and its substituted derivatives. Among them, 622 metabolites were used to generate a 0 and 1 matrix based on their presence or absence, and these metabolites were enriched in arachidonic acid metabolism, tyrosine metabolism, phenylalanine metabolism, and insect hormone biosynthesis pathways. Our study revealed that there is a high coincidence between the evolutionary relationships of the species and the hierarchical cluster based on the types of metabolites, while the quantities of the metabolites show a high diversity among species. The metabolome of the nine representative insects provides an important platform for implementing the analysis of insect systemic metabolites and biological events at the metabolic level.

Peroxisomes are eukaryotic organelles that sequester critical oxidative reactions and process the resulting reactive oxygen species into less toxic byproducts. Peroxisome function and formation are coordinated by peroxins (PEX proteins) that guide peroxisome biogenesis and division and shuttle proteins into the lumen and membrane of the organelle. Despite the importance of peroxins in plant metabolism and development, no plant peroxin structures have been reported. Here we report the X-ray crystal structure of the PEX4-PEX22 peroxin complex from the reference plant Arabidopsis thaliana. PEX4 is a ubiquitin-conjugating enzyme (UBC) that ubiquitinates proteins associated with the peroxisomal membrane, and PEX22 is a peroxisomal membrane protein that anchors PEX4 to the peroxisome and facilitates PEX4 activity. We co-expressed Arabidopsis PEX4 as a translational fusion with the soluble PEX4-interacting domain of PEX22 in E. coli. The fusion was linked via a protease recognition site, allowing us to separate PEX4 and PEX22 following purification and solve the structure of the complex. We compared the structure of the PEX4-PEX22 complex to the previously published structures of yeast orthologs. Arabidopsis PEX4 displays the typical UBC structure expected from its sequence. Although Arabidopsis PEX22 lacks notable sequence identity to yeast PEX22, it maintains a similar Rossmann fold-like structure. Several salt bridges are positioned to contribute to the specificity of PEX22 for PEX4 versus other Arabidopsis UBCs, and the long unstructured PEX22 tether would allow PEX4-mediated ubiquitination of distant peroxisomal membrane targets without dissociation from PEX22. The Arabidopsis PEX4-PEX22 structure also revealed that the residue altered in pex4-1 (P123L), a mutant previously isolated via a forward-genetic screen for peroxisomal dysfunction, is near the active site cysteine of PEX4. We demonstrated in vitro UBC activity for the PEX4-PEX22 complex and found that the pex4-1 enzyme has reduced in vitro ubiquitin-conjugating activity and altered specificity compared to PEX4. Our findings illuminate the role of PEX4 and PEX22 in peroxisome structure and function and provide tools for future exploration of ubiquitination at the peroxisome surface.

Abstract Introduction: This study’s objective is to investigate the effect of downregulation of micro ribonucleic acid (miR)-124a on myocardial injury after ischemia reperfusion (I/R) in rats. Methods: Sprague Dawley (SD) rats (n=20) were divided into four groups - sham, I/R, I/R+miR-124a antagomir (I/R+ant-miR-124a), and I/R+ant-normal control (NC). The pathomorphological and infarct size variance of injured myocardial tissues with IR were conducted with hematoxylin (HE) and triphenyltetrazolium chloride (TTC) staining. The expression levels of miR-124a, BAX, nuclear factor kappa B (NF-KB), Notch1, and Hes1 were examined by quantitative real-time polymerase chain reaction or Western blot in myocardium. The inflammatory cytokines interleukin (IL)-6, IL-1β, and tumor necrosis factor alpha (TNF-α) were detected by the enzyme-linked immunosorbent assay, as well as the activity of lactate dehydrogenase (LDH) and creatine kinase (CK) in serum by colorimetry. Results: The expression of miR-124a was increased in the I/R group. Compared with I/R and I/R+ant-NC groups, after downregulating miR-124a, the expression of IL-6, IL-1β, TNF-α, BAX, NF-KB, LDH, and CK were decreased, but the expression of Notch1 and Hes1 were increased. In HE staining, myocardial tissue edema, red blood cell exudation, and myocardial fiber arrangement disorder were accompanied by inflammatory cell infiltration and local necrosis in the I/R group. However, the pathological injury of myocardial tissue was alleviated after downregulating miR-124a. Additionally, TTC results showed that the myocardial infarction area was decreased in the I/R+ant-miR-124a group. Conclusion: Downregulation of miR-124a expression through Notch pathway can significantly reduce myocardial damage after 24 hours of I/R in SD rats. Therefore, miR-124a may become a potential therapeutic target for I/R injury.

EMS1 is a receptor-like kinase that recognizes the peptide ligand TPD1 to specify tapeta in Arabidopsis. Here, via a reciprocal complementation approach, the authors provide evidence that intracellular signaling by EMS1 is interchangeable with that of the brassinosteroid receptor BRI1.

Integrated modular avionics is one of the most advanced systems which has been widely applied in modern aircraft. The performance of integrated modular avionics deeply impacts flight mission. Remaining useful life prediction is the critical manner which can efficiently improve the safety and reliability of aircraft. Since integrated modular avionics is a real-time system, the prediction algorithm should have fast learning speed to satisfy the real-time requirement. In this paper, an enhanced online sequential method is proposed to predict the remaining useful life of integrated modular avionics. Firstly, this paper proposes an online sequential network which is based on the architecture of parallel layer network. Secondly, to enhance the learning capability, this paper adopts the extreme learning machine denosing autoencoder to determine the input weights of the network. Thirdly, an adaptive forgetting factor is added to further improve the performance of the proposed method. The effectiveness and the superiority of the proposed method are verified in comparison with three online sequential algorithms on the standard datasets. Finally, a degradation model is built to depict the deteriorated process of integrated modular avionics. The prediction results confirms that the proposed method can effectively address remaining useful life of integrated modular avionics.

Under the Gaussian noise assumption, the probability hypothesis density (PHD) filter represents a promising tool for tracking a group of moving targets with a time-varying number. However, inaccurate prior statistics of the random noise will degrade the performance of the PHD filter in many practical applications. This paper presents an adaptive Gaussian mixture PHD (AGM-PHD) filter for the multi-target tracking (MTT) problem in the scenario where both the mean and covariance of measurement noise sequences are unknown. The conventional PHD filters are extended to jointly estimate both the multi-target state and the aforementioned measurement noise statistics. In particular, the Normal-inverse-Wishart and Gaussian distributions are first integrated to represent the joint posterior intensity by transforming the measurement model into a new formulation. Then, the updating rule for the hyperparameters of the model is derived in closed form based on variational Bayesian (VB) approximation and Bayesian conjugate prior heuristics. Finally, the dynamic system state and the noise statistics are updated sequentially in an iterative manner. Simulations results with both constant velocity and constant turn model demonstrate that the AGM-PHD filter achieves comparable performance as the ideal PHD filter with true measurement noise statistics.

Polyketide synthase 13 (Pks13), an essential enzyme for the survival of Mycobacterium tuberculosis (Mtb), is an attractive target for new anti-TB agents. In our previous work, we have identified 2-phenylindole derivatives against Mtb. The crystallography studies demonstrated that the two-position phenol was solvent-exposed in the Pks13-TE crystal structure and a crucial hydrogen bond was lost while introducing bulkier hydrophobic groups at indole N moieties. Thirty-six N-phenylindole derivatives were synthesized and evaluated for antitubercular activity using a structure-guided approach. The structure–activity relationship (SAR) studies resulted in the discovery of the potent Compounds 45 and 58 against Mtb H37Rv, with an MIC value of 0.0625 μg/mL and 0.125 μg/mL, respectively. The thermal stability analysis showed that they bind with high affinity to the Pks13-TE domain. Preliminary ADME evaluation showed that Compound 58 displayed modest human microsomal stability. This report further validates that targeting Pks13 is a valid strategy for the inhibition of Mtb and provides a novel scaffold for developing leading anti-TB compounds.

Summary: Histone deacetylases (HDACs) drive innate immune cell-mediated inflammation. Here we identify class IIa HDACs as key molecular links between Toll-like receptor (TLR)-inducible aerobic glycolysis and macrophage inflammatory responses. A proteomic screen identified the glycolytic enzyme pyruvate kinase M isoform 2 (Pkm2) as a partner of proinflammatory Hdac7 in murine macrophages. Myeloid-specific Hdac7 overexpression in transgenic mice amplifies lipopolysaccharide (LPS)-inducible lactate and promotes a glycolysis-associated inflammatory signature. Conversely, pharmacological or genetic targeting of Hdac7 and other class IIa HDACs attenuates LPS-inducible glycolysis and accompanying inflammatory responses in macrophages. We show that an Hdac7-Pkm2 complex acts as an immunometabolism signaling hub, whereby Pkm2 deacetylation at lysine 433 licenses its proinflammatory functions. Disrupting this complex suppresses inflammatory responses in vitro and in vivo. Class IIa HDACs are thus pivotal intermediates connecting TLR-inducible glycolysis to inflammation via Pkm2. : Das Gupta et al. show that HDAC7 and other class IIa HDAC enzymes control macrophage metabolism. They initiate TLR-inducible glycolysis in these cells and interact with the glycolytic enzyme PKM2 to drive inflammatory responses in vitro and in vivo. Class IIa HDAC inhibitors may have potential for attenuating immunometabolism-linked inflammation. Keywords: glycolysis, histone deacetylases, immunometabolism, inflammation, lysine acetylation, macrophage, post-translational modification, pyruvate kinase, toll-like receptor

Mean reversion is an important property when constructing efficient contrarian strategies. Researchers observe that mean reversion has multiperiodical and asymmetric nature simultaneously in real market. To better utilize mean reversion and improve the existing online portfolio selection strategies, we propose a new online strategy named multiperiodical asymmetric mean reversion (MAMR). The MAMR strategy incorporates a multipiecewise loss function with the moving average method and then imitates the passive-aggressive algorithm. We further provide a solution via convex optimization. This strategy runs in linear time and thus is suitable for large-scale trading applications. Our empirical results testing six real market datasets show that this strategy can achieve better results in bearing higher transaction cost.

Many actual rental activities present online rental problems with multiple units of assets or equipment whose use can be continuous, separable, or discrete. Using online algorithms and competitive analysis, continuous multiple online rental problems have obtained the optimal risk control strategy and the optimal competitive ratio. For multiple online rental problems with discrete assets, first, we present an approximation algorithm for a risk control strategy and the upper bound of the optimal competitive ratio. Moreover, in practical applications, the approximation algorithm of the discrete online problem provides the approximate rental quantities in each period and the solution principle for the approximate competitive ratio. Second, we present the approximate optimal rental quantities and the correction algorithm to obtain a better competitive ratio based on the approximation algorithm. Finally, we compare the approximation algorithm with the correction algorithm by real data. Our findings show that when the approximate solution is used to replace the corrected solution, the resulting approximation error is usually less than the magnitude of 1ms where m is the total units of certain assets or equipment and s is the price to buy one unit in each period. Keywords: Discrete multiple online rental problem, Risk control strategy, Online algorithms, Competitive ratio

Abstract Background Breast cancer negatively affects women’s health worldwide. The tumour microenvironment plays a critical role in tumour initiation, proliferation, and metastasis. Cancer cells are traditionally grown in two-dimensional (2D) cultures as monolayers on a flat solid surface lacking cell–cell and cell–matrix interactions. These experimental conditions deviate from the clinical situation. Improved experimental systems that can mimic the in vivo situation are required to discover new therapies, particularly for anti-angiogenic agents that mainly target intercellular factors and play an essential role in treating some cancers. Methods Chitosan can be modified to construct three-dimensional (3D) tumour models. Here, we report an in vitro 3D tumour model using a hydroxyethyl chitosan/glycidyl methacrylate (HECS–GMA) hydrogel produced by a series of chitosan modifications. Parameters relating to cell morphology, viability, proliferation, and migration were analysed using breast cancer MCF-7 cells. In a xenograft model, secretion of angiogenesis-related growth factors and the anti-angiogenic efficacy of Endostar and Bevacizumab in cells grown in HECS–GMA hydrogels were assessed by immunohistochemistry. Results Hydroxyethyl chitosan/glycidyl methacrylate hydrogels had a highly porous microstructure, mechanical properties, swelling ratio, and morphology consistent with a 3D tumour model. Compared with a 2D monolayer culture, breast cancer MCF-7 cells residing in the HECS–GMA hydrogels grew as tumour-like clusters in a 3D formation. In a xenograft model, MCF-7 cells cultured in the HECS–GMA hydrogels had increased secretion of angiogenesis-related growth factors. Recombinant human endostatin (Endostar), but not Bevacizumab (Avastin), was an effective anti-angiogenic agent in HECS–GMA hydrogels. Conclusions The HECS–GMA hydrogel provided a 3D tumour model that mimicked the in vivo cancer microenvironment and supported the growth of MCF7 cells better than traditional tissue culture plates. The HECS–GMA hydrogel may offer an improved platform to minimize the gap between traditional tissue culture plates and clinical applicability. In addition, the anti-angiogenic efficacy of drugs such as Endostar and Bevacizumab can be more comprehensively studied and assessed in HECS–GMA hydrogels.

Malaria, schistosomiasis and leishmaniases are among the most prevalent tropical parasitic diseases and each requires new innovative treatments. Targeting essential parasite pathways, such as those that regulate gene expression and cell cycle progression, is a key strategy for discovering new drug leads. In this study, four clinically approved anti-cancer drugs (Vorinostat, Belinostat, Panobinostat and Romidepsin) that target histone/lysine deacetylase enzymes were examined for in vitro activity against Plasmodium knowlesi, Schistosoma mansoni, Leishmania amazonensis and L. donovani parasites and two for in vivo activity in a mouse malaria model. All four compounds were potent inhibitors of P. knowlesi malaria parasites (IC50 9–370 nM), with belinostat, panobinostat and vorinostat having 8–45 fold selectivity for the parasite over human neonatal foreskin fibroblast (NFF) or human embryonic kidney (HEK 293) cells, while romidepsin was not selective. Each of the HDAC inhibitor drugs caused hyperacetylation of P. knowlesi histone H4. None of the drugs was active against Leishmania amastigote or promastigote parasites (IC50 > 20 μM) or S. mansoni schistosomula (IC50 > 10 μM), however romidepsin inhibited S. mansoni adult worm parings and egg production (IC50 ∼10 μM). Modest in vivo activity was observed in P. berghei infected mice dosed orally with vorinostat or panobinostat (25 mg/kg twice daily for four days), with a significant reduction in parasitemia observed on days 4–7 and 4–10 after infection (P

MAIT cells are activated by MR1 restricted antigens derived from riboflavin biosynthesis. Here the authors characterize MAIT cell antigenicity and synthesize a water stable antigen that activates human MAIT cellsin vitro and mouse MAIT cells in vivo.

Brassinosteroids (BRs) are essential hormones for plant growth and development. Enzymes DET2 and CYP90 family are responsible for BR biosynthesis in seed plants. Yet, their roles in non-seed plants are unknown. Here, we report the first functional study of DET2 and all 4 CYP90 genes isolated from Selaginella moellendorfii. Sm89026 (SmCPD) belonged to a clade with CYP90A1 (CPD) and CYP90B1 (DWF4) while Sm182839, Sm233379 and Sm157387 formed a distinct clade with CYP90C1 (ROT3) and CYP90D1. SmDET2, SmCPD and Sm157387 were highly expressed in both leaves and strobili while Sm233379 was only highly expressed in the leaves but not strobili, implying their differential functions in a tissue-specific manner in S. moellendorfii. We showed that only SmDET2 and SmCPD completely rescued Arabidopsis det2 and cpd mutant phenotypes, respectively, suggestive of their conserved BR biosynthetic functions. However, neither SmCPD nor other CYP90 genes rescued any other cyp90 mutants. Yet overexpression of Sm233379 altered plant fertility and BR response, which means that Sm233379 is not an ortholog of any CYP90 genes in Arabidopsis but appears to have a BR function in the S. moellendorfii leaves. This function is likely turned off during the development of the strobili. Our results suggest a dramatic functional divergence of CYP90 family in the non-seed plants. While some of them are functionally similar to that of seed plants, the others may be functionally distinct from that of seed plants, shedding light for future exploration.

This article contains datasets related to the research article titled a novel jump diffusion model based on SGT distribution and its applications (”A novel jump diffusion model based on SGT distribution and its applications” (W.J. Xu, G.F. Liu, H.Y. Li, 2016) [1]). The datasets contain continuous composite daily percentage return values which are computed from the daily closing prices. Firstly, we describe statistical properties of the datasets. Then, the datasets are split into two samples, the in-sample data and out-of-sample data. The datasets can be used as benchmarks for testing the performances of jump diffusion models.

With the increasing awareness of climate change, food carbon footprint (CF) has been analysed by many studies. Wheat is one of the world’s most favoured food sources, reaching millions of people on a daily basis. In this study, the wheat CF and total greenhouse gas (GHG) emissions were investigated using national statistical data for the period of 2003-2016. There is an interactive correlation between the wheat CF value and yield, and wheat CF could be reduced by increasing food yield. In addition, the results showed that the changes in product CF values of the crop during 14 y were minor. However, due to the increase of total national yield, the GHG emissions from wheat production were increased significantly. On the other hand, the product CF, GDP (gross domestic product) CF, and total GHG emissions from wheat production from 2017 to 2021 were predicted by grey system. From the viewpoint of GDP CF, Chinese agricultural sector has completed the 2020 emission reduction targets. However, the total GHG emissions from wheat production were increased largely. It indicated that reducing food consumption and dietary shift to the food with low CF should be paid more attention to mitigate climate change.

Maize is an important food crop, reaching millions of people on a daily basis. In this research, the greenhouse gas (GHG) emissions of maize production over the period of 2003-2016 were investigated using national statistical data. During this period, total amount of GHG emissions from maize increased gradually. The cumulative contributions of different influencing factors in 14 y showed that agricultural economic development level was the major reason of increasing GHG emissions, while agricultural efficiency was the major reason of declining GHG emissions. On the other hand, spatial and temporal patterns of maize carbon footprint (CF) showed that improving crop yield could reduce food CF, and the increased total GHG emissions from maize production was mainly because of expand production. Maize CF values showed great differences among regions. The research suggested that the cropping regions of the crops with high CF and low yield per ha should be optimized to reduce GHG emissions.

Mix-and-inject serial crystallography (MISC) is a technique designed to image enzyme catalyzed reactions in which small protein crystals are mixed with a substrate just prior to being probed by an X-ray pulse. This approach offers several advantages over flow cell studies. It provides (i) room temperature structures at near atomic resolution, (ii) time resolution ranging from microseconds to seconds, and (iii) convenient reaction initiation. It outruns radiation damage by using femtosecond X-ray pulses allowing damage and chemistry to be separated. Here, we demonstrate that MISC is feasible at an X-ray free electron laser by studying the reaction of M. tuberculosis ß-lactamase microcrystals with ceftriaxone antibiotic solution. Electron density maps of the apo-ß-lactamase and of the ceftriaxone bound form were obtained at 2.8 Å and 2.4 Å resolution, respectively. These results pave the way to study cyclic and non-cyclic reactions and represent a new field of time-resolved structural dynamics for numerous substrate-triggered biological reactions.

The welded stiffened plate is widely used in naval architecture and offshore engineering as a basic structural member. The aim of this study is to investigate the effect of welding residual stress and steel grade on the ultimate strength of stiffened plates under uniaxial compressive load by non-linear finite element analysis. Nineteen stiffened plates built with three types of stiffeners with various column slenderness ratios provided in the ISSC’2000 VI.2 benchmark calculations are employed in the present study. The commercial finite element code ABAQUS is applied to simulate the collapse behavior of the stiffened plates and verified against the benchmark calculations. Fabrication-related imperfections, such as initial deflections and residual stresses, are accounted for in the simulations. The ultimate strength of stiffened plates built in common shipbuilding steels, namely S235, S315, S355 and S390, are investigated by varying the yield strength of materials in the simulation. Analysis of the numerical results shows that the welding residual stress reduces the ultimate strength of stiffened plates, and increase in yield strength of the material can effectively improve the ultimate strength of common ship stiffened plates; and quantitative analyses of their influences have also been performed.

HipA is a bacterial serine/threonine protein kinase that phosphorylates targets, bringing about persistence and multidrug tolerance. Autophosphorylation of residue Ser150 is a critical regulatory mechanism of HipA function. Intriguingly, Ser150 is not located on the activation loop, as are other kinases; instead, it is in the protein core, where it forms part of the ATP-binding “P loop motif.” How this buried residue is phosphorylated and regulates kinase activity is unclear. Here, we report multiple structures that reveal the P loop motif's exhibition of a remarkable “in-out” conformational equilibrium, which allows access to Ser150 and its intermolecular autophosphorylation. Phosphorylated Ser150 stabilizes the “out state,” which inactivates the kinase by disrupting the ATP-binding pocket. Thus, our data reveal a mechanism of protein kinase regulation that is vital for multidrug tolerance and persistence, as kinase inactivation provides the critical first step in allowing dormant cells to revert to the growth phenotype and to reinfect the host.

We introduce the compound interest rate into the continuous version of the online leasing problem and discuss the generalized model by competitive analysis. On the one hand, the optimal deterministic strategy and its competitive ratio are obtained; on the other hand, a nearly optimal randomized strategy is constructed and a lower bound for the randomized competitive ratios is proved by Yao's principle. With the help of numerical examples, the theoretical results show that the interest rate puts off the purchase date and diminishes the uncertainty involved in the decision making.

This article focuses on China's policy response to US House Speaker Nancy Pelosi's visit to Taiwan in August 2022. Pelosi's action triggered a surge of popular nationalist sentiments in China, but the response of the Chinese government was far less tough than what many popular nationalists had expected. The article argues that the Chinese government's policy choice in response to Pelosi's visit to Taiwan did not depend on the demands of popular nationalists, but rather was based on a cost-benefit analysis according to its perceptions. The influence of popular nationalism on the government's foreign policy choices has been exaggerated owing to an overestimation of the government's reliance on nationalism for its regime legitimacy, and an underestimation of the government's control over public opinion and nationalist activities. [ABSTRACT FROM AUTHOR]