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Long‐lasting radioluminescence scintillators have recently attracted substantial attention from both research and industrial communities, primarily due to their distinctive capabilities of converting and storing X‐ray energy. However, determination of energy‐conversion kinetics in these nanocrystals remains unexplored. Here we present a strategy to probe and unveil energy‐funneling kinetics in NaLuF4:Mn2+/Gd3+ nanocrystal sublattices through Gd3+‐driven microenvironment engineering and Mn2+‐mediated radioluminescence profiling. Our photophysical studies reveal effective control of energy‐funneling kinetics and demonstrate the tunability of electron trap depth ranging from 0.66 to 0.96 eV, with the corresponding trap density varying between 2.38×105 and 1.34×107 cm−3. This enables controlled release of captured electrons over durations spanning from seconds to 30 days. It allows tailorable emission wavelength within the range of 520–580 nm and fine‐tuning of thermally‐stimulated temperature between 313–403 K. We further utilize these scintillators to fabricate high‐density, large‐area scintillation screens that exhibit a 6‐fold improvement in X‐ray sensitivity, 22 lp/mm high‐resolution X‐ray imaging, and a 30‐day‐long optical memory. This enables high‐contrast imaging of injured mice through fast thermally‐stimulated radioluminescence readout. These findings offer new insights into the correlation of radioluminescence dynamics with energy‐funneling kinetics, thereby contributing to the advancement of high‐energy nanophotonic applications. [ABSTRACT FROM AUTHOR]

Background: C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20–30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding. Results: Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes. Conclusions: Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera. [ABSTRACT FROM AUTHOR]

We numerically investigate the forced synchronization of the self-excited flow behind a plunging airfoil in ground effect at a Reynolds number of Re = 1000. On varying the plunging amplitude and frequency, we find a rich array of nonlinear dynamics, such as a period-1 limit cycle due to natural vortex shedding as well as two-frequency quasiperiodicity on a torus attractor ( T 2 ). For certain non-resonant plunging frequencies without a ground surface, we find that low-dimensional chaos emerges via the Ruelle–Takens–Newhouse route. However, we find that the chaos can be suppressed by introducing a ground surface, inducing a direct transition from T 2 quasiperiodicity to 1:1 phase locking as the plunging amplitude rises over the boundaries of the Arnold tongue. Apart from suppressing chaos, the ground surface also causes the lift and drag coefficients to become less sensitive to the plunging motion itself. Knowledge of the critical plunging conditions required for forced synchronization and chaos could be useful in various engineering applications, such as the design of pico air vehicles. [ABSTRACT FROM AUTHOR]

Objective. Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm). Approach. SPArc-particle swarm divided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated. Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarm compared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%–26% reduction of the beam delivery time (BDT) in the SPArc treatment. Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation. [ABSTRACT FROM AUTHOR]

Background Purpose Methods and Materials Results Conclusion Intensity‐modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential.This study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint.The study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO‐NEW) was compared with plans that only consider nominal optimization using CTV (NMO‐CTV) without handling uncertainties and PTV (NMO‐PTV) to handle the uncertainties, as well as with conventional robust‐optimized plans (RBO‐CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root‐mean‐square dose (RMSD)–volume histogram curves (AUC) and dose–volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency.The results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO‐NEW showing superior computational efficiency and plan quality compared to RBO‐CONV. Specifically, statistical analysis results indicated that RBO‐NEW was able to reduce the computational time from 389.70±207.40$389.70\pm 207.40$ to 228.60±123.67$228.60\pm 123.67$ s (p<0.01$p<0.01$) and reduce the mean organ‐at‐risk (OAR) dose from 9.38±12.80$9.38\pm 12.80$% of the prescription dose to 9.07±12.39$9.07\pm 12.39$% of the prescription dose (p<0.05$p<0.05$) compared to RBO‐CONV.This study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability. [ABSTRACT FROM AUTHOR]

Objective. Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm). Approach. SPArc-particle swarm divided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated. Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarm compared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%–26% reduction of the beam delivery time (BDT) in the SPArc treatment. Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation. [ABSTRACT FROM AUTHOR]

Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10 -8 ) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Long-lasting radioluminescence scintillators have recently attracted substantial attention from both research and industrial communities, primarily due to their distinctive capabilities of converting and storing X-ray energy. However, determination of energy-conversion kinetics in these nanocrystals remains unexplored. Here we present a strategy to probe and unveil energy-funneling kinetics in NaLuF 4 :Mn 2+ /Gd 3+ nanocrystal sublattices through Gd 3+ -driven microenvironment engineering and Mn 2+ -mediated radioluminescence profiling. Our photophysical studies reveal effective control of energy-funneling kinetics and demonstrate the tunability of electron trap depth ranging from 0.66 to 0.96 eV, with the corresponding trap density varying between 2.38×10 5 and 1.34×10 7  cm -3 . This enables controlled release of captured electrons over durations spanning from seconds to 30 days. It allows tailorable emission wavelength within the range of 520-580 nm and fine-tuning of thermally-stimulated temperature between 313-403 K. We further utilize these scintillators to fabricate high-density, large-area scintillation screens that exhibit a 6-fold improvement in X-ray sensitivity, 22 lp/mm high-resolution X-ray imaging, and a 30-day-long optical memory. This enables high-contrast imaging of injured mice through fast thermally-stimulated radioluminescence readout. These findings offer new insights into the correlation of radioluminescence dynamics with energy-funneling kinetics, thereby contributing to the advancement of high-energy nanophotonic applications., (© 2024 Wiley-VCH GmbH.)

Background/aim: The prognosis of ovarian cancer (OC) patients is especially poor for patients with chemotherapy resistance. Anlotinib, a novel multi-targeted tyrosine kinase inhibitor, has shown encouraging clinical efficacy in several tumor types. The aim of the present study was to examine the inhibitory efficacy and mechanism of anlotinib on the proliferation and chemosensitivity of OC cells., Materials and Methods: The inhibitory effects of Anlotinib on SKOV3 and OVCAR3 OC cells were examined using CCK-8 cell-viability, colony-formation, flow-cytometry, transwell-migration and sphere-formation assays. A xenograft mouse model was used for in vivo studies. RT-qPCR and western blotting were used to detect gene expression., Results: Molecular targets of anlotinib were elevated in OC patient tumors. Anlotinib significantly inhibited ovarian cancer cell proliferation and migration in vitro. Anlotinib enhanced the sensitivity of ovarian cancer cells to cisplatinum both in vitro and in vivo. Anlotinib suppressed sphere formation and the stemness phenotype of OC cells by inhibiting NOTCH2 expression., Conclusion: Anlotinib inhibits ovarian cancer and enhances cisplatinum sensitivity, suggesting its future clinical promise., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10 -8 ). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine ., (© 2024. The Author(s).)