Molecular Interactions Research Articles

Nutrigenomics As a Diagnostic Tool in Periodontology: The New Kid in The Block

Periodontitis is known to be a progressive inflammatory lesion that may lead to the deterioration of the attachment of the periodontal apparatus & loss of structures involved in the apparatus, mainly the gingiva, pdl, cementum & alveolar bone leading to loss of teeth. Therefore, the interest in learning more about the connections between periodontal disease and nutrition has increased as research on the pathophysiology of periodontal disease and the function of nutrition has progressed. A subfield of nutritional science called nutrigenomics focuses on understanding the molecular interactions of nutrients and genomes. This enables us to recognize early-stage abnormalities in this control and tells us of the impact of nutrition on metabolic pathways & homeostatic regulation. In this review, the role of nutrition in periodontal disease is thoroughly discussed, and dietary recommendations are made for preventing periodontal disease.

Interactive semantics neural networks for skeleton-based human interaction recognition

Interactive semantics neural networks for skeleton-based human interaction recognition

ENHANCING NOSE- TO- BRAIN DELIVERY OF PIRIBEDIL: DEVELOPMENT OF A NANOSUSPENSION DISPERSED IN NASAL IN-SITU GELLING SYSTEM

Objective: This study focuses on improving the delivery of Piribedil, a poorly soluble drug, to the brain through the nasal route using a nanosuspension in a nasal in-situ gel. Methods: The nanosuspension was prepared using the sonoprecipitation method. Quality-by-Design (QbD) principles were used to optimize both the formulation and process parameters. The optimal process parameters were determined as sonication time (7.09 min), sonication amplitude (83.44%), and infusion rate (2.41 mL/min) with a desirability value of 0.970. Results: The nanosuspension exhibited an average particle size ranging from 46.7 nm to 50.1 nm, and polydispersity index values between 0.393 and 0.425. Zeta potential values ranged from -33.78 ± 1.86 mV to -35.06 ± 2.12 mV, indicating favorable stability. FTIR studies revealed molecular interactions between Piribedil and stabilizers. XRPD and DSC analyses showed the transition from a crystalline to an amorphous state in the nanosuspension. Dissolution studies demonstrated significantly accelerated dissolution for the Piribedil nanosuspension, attributed to its nanosize and improved wettability. Stability assessments confirmed the robustness of the nanosuspension. Conclusion: This innovative approach offers potential solutions for drug solubility challenges and blood-brain barrier penetration, holding promise for effective brain-targeted treatments.

GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity.

The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key compounds in targeted therapy, encounter challenges in cancer treatment due to emerging drug resistance mutations. Consequently, machine learning has undergone significant evolution to address the challenges of cancer drug discovery related to EGFR family proteins. However, the application of deep learning in this area is hindered by inherent difficulties associated with small-scale data, particularly the risk of overfitting. Moreover, the design of a model architecture that facilitates learning through multi-task and transfer learning, coupled with appropriate molecular representation, poses substantial challenges. In this study, we introduce GraphEGFR, a deep learning regression model designed to enhance molecular representation and model architecture for predicting the bioactivity of inhibitors against both wild-type and mutant EGFR family proteins. GraphEGFR integrates a graph attention mechanism for molecular graphs with deep and convolutional neural networks for molecular fingerprints. We observed that GraphEGFR models employing multi-task and transfer learning strategies generally achieve predictive performance comparable to existing competitive methods. The integration of molecular graphs and fingerprints adeptly captures relationships between atoms and enables both global and local pattern recognition. We further validated potential multi-targeted inhibitors for wild-type and mutant HER1 kinases, exploring key amino acid residues through molecular dynamics simulations to understand molecular interactions. This predictive model offers a robust strategy that could significantly contribute to overcoming the challenges of developing deep learning models for drug discovery with limited data and exploring new frontiers in multi-targeted kinase drug discovery for EGFR family proteins.

Thermophysical characterization and reliability analysis of binary composite nano doping on stearic acid-acetamide eutectic PCM

Organic phase change materials (PCM) have been extensively studied and employed for thermal energy storage applications, especially in the last decade. Wide range of melting temperature with high latent heat of fusion and absence of super cooling have made them highly desirable for energy storage applications, yet their intrinsic low thermal conductivity has been a major drawback in practical implementation. This study intends to address this and study the thermophysical characteristics of an organic PCM through composite nano doping. Stearic acid-acetamide eutectic PCM with a melting temperature of 65.73 °C and a latent heat of 203.72 J/g, was incorporated with a binary blend of Aluminum Oxide nanoparticles and multi-walled carbon nanotubes (MWCNT). The addition of metallic oxide and carbonaceous nanoparticles increased the melting temperature of the eutectic mixture by 2.9 °C and a highly advantageous increment in latent heat of fusion by 10% was observed, due to the improved molecular interaction introduced by the nanoparticles. Composite nano doping enhanced the thermal conductivity of the eutectic PCM by a 132.7% and also resulted in high optical absorption properties. The prepared eutectic mixtures were chemically stable and the eutectic PCM showed an improved final degradation temperature and thermal stability, with composite nano doping. Thermal reliability was analyzed through accelerated thermal cycling test and the eutectic mixtures could retain their thermal characteristics and chemical stability even after 500 thermal cycles. Composite nano doping proved to be a reliable thermophysical characteristics enhancement technique for organic eutectic PCM.

Molecular interactions between metformin and D-limonene inhibit proliferation and promote apoptosis in breast and liver cancer cells

BackgroundCancer is a fatal disease that severely affects humans. Designing new anticancer strategies and understanding the mechanism of action of anticancer agents is imperative.Hypothesis/PurposeIn this study, we evaluated the utility of metformin and D-limonene, alone or in combination, as potential anticancer therapeutics using the human liver and breast cancer cell lines HepG2 and MCF-7.Study designAn integrated systems pharmacology approach is presented for illustrating the molecular interactions between metformin and D-limonene.MethodsWe applied a systems-based analysis to introduce a drug–target–pathway network that clarifies different mechanisms of treatment. The combination treatment of metformin and D-limonene induced apoptosis in both cell lines compared with single drug treatments, as indicated by flow cytometric and gene expression analysis.ResultsThe mRNA expression of Bax and P53 genes were significantly upregulated while Bcl-2, iNOS, and Cox-2 were significantly downregulated in all treatment groups compared with normal cells. The percentages of late apoptotic HepG2 and MCF-7 cells were higher in all treatment groups, particularly in the combination treatment group. Calculations for the combination index (CI) revealed a synergistic effect between both drugs for HepG2 cells (CI = 0.14) and MCF-7 cells (CI = 0.22).ConclusionOur data show that metformin, D-limonene, and their combinations exerted significant antitumor effects on the cancer cell lines by inducing apoptosis and modulating the expression of apoptotic genes.

Synchronous Regulation of Hydrophobic Molecular Architecture and Interface Engineering for Robust WORM‐Type Memristor

AbstractIn the context of human active response to exponentially increasing data volumes, memristors have emerged as a focal point in systematic problem‐solving approaches. Particularly, organic memristors, characterized by excellent scalability, flexibility, and 3D stacking capabilities, have shown its tremendous potential in innovative electronic applications. However, the modulation of molecular assembly and interface interaction at the electrode surface poses a challenging task, despite their crucial role in determining the memristive performance. Herein, a collaborative method involving hydrophobic molecular design and interface engineering is proposed to generate high‐quality nanofilms with optimal photoelectric and electrochemical properties. By subjecting the bottom electrode to O2 plasma treatment and chemical modification using a hydrophobic ionic liquid poly(diallyldimethylammonium) bis(trifluoromethanesulfonyl)imide (PTFSI), the hydrophobic compound DN demonstrates exceptional affinity and stronger intermolecular interactions with the electrode surface. Consequently, the two‐terminal device array comprising Al/DN@PTFSI/ITO exhibits robust non‐volatile write‐once‐read‐many times (WORM) memory behavior, resulting in a tripling production yield from 30% to 92% along with a lower threshold voltage of 1.5 V, higher ON/OFF current ratio of 103 and excellent stability. This study presents a versatile approach to optimize the film assembly and material/electrode interface, thereby accelerating the development of organic memristors toward future applications.

Multi-level feature interaction image super-resolution network based on convolutional nonlinear spiking neural model

Image super-resolution (ISR) is designed to recover lost detail information from low-resolution images, resulting in high-quality and high-definition high-resolution images. In the existing single ISR (SISR) methods based on convolutional neural networks (CNN), however, most of the models cannot effectively combine global and local information and are also easy to ignore the correlation between different hierarchical feature information. To address these problems, this study proposes a multi-level feature interactive image super-resolution network, which is constructed by the convolutional units inspired by nonlinear spiking mechanism in nonlinear spiking neural P systems, including shallow feature processing, deep feature extraction and fusion, and reconstruction modules. The different omni domain self-attention blocks are introduced to extract global information in the deep feature extraction and fusion stage and formed a feature enhancement module having a Transformer structure using a novel convolutional unit for extracting local information. Furthermore, to adaptively fuse features between different hierarchies, we design a multi-level feature fusion module, which not only can adaptively fuse features between different hierarchies, but also can better interact with contextual information. The proposed model is compared with 16 state-of-the-art or baseline models on five benchmark datasets. The experimental results show that the proposed model not only achieves good reconstruction performance, but also strikes a good balance between model parameters and performance.

Probing the stability and quality of the cellulose-based Pickering emulsion containing sesamolin-enriched sesame oil by chemometrics-assisted ATR-FTIR spectroscopy

This study presents the employment of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflection and principal component analysis (PCA) to analyze the stability of a Pickering emulsion stabilized by carboxylated-cellulose nanocrystal (cCNC) comprising sesame oil phases with or without sesamolin. FTIR measurements identified an intermolecular hydrogen bond between the ester group of the triglyceride and the carboxyl group of the cCNC to create the emulsion droplet. The spectral bands from the hydroxyl group vibration (3700–3050 cm−1), carbonyl (1744 cm−1), CO groups of the ester triglyceride and cCNC (1160–998 cm−1) markedly discriminated between stabilized and destabilized emulsions. The PCA of FTIR spectra detected the change of molecular interaction during storage according to creaming, aggregation, and coalescence and changes in physicochemical parameters such as droplet size, refractive index, and zeta potential. Hence, PCA enabled the observation of the destabilization of emulsion in real-time.

Highly Efficient, Recyclable Microplastic Adsorption Enabled by Chitin Hydrogen Bond Network Rearrangement

Highly Efficient, Recyclable Microplastic Adsorption Enabled by Chitin Hydrogen Bond Network Rearrangement

A Systematic Study on the Physicochemical Interactions Between Polymeric Micelles and Mucin: Toward the Development of Optimal Drug Delivery Nanocarriers

AbstractThe optimal performance of drug delivery formulations, including polymeric nanoparticles, relies on particle distribution throughout the body and the interactions with biological barriers, particularly mucosal layers, which often limit their potential. A systematic and comprehensive study is presented through a multidisciplinary approach combining conventional and novel techniques for in vitro studies to understand the key molecular interactions between polymeric micelles and mucin. The results shows that polymeric micelles are integrates within the mucin layer, mirroring its viscoelastic properties, evidenced as a dissipation difference of 0.1 ± 0.44, measured by quartz crystal microbalance with dissipation. Surface‐enhanced Raman scattering reveals predominant hydrogen bonding within the mucin's hydrophilic core, while the isothermal titration calorimetry method confirms multiple non‐specific binding sites on the protein backbone. By performing the periodic acid‐Schiff stain assay, a binding amount of 0.20 mg of mucin per milligram of nanoparticles is quantified. Furthermore, motility studies show the surface binding of mucin on the polymeric nanoparticles influencing their Brownian motion. This study sheds light toward the improvement for a better drug delivery formulation and fabrication of optimal nanoparticle colloidal systems, which can advance translational drug delivery technologies into clinical application while enriching the field of surface and colloidal chemistry.

Multifaceted investigation of Sulfamerazine: Insights from computational methods, experimental techniques, and molecular simulations

The powerful sulfonamide antibiotic Sulfamerazine has been the subject of in-depth study to clarify its complex molecular interactions. In order to understand Sulfamerazine's pharmacological behaviour and interactions with biological components, this comprehensive study uses computational tools such as Density Functional Theory (DFT) calculations, spectroscopic analyses, and molecular docking simulations. Exploitation B3LYP/6-311++G(d,p) basis set, DFT simulations have provided important new understandings of the structure, vibrational properties, and binding mechanisms of this system. Vibrational assignments have been conducted by analyzing individual vibrational modes and comparing them to experimental data. The molecule's weak interactions have been identified grounded on electron density using Reduced Density Gradient Analysis. Fukui and MEP plot analyses have been employed to pinpoint the molecule's electrophilic and nucleophilic sites. Frontier molecular orbital analysis supported the observation of charge transfer within the molecule. Sulfamerazine is a viable option for further pharmaceutical development, as shown by drug-likeness and ADME (absorption, distribution, metabolism, and excretion) studies. In docking analysis, the inhibitor 6qzh stood out as particularly potent, capable of forming up to three hydrogen bonds, resulting in a binding energy of -8.2 kcal/mol. Molecular dynamics simulations have also shed light on the stability, solubility, and possible interactions of Sulfamerazine in diverse settings. This all-encompassing strategy promises to increase our understanding of the mechanism of action of Sulfamerazine, creating new opportunities for the logical development of more potent pharmaceuticals.

DIRMC: a database of immunotherapy-related molecular characteristics.

Cancer immunotherapy has brought about a revolutionary breakthrough in the field of cancer treatment. Immunotherapy has changed the treatment landscape for a variety of solid and hematologic malignancies. To assist researchers in efficiently uncovering valuable information related to cancer immunotherapy, we have presented a manually curated comprehensive database called DIRMC, which focuses on molecular features involved in cancer immunotherapy. All the content was collected manually from published literature, authoritative clinical trial data submitted by clinicians, some databases for drug target prediction such as DrugBank, and some experimentally confirmed high-throughput data sets for the characterization of immune-related molecular interactions in cancer, such as a curated database of T-cell receptor sequences with known antigen specificity (VDJdb), a pathology-associated TCR database (McPAS-TCR) etal. By constructing a fully connected functional network, ranging from cancer-related gene mutations to target genes to translated target proteins to protein regions or sites that may specifically affect protein function, we aim to comprehensively characterize molecular features related to cancer immunotherapy. We have developed the scoring criteria to assess the reliability of each MHC-peptide-T-cell receptor (TCR) interaction item to provide a reference for users. The database provides a user-friendly interface to browse and retrieve data by genes, target proteins, diseases and more. DIRMC also provides a download and submission page for researchers to access data of interest for further investigation or submit new interactions related to cancer immunotherapy targets. Furthermore, DIRMC provides a graphical interface to help users predict the binding affinity between their own peptide of interest and MHC or TCR. This database will provide researchers with a one-stop resource to understand cancer immunotherapy-related targets as well as data on MHC-peptide-TCR interactions. It aims to offer reliable molecular characteristics support for both the analysis of the current status of cancer immunotherapy and the development of new immunotherapy. DIRMC is available at http://www.dirmc.tech/. Database URL: http://www.dirmc.tech/.

Omics technology draws a comprehensive heavy metal resistance strategy in bacteria.

The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.

Studies on the Interaction of Imidazolium Ionic Liquids with Human Serum Albumin

Imidazolium-based ionic liquids have emerged as promising bio-compatible solvents for bio-molecules. The interaction of two imidazolium-based ionic liquids, namely 1-decyl-3-methyl-imidazolium tetrafluoroborate [Dmim][BF4] and 1-butyl-3-methylimidazolium octylsulfate [Bmim][OS], with human serum albumin (HSA) have been investigated using UV-visible, fluorescence and fourier transform infrared spectroscopy. Stern-Volmer quenching constant (Ksv) and the binding affinity (Ka) value have been also calculated to reveals the molecular interactions between HSA and the imidazolium-based ILs. Additionally, we explored the thermodynamic feasibility of these interactions by calculating the Gibbs free energy (∆G), entropy (∆S), and enthalpy (∆H). Hydrophobic interactions have been identified as exerting a more significant influence than hydrogen bonding in the interactions between proteins and ionic liquids. This implies that the hydrophobic characteristics of the ionic liquids play a pivotal role in the denaturation of proteins. Consequently, we conclude that the hydrophobic nature of the ionic liquids is essential for inducing interactions with proteins and potentially contributing to protein structure denaturation.

Study on the molecular interactions of some binary mixtures through thermodynamic properties and FT-IR spectra and correlation with the Jouyban–Acree model

ABSTRACT Densities (ρ), speeds of sound (u) and viscosities (η) were measured for three binary mixtures of propargyl alcohol with tetra chloromethane, trichloromethane, and dichloromethane from 303.15 K to 313.15 K at atmospheric pressure across the composition range. Excess molar volume, excess isentropic compressibility, deviation in viscosity, and excess Gibbs free energy of activation of viscous flow were calculated. Partial molar properties and infinite dilution molar partial properties were also determined for each system. Results suggest heteroassociates forming cross complexes and chemical forces with specific interactions. PFP theory was used to identify the predominant molecular interactions. The Jouyban–Acree model findings were discussed, considering mean relative deviation (MRDs) and individual relative deviation (IRD) between calculated and experimental data. FTIR studies were included to corroborate the experimental findings.

Quantitative analysis of molecular interactions in κ-carrageenan-Isovanillin biocomposite for biodegradable packaging and pharmaceutical applications using NMR, TOF-SIMS, and XPS approach

This study explores the molecular interactions and structural changes in κ-carrageenan crosslinked with isovanillin to create a biocomposite material suitable for hard capsule and bio-degradable packaging applications. Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy revealed chemical changes in the conjugate molecule, indicating improved electronegativity due to intermolecular hydrogen bonding between κ-carrageenan and isovanillin. Time-of-flight Secondary Ion Mass Spectrometry (ToF-SIMS) analysis revealed enhanced ion intensity due to intermolecular interactions, particularly between sulphate and hydrogen ions. X-ray Photoelectron Spectroscopy (XPS) study demonstrated that κ-carrageenan and isovanillin form stronger hydrogen bonds, with a shift in binding energy indicating higher electronegativity. These findings shed light on the molecular mechanisms that underpin the formation of the biocomposite material, as well as its potential for use in hard capsule and biodegradable packaging materials, addressing the need for sustainable alternatives in the pharmaceutical and packaging industries while also contributing to environmental conservation.

Exploring the structure and dynamics of a fluorescent schiff base (1E,1′E)-1,1′-(1,4-phenylene) bis(N-(4-chlorophenyl) methamine: Synthesis, spectroscopic analysis, thermal, electronic and crystallographic study with biological applications

Schiff bases have emerged as attractive biological agents with a wide range of uses due to the extraordinary physical, chemical, and pharmacological characteristics that they possess. This study focuses on the effective synthesis of a Schiff base that is produced from 4-chloroaniline and terephthaldehyde. The success of this synthesis is supported by a variety of spectroscopic methods and Single crystal XRD analysis. The chemical that was synthesised had significant fluorescence qualities, with measured values at 457.13, 481.49, and 524.15 nm, highlighting the fact that it has the potential to be utilised in a variety of applications within the field. Using thermogravimetric analysis, the thermal stability of the compound was studied, which revealed an excellent stability at 399 °C. Thermal stability is an essential component of compound usefulness. Molecular insights were obtained by the utilisation of Density Functional Theory, which revealed an energy gap of 1.70 electron volts (eV) and electrophilic behaviour in certain atoms. The distribution of charges was brought to light through the use of Mulliken charges and molecular electrostatic potential analysis, which brought attention to the distinctive qualities of the subject molecule. An examination of the electron localization function revealed that the electron density inside carbon, nitrogen, and chlorine atoms had been delocalized. Additionally, the localised orbital locator wave function and reduced density gradient maps offered vital insights into the non-covalent interactions that were taking place within the system under investigation. In the course of the evaluation of antimicrobial efficacy, it was discovered that the chemical exhibited more powerful antibacterial activity against gram-positive B. subtilis than the conventional antibiotic amoxicillin. The antibacterial findings were further supported by molecular docking tests, which involved using particular proteins from the target species. These investigations showed that B. subtilis had a higher affinity for binding. These findings were further validated by molecular dynamic simulations. The synthesised chemical was subjected to in silico toxicity assessment using seven models, which demonstrated its non-irritating properties on the skin and eyes. The extensive analysis that is given here lays the groundwork for more targeted research on novel antibacterial drugs, with a particular focus on the safety, molecular interactions, and effectiveness of these compounds. As a result of the compound's potential applicability in biocompatible antimicrobial formulations, it is a viable candidate for improving the development of antibacterial medicines that are both effective and safe.

Molecular interactions between a diphenyl scaffold and PED/PEA15: Implications for type II diabetes therapeutics targeting PED/PEA15 – Phospholipase D1 interaction

In a recent study, we have identified BPH03 as a promising scaffold for the development of compounds aimed at modulating the interaction between PED/PEA15 (Phosphoprotein Enriched in Diabetes/Phosphoprotein Enriched in Astrocytes 15) and PLD1 (phospholipase D1), with potential applications in type II diabetes therapy. PED/PEA15 is known to be overexpressed in certain forms of diabetes, where it binds to PLD1, thereby reducing insulin-stimulated glucose transport. The inhibition of this interaction reestablishes basal glucose transport, indicating PED as a potential target of ligands capable to recover glucose tolerance and insulin sensitivity. In this study, we employ computational methods to provide a detailed description of BPH03 interaction with PED, evidencing the presence of a hidden druggable pocket within its PLD1 binding surface. We also elucidate the conformational changes that occur during PED interaction with BPH03. Moreover, we report new NMR data supporting the in-silico findings and indicating that BPH03 disrupts the PED/PLD1 interface displacing PLD1 from its interaction with PED. Our study represents a significant advancement toward the development of potential therapeutics for the treatment of type II diabetes.

A Review on Pharmacological Advancement of Ellagic Acid

Background: In recent years, ellagic acid has emerged as a focal point in pharmacological research, showcasing promising developments and potential therapeutic applications as a competitive inhibitor of Src homology phosphotyrosyl phosphatase 2 for the treatment of cancer, as a shielding impact that stimulates sirtuin 6 (SIRT 6), against nephrotoxicity induced by cisplatin, as adjuvant treatment in sickle cell anemia, as antiaging and to avoid mild cognitive impairment. Purpose: This review provides a concise overview of the latest advancements in ellagic acid research, highlighting novel pharmacological findings and emerging trends. Methods: A comprehensive search of relevant literature was conducted to gather information on the pharmacological properties and therapeutic applications of ellagic acid. Studies investigating its antioxidant properties, anti-inflammatory effects, molecular interactions, and therapeutic implications were included in the analysis. Results: The review summarizes the multifaceted pharmacological landscape of ellagic acid, encompassing its antioxidant properties, anti-inflammatory effects, and potential therapeutic applications. It sheds light on its evolving role in modern medicine and underscores its significance as a promising avenue for future pharmaceutical exploration. Conclusion: The recent strides in ellagic acid development highlight its potential as a valuable therapeutic agent in various health conditions. Further research into its molecular interactions and clinical applications is warranted to fully harness its therapeutic potential and improve patient outcomes.