3D Structure Research Articles

Identification of novel RANKL inhibitors through in silico analysis

Receptor activator of nuclear factor-κB ligand (RANKL) is considered the principal regulator of osteoclast differentiation. Therefore, strategies interfering with the RANKL-RANK signaling pathway may effectively inhibit osteoclast differentiation and mitigate bone resorption. Consequently, RANKL has become a promising target for new drug design strategies. Despite extensive research on specific drugs and antibodies, only a few have shown efficacy in treating osteoporosis. To address this challenge, we aimed to explore new approaches for designing drugs for osteoporosis. In this study, a 3D quantitative structure–activity relationship (QSAR) pharmacophore model was built for RANKL with reference to known inhibitor IC50 values. The optimal pharmacophore model was then employed as a 3D query to screen databases for novel lead compounds. The obtained compounds were subjected to ADMET and TOPKAT analyses to predict drug pharmacokinetics and toxicity. Molecular docking and de novo evolution approaches were applied to verify the docking binding affinities of the compounds. Five candidate compounds were subjected to further in vitro analyses to assess their anti-osteoporotic effects, among which compound 4 demonstrated significant inhibitory activity, achieving an inhibitory rate of 92.6 % on osteoclastogenesis at a concentration of 10 μM. Subsequent molecular dynamics (MD) simulations to assess the stability and behavior of compound 4 and its evolved variant, ZINC00059014397_Evo, within the RANKL binding site revealed that the variant is a potential therapeutic agent for targeting osteoclasts. This study offers valuable insights for developing next generation RANKL inhibitors for osteoporosis treatments.

In Situ Growth of MoS2 Onto Co-Based MOF Derivatives Toward High-Efficiency Quantum Dot-Sensitized Solar Cells.

Quantum dot sensitized solar cells (QDSCs) represent a promising third-generation photovoltaic technology, boasting a high theoretical efficiency of 44% and cost efficiency. However, their practical efficiency is constrained by reduced photovoltage (Voc) and fill factor (FF). One primary reason is the inefficient charge transfer and elevated recombination rates at the counter electrode (CE). In this work, a novel CE composed of a titanium mesh loaded with Co,N─C@MoS2 is introduced for the assembly of QDSCs. The incorporation of nanosized MoS2 enhances the density of catalytic sites, while the Co,N─C component ensures high conductivity and provides a substantial active surface area. Additionally, the titanium mesh's 3D structure serves as an effective electrical conduit, facilitating rapid electron transfer from the external circuit to the composite. These improvements in catalytic activity, charge transfer rate, and stability of the CE significantly enhance the photovoltaic performance of QDSCs. The optimized cells achieve a groundbreaking power conversion efficiency (PCE) of 16.39%, accompanied by a short-circuit current density (Jsc) of 27.26mA cm-2, Voc of 0.818V, and FF of 0.735. These results not only offer a new strategy for designing electrodes with high catalytic activity but also underscore the promising application of the Co,N─C@MoS2 composite in enhancing QDSC technology.

Detecting 3D Salinity Anomalies from Soil Sampling Points: A Case Study of the Yellow River Delta, China

Rapidly capturing the spatial distribution of soil salinity plays important roles in saline soils’ management. Existing studies mostly focus on the macroscopic distribution of soil-salinity changes, lacking effective methods to detect the structure of micro-regional areas of soil-salinity anomalies. To overcome this problem, this study proposes a 3D Soil-Salinity Anomaly Structure Extraction (3D-SSAS) methodology to discover soil-salinity anomalies and step forward in revealing the irregular 3D structure of soil-anomaly salinity areas from limited sampling points. We first interpolate the sampling points to soil voxels using 3D EBK. A novel concept, the Local Anomaly Index (LAI), is developed to identify the candidate soil-salinity anomalies with the greatest amplitude of change. By performing differential calculations on the LAI sequence to determine the threshold, the anomaly candidates are selected. Finally, we adopt 3D DBSCAN to construct anomalous candidates as a 3D soil-salinity anomaly structure. The experimental results from the Yellow River Delta data set show that 3D-SSAS can effectively identify the 3D structure of salinity-anomaly areas, which are highly correlated with the geographical distribution mechanism of soil salinity. This study provides a novel method for soil science, which is conducive to further research on the complex variation process of soil salinity’s spatial distribution.

Achieving high kinetics anode materials for all-solid-state lithium-ion batteries

Transition metal dichalcogenides (TMDs) have enormous commercial potential as anode materials for all-solid-state lithium-ion batteries (ASSLIBs). Herein, the copper sulfides (CuS) with a hierarchical nanosphere structure are designed through a facile one-step solvothermal synthetic route. When employed as an anode for ASSLIBs, the CuS hierarchical nanospheres (hn-CuS) exhibited a high capacity of 350 mA h g−1 after 50 cycles at a current density of 250 mA g−1 and an outstanding rate capability. The unique three-dimensional (3D) structure of hn-CuS plays an important role in alleviating the volume expansion, thus obtaining excellent electrochemical properties. Moreover, ex-situ X-ray diffraction was used to investigate the possible kinetics and reaction mechanism of the hn-CuS anode. This work inspired a new promise for preparing the other TMDs as anode materials for ASSLIBs with high performance.

Contact Hole Shrinkage: Simulation Study of Resist Flow Process and Its Application to Block Copolymers.

For vertical interconnect access (VIA) in three-dimensional (3D) structure chips, including those with high bandwidth memory (HBM), shrinking contact holes (C/Hs) using the resist flow process (RFP) represents the most promising technology for low-k1 (where CD=k1λ/NA,CD is the critical dimension, λ is wavelength, and NA is the numerical aperture). This method offers a way to reduce dimensions without additional complex process steps and is independent of optical technologies. However, most empirical models are heuristic methods and use linear regression to predict the critical dimension of the reflowed structure but do not account for intermediate shapes. In this research, the resist flow process (RFP) was modeled using the evolution method, the finite-element method, machine learning, and deep learning under various reflow conditions to imitate experimental results. Deep learning and machine learning have proven to be useful for physical optimization problems without analytical solutions, particularly for regression and classification tasks. In this application, the self-assembly of cylinder-forming block copolymers (BCPs), confined in prepatterns of the resist reflow process (RFP) to produce small contact hole (C/H) dimensions, was described using the self-consistent field theory (SCFT). This research paves the way for the shrink modeling of the enhanced resist reflow process (RFP) for random contact holes (C/Hs) and the production of smaller contact holes.

Synthesis, crystal structures and properties of three sodium coordination polymers based on bridging polyoxometalate ligands

The syntheses, crystal structures, spectral characterization, electrochemical, photoredox properties and biological studies of three sodium coordination polymers viz. (ImH)4[(µ2-HMo7O24)Na(H2O)8]∙7H2O 1 (Im = Imidazole), [(TEAH)Na5(H2O)12(µ5-Mo7O24)] 2 (TEA=triethanolamine) and [Na2(PyrH)2(µ2-Mo8O26)(H2O)7]∙8H2O 3 (Pyr = pyrazole) are reported. The unique Na atom in 1 exhibits ten coordination unlike hexa coordination observed in 2 and 3. The µ2-bridging heptamolybdate (or octamolybdate) anion in 1 (or 3) links the sodium cations into an infinite chain resulting in a one-dimensional coordination polymer. In 2, the heptamolybdate anion exhibits an unprecedented µ5-nonadentate binding resulting in a three- dimensional (3D) structure. Compounds 1–3 exhibit characteristic Raman bands. Solar irradiation of 2 results in photodimerization, which is further supported by electrochemical studies. Compounds 1–3 exhibit antibacterial activity, with 3 being the most effective against S. Pyogenes, followed by P. aeruginosa, S.typhi and S. aureus. Compound 3 exhibits excellent antidiabetic and anti-inflammatory properties. A comparative study of the binding modes of several heptamolybdates and octamolybdates based compounds is presented.

Development of dual drug loaded-hydrogel scaffold combining microfluidics and coaxial 3D-printing for intravitreal implantation

Treating diabetic retinopathy (DR) effectively is challenging, aiming for high efficacy with minimal discomfort. While intravitreal injection is the current standard, it has several disadvantages. Implantable systems offer an alternative, less invasive, with long-lasting effects drug delivery system (DDS). The current study aims to develop a soft, minimally invasive, biodegradable, and bioadhesive material-based hydrogel scaffold to prevent common issues with implants. A grid-shaped scaffold was created using coaxial 3D printing (3DP) to extrude two bioinks in a single filament. The scaffold comprises an inner core of curcumin-loaded liposomes (CUR-LPs) that prepared by microfluidics (MFs) embedded in a hydrogel of hydroxyethyl cellulose (HEC), and an outer layer of hyaluronic acid-chitosan matrix with free resveratrol (RSV), delivering two Sirt1 agonists synergistically activating Sirt1 downregulated in DR. Optimized liposomes, prepared via MFs, exhibit suitable properties for retinal delivery in terms of size (<200 nm), polydispersity index (PDI) (<0.3), neutral zeta potential (ZP), encapsulation efficiency (∼97 %), and stability up to 4 weeks. Mechanical studies confirm scaffold elasticity for easy implantation. The release profiles show sustained release of both molecules, with different patterns related to different localization of the molecules. RSV released initially after 30 min with a total release more than 90 % at 336 h. CUR release starts after 24 h with only 4.78 % of CUR released before and gradually released thanks to its internal localization in the scaffold. Liposomes and hydrogels can generate dual drug-loaded 3D structures with sustained release. Microscopic analysis confirms optimal distribution of liposomes within the hydrogel scaffold. The latter resulted compatible in vitro with human retinal microvascular endothelial cells up to 72 h of exposition. The hydrogel scaffold, composed of hyaluronic acid and chitosan, shows promise for prolonged treatment and minimally invasive surgery.

The Phylogenomic Characterization of Planotetraspora Species and Their Cellulases for Biotechnological Applications.

This study aims to evaluate the in silico genomic characteristics of five species of the genus Planotetraspora: P. kaengkrachanensis, P. mira, P. phitsanulokensis, P. silvatica, and P. thailandica, with a view to their application in therapeutic research. The 16S rRNA comparison indicated that these species were phylogenetically distinct. Pairwise comparisons of digital DNA-DNA hybridization (dDDH) and OrthoANI values between these studied type strains indicated that dDDH values were below 62.5%, while OrthoANI values were lower than 95.3%, suggesting that the five species represent distinct genomospecies. These results were consistent with the phylogenomic study based on core genes and the pangenome analysis of these five species within the genus Planotetraspora. However, the genome annotation showed some differences between these species, such as variations in the number of subsystem category distributions across whole genomes (ranging between 1979 and 2024). Additionally, the number of CAZYme (Carbohydrate-Active enZYme) genes ranged between 298 and 325, highlighting the potential of these bacteria for therapeutic research applications. The in silico physico-chemical characteristics of cellulases from Planotetraspora species were analyzed. Their 3D structure was modeled, refined, and validated. A molecular docking analysis of this cellulase protein structural model was conducted with cellobiose, cellotetraose, laminaribiose, carboxymethyl cellulose, glucose, and xylose ligand. Our study revealed significant interaction between the Planotetraspora cellulase and cellotetraose substrate, evidenced by stable binding energies. This suggests that this bacterial enzyme holds great potential for utilizing cellotetraose as a substrate in various applications. This study enriches our understanding of the potential applications of Planotetraspora species in therapeutic research.

Synthesis of N/O Atoms Co-doped Biochar with 3D Porous Structure for Effective Electromagnetic Wave Absorption.

Developing biochar with large specific surface area (SSA), heteroatom doping, and porous structure is attracting substantial attention to absorb electromagnetic wave (EMW) in recent. Herein, a novel method of ethanol and KOH co-treatment is used to produce the biomass carbon deriving from pitaya peels. The obtained carbon possesses the high SSA of 1580 m2/g, successful N/O atoms co-doping, and massive pores with different size. The results of EMW absorption measurement show that the prepared biochar could achieve over 99% absorpition to EMW, which the highest reflection loss is of ca. -45.25 dB at 7.54 GHz with an effective absorption bandwidth (EAB) of ca. 4.87 GHz. The execellent microwave absorption property is caused by the surface defects, dipole and interface polarizations of the synthesized biochar owning unique microstructure and N/O atoms co-doping. Hence, this avenue provides a new reference for fabricating low-cost and eco-friendly biochar as a microwave absorber.

Free‐Standing Si@C/CNFs Prepared by Simple Electrospinning as a Stable Anode for Lithium‐Ion Batteries

AbstractThe development of free‐standing and foldable electrodes with excellent electrochemical performance is paramount for flexible electronic devices. However, the silicon‐based free‐standing anodes lack a straightforward preparation process. Herein, we successfully designed a hierarchical Si@C/CNFs composite material by combining hydrothermal and electrospinning techniques, in which the carbon‐coated silicon (Si@C) is served as the primary nanostructure and carbon nanofibers (CNFs) from electrospinning are maintained as the network matrix, resulting in a free‐standing anode. Owing to the amorphous carbon coating on Si nanoparticles and the formation of a 3D network structure of CNFs, which tightly encases the primary Si@C nanostructure, the Si@C/CNFs electrode demonstrates exceptional conductivity and flexibility. This dual carbon‐layer structure further enhances kinetics and mitigates the volume expansion of Si nanoparticles. The Si@C/CNFs electrode exhibits a high specific capacity (1573 mAh g−1 at 0.1 A g−1), exceptional rate capability, and excellent cycling stability (78.5 % capacity retention after 100 cycles). Thus, Si@C/CNFs can be a promising material for the anode electrode in flexible lithium‐ion batteries.

Hybrid scaffolds for bone tissue engineering: Integration of composites and bioactive hydrogels loaded with hDPSCs

Bone tissue regeneration remains a significant challenge in clinical settings due to the complexity of replicating the mechanical and biological properties of bone environment. This study addresses this challenge by proposing a hybrid scaffold designed to enhance both bioactivity and physical stability for bone tissue regeneration. This research is the fisrt to develop a rigid 3D structure composed of polycaprolactone (PCL) and hydroxyapatite nanoparticles (nHA) integrated with a bioink containing human dental pulp stem/stromal cells (hDPSCs), alginate, nHA and collagen (Col). The biofabricated constructs were extensively characterized through cytocompatibility tests, osteogenic differentiation assessment, and biocompatibility evaluation in a rat model. In vitro results demontrated that the hybrid scaffolds presented significantly higher cell viability after 168 h compared to the control group. Furthermore, the hybrid scaffolds showed increased osteogenic differentiation relative to other groups. In vivo evaluation indicated good biocompatibility, characterized by minimal inflammatory response and successful tissue integration. These findings highlight the scaffold's potential to support bone tissue regeneration by combining the mechanical strength of PCL and nHA with the biological activity of the alginate-nHA-Col and hDPSCs bioink. The current study provides a promising foundation for the development of biomaterials aimed at improving clinical outcomes in bone repair and regeneration, particulary for the treatment of critical-size bone defects, targeted drug administration, and three-dimensional models for bone tissue engineering.

GraphNABP: Identifying nucleic acid-binding proteins with protein graphs and protein language models

The computational identification of nucleic acid-binding proteins (NABP) is of great significance for understanding the mechanisms of these biological activities and drug discovery. Although a bunch of sequence-based methods have been proposed to predict NABP and achieved promising performance, the structure information is often overlooked. On the other hand, the power of popular protein language models (pLM) has seldom been harnessed for predicting NABPs. In this study, we propose a novel framework called GraphNABP, to predict NABP by integrating sequence and predicted 3D structure information. Specifically, sequence embeddings and protein molecular graphs were first obtained from ProtT5 protein language model and predicted 3D structures, respectively. Then, graph attention (GAT) and bidirectional long short-term memory (BiLSTM) neural networks were used to enhance feature representations. Finally, a fully connected layer is used to predict NABPs. To the best of our knowledge, this is the first time to integrate AlphaFold and protein language models for the prediction of NABPs. The performances on multiple independent test sets indicate that GraphNABP outperforms other state-of-the-art methods. Our results demonstrate the effectiveness of pLM embeddings and structural information for NABP prediction. The codes and data used in this study are available at https://github.com/lixiangli01/GraphNABP.

Experimental characterization and prediction of Escherichia coli host cell proteome retention during preparative chromatography.

Purification of recombinantly produced biopharmaceuticals involves removal of host cell material, such as host cell proteins (HCPs). For lysates of the common expression host Escherichia coli (E. coli) over 1500 unique proteins can be identified. Currently, understanding the behavior of individual HCPs for purification operations, such as preparative chromatography, is limited. Therefore, we aim to elucidate the elution behavior of individual HCPs from E. coli strain BLR(DE3) during chromatography. Understanding this complex mixture and knowing the chromatographic behavior of each individual HCP improves the ability for rational purification process design. Specifically, linear gradient experiments were performed using ion exchange (IEX) and hydrophobic interaction chromatography, coupled with mass spectrometry-based proteomics to map the retention of individual HCPs. We combined knowledge of protein location, function, and interaction available in literature to identify trends in elution behavior. Additionally, quantitative structure-property relationship models were trained relating the protein 3D structure to elution behavior during IEX. For the complete data set a model with a cross-validated R2 of 0.55 was constructed, that could be improved to a R2 of 0.70 by considering only monomeric proteins. Ultimately this study is a significant step toward greater process understanding.

Glucose-6-phosphate dehydrogenase and its 3D structures from crystallography and electron cryo-microscopy.

Glucose-6-phosphate dehydrogenase (G6PD) is the first enzyme in the pentose phosphate pathway. It has been extensively studied by biochemical and structural techniques. 13 X-ray crystal structures and five electron cryo-microscopy structures in the PDB are focused on in this topical review. Two F420-dependent glucose-6-phosphate dehydrogenase (FGD) structures are also reported. The significant differences between human and parasite G6PDs can be exploited tofind selective drugs against infections such as malaria and leishmaniasis. Furthermore, G6PD is a prognostic marker in several cancer types and is also considered to be a tumour target. On the other hand, FGD is considered to be a target against Mycobacterium tuberculosis and possesses a high biotechnological potential in biocatalysis and bioremediation.

ARTEMIS: a method for topology-independent superposition of RNA 3D structures and structure-based sequence alignment.

Non-coding RNAs play a major role in diverse processes in living cells with their sequence and spatial structure serving as the principal determinants of their function. Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA. To date, state-of-the-art methods for RNA 3D structure superposition rely on intricate heuristics, and the potential for topology-independent superposition has not been exhausted. Recently, we introduced the ARTEM method for unrestrained pairwise superposition of RNA 3D modules and now we developed it further to solve the global RNA 3D structure alignment problem. Our new tool ARTEMIS significantly outperforms state-of-the-art tools in both sequentially-ordered and topology-independent RNA 3D structure superposition. Using ARTEMIS we discovered a helical packing motif to be preserved within different backbone topology contexts across various non-coding RNAs, including multiple ribozymes and riboswitches. We anticipate that ARTEMIS will be essential for elucidating the landscape of RNA 3D folds and motifs featuring sequence permutations that thus far remained unexplored due to limitations in previous computational approaches.

Ion pump-inspired biomimetic interfacial evaporation platform for simultaneous seawater desalination, uranium extraction, and electricity generation

To accelerate progress toward the Sustainable Development Goals (SDGs), here we develop an ion pump-inspired biomimetic interfacial evaporation platform (IBIP). Such an innovative platform integrates seawater desalination, electricity generation, and uranium extraction. A biochar-doped sodium alginate hydrogel is used to validate the IBIP’s efficacy. In long-term trials under 1 sun, IBIP maintains a stable evaporation rate of 1.80 kg m−2 h−1 and achieves a consistent uranium adsorption ratio exceeding 80 % within 48 h in real seawater. Additionally, the IBIP demonstrates an enhanced electricity output, with Voc and Isc reaching 0.9 V and 14.0 μA, respectively. By constructing a 3D structure, the IBIP’s performance under 1 sun significantly escalates to 4.3 kg m−2 h−1 for evaporation rate, 168.1 mg g−1 for uranium extraction capacity, and 1.02 V for Voc, respectively. In conclusion, this work offers a high-efficiency and eco-friendly way for the sustainable utilization of seawater resources.

Applications of reinforcement learning, machine learning, and virtual screening in SARS-CoV-2-related proteins

Similarly, to all coronaviruses, SARS-CoV-2 uses the S glycoprotein to enter host cells, which contains two functional domains: S1 and S2 receptor binding domain (RBD). Angiotensin-converting enzyme 2 (ACE2) is recognizable by the S proteins on the surface of the SARS-CoV-2 virus. The SARS-CoV-2 virus causes SARS, but some mutations in the RBD of the S protein markedly enhance their binding affinity to ACE2. Searching for new compounds in COVID-19 is an important initial step in drug discovery and materials design. Still, the problem is that this search requires trial-and-error experiments, which are costly and time-consuming. In the automatic molecular design method based on deep reinforcement learning, it is possible to design molecules with optimized physical properties by combining a newly devised coarse-grained representation of molecules with deep reinforcement learning. Also, structured-based virtual screening uses protein 3D structure information to evaluate the binding affinity between proteins and compounds based on physicochemical interactions such as van der Waals forces, Coulomb forces, and hydrogen bonds, and select drug candidate compounds. In addition, AlphaFold can predict 3D protein structures, given the amino acid sequence, and the protein building blocks. Ensemble docking, in which multiple protein structures are generated using the molecular dynamics method and docking calculations are performed for each, is often performed independently of docking calculations. In the future, the AlphaFold algorithm can be used to predict various protein structures related to COVID-19.

In-situ constructing oxygen-enriched vacancies BiOCl with 3D flower-structure for exceptional visible-light-driven photocatalytic properties

Bismuth oxychloride (BiOCl), emerging as a novel environmentally friendly nanomaterial, possesses considerable potential for photocatalytic degradation of organic wastewater. However, inadequate active sites and inhibited electron separation efficiency severely hinder its visible-light photocatalytic activity. To address this issue, herein we present a facile approach to in-situ construct BiOCl three-dimensional (3D) flower-structure (BOC-F) with oxygen-enriched vacancies for abundant active sites and effective electron separation efficiency through morphology control and vacancy engineering. The visible photocatalytic activity of BOC-F and BiOCl with 2D flaky-structure (BOC-S) was assessed through a systematic examination of the degradation efficiencies of tetracycline hydrochloride (TC-HCl) and rhodamine B (RhB). Under visible light irradiation, BOC-F exhibited superior visible photocatalytic activity, effectively degrading tetracycline hydrochloride (TC-HCl) (20 mg/L) and rhodamine B (RhB) (200 mg/L) within 90 min and 20 min of light exposure, respectively. The findings elucidate that BOC-F, possessing a 3D flower structure, manifests a heightened concentration of oxygen vacancies in contrast to BOC-S, consequently yielding excellent performance. Moreover, The ESR test showed that singlet oxygen (1O2) and hole (h+) were two main active species in the photocatalytic degradation of BOC-F. This work not only furnishes a facile method for constructing oxygen-rich vacancies in BiOCl but also provides fresh insights into the potential for enhancing the visible photocatalytic properties of Bi-based materials through vacancy engineering.

Aptamer-based Strategies for COVID-19 Detection and Treatment: A Systematic Review Study

Background: Aptamer-based strategies have emerged as promising tools for the detection and treatment of COVID-19, offering advantages such as high specificity, sensitivity, and versatility. This systematic review aims to evaluate the effectiveness and innovation of aptamer-based approaches for COVID-19 detection and treatment. Methods: Following the guidelines of the Cochrane Handbook for Systematic Reviews and the PRISMA 2020 guidelines, a systematic search was conducted across multiple databases up to 2024. The search included studies that utilized aptamers for the diagnosis or therapy of COVID-19. Screening and selection of studies were performed independently by two reviewers, with any disagreements resolved by a third reviewer. Data were extracted regarding study characteristics, aptamer details, and outcomes. Results: In our systematic review, 98 studies from an initial pool of 1541 records met the inclusion criteria for analysis. Aptamers, single-stranded DNA or RNA molecules with unique threedimensional (3D) structures, were extensively explored for COVID-19 detection and treatment. Various aptamer-based assays, including electrochemical sensors, surface plasmon resonance (SPR) biosensors, and lateral flow assays, demonstrated high sensitivity and specificity in detecting SARSCoV- 2 in clinical samples such as saliva, nasal swabs, and wastewater. Several aptamer structures targeting viral proteins like the spike and nucleocapsid proteins were employed. Nucleic Acid Amplification Techniques (NAATs) utilizing aptamers, such as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based and Loop-mediated Isothermal Amplification (LAMP) assays, showed exceptional sensitivity in detecting viral genetic material. Aptamer-based therapeutic approaches showed potential by blocking viral protein activity or serving as delivery vehicles for therapeutic agents like small interfering RNAs (siRNAs). Despite their advantages, aptamer technologies face limitations such as susceptibility to nuclease degradation and rapid renal clearance, highlighting the need for further optimization. Conclusion: Aptamer-based strategies present promising avenues for COVID-19 detection and treatment. These approaches offer advantages such as high sensitivity, specificity, and rapid detection, making them valuable tools in combating the COVID-19 pandemic. Further research and development are warranted to optimize aptamer-based strategies for widespread application in clinical settings.

EXPERIMENTAL STUDY ON OPTIMIZING THE FUSED DEPOSITION MODELING PARAMETERS FOR POLYETHYLENE TEREPHTHALATE GLYCOL MATERIAL USING TAGUCHI METHOD

In many different manufacturing techniques, additive manufacturing technologies have proven to be quite useful for developing a prototype model in wide range of applications. In that technique, Fused Deposition Modeling (FDM) is one of the concern favorite methods used in industries, because it can create complex structures at a low cost. FDM uses the polymer ingredients that are melted, extruded, and layered on top of one another to create the desired product, independent of design intricacy. This examination analyzes the effects of several process variables on the flexural and impact characteristics of parts produced of polyethylene terephthalate glycol (PETG)material, including infill structure, layer thinness, infill multi-layering, and infill concentration. The L9 orthogonal array was developed by the Taguchi method to be employed in this design of experiment. Through the analysis of variance (ANOVA), the study elucidated the relative substance and percentage effort of each process parametric quantity to the desired outcomes. The results obtained through the Taguchi method revealed optimal parameters for both impact strength and flexural tests. For impact strength, the optimum factor was determined as a layer thinness of 0.12-millimeter, quarter cubic infill structure, 30% infill denseness (density), and a multi-layering of 3. Conversely, for the flexural test, the optimal factor was found to be a layer thinness of 0.12-millimeter, cross 3D infill structure, 60% infill denseness, and a multi-layering of 4 respectively.