Tanshinone IIA ameliorates energy metabolism dysfunction of pulmonary fibrosis using 13C metabolic flux analysis

Evidence indicates that metabolic reprogramming characterized by the changes in cellular metabolic patterns contributes to the pathogenesis of pulmonary fibrosis (PF). It is considered as a promising therapeutic target anti-PF. The well-documented against PF properties of Tanshinone IIA (Tan IIA) have been primarily attributed to its antioxidant and anti-inflammatory potency. Emerging evidence suggests that Tan IIA may target energy metabolism pathways, including glycolysis and tricarboxylic acid (TCA) cycle. However, the detailed and advanced mechanisms underlying the anti-PF activities remain obscure. In this study, we applied [U-13C]-glucose metabolic flux analysis (MFA) to examine metabolism flux disruption and modulation nodes of Tan IIA in PF. We identified that Tan IIA inhibited the glycolysis and TCA flux, thereby suppressing the production of transforming growth factor-β1 (TGF-β1)-dependent extracellular matrix and the differentiation and proliferation of myofibroblasts in vitro. We further revealed that Tan IIA inhibited the expression of key metabolic enzyme hexokinase 2 (HK2) by inhibiting phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR)/hypoxia-inducible factor 1α (HIF-1α) pathway activities, which decreased the accumulation of abnormal metabolites. Notably, we demonstrated that Tan IIA inhibited ATP citrate lyase (ACLY) activity, which reduced the collagen synthesis pathway caused by cytosol citrate consumption. Further, these results were validated in a mouse model of bleomycin-induced PF. This study was novel in exploring the mechanism of the occurrence and development of Tan IIA in treating PF using 13C-MFA technology. It provided a novel understanding of the mechanism of Tan IIA against PF from the perspective of metabolic reprogramming.

The profiles of mitochondrial respiration and glycolysis using extracellular flux analysis in porcine enterocyte IPEC-J2

The porcine intestinal mucosa require large amounts of energy for nutrient processing and cellular functions and is vulnerable to injury by weaning stress involving bioenergetics failure. The mitochondrial bioenergetic measurement in porcine enterocytes have not been defined. The present study was to establish a method to measure mitochondrial respiratory function and profile mitochondrial function of IPEC-J2 using cell mito stress test and glycolysis stress test assay by XF24 extracellular flux analyzer. The optimal seeding density and concentrations of the injection compounds were determined to be 40,000 cells/well as well as 0.5 μ M oligomycin, 1 μM carbonyl cyanide p-trifluoromethoxy-phenylhydrazone(FCCP) and 1 μM rotenone & antimycin A, respectively. The profiles of mitochondrial respiration and glycolysis confirmed that porcine enterocyte preferentially derived much more energy from glutamine than glucose. These results will provide a basis for further study of mitochondrial function and bioenergetics of the porcine small intestine.

Metabolic flux analysis on arachidonic acid fermentation

The analysis of flux distributions in metabolic networks has become an important approach for understand-ing the fermentation characteristics of the process.A model of metabolic flux analysis of arachidonic acid(AA)synthesis in Mortierella alpina ME-1 was established and carbon flux distributions were estimated in different fermentation phases with different concentrations of N-source.During the expo-nential,decelerating and stationary phase,carbon fluxes to AA were 3.28%,8.80%and 6.97%,respectively,with sufficient N-source broth based on the flux of glucose uptake,and those were increased to 3.95%,19.21%and 39.29%,respectively,by regulating the shifts of carbon fluxes via fermentation with limited N-source broth and adding 0.05% NaNO_(3) at 96 h.Eventually AA yield was increased from 1.3 to 3.5 g·L^(−1).These results suggest a way to improve AA fermentation,that is,fermentation with limited N-source broth and adding low concentration N-source during the stationary phase.

Flux Balance Analysis Reveals Potential Anti-HIV-1 Metabolic Targets

Background:Human immunodeficiency virus type 1(HIV-1)remains a persistent global health challenge.Therefore,a continuous exploration of novel therapeutic strategies is essential.A comprehensive understanding of how HIV-1 utilizes the cellular metabolism machinery for replication can provide insights into new therapeutic approaches.Methods:In this study,we performed a flux balance analysis using a genome-scale metabolic model(GEM)integrated with an HIV-1 viral biomass objective function to identify potential targets for anti–HIV-1 interventions.We generated a GEM by integrating an HIV-1 production reaction into CD4+T cells and optimized for both host and virus optimal states as objective functions to depict metabolic profiles of cells in the status for optimal host biomass maintenance or for optimal HIV-1 virion production.Differential analysis was used to predict biochemical reactions altered optimal for HIV-1 production.In addition,we conducted in silico simulations involving gene and reaction knock-outs to identify potential anti–HIV-1 targets,which were subsequently validated by human phytohemagglutinin(PHA)blasts infected with HIV-1.Results:Differential analysis identified several altered biochemical reactions,including increased lysine uptake and oxidative phosphorylation(OXPHOS)activities in the virus optima compared with the host optima.In silico gene and reaction knock-out simulations revealed de novo pyrimidine synthesis,and OXPHOS could serve as potential anti–HIV-1 metabolic targets.In vitro assay confirmed that targeting OXPHOS using metformin could suppress the replication of HIV-1 by 56.6%(385.4±67.5 pg/mL in the metformintreated group vs.888.4±32.3 pg/mL in the control group,P<0.001).Conclusion:Our integrated host-virus genome-scale metabolic study provides insights on potential targets(OXPHOS)for anti-HIV therapies.

A novel hyper-cube shrink algorithm to predict metabolic fluxes based on enzyme activity only

OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.

Kinetic roles of vibrational excitation in RF plasma assisted methane pyrolysis

A combined experimental and simulational work was carried out in this paper to investigate the kinetic effects of non-equilibrium excitation by direct electron impact on low temperature pyrolysis of CH4 in a RF dielectric barrier discharge.Special attention was placed on the vibrational chemistry of CH4 and some other important products including H2,C2H2,C2H4,C2H6 and C3H8 largely produced in CH4/He discharge under an intermediate reduced electric field ranging 51-80 Td.A detailed kinetic mechanism incorporating a set of electron impact reactions,electron-ion recombination reactions,negative ions attachment reactions,charge exchange reactions,reactions involving vibrationally excited molecules and the relaxation process of vibrationally excited species was assembled and experimentally validated.The modeling results showed a reasonable agreement with the experimentally measured results in terms of CH4 conversion and products production including C2 hydrocarbons and hydrogen.A linear increasing trend of methane conversion with increasing plasma power input was discovered,which suggested a strong dependence of molecular excitation on energy input.Both the CH4/He mole ratio and the reactor temperature play significant roles in CH4 conversion and major products production.The experimental results showed that the selectivity of value-added products C2H4 and H2 keeps essentially unchanged with increasing energy input,mostly because the contribution CH4 ionization and He excitation effectively compete with vibrational excitation and dissociation of CH4 molecule with the E/N value increasing.The calculated results showed that the typical relaxation time of vibrational states is comparable to the gas-kinetics time in a CH4/He discharge mixture,thus the vibrationally excited molecules can significantly accelerate chemical reactions through an effective decrease of activation energy.The path flux analysis revealed that the vibrationally excited molecules CH4(v)and H2(v)enhanced chain propagation reactions,such as CH4(v)+H→CH3+H2,CH4(v)+CH→C2 H4+H,and H2(v)+C→CH+H,further stimulating the production of active radicals and final products.Specifically,H2(v)+C→CH+H was responsible for 7.9%of CH radical formation and CH4(v)+CH→C2 H4+H accounted for 31.4%of total C2 H4 production.This kinetic study provides new sights in demonstrating the contribution of vibrationally excited molecules in RF plasma assisted methane pyrolysis.

Optimization of the bioconversion of glycerol to ethanol using Escherichia coli by implementing a bi-level programming framework for proposing gene transcription control strategies based on genetic algorithms

In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approaches that can be exploited in order to enhance yield of processes which are based on biological reactions. Here, we propose an evolutionary approach aiming to suggest different mutant for augmenting ethanol yield using glycerol as substrate in Escherichia coli. We found that this algorithm, even though is far from providing the global optimum, is able to uncover genes that a global optimizer would be incapable of. By over-expressing accB, eno, dapE, and accA mutants in ethanol production was augmented up to 2 fold compared to its counterpart E. coli BW25113.

PRINCIPLES AND PARAMETER DESIGN FOR AC-DC THREE-DEGREE FREEDOM HYBRID MAGNETIC BEARINGS

To simplify the mechanical structure, decrease the overall system size of the 3-degree freedom axial-radial magnetic bearings and reduce the manufacturing costs as well as operating costs, an innovated AC-DC 3-degree freedom hybrid magnetic bearing is proposed, which is driven by a DC amplifier in axial direction and a 3-phase power converter in radial directions respectively, and the axial and radial bias magnetic fluxes are provided with a common radial polarized permanent magnet ring. The principle producing magnetic suspension forces is introduced. By using equivalent magnetic circuit method, the calculation formulas of magnetic suspension forces and the mathematics models of the system are deduced. Nonlinearities of suspension forces and cross coupling between different degree freedoms are studied further by calculating the suspension forces at different displacements and control currents to validate the feasibility of the mathematics model. Then based on the mathematics models of the bearing, a control method of this novel bearing is designed. Lastly, the methods on parameter design and calculations of the bearing are presented, and an applicable prototype is simulated to analyze the magnetic path by using finite element analysis. The theory analysis and simulation results have shown that this magnetic bearing incorporates the merits of 3-phase AC drive, permanent magnet flux biased and axial-radial combined control, and reduces overall system size and has higher efficiency and lower cost, This innovated magnetic bearing has a wide application in super-speed and super-precision numerical control machine tools, bearingless motors, high-speed flywheels, satellites, etc.

BRAKE TEST OF SiCp/A356 BRAKE DISK AND INTERPRETATION OF EXPERIMENTAL RESULTS

Material properties are obvious different between aluminum matrix composites and iron and steel materials. After the brake disk braked at the same speed, the average temperature of the aluminum brake disk is 1.5 times as high as one of iron and steel brake disk, the thermal expansion value of the aluminum brake disk is 2 times as big as one of iron and steel brake disk. Mechanical property of the material decreases with the temperature increasing generally during braking, on the other hand, the big thermal stress in the brake disk happens because the material expansion is constrained. Firstly, the reasons of the thermal stress generation and the fracture failure of brake disks during braking are analyzed qualitatively by virtue of three-bar stress frame and sandwich deformation principles in physic, and then the five constraints which cause the thermal stress are summarized. On the base of the experimental results on the 1：1 emergency brake test, the thermal stress and temperature fields are simulated; The behavior of the fracture failure is interpreted semi-quantitatively by finite element analysis, There is the coincident forecast for the fraction position in term of the two methods. In the end, in the light of the analysis and calculation results, it is the general principles observed by the structure design and assembly of the brake disk that are summarized.

Double-averaging analysis of turbulent kinetic energy fluxes and budget based on large-eddy simulation

The turbulent flow over a channel bed roughened by three layers of closely packed spheres with a Reynolds number of Re= 15 000 is investigated using the large eddy simulation（LES） and the double-averaging（DA） method. The DA velocity is compared with the results of the corresponding laboratory experiments to validate the LES results. The existence of the types of vortex structures is demonstrated by the Q-criterion above the permeable bed. The turbulent kinetic energy（TKE） fluxes and budget are quantified and discussed. The results show that the TKE fluxes are directed downward and downstream near the virtual bed level. In the TKE budget, the form-induced diffusion rate is significant in the vicinity of the crest bed level, and the TKE production rate and the dissipation rate attain their peaks at the crest bed level and decrease sharply below it.

Noise effect in metabolic networks

Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term‘noise＇, and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Constructing efficient bacterial cell factories to enable one-carbon utilization based on quantitative biology:A review

Developing methylotrophic cell factories that can efficiently catalyze organic one-carbon(C1)feedstocks derived from electrocatalytic reduction of carbon dioxide into bio-based chemicals and biofuels is of strategic significance for building a carbon-neutral,sustainable economic and industrial system.With the rapid advancement of RNA sequencing technology and mass spectrometer analysis,researchers have used these quantitative microbiology methods extensively,especially isotope-based metabolic flux analysis,to study the metabolic processes initiating from C1 feedstocks in natural C1-utilizing bacteria and synthetic C1 bacteria.This paper reviews the use of advanced quantitative analysis in recent years to understand the metabolic network and basic principles in the metabolism of natural C1-utilizing bacteria grown on methane,methanol,or formate.The acquired knowledge serves as a guide to rewire the central methylotrophic metabolism of natural C1-utilizing bacteria to improve the carbon conversion efficiency,and to engineer non-C1-utilizing bacteria into synthetic strains that can use C1 feedstocks as the sole carbon and energy source.These progresses ultimately enhance the design and construction of highly efficient C1-based cell factories to synthesize diverse high value-added products.The integration of quantitative biology and synthetic biology will advance the iterative cycle of understand–design–build–testing–learning to enhance C1-based biomanufacturing in the future.

Laboratory study of a hydronic concrete deck heated externally in a controlled sub-freezing environment

Geothermal heating of bridge decks is a reliable and sustainable method for bridge de-icing that has been in-creasing in demand since conventional de-icing methods were proved to be environmentally hazardous.Previous research on geothermal heating of bridge decks relied on hydronic pipes embedded inside of bridge decks,which are confined to newly constructed bridges.For existing bridges,a newly devised method for external heating has been recently tested under limited laboratory conditions to determine its overall performance.This study explores laboratory heating tests of a concrete slab with a thickness representing a typical concrete bridge deck.This slab was equipped with a simulated geothermal bridge de-icing system and tested inside a freezer subjected to sub-freezing controlled conditions.Various winter scenarios were applied to the system to determine its heat-ing performance and how feasible it will be for the system to be transferred to the field.A prediction equation was developed to estimate the total energy reserves required to permit de-icing,and statistical analysis was performed and validated with test results.The slab surface heat flux was estimated to range from 27 W/m^(2) K to 73 W/m^(2) K from the heating test.The externally-heated deck can be designed with the developed prediction equation for snow melting.

Using high-throughput data and dynamic flux balance modeling techniques to identify points of constraint in xylose utilization in Saccharomyces cerevisiae

Background Several enzymes and cofactors have been identified as contributing to the slow utilization of xylose by xylose-fermenting strains of Saccharomyces cerevisiae.However,there has been no consensus on which of these possible bottle-necks are the most important to address.A previous strain characterization study from our lab suggested that insufficient NAD+limits fermentation and may be the most important bottleneck affecting utilization of xylose for the production of ethanol.The development and validation of a genome scale dynamic flux balance model would help to verify the existence and extent of this and other metabolic bottlenecks and suggest solutions to guide future strain development thereby minimiz-ing bottleneck impact on process economics.Results A dynamic flux balance model was developed to identify bottlenecks in several strains of S.cerevisiae,both with wild-type pentose phosphate pathway expression and with the pathway over expressed.ZWF1 was found to be limiting in the oxidative portion of the pentose phosphate pathway under oxygen replete conditions.This pathway is used to regenerate NADPH.Under oxygen limiting conditions,respiration of xylose was limited by the lack of oxygen as a terminal electron acceptor.Ethanol production was also limited under these conditions due to the inability to balance NAD+/NADH.The model suggests the use of the anaplerotic glyoxylate pathway to improve NAD+/NADH balance,increasing ethanol produc-tion by 50%while producing succinate as a coproduct at upwards of 20 g/l.Conclusion In the production of high value chemicals from biomass,the use of the respiratory metabolism is a waste of feedstock carbon.Bottlenecks previously identified in the oxidative pentose phosphate pathway are currently only relevant under oxygen-replete conditions and cannot impact the partitioning of carbon between the respiratory and fermentative pathways.Focusing future efforts on the non-respiratory balancing of NAD+/NADH,perhaps through the glyoxylate pathway,would improve the economics of ethanol production both directly and through coproduct formation.

Experimental and Modeling Study on C_(2)H_(2)Oxidation and Aromatics Formation at 1.2 MPa

Oxidation of acetylene(C_(2)H_(2))has been investigated in a high-pressure jet-stirred reactor(HP-JSR)with equivalence ratiosΦ=0.5,1.0,2.0 and 3.0 in the temperature range of 650 K-900 K at 1.2 MPa.18 products and intermediates were analyzed qualitatively and quantitatively by gas chromatography(GC)and gas chromatography-mass spectrometry(GC-MS).Generally,withΦincreasing,the production of intermediates increases significantly.CH_(4),C_(2)H_(4),C_(2)H_(6),C_(3)H_(6)and C_(3)H_(8)were important intermediates,which were formed abundantly atΦ=3.0.Sufficient light hydrocarbon intermediates could be an important reason for significant formation of cyclopentadiene,benzene,toluene and styrene atΦ=3.0.A detailed kinetic mechanism consisting of 299 species and 2041 reactions has been developed with reasonable predictions against the present data and previous results obtained at 0.1 MPa.According to flux and sensitivity analysis,H and OH radicals play important roles in the consumption of C_(2)H_(2).The combinations among light hydrocarbons and their free radicals are the main generation pathways of aromatics.C_(3)H_(3),IC_(4)H_(5)and AC_(3)H_(5)are important precursors for the formation of aromatics.By comparing the results of atmospheric pressure and high pressure,it can be found that increasing the pressure is conducive to fuel consumption and aromatics generation.

Analytical strategies for studying stem cell metabolism

Owing to their capacity for self-renewal and pluripotency, stem cells possess untold potential for revolutionizing the field of regenerative medicine through the development of novel therapeutic strategies for treating cancer, diabetes, cardiovascular and neurodegenerative diseases. Central to developing these strategies is improving our understanding of biological mechanisms responsible for governing stem cell fate and self-renewal. Increasing attention is being given to the significance of metabolism, through the production of energy and generation of small molecules, as a critical regulator of stem cell functioning. Rapid advances in the field of metabolomics now allow for in-depth profiling of stem cells both in vitro and in vivo, providing a systems perspective on key metabolic and molecular pathways which influence stem cell biology. Understanding the analytical platforms and techniques that are currently used to study stem cell metabolomics, as well as how new insights can be derived from this knowledge, will accelerate new research in the field and improve future efforts to expand our understanding of the interplay between metabolism and stem cell biology.

OP-Synthetic： identification of optimal genetic manipulations for the overproduction of native and non-native metabolites

Constraint-based flux analysis has been widely used in metabolic engineering to predict genetic optimization strategies. These methods seek to find genetic manipulations that maximally couple the desired metabolites with the cellular growth objective. However, such framework does not work well for overproducing chemicals that are not closely correlated with biomass, for example non-native biochemical production by introducing synthetic pathways into heterologous host cells. Here, we present a computational method called OP-Synthetic, which can identify effective manipulations （upregulation, downregulation and deletion of reactions） and produce a step-by-step optimization strategy for the overproduction of indigenous and non-native chemicals. We compared OP-Synthetic with several state-of-the-art computational approaches on the problems of succinate overproduction and N- acetylneuraminic acid synthetic pathway optimization in Escherichia coli. OP-Synthetic showed its advantage for efficiently handling multiple steps optimization problems on genome wide metabolic networks. And more importantly, the optimization strategies predicted by OP-Synthetic have a better match with existing engineered strains, especially for the engineering of synthetic metabolic pathways for non-native chemical production. OP- Synthetic is freely available at：http：//bioinfo.au.tsinghua.edu.cn/member/xwwang/OPSynthetic/.

High production of butyric acid by Clostridium tyrobutyricum mutant

The objective of this study was to improve the production of butyric acid by process optimization using the metabolically engineered mutant of Clostridium tyrobutyricum （PAK-Em）. First, the free-cell fermentation at pH 6.0 produced butyric acid with concentration of 38.44 g/L and yield of 0.42 g/g. Second, the immobilized- cell fermentations using fibrous-bed bioreactor （FBB） were run at pHs of 5.0, 5.5, 6.0, 6.5 and 7.0 to optimize fermentation process and improve the butyric acid production. It was found that the highest titer of butyric acid, 63.02g/L, was achieved at pH 6.5. Finally, the metabolic flux balance analysis was performed to inves- tigate the carbon rebalance in C. tyrobutyricum. The results show both gene manipulation and fermentation pH change redistribute carbon between biomass, acetic acid and butyric acid. This study demonstrated that high butyric acid production could be obtained by integrating metabolic engineering and fermentation process optimization.

Dry deposition of PM_(10) over the Yellow Sea during Asian dust events from 2001 to 2007

Dry deposition velocities and fluxes of PM10 during Asian dust events over the Yellow Sea from 2001 to 2007 were investigated using observation data in Qingdao, China and Jeju, Korea. The dry deposition velocities of PM 10 during dust events over the Yellow Sea ranged from 0.19 to 8.17 cm/sec, with an average of 3.38 cm/sec. Dry deposition fluxes of PM10 during dust events over the Yellow Sea were in the range of 68.5-2647.1 mg/（m2.day）, with an average of 545.4 mg/（m2.day）, which is 2-10 times higher than those reported by other studies for both dust and non-dust periods. It was estimated that 2.6× 10^11-48.7 × 10^11 g dust particles deposit to the Yellow Sea during dust events through dry deposition every year. Compared with the results in previous studies, it was found that the dry deposition of PM10 over the Yellow Sea during dust events in the years with high frequency of dust could account for a large or overwhelming fraction of the annual total dry deposition. Backward air mass trajectory analysis showed that dust events influenced Jeju mainly originated from the desert regions located in Mongolia and Inner Mongolia, China. There were 119 backward trajectories influenced both Qingdao and Jeju during 15 dust events from 2001 to 2007, accounting for 61.3% of the total trajectories of 194, indicating that Qingdao and Jeju were usually on the same pathway of dust transport downwind from source areas.

Genome-scale metabolic modeling in antimicrobial pharmacology

The increasing antimicrobial resistance has seriously threatened human health worldwide over the last three decades.This severe medical crisis and the dwindling antibiotic discovery pipeline require the development of novel antimicrobial treatments to combat life-threatening infections caused by multidrug-resistant micro-bial pathogens.However,the detailed mechanisms of action,resistance,and toxicity of many antimicrobials remain uncertain,significantly hampering the development of novel antimicrobials.Genome-scale metabolic model(GSMM)has been increasingly employed to investigate microbial metabolism.In this review,we discuss the latest progress of GSMM in antimicrobial pharmacology,particularly in elucidating the complex interplays of multiple metabolic pathways involved in antimicrobial activity,resistance,and toxicity.We also highlight the emerging areas of GSMM applications in modeling non-metabolic cellular activities(e.g.,gene expression),identi-fication of potential drug targets,and integration with machine learning and pharmacokinetic/pharmacodynamic modeling.Overall,GSMM has significant potential in elucidating the critical role of metabolic changes in antimi-crobial pharmacology,providing mechanistic insights that will guide the optimization of dosing regimens for the treatment of antimicrobial-resistant infections.