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Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.
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http://dx.doi.org/10.1016/j.media.2022.102483 | DOI Listing |
Int J Cosmet Sci
September 2025
Smart Foods and Bioproducts, AgResearch, Lincoln, New Zealand.
Objective: This study investigated the locations of amino acid modifications within two major human hair keratins (Type I K31 and Type II K85) with probable implications for protein and hair structural component integrity. The particular focus was on cysteine modifications that disrupt intra-protein and inter-protein disulphide bonds.
Methods: Human hair was exposed to accelerated, sequential heat or UV treatments, simulating effects resulting from the use of heated styling tools and environmental exposure over a time frame approximating one year.
Med Phys
September 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
Background: Dual-energy computed tomography (DECT) enhances material differentiation by leveraging energy-dependent attenuation properties particularly for carbon ion therapy. Accurate estimation of tissue elemental composition via DECT can improve quantification of physical and biological doses.
Objective: This study proposed a novel machine-learning-based DECT (ML-DECT) method to predict the physical density and mass ratios of H, C, N, O, P, and Ca.
Adv Ther
September 2025
Teva Branded Pharmaceutical Products R&D LLC, West Chester, PA, USA.
Introduction: Pharmacokinetic differences between long-acting injectable antipsychotic (LAI) formulations, combined with a lack of clinical switch studies, contribute to clinician uncertainty when transitioning between LAIs. This analysis employed a population pharmacokinetic (popPK) modeling approach to characterize dosing conversions and switching strategies from intramuscular paliperidone palmitate once monthly (PP1m) to TV-46000, a long-acting subcutaneous formulation of risperidone, once monthly (q1m), with a secondary analysis of PP1m to TV-46000 every 2 months (q2m).
Methods: For PP1m and TV-46000, concentration-time profiles for paliperidone and TV-46000 total active moiety (TAM; risperidone + paliperidone) were simulated on the basis of published popPK models with virtual populations of 5000 patients.
Adv Sci (Weinh)
September 2025
Faculty of Engineering, University of Technology Sydney, P.O. Box 123, Broadway, Sydney, NSW, 2007, Australia.
Microalgae-bacteria symbiosis system is significant for sustainable and low-carbon wastewater treatment, with self-aggregation being key to its stable operation and effective pollutant removal. Cellular motility is the main driving force behind self-aggregation, crucial for symbiosis stability, but the characteristics and patterns involved still remain largely unexplored. Here, cellular movement dynamics into the microalgae-activated sludge model (ASM3) is incorporated, enabling synchronized simulation of metabolic activities and movement behaviors through physical and biochemical interactions in bioreactor systems.
View Article and Find Full Text PDFAnal Chim Acta
November 2025
Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, 10000, Viet Nam. Electronic address:
Background: Recent advancements in cancer therapeutics have catalyzed the development of noninvasive treatment modalities, including the utilization of fluorescent chemotherapeutic agents. These agents offer dual functionality, enabling targeted drug delivery, real-time tumor imaging, and personalized therapy monitoring. Such capabilities are instrumental in the progression toward more precise and effective cancer interventions.
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