In this research article, novel starch phosphate grafted polyvinyl imidazole (StP-g-PIMDZs) was synthesized. Firstly, a phosphate group was attached to starch polymer via a phosphorylation reaction. Next, 1-vinyl imidazole (VIMDZ) was grafted on the backbone of starch phosphate (StP) through a free radical polymerization reaction. The synthesis of these modified starches was confirmed by 1H NMR, 31P NMR and FT-IR techniques. The grafting of vinyl imidazole onto StP diminished the crystallinity. Due to the insertion of the aromatic imidazole ring, the StP-g-PIMDZs demonstrated greater thermal stability. The StP and StP-g-PIMDZs were used as sorbents for the adsorption of methylene blue dye (MBD) from the model solution. The maximum removal percentage for starch, StP, StP-g-PIMDZ 1, StP-g-PIMDZ 2 and StP-g-PIMDZ 3 was found to be 60.6%, 66.7%, 74.2%, 85.3 and 95.4%, respectively. The Pseudo second order kinetic model and Langmuir adsorption isotherm were best suited to the experimental data with R2 = 0.999 and 0.99, respectively. Additionally, the thermodynamic parameters showed that the adsorption process was feasible, spontaneous, endothermic and favored chemi-sorption mechanism.
Atherosclerosis is known as the leading factor in heart disease with the highest mortality rate among the Malaysian population. Usually, the gold standard for diagnosing atherosclerosis is by using the coronary computed tomography angiography (CCTA) technique to look for plaque within the coronary artery. However, qualitative diagnosis for noncalcified atherosclerosis is vulnerable to false-positive diagnoses, as well as inconsistent reporting between observers. In this study, we assess the reproducibility and repeatability of segmenting atherosclerotic lesions manually and semiautomatically in CCTA images to identify the most appropriate CCTA image segmentation method for radiomics analysis to quantitatively extract the atherosclerotic lesion. Thirty (30) CCTA images were taken retrospectively from the radiology image database of Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia. We extract 11,700 radiomics features which include the first-order, second-order and shape features from 180 times of image segmentation. The interest vessels were segmentized manually and semiautomatically using LIFEx (Version 7.0.15, Institut Curie, Orsay, France) software by two independent radiology experts, focusing on three main coronary blood vessels. As a result, manual segmentation with a soft-tissuewindowing setting yielded higher repeatability as compared to semiautomatic segmentation with a significant intraclass correlation coefficient (intra-CC) 0.961 for thefirst-order and shape features; intra-CC of 0.924 for thesecond-order features with p < 0.001. Meanwhile, the semiautomatic segmentation has higher reproducibility as compared to manual segmentation with significant interclass correlation coefficient (inter-CC) of 0.920 (first-order features) and a good interclass correlation coefficient of 0.839 for the second-order features with p < 0.001. The first-order, shape order and second-order features for both manual and semiautomatic segmentation have an excellent percentage of reproducibility and repeatability (intra-CC > 0.9). In conclusion, semi-automated segmentation is recommended for inter-observer study while manual segmentation with soft tissue-windowing can be used for single observer study.
Among wide range of membrane-based operations, membrane contactors, as they reify comparatively modern membrane-based mechanism are gaining quite an attention in both pilot and industrial scales. In recent literature, carbon capture is one of the most researched applications of membrane contactors. Membrane contactors have the potential to minimize the energy consumption and capital cost of traditional CO2 absorptions columns. In a membrane contactor, CO2 regeneration can take place below the solvent boiling point, resulting into lower consumption of energy. Various polymeric as well as ceramic membrane materials have been employed in gas liquid membrane contactors along with several solvents including amino acids, ammonia, amines etc. This review article provides detailed introduction of membrane contactors in terms of CO2 removal. It also discusses that the main challenge that is faced by membrane contactors is membrane pore wetting caused by solvent that in turn can reduce the mass transfer coefficient. Other potential challenges such as selection of suitable solvent and membrane pair as well as fouling are also discussed in this review and are followed by potential ways to reduce them. Furthermore, both membrane gas separation and membrane contactor technologies are analysed and compared in this study on the basis of their characteristics, CO2 separation performances and techno economical transvaluation. Consequently, this review provides an opportunity to thoroughly understand the working principle of membrane contactors along its comparison with membrane-based gas separation technology. It also provides a clear understanding of latest innovations in membrane contactor module designs as well as challenges encountered by membrane contactors along with possible solutions to overcome these challenges. Finally, semi commercial and commercial implementation of membrane contactors has been highlighted.
This paper presents an assessment of the effect of isothermal annealing of Sn whisker growth behavior on the surface of Sn0.7Cu0.05Ni solder joints using the hot-dip soldering technique. Sn0.7Cu and Sn0.7Cu0.05Ni solder joints with a similar solder coating thickness was aged up to 600 h in room temperature and annealed under 50 °C and 105 °C conditions. Through the observations, the significant outcome was the suppressing effect of Sn0.7Cu0.05Ni on Sn whisker growth in terms of density and length reduction. The fast atomic diffusion of isothermal annealing consequently reduced the stress gradient of Sn whisker growth on the Sn0.7Cu0.05Ni solder joint. It was also established that the smaller (Cu,Ni)6Sn5 grain size and stability characteristic of hexagonal η-Cu6Sn5 considerably contribute to the residual stress diminished in the (Cu,Ni)6Sn5 IMC interfacial layer and are able to suppress the growth of Sn whiskers on the Sn0.7Cu0.05Ni solder joint. The findings of this study provide environmental acceptance with the aim of suppressing Sn whisker growth and upsurging the reliability of the Sn0.7Cu0.05Ni solder joint at the electronic-device-operation temperature.
Coronavirus disease 2019 is a severe communicable pulmonary medical problem that has been a challenging disease for everyone in the globe, but vaccines development and administration against this severe acute respiratory syndrome-inducing disease (coronavirus disease 2019) are currently yielding fabulous results. The mean duration of the coronavirus disease 2019 pandemic for this study spanned from 2020 until 2022. These manifestations are accompanied by symptoms of respiratory tract illnesses such as non-productive cough, sore throat, and nasal discharge. Relevant reviews on coronavirus disease 2019 manifestations and outcomes, consisting mainly of the infections/outbreaks, experimental information, and pre- and post-serovaccination details that occurred, were described. After a typical vaccination course, the study aims to summarize and understand more about the effectiveness of exercise on the pre-and post-coronavirus disease 2019 vaccination and its implementations. Physical activity is an immunological function adjuvant to decrease communicable disease risk and enhance immunity post-viral infection vaccination. Moderate-intensity resistance exercisesession directly before getting the influenza vaccine decreases vaccine responses in older adults, such as redness, pain, or inflammation at the injection spot or other adverse consequences compared to the inactive circumstance. However, it was reported that exercise after a shot is generally safe as long as vaccinated people feel well enough. Though exercise before or after vaccination has no negative impact on the protection afforded by the vaccine, people can exercise immediately after receiving the vaccine, as any changes in blood flow will not affect the vaccine's response. One episode of light-to-moderate-intensifying exercise after vaccination may improve the antibody reactions to influenza or the coronavirus disease 2019 vaccine. Vaccination administered pre- and post-regular exercise is an effective approach for boosting antibody responses due to its immunostimulant effects. Future research should investigate how different vaccine antibodies respond to low, moderate, and high physical activity levels.
Limited research has been conducted in Asian elderly patients (aged 65 years and above) for in-hospital mortality prediction after an ST-segment elevation myocardial infarction (STEMI) using Deep Learning (DL) and Machine Learning (ML). We used DL and ML to predict in-hospital mortality in Asian elderly STEMI patients and compared it to a conventional risk score for myocardial infraction outcomes. Malaysia's National Cardiovascular Disease Registry comprises an ethnically diverse Asian elderly population (3991 patients). 50 variables helped in establishing the in-hospital death prediction model. The TIMI score was used to predict mortality using DL and feature selection methods from ML algorithms. The main performance metric was the area under the receiver operating characteristic curve (AUC). The DL and ML model constructed using ML feature selection outperforms the conventional risk scoring score, TIMI (AUC 0.75). DL built from ML features (AUC ranging from 0.93 to 0.95) outscored DL built from all features (AUC 0.93). The TIMI score underestimates mortality in the elderly. TIMI predicts 18.4% higher mortality than the DL algorithm (44.7%). All ML feature selection algorithms identify age, fasting blood glucose, heart rate, Killip class, oral hypoglycemic agent, systolic blood pressure, and total cholesterol as common predictors of mortality in the elderly. In a multi-ethnic population, DL outperformed the TIMI risk score in classifying elderly STEMI patients. ML improves death prediction by identifying separate characteristics in older Asian populations. Continuous testing and validation will improve future risk classification, management, and results.
Water- and food-related health issues have received a lot of attention recently because food-poisoning bacteria, in particular, are becoming serious threats to human health. Currently, techniques used to detect these bacteria are time-consuming and laborious. To overcome these challenges, the colorimetric strategy is attractive because it provides simple, rapid and accurate sensing for the detection of Salmonella spp. bacteria. The aim of this study is to review the progress regarding the colorimetric method of nucleic acid for Salmonella detection. A literature search was conducted using three databases (PubMed, Scopus and ScienceDirect). Of the 88 studies identified in our search, 15 were included for further analysis. Salmonella bacteria from different species, such as S. Typhimurium, S. Enteritidis, S. Typhi and S. Paratyphi A, were identified using the colorimetric method. The limit of detection (LoD) was evaluated in two types of concentrations, which were colony-forming unit (CFU) and CFU per mL. The majority of the studies used spiked samples (53%) rather than real samples (33%) to determine the LoDs. More research is needed to assess the sensitivity and specificity of colorimetric nucleic acid in bacterial detection, as well as its potential use in routine diagnosis.
Herbicides made from natural molecules are cost-effective and environmentally friendly alternatives to synthetic chemical herbicides for controlling weeds in the crop field. In this context, an investigation was carried out to ascertain the allelopathic potential of Parthenium hysterophorus L. as well as to identify its phenolic components which are responsible for the allelopathic effect. During the observation, the rate of germination and seedlings' growth of Vigna subterranea (L.) Verdc, Raphanus sativus (L.) Domin, Cucurbita maxima Duchesne., Cucumis sativus L., Solanum lycopersicum L., Capsicum frutescens L., Zea mays L., Abelmoschus esculentus (L.) Moench, Daucus carota L., Digitaria sanguinalis (L.) Scop and Eleusine indica (L.) Gaertn were investigated by using methanol extracts, isolated from leaf, stem and flower of P. hysterophorus. Six concentrations (i.e., 25, 50, 75, 100, and 150 g L-1) of methanol extracts were isolated from P. hysterophorus leaf, stem and flower were compared to the control (distilled water). It was also observed that the concentration of methanol extracts (isolated from P. hysterophorus leaf, stem, and flower) while increased, the rate of seed germination and seedling growth of both selected crops and weeds decreased drastically, indicating that these methanol extracts have allelopathic potential. The allelopathic potential of P. hysterophorus leaf extraction (811) was found higher than the extraction of the stem (1554) and flower (1109), which is confirmed by EC50 values. The principal component analysis (PCA) was also used to re-validate the allelopathic potentiality of these methanol extracts and confirmed that Raphanus sativus, Solanum lycopersicum, Capsicum frutescens, Abelmoschus esculentus, Daucus carota, Digitaria sanguinalis, and Eleusine indica were highly susceptible to allelochemicals of P. hysterophorus. Besides these, the LC-MS analysis also revealed that the P. hysterophorus leaf extract contained 7 phenolic compounds which were responsible for the inhibition of tested crops and weeds through allelopathic effect. The results of the current study revealed that the leaf of P. hysterophorus is a major source of allelopathic potential on crops and weeds and which could be used as a valuable natural herbicide in the future for the sustainability of crop production through controlling weeds.
Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.
Cancer recurrence is often associated with the acquisition of radioresistance by cancer tissues due to failure in radiotherapy. The underlying mechanism leading to the development of acquired radioresistance in the EMT6 mouse mammary carcinoma cell line and the potential pathway involved was investigated by comparing differential gene expressions between parental and acquired radioresistance cells. EMT6 cell line was exposed to 2 Gy/per cycle of gamma-ray and the survival fraction between EMT6-treated and parental cells was compared. EMT6RR_MJI (acquired radioresistance) cells was developed after 8 cycles of fractionated irradiation. The development of EMT6RR_MJI cells was confirmed with further irradiation at different doses of gamma-ray, and both the survival fraction and migration rates were measured. Higher survival fraction and migration rates were obtained in EMT6RR_MJI cells after exposure to 4 Gy and 8 Gy gamma-ray irradiations compared to their parental cells. Gene expression between EMT6RR_MJI and parental cells was compared, and 16 genes identified to possess more than tenfold changes were selected and validated using RT-PCR. Out of these genes, 5 were significantly up-regulated i.e., IL-6, PDL-1, AXL, GAS6 and APCDD1. Based on pathway analysis software, the development of acquired radioresistance in EMT6RR_MJI was hypothesized through JAK/STAT/PI3K pathway. Presently, CTLA-4 and PD-1 were determined to be associated with JAK/STAT/PI3K pathway, where both their expressions were significantly increased in EMT6RR_MJI compared to parental cells in the 1st, 4th and 8th cycle of radiation. As a conclusion, the current findings provided a mechanistic platform for the development of acquired radioresistance in EMT6RR_MJI through overexpression of CTLA-4 and PD-1, and novel knowledge on therapeutic targets for recurrent radioresistant cancers.
In this numerical investigation, completely developed laminar convective heat transfer characteristics of a Williamson hybrid ferronanofluid over a cylindrical surface are reported. This new model in 2D is engaged to examine the effects of the magnetic field, thermal radiation factor, volume fraction of ultrafine particles, and Weissenberg number with the help of the Keller box method. The numerical calculations are implemented at a magnetic parameter range of 0.4 to 0.8, volume fraction range of 0.0 to 0.1, and a Weissenberg number range of 0.1 to 0.8. The numerical outcomes concluded that the velocity increases when the thermal radiation parameter and the volume fraction of a nanoparticle are increased, but inverse impacts are obtained for the magnetic parameter and the Weissenberg number. The rate of energy transport increases with increasing thermal radiation and volume fraction, while it declines with increasing the magnetic parameter and Weissenberg number. The drag force shows a positive relationship with the thermal radiation parameter and has an opposite relationship with the Weissenberg number and the magnetic parameter. Furthermore, even when the magnetic field, thermal radiation, volume fraction, and Weissenberg number are all present, the heat transfer rate of Williamson hybrid ferronanofluid is greater than that of mono Williamson ferronanofluid.
Optimizing Resistance spot welding, often used as a time and cost-effective process in many industrial sectors, is very time-consuming due to the obscurity inherent within process with numerous interconnected welding parameters. Small changes in values will give effect to the quality of welds which actually can be easily analysed using application tool. Unfortunately, existing software to optimize the parameters are expensive, licensed and inflexible which makes small industries and research centres refused to acquire. In this study, application tool using open-sourced and customized algorithm based on artificial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifications (WQC). A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg-Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. All the display and calculation processes are developed and compiled in the form of application tool of graphical user interface (GUI). Results showed that this low-cost application tool Q-Check based on ANN models can predict with 80% training and 20% test set on TSLBC with an accuracy of 87.220%, 92.865% and 93.670% for GD, SGD and LM algorithms respectively while on WQC 62.5% for GD and 75% for both SGD and LM. It is also expected that tool with flexible GUI can be widely used and enhanced by practitioner with minimum knowledge in the domain.
The JCV (John Cunningham Virus) is known to cause progressive multifocal leukoencephalopathy, a condition that results in the formation of tumors. Symptoms of this condition such as sensory defects, cognitive dysfunction, muscle weakness, homonosapobia, difficulties with coordination, and aphasia. To date, there is no specific and effective treatment to completely cure or prevent John Cunningham polyomavirus infections. Since the best way to control the disease is vaccination. In this study, the immunoinformatic tools were used to predict the high immunogenic and non-allergenic B cells, helper T cells (HTL), and cytotoxic T cells (CTL) epitopes from capsid, major capsid, and T antigen proteins of JC virus to design the highly efficient subunit vaccines. The specific immunogenic linkers were used to link together the predicted epitopes and subjected to 3D modeling by using the Robetta server. MD simulation was used to confirm that the newly constructed vaccines are stable and properly fold. Additionally, the molecular docking approach revealed that the vaccines have a strong binding affinity with human TLR-7. The codon adaptation index (CAI) and GC content values verified that the constructed vaccines would be highly expressed in E. coli pET28a (+) plasmid. The immune simulation analysis indicated that the human immune system would have a strong response to the vaccines, with a high titer of IgM and IgG antibodies being produced. In conclusion, this study will provide a pre-clinical concept to construct an effective, highly antigenic, non-allergenic, and thermostable vaccine to combat the infection of the John Cunningham virus.
In 1999, the Polynomial Reconstruction Problem (PRP) was put forward as a new hard mathematics problem. A univariate PRP scheme by Augot and Finiasz was introduced at Eurocrypt in 2003, and this cryptosystem was fully cryptanalyzed in 2004. In 2013, a bivariate PRP cryptosystem was developed, which is a modified version of Augot and Finiasz's original work. This study describes a decryption failure that can occur in both cryptosystems. We demonstrate that when the error has a weight greater than the number of monomials in a secret polynomial, p, decryption failure can occur. The result of this study also determines the upper bound that should be applied to avoid decryption failure.
Rice blast, an extremely destructive disease caused by the filamentous fungal pathogen Magnaporthe oryzae, poses a global threat to the production of rice (Oryza sativa L.). The emerging trend of reducing dependence on chemical fungicides for crop protection has increased interest in exploring bioformulated nanomaterials as a sustainable alternative antimicrobial strategy for effectively managing plant diseases. Herein, we used physiomorphological, transcriptomic, and metabolomic methods to investigate the toxicity and molecular action mechanisms of moringa-chitosan nanoparticles (M-CNPs) against M. oryzae. Our results demonstrate that M-CNPs exhibit direct antifungal properties by impeding the growth and conidia formation of M. oryzae in a concentration-dependent manner. Propidium iodide staining indicated concentration-dependent significant apoptosis (91.33%) in the fungus. Ultrastructural observations revealed complete structural damage in fungal cells treated with 200 mg/L M-CNPs, including disruption of the cell wall and destruction of internal organelles. Transcriptomic and metabolomic analyses revealed the intricate mechanism underlying the toxicity of M-CNPs against M. oryzae. The transcriptomics data indicated that exposure to M-CNPs disrupted various processes integral to cell membrane biosynthesis, aflatoxin biosynthesis, transcriptional regulation, and nuclear integrity in M. oryzae., emphasizing the interaction between M-CNPs and fungal cells. Similarly, metabolomic profiling demonstrated that exposure to M-CNPs significantly altered the levels of several key metabolites involved in the integral components of metabolic pathways, microbial metabolism, histidine metabolism, citrate cycle, and lipid and protein metabolism in M. oryzae. Overall, these findings demonstrated the potent antifungal action of M-CNPs, with a remarkable impact at the physiological and molecular level, culminating in substantial apoptotic-like fungal cell death. This research provides a novel perspective on investigating bioformulated nanomaterials as antifungal agents for plant disease control.
Robotic-assisted hip and knee arthroplasty represents cutting-edge advancements in orthopedic surgery, harnessing robotic technology to enhance precision, improve clinical outcomes, and facilitate intra-operative procedures. In these robotic-assisted surgeries, the robotic systems assist surgeons in planning and executing joint replacement surgeries, thereby facilitating personalized implant positioning and optimizing the fit and alignment of hip and knee implants. Despite the increasing attention garnered by robotic-assisted hip and knee arthroplasty in recent years, a comprehensive bibliometric analysis using the Scopus database has yet to be conducted. This bibliometric analysis reviews the Scopus database from 1961 until 2022 to investigate the literature on the field of robotic-assisted hip and knee arthroplasty. A total of 577 articles that satisfied the selection criteria were included in this review. The majority of the articles focus more on total knee replacement, compared to total hip replacement and unicompartmental knee arthroplasty. The overwhelming majority of the articles were authored by researchers and clinicians from the United States of America (USA) and the United Kingdom (UK). Similarly, most of the articles with the highest number of citations were authored by researchers and clinicians from these regions. This comprehensive bibliometric analysis using Scopus in the domain of robotic-assisted hip and knee replacement has the potential to act as a roadmap for researchers, clinicians, and policymakers, facilitating informed decision-making, promoting collaborative initiatives, and guiding the development of future studies to further advance the field of robotic-assisted hip and knee arthroplasty.
Crucial to the Earth's oceans, ocean currents dynamically react to various factors, including rotation, wind patterns, temperature fluctuations, alterations in salinity and the gravitational pull of the moon. Climate change impacts coastal ecosystems, emphasizing the need for understanding these currents. This study explores multibeam echosounder (MBES), specifically R2-Sonic 2020 instrument, offering detailed seabed information. Investigating coral reefs, rocky reefs and artificial reefs aimed to map seafloor currents movement and their climate change responses. MBES data viz. Bathymetry and backscatter were classified and acoustic doppler current profiler (ADCP) ground data were validated using random forest regression. Results indicated high precision in currents speed measurement i.e. coral reefs with 0.96, artificial reefs with 0.94 and rocky reefs with 0.97. Currents direction accuracy was notable in coral reefs with 0.85, slightly lower in rocky reefs with 0.72 and artificial reefs with 0.60. Random forest identified sediment and backscatter as key for speed prediction while direction relies on bathymetry, slope and aspect. The study emphasizes integrating sediment size, backscatter, bathymetry and ADCP data for seafloor current analysis. This multibeam data on sediments and currents support better marine spatial planning and determine biodiversity patterns planning in the reef area.
The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to over six million deaths worldwide. In human immune system, the type 1 interferon (IFN) pathway plays a crucial role in fighting viral infections. However, the ORF8 protein of the virus evade the immune system by interacting with IRF3, hindering its nuclear translocation and consequently downregulate the type I IFN signaling pathway. To block the binding of ORF8-IRF3 and inhibit viral pathogenesis a quick discovery of an inhibitor molecule is needed. Therefore, in the present study, the interface between the ORF8 and IRF3 was targeted on a high-affinity carbon nanotube by using computational tools. After analysis of 62 carbon nanotubes by multiple docking with the induced fit model, the top five compounds with high docking scores of - 7.94 kcal/mol, - 7.92 kcal/mol, - 7.28 kcal/mol, - 7.19 kcal/mol and - 7.09 kcal/mol (top hit1-5) were found to have inhibitory activity against the ORF8-IRF3 complex. Molecular dynamics analysis of the complexes revealed the high compactness of residues, stable binding, and strong hydrogen binding network among the ORF8-nanotubes complexes. Moreover, the total binding free energy for top hit1-5 was calculated to be - 43.21 ± 0.90 kcal/mol, - 41.17 ± 0.99 kcal/mol, - 48.85 ± 0.62 kcal/mol, - 43.49 ± 0.77 kcal/mol, and - 31.18 ± 0.78 kcal/mol respectively. These results strongly suggest that the identified top five nanotubes (hit1-5) possess significant potential for advancing and exploring innovative drug therapies. This underscores their suitability for subsequent in vivo and in vitro experiments, marking them as promising candidates worthy of further investigation.