Search Results (36)

Radiation is often used as the primary treatment for a range of cancers. Nonetheless, its ability to trigger secondary tumors has emerged as a significant issue. Therefore, gaining insight into and predicting radiation-induced secondary cancers is essential for enhancing the long-term prognosis of cancer survivors. Background and Objectives: Previous studies have identified several factors; however, research on the use of serum-based inflammatory markers as prognostic tools for predicting radiation-induced secondary malignancies is limited. Investigating the potential of serum-based inflammation prognostic scores could provide a minimally invasive and affordable method for the early prediction of secondary malignancies. Methods: We retrospectively analyzed a patient cohort with radiation-induced secondary malignancy from the electronic database MIMIC-IV to investigate whether a serum-based inflammatory marker score can serve as a predictive tool. Results: This study seeks not only to assess the efficacy of the risk score, but also to develop a clinical utility tool nomogram for predicting the occurrence of radiation-induced secondary cancers. A RISM of 4.28% was observed in a cohort from the MIMIC-IV database using SIRI-RT as a risk index, with the Charlson comorbidity index, chemotherapy, and creatinine levels as significant confounding risk factors. Conclusions: Our study suggests that elevated serum-based inflammation prognostic scores and the nomogram developed herein can be used to predict a greater likelihood of developing secondary malignancies following radiation therapy. Full article

The utilization of dodecaborate boron clusters, [B₁₂X₁₂]²⁻ (X = Cl, Br, or I), as membrane carriers has been demonstrated recently, and their activity is known to be due to their superchaotropic nature. In this work, the mono-alkylation of [B₁₂Br₁₁OH]²⁻ to functionalize it with an aliphatic spacer was developed with a view to expanding the known chemical space of membrane carriers based on [B₁₂Br₁₂]²⁻. A new and improved facile route for the preparation of [B₁₂Br₁₁OH]²⁻, which is an important precursor to other [B₁₂Br₁₁OR]²⁻ species, is reported. Various alkoxylated [B₁₂Br₁₁O(CH₂)₅Z]²⁻ (Z = OH, N(CO)₂C₆H₄, CN and N₃) derivatives were prepared via a divergent synthesis based on [B₁₂Br₁₁O(CH₂)₅Br]²⁻. One of the newly synthesized compounds was utilized as a membrane carrier, and its impact on cell viability was examined. Full article

The modification of carborane anion monocarba-closo-dodecaborate (1) with perfluoroalkyl groups enhances its solubility in fluorinated ethers. This novel approach achieves a degree of solubility that is unattainable by using traditional lipophilic modifications or boro–vertex functionalizations of 1. A spectroscopic analysis in combination with DFT calculations confirmed that these new anions retain their weakly coordinating nature and exhibit moderate chemical stability. Full article

Anionic boron clusters, such as [B₁₂X₁₂]²⁻ (X = Cl, Br, I), have attracted attention in pharmaceuticals due to their unique superchaotropic properties. In particular, [B₁₂Br₁₂]²⁻ (1) has demonstrated strong interactions with biomolecules, facilitating cargo translocation across plasma membranes. In this study, we investigated the effect of covalently attaching chlorinated dodecaborate moiety [B₁₂Cl₁₁O-]²⁻ to 6-carboxyfluorescein (6-FAM) (3) via a PEG3 linker to form conjugate (4). We compared the membrane permeability of this covalent conjugate with that of non-covalent interactions between 6-FAM (3) and [B₁₂Cl₁₂]²⁻ (2). Live-cell fluorescence imaging revealed that the covalent conjugate exhibited enhanced membrane permeability and water solubility while maintaining low cytotoxicity. These results highlight the potential of covalent conjugation with boron clusters for improving the cellular uptake of hydrophilic cargos. Full article

Endolysins of bacteriophages, which degrade the bacterial cell wall peptidoglycan, are applicable in many industries to deal with biofilms and bacterial infections. While multi-domain endolysins have both enzymatically active and cell wall-binding domains, single-domain endolysins consist only of an enzymatically active domain, and their mechanism of peptidoglycan binding remains unexplored, for this is a challenging task experimentally. This research aimed to explore the binding mechanism of endolysins using computational approaches, namely molecular docking and bioinformatical tools, and analyze the performance of these approaches. The docking engine Autodock Vina 1.1.2 and the 3D-RISM module of AmberTools 24 were studied in the current work and used for receptor–ligand affinity and binding energy calculations, respectively. Two possible mechanisms of single-domain endolysin–ligand binding were predicted by Autodock Vina and verified by the 3D-RISM. As a result, the previously obtained experimental results on peptidoglycan binding of the isolated gamma phage endolysin PlyG enzymatically active domain were supported by molecular docking. Both methods predicted that single-domain endolysins are able to bind peptidoglycan, with Autodock Vina being able to give accurate numerical estimates of protein–ligand affinities and 3D-RISM providing comparative values. Full article

In this paper, a robust bumpless transfer control scheme for tracking control is proposed to avoid large jumps in the control signals for a switched system (SS) with unmatched uncertainty and disturbance. The robust bumpless controller comprises a robust linear feedback control (RLFC) and a continuous sliding mode control (CSMC) based on the given robust integral sliding mode (RISM). The RLFC meets the requirement of bumpless indices, and the CSMC suppresses the unmatched uncertainty and disturbance. First, the RLFC design is proposed, and the linear feedback coefficients satisfy the bumpless indices, despite the uncertainty and disturbance. Then, a RISM surface design is proposed, in which the uncertain SS satisfies the given H-infinity robust performance index, and can resist the unmatched uncertainty. Consequently, the CSMC ensures that the RISM surface can be reached in finite time from the initial time instant. By composing the CSMC with the RLFC, the control scheme achieves the robust trajectory tracking and the suppression of the control signal bumps during switching. Finally, the proposed robust bumpless transfer control scheme was applied to the different examples, and the simulation results verified its effectiveness. Full article

Understanding the interactions between solutes and solvents is vital in many areas of the chemical sciences. Solvation free energy (SFE) is an important thermodynamic property in characterising molecular solvation and so accurate prediction of this property is sought after. The One-Dimensional Reference Interaction Site Model (RISM) is a well-established method for modelling solvation, but it is known to yield large errors in the calculation of SFE. In this work, we show that a single machine learning free energy functional for RISM can accurately model solvation thermodynamics in multiple solvents. A convolutional neural network is trained on solvation free energy density functions calculated by RISM for small organic molecules in approximately 100 different solvent systems. We achieve an average RMSE of 1.41 kcal/mol and an ${\mathrm{R}}^2$ of 0.89 across all solvent systems. We also compare the performance for the most and least commonly represented solvents and show that higher accuracy is generally seen with higher volumes of data, with RMSE values of 0.69–1.29 kcal/mol and ${\mathrm{R}}^2$ values of 0.78–0.97 for solvents with more than 50 data points. We have shown that machine learning can greatly improve solvation free energy predictions in RISM, while demonstrating that the methodology is generalisable across solvent systems. This represents a significant step towards a universal machine learning SFE functional for RISM. Full article

Viruses are the most numerous biological form living in any ecosystem. Viral diseases affect not only people but also representatives of fauna and flora. The latest pandemic has shown how important it is for the scientific community to respond quickly to the challenge, including critically assessing the viral threat and developing appropriate measures to counter this threat. Scientists around the world are making enormous efforts to solve these problems. In silico methods, which allow quite rapid obtention of, in many cases, accurate information in this field, are effective tools for the description of various aspects of virus activity, including virus–host cell interactions, and, thus, can provide a molecular insight into the mechanism of virus functioning. The three-dimensional reference interaction site model (3D-RISM) seems to be one of the most effective and inexpensive methods to compute hydrated viruses, since the method allows us to provide efficient calculations of hydrated viruses, remaining all molecular details of the liquid environment and virus structure. The pandemic challenge has resulted in a fast increase in the number of 3D-RISM calculations devoted to hydrated viruses. To provide readers with a summary of this literature, we present a systematic overview of the 3D-RISM calculations, covering the period since 2010. We discuss various biophysical aspects of the 3D-RISM results and demonstrate capabilities, limitations, achievements, and prospects of the method using examples of viruses such as influenza, hepatitis, and SARS-CoV-2 viruses. Full article

To meet the United Nations and European Union goals of reducing road crash fatalities and injuries, it is also relevant to address the negative externalities due to mega-events on the road network and the local communities, to assess the safety of the road network involved, and to implement appropriate measures for different road environments. Despite their relevance, the literature often overlooks social costs and risks associated with mega-events. This study presents an operating framework for rapidly assessing the safety of the Milano–Cortina 2026—“Via Olimpica” road—which will host a significant proportion of the traffic during the Winter Olympic Games in 2026. The framework proposes a simplified Road Infrastructure Safety Management (RISM) to address the unique challenges posed by the limited time available for screening and implementation by local authorities. The framework integrates four data sources and follows a seven-step procedure. It provides recommendations for improving road safety by identifying critical road sections and blackspots. Road authorities, practitioners, and public administrations may all benefit from the framework, as it makes it easier to prioritise safety improvements within time constraints. Full article

The theory of fluids is used to modify the integral equations of the reference interaction site model (RISM) approximation. Its applicability to the study of biomolecules solvation is evaluated. Unlike traditional RISM applications, the new integral equation contains an intramolecular correlation matrix that only needs to be calculated once. This allows us to bypass the effort of repeatedly solving RISM equations and the time-consuming averaging of values obtained for each time point of a molecular trajectory. The new approach allows for the assessment of the conformational transience of dissolved molecules while taking into account the effects of solvation. The free energy of oxytocin, which is a peptide hormone, as well as self-assembled ionic peptide complexes calculated using both the traditional RISM and the new RISM with average matrix (RISM-AM) approach are estimated. The free energy of oxytocin calculated using RISM-AM shows that the statistical error does not exceed the error obtained by standard averaging of solutions in the RISM equation. Despite the somewhat ambiguous results obtained for ionic peptide self-assembly using RISM-AM with Lennard–Jones repulsion correction, this method can still be considered applicable for fast molecular dynamics analysis. Since the required computational power can be reduced by at least two orders of magnitude, the medium-matrix RISM is indeed a highly applicable tool for studying macromolecular conformations as well as corresponding solvation effects. Full article

In 2012, Kim and Hirata derived two generalized Langevin equations (GLEs) for a biomolecule in water, one for the structural fluctuation of the biomolecule and the other for the density fluctuation of water, by projecting all the mechanical variables in phase space onto the two dynamic variables: the structural fluctuation defined by the displacement of atoms from their equilibrium positions, and the solvent density fluctuation. The equation has an expression similar to the classical Langevin equation (CLE) for a harmonic oscillator, possessing terms corresponding to the restoring force proportional to the structural fluctuation, as well as the frictional and random forces. However, there is a distinct difference between the two expressions that touches on the essential physics of the structural fluctuation, that is, the force constant, or Hessian, in the restoring force. In the CLE, this is given by the second derivative of the potential energy among atoms in a protein. So, the quadratic nature or the harmonicity is only valid at the minimum of the potential surface. On the contrary, the linearity of the restoring force in the GLE originates from the projection of the water’s degrees of freedom onto the protein’s degrees of freedom. Taking this into consideration, Kim and Hirata proposed an ansatz for the Hessian matrix. The ansatz is used to equate the Hessian matrix with the second derivative of the free-energy surface or the potential of the mean force of a protein in water, defined by the sum of the potential energy among atoms in a protein and the solvation free energy. Since the free energy can be calculated from the molecular mechanics and the RISM/3D-RISM theory, one can perform an analysis similar to the normal mode analysis (NMA) just by diagonalizing the Hessian matrix of the free energy. This method is referred to as the Generalized Langevin Mode Analysis (GLMA). This theory may be realized to explore a variety of biophysical processes, including protein folding, spectroscopy, and chemical reactions. The present article is devoted to reviewing the development of this theory, and to providing perspective in exploring life phenomena. Full article

Herein, we report the nanofiltration performance of poly(p-xylylene) thin films with imidazole side chains that were deposited onto commercial polyethersulfone ultrafiltration membranes using a chemical vapor deposition process. The resulting thin films with a few tens of nanometers exhibited water permeation under a pressure difference of 0.5 MPa and selectively rejected water-soluble organic dyes based on their molecular sizes. Additionally, thin flaky ZIF-L crystals (Zn(mim)₂·(Hmim)_1/2·(H₂O)_3/2) (Hmim = 2-methylimidazole) formed on the surface of imidazole-containing poly(p-xylylene) films, and the composite films demonstrated the ability to adsorb methylene blue molecules within the cavities of ZIF-L. Full article

3D-RISM-KH molecular solvation theory based on statistical mechanics has been an engine of the multiscale methods framework, which also includes molecular simulation techniques. Its applications range from the solvation energy of small molecules to the phase behavior of polymers and biomolecules. Molecular solvation theory predicts and explains the molecular mechanisms and functioning of a variety of chemical and biomolecular systems. This includes the self-assembly and conformational stability of synthetic organic rosette nanotubes (RNTs), the aggregation of peptides and proteins related to neurodegeneration, the binding of ligands to proteins, and the solvation properties of biomolecules related to their functions. The replica RISM-KH-VM molecular solvation theory predicts and explains the structure, thermodynamics, and electrochemistry of electrolyte solutions sorbed in nanoporous carbon supercapacitor electrodes, and is part of recent research and development efforts. A new quasidynamics protocol couples multiple time step molecular dynamics (MTS-MD) stabilized with an optimized isokinetic Nosé–Hoover (OIN) thermostat driven by 3D-RISM-KH mean solvation forces at gigantic outer time steps of picoseconds, which are extrapolated forward at short inner time steps of femtoseconds with generalized solvation force extrapolation (GSFE). The OIN/3D-RISM-KH/GSFE quasidynamics is implemented in the Amber Molecular Dynamics package. It is validated on miniprotein 1L2Y and protein G in ambient aqueous solution, and shows the rate of sampling 150 times faster than in standard MD simulations on these biomolecules in explicit water. The self-consistent field version of Kohn–Sham DFT in 3D-RISM-KH mean solvation forces is implemented in the Amsterdam Density Functional (ADF) package. Its applications range from solvation thermochemistry, conformational equilibria, and photochemistry to activation barriers of different nanosystems in solutions and ionic liquids. Full article

This paper addresses the issue of external unknown environmental interference affecting the trajectory tracking performance and driving stability of autonomous vehicles. This seriously impacts the performance and stability of the vehicle while driving. In order to provide precise, reliable, and safe trajectory tracking performance for autonomous vehicles, this paper proposes a recursive integral terminal sliding mode control (RITSMC) method. The proposed RITSMC combines the advantages of recursive integral sliding mode (RISM), terminal sliding mode (TSM), and adaptive algorithms, and can effectively achieve precise trajectory tracking and driving stability of autonomous vehicles. Furthermore, compared with traditional methods, an adaptive algorithm is introduced on the recursive sliding surface to enable real-time adaptation of the control parameters of the recursive controller, further improving the trajectory tracking accuracy and driving stability of autonomous vehicles. The stability of this control system is demonstrated by using a Lyapunov function. Finally, multiple simulation tests were conducted on different lane speeds on both wet and dry asphalt road sections. By comparing the simulation results, it was found that the proposed RITSMC exhibits excellent performance in terms of the precision of tracking trajectories and the stability of driving, in contrast to traditional sliding mode controllers (SMC) and integral terminal sliding mode controllers (ITSMC). Full article

Hydration free energies of small molecules are commonly used as benchmarks for solvation models. However, errors in predicting hydration free energies are partially due to the force fields used and not just the solvation model. To address this, we have used the 3D reference interaction site model (3D-RISM) of molecular solvation and existing benchmark explicit solvent calculations with a simple element count correction (ECC) to identify problems with the non-bond parameters in the general AMBER force field (GAFF). 3D-RISM was used to calculate hydration free energies of all 642 molecules in the FreeSolv database, and a partial molar volume correction (PMVC), ECC, and their combination (PMVECC) were applied to the results. The PMVECC produced a mean unsigned error of $1.01\pm 0.04\mathrm{kcal}/\mathrm{mol}$ and root mean squared error of $1.44\pm 0.07\mathrm{kcal}/\mathrm{mol}$, better than the benchmark explicit solvent calculations from FreeSolv, and required less than 15 s of computing time per molecule on a single CPU core. Importantly, parameters for PMVECC showed systematic errors for molecules containing Cl, Br, I, and P. Applying ECC to the explicit solvent hydration free energies found the same systematic errors. The results strongly suggest that some small adjustments to the Lennard–Jones parameters for GAFF will lead to improved hydration free energy calculations for all solvent models. Full article