Search Results (59)

HIV-1 protease (PR) is an essential enzyme in the viral life cycle and a primary target of antiretroviral therapies, particularly protease inhibitors (PIs). Understanding the dynamics of viral evolution and the factors governing the emergence or loss of resistance-associated mutations is critical for improving PI efficacy and managing drug resistance in HIV/AIDS treatment. In this study, we investigated the impact of three natural HIV-1 polymorphisms (T12A, L63Q, and H69N), whose prevalence varies depending on treatment status and viral subtype, on the structural stability and conformational dynamics of PR using molecular dynamics (MD) simulations. Three independent 500 ns MD simulations were performed for the native protease and each mutant system. Although none of the mutations disrupts the overall structural integrity of HIV-1 PR, they induce mutation-specific alterations in flexibility and residue interactions. In particular, T12A and H69N exhibit increased structural deviations, especially in the flap regions, along with enhanced conformational fluctuations. In contrast, the L63Q mutation shows a slight reduction in flap flexibility compared to both the native protease and the other mutants. Consistently, the fraction of time spent in open-flap conformations is higher for T12A and H69N and lower for L63Q relative to the native system. Moreover, mutations in the Fulcrum (T12A) and Cantilever (L63Q and H69N) regions do not disrupt the long-range network of correlated motions observed in the native protease, both inter- and intra-monomer, but instead increase the extent of correlated and anti-correlated motions in other regions of PR. Full article

Background: Gamma Knife radiosurgery (GKS) delivers highly conformal intracranial irradiation, yet clinical decision-making still relies predominantly on physical dose metrics that do not account for fractionation, dose rate, treatment time, or DNA repair. Classical radiobiological models—including the linear–quadratic (LQ) formula and the Jones–Hopewell single-session repair model—do not extend naturally to 3- and 5-fraction GKS. Meanwhile, growing evidence suggests that biologically effective dose (BED) may better capture radiosurgical response in selected pathologies. A unified, biologically grounded, multi-fraction GKS framework has been lacking. Methods: We developed AI-BED-Fx, the first multi-fraction extension of the Jones–Hopewell radiobiological model capable of computing fraction-resolved BED for 1-, 3-, and 5-fraction GKS. The framework incorporates α/β ratio, dual-component repair kinetics, isocentre geometry, beam-on–time structure, and lesion-specific biological parameters. Four synthetic pathology-specific cohorts—arteriovenous malformation (AVM), meningioma (MEN), vestibular schwannoma (VS), and brain metastasis (BM)—were generated using distinct radiobiological signatures. Machine-learning models were trained to quantify the predictive value of physical dose versus BED for local control or obliteration. Additional experiments included Bayesian estimation of α/β and a neural-network surrogate for fast BED prediction. An exploratory comparison with a 60-lesion clinical brain–metastasis dataset was performed to assess whether key trends observed in the synthetic BM cohort were consistent with real radiosurgical outcomes. Results: AI-BED-Fx produced realistic pathology-specific BED distributions (AVM 60–210 Gy_2.47; MEN 41–85 Gy_3.5; VS 46–68 Gy₃; BM 37–75 Gy₁₀) and biologically coherent dose–response relationships. Predictive modeling demonstrated strong pathology dependence. In AVM, the three models achieved AUCs of 0.921 (Model A), 0.922 (Model B), and 0.924 (Model C), with corresponding Brier scores of 0.054, 0.051, and 0.051, with BED-based models performing best. In meningioma, BED was the dominant predictor, with AUCs of 0.642 (Model A), 0.660 (Model B), and 0.661 (Model C) and Brier scores of 0.181, 0.177, and 0.179, respectively. In vestibular schwannoma, the narrow BED range resulted in minimal BED contribution, with AUCs of 0.812, 0.827, and 0.830 and Brier scores of 0.165, 0.160, and 0.162, with physical dose and tumor volume determining performance. In brain metastases, outcomes were driven primarily by volume and physical dose, with AUCs of 0.614, 0.630, and 0.629 and Brier scores of 0.254, 0.250, and 0.253, showing negligible improvement from BED. AI-BED-Fx also accurately recovered the true α/β from synthetic outcomes (posterior mean 2.54 vs. true 2.47), and a neural-network surrogate reproduced full radiobiological BED calculations with near-perfect fidelity (R² = 0.9991). Conclusions: AI-BED-Fx provides the first unified, biologically explicit framework for modeling single- and multi-fraction Gamma Knife radiosurgery. The findings show that the predictive usefulness of BED is pathology-specific rather than universal, and that radiobiological dose provides additional predictive value only when repair kinetics and dose–response biology support it. By integrating mechanistic radiobiology with machine learning, AI-BED-Fx establishes the conceptual and computational foundations for biologically adaptive, AI-guided radiosurgery, and cross-pathology comparison of treatment response. This work uses large radiobiologically grounded synthetic cohorts for methodological validation; limited real-patient data are included only for exploratory consistency checks, and full clinical validation is planned. Full article

Injection molding is widely used for plastic parts, but its performance is limited by the cooling stage, which dominates cycle time and affects dimensional stability and energy consumption. Conformal cooling channels, which can be manufactured using additive technologies, improve thermal efficiency but introduce a high-dimensional design problem. This work proposes an integrated methodology for optimizing injection molds with conformal cooling channels that combines parametric CAD (Computer-Aided Drawing), simulation, non-linear principal component analysis, artificial neural network, and multi-objective evolutionary optimization. The workflow is applied to a case study with five cooling layouts. An initial set of 36 metrics related to temperature gradients, warpage, shrinkage, and energy is reduced to a small number of latent objectives, simplifying the search space while preserving the main physical trends. Artificial neural networks surrogates accurately reproduce numerical results, enabling exploration of the design space at a fraction of the computational cost. The optimization yields diverse Pareto-optimal solutions that balance cycle time, dimensional stability, and energy consumption, assisting the design of more sustainable injection molds. Sensitivity analysis identifies mold temperature and channel position/diameter as key design levers. The proposed methodology reduces dependence on expensive simulations and is readily transferable to industrial mold design. Full article

Spine stereotactic radiotherapy and radiosurgery (SSRS) techniques, encompassing both fractionated stereotactic treatments and single-fraction radiosurgery, are widely used for the management of spinal metastases due to their ability to deliver highly conformal radiation while limiting dose to adjacent critical structures. Clinical outcomes following SSRS, including durable local control and acceptable toxicity, have been reported previously in multiple institutional series. In this manuscript, we describe the clinical workflow used to deliver SSRS at a high-volume academic center, with emphasis on the medical physics processes that support routine clinical practice. Key elements of the workflow include patient selection, treatment region-specific immobilization, CT and MRI-based simulation, treatment planning, patient-specific quality assurance, and image-guided treatment delivery. Rather than presenting new outcome data, this work provides a descriptive overview of how established SSRS techniques are integrated into day-to-day clinical care. Full article

This paper proposes a dual-fractional framework for stochastic differential equations (SDEs) that integrates conformable fractional calculus into both the system dynamics and the stochastic driving noise. For the first time, a conformable formulation of fractional noise is introduced, replacing the traditional Caputo-based representation. This modification eliminates singular kernel functions while preserving the fundamental properties of classical calculus, thereby simplifying both the analysis and numerical implementation. A complete analytical study is presented, rigorously addressing the convergence properties, deriving explicit error estimates, and establishing the numerical stability of the proposed scheme. The framework is realized through an enhanced conformable fractional discrete Temimi–Ansari method (CFDTAM), which accommodates distinct fractional orders for the system dynamics and the stochastic component. The stability and accuracy of the proposed scheme are validated through comparisons with the stochastic Runge–Kutta method (SRK) as implemented in Mathematica 12. Applications to benchmark models—including the fractional Langevin, Ginzburg–Landau, and Davis–Skodje systems—further demonstrate the robustness of the framework, especially in regimes where the Hurst exponent $\overline{\mathrm{Ӊ}}$ greater than 0.5. Overall, the results establish the method as a rigorous and efficient tool for modelling and analyzing stochastic fractional systems in finance, biophysics, and engineering. Full article

Fractional calculus provides powerful tools for modeling nonlocality, dissipative systems, and, when defined in the time representation, provides an interesting memory effect in mathematical physics. In this paper, we review four standard fractional approaches: the Riemann–Liouville, Gerasimov–Caputo, Grünwald–Letnikov, and Riesz formulations. We present their definitions, basic properties, Weyl–Marchaud, and physical interpretations. We also give a brief review of related operators that have been used recently in applications but have received less attention in the physical literature: the fractional Laplacian, conformable derivatives, and the Fractional Action-Like Variational Approach (FALVA) for variational principles with fractional action weights. Our emphasis is on how these operators are, and can be, applied in physical problems rather than on exhaustive coverage of the field. This review is intended as an accessible introduction for physicists working in diverse areas interested in fractional calculus and fractional methods. For deeper technical or domain-specific treatments, readers are encouraged to consult the works in the corresponding fields, for which the bibliography suggests a starting point. Full article

Stereotactic ablative radiotherapy (SABR) has revolutionized the management of patients with oligometastatic and selected primary cancers due to its ability to deliver highly conformal, high-dose radiation in few fractions with minimal toxicity. However, the biological heterogeneity among patients treated with SABR results in variable outcomes, emphasizing the need for predictive and prognostic biomarkers to guide patient selection and post-treatment management. This narrative review discusses the current landscape of biomarker development in the context of SABR across tumor types. Key classes include circulating tumor DNA (ctDNA), extracellular vesicles (EVs), radiomic features, and immunological markers. We highlight the role of each biomarker category in refining therapeutic approaches, their integration into ongoing clinical trials, and future directions for personalized SABR paradigms. Translating these promising biomarker strategies into clinical SABR workflows will require further standardisation, validation, and regulatory alignment. Full article

This work presents new results concerning weighted Hardy-type inequalities within the framework of delta conformable fractional integrals on arbitrary time scales. The proposed approach unifies the treatment of inequalities across continuous and discrete domains, enabling the derivation of original forms in both settings. The obtained results exhibit symmetry with classical inequalities, and several integral and discrete inequalities arise as special cases. These findings extend and generalize known results and enrich the theory of integral inequalities in fractional and dynamic calculus, providing a versatile platform for further developments in symmetric and weighted inequality analysis. Full article

In this work, we introduce the conformabletriple Laplace–Sumudu transform (CTLST), a novel integral transform designed to solve both linear and nonlinear conformable FPDEs. This new approach builds on the recent development of the triple Laplace–Sumudu transform and incorporates the conformable derivative to extend its applicability to fractional models. We first present the foundational definitions and key properties of the CTLST, followed by its application to a variety of two- and three-dimensional conformable FPDEs. The effectiveness of the proposed method is demonstrated through several examples, where exact and approximate solutions are derived, illustrative 3D plots are presented, and symmetry analysis is employed to verify the obtained results. The CTLST provides a promising analytical tool for tackling complex conformable FPDEs in mathematical physics and engineering. Full article

Objectives: This study aimed to assess the precision of dose delivery to the target in adaptive carbon ion radiotherapy (CIRT) for locally advanced non-small cell lung cancer (LA-NSCLC) in cumulative dosimetry. Methods: Forty-six patients who received CIRT were included (64 Gy[relative biological effectiveness, RBE] in 16 fractions) with treatment plan computed tomography (CT) and weekly CT scans. Offline adaptive radiotherapy (ART) was administered if the dose distribution significantly worsened. Daily doses were calculated from weekly CTs and integrated into plan CT scans using deformable image registration. The dosimetry parameters were compared between the as-scheduled plan and adaptive replan in patients receiving ART. Survival outcomes and toxicity were compared between the ART and non-ART groups. Results: ART was implemented for 27 patients in whom adaptive replans significantly increased the median V_98% of the clinical tumor volume from 96.5% to 98.1% and D_98% from 60.5 to 62.7 Gy(RBE) compared with the as-scheduled plans (p < 0.001). The conformity and uniformity of the dose distribution improved (p < 0.001), with no significant differences in the doses to normal tissues (lungs, heart, esophagus, and spinal cord) from the as-scheduled plans (p > 0.05). The ART and non-ART groups demonstrated comparable local control, progression-free survival, and overall survival (p > 0.05). No grade 3 or higher radiation-related toxicities were observed. Conclusions: ART enhanced target dose coverage while maintaining acceptable normal tissue exposure, supporting weekly CT monitoring integration during CIRT for the timely intervention for anatomical variations, ensuring precise dose delivery in LA-NSCLC. Full article

Radiotherapy (RT) has undergone transformative advancements since its inception over a century ago. This review highlights the most promising and impactful innovations shaping the current and future landscape of RT. Key technological advances include adaptive radiotherapy (ART), which tailors treatment to daily anatomical changes using integrated imaging and artificial intelligence (AI), and advanced image guidance systems, such as MR-LINACs, PET-LINACs, and surface-guided radiotherapy (SGRT), which enhance targeting precision and minimize collateral damage. AI and data science further support RT through automation, improved segmentation, dose prediction, and treatment planning. Emerging biological and targeted therapies, including boron neutron capture therapy (BNCT), radioimmunotherapy, and theranostics, represent the convergence of molecular targeting and radiotherapy, offering personalized treatment strategies. Particle therapies, notably proton and heavy ion RT, exploit the Bragg peak for precise tumor targeting while reducing normal tissue exposure. FLASH RT, delivering ultra-high dose rates, demonstrates promise in sparing normal tissue while maintaining tumor control, though clinical validation is ongoing. Spatially fractionated RT (SFRT), stereotactic techniques and brachytherapy are evolving to treat challenging tumor types with enhanced conformality and efficacy. Innovations such as 3D printing, Auger therapy, and hyperthermia are also contributing to individualized and site-specific solutions. Across these modalities, the integration of imaging, AI, and novel physics and biology-driven approaches is redefining the possibilities of cancer treatment. This review underscores the multidisciplinary and translational nature of modern RT, where physics, engineering, biology, and informatics intersect to improve patient outcomes. While many approaches are in various stages of clinical adoption and investigation, their collective impact promises to redefine the therapeutic boundaries of radiation oncology in the coming decade. Full article

Currently, advanced RT techniques such as VMAT and HT are being developed to optimize tumor coverage while minimizing radiation exposure to the surrounding organs that are at risk. Despite their growing clinical use, comparative studies evaluating the dosimetric and radiobiological effects of these modalities remain limited. In this study, A549, HeLa, and HepG2 cells were exposed to a single 2 Gy dose, using three RT techniques (3D-CRT, dual arc VMAT, and HT). Treatment plans were generated using a water phantom to ensure consistent target coverage and comparable dosimetric parameters across the techniques. Multiple radiobiological endpoints were assessed to evaluate the cellular responses. Although all three techniques yielded similar dosimetric parameters without statistically significant differences, the biological responses varied among the cell lines. Notably, VMAT and HT demonstrated superior tumor cell suppression compared to 3D-CRT. This was likely due to their enhanced dose conformity and modulation precision, which potentially led to improved tumor cell killing. These findings highlight the importance of integrating radiobiological assessments with physical dose metrics to inform the clinical application of advanced RT technologies. However, this study had several limitations. The use of a single radiation dose limited its clinical relevance, and the immediate post-irradiation assessments may not have captured delayed biological responses. Additionally, the small number of replicates may have reduced the study’s statistical power. Future studies incorporating dose fractionation schemes, time course analyses, and larger sample sizes are warranted to better simulate clinical conditions and further elucidate the radiobiological effects of advanced RT techniques. Full article

This work investigates the effects of gamma irradiation (0.1–10 kGy) on four Italian wheat matrices, such as durum, conventional soft, integrated soft, and biological soft wheat, by coupling Raman, FTIR-ATR and EPR spectroscopies to provide complementary insights into the structural, conformational, and radical-based transformations occurring in starch, the primary polysaccharide in wheat. As a general trend, gamma irradiation up to 10 kGy does not induce drastic degradation or depolymerization of wheat components. However, deeper investigations reveal that wheat composition is crucial in modulating the effects of gamma irradiation on structural and conformational rearrangements of starch units. Raman and FTIR-ATR spectroscopy analyses showed an increase in random coil fractions, with the most significant changes observed in durum wheat, plausibly attributed to its higher protein content. EPR analyses confirmed a dose-dependent increase in free radicals, with different recombination kinetics between wheat types influenced by their intrinsic composition and molecular organization. The proposed spectroscopic approaches allow for rapid and non-destructive analyses of molecular structure, chemical composition, and free radical content in irradiated wheat matrices with minimal sample preparation. These approaches can be extended in the development of screening methods for a wide range of polysaccharides in a variety of crops. Full article

In this study, the extended finite element method (XFEM) was integrated into the generalized multiscale finite element method with global–local enrichment (GFEM^gl) to simulate 2D heat conduction in highly heterogeneous materials (i.e., matrixes with numerous randomly distributed inclusions or voids). This multiscale scheme was used to evaluate the effective thermal conductivity (ETC) of composites through simulation based on a representative volume element (RVE). In the proposed method, global–local enrichments are numerically constructed and incorporated into the global approximation in a hierarchical manner to integrate microstructure information into the macroscale problem. The XFEM is employed on a microscale mesh to avoid using a conformal mesh. RVEs containing numerous inclusions or voids with different volume fractions were numerically simulated using the proposed multiscale method, and the obtained results were compared with those of the standard single-scale XFEM and analytical models. The simulation results indicated that the proposed method has excellent accuracy and considerably lower computational cost. Full article

This paper investigates the oscillatory behavior of a class of mixed fractional-order nonlinear differential equations incorporating both the Liouville right-sided and conformable fractional derivatives. Symmetry plays a key role in understanding the oscillatory behavior of these systems. The motivation behind this study arises from the need for a more generalized framework to analyze oscillatory behavior in fractional differential equations, bridging the gap in the existing literature. By employing the generalized Riccati technique and the integral averaging method, we establish new oscillation criteria that extend and refine previous results. Illustrative examples are provided to validate the theoretical findings and highlight the effectiveness of the proposed methods. Full article