Engineered Age-Mimetic Breast Cancer Models Reveal Differential Drug Responses in Young and Aged Microenvironments

Aging is one of the most significant risk factors for breast cancer. With the growing interest in the alterations of the aging breast tissue microenvironment, it is identified that aging is related to tumorigenesis, invasion, and drug resistance. However, current pre-clinical disease models often neglect the impact of aging and sometimes result in worse clinical outcomes. In this study, aged animal-generated materials are utilized to create and validate a novel age-mimetic breast cancer model that generates an aging microenvironment for cells and alters cells toward a more invasive phenotype found in the aged environment. Furthermore, the age-mimetic models are utilized for 3D breast cancer invasion assessment and high-throughput screening of over 700 drugs in the FDA-approved drug library. 36 potential effective drug targets as well as 34 potential drug targets with different drug responses in different age groups are identified, demonstrating the potential of this age-mimetic breast cancer model for further in-depth breast cancer studies and drug development.

Texture-preserving diffusion model for CBCT-to-CT synthesis

Cone beam computed tomography (CBCT) serves as a vital imaging modality in diverse clinical applications, but is constrained by inherent limitations such as reduced image quality and increased noise. In contrast, computed tomography (CT) offers superior resolution and tissue contrast. Bridging the gap between these modalities through CBCT-to-CT synthesis becomes imperative. Deep learning techniques have enhanced this synthesis, yet challenges with generative adversarial networks persist. Denoising Diffusion Probabilistic Models have emerged as a promising alternative in image synthesis. In this study, we propose a novel texture-preserving diffusion model for CBCT-to-CT synthesis that incorporates adaptive high-frequency optimization and a dual-mode feature fusion module. Our method aims to enhance high-frequency details, effectively fuse cross-modality features, and preserve fine image structures. Extensive validation demonstrates superior performance over existing methods, showcasing better generalization. The proposed model offers a transformative pathway to augment diagnostic accuracy and refine treatment planning across various clinical settings. This work represents a pivotal step toward non-invasive, safer, and high-quality CBCT-to-CT synthesis, advancing personalized diagnostic imaging practices.

Highly porous phosphate-based glasses for controlled delivery of antibacterial Cu ions prepared via sol-gel chemistry

Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P₂O₅-CaO-Na₂O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol-gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N₂ adsorption-desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state ³¹P Magic Angle Spinning Nuclear Magnetic Resonance (³¹P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca²⁺, Na⁺ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.

Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study

Background

Currently, the volume computed tomography dose index (CTDI_vol), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on the water-equivalent diameter (D_W) overcome those issues. The proposed methods found in the literature do not allow real-time computation of D_W and SSDE.

Purpose

This study aims to develop a software to compute D_W and SSDE in a real-time clinical workflow.

Method

In total, 430 CT studies and scans of a water-filled funnel phantom were used to compute accuracy and evaluate the times required to compute the D_W and SSDE. Two one-sided tests (TOST) equivalence test, Bland–Altman analysis, and bootstrap-based confidence interval estimations were used to evaluate the differences between actual diameter and D_W computed automatically and between D_W computed automatically and manually.

Results

The mean difference between the D_W computed automatically and the actual water diameter for each slice is −0.027% with a TOST confidence interval equal to [−0.087%, 0.033%]. Bland–Altman bias is −0.009% [−0.016%, −0.001%] with lower limits of agreement (LoA) equal to −0.0010 [−0.094%, −0.068%] and upper LoA equal to 0.064% [0.051%, 0.077%]. The mean difference between D_W computed automatically and manually is −0.014% with a TOST confidence interval equal to [−0.056%, 0.028%] on phantom and 0.41% with a TOST confidence interval equal to [0.358%, 0.462%] on real patients. The mean time to process a single image is 13.99 ms [13.69 ms, 14.30 ms], and the mean time to process an entire study is 11.5 s [10.62 s, 12.63 s].

Conclusion

The system shows that it is possible to have highly accurate D_W and SSDE in almost real-time without affecting the clinical workflow of CT examinations.

Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques

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Filters reduce the noise at the expense of visual image quality.

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Digital interpretation of images prevents misinterpretation of the images due to blurring of the images.

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Dose reduction without compromising the diagnostic.

Introduction

Medical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate.

Objectives

This study aims at assessing image quality during CT abdomen and brain examinations using filtering techniques as well as estimating the radiogenic risk associated with CT abdomen and brain examinations.

Materials and Methods

The data were collected from the Radiology Department at Royal Care International (RCI) Hospital, Khartoum, Sudan. The study included 100 abdominal CT images and 100 brain CT images selected from adult patients. Filters applied are namely: Mean filter, Gaussian filter, Median filter and Minimum filter. In this study, image quality after denoising is measured based on the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Metric (SSIM).

Results

The results show that the images quality parameters become higher after applications of filters. Median filter showed improved image quality as interpreted by the measured parameters: PSNR and SSIM, and it is thus considered as a better filter for removing the noise from all other applied filters.

Discussion

The noise removed by the different filters applied to the CT images resulted in enhancing high quality images thereby effectively revealing the important details of the images without increasing the patients’ risks from higher doses.

Conclusions

Filtering and image reconstruction techniques not only reduce the dose and thus the radiation risks, but also enhances high quality imaging which allows better diagnosis.

High natural PHA production from acetate in Cobetia sp. MC34 and Cobetia marina DSM 4741T and in silico analyses of the genus specific PhaC2 polymerase variant

BACKGROUND

Several members of the bacterial Halomonadacea family are natural producers of polyhydroxyalkanoates (PHA), which are promising materials for use as biodegradable bioplastics. Type-strain species of Cobetia are designated PHA positive, and recent studies have demonstrated relatively high PHA production for a few strains within this genus. Industrially relevant PHA producers may therefore be present among uncharacterized or less explored members. In this study, we characterized PHA production in two marine Cobetia strains. We further analyzed their genomes to elucidate pha genes and metabolic pathways which may facilitate future optimization of PHA production in these strains.

RESULTS

Cobetia sp. MC34 and Cobetia marina DSM 4741T were mesophilic, halotolerant, and produced PHA from four pure substrates. Sodium acetate with- and without co-supplementation of sodium valerate resulted in high PHA production titers, with production of up to 2.5 g poly(3-hydroxybutyrate) (PHB)/L and 2.1 g poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)/L in Cobetia sp. MC34, while C. marina DSM 4741T produced 2.4 g PHB/L and 3.7 g PHBV/L. Cobetia marina DSM 4741T also showed production of 2.5 g PHB/L from glycerol. The genome of Cobetia sp. MC34 was sequenced and phylogenetic analyses revealed closest relationship to Cobetia amphilecti. PHA biosynthesis genes were located at separate loci similar to the arrangement in other Halomonadacea. Further genome analyses revealed some differences in acetate- and propanoate metabolism genes between the two strains. Interestingly, only a single PHA polymerase gene (phaC2) was found in Cobetia sp. MC34, in contrast to two copies (phaC1 and phaC2) in C. marina DSM 4741T. In silico analyses based on phaC genes show that the PhaC2 variant is conserved in Cobetia and contains an extended C-terminus with a high isoelectric point and putative DNA-binding domains.

CONCLUSIONS

Cobetia sp. MC34 and C. marina DSM 4741T are natural producers of PHB and PHBV from industrially relevant pure substrates including acetate. However, further scale up, optimization of growth conditions, or use of metabolic engineering is required to obtain industrially relevant PHA production titers. The putative role of the Cobetia PhaC2 variant in DNA-binding and the potential implications remains to be addressed by in vitro- or in vivo methods.

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy

Objective: To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. Methods: 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the CycleGAN, Pix2pix and U-Net models were used to generate the sCT images. The Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) were used to quantify the accuracy of the proposed models in a testing cohort of 34 patients. Radiation dose were calculated on pCT and sCT following the same protocol. Dose distributions were evaluated for 4 patients by comparing the dose-volume-histogram (DVH) and 2D gamma index analysis. Results: The average MAE and RMSE values between sCT by three models and pCT reduced by 15.4 HU and 26.8 HU at least, while the mean PSNR and SSIM metrics between sCT by different models and pCT added by 10.6 and 0.05 at most, respectively. There were only slight differences for DVH of selected contours between different plans. The passing rates of 2D gamma index analysis under 3 mm/3% 3 mm/2%, 2 mm/3%and 2 mm/2% criteria were all higher than 95%. Conclusions: All the sCT had achieved better evaluation metrics than those of original CBCT, while the performance of CycleGAN model was proved to be best among three methods. The dosimetric agreement confirmed the HU accuracy and consistent anatomical structures of sCT by deep learning methods.

Assessment of myocardial viscoelasticity with Brillouin spectroscopy in myocardial infarction and aortic stenosis models

Heart diseases are associated with changes in the biomechanical properties of the myocardial wall. However, there is no modality available to assess myocardial stiffness directly. Brillouin microspectroscopy (mBS) is a consolidated mechanical characterization technique, applied to the study of the viscoelastic and elastic behavior of biological samples and may be a valuable tool for assessing the viscoelastic properties of the cardiac tissue. In this work, viscosity and elasticity were assessed using mBS in heart samples obtained from healthy and unhealthy mice (n = 6 per group). Speckle-tracking echocardiography (STE) was performed to evaluate heart deformation. We found that mBS was able to detect changes in stiffness in the ventricles in healthy myocardium. The right ventricle showed reduced stiffness, in agreement with its increased compliance. mBS measurements correlated strongly with STE data, highlighting the association between displacement and stiffness in myocardial regions. This correlation was lost in pathological conditions studied. The scar region in the infarcted heart presented changes in stiffness when compared to the rest of the heart, and the hypertrophied left ventricle showed increased stiffness following aortic stenosis, compared to the right ventricle. We demonstrate that mBS can be applied to determine myocardial stiffness, that measurements correlate with functional parameters and that they change with disease.

Gold Nanoparticle DNA Damage by Photon Beam in a Magnetic Field: A Monte Carlo Study

Ever since the emergence of magnetic resonance (MR)-guided radiotherapy, it is important to investigate the impact of the magnetic field on the dose enhancement in deoxyribonucleic acid (DNA), when gold nanoparticles are used as radiosensitizers during radiotherapy. Gold nanoparticle-enhanced radiotherapy is known to enhance the dose deposition in the DNA, resulting in a double-strand break. In this study, the effects of the magnetic field on the dose enhancement factor (DER) for varying gold nanoparticle sizes, photon beam energies and magnetic field strengths and orientations were investigated using Geant4-DNA Monte Carlo simulations. Using a Monte Carlo model including a single gold nanoparticle with a photon beam source and DNA molecule on the left and right, it is demonstrated that as the gold nanoparticle size increased, the DER increased. However, as the photon beam energy decreased, an increase in the DER was detected. When a magnetic field was added to the simulation model, the DER was found to increase by 2.5-5% as different field strengths (0-2 T) and orientations (x-, y- and z-axis) were used for a 100 nm gold nanoparticle using a 50 keV photon beam. The DNA damage reflected by the DER increased slightly with the presence of the magnetic field. However, variations in the magnetic field strength and orientation did not change the DER significantly.

Gold Nanoparticles as Radiosensitizers in Cancer Radiotherapy

The rapid development of nanotechnology offers a variety of potential therapeutic strategies for cancer treatment. High atomic element nanomaterials are often utilized as radiosensitizers due to their unique photoelectric decay characteristics. Among them, gold nanoparticles (GNPs) are one of the most widely investigated and are considered to be an ideal radiosensitizers for radiotherapy due to their high X-ray absorption and unique physicochemical properties. Over the last few decades, multi-disciplinary studies have focused on the design and optimization of GNPs to achieve greater dosing capability and higher therapeutic effects and highlight potential mechanisms for radiosensitization of GNPs. Although the radiosensitizing potential of GNPs has been widely recognized, its clinical translation still faces many challenges. This review analyses the different roles of GNPs as radiosensitizers in cancer radiotherapy and summarizes recent advances. In addition, the underlying mechanisms of GNP radiosensitization, including physical, chemical and biological mechanisms are discussed, which may provide new directions for the optimization and clinical transformation of next-generation GNPs.

Depth Dose Enhancement on Flattening-Filter-Free Photon Beam: A Monte Carlo Study in Nanoparticle-Enhanced Radiotherapy

The aim of this study is to investigate the variations of depth dose enhancement (DDE) on different nanoparticle (NP) variables, when using the flattening-filter-free (FFF) photon beam in nanoparticle-enhanced radiotherapy. Monte Carlo simulation under a macroscopic approach was used to determine the DDE ratio (DDER) with variables of NP material (gold (Au) and iron (III) oxide (Fe2O3)), NP concentration (3–40 mg/mL) and photon beam (10 MV flattening-filter (FF) and 10 MV FFF). It is found that Au NPs had a higher DDER than Fe2O3 NPs, when the depths were shallower than 6 and 8 cm for the 10 MV FF and 10 MV FFF photon beams, respectively. However, in a deeper depth range of 10–20 cm, DDER for the Au NPs was lower than Fe2O3 NPs mainly due to the beam attenuation and photon energy distribution. It is concluded that DDER for the Au NPs and Fe2O3 NPs decreased with an increase of depth in the range of 10–20 cm, with rate of decrease depending on the NP material, NP concentration and the use of FF in the photon beam.

Application of Nanomaterials in Biomedical Imaging and Cancer Therapy

Nanomaterials, such as nanoparticles, nanorods, nanosphere, nanoshells, and nanostars, are very commonly used in biomedical imaging and cancer therapy. They make excellent drug carriers, imaging contrast agents, photothermal agents, photoacoustic agents, and radiation dose enhancers, among other applications. Recent advances in nanotechnology have led to the use of nanomaterials in many areas of functional imaging, cancer therapy, and synergistic combinational platforms. This review will systematically explore various applications of nanomaterials in biomedical imaging and cancer therapy. The medical imaging modalities include magnetic resonance imaging, computed tomography, positron emission tomography, single photon emission computerized tomography, optical imaging, ultrasound, and photoacoustic imaging. Various cancer therapeutic methods will also be included, including photothermal therapy, photodynamic therapy, chemotherapy, and immunotherapy. This review also covers theranostics, which use the same agent in diagnosis and therapy. This includes recent advances in multimodality imaging, image-guided therapy, and combination therapy. We found that the continuous advances of synthesis and design of novel nanomaterials will enhance the future development of medical imaging and cancer therapy. However, more resources should be available to examine side effects and cell toxicity when using nanomaterials in humans.

Gold Nanoparticles for Drug Delivery and Cancer Therapy

Nanomaterials are popularly used in drug delivery, disease diagnosis and therapy. Among a number of functionalized nanomaterials such as carbon nanotubes, peptide nanostructures, liposomes and polymers, gold nanoparticles (Au NPs) make excellent drug and anticancer agent carriers in biomedical and cancer therapy application. Recent advances of synthetic technique improved the surface coating of Au NPs with accurate control of particle size, shape and surface chemistry. These make the gold nanomaterials a much easier and safer cancer agent and drug to be applied to the patient’s tumor. Although many studies on Au NPs have been published, more results are in the pipeline due to the rapid development of nanotechnology. The purpose of this review is to assess how the novel nanomaterials fabricated by Au NPs can impact biomedical applications such as drug delivery and cancer therapy. Moreover, this review explores the viability, property and cytotoxicity of various Au NPs.

Characterization and comparison of imaging contrast enhancement with PEG-functionalized gold nanoparticles in kV cone beam computed tomography and computed tomography imaging

The purpose of this study is to define a simplified method to accurately predict and characterize kV cone beam computed tomography (kV CBCT) and computed tomography (CT) image contrast enhancement from gold nanoparticles (GNPs). Parameters of the kV CBCT of a Varian Novalis Tx linear accelerator and of a GE LightSpeed 4 Big Bore CT machine were modeled using the MCNP 6.2 Monte Carlo code. A 0.25 × 0.25 cm² source, defined with a 100 kVp energy spectrum with appropriate filtration, was implemented in the MCNP6.2 model for kV CBCT, which also contained x- and y-blades and a full bowtie filter. A 1 cm³ cube of GNP solution (modeled as a mass percentage of gold in water) was placed 100 cm below the source. For the CT-simulator model, a source was defined with energy spectra for 80 and 140 kVp x-rays with appropriate filtration and angular spectrum. A 1 cm³ GNP solution was modeled as before and a detector was placed 40 cm below that. Attenuation coefficients of four GNP solutions were computed and Hounsfield unit (HU) values were calculated. The computed HU values were compared against experimentally measured values obtained by scanning batches of GNPs of various sizes and concentrations using a GE LightSpeed 4 Big Bore CT scanner at 80 kVp and 140 kVp energies, as well as the kV CBCT capability of a Varian Novalis Tx linear accelerator. HU analysis was carried out using Velocity Medical Solutions clinical CT image analysis software. The MCNP calculated HU values matched the measured values to within ± 5%. Image contrast enhancement analysis showed a total increase in HU of up to 223. The sample having the highest gold mass percentage tested showed the greatest increase in HU number compared to water.

Dose Enhancement for the Flattening-Filter-Free and Flattening-Filter Photon Beams in Nanoparticle-Enhanced Radiotherapy: A Monte Carlo Phantom Study

Monte Carlo simulations were used to predict the dose enhancement ratio (DER) using the flattening-filter-free (FFF) and flattening-filter (FF) photon beams in prostate nanoparticle-enhanced radiotherapy, with multiple variables such as nanoparticle material, nanoparticle concentration, prostate size, pelvic size, and photon beam energy. A phantom mimicking the patient’s pelvis with various prostate and pelvic sizes was used. Macroscopic Monte Carlo simulation using the EGSnrc code was used to predict the dose at the prostate or target using the 6 MV FFF, 6 MV FF, 10 MV FFF, and 10 MV FF photon beams produced by a Varian TrueBeam linear accelerator (Varian Medical System, Palo Alto, CA, USA). Nanoparticle materials of gold, platinum, iodine, silver, and iron oxide with concentration varying in the range of 3–40 mg/ml were used in simulations. Moreover, the prostate and pelvic size were varied from 2.5 to 5.5 cm and 20 to 30 cm, respectively. The DER was defined as the ratio of the target dose with nanoparticle addition to the target dose without nanoparticle addition in the simulation. From the Monte Carlo results of DER, the best nanoparticle material with the highest DER was gold, based on all the nanoparticle concentrations and photon beams. Smaller prostate size, smaller pelvic size, and a higher nanoparticle concentration showed better DER results. When comparing energies, the 6 MV beams always had the greater enhancement ratio. In addition, the FFF photon beams always had a better DER when compared to the FF beams. It is concluded that gold nanoparticles were the most effective material in nanoparticle-enhanced radiotherapy. Moreover, lower photon beam energy (6 MV), FFF photon beam, higher nanoparticle concentration, smaller pelvic size, and smaller prostate size would all increase the DER in prostate nanoparticle-enhanced radiotherapy.