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14 result(s) for "Yang, Wuke"
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Postoperative analgesic effectiveness of quadratus lumborum block: systematic review and meta-analysis for adult patients undergoing hip surgery
Background Quadratus lumborum block is a truncal block with several technique variations. It has been reported as providing effective analgesia for postoperative pain. The aim of this study is to determine the efficacy of the QL block in providing postoperative analgesia for hip surgery when compared with placebo or no block or other analgesic techniques. Methods Randomized trials evaluating quadratus lumborum block benefits in elective hip surgery were sought. The primary outcome was the 24 h opioid requirement after surgery. Two independent reviewers selected the studies and extracted the data. Results Thirteen randomized-controlled trials were included in this study. The included studies had significant heterogeneity regarding comparator groups; therefore, a limited quantitative analysis was undertaken for the comparison of QL block versus no block or placebo only. QL block reduced the opioid use by 15.78 (95% CI, 2.31 to 29.26) mg IME in the first postoperative 24 h compared with no block or placebo with no difference in static pain scores, pain grade was reduced by 2.95 (95% CI, 2.40 to 3.60) in the QL block group compared with placebo or no block in the first postoperative 24 h during movement. Conclusions Our meta-analysis indicates that QL block may be effective for analgesia in patients after hip surgery compared with placebo or no block. There is currently limited evidence comparing QL block with other analgesic techniques for hip surgery.
Identification and functional characterization of three iridoid synthases in Gardenia jasminoides
Iridoids are a class of noncanonical monoterpenes that are found naturally in the plant kingdom mostly as glycosides. Over 40 iridoid glycosides (e.g., geniposide, gardenoside and shanzhiside) have been isolated from Gardenia jasminoides. They have multiple pharmacological properties and health-promoting effects. However, their biosynthetic pathway is poorly understood, and the iridoid synthase (ISY) responsible for the cyclization of the core scaffold remains unclear. In this study, three homologs of ISYs from G. jasminoides (GjISY, GjISY2 and GjISY4) were identified on the basis of transcriptomic data and functionally characterized. The genomic structure and intron–exon arrangement revealed that all three ISYs contained an intron. Biochemical assays indicated that all three recombinant enzymes reduced 8-oxogeranial to nepetalactol and its open forms (iridodials) as the products of the classical CrISY (Catharanthus roseus). In addition, all three enzymes reduced progesterone to 5-β-prognane-3,20-dione. However, only GjISY2 and GjISY4 reduced 2-cyclohexen-1-one to cyclohexanone. Overall, the GjISY2 expression levels in the flowers and fruits were similar to the GjISY and GjISY4 expression levels. By contrast, the GjISY2 expression levels in the upper and lower leaves were substantially higher than the GjISY and GjISY4 expression levels. Among the three, GjISY2 exhibited the highest catalytic efficiency for 8-oxogeranial. GjISY2 might be the major contributor to iridoid biosynthesis in G. jasminoides. Collectively, our results advance the understanding of iridoid scaffold/iridoid glycoside biosynthesis in G. jasminoides and provide a potential target for metabolic engineering and breeding.
A Novel Hybrid Improved RIME Algorithm for Global Optimization Problems
The RIME algorithm is a novel physical-based meta-heuristic algorithm with a strong ability to solve global optimization problems and address challenges in engineering applications. It implements exploration and exploitation behaviors by constructing a rime-ice growth process. However, RIME comes with a couple of disadvantages: a limited exploratory capability, slow convergence, and inherent asymmetry between exploration and exploitation. An improved version with more efficiency and adaptability to solve these issues now comes in the form of Hybrid Estimation Rime-ice Optimization, in short, HERIME. A probabilistic model-based sampling approach of the estimated distribution algorithm is utilized to enhance the quality of the RIME population and boost its global exploration capability. A roulette-based fitness distance balanced selection strategy is used to strengthen the hard-rime phase of RIME to effectively enhance the balance between the exploitation and exploration phases of the optimization process. We validate HERIME using 41 functions from the IEEE CEC2017 and IEEE CEC2022 test suites and compare its optimization accuracy, convergence, and stability with four classical and recent metaheuristic algorithms as well as five advanced algorithms to reveal the fact that the proposed algorithm outperforms all of them. Statistical research using the Friedman test and Wilcoxon rank sum test also confirms its excellent performance. Moreover, ablation experiments validate the effectiveness of each strategy individually. Thus, the experimental results show that HERIME has better search efficiency and optimization accuracy and is effective in dealing with global optimization problems.
A connection from Arctic stratospheric ozone to El Niño-Southern oscillation
Antarctic stratospheric ozone depletion is thought to influence the Southern Hemisphere tropospheric climate. Recently, Arctic stratospheric ozone (ASO) variations have been found to affect the middle-high latitude tropospheric climate in the Northern Hemisphere. This paper demonstrates that the impact of ASO can extend to the tropics, with the ASO variations leading El Niño-Southern Oscillation (ENSO) events by about 20 months. Using observations, analysis, and simulations, the connection between ASO and ENSO is established by combining the high-latitude stratosphere to troposphere pathway with the extratropical to tropical climate teleconnection. This shows that the ASO radiative anomalies influence the North Pacific Oscillation (NPO), and the anomalous NPO and induced Victoria Mode anomalies link to the North Pacific circulation that then influences ENSO. Our results imply that incorporating realistic and time-varying ASO into climate system models may help to improve ENSO predictions.
Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering
Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Pro tein M utational E ffect P redictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.
The Neural Basis of Herding Decisions in Enterprise Clustering: An Event-Related Potential Study
Herding behavior refers to the social phenomenon in which people are intensely influenced by decisions and behaviors of others in the same group. Even though several recent studies have explored the neural basis of herding decisions in people’s daily life (e.g., consumption decision), the neural processing of herding decisions in enterprise behavior is still unclear. To address this issue, this study extracted the event-related potentials (ERPs) from electroencephalographic data when participants (i.e., top executives in real enterprises) performed a choice task in which they should judge whether to let their enterprises settle in an industrial zone when the occupancy rate of the industrial zone is low or high. The behavioral results showed that participants elicited a higher acceptance rate in the high occupancy rate condition than the low one, suggesting the existence of herding tendency in top executives’ business decisions. The ERPs results indicated that anticonformity choices induced a larger N2 amplitude compared to herding choices, demonstrating that participants may experience greater perceived risk and higher decisional conflicts when they made anticonformity choices. In contrast, we observed that herding choices induced a larger LPP amplitude relative to anticonformity choices, hinting that participants may experience better evaluation categorization and greater decision confidence when they made herding choices. Based on these results, this study provides new insights into the neural basis of top executives’ herding decisions in business behavior.
A Comparison of Two Monoterpenoid Synthases Reveals Molecular Mechanisms Associated With the Difference of Bioactive Monoterpenoids Between Amomum villosum and Amomum longiligulare
The fruits of Amomum villosum and Amomum longiligulare are both used medicinally as Fructus Amomi the famous traditional Chinese medicine, however, the medicinal quality of A. villosum is better than that of A. longiligulare . Volatile terpenoids in the seeds, especially bornyl acetate and borneol, are the medicinal components of Fructus Amomi. The volatile terpenoids and transcriptome of developing seeds of A. villosum and A. longiligulare were compared in this study. The result revealed that the bornyl acetate and borneol contents were higher in A. villosum than in A. longiligulare . Additionally, six terpenoid synthase genes ( AlTPS1–AlTPS6 ) were screened from the transcriptome of A. longiligulare , and AlTPS2 and AlTPS3 were found to share 98 and 83% identity with AvTPS2 and AvBPPS (bornyl diphosphate synthase) from A. villosum , respectively. BPPS is the key enzyme for the biosynthesis of borneol and bornyl acetate. Biochemical assays improved that AlTPS2 had an identical function to AvTPS2 as linalool synthase; however, AlTPS3 produced camphene as the major product and bornyl diphosphate (BPP) as the secondary product, whereas AvBPPS produced BPP as its major product. There was only one different amino acid between AlTPS3 (A496) and AvBPPS (G495) in their conserved motifs, and the site-directed mutation of A496G in DTE motif of AlTPS3 changed the major product from camphene to BPP. Molecular docking suggests that A496G mutation narrows the camphene-binding pocket and decreases the BPP-binding energy, thus increases the product BPP selectivity of enzyme. In addition, the expression level of AvBPPS was significantly higher than that of AlTPS3 in seeds, which was consistent with the related-metabolites contents. This study provides insight into the TPS-related molecular bases for the biosynthesis and accumulation differences of the bioactive terpenoids between A. villosum and A. longiligulare . BPPS , the key gene involved in the biosynthesis of the active compound, was identified as a target gene that could be applied for the quality-related identification and breeding of Fructus Amomi .
Substantial Near-Surface Spring Ozone Enhancement due to Stratospheric Intrusion in the Northeastern Qinghai–Tibet Plateau, China
Stratospheric ozone intrusion plays an important role in affecting the tropospheric ozone concentrations in the troposphere through stratosphere to troposphere transport (STT). Nevertheless, there are very limited studies on the quantification of the effect. Focusing on a typical event on 9–12 May 2015, when STT occurs over the northeastern Qinghai–Tibet Plateau of China, the observations and reanalysis data indicate that STT is accompanied by high potential vorticity and low specific humidity. In order to quantify the extent to which the STT may elevate the ozone concentrations, an inert tracer is added to the boundary conditions of the Community Multiscale Air Quality (CMAQ), which is driven by the Weather Research and Forecasting (WRF) model. The meteorological conditions simulated by WRF nicely reproduce the distributions of potential vorticity (PV) and water vapor in the upper troposphere. Through the physical processes of diffusion, advection, and dry and wet deposition, the ozone tracer concentrations simulated from CMAQ well capture the spatial propagation and evolution of stratospheric ozone intrusion over Qinghai–Tibet Plateau, warranting the confidence in interpreting the simulated results in quantifying the STT. The STT event indicates the near-surface ozone enhancement of approximately 10–20 ppbv covering half of Qinghai province, even spreading to a broader area of eastern China. For the typical remote mountain such as Waliguan, clear ozone enhancement is obtained over the lower level of the troposphere. The method used in this study is applicable to other regions as well, which can be applied in the future to detect the STT at a wider spatiotemporal scale and help the policymakers identify the ozone sources and make efficient strategies for the ozone pollution control.
Study on Production Decline Law of Multilateral Horizontal Well in Coalbed Methane Reservoirs
China is rich in coal-bed gas resources, however, because of the low abundance of coalbed methane, the low filtration ability of coal matrix and the complexity of gas streaming process, causing the single well productivity of conventional coalbed methane well is low. To improve the individual well producing rate and the economic effects of coal-bed gas reservoirs, the multilateral horizontal wells are being popularized on a large scale. Therefore, it is necessary to study the production decline law of multi-branch horizontal well in coalbed methane reservoirs. Based on the seepage physical model, a mathematical model based on resolution-diffusion-filtration was established. By using the point source function, the bottom pressure response function of single branch horizontal well was solved. By utilizing the theory of pressure superposition, mathematical model of production decline was gained, and the key elements influencing production decline were analyzed. The research results in this paper will have some guiding significance for efficient development of coalbed methane.