Thanks to the exceptional materials properties of silica aerogels, this fascinating highly porous material has found high-performance and real-life applications in various modern industries. However, ...a requirement for a broadening of these applications is based on the further improvement of the aerogel properties, especially with regard to mechanical strength and postsynthesis processability with minimum compromise to the other physical properties. Here, we report an entirely novel, simple, and aqueous-based synthesis approach to prepare mechanically robust aerogel hybrids by cogelation of silk fibroin (SF) biopolymer extracted from silkworm cocoons. The synthesis is based on sequential processes of acid catalyzed (physical) cross-linking of the SF biopolymer and simultaneous polycondensation of tetramethylorthosilicate (TMOS) in the presence of 5-(trimethoxysilyl)pentanoic acid (TMSPA) as a coupling agent and subsequent solvent exchange and supercritical drying. Extensive characterization by solid-state 1H NMR, 29Si NMR, and 2D 1H–29Si heteronuclear correlation (HETCOR) MAS NMR spectroscopy as well as various microscopic techniques (SEM, TEM) and mechanical assessment confirmed the molecular-level homogeneity of the hybrid nanostructure. The developed silica–SF aerogel hybrids contained an improved set of material properties, such as low density (ρb,average = 0.11–0.2 g cm–3), high porosity (∼90%), high specific surface area (∼400–800 m2 g–1), and excellent flexibility in compression (up to 80% of strain) with three orders of magnitude improvement in the Young’s modulus over that of pristine silica aerogels. In addition, the silica–SF hybrid aerogels are fire retardant and demonstrated excellent thermal insulation performance with thermal conductivities (λ) of 0.033–0.039 W m–1 K–1. As a further advantage, the formulated hybrid silica–SF aerogel showed an excellent printability in the wet state using a microextrusion-based 3D printing approach. The printed structures had comparable properties to their monolith counterparts, improving postsynthesis processing or shaping of the silica aerogels significantly. Finally, the hybrid silica–SF aerogels reported here represent significant progress for a mechanically customized and robust aerogel for multipurpose applications, namely, as a customized thermal insulation material or as a dual porous open-cell biomaterial used in regenerative medicine.
Anisotropy is a key factor regarding mechanical or transport properties and thus the functionality of porous materials. However, the ability to deliberately design the pore structure of ...hierarchically organized porous networks toward anisotropic features is limited. Here, we report two straightforward routes toward hierarchically structured porous carbon monoliths with an anisotropic alignment of the microstructure on the level of macro- and mesopores. One approach is based on nanocasting (NC) of carbon precursors into hierarchical and anisotropic silica hard templates. The second route, a direct synthesis approach based on soft templating (ST), makes use of the flexibility of hierarchically structured resorcinol–formaldehyde gels, which are compressed and simultaneously carbonized in the deformed state. We present structural data of both types of carbon monoliths obtained by electron microscopy, nitrogen adsorption analysis, and SAXS measurements. In addition, we demonstrate how the degree of anisotropy can easily be controlled via the ST route.
The goal of this work is to understand adsorption-induced deformation of hierarchically structured porous silica exhibiting well-defined cylindrical mesopores. For this purpose, we performed an in ...situ dilatometry measurement on a calcined and sintered monolithic silica sample during the adsorption of N2 at 77 K. To analyze the experimental data, we extended the adsorption stress model to account for the anisotropy of cylindrical mesopores, i.e., we explicitly derived the adsorption stress tensor components in the axial and radial direction of the pore. For quantitative predictions of stresses and strains, we applied the theoretical framework of Derjaguin, Broekhoff, and de Boer for adsorption in mesopores and two mechanical models of silica rods with axially aligned pore channels: an idealized cylindrical tube model, which can be described analytically, and an ordered hexagonal array of cylindrical mesopores, whose mechanical response to adsorption stress was evaluated by 3D finite element calculations. The adsorption-induced strains predicted by both mechanical models are in good quantitative agreement making the cylindrical tube the preferable model for adsorption-induced strains due to its simple analytical nature. The theoretical results are compared with the in situ dilatometry data on a hierarchically structured silica monolith composed by a network of mesoporous struts of MCM-41 type morphology. Analyzing the experimental adsorption and strain data with the proposed theoretical framework, we find the adsorption-induced deformation of the monolithic sample being reasonably described by a superposition of axial and radial strains calculated on the mesopore level. The structural and mechanical parameters obtained from the model are in good agreement with expectations from independent measurements and literature, respectively.
Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance ...imaging (MRI) images are used for tumor delineation. Therefore, MRI and CT need to be registered, which is an error prone process. The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data.
A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery.
Compared to CT, MRI offers a superior soft tissue contrast without additional radiation dose to the patients. However, up to now, even though the dosimetrical equivalence of CT and sCT has been shown in several retrospective studies, MRI-only workflows have still not been widely adopted. The present study aims to determine feasibility and safety of deep learning-based MRI-only radiotherapy in a holistic manner incorporating the whole radiotherapy workflow.
NCT06106997.
Homotypic or heterotypic internalization of another, either living or necrotic cell is currently in the center of research interest. The active invasion of a living cell called entosis and ...cannibalism of cells by rapidly proliferating cancers are prominent examples. Additionally, normal healthy tissue cells are capable of non-professional phagocytosis. This project studied the relationship between non-professional phagocytosis, individual proliferation and cell cycle progression. Three mesenchymal and two epithelial normal tissue cell lines were studied for homotypic non-professional phagocytosis. Homotypic dead cells were co-incubated with adherent growing living cell layers. Living cells were synchronized by mitotic shake-off as well as Aphidicolin-treatment and phagocytotic activity was analyzed by immunostaining. Cell cycle phases were evaluated by flow cytometry. Mesenchymal and epithelial normal tissue cells were capable of internalizing dead cells. Epithelial cells had much higher non-professional phagocytotic rates than mesenchymal cells. Cells throughout the entire cell cycle were able to phagocytose. The phagocytotic rate significantly increased with progressing cell cycle phases. Mitotic cells regularly phagocytosed dead cells, this was verified by Nocodazole and Colcemid treatment. Taken together, our findings indicate the ability of human tissue cells to phagocytose necrotic neighboring cells in confluent cell layers. The origin of the cell line influences the rate of cell-in-cell structure formation. The higher cell-in-cell structure rates during cell cycle progression might be influenced by cytoskeletal reorganization during this period or indicate an evolutionary anchorage of the process. Recycling of nutrients during cell growth might also be an explanation.
Background:
While the role of stereotactic radiotherapy for brain metastases is increasing, evidence on the comparative efficacy and safety of fractionated stereotactic radiotherapy (FSRT) and ...single-session radiosurgery (SRS) is scarce.
Methods:
Longitudinal volumetric analysis was performed in a consecutive cohort of 120 patients and 190 brain metastases (>0.065 cm
3
in volume / > ~5 mm in diameter) treated exclusively with FSRT (
n
= 98) and SRS (
n
= 92), respectively. A total of 972 tumor segmentations was used, averaging 5.1 time points per metastasis. Progression was defined using a volumetric extension of the RANO-BM criteria. Local control and radionecrosis were compared for lesions treated with FSRT and SRS, respectively.
Results:
Metastases treated with FSRT were significantly larger at baseline (mean, 4.66 vs. 0.40 cm
3
,
p
< 0.001). Biologically effective dose (BED) for metastases (α/β = 12, linear-quadratic-cubic model) was significantly associated with local control, whereas BED for normal brain (α/β = 2, linear-quadratic model) was significantly associated with radionecrosis. Median time to local progression was 22.9 months in the FSRT group compared to 14.5 months in the SRS group (
p
= 0.022). Overall radionecrosis rate at 12 months was 3.4% for FSRT and 14.8% for SRS (
p
= 0.010). Radionecrosis °IV requiring resection with histologic proof of radiation necrosis also was significantly reduced in the FSRT group (FSRT 0.0% vs. SRS 3.9%,
p
= 0.041). In multivariate analysis, FSRT was associated with reduced risk of progression (HR 0.47,
p
= 0.015) and reduced risk of radionecrosis (HR 0.18,
p
= 0.045).
Conclusions:
This volumetric study provides initial evidence that the improvements in therapeutic ratio expected for FSRT in larger brain metastases, might equally extend into the domain of smaller metastases, traditionally less considered for fractionated treatment. FSRT might constitute an important tool to further increase local control and reduce radionecrosis risk in stereotactic radiotherapy for brain metastases, that should be assessed in randomized intervention trials.
Purpose
To investigate the dosimetric influence of daily interfractional (inter) setup errors and intrafractional (intra) target motion on the planning target volume (PTV) and the possibility of an ...offline adaptive radiotherapy (ART) method to correct larger patient positioning uncertainties in image-guided radiotherapy for prostate cancer (PCa).
Materials and methods
A CTV (clinical target volume)-to-PTV margin ranging from 15 mm in LR (left-right) and SI (superior-inferior) and 5–10 mm in AP (anterior-posterior) direction was applied to all patients. The dosimetric influence of this margin was retrospectively calculated by analysing systematic and random components of inter and intra errors of 31 consecutive intermediate- and high-risk localized PCa patients using daily cone beam computed tomography and kV/kV (kilo-Voltage) imaging. For each patient inter variation was assessed by observing the first 4 treatment days, which led to an offline ART-based treatment plan in case of larger variations.
Results:
Systematic inter uncertainties were larger (1.12 in LR, 2.28 in SI and 1.48 mm in AP) than intra systematic errors (0.44 in LR, 0.69 in SI and 0.80 mm in AP). Same findings for the random error in SI direction with 3.19 (inter) and 2.30 mm (intra), whereas in LR and AP results were alike with 1.89 (inter) and 1.91 mm (intra) and 2.10 (inter) and 2.27 mm (intra), respectively. The calculated margin revealed dimensions of 4–5 mm in LR, 8–9 mm in SI and 6–7 mm in AP direction. Treatment plans which had to be adapted showed smaller variations with 1.12 (LR) and 1.72 mm (SI) for Σ and 4.17 (LR) and 3.75 mm (SI) for σ compared to initial plans with 1.77 and 2.62 mm for Σ and 4.46 and 5.39 mm for σ in LR and SI, respectively.
Conclusion
The currently clinically used margin of 15 mm in LR and SI and 5–10 mm in AP direction includes inter and intra uncertainties. The results show that offline ART is feasible which becomes a necessity with further reductions in PTV margins.
Purpose
The potential of large language models in medicine for education and decision-making purposes has been demonstrated as they have achieved decent scores on medical exams such as the United ...States Medical Licensing Exam (USMLE) and the MedQA exam. This work aims to evaluate the performance of ChatGPT-4 in the specialized field of radiation oncology.
Methods
The 38th American College of Radiology (ACR) radiation oncology in-training (TXIT) exam and the 2022 Red Journal Gray Zone cases are used to benchmark the performance of ChatGPT-4. The TXIT exam contains 300 questions covering various topics of radiation oncology. The 2022 Gray Zone collection contains 15 complex clinical cases.
Results
For the TXIT exam, ChatGPT-3.5 and ChatGPT-4 have achieved the scores of 62.05% and 78.77%, respectively, highlighting the advantage of the latest ChatGPT-4 model. Based on the TXIT exam, ChatGPT-4’s strong and weak areas in radiation oncology are identified to some extent. Specifically, ChatGPT-4 demonstrates better knowledge of statistics, CNS & eye, pediatrics, biology, and physics than knowledge of bone & soft tissue and gynecology, as per the ACR knowledge domain. Regarding clinical care paths, ChatGPT-4 performs better in diagnosis, prognosis, and toxicity than brachytherapy and dosimetry. It lacks proficiency in in-depth details of clinical trials. For the Gray Zone cases, ChatGPT-4 is able to suggest a personalized treatment approach to each case with high correctness and comprehensiveness. Importantly, it provides novel treatment aspects for many cases, which are not suggested by any human experts.
Conclusion
Both evaluations demonstrate the potential of ChatGPT-4 in medical education for the general public and cancer patients, as well as the potential to aid clinical decision-making, while acknowledging its limitations in certain domains. Owing to the risk of hallucinations, it is essential to verify the content generated by models such as ChatGPT for accuracy.
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