Gold Nanoparticles with Self-Assembled Cysteine Monolayer Coupled to Nitrate Reductase in Polypyrrole Matrix Enhanced Nitrate Biosensor

We have developed here a novel, highly sensitive and selective nitrate (NO– 3) biosensor by covalent immobilization of nitrate reductase (NaR) in self-assembled monolayer (SAM) of cysteine on gold nanoparticles (GNP)-polypyrrole (PPy) modified platinum electrode. Incorporation of GNP in highly microporous PPy matrix was confirmed by morphological scanning electron microscope (SEM) images. The electrochemical behavior of the NaR modified electrode exhibited the characteristic reversible redox peaks at the potential, –0.76 and –0.62 V versus Ag/AgCl. Further, the GNP-PPy nanocomposite enhanced the current response by 2-fold perhaps by enhancing the immobilization of NaR and also direct electron transfer between the deeply buried active site and the electrode surface. The common biological interferences like ascorbic acid, uric acid were not interfering with the NO– 3 measurement at low concentration levels. This biosensor showed a wide linear range of response over the concentration of NO– 3 from 1 μM to 1 mM, with higher sensitivity of 84.5 nA μM–1 and a detection limit of 0.5 μM. Moreover, the NO– 3 level present in the nitrate-rich beetroot juice and the NO– 3 release from the lipopolysaccharide treated human breast cancer cells were estimated

Compressive strength performance of 3D printed PLA/almond shell particles reinforced PLA multi-material composite

The advent of 3D printing has revolutionized the manufacturing landscape, enabling the creation of intricate structures and personalized designs. The use of multi-material polymer composites in additive manufacturing has further expanded possibilities, offering enhanced mechanical properties and advanced functionalities. In the present study, PLA/Almond shell reinforced PLA (PLA/AmdPLA) multi-material composites were developed using Fused Filament Fabrication (FFF) method. The objective of this study is to develop the multi-material and optimize the 3D-Printing Parameters (3D-PP) with respect to Printing Speed (PS), Layer Height (LH), and Printing Temperature (PT), in order to maximize the compressive strength of the composites. The L16 Taguchi orthogonal array was established to systematically study the effects of the 3D-PP on the compressive strength. Through a series of experiments, varying the levels of each 3D-PP, data was collected and analyzed to determine the optimal 3D-PP settings. The results demonstrate that the PLA/AmdPLA multi-material composites achieved its maximum compressive strength when fabricated at a PS of 20 mm/sec, a LH of 0.1 mm, and a PT of 210°C. Furthermore, the findings revealed that the PS and LH significantly influenced the compressive strength, while the PT exhibited moderate effects. The regression analysis results indicate that the compression experiments conducted on the PLA/AmdPLA multi-material composites yielded an error percentage of 4.73%. This suggests a strong agreement between the predicted values obtained from the regression model and the actual experimental results which shows that the model has high accuracy. Therefore, these functional composite materials are recognized for their superior strength, lightweight properties, appealing aesthetics, and sustainable qualities in various consumer applications

Preparation and performance evaluation of 3D printed poly lactic acid composites reinforced with silane functionalized walnut shell for food packaging applications

The main goal of this work is to develop silane-grafted Poly Lactic Acid (PLA) bio-composites reinforced by various compositions of 0, 5, 10, and 15 wt% Walnut shell (WAL) particles and 3D printed by Fused Filament Fabrication (FFF) technique. The composite filaments are extruded by filament extrusion technique, and the 3D printed Walnut shell/PLA (WAL/PLA) bio-composite samples are evaluated for various mechanical, water absorption and biodegradation properties. The effect of silane grafting increases the crystallinity index value of 61.2% for the silane-grafted WAL particles. The mechanical property results reveal that using WAL particles reduces the strength value and improves the modulus of both untreated and silane-treated WAL/PLA composites. The silane grafted 15% WAL/PLA samples show the highest shore hardness value of 71 MPa and the heat deflection temperature of 63.79 ℃. The biodegradation test results reveal that the untreated 15% WAL/PLA composites have a higher mass loss of 6.4% and 19.1% for 30 and 60 days, respectively. Fractographical results of silane-treated 10% WAL/PLA composites exhibit a uniform distribution of WAL particles with minimum particle pull-out from the polymeric matrix. The findings of this study affirm the potential of WAL/PLA bio-composites as a viable and sustainable material for application in food storage and service

Molecular dynamics simulation approach to explore atomistic molecular mechanism of peroxidase activity of apoptotic cytochrome c mutants

Mutations in cytochrome c (Cyt c) have been reported in tuning peroxidase activity, which in-turn cause Cyt c release from mitochondria and early apoptosis. However, the molecular tuning mechanism underlying this activity remains elusive. Herein, multiple 20 ns molecular dynamics (MD) simulations of wild type (WT), Y67F and K72W mutated Cyt c in aqueous solutions have been carried out to study how the changes in structural features alters the peroxidase activity of the protein. MD simulation results indicate that Y67F mutation caused, (i) increased distances between critical electron-transfer residues, (ii) higher fluctuations in omega loops, and (iii) weakening of intraprotein hydrogen bonds result in open conformation at heme crevice loop in Cyt c leading to an enhanced peroxidase activity. Interestingly, the aforementioned structural features are strengthened in K72W compared to WT and Y67F, which triggers K72W mutated Cyt c into a poor peroxidase. Essential dynamics results unveil that first two eigenvectors are responsible for overall motions of WT, Y67F and K72W mutated Cyt c. This study thus provides atomic level insight into molecular mechanism of peroxidase activity of Cyt c, which will help in designing novel Cyt c structures that is more desirable than natural Cyt c for biomedical and industrial processe

Predictive modeling of compressive strength for additively manufactured PEEK spinal fusion cages using machine learning techniques

The current study delves into the utilization of Machine Learning (ML) algorithms to evaluate the mechanical properties of additively manufactured PEEK spinal fusion cages. In this research, a range of ML models, including Linear Regression (LiR), Lasso Regression (LaR), Decision tree (DT), and K-Nearest Neighbor (KNN) are harnessed to enhance compressive strength prediction. Ensemble learning techniques such as bagging, boosting, and stacking are applied to identify the most accurate ML model in terms of achieving heightened accuracy and minimized errors. To facilitate this, spinal fusion cages are 3D printed using the Fused Filament Fabrication (FFF) technique and subsequently tested using a Universal Testing Machine (UTM). The development of ML models involves the exploration of independent material-extrusion factors, encompassing layer height (0.1 mm, 0.2 mm, 0.3 mm), printing temperature (370℃, 390℃, 410℃), printing speed (10 mm/sec, 30 mm/sec, 50 mm/sec), infill density (40%, 70%, 100%), build orientation (0º, 45º, 90º), and line width (0.1 mm, 0.2 mm, 0.3 mm). The robustness and effectiveness of the developed ML models in predicting compressive strength properties are optimized through comprehensive error metric analysis. The results indicate that the LiR model, particularly when implemented under the boosting ensemble technique, demonstrates the highest accuracy with a Mean Absolute Error (MAE) of 0.657, Root Mean Square Error (RMSE) of 0.758, and Median Absolute Error (MedAE) of 0.634. This underscores the potential of LiR for precise compressive strength prediction in 3D-printed PEEK spinal fusion cages for spinal and maxillomandibular reconstruction

Double transition metal MXene (TixTa4−xC3) 2D materials as anodes for Li-ion batteries

Abstract A bi-metallic titanium–tantalum carbide MXene, TixTa(4−x)C3 is successfully prepared via etching of Al atoms from parent TixTa(4−x)AlC3 MAX phase for the first time. X-ray diffractometer and Raman spectroscopic analysis proved the crystalline phase evolution from the MAX phase to the lamellar MXene arrangements. Also, the X-ray photoelectron spectroscopy (XPS) study confirmed that the synthesized MXene is free from Al after hydro fluoric acid (HF) etching process as well as partial oxidation of Ti and Ta. Moreover, the FE-SEM and TEM characterizations demonstrate the exfoliation process tailored by the TixTa(4−x)C3 MXene after the Al atoms from its corresponding MAX TixTa(4−x)AlC3 phase, promoting its structural delamination with an expanded interlayer d-spacing, which can allow an effective reversible Li-ion storage. The lamellar TixTa(4−x)C3 MXene demonstrated a reversible specific discharge capacity of 459 mAhg−1 at an applied C-rate of 0.5 °C with a capacity retention of 97% over 200 cycles. An excellent electrochemical redox performance is attributed to the formation of a stable, promising bi-metallic MXene material, which stores Li-ions on the surface of its layers. Furthermore, the TixTa(4−x)C3 MXene anode demonstrate a high rate capability as a result of its good electron and Li-ion transport, suggesting that it is a promising candidate as Li-ion anode material