Energetic Information from Information-Theoretic Approach in Density Functional Theory as Quantitative Measures of Physicochemical Properties.

The Hohenberg-Kohn theorem of density functional theory (DFT) stipulates that energy is a universal functional of electron density in the ground state, so energy can be thought of having encoded essential information for the density. Based on this, we recently proposed to quantify energetic information within the framework of information-theoretic approach (ITA) of DFT (J. Chem. Phys. 2022, 157, 101103). In this study, we systematically apply energetic information to a variety of chemical phenomena to validate the use of energetic information as quantitative measures of physicochemical properties. To that end, we employed six ITA quantities such as Shannon entropy and Fisher information for five energetic densities, yielding twenty-six viable energetic information quantities. Then, they are applied to correlate with physicochemical properties of molecular systems, including chemical bonding, conformational stability, intermolecular interactions, acidity, aromaticity, cooperativity, electrophilicity, nucleophilicity, and reactivity. Our results show that different quantities of energetic information often behave differently for different properties but a few of them, such as Shannon entropy of the total kinetic energy density and information gain of the Pauli energy density, stand out and strongly correlate with several properties across different categories of molecular systems. These results suggest that they can be employed as quantitative measures of physicochemical properties. This work not only enriches the body of our knowledge about the relationship between energy and information, but also provides scores of newly introduced explicit density functionals to quantify physicochemical properties, which can serve as robust features for building machine learning models in future studies.

Steric Effect and Intrinsic Electrophilicity and Nucleophilicity from a Conceptual Density Functional Theory and Information-Theoretic Approach as Quantitative Probes of Chemical Reactions.

Appreciating reactivity in terms of physicochemical effects for chemical processes is one of the most important undertakings in chemistry. While transition state (TS) theory provides the framework enabling the reliable calculation of the barrier height for a given elementary step, analytical tools are necessary to gain insight into key factors governing the different processes during chemical reactions. In this contribution, we partition the potential energy surface of an elementary step along the intrinsic coordinate into three segments, the so-called Pre-TS, TS, and Post-TS regions, and then determine the most important factors dictating each segment. This analysis is based on the use of both reactivity descriptors from conceptual density functional theory and concepts from the information-theoretic approach in density functional theory. We found that in both Pre-TS and Post-TS regions, steric effects are the dominant factors, whereas in the TS region, it is the intrinsic electrophilic and nucleophilic propensity of the transition state structure that governs the reactivity. The wide applicability of our approach is shown by a validation for a total of 37 organic and inorganic reactions. This work thus, in our view, provides a novel perspective on how chemical reactivity can be quantified at different stages of chemical reactions.

Lactobacillus rhamnosus GG triggers intestinal epithelium injury in zebrafish revealing host dependent beneficial effects.

Lactobacillus rhamnosus GG (LGG), the well-characterized human-derived probiotic strain, possesses excellent properties in the maintenance of intestinal homeostasis, immunoregulation and defense against gastrointestinal pathogens in mammals. Here, we demonstrate that the SpaC pilin of LGG causes intestinal epithelium injury by inducing cell pyroptosis and gut microbial dysbiosis in zebrafish. Dietary SpaC activates Caspase-3-GSDMEa pathways in the intestinal epithelium, promotes intestinal pyroptosis and increases lipopolysaccharide (LPS)-producing gut microbes in zebrafish. The increased LPS subsequently activates Gaspy2-GSDMEb pyroptosis pathway. Further analysis reveals the Caspase-3-GSDMEa pyroptosis is initiated by the species-specific recognition of SpaC by TLR4ba, which accounts for the species-specificity of the SpaC-inducing intestinal pyroptosis in zebrafish. The observed pyroptosis-driven gut injury and microbial dysbiosis by LGG in zebrafish suggest that host-specific beneficial/harmful mechanisms are critical safety issues when applying probiotics derived from other host species and need more attention.

Microstructure and Hardness Characteristics of Swing-Arc SAW Hardfacing Layers.

Hot-rolled backup rolls are widely used in steel rolling and usually need to be repaired by arc hardfacing after becoming worn. However, a corrugated-groove defect commonly occurs on the roll surface due to the uneven hardness distribution in the hardfacing layers, affecting the proper usage of the roll. Accordingly, a new swing-arc submerged arc welding (SA-SAW) process is proposed to attempt to solve this drawback. The microstructure and hardness are then investigated experimentally for both SAW and SA-SAW hardfacing layers. It is revealed that a self-tempering effect occurs in the welding pass bottom and the welding pass side neighboring the former pass for both processes, refining the grain in the two areas. In all the zones, including the self-tempering zone (STZ), heat-affected zone (HAZ), and not-heat-affected zone in the welding pass, both SAW and SA-SAW passes crystallize in a type of columnar grain, where the grains are the finest in STZ and the coarsest in HAZ. In addition, the arc swing improves the microstructure homogeneity of the hardfacing layers by obviously lowering the tempering degree in HAZ while promoting the even distribution of the arc heat. Accordingly, the hardness of the SA-SAW bead overall increases and distributes more uniformly with a maximum difference of < 80 HV0.5 along the horizontal direction of the bead. This hardness difference in SA-SAW is accordingly decreased by ~38.5% compared to that of the SAW bead, further indicating the practicability of the new process.

Dietary Bacillus velezensis T23 fermented products supplementation improves growth, hepatopancreas and intestine health of Litopenaeus vannamei.

This study aimed to elucidate the effects of dietary fermented products of Bacillus velezensis T23 on the growth, immune response and gut microbiota in Pacific white shrimp (Litopenaeus vannamei). Shrimp were fed with diets containing fermentation products of B. velezensis T23 at levels of (0, 0.05, 0.1, 0.2, 0.3, 0.4, and 0.5 g/kg) for 4 weeks, to assess the influence on shrimp growth. The results showed that 0.3 and 0.4 g/kg T23 supplementation improved shrimp growth and feed utilization. Based on these results we selected these three diets (Control, 0.3T23 and 0.4T23) to assess the effect on immune response and gut microbiota of shrimp. Compared with the control, the 0.3T23 and 0.4T23 groups enhanced lipase and α-amylase activities in the gut significantly. Moreover, the 0.4T23 group decreased TAG and MDA levels in hepatopancreas, ALT and AST levels of serum significantly (P < 0.05). In hepatopancreas, CAT and SOD activities were improved observably and the MDA content was reduced markedly in both T23 groups. The expressions of antimicrobial related genes, Cru and peroxinectin in the 0.3T23 group, and proPO and peroxinectin in the 0.4T23 group were up-regulated remarkably (P < 0.05). Moreover, hepatopancreas of shrimp fed with a diet amended with T23 showed a significant down-regulated expression of nf-kb and tnf-α genes, while expressions of tgf-ß was considerably up-regulated. Furthermore, serum LPS and LBP contents were reduced markedly in T23 groups. Intestinal SOD and CAT were noteworthy higher in T23 groups (P < 0.05). In the intestine of shrimp fed on the diet enriched with T23 the expression of nf-κb and tnf-α exhibited markedly down-regulated, whereas hif1α was up-regulated (P < 0.05). Besides, in the intestine of shrimp grouped under T23, Cru and peroxinectin genes were markedly up-regulated (P < 0.05). Dietary 0.3 g/kg T23 also upregulated the ratio of Rhodobacteraceae to Vibrionaceae in the gut of the shrimp. Taken together, the inclusion of B. velezensis T23 in the diet of shrimp enhanced the growth and feed utilization, enhanced hepatopancreas and intestine health.

C(sp3)-H (N-Phenyltetrazole)thiolation as an Enabling Tool for Molecular Diversification.

Methods enabling the broad diversification of C(sp3)-H bonds from a common intermediate are especially valuable in chemical synthesis. Herein, we report a site-selective (N-phenyltetrazole)thiolation of aliphatic and (hetero)benzylic C(sp3)-H bonds using a commercially available disulfide to access N-phenyltetrazole thioethers. The thioether products are readily elaborated in diverse fragment couplings for C-C, C-O, or C-N construction. The C-H functionalization proceeds via a radical-chain pathway involving hydrogen atom transfer by the electron-poor N-phenyltetrazolethiyl radical. Hexafluoroisopropanol was found to be essential to reactions involving aliphatic C(sp3)-H thiolation, with computational analysis consistent with dual hydrogen bonding of the N-phenyltetrazolethiyl radical imparting increased radical electrophilicity to facilitate the hydrogen atom transfer. Substrate is limiting reagent in all cases, and the reaction displays an exceptional functional group tolerance well suited to applications in late-stage diversification.

Harvesting Chemical Understanding with Machine Learning and Quantum Computers.

It is tenable to argue that nobody can predict the future with certainty, yet one can learn from the past and make informed projections for the years ahead. In this Perspective, we overview the status of how theory and computation can be exploited to obtain chemical understanding from wave function theory and density functional theory, and then outlook the likely impact of machine learning (ML) and quantum computers (QC) to appreciate traditional chemical concepts in decades to come. It is maintained that the development and maturation of ML and QC methods in theoretical and computational chemistry represent two paradigm shifts about how the Schrödinger equation can be solved. New chemical understanding can be harnessed in these two new paradigms by making respective use of ML features and QC qubits. Before that happens, however, we still have hurdles to face and obstacles to overcome in both ML and QC arenas. Possible pathways to tackle these challenges are proposed. We anticipate that hierarchical modeling, in contrast to multiscale modeling, will emerge and thrive, becoming the workhorse of in silico simulations in the next few decades.

Chiral Jahn-Teller Distortion in Quasi-Planar Boron Clusters.

In this work, we have observed that some chiral boron clusters (B16-, B20-, B24-, and B28-) can simultaneously have helical molecular orbitals and helical spin densities; these seem to be the first compounds discovered to have this intriguing property. We show that chiral Jahn-Teller distortion of quasi-planar boron clusters drives the formation of the helical molecular spin densities in these clusters and show that elongation/enhancement in helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity of these boron clusters is discussed. Chiral boron clusters may find potential applications in spintronics, such as molecular magnets.

Relative cooperativity in neutral and charged molecular clusters using QM/MM calculations.

QM/MM methods have been used to study electronic structure properties and chemical reactivity in complex molecular systems where direct electronic structure calculations are not feasible. In our previous work, we showed that non-polarizable force fields, by design, describe intermolecular interactions through pairwise interactions, overlooking many-body interactions involving three or more particles. In contrast, polarizable force fields account partially for many-body effects through polarization, but still handle van der Waals and permanent electrostatic interactions pairwise. We showed that despite those limitations, polarizable and non-polarizable force fields can reproduce relative cooperativity achieved using density functional theory due to error compensation mechanisms. In this contribution, we assess the performance of QM/MM methods in reproducing these phenomena. Our study highlights the significance of the QM region size and force field choice in QM/MM calculations, emphasizing the importance of parameter validation to obtain accurate interaction energy predictions.

Fragment-Based Deep Learning for Simultaneous Prediction of Polarizabilities and NMR Shieldings of Macromolecules and Their Aggregates.

Simultaneous prediction of the molecular response properties, such as polarizability and the NMR shielding constant, at a low computational cost is an unresolved issue. We propose to combine a linear-scaling generalized energy-based fragmentation (GEBF) method and deep learning (DL) with both molecular and atomic information-theoretic approach (ITA) quantities as effective descriptors. In GEBF, the total molecular polarizability can be assembled as a linear combination of the corresponding quantities calculated from a set of small embedded subsystems in GEBF. In the new GEBF-DL(ITA) protocol, one can predict subsystem polarizabilities based on the corresponding molecular wave function (thus electron density and ITA quantities) and DL model rather than calculate them from the computationally intensive coupled-perturbed Hartree-Fock or Kohn-Sham equations and finally obtain the total molecular polarizability via a linear combination equation. As a proof-of-concept application, we predict the molecular polarizabilities of large proteins and protein aggregates. GEBF-DL(ITA) is shown to be as accurate enough as GEBF, with mean absolute percentage error <1%. For the largest protein aggregate (>4000 atoms), GEBF-DL(ITA) gains a speedup ratio of 3 compared with GEBF. It is anticipated that when more advanced electronic structure methods are used, this advantage will be more appealing. Moreover, one can also predict the NMR chemical shieldings of proteins with reasonably good accuracy. Overall, the cost-efficient GEBF-DL(ITA) protocol should be a robust theoretical tool for simultaneously predicting polarizabilities and NMR shieldings of large systems.

Optimized Incorporation of Furan into Diketopyrrolopyrrole-Based Conjugated Polymers for Organic Field-Effect Transistors.

Flexible electronics have received considerable attention in the past decades due to their promising application in rollable display screens, wearable devices, implantable devices, and other electronic applications. In particular, conjugated polymers are favored for flexible electronics due to their mechanical flexibility and potential for solution-processed fabrication techniques, such as blade-coating, roll-to-roll printing, and high-throughput printing allowing for high-performance transistor devices. Thiophene is the prevailing conjugated unit to construct these conjugated polymers due to its favorable electronic properties. On the other hand, furans are among the few conjugated moieties that are easily derived from bio renewable resources. To promote sustainability, we selectively introduced furan into the conjugated backbone of a high-mobility polymer scaffold and systematically studied the effect on the microstructure and charge transport. We show that partially and selectively replacing thiophene units with furan can yield nearly comparable performance compared to the all-thiophene polymer. This strategy offers an improvement in the sustainability of the polymer by incorporating bio-sourced furan without sacrificing the high-performance characteristics. Meanwhile, polymers with incorrect or complete furan incorporation show reduced mobilities. This work serves to develop coherent structure-morphology-performance relationships; such knowledge will establish guidelines for the future development of sustainable, furan-based conjugated materials.

Extending the Scope of Conceptual Density Functional Theory with Second Order Analytical Methodologies.

In the context of the growing impact of conceptual density functional theory (DFT) as one of the most successful chemical reactivity theories, response functions up to second order have now been widely applied; in recent years, among others, particular attention has been focused on the linear response function and also extensions to higher order have been put forward. As the larger part of these studies have been carried using a finite difference approach to compute these concepts, we now embarked on (an extension of) an analytical approach to conceptual DFT. With the ultimate aim of providing a complete set of analytically computable second order properties, including the softness and hardness kernels, the hardness as the simplest second order response function is scrutinized again with numerical results highlighting the difference in nature between the analytical hardness (referred to as hardness condition) and the Parr-Pearson absolute chemical hardness. The hardness condition is investigated for its capability to gauge the (de)localization error of density functional approximations (DFAs). The analytical Fukui function, besides overcoming the difficulties in the finite difference approach in treating negatively charged systems, also showcases the errors of deviating from the straight-line behavior using fractional occupation number calculations. Subsequently, the softness kernel and its atom-condensed inverse, the hardness matrix, are accessed through the Berkowitz-Parr relation. Revisiting the softness kernel confirms and extends previous discussions on how Kohn's Nearsightedness of Electronic Matter principle can be retrieved and identified as the physicist's version of the chemist's "transferability of functional groups" concept. The accurate, analytical hardness matrix evaluation on the other hand provides further support for the basics of Nalewajski's charge sensitivity analysis. Based on Parr and Liu's functional expansion of the energy functional, a new energy decomposition is introduced with an order of magnitude analysis of the different terms for a series of simple molecules both at their equilibrium geometry and upon variation in bond length and dihedral angle. Finally, for the first time, the perturbation expansion of the energy functional is studied numerically up to second order now that all response functions and integration techniques are at hand. The perturbation expansion energies are in excellent agreement with those obtained directly from DFA calculations giving confidence in the convergence of the perturbation series and its use in judging the importance of the different terms in reactivity investigations.

The interaction between lipid and vitamin D3 impacts lipid metabolism and innate immunity in Chinese mitten crabs Eriocheir sinensis.

As a fat-soluble vitamin, vitamin D3 relies on fat to perform its biological function, affecting lipid metabolism and innate immunity. This study used different percentages of lipid and vitamin D3 diets to evaluate the synergistic effects on the growth, lipid metabolism and immunity of juvenile Eriocheir sinensis (5.83 ± 0.01 g) for 56 days, including low lipid (LL, 1.5%) and normal lipid (NL, 7.5%) and three levels of vitamin D3: low (LVD, 0 IU/kg), medium (MVD, 9000 IU/kg) and high (HVD, 27,000, IU/kg). The synergistic effect of lipid and vitamin D3 was not significant on growth but significant on ash content, total protein, hepatopancreas lipid content, hemolymph 1α,25-hydroxy vitamin D3 [1α,25(OH)2D3] content, hepatopancreas lipolysis and synthesis genes. Crabs fed normal lipid (7.5%) and medium vitamin D3 (9000 IU/kg) had the highest hepatopancreas index, hemolymph 1α,25(OH)2D3 content, antibacterial ability, immune-related genes and hepatopancreatic lipid synthesis genes expression, but down-regulated the lipolysis genes expression. In contrast, crabs fed diets with low lipid percentage (1.5%) had low growth performance, hemolymph 1α,25(OH)2D3, mRNA levels of lipid synthesis genes, antibacterial ability and immune-related gene expression. At the 1.5% lipid level, excessive or insufficient vitamin D3 supplementation led to the obstruction of ash and protein deposition, reduced growth and molting, aggravated the reduction in antioxidant capacity, hindered antimicrobial peptide gene expression and reduced innate immunity, and resulted in abnormal lipid accumulation and the risk of oxidative stress. This study suggests that diets' lipid and vitamin D3 percentage can enhance antioxidant capacity, lipid metabolism and innate immunity in E. sinensis. A low lipid diet can cause growth retardation, reduce antioxidant capacity and innate immunity, and enhance lipid metabolism disorder.

Some Recent Advances in Density-Based Reactivity Theory.

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Multimodal integration for Barrett's esophagus.

The esophageal adenocarcinoma is facing a worldwide challenge: early prediction and risk assessment in clinical Barrett's esophagus (BE). In recent years, the growing interests have been witnessed in prediction and risk assessment in clinical BE. However, the resolution is limited, and the system is huge and expensive for the existing devices. Inspired by the principle of collaboration between human eye vision and brain cortex in data processing, here we propose multimodal learning framework to tackle tasks from various modalities, which can benefit from each other. To our findings, the experimental result indicates that low-level modality can directly affect high-level modality and form the final risk grading based on contribution, which maximizes the clinical performance of medical professionals based on our findings.

Finite temperature string by K-means clustering sampling with order parameters as collective variables for molecular crystals: application to polymorphic transformation between ß-CL-20 and ε-CL-20.

Polymorphic transformation of molecular crystals is a fundamental phase transition process, and it is important practically in the chemical, material, biopharmaceutical, and energy storage industries. However, understanding of the transformation mechanism at the molecular level is poor due to the extreme simulating challenges in enhanced sampling and formulating order parameters (OPs) as the collective variables that can distinguish polymorphs with quite similar and complicated structures so as to describe the reaction coordinate. In this work, two kinds of OPs for CL-20 were constructed by the bond distances, bond orientations and relative orientations. A K-means clustering algorithm based on the Euclidean distance and sample weight was used to smooth the initial finite temperature string (FTS), and the minimum free energy path connecting ß-CL-20 and ε-CL-20 was sketched by the string method in collective variables, and the free energy profile along the path and the nucleation kinetics were obtained by Markovian milestoning with Voronoi tessellations. In comparison with the average-based sampling, the K-means clustering algorithm provided an improved convergence rate of FTS. The simulation of transformation was independent of OP types but was affected greatly by finite-size effects. A surface-mediated local nucleation mechanism was confirmed and the configuration located at the shoulder of potential of mean force, rather than overall maximum, was confirmed to be the critical nucleus formed by the cooperative effect of the intermolecular interactions. This work provides an effective way to explore the polymorphic transformation of caged molecular crystals at the molecular level.

Simultaneous identification of strong and weak interactions with Pauli energy, Pauli potential, Pauli force, and Pauli charge.

Strong and weak interatomic interactions in chemical and biological systems are ubiquitous, yet how to identify them on a unified theoretical foundation is still not well established. Recently, we proposed employing Pauli energy-based indexes, such as strong covalent interaction and bonding and noncovalent interaction indexes, in the framework of density functional theory for the purpose. In this work, we extend our previous theoretical work by directly employing Pauli energy, Pauli potential, Pauli force, and Pauli charge to simultaneously identify both strong covalent bonding and weak noncovalent interactions. Our results from this work elucidate that using their signature isosurfaces, we can identify different types of interactions, either strong or weak, including single, double, triple, and quadruple covalent bonds, ionic bond, metallic bond, hydrogen bonding, and van der Waals interaction. We also discovered strong linear correlations between Pauli energy derived quantities and different covalent bond orders. These qualitative and quantitative results from our present study solidify the viewpoint that a unified approach to simultaneously identify both strong and weak interactions is possible. In our view, this work signifies one step forward towards the goal of establishing a density-based theory of chemical reactivity in density functional theory.

Cooperativity and Frustration Effects (or Lack Thereof) in Polarizable and Non-polarizable Force Fields.

Understanding cooperativity and frustration is crucial for studying biological processes such as molecular recognition and protein aggregation. Force fields have been extensively utilized to explore cooperativity in the formation of protein secondary structures and self-assembled systems. Multiple studies have demonstrated that polarizable force fields provide more accurate descriptions of this phenomenon compared to fixed-charge pairwise nonpolarizable force fields, thanks to the incorporation of polarization effects. In this study, we assess the performance of the AMOEBA polarizable force field and the AMBER and OPLS nonpolarizable pairwise force fields in capturing positive and negative cooperativity recently explored in neutral and charged molecular clusters using density functional theory. Our findings show that polarizable and nonpolarizable force fields qualitatively reproduce the relative cooperativity observed in electron structure calculations. However, AMBER and OPLS fail to describe absolute cooperativity. In contrast, AMOEBA accounts for the absolute cooperativity by considering interactions beyond pairwise interactions. According to the energy decomposition analysis, it is observed that the electrostatic interactions calculated with the AMBER and OPLS force fields seem to play an important and counterintuitive role in reproducing the adiabatic interaction energies calculated with density functional theory. However, it is important to note that these force fields, due to their nature, do not explicitly incorporate many-body effects, which limits their ability to accurately describe cooperativity. On the other hand, frustration in polarizable and nonpolarizable force fields is caused by changes in bond stretching and angle bending terms of the building blocks when they are forming a complex.

Silencing of CD147 inhibits cell proliferation, migration, invasion, lipid metabolism dysregulation and promotes apoptosis in lung adenocarcinoma via blocking the Rap1 signaling pathway.

OBJECTIVE: CD147 is an important glycoprotein that participates in the progression of diverse cancers. This study aims to explore the specific function of CD147 in lung adenocarcinoma (LUAD) and to reveal related downstream molecular mechanisms. METHODS: Followed by silencing of CD147, the viability, migration, invasion, and apoptosis of LUAD cells were measured by CCK8, wound healing, transwell assay, and flow cytometer, respectively. The expression of CD147 and two markers of lipid metabolism (FASN and ACOX1) were detected by qRT-PCR. A xenograft tumor model was constructed to investigate the function of CD147 in vivo. Then transcriptome sequencing was performed to explore the potential mechanisms. After measuring the expression of Rap1 and p-p38 MAPK/p38 MAPK by western blot, the changes of CD147 and lipid metabolism markers (FASN, ACOX1) was detected by Immunohistochemistry. Moreover, a Rap1 activator and a Rap1 inhibitor were applied for feedback functional experiments. RESULTS: CD147 was up-regulated in LUAD cells, and its silencing inhibited cell proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis, while overexpression of CD147 showed the opposite results. Silencing of CD147 also inhibited the growth of tumor xenografts in mice. Transcriptome sequencing revealed 834 up-regulated differentially expressed genes (DEGs) and 602 down-regulated DEGs. After functional enrichment, the Rap1 signaling pathway was selected as a potential target, which was then verified to be blocked by CD147 silencing. In addition, the treatment of Rap1 activator weakened the inhibiting effects of si-CD147 on the proliferation, migration, invasion, and lipid metabolism in LUAD cells, while the intervention of RAP1 inhibitor showed the opposite results. CONCLUSIONS: Silencing of CD147 inhibited the proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis of LUAD cells through blocking the Rap1 signaling pathway.