Proton exchange membranes with high proton conductivity and low crossover of fuel molecules are required to realize advanced fuel‐cell technology. The selective transportation of protons, which occurs by blocking the transportation of fuel molecules across a proton exchange membrane, is crucial to suppress crossover while maintaining a high proton conductivity. In this study, a simple yet powerful method is proposed for optimizing the crossover‐conductivity relationship by pasting sulfanilic‐functionalized holey graphenes onto a Nafion membrane. The results show that the sulfanilic‐functionalized holey graphenes supported by the membrane suppresses the crossover by 89% in methanol and 80% in formate compared with that in the self‐assembled Nafion membrane; an ≈60% reduction is observed in the proton conductivity. This method exhibits the potential for application in advanced fuel cells that use methanol and formic acid as chemical fuels to achieve high energy efficiency. Proton exchange membranes with high proton conductivity and low crossover of fuel molecules are required to realize advanced fuel‐cell technology. The sulfanilic‐functionalized holey graphene, which is supported by the membrane suppresses the crossover by 89% in methanol and 80% in formate compared with that in the self‐assembled Nafion membrane; an ≈60% reduction is observed in the proton conductivity. A promising technology to reduce CO2 emissions is the electrochemical CO2 reduction reaction that uses renewable energy to produce energy carriers, including methanol and formic acid. These energy carriers can be directly used as chemical fuels for fuel cells, without requiring dehydrogenation processes. These fuel cells are called direct methanol fuel cells (DMFC) and direct formic acid fuel cells (DFAFC).[−] A high proton conductivity and low crossover of fuel molecules are required in these fuel cells. Nafion is the standard membrane used in fuel cells because it exhibits excellent proton conductivity .[−] However, the Nafion membrane displays a large crossover from the anode to cathode chambers  that prevents the practical use of DMFC and DFAFC. The crossover of fuel molecules in a full‐cell system is caused by electro‐osmosis and pressure/concentration gradients between the cathode and anode chambers.Recycling carbon dioxide , graphene,[−] and other 2D nanomaterials on the surface of the Nafion membrane. In particular, graphene sheets have been reported to block large molecules from penetrating the graphene lattice while allowing protons to penetrate. The combination of Nafion and graphene successfully suppressed the crossover of fuel molecules such as methanol and formic acid.[−] However, such membranes failed to meet the minimum requirement of proton conductivity in the fuel cells . To date, attempts to maintain a high proton conductivity have been unsuccessful, and advanced fuel cells have not been used practically. A balance is required between the crossover of fuel molecules and proton conductivity.The former may be mitigated by improving the selectivity of the membranes to molecules and ions in the cell,18 by  Moreover, density functional theory (DFT) calculations indicated that graphene comprising sulfanilic functional groups increased the energy barrier of the transport of methanol and formic acid and provided a hopping conduction pathway for protons through the membranes. This graphene‐based technology is a simple yet powerful method for the rational design of fuel membranes.In this study, we achieved an excellent balance between the crossover of fuel molecules and proton conductivity by fabricating holey graphene with physical and chemical modifications. The incorporation of 5−20 nm holes on graphene markedly increased the proton conductivity, whereas the introduced functional groups on the graphene suppressed the crossover of fuel molecules. The membrane fabricated with the sulfanilic functional group suppressed the crossover by >80% with a slightly reduced proton conductivity compared with the Nafion membranes. It is acknowledged that sulfanilic groups suppress the crossover but increase the proton conductivity.22 Mor22.1 For the single‐functional graphene layer (1fGL), we chemically functionalized 1hGL with sulfanilic acids to introduce benzenesulfonic acid groups (─C6H4─SO3H) on the edges of the holes .A high‐quality single graphene layer (1GL) and a single holey graphene layer (1hGL) were synthesized on a Cu sheet with the chemical vapor deposition (CVD) method with/without Si nanoparticles (≈20 nm in diameter) on the Cu sheet before the CVD process  images indicate that the holes on 1hGL and 1fGL are 5–20 nm in diameter Figure . The cor−1 (─SO3Na), which are not observed in the spectra of the hGL samples . The atomic concentration of the S atoms is ≈2.49 at.% on the 1fGL samples  and X‐ray photoelectron spectroscopy (XPS). The FT‐IR spectra of the fGL samples show fingerprints of the sulfanilic‐functionalized group at 1058 and 1093 cm(─SO3Na),31 whi3N4 chip (window size: 20 × 20 µm) were examined to study the relationship between the functionalization and level of defects. The Nafion/graphene/Nafion‐sandwiched membranes have ≈2 µm thickness with 80 nm maximum roughness and 4% roughness ratio  intensity ratio: 1.78−3.22). Moreover, the N/1fGL/N show a relatively high defect level (D‐band to G‐band (ID/IG) intensity ratio: 0.88−1.75)  and N/1hGL/N   sandwiched by two spin‐coated Nafion membranes on a window‐attached Si) Figure  compared2.23N4 chip to serve both as proton exchange and separating membrane in an H‐type cell. The Si3N4 chip was reinforced with a polyethylene terephthalate (PET) sheet to fix it in the H‐type cell to physically isolate the working and counter electrode chambers of the H‐type cell  and performed electrochemical tests using a two‐electrode method with Pt mesh electrodes. Figure I–V) characteristics measured in the devices using the N/xGL/N, N/xhGL/N, and N/xfGL/N. The measured proton current, I, varies linearly with the bias voltage, V. The conductance S ( = I/V) divided by the effective membrane area (A) is discussed below as the areal proton conductivity σ ( = S/A). The crossover rate of the fuel molecules was calculated from the quantity of fuel molecules that crossed over from the working electrode chamber containing methanol or formate (formic acid exists as formate in acid) to the counter electrode chamber using chronoamperometry (CA)  through various graphene membranes , which was prepared from Nafion solution  compared with that in the N/N (1930 mS cm−2) .To prevent crossover of the fuel molecules, we introduced 1GL by sandwiching the graphene sheet using a Nafion membrane  .25−1, which is comparable with that of the N/N. Surprisingly, the crossover rates of methanol and formate are 0.715 and 0.163 mol m−2s−1, respectively, and are comparable with those of N/1GL/N; they are markedly improved compared with those of the N/N (methanol: 1.060 mol m−2s−1 and formate: 0.261 mol m−2s−1). These results indicate that the holes on the graphene sheet enable the selective transport of the molecules and protons.To improve the areal proton conductivity, we created holes with radii of 5–20 nm on 1GL ; the crossover for methanol and formate is 0.573 and 0.163 mol m−2s−1, respectively; this result is comparable with that obtained for N/1hGL/N (methanol: 0.715 mol m−2s−1 and formate: 0.163 mol m−2s−1). Therefore, the sulfanilic functional groups on 1hGL  maintain 77.7% proton conductivity and suppress the crossover rates for methanol and formate by 45.9% and 37.5%, respectively, compared with those of the N/N , N/3hGL/N (509 mS cm−2), and N/3fGL/N (818 mS cm−2); the areal proton conductivity is approximately half that of the N/N  than those of N/3hGL/N; the crossover rate of N/3fGL/N is comparable with that of N/3GL/N  for fuel cell operations. Notably, N/3fGL/N exhibits an areal proton conductivity of 1196 mS cm−2 at 50 °C , which completely meets the requirement of hydrogen‐type fuel cells  demonstrates the best balance between the proton conductivity and suppression of the fuel crossover 10 fors Figure .[10]Subsequently, we investigated the membrane stability by scanning electron microscope (SEM) and Raman spectroscopy. The cross‐sectional SEM images after the crossover tests confirmed that the membranes maintained their dimensions  and proton conductivity  are observed with an increase of the thickness of the membrane from 2 to 180 µm  and Nafion 117  compared with those of our Nafion . Notable reductions of the crossover rate  on the molecular sieving effect. First, we investigated hole size dependence of the proton and fuel molecular penetration energy barriers and confirmed that the energy barriers on a graphene model with a hole ≥1 nm diameter are negligible ; iii) apparent energy barrier of the crossover of both methanol and formate increases upon the introduction of the bulky net‐like sulfanilic functional groups on the molecular migration pathway; iv) negatively charged sulfanilic functional groups introduce a steric hindrance and block anionic molecules, thereby inhibiting the migration of methanol and formate, although allowing the migration of small and positively charged protons. The synergistic effects of introducing holes and sulfanilic‐functionalized groups into graphene play a crucial role in balancing selective proton transfer and suppressing the crossover of fuel molecules.We investigated the effect of sulfanilic‐functionalized holey graphene on areal proton conductivity and methanol and formic acid crossover rates by combining electrochemical measurements and DFT‐calculated energy barriers. The fGL membranes notably suppressed crossover while maintaining high areal proton conductivity. The improvements could be attributed to the following factors: i) introduction of holes into the graphene lattice  provides multiple proton penetration pathways between graphenes; ii) sulfanilic‐functionalized groups on holey graphene  enable the formation of new proton conduction pathways by the transfer of H42 reduction and advanced fuel cells such as DMFCs and DFAFCs, and can be used for other chemical fuels such as ammonia, urea, and hydrogen peroxide by changing proper functional groups in advanced fuel cells for facilitating a carbon‐neutral society.In this study, we systematically revealed the penetration mechanisms of protons, methanol, and formate molecules through sulfanilic‐functionalized holey graphene. The results indicated that proton conductivity and crossover of fuel molecules could be tuned by introducing nanometer‐sized holes in graphene, functionalizing holey graphene with sulfanilic functional groups, and adjusting the number of graphene layers. The crossover suppression and maintenance of high areal proton conductivity were realized, and all the membranes reported previously could be improved by simply pasting the graphene membrane on their surface, thereby reducing the material cost of Nafion membrane and the cell volume. Our findings should contribute to the development of electro synthetic cells for electrochemical CO52  and Ar . Thereafter, mono‐layer graphene was grown with an additional flow of CH4  for 30 min. After the graphene growth, the furnace was immediately opened, and the quartz tube was cooled down to room temperature (25 °C) with a fan. 1hGL was synthesized by a similar method as that used for 1GL, but SiO2 nanoparticles  were distributed on the Cu foil before the CVD process. A purchased SiO2 solution was diluted to 1×10−4 wt.% with ultrapure water and then it was further diluted with 2‐propanol (water:2‐propanol=1:1 (v/v)) to control the density of holes. Thereafter, 10 µL of the dispersion was added dropwise onto a 1 cm2 copper foil and dried. Subsequently, 1hGL was obtained under the same CVD conditions as those used for 1GL. For 1fGL, the synthesized 1hGL on the Cu foil was immersed in a mixed solution of 50 mL of sulfanilic acid solution (0.1 m) and 10 mL of NaNO2 solution (0.01 m), and heated at 70 °C for 12 h. After heating, the blackened solution was replaced with pure water several times for washing and the 1fGL on the Cu foil was dried. The as‐synthesized graphene on the Cu foil was chemically etched away in 50 mL of Fe(NO3)3 (0.25 m) solution and the isolated graphene was manually stacked to prepare graphene membranes  with a conventional CVD method. The Cu foil was inserted into the center of a quartz tube (φ30 × φ27 × 1000 mm) in a furnace. The tube was heated at 1000 °C for 1 h under an atmosphere of H2, Solid angle 0.26 sr). Raman spectra were obtained using a Renishaw InVia Reflex with an incident wavelength of 532.5 nm. Raman measurements were performed using this Si3N4 chip‐supported Nafion/graphenes/Nafion membrane. The obtained Raman spectra were normalized by the maximum peak intensity. Fourier transform infrared (FT‐IR) spectroscopy (ThermoFisher (Nicolet iS 50) FT‐IR spectrometer) with the wavenumber ranging from 3200 to 600 cm−1 was performed using an attenuated total reflection method. To obtain a clear signal intensity from the FT‐IR, the study measured 30 layers stacked 1hGL and 1fGL samples, respectively. Surface chemical states were studied using XPS  with an Al Ka and X‐ray monochromator. All samples were transferred on a Si3N4 chip or Cu TEM mesh grid for the measurements. The surface roughness measurements were performed on a thermal oxide Si wafer substrate  by AFM .The morphology and microstructure of the as‐synthesized graphene were characterized using a SEM (JEOL JCM‐7000) and TEM (JEOL JEM‐2100F and JEM‐ARM200F‐B) with 80 kV accelerating voltage to prevent damage to the graphene, and equipped EDS  fixed in the center was used to isolate the working electrode and counter electrode chambers filled with H2SO4 (0.05 m) solution. Proton conductivity measurements were performed in a two‐electrode system, where both Pt meshes (35 × 25 mm) were used as a working and counter electrode. Note that the proton conductivity was checked using aqueous H2SO4 (0.05 m) and aqueous H2SO4 (0.5 m) solution and there were no obvious differences  characteristics with a bias voltage of +200 to −200 mV, applied between two Pt mesh electrodes. The temperature dependence of the areal proton conductivity was measured from −1.0 to +0.2 V after a 5 min waiting time to stabilize the measurement temperature.An electrochemical workstation  equipped with an H‐type cell was used for electrochemical measurements. The schematic of the H‐type cell configurations for electrochemical measurements of proton penetration was shown in Figure 2SO4 (0.05 m) solution were used as the electrolytes for the working electrode for chronoamperometry (CA) measurements at −1.6 V using a two‐electrode system. After the 5 h CA test, the electrolyte in the counter electrode chamber was collected, and a quantitative analysis of methanol and formate was performed using nuclear magnetic resonance (NMR) and gas chromatography (GC). The crossover rate from the working electrode to the counter electrode chamber was calculated using the following Equation:c is the detected molar concentration of methanol or formate (mol/mL), V is the electrolyte volume (mL), A is the membrane area in the chip window (m2), and t is the measurement time (s).A 30% volumetric concentration of methanol or formic acid in the aqueous H The Becke‐Lee‐Yang‐Parr (BLYP) exchange‐correlation functional was used. Double‐zeta valence plus polarization (DZVP) basis sets were used. The core electrons were described by the Goedecker‐Teter‐Hutter pseudopotential. The real‐space density cut‐off was set to 320 Ry. The van der Waals correction was included via Grimme's D3 method. The simulation cell lengths in the x‐, y‐, and z‐directions were 25.56, 24.595, and 50 Å.DFT calculations were performed via the CP2K program.42 The6H4─SO3H). The nudged elastic band method was used to calculate the energy barriers for the penetration of proton, methanol, and formic acid.The graphene interlayer model was constructed using two overlapping graphene nanoribbons having a width of ≈15 Å. The edge of the graphene nanoribbon was terminated with hydrogen atoms. The sulfanilic‐functionalized graphene interlayer was created by replacing the terminal 8 hydrogen atoms per unit cell with benzenesulfonic acid groups (─Cnd method46 wasThe authors declare no conflict of interest.Y.I. conceived the research idea. S.J. performed the experiments. S.J., T.N. analysed the samples T.O. performed the DFT calculations. S.J., T.O., T.N., Y.N., and Y.I. wrote the manuscript. J.F. contributed to the discussions and revisions.Supporting InformationClick here for additional data file.


As their potential use as effective metallodrugs is continuously confirmed, the issue of their administration, distribution and delivery to desired biological targets emerges. Graphene and its derivatives possess attractive properties in terms of high affinity and low toxicity, suggesting that they can efficaciously be used as drug nanocarriers. In the present study, we computationally address the adsorption of a gold(I) N-heterocyclic monocarbene, namely, IMeAuCl , on graphene. The Au(I) N-heterocyclic carbene family has indeed shown promising anticancer activity and the N-heterocyclic ring could easily interact with planar graphene nanostructures. By means of high-level electronic structure approaches, we investigated the strength and nature of the involved interaction using small graphene prototypes, which allow us to benchmark the best-performing DFT functionals as well as assess the role of the different contributions to total interaction energies. Moreover, realistic adsorption enthalpies and free energy values are obtained by exploiting the optimal DFT method to describe the drug adsorption on larger graphene models. Such values (ΔH Molecular nanocarriers have found increasing applications for specific drug delivery, particularly important in the case of cancer-related therapy ,23, wherre found : alkalin37H16 to C150H30, were considered. The smallest one allows us to select the best computationally affordable level of theory, when benchmarked against highly accurate post-HF methods, and to study the physical components of the interaction between IMeAuCl and graphene in detail. The increasing size of the larger models allows us to consider the convergence of the calculation with respect to more realistic representations of the graphene sheet and to accurately calculate the thermodynamics of the adsorption process. Recent theoretical studies ,34,35 haThe article is organized as follows. The obtained results are described, analyzed and discussed in 37H16 , M062X, and B3LYP-D3(BJ) functionals, as described in the Computational Methods section. All energy values are BSSE corrected and can be found in We investigated several different initial mutual geometries for the CAt all levels of theory, the minimum configuration is found at R ≈ 3.3 Å. The two reference profiles, DFT-SAPT/CBS and MP2C/CBS, provide a lower and an upper limit of the involved interactions, with a minimum and maximum interaction energy of ca. −770 meV and −680 meV, respectively. PBE-D3(BJ) results are very close to the DFT-SAPT reference and only slightly more attractive at long range. For M062X, though the well depth is approximately the same, the equilibrium distance R is sensibly shorter, and the long-range potential is much less attractive, which could be due to documented faults of the M062X functional in the asymptotic regions . B3LYP-D37H16 prototype. The results are shown in The interaction energy decomposition into its physically significant contributions has been examined at the DFT-SAPT level of theory, allowing us to characterize the nature of the adsorption of IMeAuCl onto the C37H16. A preliminary minimization of the isolated IMeAuCl structure shows that the calculated values accurately match the crystallographic data [37H16 at the equilibrium distance is also reported and shown to be substantially unmodified, with only a slight elongation (0.01 Å) of the Au-Cl bond distance.The optimization of the adsorption geometry was therefore carried out at the PBE-D3(BJ)/6-311++G-SDD level of theory (as well as at B3LYP-D3(BJ) and M062X) by considering either rigid or flexible Chic data , with Au37H16 geometry relaxation upon IMeAuCl adsorption has also been investigated: the atom-by-atom superimposition of the structures for a fully relaxed (red) over a rigid structure (black) is shown in int values calculated at PBE-D3(BJ)/6-311++G+SDD lie in between those obtained at the MP2C and DFT-SAPT level, being only slightly lower (about 20–30 meV) than the latter. Conversely, B3LYP-D3(BJ) largely overestimates the binding energy, and the minimum interaction distance R is shorter than PBE-D3(BJ) (R = 3.35 Å for PBE-D3(BJ), R = 3.28 Å for B3LYP-D3(BJ) and R = 3.29 Å for M062X). The minimum position only slightly grows , R = 3.30 Å for B3LYP-D3(BJ) and R = 3.31 Å for M062X) when relaxing the C37H16 structure, and, as expected, the corresponding binding energies are more attractive from 30 to 70 meV. This might well be due to the increased interaction with the hydrogen atoms at the edges, an artificial effect which would be removed with the use of larger graphene prototypes. On the other hand, experimental adsorption energies and enthalpies on graphene are often found to be slightly more negative than the theoretical prediction, because graphene monolayers might present a wrinkled surface [The effect of C surface , where g54H18 (circumcoronene), C96H24 (circumcircumcoronene) and C150H30 (150H30 prototype), as well as partial optimizations of the free IMeAuCl onto rigid graphene models, were carried out, obtaining the BSSE-corrected and -uncorrected Eint values, reported in The effect of the use of larger, more realistic PAHs to model graphene sheets, such as C C150H30 , was exa54H18 and IMeAuCl-C96H24, complexes are shown. The interaction energy difference between one model and the next larger one in fact decreases with the prototype size: the difference between the largest C150H30 and the minimal C37H16 one amounts to 15% ca. Such differences are lower when relaxed supports are employed due to a compensation between the increased interaction surface and the larger interaction with the atoms at the edge of the support.As was to be expected, the impact of the PAH moiety relaxation decreases as its size increases, a sign that the surface curvature is not substantially modified by IMeAuCl adsorption; the more negative interaction energies found for relaxed smaller models are essentially due to the artificially larger interaction with peripheral atoms. The limited change of the graphene model geometry upon increasing their size is also visible in The effect of BSSE on the calculated energies is rather relevant and slightly grows with the prototype size, i.e., with the presence of more spatially extended basis functions for only one monomer.It can be interesting to compare the interaction energies for the Gold(I) monocarbene complex with those recently obtained for cisplatin (CP) on the same or very similar graphene models . We, theads), enthalpy (ΔHads) and free energy (ΔGads)  and in thermal corrections (less than 0.7 meV) are in fact extremely small and therefore will not have a large impact when transposed on larger models. ΔSads values are also very small and, as could be expected, grow with the size of the prototype: ΔSads(IMeAuCl-C37H16) = 1.53 meV/K; ΔSads(IMeAuCl-C54H18) = 1.55 meV/K; ΔSads(IMeAuCl-C96H24) = 1.64 meV/K. The adsorption process is found to be very exothermic  and very exergonic , notwithstanding the unfavorable entropic contribution due to the loss of one translational degree of freedom upon adsorption. A comparison with the corresponding cisplatin adsorption values [32H14 complex at the PBE-D3(BJ)/6-311+G+SDD level of theory is also reported in the same table and shows that the magnitude of the adsorption enthalpy and free energy is comparable. These favorable values indicate that graphene and its derivatives can be considered as promising nanomaterials for the load and delivery of gold(I)-carbene drugs. Indeed, these properties can be further enhanced or modulated by functionalizing graphene . Graphene oxide, alternating planar graphene-like and oxidized regions functionalized by epoxy and hydroxy groups, might further improve and modulate the adsorption properties of IMeAuCl. GO layers keep the same high surface-to-volume ratio and better biocompatibility than graphene, with the electrostatic and hydrogen bonding components of the interactions being enhanced. One can therefore take advantage of the solvent polarizability, of the cell pH, and generally of the environmental conditions to modify the GO adsorption/desorption ability. Such an effect has indeed already been observed experimentally [3O+ groups with epoxy and hydroxy groups. Similar effects are expected to come into play for the adsorption of IMeAuCl on GO. Work in this direction is in progress.Considering that rigid prototypes, particularly the largest ones, provide a good representation of the geometry and interactions occurring in a graphene sheet, these models have been used to compute adsorption energy (ΔE (ΔGads) , i.e., wn values  for the Graphene coating with biocompatible materials is another way to take advantage of the graphene structure, endowing it with additional specific chemical, physical and medicinal properties, and it is very often found in applications ,25 since36H17) were obtained at the density functional theory-symmetry adapted perturbation theory (DFT-SAPT) [Benchmark potential energies for the interaction between IMeAuCl and the smallest considered graphene prototype (CFT-SAPT) ,42 and aFT-SAPT)  level ofFT-SAPT) . In the FT-SAPT)  was usedFT-SAPT) , obtaineFT-SAPT)  basis seFT-SAPT)  set for FT-SAPT) , which cAs for the MP2C computations, which have been proven to provide accurate results for the interaction between aromatic species , the samCorresponding interaction energies were estimated also at the DFT level using three distinct approaches, namely, PBE , B3LYP  and M06236H17, C54H18, C96H24 and C150H30.Geometry optimization calculations to find the most stable structures and their energies were also carried out by exploiting the best performing DFT level (PBE-D3(BJ)), which was previously proven to be reliable for the description of the adsorption of a cisplatin (CP) molecule on finite graphene prototypes . In partads) and free energy (ΔGads) of the clusters in the gas phase at 298 K and 1 atm. To obtain those parameters, the needed frequency calculations were performed by freezing the graphene prototype (GP) support while allowing the internal coordinates of the adsorbed drug to relax, and the rigid-rotor and harmonic oscillator approximations were also assumed.We followed the principles in Refs. ,34 to prAll DFT computations were performed by using the Gaussian 09  code.We computationally investigated the interaction energy and thermodynamics of the adsorption of a Gold(I) monocarbene species, IMeAuCl, with relevant anticancer properties, onto a graphene sheet modeled by using prototypes of growing size, in view of a possible use of graphene-based nanostructures for drug delivery and the administration of Gold(I) N-heterocyclic carbenes, which are finding increasing applications in medicine.150H30, indicating a very favorable adsorption process.After a benchmark of the best computational method in terms of accuracy and computational feasibility, we evaluated at the chosen PBE-D3(BJ)/6-311++G level the interaction enthalpy and free energy for a sufficiently large PAH, CThe use of the accurate DFT-SAPT methods has also allowed us to characterize the physical components of the interaction, which provide useful information on how to functionalize or decorate the graphene surface to modulate the load/release capabilities of the drug carrier. In the present case, the favorable interaction energy and adsorption enthalpy mainly arise from the dispersion and, to a lesser extent, the electrostatic contributions. The latter component could be improved by the introduction of polar groups in graphene, as is the case for graphene oxide platelets or quantum dots. The adsorption of Gold(I) carbene molecules on graphene oxide and on functionalized graphene layers are currently under investigation and will be the subject of a subsequent publication.


The emergence of large language models (LLM) with remarkable performance such as ChatGPT and GPT-4, has led to an unprecedented uptake in the population. One of their most promising and studied applications concerns education due to their ability to understand and generate human-like text, creating a multitude of opportunities for enhancing educational practices and outcomes. The objective of this study is twofold: to assess the accuracy of ChatGPT/GPT-4 in answering rheumatology questions from the access exam to specialized medical training in Spain (MIR), and to evaluate the medical reasoning followed by these LLM to answer those questions. A dataset, RheumaMIR, of 145 rheumatology-related questions, extracted from the exams held between 2010 and 2023, was created for that purpose, used as a prompt for the LLM, and was publicly distributed. Six rheumatologists with clinical and teaching experience evaluated the clinical reasoning of the chatbots using a 5-point Likert scale and their degree of agreement was analyzed. The association between variables that could influence the models’ accuracy  was studied. ChatGPT demonstrated a high level of performance in both accuracy, 66.43%, and clinical reasoning, median (Q1–Q3), 4.5 (2.33–4.67). However, GPT-4 showed better performance with an accuracy score of 93.71% and a median clinical reasoning value of 4.67 (4.5–4.83). These findings suggest that LLM may serve as valuable tools in rheumatology education, aiding in exam preparation and supplementing traditional teaching methods. A clear example of this burgeoning interest is the notable surge in scientific research focusing on ChatGPT’s role within the medical field. From January 1st, 2023 until July 10th, 2023, there have been over 768 publications indexed in PubMed, that contain the string “ChatGPT” and that delve into various aspects of this Generative Pre-trained Transformer (GPT) chatbot. Some of the topics of such publications include the potential impact of ChatGPT on clinical and translational medicine3, clinical pharmacology4, scientific communication5 and medical writing6, medical evidence summarization7, patient question-answering8, public health9, ethical and legal10, health policy making11, plastic and colorectal surgery13, doctor-patient communication9, or drug-drug interaction and explainability14.The emergence of large language models (LLM) with remarkable performance such as ChatGPT, has led to an unprecedented uptake in the population, being the fastest-growing application in history15. A query conducted on July 10th in PubMed, “Rheumatology AND ChatGPT” produced 12 results. For instance, in Ref.16, the authors asked ChatGPT to draft an editorial about AI potentially replacing rheumatologists in editorial writing and discussed the ethical aspects and the future role of rheumatologists. In Ref.17, the authors discussed the role of ChatGPT as an author, and the inherent terms associated with the concept of authorship such as accountability, bias, accuracy, and responsibility. Eventually, they considered refusing to recognize ChatGPT as an author, in accordance also to Nature announcement18. For their part, the authors in Ref.19 provided an overview of the potential use of ChatGPT as a rheumatologist, its capabilities, and risks. They concluded that although chatbots will not be able to make clinical decisions for now; they will be able, for example, to design study protocols, streamline information accessibility and contribute to time-saving. A similar correspondence article highlighted five areas in which ChatGPT has the potential to assist in rheumatology care delivery, to note: patient drug education, medical imaging reporting, medical note-keeping for outpatient consultations, medical education and training and clinical audit and research. Authors in Ref.20 used ChatGPT as an assistant tool to aid in writing a case report of a systemic lupus erythematosus patient. Recently, a study21 aimed to assess the diagnostic accuracy of GPT-4 in comparison with rheumatologists. For that purpose, this LLM was instructed to name the top five differential diagnoses. Authors concluded that GPT-4 showed a higher accuracy for the top three overall diagnoses compared to the rheumatologist’s assessment.In rheumatology, the use of artificial intelligence (AI) and LLM, such chatbots, is gaining relevance26. Within this field, one of the most extensively studied applications of ChatGPT is its ability and reasoning in answering medical examination questions. One of the most prominent studies was27. This study demonstrated how ChatGPT performed at or near the passing threshold for all three tests of the United States Medical Licensing Exam despite not having undergone any specialized training or reinforcement. However, many similar studies have emerged in recent months.One of the most promising and studied applications for tools like ChatGPT lies within the realm of education. The ability of these language models to understand and generate human-like text creates a multitude of opportunities for enhancing educational practices and outcomesGiven the range of studies that have subjected ChatGPT to different medical exam questions , the disparity in the results obtained, and the proficiency of ChatGPT in understanding context and generating detailed responses, we hypothesize that these tools could aid in the learning process of medical students, particularly in the study of rheumatology and musculoskeletal diseases.First, we seek to ascertain the accuracy of ChatGPT/GPT-4 in answering rheumatology questions from the access exam to specialized medical training in Spain, Médico Interno Residente (MIR).Secondly, we aim to evaluate the clinical reasoning followed by ChatGPT/GPT-4 in answering those multiple-choice questions.Therefore, the objective of this study is twofold:ChatGPT, an iteration of the Generative Pre-trained Transformer (GPT) model, is an AI chatbot, which belongs to the category of large language models (LLM), that was developed by OpenAI. These models are language models  that rely on neural networks with millions of parameters. ChatGPT is trained on diverse and extensive data sources  and exhibits a groundbreaking ability to generate relevant and context-aware responses, making it a promising tool in the medical education area. The training data cut-off was September 2021. This means that data after this date were not used for training. The model is defined by OpenAI as “Our fastest model, great for most everyday tasks”.28. The model is defined by OpenAI as “Our most capable model, great for tasks that require creativity and advanced reasoning”. For the purpose of this study, we utilized the version of ChatGPT/GPT-4 that was released on May 3rd 2023, as documented in OpenAI’s release notes29. This version was used to answer all the rheumatology questions from the MIR exams in our study.On the other hand, GPT-4, is a large multimodal  model, also developed by OpenAI, faster, with more parameters and better performance than ChatGPT. More details and a comparison between both LLM used in this work are available in Ref.30. The questions from this examination serve as an invaluable resource for this study, as they represent standardized, expertly crafted questions designed to evaluate a comprehensive understanding of medical subjects, and, therefore, are leveraged to evaluate the accuracy and clinical reasoning of ChatGPT and GPT-4 when exposing them to the rheumatology discipline.The MIR is an annual competitive examination required for entry into specialist medical training in Spain. It is comprised of 210 questions from more than 30 competencies , see the Supplementary Material Excel File “Rheumatology-related questions from MIR exams published from 2009–2010 to 2022–2023 were included in this study. Questions assigned to other specialities, , that intersected with the field of rheumatology were also included.On the other hand, questions containing images were excluded from the analysis. This decision was taken because of the current limitations of ChatGPT, as it is primarily a text-based model and does not possess the capability to process or interpret image data. GPT-4 allows images as input data, but this feature was not publicly available at the time of this research. Hence, any questions in the MIR exams that were dependent on visual information, such as graphs, pictures, or clinical image data , were not included. Finally, questions invalidated by the Spanish Ministry of Health were also excluded from the analysis.Questions from the MIR exams were used as prompts. For each question provided to ChatGPT/GPT-4, the sentence “Justify your answer” was added at the end. The responses generated by ChatGPT and GPT-4 to the rheumatology questions were evaluated by six independent rheumatologists. Three of them, ZRR, LCO, and CPR, in addition to being practising clinicians, are MIR training professors. The length of the text generated by the models was not artificially limited.The medical experts evaluated the clinical reasoning of the chatbots followed in each of the responses. Their evaluation was based on a 1–5 scale, where a score of 5 indicates that the reasoning was entirely correct and flawless, while a score of 1 signifies that the reasoning was inconsistent or contained significant errors. Intermediate scores were used to denote minor errors in reasoning and the severity of these errors was reflected in the score; see Table DeepL. In cases where the answers provided by the models were not singular, a new prompt was used to ask for a single and unique response with the following instruction: “If you had to choose one of the answers, the most relevant one, which would it be?”.For this study, we solely relied on the initial responses generated by ChatGPT/GPT-4, without employing the “regenerate response” function. The questions were prompted in Spanish, exactly as they were extracted from the exam. Nonetheless, an English translation of both the question and the clinical reasoning by the LLM was obtained with The clinical reasoning of the models was evaluated by the medical experts in Spanish.A questionnaire was provided to each evaluator to assess the overall performance of the language models and their suitability for use in education and clinical practice. This questionnaire comprises seven free-text questions and can be found in the Supplementary Material “Finally, the exam questions and chatbot answers lacked identifiable patient information.Accuracy, defined as the match between the official MIR question response and the chosen option by ChatGPT/GPT-4.Score assigned to the clinical reasoning of ChatGPT/GPT-4 by the six evaluators.Two main variables were considered for evaluation:Covariables to be considered in this study included: year of the exam question, type of question, patient’s gender, pathology that the question addresses, and chatbot model used.Dichotomous and categorical variables were summarized using proportions. Continuous variables were summarized using the median and the first and third quartiles (Q1–Q3). The distribution of correct answers  among the different covariates was analyzed using chi-square or Fisher’s test, depending on the number of events. Differences between LLM, in terms of accuracy, were evaluated using McNemar’s test.31 and Gwet’s AC2 coefficient32. The Kappa-Fleiss coefficient was not used as raters are considered unique . The final clinical reasoning score given to each question was determined by a majority vote among evaluators. In the event of a tie, the worst score was chosen.The degree of agreement in the score assigned to the clinical reasoning by the evaluators was analyzed using Krippendorff’s alpha coefficient, Kendall’s coefficient with and without tie correction coefficientsDifferences between LLM, in terms of clinical reasoning, were evaluated using Wilcoxon signed-rank test. The effect of covariates on the clinical reasoning score was studied using ordinal logistic regression.R version 4.3.1 was used to perform the statistical analysis.10, the Hospital Clínico San Carlos (HCSC) Ethics Review Board evaluated this project, 23/370-E, and stated that this committee was not competent to evaluate studies of this type, since they do not encompass human subjects, or the use of biological samples, or personal data.As suggested in Ref.https://openai.com/policies/terms-of-use), Google BARD (https://support.google.com/bard/answer/13594961?hl=en) and Antrophic .The use of language models in this study complies with the established terms of service of OpenAI .A previous draft of this work was published as a preprint and can be found at: Madrid-García, A. Zenodo33.The questions evaluated by ChatGPT/GPT-4, the answer by both systems, as well as the official answer, the medical experts’ evaluation of the clinical reasoning, the year, genre, type of question, whether the question was invalidated or not, the type of disease being asked about, the English translation of the questions and the clinical reasoning are shown in the RheumaMIR dataset accessible through After applying the inclusion criteria, 143 questions from 14 MIR exams remained . Table −09).Out of 143 questions, GPT-4 correctly answered 134 (93.71%), demonstrating a high level of accuracy. On the other hand, ChatGPT accurately answered 95 questions (66.43%), indicating a somewhat lower level of performance in comparison to GPT-4 .The median (Q1–Q3) value of the average score for the clinical reasoning of GPT-4 was 4.67 (4.5–4.83), while for ChatGPT was 4.5 (2.33–4.67). There exist statistically significant differences in the clinical reasoning score, after applying the majority vote, of both LLM .ChatGPT/GPT-4 models are unaware of the limitations and scope of their knowledge, sometimes justifying facts in a tortuous manner and potentially misleading the reader.On its behalf, Fig. In this study, we have evaluated the accuracy and clinical reasoning of two LLM in answering rheumatology questions from Spanish official medical exams. To our knowledge, this is the first study to evaluate the usefulness of LLM applied to the training of medical students with a special focus on rheumatology.35, but are also specifically designed for a broad range of tasks .The ability of GPT-4 to answer questions with high accuracy and sound clinical reasoning is remarkable. This could make such models valuable learning tools for medical students. However, ChatGPT/GPT-4 LLM are only the first models that have reached the public in the rapidly expanding field of LLM chatbots. At present, a myriad of additional models are under development. Some of these nascent models are not only pre-trained in biomedical texts36, evaluated ChatGPT’s ability to answer questions from the 2022 MIR exam. In this cross-sectional and descriptive analysis, 210 questions from the exam were entered into the model. ChatGPT correctly answered 51.4% of the questions. This resulted in a 7688 position, slightly below the median of the population tested but above the passing score.Studies with a similar objective to this one have been conducted. For example, a Spanish study37, the proficiency of ChatGPT in answering higher-order thinking questions related to medical biochemistry, including 11 competencies such as basic biochemistry, enzymes, chemistry and metabolism of carbohydrates, lipids and proteins, oncogenesis, and immunity, was studied. Two-hundred questions were randomly chosen from an institution’s question bank and classified according to the Competency-Based Medical Education. The answers were evaluated by two expert biochemistry academicians on a scale of zero to five. ChatGPT obtained a median score of 4 out of 5, with oncogenesis and immunity competition having the lowest score and basic biochemistry the competition with the highest.In another research38. In this study, the authors appraised the capability of ChatGPT in answering first- and second-order questions on microbiology  from the Competency Based Medical Education curriculum. A total of 96 essay questions were reviewed for content validity by an expert microbiologist. Subsequently, ChatGPT responses were evaluated on a scale of 1 to 5, with five being the highest score, by three microbiologists. A median score of 4.04 was achieved.Research of a similar nature was conducted in Ref.39. Out of 1129 questions, ChatGPT answered 630 (55.8%) correctly. When compared with the performance of plastic surgery residents in 2022, ChatGPT ranked in the 49th percentile for first-year residents, but its performance fell significantly among residents in higher years of training, dropping to the 0th percentile for 5th and 6th-year residents.On the other hand, ChatGPT was tested on the Plastic Surgery In-Service examinations from 2018 to 2022 and its performance was compared to the national average performance of plastic surgery residents40, who aimed to assess whether ChatGPT could score equivalently to human candidates in a virtual objective structured clinical examination in obstetrics and gynecology. Seven structured examination questions were selected, and the responses of ChatGPT were compared to the responses of two human candidates and evaluated by fourteen qualified examiners. ChatGPT received an average score of 77.2%, while the average historical human score was 73.7%.Another study was conducted by researchers in Ref.41 instructed ChatGPT to deliver concise answers to the 24-item diabetes knowledge questionnaire, consisting of a clear “Yes” or “No” response, followed by a concise rationale comprising two sentences for each question. The authors found that ChatGPT successfully answered all the questions.Moreover, the authors in Ref.42, the researchers were interested in evaluating the performance of ChatGPT on open-ended clinical reasoning questions. Therefore, fourteen multi-part cases were selected from clinical reasoning exams administered to first and second-year medical students and provided to ChatGPT. Each case was comprised of 2–7 open-ended questions and was shown to ChatGPT twice. ChatGPT achieved or surpassed the pre-established passing score of 70% in 43% of the runs (12 out of 28), registering an average score of 69%.In Ref.43. In this investigation, ChatGPT correctly answered 17 out of 20 multiple-choice questions, while providing a comprehensive explanation for each one. On their side, researchers in Ref.44 proposed a four-grading system to classify the answers of ChatGPT, to note, comprehensive, correct but inadequate, mixed with correct and incorrect/outdated data, and completely incorrect. ChatGPT showed a 79% and a 74% of accuracy when answering questions related to cirrhosis and hepatocellular carcinoma. However, only the 47% and 41% of the answers were classified as comprehensive.Some studies showed remarkable performance, for instance, a research study evaluated the performance of ChatGPT in medical physiology university examination of phase I MBBS45 in which ChatGPT was exposed to the family medicine course’s multiple-choice exam of Antwerp University, only 2/125 students performed worse than ChatGPT. Since the questions were prompted in Dutch language, the potential correlation between ChatGPT’s low performance and the proportion of Dutch texts used in its training could be a factor worth considering for this discordant result.Conversely, in another research46, evaluated ChatGPT’s performance on standardized admission tests in the United Kingdom, including the BioMedical Admissions Test (BMAT), Test of Mathematics for University Admission (TMUA), Law National Aptitude Test (LNAT), and Thinking Skills Assessment (TSA). A dataset of 509 multiple-choice questions from these exams, ranging from 2019 to 2022 was used. The results varied among specialities. For BMAT, the percentage of correct answers varied from 5 to 66%, for TMUA varied from 11 to 22%, for LNAT from 36 to 53%; and for TSA from 42 to 60%. The authors concluded that while ChatGPT demonstrated potential as a supplemental tool for areas assessing aptitude, problem-solving, critical thinking, and reading comprehension, it showed limitations in scientific and mathematical knowledge and applications.Another study, Ref.The results shown by most of these studies are in line with our results, the average score of ChatGPT is between 4 and 5  when answering medical-related questions. However, in these studies, GPT-4 performance was not evaluated. Based on our results, we can postulate that there would be an increase in accuracy in comparison to those obtained by ChatGPT. In addition, to solve some of the limitations identified by our evaluators, such as the employment of a language that can lack technical precision by the models, LLM could perform better if trained or fine-tuned with biomedical texts.47. For instance, the authors pointed out that LLM reflect any false, outdated, and biased data from which the model was trained, and that they could not reflect the latest guidelines. Some authors have pointed out the risks of perpetuating biases if the model has been trained on biased data49 Other authors go further and declare that these types of models should not be used in clinical practice50. The motivation behind this statement lies in the presence of biases such as clinician bias, which may exacerbate racial-ethnic disparities, or “hallucinations” meaning that ChatGPT produces high levels of confidence in its output even when insufficient or masked information in the prompt. According to the authors, this phenomenon could lead users to place unwavering trust in the output of chatbots, even if it contains unreliable information. This was also pointed out by our evaluators, as shown in the Supplementary Material ‘51 compared the diagnostic accuracy of medical students regarding the typical rheumatic diseases, with and without the use of a DDSS and concluded that no significant advantage was observed from the use of the DDSS. Moreover, researchers reported that students accepted false DDSS diagnostic suggestions in a substantial number of situations. This phenomenon could be exacerbated when using LLM, and therefore should be study with caution.A large part of the concerns and doubts that arise from using these models are due to regulatory and ethical issues. Some of the ethical dilemmas have been highlighted in Ref.52.In our study, due to the nature of the questions, we were unable to assess racial or ethnic disparities. However, we did not find any gender bias when considering the clinical case questions. Finally, a relevant study that looks in depth at the biases that can arise when using LLMs can be found in Ref.53 is a good example of this. According to our results, in these early stages of LLM, the corpus used for training, as well as the content generated by them, should be carefully analyzed.Regarding regulation, the arrival of these models has led to greater efforts being made to regulate the use of AI. The EU AI Act54 authors studied the performance of ChatGPT when introducing the most searched keywords related to seven rheumatic and musculoskeletal diseases. The content of each answer was evaluated in terms of usefulness for patients with the ChatGPT in a scale from 1 to 7 by two raters.During the writing of this manuscript, new articles have emerged. For instance, in Ref.Finally, further analysis is needed to explore these observations and understand their implications for the development and use of AI in medical education and practice.Two chatbots were primarily used in this study, ChatGPT and GPT-4, both owned by OpenAI. However, other LLM such as BARD or Med-PaLM2 by Google, Claude 2 by Anthropic or LLaMA and LIMA by Meta are in development. Some of them are publicly available. To provide a better overview of other LLM, the accuracy of BARD (60.84%) and Claude 2 (79.72%) was calculated and compared against ChatGPT/GPT-4 in the Supplementary Material File Section ‘56, and tends to appear in skewed distributions such as the one presented in this study. More details can be found in Ref.31. In this study, since the ChatGPT clinical reasoning score distribution is less skewed, the reliability coefficient values are higher, between 0.624 and 0.783, than the ones obtained with GPT-4. However, when considering the Gwet’s AC2 coefficient, the trend is reversed, 0.924 vs. 0.759, with higher inter-rater agreement in GPT-4 compared to ChatGPT. These large differences between interrater reliability indices have been observed in simulation studies with skewed distributions57.The Krippendorff’s alpha coefficient and Kendall’s coefficient of agreement oscillates between 0.225 and 0.452 for the clinical reasoning of GPT-4, although the most repeated score of five out of six evaluators is 5 (the percentage of four and five scores oscillates between 87.41% and 93.70%), see Fig. 44, and a default feature of BARD. However, in the tests we conducted, the responses were consistent across iterations and this would have doubled the workload of evaluators, so we chose to include more questions from a single run, rather than fewer questions run multiple times. In addition, according to Ref.44, the 90.48% of “regenerated questions” produced two similar responses with similar grading.To ensure reproducibility and facilitate the comparison of results, each question could have been submitted twice to ChatGPT/GPT-4, a strategy supported by previous research endeavoursThe format of each question could have been transformed from multiple choice to open-ended. With this approach, it could have been possible to delve deeper into ChatGPT’s clinical reasoning. As explained in the previous point, this would have doubled the workload. Additionally, there are no open questions in the MIR exams.When conducting such studies, it is crucial to consider the evolution of knowledge over time. Evaluating older questions with models trained on recent data may reveal disparities compared to previously accepted and conventional beliefs. Therefore, accounting for this temporal aspect is essential to ensure the accuracy and relevance of the study findings. Moreover, although not extensively explored in this research, one of the key concepts when using LLM chatbots is what is known as the prompt or input text that is entered into the model. Depending on how well-defined the prompt is, the results can vary significantly. In this study, we tried to adhere closely to the official question while minimizing any unnecessary additional text.Another identified limitation of the study is the absence of medical students evaluation for the models’ clinical reasoning. This would have allowed us to determine whether students can recognize the main issues discussed above , and analyze to what extent these limitations may affect their usefulness.One of the main criticisms of the evaluators in assessing the LLM response was the use of non-technical language. This could have been remedied, in part, by using prompt engineering, this is, by modifying the initial input of the model and asking for a more technical response.58. Hence, special caution should be taken when extrapolating the results to other languages.We have explored the performance of GPT-4/ChatGPT in Spanish questions. However, different authors have suggested that such performance is language-dependentThe accuracy of ChatGPT and GPT-4 in answering the rheumatology questions of the Spanish access exam to specialized medical training is high, as well as the clinical reasoning. Nevertheless, discerning the veracity of such reasoning can pose a challenge for students in situations where the LLM experiences failures, given the comprehensive and seemingly accurate elaboration present in erroneous responses. Hence, extreme caution should be exercised when using these models as teaching aids and even greater diligence should be taken when using them in clinical practice. However, these kinds of models hold the potential to serve as a valuable asset in the development of pedagogical materials, subject to rigorous expert evaluation.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.


Graphene, a 2D carbon allotrope, is revolutionizing many biomedical applications due to its unique mechanical, electrical, thermal, and optical properties. When bioengineers realized that these properties could dramatically enhance the performance of cardiac sensors and actuators and may offer fundamentally novel technological capabilities, the field exploded with numerous studies developing new graphene-based systems and testing their limits. Here we will review the link between specific properties of graphene and mechanisms of action of cardiac sensors and actuators, analyze the performance of these systems from inaugural studies to the present, and offer future perspectives. We want to ensure that this average will steadily increase for years to come, but today cardiovascular diseases are still the leading cause of death in the world. Due to the life-or-death importance of the heart, scientists have been designing and fabricating diverse bioengineering systems tasked with supporting, monitoring, and modulating the cardiac activity. The development of such systems , and a current density ∼1,000,000 times greater than in copper. The tensile strength of graphene is 130 GPa . Graphene has low density  and a large Youngs modulus (∼1 TPa). Graphene is the thinnest (0.335 nm), the lightest (0.77 mg/m2), and the strongest (42 N/m) material  graphene field effect transistors, 2) and graphene microelectrode arrays, or electrically as 3) wearable electrophysiology sensors and 4) electromechanical pressure sensors, and finally as 5) optical sensors. The third section overviews graphene-based actuators that can function electrically or optically. Finally, we conclude with a section on future perspectives and advances in the upcoming advanced cardiac biosensors and actuators.This review provides a critical perspective on the existing technologies where graphene-based materials enhance the functionalities of cardiac sensors and actuators. Following the introduction, we begin with a broad review of graphene-based sensors functioning either electrically as in vitro and in vivo.The need to continuously, accurately, and reliably monitor various aspects of cardiac activity demands particular properties from cardiac biosensors. The presence of graphene in cardiac biosensors can address many of these demands: electrical properties of graphene offer high conductivity, low impedance, and high signal-to-noise ratio (SNR); mechanical properties of graphene can endow biosensors with flexibility, stretchability, durability, and foldability; a high surface area-to-volume ratio makes graphene-based biosensors extremely sensitive to their environment. Therefore, graphene can offer significant advantages for next-generation biosensors because it can be incorporated into various flexible, electrogenic, lightweight, transparent interfaces and devices for continuous long-term cardiac activity monitoring 2/Vs8, which is ∼1,000 times higher than in silicon), GFETs can operate at a frequency up to 500 GHz, and detect individual spikes with a high SNR. When cardiac cells are brought in contact with the graphene channel, the electrical signal associated with depolarization of their membrane will affect the local potential distribution and the electrical double layer formed at the graphene surface, resulting in local doping of graphene channel, which is recorded as a change in drain-source current (see Graphene field electric transistors (GFETs) have first been developed in 2004 and have since been fabricated in different shapes and forms , and we would refer the readers to the relevant reviews . The onlrent see .The very first GFETs were fabricated by placing mechanically exfoliated graphene flakes of two different sizes (20.8 μm × 9.8 μm or 2.4 μm × 3.4 μm) on an oxidized Si substrate  see Fig. These G2) on sapphire substrates using large-area CVD-grown graphene sheets , and exceptional charge mobility . These flexible GFETs successfully recorded extracellular action potentials and their spatial propagation across the HL-1 cell layer in vitro, as well as electrical signals from primary embryonic rat heart tissues ex vivo.To improve the interfacing between soft cardiac tissues and electronic devices, Kireev et al. fabricated GFETs on controllably flexible polyimide-on-steel substrates . These GTo comprehensively characterize the electrical activity in 3D cardiac cell models, the GFET geometry should preferably also be in a 3D format. Recently, . The SNR for graphene electrodes is approximately six times lower than for gold electrodes, ensuring the significantly improved sensitivity of graphene-based recording systems (Graphene microelectrode arrays (GMEAs) for monitoring cardiac electrical activity offer several critical advantages, including flexibility, ease of fabrication, high electrical conductance, mechanical and chemical stability, surface roughness, and long-term biocompatibility. The GMEAs typically require one lead per electrode, and a single differential amplifier, with a global reference electrode . Incorpo systems .Reducing the dimensions of graphene electrodes can also enhance the integration between electrodes and contracting cardiac tissues. In addition, smaller electrodes would improve the spatial resolution of recordings. However, smaller electrodes usually exhibit high electrochemical impedances and produce recordings of a diminished quality with a lower SNR. This issue was addressed in the study that fabricated transparent 30-µm graphene microelectrodes on float glass substrates followed by electrochemical deposition of the conducting polymer poly polystyrene sulfonate (PEDOT:PSS) . GraphenSilicon nanowire-templated out-of-plane synthesized three-dimensional fuzzy graphene (NT-3DFG)  may offe2) and high repetition rate (80 MHz) were used for transient poration of cell membranes of hiPSC-derived cardiomyocytes cultured on 3DFG electrodes. Authors hypothesized that 3DFG-assisted membrane poration was produced by an electron plasma generated in graphene by a laser but did not verify this hypothesis experimentally. Based on numerous published studies, a more likely explanation for observed optoporation is that a high-intensity high-repetition pulsed NIR laser can cause the poration of the cell membrane on its own without any help from graphene  due to drastically varied levels of coupling reached after optoporation. Further, the different areas of the same reasonably large 3DFG electrode may be simultaneously exposed to an extracellular environment and have partial access to intracellular compartments of a cardiomyocyte, producing variable signals of a hybrid identity. Technological development of the 3DFG MEA platform may address these issues in the future.An electrocardiogram (ECG) is a vital physiological measurement routinely performed for the evaluation of the cardiac activity. ECG time trace  vacuum-controlled absorption of graphene layers on the top and bottom surfaces of flexible polyester fibers, 2) using a 60-µm-thick graphene paper, or 3) depositing few-nanometer-thick graphene films on 280-µm-thick polyethylene terephthalate substrates . The intThe majority of the above-mentioned wearable devices feature bulky substrates that do not adhere well to the skin. This problem was recently solved by creating the so-called graphene electronic tattoos (GETs) designed as filamentary serpentines . GETs ar2 and gold e-tattoo. These GET-electrodes were successfully applied for monitoring cardiac electrical activity in an ex vivo Langendorff-perfused mouse heart model. The simultaneously recorded ECG and graphene electrogram show a good temporal correlation between R-waves and elapsed time between two successive R-waves, and the SNR above 20 for GET-electrodes with a 1-mm electrode opening.The increase in the technical complexity of GETs may allow their use for recording of electrical signals directly from the surface of the heart . To achiin vivo beating rat heart and recorded electrical signals from both the right and left ventricles.To improve the spatial resolution of the cardiac electrical mapping, a novel array of micropatterned GETs (mGETs) was fabricated  where thMeasuring blood pressure within a human body is critical for continuous monitoring of health conditions, allowing timely diagnosis of potential dysfunction of the cardiovascular system. Wearable pressure sensors must exhibit a broad dynamic range, high sensitivity, linearity, rapid response, durability, stretchability, and reproducibility . Due to Piezoresistive graphene-based sensors  represenin situ using hydriodic acid. The fabrication cost of a sensor directly integrated into a fabric is expected to be minimal, which can lower the barriers to future commercialization. The performance of GNWF sensors was strongly dependent on the loading of rGO and the strain strength. For example, GNWF sensors with the rGO loading in the 0.7–1.5 wt% range acted as negative pressure sensors at a small strain range (<5%) but became positive pressure sensors at higher strains. On the other hand, in the GNWF sensors with the 2.3 wt% rGO loading, the ΔR/R0 rations were always positive. The authors hypothesized that, at small strains (<5%), the resistance of the GNWF sensors containing low rGO concentrations is decreasing due to the formation of additional conductive paths, but at higher strains, fibers in GNWF sensors became disentangled and disconnected, resulting in the increased resistance. Critically, at larger strains (>10%) (when ΔR/R0 becomes more positive), the GNWF sensors experienced destructive deformation, leading to irreversible sensor deterioration. The best-preforming GNWF sensors exhibited a gauge factor of −7.1 at 1% strain, and a sensitivity of 0.057 kPa−1. When tested on human volunteers, the GNWF sensors were responsive to stretching, bending, pressure, and respiration, but these measurements were qualitative rather than quantitative.3 (2%–6%), and 106 (>8%) due to the unique crisscross morphology of GWFs and crack propagation mode. Searching for the acceptable compromise between the sensor’s sensitivity and the linearity of its responses, this study determined the optimal balance of these two parameters using the PDMS substrates with Young’s modulus of a few MPa, which provided the linearity of ∼0.98, and a formidable sensitivity (gauge factor of ∼12). The utility of this sensor for cardiovascular monitoring under different experimental conditions was successfully demonstrated on a healthy volunteer before and after high-intensity exercise.Epipremnum aureum leaves to achieve the microstructured surface with convex polygonal structures approximately 4 μm in height. This sensor exhibited a high sensitivity of 110 kPa−1, a wide pressure working range of up to 75 kPa, a low detection limit (0.2 Pa), a fast response time (<30 ms), high stability for more than 10,000 loading/unloading cycles, and excellent durability without exhibiting hysteresis. This sensor was shown to accurately detect the pulse at rest and after an exercise and to determine the systolic and diastolic blood pressure, the ventricular rate, and the heart rate from the pulse waveform.−1 at 3–1,000 Pa, a detection limit of ∼3 Pa, fast response time—50 ms at a fast-pressing frequency of 5 Hz, high durability at over 20,000 loading-unloading cycles, and low energy consumption of ∼1 μW at a low bias voltage of 1 V. Used by a volunteer, this sensor successfully detected a typical radial artery pulse waveform with three clearly distinguishable peaks in one cycle pulse, showing that it can be used for continuous and accurate detection of cardiovascular parameters.−1 vs. 434 kPa−1 for the 90° sensor, while the ΔR/R0 of the 0° sensor was∼ 1,200%, vs. ∼16,500% for the 90° sensor. This study also found that finer graphene stripe patterns offer a higher sensitivity due to defects. Therefore, the 90° sensors with narrow graphene patterns exhibited ultra-high sensitivity, reaching the sensitivity of ∼360,000% at ∼ 195 kPa. Using this sensor, the authors performed real-time monitoring of the pulse waveform, which allowed them to infer multiple parameters  crucial for the evaluation of cardiovascular health.in situ. Subsequently, this pressure sensing element was encapsulated into a polyethylene terephthalate/polyethylene vinyl acetate (PET/EVA)-laminated plastic film to mitigate such problems as the inability of porous graphene to withstand shear forces. This manufacturing process can be fully automated, potentially allowing a low-cost fabrication. When pressure is applied to porous graphene, its deformation leads to an increase in the overlapping areas of compressed pores and a subsequent decrease in the electrical resistance of this device. This porous graphene-based sensor exhibited excellent sensitivity (53.99/MPa), high resolution (<0.3 kPa), broad range (0.3 kPa–1 MPa), and impressive repeatability . The authors demonstrated that this sensor was able to accurately monitor several vital cardiovascular parameters, including heart rate, respiration rate, and blood pressure.7). This study demonstrated that a single GLE sensor can be used for monitoring the heart rate, breathing rate, limb movements, body temperature, or body dehydration. This feature raises the possibility that changes in one parameter can affect the detection accuracy of another parameter. Indeed, these sensors were found to be very susceptible to movement noise/artifacts.−1), a fast response time (25 ms), and a broad pressure range (22 kPa).In addition to harnessing piezo effects for pressure monitoring, the changes in blood pressure can also be detected using a bioimpedance (Bio-Z) method. This method involves injecting a low amplitude high-frequency current via two outer electrodes and measuring the resultant change in voltage via two inner electrodes  Figure . When plMonitoring of heart rate, arterial oxygen saturation, and respiratory rate can be performed using photoplethysmography. This non-invasive method requires sending a light signal through the skin and optically detecting the changes in that signal caused by the contraction/expansion of blood vessels during the cardiac cycle. The recent study  introducTo enable label-free monitoring the activity of cardiac cells and heart tissues, Balch et al. developed a critically coupled waveguide-amplified graphene electric field sensor (CAGE sensor)  Figure . The CAG2, and a waveguide layer of 150 nm Ta2O5 deposited on one face of a glass prism. This configuration allowed the light signals to be reflected  ∼100 times before reaching a CCD camera, resulting in 0.07% relative change in reflectivity under 100 µV voltage modulations with the SNR of ∼5.Since voltage-driven changes in light absorption of graphene are relatively small (∼1% per 200 mV) , the autThe proof-of-concept experiments demonstrated that, by monitoring the reflectivity changes in a graphene cell substrate, the CAGE sensor acquired a complex multicomponent signal from primary chicken cardiac tissues . The majTo visualize the contractions of cardiomyocytes by observing the color shift of cell substrates, another group  developeContrary to biosensors, actuators are designed to intervene with the existing cardiac activity when correcting cardiac functional deficiencies is needed. Actuators can initiate and restore cardiac contractions  or support the heart beating at a normal rate . To allow repeated use, cardiac cell stimulation technologies must be minimally invasive, rely on physiologically relevant mechanisms, and enable fast and reversible changes in the cell membrane potential.There are two fundamentally distinct types of graphene-based actuators: electrical and optoelectronic. During electrical stimulation, graphene electrodes deliver electrical currents from an external current generator to cardiac cells and tissues, while during optical simulation, cells are stimulated by the electrons generated by light directly in graphene.in vitro applications  and in in vivo applications [e.g., when cardiac pacemakers can help to control abnormal heart rhythms  can be achieved by combining graphene with other materials such as thermally evaporated cesium carbonate  , photo-gGraMOS effects are optoelectronic rather than thermal in nature because graphene is a highly efficient light-to-electricity converter . Due to The GraMOS platform has numerous advantages. The capacitive mechanism of GraMOS is more physiological than the Faradic mechanism of electrical stimulation , and doein vivo settings, including zebrafish  to accelerate the advancement of cardiac sensors and actuators from a lab bench to patients.The unique properties of graphene have already made this nanomaterial a practically indispensable element in the emergent bioengineering systems for cardiac biosensing and actuation. Future developments in this area will be fueled by new graphene-related discoveries and will be expected to revolutionize biosensing and actuating systems and help us to be healthier and live longer. A potential example for future applications is co-growing graphene nanomaterials with cellular organoids in order to use them for next-generation cardiac transplants, as was recently shown possible with the brain . To tranFinally, besides graphene, there are many other 2D materials that hold similar optical and mechanical properties but also provide new electrical functionalities . For exa


Second language (L2) pronunciation patterns that differ from those of first language (L1) speakers can affect communication effectiveness. Research on children’s L2 pronunciation in bilingual education that involves non-English languages is much needed for the field of language acquisition. Due to limited research in these specific populations and languages, researchers often need to refer to literature on L2 pronunciation in general. However, the multidisciplinary literature can be difficult to access. This paper draws on research from different disciplines to provide a brief but holistic overview of L2 pronunciation. A conceptual model of L2 pronunciation is developed to organize multidisciplinary literature, including interlocutors’ interactions at three layers: the sociopsychological, acquisitional, and productive-perceptual layers. Narrative literature review method is used to identify themes and gaps in the field. It is suggested that challenges related to L2 pronunciation exist in communication. However, the interlocutors share communication responsibilities and can improve their communicative and cultural competencies. Research gaps are identified and indicate that more studies on child populations and non-English L2s are warranted to advance the field. Furthermore, we advocate for evidence-based education and training programs to improve linguistic and cultural competencies for both L1 speakers and L2 speakers to facilitate intercultural communication. The conResearchers from diverse disciplines have long been interested in L2 pronunciation e.g., . HoweverMoreover, child L2 learners have been given less attention in research and practice. In the few discussions about child L2 speech acquisition, the target language was usually English . ApplyinThe goal of this paper is to provide a brief but holistic overview of the multidisciplinary literature on L2 pronunciation through a conceptual model and present implications for child bilingual learners of non-English languages. This encompassing model disentangles the interactions between L2 learners and their interlocutors in terms of their sociopsychological characters, linguistic experiences, and speech production and perception. This paper addresses researchers who are interested in pronunciation development in child bilingual speech acquisition. However, the model can be used by researchers of L2 pronunciation in general as a tool to organize their literature and situate their studies, and its implications provide new ideas to not only researchers, but also educators, practitioners, and policymakers.Given the long-standing history and extensive breadth of the field, a scoping review would be unrealistic. Rather than reducing the scope, a narrative literature review methodology was adopted. The model was developed through extensive reading and discussion. Multidisciplinary literature was mapped onto this model to identify themes and gaps in research. This will point out the main issues of research and raise awareness of future research venues, especially the ones that tend to be neglected at multidisciplinary intersections. This paper will first introduce the three-layer conceptual model, then briefly review L2 speech research within each layer, and finally, present implications for child L2 learners of non-English languages through themes and gaps across the layers.2.Communication involves two or more people who convey and receive information. In the context of L2 oral communication, we will refer to them as the “L2 Learner” and “L1 Listener,” as if these were interlocutor roles or names. Such role assignment is oversimplified, as the interlocution is bidirectional, and communication also occurs among L2 speakers . HoweverThe sociopsychological layer focuses on communicators’ attitudes toward L2 pronunciation, along with other individual and situational factors. The methods to understand attitudes include observation, interview, survey, and sociopsychological experiments . UnderstThe acquisitional layer addresses the roles of phonological (speech system) experience in pronunciation learning. For L2 Learners, there are a variety of theoretical models that discuss how L1 phonology impacts L2 learning e.g., . In paraThe productive-perceptual layer is where L2 Learners and L1 Listeners are directly engaged in a “speech circuit ” and theIn this conceptual model, L2 speech production and perception are impacted by both sociopsychological and acquisitional factors. On the other hand, oral communication in the speech circuit can, in turn, affect interlocutors’ sociopsychological characters and linguistic experiences. Therefore, the layers are interrelated and the model does not proceed in a particular order.3.Researchers of child L2 pronunciation should be mindful of the ecological complexity of communication. Many sociopsychological factors at the individual and situational levels contribute to L2 oral communication, including but not limited to personality , willing3.1.L2 pronunciation that is accented does not necessarily cause ineffective communication, but it evokes the previously internalized attitudes toward certain groups . L1 ListEnglish exemplifies the role of language status. As English is established as an international language, English users are often dichotomized into native and non-native speakers, which gives a higher status to the former. According to a survey , 75% of In addition, L1 Listeners’ attitudes toward accents can be related to social stereotypes against certain groups. According to However, negative attitudes do not necessarily lead to communication failures, since their influence is mediated by communication strategies. 3.2.L2 Learners have various attitudes to foreign accents. Some learners, especially those who are in the Expanding Circle  and learIn contrast, L2 Learners accept their accents better when they perceive themselves as users of a legitimate variation of the language , for exaSociopsychological factors play a role in L2 Learners’ pronunciation learning outcomes . Saito e3.3.To summarize, a preference for native pronunciation occurs at young ages, and negative attitudes toward non-native pronunciation can impede L2 communication. Researchers advocate for more inclusive attitudes toward L2 pronunciation.Despite the rich discussion on attitudes toward L2 pronunciation, we identify the languages involved in research as a gap in this layer. Literature is rich in the attitudes toward accented English, but less is known about the attitudes toward L2 pronunciation of non-English languages  in L2 based on how they are assimilated to L1 categories. For example, if two L2 sounds are perceived as exemplars of two different L1 categories, PAM predicts good discrimination of this pair; but if both sounds are perceived as equally good exemplars of the same L1 category, PAM predicts poor discrimination. To establish a new category in L2, learners need to detect the gestural features of the L2 sounds and contrast them in minimal pairs where the sounds differentiate word meanings in the L2  according to SLM, L2 speech acquisition is impacted by perceived phonetic dissimilarity, while a measurement of such dissimilarity remains undefined ; (b) theconnections between the acoustic, phonological, and lexical levels  several parameters in the computational model are arbitrarily set up, which might not fully represent reality; and (b) the results of simulated learning are not ground truths and need to be tested empirically .In summary, perception-based theories argue that L2 speech learning is hindered but not blocked by L1-attuned perception. Through them, researchers can understand how L2 Learners’ linguistic experiences impact their L2 pronunciation acquisition and predict specific challenges in learning by examining their L1 and L2 phonological systems.4.2.Non-phonetic information, such as lexical and social-interactive information, is important in speech acquisition . The folPAM focuses on contrastive pairs and involves a lexical perspective by nature. Furthermore, PAM predicts that there is more communicative pressure to learn L2 sound pairs that involve high-frequency words, dense phonological neighborhoods, and/or importance in social communication . HoweverTo summarize, L2 speech acquisition models take linguistic, non-phonetic  information into account to different degrees. However, none of them directly addresses the effects of the linguistic-external factors in the sociopsychological layer. Sociopsychological factors such as language status, language attitudes, and motivation play an important role in L2 speech learning and communication  and shou4.3.For L2 Learners, the interaction between two languages is not unidirectional from L1 to L2. Instead, the L2 phonology can also influence their L1. PAM focuses on new L2 Learners and pays limited attention to L2 effects. In contrast, SLM and L2LP discuss L2-to-L1 influences.SLM has a radical view on L2-to-L1 influence. It believes that L1 and L2 sounds occupy the same phonetic space, therefore L2 effects are immediate and inevitable. When an L2 category is not established, the neighboring L1 categories are assimilated because they are perceptually linked. When an L2 category is established, the L1 categories are dissimilated to maintain phonetic contrast . Some evL2LP accounts for such complexity, at least in part, by assuming different models in simulated learners. In a bottom-up model, i.e., when the acoustic, phonological, and lexical strata are separated, L1 phonetic categories are retained. On the contrary, when these aspects are interactive in one stratum, learners will eventually adopt the L2 system and lose the L1 system . The autIt is clear that L2-to-L1 effects exist and are multifaceted. Empirical evidence shows that L2 can cause both segmental and suprasegmental changes in L1 e.g., . Researc4.4.Previous sections introduced how L2 Learners’ perception is attuned by their linguistic experiences. Given that the speech learning mechanism, i.e., statistical learning, remains unchanged across lifespan , we comp4.5.For L2 Learners, several themes were discussed by L2 pronunciation acquisition models, including the learning mechanisms, the roles of non-phonetic information, and bidirectional interactions between L1 and L2. A few research gaps are identified: First, most theories focused on speech sounds but not suprasegmental features  and the Vanier Canada Graduate Scholarship through SSHRC (CGV–163274). The SSHRC Insight Grant funded a series of studies that focused on speech production in children enrolled in second-language education programs, which involved all the authors. The Vanier scholarship funded the YL’s doctoral studies.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Oreochromis mossambicus. In this research, fish were given a dietary supplement of polypropylene microplastics at 100, 500, and 1000 mg/kg for acute (96 h) and sub-acute (14 days) durations to assess toxic effects on liver tissues. FTIR results revealed the presence of polypropylene microplastic in their digestion matter. The ingestion of microplastics in O. mossambicus led to fluctuations in homeostasis, an upsurge in reactive oxygen species (ROS) levels, an alteration in antioxidant parameters, including superoxide dismutase (SOD), catalase (CAT), glutathione-S–transferase (GST), and glutathione peroxidase (GPx); a promotion in the oxidation of lipid molecules; and a denaturation in the neurotransmitter enzyme acetylcholinesterase (AChE). Our data indicated that sustained exposure to microplastics (14 days) produced a more severe threat than acute exposure (96 h). In addition, higher apoptosis, DNA damage (genotoxicity), and histological changes were found in the liver tissues of the sub-acute (14 days) microplastics-treated groups. This research indicated that the constant ingestion of polypropylene microplastics is detrimental to freshwater environments and leads to ecological threats.In recent years, polypropylene microplastic has persisted in freshwater ecosystems and biota, forming ever-growing threats. This research aimed to prepare polypropylene microplastics and evaluate their toxicity to the filter feeder  O. mossambicus to investigate the effects of microplastic exposure for up to fourteen days.Microplastics may pose a hazard to a variety of ecosystems, making them a potential contaminant. Due to their diminutive size, they are readily diffused and carried throughout all aquatic environments, including sediment, the surface, and other zones such as the littoral, limnetic, profundal, euphotic, and benthic ,2,3, andMajorly three types of microplastics found in aquatic systems comprise polyethylene, polypropylene, and polystyrene, according to Li et al.  and JeyaO. mossambicus for a period of 96 h and 14 days to determine its effects on biochemical markers such as antioxidant parameters, including superoxide dismutase (SOD), catalase (CAT), glutathione-S-transferase (GST), glutathione peroxidation (GPx), reactive oxygen species level (ROS), and oxidation of lipids (Lipid peroxidation-LPO). The liver tissues were chosen as the target organ for testing toxicological effects. In addition, the cellular damage, genotoxicity, and apoptosis of liver tissues were identified as indicators of the toxicity of polypropylene microplastics.In this scenario, the current study aimed to test the hypothesis of a dietary supplement of polypropylene microplastics in palatable freshwater organisms Following our prior procedure of Jeyavani et al. ,33, commO. mossambicus (juvenile age group) was procured from a fish farm in Karaikudi, Tamil Nadu, India. The fish were acclimatized (for up to two weeks) in Fibreglass Reinforced Plastics (FRP) tank (capacity: 1000 L) and maintained in the laboratory (12:12 h of light/dark) [2 L1), total ammonia (0.09 ± 0.01 mg N-NH4 L1), conductivity (342.6 ± 16.2% s/cm), and alkalinity (42.7± 6.2% mg Caco3). Additionally, the fish were given commercial pellets once a day. Prior to beginning the experiment, the fish were famished for 24 h.ht/dark) . During The following procedures were used by Espinosa et al.  to simulO. mossambicus and proved by FTIR analysis of egestion materials.Four tanks  were used for the experimental setting. . In each tank, fish (n = 10) were maintained in 100 L glass aquaria for three days after acclimatization periods (for static movements). Then, control and test groups were frequently fed with our prepared feed formulations for 14 days. The fish were closely monitored during the supplementation periods to ensure that they consumed all the provided feed. At the end of 96 h (acute) and 14 days (chronic), from each tank (both control and microplastic exposure groups) randomly, three fish were sampled to perform the toxicity analysis. Dietary supplemented polypropylene microplastics were taken by Three fish were taken out and sacrificed from each tank at the end of 96 h (acute) and 14 days (sub-acute). The liver and brain organs were dissected, kept in ice-cold phosphate buffer saline (pH 7.2), and grained using a mortar and pestle. The obtained suspension was centrifuged (3000 rpm for 15 min). Before centrifugation, some amount of suspension was taken out for comet assay. The remaining suspensions were centrifuged, and the supernatant was used for further biochemical enzyme analysis. The obtained pellet was also suspended in phosphate buffer saline. Finally, the obtained suspension and supernatant were kept at −20 °C until further investigation. The biochemical enzyme examination of reactive oxygen species (ROS), antioxidant parameters , and oxidative stress (LPO) were performed on stored supernatants of liver tissues [both control and microplastic treated groups . In addition, it accessed reactive oxygen species (ROS) because liver tissue is used as a major detoxifying organ that reacts with their enzymes to protect the organisms from harmful pollutants. And brain tissue extract was utilized to measure acetylcholine esterase (AChE) activity. Historically, the amount of proteins in liver and brain tissues was determined and measured by the Bradford method . All tes96 microtiter well plates were used to perform the fluorometric analysis to determine the formation of ROS in polypropylene microplastic exposure groups after 96 h and 14 days . Here, dIn accordance with Suzuki , the supMalondialdehyde (MDA) formation was detected using thiobarbituric acid at 532 nm using liver tissue extract, and the results were expressed as mol MDA/mg protein using LPO activity .The level of neurotransmitter acetylcholinesterase (AChE) was investigated by Ellman et al.  using acO. mossambicus (14 days) were preserved in formalin at a concentration of 10%. In addition, each tissue was sectioned to a thickness of 4 µm after being immersed in paraffin wax. Afterward, they were stained by hematoxylin and eosin and viewed under a Nikon inverted microscope (Nikon Eclipse Ti × 100).The liver tissues of both the control and microplastic treatment groups of O. mossambicus [Using acridine orange and ethidium bromide (AO/EtBr) staining of liver cell suspensions, determine the degree of cell damage generated by food supplementation with polypropylene microplastics in sambicus . After mThe alkaline comet test, also known as single-cell gel electrophoresis, was performed by Sing et al.  and was p < 0.05. The findings were presented as the mean ± standard deviation of the three experimental triplicates.Using SPSS Package 16.0, the statistical analysis employed ANOVA (one-way variance) and Microsoft Excel aids to making the graphs. The mean values were examined using Duncan’s multiple range tests to determine if they were significant at O. mossambicus [O. mossambicus.Here, we employ sambicus , a commesambicus ,49 and cThe four types of microplastics that are most frequently detected in aquatic habitats include polyethylene, polypropylene, polystyrene, and polyethylene terephthalate . The majO. mossambicus were selected as the target organs to assess polypropylene microplastics’ toxicity. Since liver tissues in aquatic vertebrates are responsible for detoxification, when vertebrates are exposed to dangerous pollutants, their tissues will have strong stress reactions [This work was created by combining commercial pellets with polypropylene microplastic and binding it with cod liver oil. Similarly, Zhu et al.  and Espieactions .O. mossambicus (−1 (CH3 stretching); 1453–1380 cm−1 (CH3 stretching); 1164–1165 cm−1 (C-H stretching); 798–846 cm−1 . Similar to our findings, Tiwari et al. [FTIR spectroscopy helps detect the chemical bonds in polypropylene plastics. The virgin polypropylene plastic film, powdered microplastics, and egestion material of sambicus  showed si et al.  and Sathi et al.  revealedO. mossambicus fish’s liver tissues after 96 h and 14 days of exposure in When microplastic exposure to organisms can produce oxidative stress in the detoxification organ due to the formation of unpaired electrons in oxygen, the organisms rapidly increase ROS. Moreover, ROS levels are governed by mitochondria in the bodies of organisms. When ROS level increases, exposure to microplastics in organisms indicates damage to mitochondria . This stO. mossambicus rose continuously (p≤ 0.05) after being exposed to polypropylene microplastic in the food for 14 days . When there is an excess of ROS, the body’s natural redox equilibrium is disrupted. Hence, alterations in antioxidant status and oxidative stress are inevitable outcomes. In support of our results, ROS production was increased in goldfish larvae when exposed to polystyrene microplastic (1000 μg/L) for 7 days [In addition, the ROS level in r 7 days .O. mossambicus and entered the body via the gills and orally. Accumulated ingested plastic particles were in various body parts, such as the gastrointestinal tract, liver, tissues, gallbladder, etc. [In this study, dietary-supplemented polypropylene microplastic particles were consumed by er, etc. . Free raer, etc. .−) into hydrogen peroxide (H2O2). Likewise, in this study, O. mossambicus exposed to polypropylene microplastics  for 96 h (acute) and 14 days (subacute), liver antioxidant enzyme SOD level difference didn’t occur (p < 0.05) due to O. mossambicus protecting the body from oxidative stress. Similar outcomes were detected by Wen et al. [Symphysodon aequifasciatus enhanced the production of SOD level.In fish, superoxide dismutase (SOD) is the first line of defense against oxidative stress because it converts the free radicals  in 96 h and 14 days of polypropylene microplastics exposure in O. mossambicus groups compared with the control groups  at 14 days and slightly raised (p < 0.05) in 96 h compared with the control groups  is a crucial antioxidant enzyme concerned with phase 2 detoxification of cells from oxidative stress. GST, which is involved in the phase II detoxification process, prevents damage to cellular biological molecules by accelerating glutathione’s binding to foreign substances such as MPs . In thisl groups c. The ing et al. , Solomang et al.  and Romag et al.  showed cp < 0.05) increased in microplastic exposure groups 3 (1000 mg/kg) in the acute period (Danio rerio decreased the GPx activity [The decomposition of hydrogen peroxide is converted into fewer toxic hydroxyl molecules by Glutathione peroxidase (GPx) enzyme that helps protect the cells from oxidative damage. Similarly, the GPx activity also expressedly  raised in both acute (96 h) and sub-acute (14 days) exposure to polypropylene microplastics  treated groups due to oxidative damage or stress of lipids  is the lipid by-product of oxidative damage generation  and is af lipids e. Similas labrax  and O. niloticus . It incrp < 0.05)  . In conttoxicity  due to dtoxicity . It leadtoxicity ,68.O. mossambicus were chosen for histological analysis to study the cellular damages. The histology of liver tissues is reported in O. mossambicus generates ROS levels that lead to oxidative stress that causes damage to liver tissues.Polypropylene microplastic exposure (14 days) groups  and the control group’s liver tissues of O. mossambicus induces oxidative damage to cells.AO/EtBr labeling helps distinguish between living and nonliving cells in tissue samples. The AO stain rapidly penetrates the cell membrane and reaches the nucleus, where it bonds with DNA to generate a green fluorescent color (indicating live cells); the EtBr stain only penetrates damaged cells and produces an orange fluorescent color. Early apoptotic cells are shown yellow with condensation of nuclear chromatin, and late apoptotic entire cells have red nuclei with complete structure. In this study, after AO/ EtBr staining, three types of cells were distinguished under the fluorescent microscope . Namely,O. mossambicus. From O. mossambicus. It may induce apoptosis or cell death in liver tissues. The length of the olive tail of microplastics exposure groups 1, 2, and 3—15.79 µm, 21.87 µm, and 26.34 µm, respectively. Likewise, ingesting polystyrene microplastics in freshwater fish Danio rerio and Perca fluviatilis causes DNA damage in the liver and gill tissue [Consumption of microplastics by aquatic organisms causes genotoxicity through ROS production in their bodies . DNA daml tissue .O. mossambicus. Raised the ROS level, which initially affects the physiological oxidative pathways [2O2)  to microplastics enters into the bodies of the organisms, which could disrupt redox homeostasis. The organisms that were exposed for 96 h protected themselves from the disruption of redox-homeostasis with the help of an antioxidant system  and restpathways . This unys [2O2) a. The hiis study b. Furtheis study c,d. Our Finally, the formation of hydroxyl ions affects biomolecules in the cells . LikewisO. mossambicus when polypropylene microplastics were supplemented into the diet. Consequently, generating the ROS level leads to fluctuations in antioxidant biomarkers  and promotes the oxidation of lipid biomolecules in liver tissues. The results indicated that prolonged polypropylene microplastic consumption (14 days) by O. mossambicus is more dangerous. Furthermore, 14 days of exposure to microplastic-treated organisms increased cell death and DNA damage in liver tissues. Moreover, histological results showed that morphological changes included a reduction of infiltration of sinusoids with leukocytes, necrosis and production of vacuoles in hepatocytes, and atrophy of dilated sinusoids in the liver of O. mossambicus. Overall, the outcome of this study elucidated that prolonged ingestion of polypropylene microplastics by aquatic organisms collapses the complete food web. Future research will focus on better remedial practices for destroying microplastics in the aquatic ecosystem.Redox metabolism was shown to be altered in