Search Results (47)

The combination of polypyrrole (PPy) with graphene has attracted extensive attention as a nonlinear optical material with various optoelectronic applications. Here, we describe the development of PPy nanoplates prepared using a simple spin-coating method. The appropriate volume of the dropped PPy solution was determined to be 50 drops by comparing the surface morphologies, chain structures, elementary compositions, and optical properties of PPy saturable absorbers (SAs). The hybrid PPy/graphene heterostructure SA was obtained using the wet transfer process of a graphene layer. This approach led to significant improvements in optical properties, including a ~7.2% increase in linear optical absorption, a 2.5-fold increase in modulation depth, and a third decrease in saturable intensity at 1550 nm due to the additional optical absorption and the π-π interaction between PPy nanoplates and the graphene layer. By inserting the PPy/graphene heterostructure SA into the passively mode-locked fiber laser cavity, 1559 nm ultrashort laser pulses were generated, with an average output power of 1.24 mW, a 815 fs pulse width, and a repetition frequency of 3.26 MHz. Our experimental results demonstrate that the prepared PPy SA has excellent nonlinear optical characteristics, providing a new opportunity for the generation of ultrashort laser pulses. Full article

Human activities and river course change have a complex reciprocal interaction. The river channel is altered by human activity, and these alterations have an impact on the activities and settlements along the riverbank. Understanding the relationship between urbanization and changes in river morphology is crucial for effective river management, safeguarding the urban environment, and mitigating flood hazards. In this context, this study has been conducted to investigate the interrelationship between morphological dynamics, built-up growth, and urban flood risk along the Manohara River in Kathmandu Valley, Nepal. The Sinuosity Index was used to analyze variation in river courses and instability from 1996 to 2023. Built-up change analysis is carried out using supervised maximum likelihood classification method and rate of change is calculated for built-up area growth (2003–2023) and building construction between 2003 and 2021. Flood hazard risk manning was carried out using flood frequency estimation method integrating HEC-GeoRAS modeling. Linear regression and spatial overlay analysis was carried out to examine the interrelationship between river morphology, urban growth, and fold hazed risk. In recent years (2016–2023), the Manohara River has straightened, particularly after 2011. Before 2011, it had significant meandering with pronounced curves and bends, indicating a mature river system. However, the SI value of 1.45 in 2023 and 1.80 in 2003 indicates a significant straightening of high meandering over 20 years. A flood hazard modeling carried out within the active floodplain of the Manohara River shows that 26.4% of the area is under high flood risk and 21% is under moderate risk. Similarly, over 10 years from 2006 to 2016, the rate of built-up change was found to be 9.11, while it was 7.9 between 2011 and 2021. The calculated R² value of 0.7918 at a significance level of 0.05 (with a p value of 0.0175, and a standard error value of 0.07877) indicates a strong positive relationship between decreasing sinuosity and increasing built-up, which demonstrates the effect of built-up expansion on river morphology, particularly the anthropogenic activities of encroachment and haphazard constructions, mining, dumping wastes, and squatter settlements along the active floodplain, causing instability on the river course and hence, lateral shift. The riverbank and active floodplain are not defined scientifically, which leads to the invasion of the river area. These activities, together with land use alteration in the floodplain, show an increased risk of flood hazards and other natural calamities. Therefore, sustainable protection measures must be prioritized in the active floodplain and flood risk areas, taking into account upstream–downstream linkages and chain effects caused by interaction between natural and adverse anthropogenic activities. Full article

Staphylococcus aureus is the primary pathogen responsible for mastitis in dairy cows and foodborne illnesses, posing a significant threat to public health and food safety. Here, we developed an enhanced sensor based on solid-phase separation using gold-magnetic nanoparticles (Au@Fe₃O₄) and signal amplification via dendritic DNA nanostructures. The substrate chain was specifically immobilized using thiol–gold coordination, and a three-dimensional dendritic structure was constructed through sequential hybridization of DNAzymes, L chains, and Y chains, resulting in a 2.8-fold increase in initial fluorescence intensity. Upon specific cleavage of the substrate chain at the rA site by S. aureus DNA, the complex dissociates, resulting in fluorescence intensity decay. The fluorescence intensity is negatively correlated with the concentration of Staphylococcus aureus. After optimization, the biosensor maintains a detection limit of 1 CFU/mL within 3 min, with a linear range extended to 1–10⁷ CFU/mL (R² = 0.998) and recovery rates of 85.6–102.1%, significantly enhancing resistance to matrix interference. This provides an innovative solution for rapid on-site detection of foodborne pathogens. Full article

Virus-like nanoparticles (VNPs) based on Moloney murine leukemia virus represent a well-established platform for the expression of heterologous molecules such as cytokines, cytokine receptors, peptide MHC (pMHC) and major allergens, but their application for inducing protective anti-viral immunity has remained understudied as of yet. Here, we variably fused the wildtype SARS-CoV-2 spike, its receptor-binding domain (RBD) and nucleocapsid (NC) to the minimal CD16b-GPI anchor acceptor sequence for expression on the surface of VNP. Moreover, a CD16b-GPI-anchored single-chain version of IL-12 was tested for its adjuvanticity. VNPs expressing RBD::CD16b-GPI alone or in combination with IL-12::CD16b-GPI were used to immunize BALB/c mice intramuscularly and subsequently to investigate virus-specific humoral and cellular immune responses. CD16b-GPI-anchored viral molecules and IL-12-GPI were well-expressed on HEK-293T-producer cells and purified VNPs. After the immunization of mice with VNPs, RBD-specific antibodies were only induced with RBD-expressing VNPs, but not with empty control VNPs or VNPs solely expressing IL-12. Mice immunized with RBD VNPs produced RBD-specific IgM, IgG_2a and IgG₁ after the first immunization, whereas RBD-specific IgA only appeared after a booster immunization. Protein/peptide microarray and ELISA analyses confirmed exclusive IgG reactivity with folded but not unfolded RBD and showed no specific IgG reactivity with linear RBD peptides. Notably, booster injections gradually increased long-term IgG antibody avidity as measured by ELISA. Interestingly, the final immunization with RBD–Omicron VNPs mainly enhanced preexisting RBD Wuhan Hu-1-specific antibodies. Furthermore, the induced antibodies significantly neutralized SARS-CoV-2 and specifically enhanced cellular cytotoxicity (ADCC) against RBD protein-expressing target cells. In summary, VNPs expressing viral proteins, even in the absence of adjuvants, efficiently induce functional SARS-CoV-2-specific antibodies of all three major classes, making this technology very interesting for future vaccine development and boosting strategies with low reactogenicity. Full article

Herein, a sensitive electrochemiluminescence (ECL) immunosensor is designed by immobilizing ruthenium-tagged immune complexes at flexible poly-ethylene-glycol (PEG) chains on the electrode surface, which offers more freedom for the collision of the ruthenium complex at the electrode during the initial ECL reaction. The electrochemical characterizations confirm the loose structure of the assembled layer with the immune complex, providing an increase in the current and the resultant enhanced ECL emissions. Comparing the sensors with the rigid structure, a 34-fold increase in the maximal ECL emission is recorded when PEG3400 is used as a linker. Using the optimized protocol, the prepared immunosensor exhibits a wide-ranging linear response to the model antibody (glutamate decarboxylase antibody) ranging from 10 pg/mL to 10 ng/mL. The detection limit is almost two orders lower than the value using the classic enzyme-linked immunosorbent assay, which offers a new design to enhance ECL emissions and the resultant analytical performance. Full article

We start presenting an overview on recent applications of linear polymers and networks in condensed matter physics, chemistry and biology by briefly discussing selected papers (published within 2022–2024) in some detail. They are organized into three main subsections: polymers in physics (further subdivided into simulations of coarse-grained models and structural properties of materials), chemistry (quantum mechanical calculations, environmental issues and rheological properties of viscoelastic composites) and biology (macromolecules, proteins and biomedical applications). The core of the work is devoted to a review of theoretical aspects of linear polymers, with emphasis on self-avoiding walk (SAW) chains, in regular lattices and in both deterministic and random fractal structures. Values of critical exponents describing the structure of SAWs in different environments are updated whenever available. The case of random fractal structures is modeled by percolation clusters at criticality, and the issue of multifractality, which is typical of these complex systems, is illustrated. Applications of these models are suggested, and references to known results in the literature are provided. A detailed discussion of the reptation method and its many interesting applications are provided. The problem of protein folding and protein evolution are also considered, and the key issues and open questions are highlighted. We include an experimental section on polymers which introduces the most relevant aspects of linear polymers relevant to this work. The last two sections are dedicated to applications, one in materials science, such as fractal features of plasma-treated polymeric materials surfaces and the growth of polymer thin films, and a second one in biology, by considering among others long linear polymers, such as DNA, confined within a finite domain. Full article

Background: Tetrahydrocannabivarin (THCV) is a phytocannabinoid commonly found in cannabis with potential pharmacological properties; however, its post-acute pharmacokinetics (PK) in humans have not been studied yet. THCV has two isomers, Δ9- and Δ8-THCV, which seem to have different pharmacological properties. We investigated the PK of the Δ8-THCV isomer after oral administration as part of a two-phase, dose-ranging, placebo-controlled trial in healthy participants. Methods: Participants (n = 21) were enrolled in six study sessions and randomly received the following doses of a medium-chain triglyceride (MCT) oil oral formulation of Δ8-THCV: placebo, 12.5 mg, 25 mg, 50 mg, 100 mg, and 200 mg. Plasma samples from 15 participants were collected up to 8 h after administration and were analyzed by a validated two-dimensional high-performance liquid chromatography–tandem mass spectrometry assay. The trial was registered on clinicaltrials.gov (NCT05210634). Results: After oral administration, 11-nor-9-carboxy-Δ8-THCV (Δ8-THCV-COOH) was the main metabolite detected. The median time-to-maximum concentration (t_max) ranged 3.8–5.0 h across doses for Δ8-THCV and 4.6–5.3 h for Δ8-THCV-COOH. The maximum concentration (C_max) and area under the concentration–time curve over the observation period (AUC_last) appeared to be dose-linear. Median AUC_last increased 2.3- to 4.8-fold and 1.7- to 2.9-fold for Δ8-THCV and Δ8-THCV-COOH, respectively, every two-fold increase in the dose. The isomers Δ9-THCV and Δ9-THCV-COOH were detected in plasma, despite being undetected in the formulated drug product analyzed by a third-party laboratory. Conclusions: For the first time, we report the pharmacokinetics of Δ8-THCV and its major metabolites after oral administration in humans. Δ8-THCV AUC_last showed dose linearity but the observed possible conversion to the Δ9-THCV isomer should be further studied. Full article

The molecular machines of life, proteins, are made up of twenty kinds of amino acids, each with distinctive side chains. We present a geometrical analysis of the protrusion statistics of side chains in more than 4000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of C_α atoms and consider just the heavy atoms of the side chains. We study the large variety of behaviors of the amino acids based on both rudimentary structural chemistry as well as geometry. Our geometrical analysis uses a backbone Frenet coordinate system for the common study of all amino acids. Our analysis underscores the richness of the repertoire of amino acids that is available to nature to design protein sequences that fit within the putative native state folds. Full article

Carbon-based novel low-dimensional XC/YC (with X, Y ≡ Si, Ge, and Sn) heterostructures have recently gained considerable scientific and technological interest in the design of electronic devices for energy transport use in extreme environments. Despite many efforts made to understand the structural, electronic, and vibrational properties of XC and X_xY_1−xC alloys, no measurements exist for identifying the phonon characteristics of superlattices (SLs) by employing either an infrared and/or Raman scattering spectroscopy. In this work, we report the results of a systematic study to investigate the lattice dynamics of the ideal ${\left(\mathrm{X}\mathrm{C}\right)}_{\mathrm{m}}$/${\left(\mathrm{Y}\mathrm{C}\right)}_{\mathrm{n}}$ as well as graded ${\left(\mathrm{X}\mathrm{C}\right)}_{10-∆}/{\left({\mathrm{X}}_{0.5}{\mathrm{Y}}_{0.5}\mathrm{C}\right)}_{∆}/{\left(\mathrm{Y}\mathrm{C}\right)}_{10-∆}/{\left({\mathrm{X}}_{0.5}{\mathrm{Y}}_{0.5}\mathrm{C}\right)}_{∆}$ SLs by meticulously including the interfacial layer thickness $∆$ (≡1–3 monolayers). While the folded acoustic phonons (FAPs) are calculated using a Rytov model, the confined optical modes (COMs) and FAPs are described by adopting a modified linear-chain model. Although the simulations of low-energy dispersions for the FAPs indicated no significant changes by increasing $∆$, the results revealed, however, considerable “downward” shifts of high frequency COMs and “upward” shifts for the low energy optical modes. In the framework of a bond polarizability model, the calculated results of Raman scattering spectra for graded SLs are presented as a function of $∆.$ Special attention is paid to those modes in the middle of the frequency region, which offer strong contributions for enhancing the Raman intensity profiles. These simulated changes are linked to the localization of atomic displacements constrained either by the XC/YC or YC/XC unabrupt interfaces. We strongly feel that this study will encourage spectroscopists to perform Raman scattering measurements to check our theoretical conjectures. Full article

As enterprises look forward to new market share and supply chain opportunities, innovative strategies and sustainable manufacturing play important roles for micro-, small, and mid-sized enterprises worldwide. Sustainable manufacturing is one of the practices aimed towards deploying green energy initiatives to ease climate change, presenting three main pillars—economic, social, and environmental. The issue of how to reach sustainability goals within the sustainable manufacturing of pillars is a less-researched area. This paper’s main purpose and novelty is two-fold. First, it aims to provide a hierarchy of the green energy indicators and their measurements through a multi-criteria decision-making point of view to implement them as an alliance strategy towards sustainable manufacturing. Moreover, we aim to provide researchers and practitioners with a forecasting method to re-prioritize green energy indicators through a linearity factor model. The CODAS–Hamming–Mahalanobis method is used to obtain preference scores and rankings from a 50-item list. The resulting top 10 list shows that enterprises defined nine items within the economic pillar as more important and one item on the environmental pillar; items from the social pillar were less important. The implication for MSMEs within the manufacturing sector represents an opportunity to work with decision makers to deploy specific initiatives towards sustainable manufacturing, focused on profit and welfare while taking care of natural resources. In addition, we propose a continuous predictive analysis method, the linearity factor model, as a tool for new enterprises to seek a green energy hierarchy according to their individual needs. The resulting hierarchy using the predictive analysis model presented changes in the items’ order, but it remained within the same two sustainable manufacturing pillars: economic and environmental. Full article

Metal-mediated base pairing of DNA has been a topic of extensive research spanning over more than four decades. Precise positioning of a single metal ion by predetermining the DNA sequence, as well as improved conductivity offered by the ions, make these structures interesting candidates in the context of using DNA in nanotechnology. Here, we report the formation and characterization of conjugates of long (kilo bases) homoguanine DNA strands with silver ions. We demonstrate using atomic force microscopy (AFM) and scanning tunneling microscope (STM) that binding of silver ions leads to folding of homoguanine DNA strands in a “hairpin” fashion to yield double-helical, left-handed molecules composed of G-G base pairs each stabilized by a silver ion. Further folding of the DNA–silver conjugate yields linear molecules in which the two halves of the double helix are twisted one against the other in a right-handed fashion. Quantum mechanical calculations on smaller molecular models support the helical twist directions obtained by the high resolution STM analysis. These long guanine-based nanostructures bearing a chain of silver ions have not been synthesized and studied before and are likely to possess conductive properties that will make them attractive candidates for nanoelectronics. Full article

Thalassemia represents one of the most common genetic disorders worldwide, characterized by defects in hemoglobin synthesis. The affected individuals suffer from malfunctioning of one or more of the four globin genes, leading to chronic hemolytic anemia, an imbalance in the hemoglobin chain ratio, iron overload, and ineffective erythropoiesis. Despite the challenges posed by this condition, recent years have witnessed significant advancements in diagnosis, therapy, and transfusion support, significantly improving the prognosis for thalassemia patients. This research empirically evaluates the efficacy of models constructed using classification methods and explores the effectiveness of relevant features that are derived using various machine-learning techniques. Five feature selection approaches, namely Chi-Square (χ2), Exploratory Factor Score (EFS), tree-based Recursive Feature Elimination (RFE), gradient-based RFE, and Linear Regression Coefficient, were employed to determine the optimal feature set. Nine classifiers, namely K-Nearest Neighbors (KNN), Decision Trees (DT), Gradient Boosting Classifier (GBC), Linear Regression (LR), AdaBoost, Extreme Gradient Boosting (XGB), Random Forest (RF), Light Gradient Boosting Machine (LGBM), and Support Vector Machine (SVM), were utilized to evaluate the performance. The χ2 method achieved accuracy, registering 91.56% precision, 91.04% recall, and 92.65% f-score when aligned with the LR classifier. Moreover, the results underscore that amalgamating over-sampling with Synthetic Minority Over-sampling Technique (SMOTE), RFE, and 10-fold cross-validation markedly elevates the detection accuracy for αT patients. Notably, the Gradient Boosting Classifier (GBC) achieves 93.46% accuracy, 93.89% recall, and 92.72% F1 score. Full article

AlphaFold is a groundbreaking deep learning tool for protein structure prediction. It achieved remarkable accuracy in modeling many 3D structures while taking as the user input only the known amino acid sequence of proteins in question. Intriguingly though, in the early steps of each individual structure prediction procedure, AlphaFold does not respect topological barriers that, in real proteins, result from the reciprocal impermeability of polypeptide chains. This study aims to investigate how this failure to respect topological barriers affects AlphaFold predictions with respect to the topology of protein chains. We focus on such classes of proteins that, during their natural folding, reproducibly form the same knot type on their linear polypeptide chain, as revealed by their crystallographic analysis. We use partially artificial test constructs in which the mutual non-permeability of polypeptide chains should not permit the formation of complex composite knots during natural protein folding. We find that despite the formal impossibility that the protein folding process could produce such knots, AlphaFold predicts these proteins to form complex composite knots. Our study underscores the necessity for cautious interpretation and further validation of topological features in protein structures predicted by AlphaFold. Full article

Systematic results of lattice dynamical calculations are reported as a function of m and n for the novel (SiC)_m/(GeC)_n superlattices (SLs) by exploiting a modified linear-chain model and a realistic rigid-ion model (RIM). A bond polarizability method is employed to simulate the Raman intensity profiles (RIPs) for both the ideal and graded (SiC)_10-Δ/(Si_0.5Ge_0.5C)_Δ/(GeC)_10-Δ/(Si_0.5Ge_0.5C)_Δ SLs. We have adopted a virtual-crystal approximation for describing the interfacial layer thickness, Δ (≡0, 1, 2, and 3 monolayers (MLs)) by selecting equal proportions of SiC and GeC layers. Systematic variation of Δ has initiated considerable upward (downward) shifts of GeC-(SiC)-like Raman peaks in the optical phonon frequency regions. Our simulated results of RIPs in SiC/GeC SLs are agreed reasonably well with the recent analyses of Raman scattering data on graded short-period GaN/AlN SLs. Maximum changes in the calculated optical phonons (up to ±~47 cm⁻¹) with Δ = 3, are proven effective for causing accidental degeneracies and instigating localization of atomic displacements at the transition regions of the SLs. Strong Δ-dependent enhancement of Raman intensity features in SiC/GeC are considered valuable for validating the interfacial constituents in other technologically important heterostructures. By incorporating RIM, we have also studied the phonon dispersions [${{{\mathsf{\omega }}_{}}_{\mathrm{j}}^{\mathrm{S}\mathrm{L}}}_{}\left(\overrightarrow{\mathbf{q}}\right)$] of (SiC)_m/(GeC)_n SLs along the growth [001] as well as in-plane [100], [110] directions [i.e., perpendicular to the growth]. In the acoustic mode regions, our results of ${{{\mathsf{\omega }}_{}}_{\mathrm{j}}^{\mathrm{S}\mathrm{L}}}_{}\left(\overrightarrow{\mathbf{q}}\right)$ have confirmed the formation of mini-gaps at the zone center and zone edges while providing strong evidences of the anti-crossing and phonon confinements. Besides examining the angular dependence of zone-center optical modes, the results of phonon folding, confinement, and anisotropic behavior in (SiC)_m/(GeC)_n are compared and contrasted very well with the recent first-principles calculations of (GaN)_m/(AlN)_n strained layer SLs. Full article

The folded structures of proteins can be accurately predicted by deep learning algorithms from their amino-acid sequences. By contrast, in spite of decades of research studies, the prediction of folding pathways and the unfolded and misfolded states of proteins, which are intimately related to diseases, remains challenging. A two-state (folded/unfolded) description of protein folding dynamics hides the complexity of the unfolded and misfolded microstates. Here, we focus on the development of simplified order parameters to decipher the complexity of disordered protein structures. First, we show that any connected, undirected, and simple graph can be associated with a linear chain of atoms in thermal equilibrium. This analogy provides an interpretation of the usual topological descriptors of a graph, namely the Kirchhoff index and Randić resistance, in terms of effective force constants of a linear chain. We derive an exact relation between the Kirchhoff index and the average shortest path length for a linear graph and define the free energies of a graph using an Einstein model. Second, we represent the three-dimensional protein structures by connected, undirected, and simple graphs. As a proof of concept, we compute the topological descriptors and the graph free energies for an all-atom molecular dynamics trajectory of folding/unfolding events of the proteins Trp-cage and HP-36 and for the ensemble of experimental NMR models of Trp-cage. The present work shows that the local, nonlocal, and global force constants and free energies of a graph are promising tools to quantify unfolded/disordered protein states and folding/unfolding dynamics. In particular, they allow the detection of transient misfolded rigid states. Full article