Oral nanotherapeutic formulation of insulin with reduced episodes of hypoglycaemia.

Injectable insulin is an extensively used medication with potential life-threatening hypoglycaemic events. Here we report on insulin-conjugated silver sulfide quantum dots coated with a chitosan/glucose polymer to produce a responsive oral insulin nanoformulation. This formulation is pH responsive, is insoluble in acidic environments and shows increased absorption in human duodenum explants and Caenorhabditis elegans at neutral pH. The formulation is sensitive to glucosidase enzymes to trigger insulin release. It is found that the formulation distributes to the liver in mice and rats after oral administration and promotes a dose-dependent reduction in blood glucose without promoting hypoglycaemia or weight gain in diabetic rodents. Non-diabetic baboons also show a dose-dependent reduction in blood glucose. No biochemical or haematological toxicity or adverse events were observed in mice, rats and non-human primates. The formulation demonstrates the potential to orally control blood glucose without hypoglycaemic episodes.

Online dynamical learning and sequence memory with neuromorphic nanowire networks.

Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems that exploit the unique physical properties of nanostructured materials. In addition to their neural network-like physical structure, NWNs also exhibit resistive memory switching in response to electrical inputs due to synapse-like changes in conductance at nanowire-nanowire cross-point junctions. Previous studies have demonstrated how the neuromorphic dynamics generated by NWNs can be harnessed for temporal learning tasks. This study extends these findings further by demonstrating online learning from spatiotemporal dynamical features using image classification and sequence memory recall tasks implemented on an NWN device. Applied to the MNIST handwritten digit classification task, online dynamical learning with the NWN device achieves an overall accuracy of 93.4%. Additionally, we find a correlation between the classification accuracy of individual digit classes and mutual information. The sequence memory task reveals how memory patterns embedded in the dynamical features enable online learning and recall of a spatiotemporal sequence pattern. Overall, these results provide proof-of-concept of online learning from spatiotemporal dynamics using NWNs and further elucidate how memory can enhance learning.

Neuromorphic learning, working memory, and metaplasticity in nanowire networks.

Nanowire networks (NWNs) mimic the brain's neurosynaptic connectivity and emergent dynamics. Consequently, NWNs may also emulate the synaptic processes that enable higher-order cognitive functions such as learning and memory. A quintessential cognitive task used to measure human working memory is the n-back task. In this study, task variations inspired by the n-back task are implemented in a NWN device, and external feedback is applied to emulate brain-like supervised and reinforcement learning. NWNs are found to retain information in working memory to at least n = 7 steps back, remarkably similar to the originally proposed "seven plus or minus two" rule for human subjects. Simulations elucidate how synapse-like NWN junction plasticity depends on previous synaptic modifications, analogous to "synaptic metaplasticity" in the brain, and how memory is consolidated via strengthening and pruning of synaptic conductance pathways.

Information dynamics in neuromorphic nanowire networks.

Neuromorphic systems comprised of self-assembled nanowires exhibit a range of neural-like dynamics arising from the interplay of their synapse-like electrical junctions and their complex network topology. Additionally, various information processing tasks have been demonstrated with neuromorphic nanowire networks. Here, we investigate the dynamics of how these unique systems process information through information-theoretic metrics. In particular, Transfer Entropy (TE) and Active Information Storage (AIS) are employed to investigate dynamical information flow and short-term memory in nanowire networks. In addition to finding that the topologically central parts of networks contribute the most to the information flow, our results also reveal TE and AIS are maximized when the networks transitions from a quiescent to an active state. The performance of neuromorphic networks in memory and learning tasks is demonstrated to be dependent on their internal dynamical states as well as topological structure. Optimal performance is found when these networks are pre-initialised to the transition state where TE and AIS are maximal. Furthermore, an optimal range of information processing resources (i.e. connectivity density) is identified for performance. Overall, our results demonstrate information dynamics is a valuable tool to study and benchmark neuromorphic systems.

Avalanches and edge-of-chaos learning in neuromorphic nanowire networks.

The brain's efficient information processing is enabled by the interplay between its neuro-synaptic elements and complex network structure. This work reports on the neuromorphic dynamics of nanowire networks (NWNs), a unique brain-inspired system with synapse-like memristive junctions embedded within a recurrent neural network-like structure. Simulation and experiment elucidate how collective memristive switching gives rise to long-range transport pathways, drastically altering the network's global state via a discontinuous phase transition. The spatio-temporal properties of switching dynamics are found to be consistent with avalanches displaying power-law size and life-time distributions, with exponents obeying the crackling noise relationship, thus satisfying criteria for criticality, as observed in cortical neuronal cultures. Furthermore, NWNs adaptively respond to time varying stimuli, exhibiting diverse dynamics tunable from order to chaos. Dynamical states at the edge-of-chaos are found to optimise information processing for increasingly complex learning tasks. Overall, these results reveal a rich repertoire of emergent, collective neural-like dynamics in NWNs, thus demonstrating the potential for a neuromorphic advantage in information processing.

Quantum Dot Nanomedicine Formulations Dramatically Improve Pharmacological Properties and Alter Uptake Pathways of Metformin and Nicotinamide Mononucleotide in Aging Mice.

Orally administered Ag2S quantum dots (QDs) rapidly cross the small intestine and are taken up by the liver. Metformin and nicotinamide mononucleotide (NMN) target metabolic and aging processes within the liver. This study examined the pharmacology and toxicology of QD-based nanomedicines as carriers of metformin and NMN in young and old mice, determining if their therapeutic potency and reduced effects associated with aging could be improved. Pharmacokinetic studies demonstrated that QD-conjugated metformin and NMN have greater bioavailability, with selective accumulation in the liver following oral administration compared to unconjugated formulations. Pharmacodynamic data showed that the QD-conjugated medicines had increased physiological, metabolic, and cellular potency compared to unconjugated formulations (25× metformin; 100× NMN) and highlighted a shift in the peak induction of, and greater metabolic response to, glucose tolerance testing. Two weeks of treatment with low-dose QD-NMN (0.8 mg/kg/day) improved glucose tolerance tests in young (3 months) mice, whereas old (18 and 24 months) mice demonstrated improved fasting and fed insulin levels and insulin resistance. High-dose unconjugated NMN (80 mg/kg/day) demonstrated improvements in young mice but not in old mice. After 100 days of QD (320 µg/kg/day) treatment, there was no evidence of cellular necrosis, fibrosis, inflammation, or accumulation. Ag2S QD nanomedicines improved the pharmacokinetic and pharmacodynamic properties of metformin and NMN by increasing their therapeutic potency, bypassing classical cellular uptake pathways, and demonstrated efficacy when drug alone was ineffective in aging mice.

Positron annihilation localization by nanoscale magnetization.

In positron emission tomography (PET), the finite range over which positrons travel before annihilating with an electron places a fundamental physical limit on the spatial resolution of PET images. After annihilation, the photon pair detected by the PET instrumentation is emitted from a location that is different from the positron-emitting source, resulting in image blurring. Here, we report on the localization of positron range, and hence annihilation quanta, by strong nanoscale magnetization of superparamagnetic iron oxide nanoparticles (SPIONs) in PET-MRI. We found that positron annihilations localize within a region of interest by up to 60% more when SPIONs are present (with [Fe] = 3 mM) compared to when they are not. The resulting full width at half maximum of the PET scans showed the spatial resolution improved by up to [Formula: see text] 30%. We also found evidence suggesting that the radiolabeled SPIONs produced up to a six-fold increase in ortho-positronium. These results may also have implications for emerging cancer theranostic strategies, where charged particles are used as therapeutic as well as diagnostic agents and improved dose localization within a tumor is a determinant of better treatment outcomes.

High-sensitivity in vivo contrast for ultra-low field magnetic resonance imaging using superparamagnetic iron oxide nanoparticles.

Magnetic resonance imaging (MRI) scanners operating at ultra-low magnetic fields (ULF; <10 mT) are uniquely positioned to reduce the cost and expand the clinical accessibility of MRI. A fundamental challenge for ULF MRI is obtaining high-contrast images without compromising acquisition sensitivity to the point that scan times become clinically unacceptable. Here, we demonstrate that the high magnetization of superparamagnetic iron oxide nanoparticles (SPIONs) at ULF makes possible relaxivity- and susceptibility-based effects unachievable with conventional contrast agents (CAs). We leverage these effects to acquire high-contrast images of SPIONs in a rat model with ULF MRI using short scan times. This work overcomes a key limitation of ULF MRI by enabling in vivo imaging of biocompatible CAs. These results open a new clinical translation pathway for ULF MRI and have broader implications for disease detection with low-field portable MRI scanners.

Roadmap for metal nanoparticles in radiation therapy: current status, translational challenges, and future directions.

This roadmap outlines the potential roles of metallic nanoparticles (MNPs) in the field of radiation therapy. MNPs made up of a wide range of materials (from Titanium, Z = 22, to Bismuth, Z = 83) and a similarly wide spectrum of potential clinical applications, including diagnostic, therapeutic (radiation dose enhancers, hyperthermia inducers, drug delivery vehicles, vaccine adjuvants, photosensitizers, enhancers of immunotherapy) and theranostic (combining both diagnostic and therapeutic), are being fabricated and evaluated. This roadmap covers contributions from experts in these topics summarizing their view of the current status and challenges, as well as expected advancements in technology to address these challenges.

Topological Properties of Neuromorphic Nanowire Networks.

Graph theory has been extensively applied to the topological mapping of complex networks, ranging from social networks to biological systems. Graph theory has increasingly been applied to neuroscience as a method to explore the fundamental structural and functional properties of human neural networks. Here, we apply graph theory to a model of a novel neuromorphic system constructed from self-assembled nanowires, whose structure and function may mimic that of human neural networks. Simulations of neuromorphic nanowire networks allow us to directly examine their topology at the individual nanowire-node scale. This type of investigation is currently extremely difficult experimentally. We then apply network cartographic approaches to compare neuromorphic nanowire networks with: random networks (including an untrained artificial neural network); grid-like networks and the structural network of C. elegans. Our results demonstrate that neuromorphic nanowire networks exhibit a small-world architecture similar to the biological system of C. elegans, and significantly different from random and grid-like networks. Furthermore, neuromorphic nanowire networks appear more segregated and modular than random, grid-like and simple biological networks and more clustered than artificial neural networks. Given the inextricable link between structure and function in neural networks, these results may have important implications for mimicking cognitive functions in neuromorphic nanowire networks.

A Radio-Nano-Platform for T1/T2 Dual-Mode PET-MR Imaging.

PURPOSE: This study aimed to develop a chelate-free radiolabeled nanoparticle platform for simultaneous positron emission tomography (PET) and magnetic resonance (MR) imaging that provides contrast-enhanced diagnostic imaging and significant image quality gain by integrating the high spatial resolution of MR with the high sensitivity of PET. METHODS: A commercially available super-paramagnetic iron oxide nanoparticle (SPION) (Feraheme®, FH) was labeled with the [89Zr]Zr using a novel chelate-free radiolabeling technique, heat-induced radiolabeling (HIR). Radiochemical yield (RCY) and purity (RCP) were measured using size exclusion chromatography (SEC) and radio-thin layer chromatography (radio-TLC). Characterization of the non-radioactive isotope 90Zr-labeled FH was performed by transmission electron microscopy (TEM). Simultaneous PET-MR phantom imaging was performed with different 89Zr-FH concentrations. The MR quantitative image analysis determined the contrast-enhancing properties of FH. The signal-to-noise ratio (SNR) and full-width half-maximum (FWHM) of the line spread function (LSF) were calculated before and after co-registering the PET and MR image data. RESULTS: High RCY (92%) and RCP (98%) of the [89Zr]Zr-FH product was achieved. TEM analysis confirmed the 90Zr atoms adsorption onto the SPION surface (≈ 10% average radial increase). Simultaneous PET-MR scans confirmed the capability of the [89Zr]Zr-FH nano-platform for this multi-modal imaging technique. Relative contrast image analysis showed that [89Zr]Zr-FH can act as a dual-mode T1/T2 contrast agent. For co-registered PET-MR images, higher spatial resolution (FWHM enhancement ≈ 3) and SNR (enhancement ≈ 8) was achieved at a clinical dose of radio-isotope and Fe. CONCLUSION: Our results demonstrate FH is a highly suitable SPION-based platform for chelate-free labeling of PET tracers for hybrid PET-MR. The high RCY and RCP confirmed the robustness of the chelate-free HIR technique. An overall image quality gain was achieved compared to PET- or MR-alone imaging with a relatively low dosage of [89Zr]Zr-FH. Additionally, FH is suitable as a dual-mode T1/T2 MR image contrast agent.

A Chelate-Free Nano-Platform for Incorporation of Diagnostic and Therapeutic Isotopes.

PURPOSE: Using our chelate-free, heat-induced radiolabeling (HIR) method, we show that a wide range of metals, including those with radioactive isotopologues used for diagnostic imaging and radionuclide therapy, bind to the Feraheme (FH) nanoparticle (NP), a drug approved for the treatment of iron anemia. MATERIAL AND METHODS: FH NPs were heated (120°C) with nonradioactive metals, the resulting metal-FH NPs were characterized by inductively coupled plasma mass spectrometry (ICP-MS), dynamic light scattering (DLS), and r1 and r2 relaxivities obtained by nuclear magnetic relaxation spectrometry (NMRS). In addition, the HIR method was performed with [90Y]Y3+, [177Lu]Lu3+, and [64Cu]Cu2+, the latter with an HIR technique optimized for this isotope. Optimization included modifying reaction time, temperature, and vortex technique. Radiochemical yield (RCY) and purity (RCP) were measured using size exclusion chromatography (SEC) and thin-layer chromatography (TLC). RESULTS: With ICP-MS, metals incorporated into FH at high efficiency were bismuth, indium, yttrium, lutetium, samarium, terbium and europium (>75% @ 120 oC). Incorporation occurred with a small (less than 20%) but statistically significant increases in size and the r2 relaxivity. An improved HIR technique (faster heating rate and improved vortexing) was developed specifically for copper and used with the HIR technique and [64Cu]Cu2+. Using SEC and TLC analyses with [90Y]Y3+, [177Lu]Lu3+ and [64Cu]Cu2+, RCYs were greater than 85% and RCPs were greater than 95% in all cases. CONCLUSION: The chelate-free HIR technique for binding metals to FH NPs has been extended to a range of metals with radioisotopes used in therapeutic and diagnostic applications. Cations with f-orbital electrons, more empty d-orbitals, larger radii, and higher positive charges achieved higher values of RCY and RCP in the HIR reaction. The ability to use a simple heating step to bind a wide range of metals to the FH NP, a widely available approved drug, may allow this NP to become a platform for obtaining radiolabeled nanoparticles in many settings.

Rapid Intestinal Uptake and Targeted Delivery to the Liver Endothelium Using Orally Administered Silver Sulfide Quantum Dots.

Quantum dots (QDs) are used for imaging and transport of therapeutics. Here we demonstrate rapid absorption across the small intestine and targeted delivery of QDs with bound materials to the liver sinusoidal endothelial cells (LSECs) or hepatocytes in vitro and in vivo following oral administration. QDs were radiolabeled with 3H-oleic acid, with a fluorescent tag or 14C-metformin placed within a drug binding site. Three different biopolymer shell coatings were compared (formaldehyde-treated serum albumin (FSA), gelatin, heparin). Passage across the small intestine into mesenteric veins is mediated by clathrin endocytosis and micropinocytosis. 60% of an oral dose of QDs was rapidly distributed to the liver within 30 min, and this increased to 85% with FSA biopolymer coating. Uptake into LSECs also increased 3-fold with FSA coating, while uptake into hepatocytes was increased from 40% to 85% with gelatin biopolymer coating. Localization of QDs to LSECs was confirmed with immunofluorescence and transmission electron microscopy. 85% of QDs were cleared within 24 h of administration. The bioavailability of 14C-metformin 2 h post-ingestion was increased 5-fold by conjugation with QD-FSA, while uptake of metformin into LSECs was improved 50-fold by using these QDs. Endocytosis of QDs by SK-Hep1 cells (an LSEC immortal cell line) was via clathrin- and caveolae-mediated pathways with QDs taken up into lysosomes. In conclusion, we have shown high specificity targeting of the LSEC or hepatocytes after oral administration of QDs coated with a biopolymer layer of FSA or gelatin, which improved the bioavailability and delivery of metformin to LSECs.

Radio-enhancement effects by radiolabeled nanoparticles.

In cancer radiation therapy, dose enhancement by nanoparticles has to date been investigated only for external beam radiotherapy (EBRT). Here, we report on an in silico study of nanoparticle-enhanced radiation damage in the context of internal radionuclide therapy. We demonstrate the proof-of-principle that clinically relevant radiotherapeutic isotopes (i.e. 213Bi, 223Ra, 90Y, 177Lu, 67Cu, 64Cu and 89Zr) labeled to clinically relevant superparamagnetic iron oxide nanoparticles results in enhanced radiation damage effects localized to sub-micron scales. We find that radiation dose can be enhanced by up to 20%, vastly outperforming nanoparticle dose enhancement in conventional EBRT. Our results demonstrate that in addition to the favorable spectral characteristics of the isotopes and their proximity to the nanoparticles, clustering of the nanoparticles results in a nonlinear collective effect that amplifies nanoscale radiation damage effects by electron-mediated inter-nanoparticle interactions. In this way, optimal radio-enhancement is achieved when the inter-nanoparticle distance is less than the mean range of the secondary electrons. For the radioisotopes studied here, this corresponds to inter-nanoparticle distances <50 nm, with the strongest effects within 20 nm. The results of this study suggest that radiolabeled nanoparticles offer a novel and potentially highly effective platform for developing next-generation theranostic strategies for cancer medicine.

Emergent dynamics of neuromorphic nanowire networks.

Neuromorphic networks are formed by random self-assembly of silver nanowires. Silver nanowires are coated with a polymer layer after synthesis in which junctions between two nanowires act as resistive switches, often compared with neurosynapses. We analyze the role of single junction switching in the dynamical properties of the neuromorphic network. Network transitions to a high-conductance state under the application of a voltage bias higher than a threshold value. The stability and permanence of this state is studied by shifting the voltage bias in order to activate or deactivate the network. A model of the electrical network with atomic switches reproduces the relation between individual nanowire junctions switching events with current pathway formation or destruction. This relation is further manifested in changes in 1/f power-law scaling of the spectral distribution of current. The current fluctuations involved in this scaling shift are considered to arise from an essential equilibrium between formation, stochastic-mediated breakdown of individual nanowire-nanowire junctions and the onset of different current pathways that optimize power dissipation. This emergent dynamics shown by polymer-coated Ag nanowire networks places this system in the class of optimal transport networks, from which new fundamental parallels with neural dynamics and natural computing problem-solving can be drawn.

Radio-enhancement by gold nanoparticles and their impact on water radiolysis for x-ray, proton and carbon-ion beams.

Gold nanoparticle (GNP) radio-enhancement is a promising technique to increase the dose deposition in a tumor while sparing neighboring healthy tissue. Previous experimental studies showed effects on cell survival and tumor control for keV x-rays but surprisingly also for MV-photons, proton and carbon-ion beams. In a systematic study, we use the Monte Carlo simulation tool TOPAS-nBio to model the GNP radio-enhancement within a cell as a function of GNP concentration, size and clustering for a wide range of energies for photons, protons and, for the first time, carbon-ions. Moreover, we include water radiolysis, which has been recognized as a major pathway of GNP mediated radio-enhancement. At a GNP concentration of 0.5% and a GNP diameter of 10 nm, the dose enhancement ratio was highest for 50 keV x-rays (1.36) and decreased in the orthovoltage (1.04 at 250 keV) and megavoltage range (1.01 at 1 MeV). The dose enhancement linearly increased with GNP concentration and decreased with GNP size and degree of clustering for all radiation modalities. While the highest physical dose enhancement at 5% concentrations was only 1.003 for 10 MeV protons and 1.004 for 100 MeV carbon-ions, we find the number of hydroxyl ([Formula: see text]) altered by 23% and 3% after 1 [Formula: see text]s at low, clinically-relevant concentrations. For the same concentration and proton-impact, the G-value is most sensitive to the nanoparticle size with 46 times more radical interactions at GNPs for 2 nm than for 50 nm GNP diameter within 1 [Formula: see text]s. Nanoparticle clustering was found to decrease the number of interactions at GNPs, e.g. for a cluster of 25 GNPs by a factor of 3.4. The changes in G-value correlate to the average distance between the chemical species and the GNPs. While the radiochemistry of GNP-loaded water has yet to be fully understood, this work offers a first relative quantification of radiolysis products for a broad parameter-set.

Technical Note: The first live treatment on a 1.0 Tesla inline MRI-linac.

PURPOSE: This work describes the first live imaging and radiation delivery performed on a prototype 1.0 T inline MRI-Linac system in a rat brain tumor model, which was conducted on 29 January 2019. METHODS: A human scale 1.0 T MRI-Linac was adapted to be suitable for animal studies via a specially constructed open 6-channel receiver radiofrequency (RF) coil. A Fischer rat injected with 9L glioma cells in the right hemisphere was imaged and irradiated at day 11 post surgery as part of a larger cohort survival study. The rat was anesthetized and positioned at the iscocenter of the MRI-Linac. Imaging was used to localize the brain and confirm the presence of a tumor following the administration of a gadolinium nanoparticle contrast agent. A single dose of 10 Gy was delivered using a 2.25 cm × 2.90 cm radiation field covering the whole brain and verified with radiosensitive film in situ. Real-time imaging was used throughout the irradiation period to monitor the animal and target position. RESULTS: The signal-to-noise ratio (SNR) measured in the rat brain was 38. Postcontrast imaging was able to demonstrate a tumor of 5 mm diameter in the upper right hemisphere of the brain approximately 45 min after administration of the nanoparticles. The radiation beam had no impact on SNR and images at the rate of 2 Hz were effective in monitoring both respiration and intrafractional motion. In vivo film dosimetry confirmed the intended dose delivery. The total procedure time was 35 min. CONCLUSIONS: We have successfully used MRI guidance to localize and subsequently deliver a radiation field to the whole brain of a rat with a right hemispheric tumor. Real-time imaging during beam on was of sufficient quality to monitor breathing and perform exception gating of the treatment. This represents the first live use of a high field inline MRI-Linac.

IMPACT OF NANOPARTICLE CLUSTERING ON DOSE RADIO-ENHANCEMENT.

High atomic number nanoparticles (NPs) have been shown to enhance the effects of radiation in vitro and in vivo. However, NPs are often observed to cluster together, leading to inhomogeneous distribution within the tissue and within cells themselves. The effect of this clustering on the capability of NPs to enhance radiation dose has not yet been fully investigated. In this Monte Carlo simulation study, the dependence of radio-enhancement on a separation parameter characterising NP clustering was investigated. A target water cube of side length 100 µm was simulated containing gold NPs constituting ~1% by mass. The NPs were placed in a cubic grid pattern and the separation distance between nanoparticles was varied. For NPs of 100 nm radius widely separated 2 µm apart, 91% of the total energy deposit was found to occur in the surrounding water, compared to only 56% when the NPs were moved closer together to 0.2 µm. The remaining energy deposit was absorbed by the NPs themselves. A similar trend was observed for NPs of radius 50 nm. The clustering effect was found to persist to greater separations for the larger NPs. The proportion of energy deposit in the available water of the target impacts the potential for cellular damage. Energy deposited within nanoparticles is unlikely to cause biological damage, as ionisations in the surrounding water are required to create radical oxygen species which then progress to cause the biological response to radiation. Clustering of nanoparticles is therefore expected to decrease their effectiveness for enhancing radiotherapy.

Comparison of radiobiological parameters for 90Y radionuclide therapy (RNT) and external beam radiotherapy (EBRT) in vitro.

BACKGROUND: Dose rate variation is a critical factor affecting radionuclide therapy (RNT) efficacy. Relatively few studies to date have investigated the dose rate effect in RNT. Therefore, the aim of this study was to benchmark 90Y RNT (at different dose rates) against external beam radiotherapy (EBRT) in vitro and compare cell kill responses between the two irradiation processes. RESULTS: Three human colorectal carcinoma (CRC) cell lines (HT29, HCT116, SW48) were exposed to 90Y doses in the ranges 1-10.4 and 6.2-62.3 Gy with initial dose rates of 0.013-0.13 Gy/hr (low dose rate, LDR) and 0.077-0.77 Gy/hr (high dose rate, HDR), respectively. Results were compared to a 6-MV photon beam doses in the range from 1-9 Gy with constant dose rate of 277 Gy/hr. The cell survival parameters from the linear quadratic (LQ) model were determined. Additionally, Monte Carlo simulations were performed to calculate the average dose, dose rate and the number of hits in the cell nucleus. For the HT29 cell line, which was the most radioresistant, the α/ß ratio was found to be ≈ 31 for HDR-90Y and ≈ 3.5 for EBRT. LDR-90Y resulting in insignificant cell death compared to HDR-90Y and EBRT. Simulation results also showed for LDR-90Y, for doses ≲ 3 Gy, the average number of hits per cell nucleus is ≲ 2 indicating insufficiently delivered lethal dose. For 90Y doses [Formula: see text] 3 Gy the number of hits per nucleus decreases rapidly and falls below ≈ 2 after ≈ 5 days of incubation time. Therefore, our results demonstrate that LDR-90Y is radiobiologically less effective than EBRT. However, HDR-90Y at ≈ 56 Gy was found to be radiobiologically as effective as acute ≈ 8 Gy EBRT. CONCLUSION: These results demonstrate that the efficacy of RNT is dependent on the initial dose rate at which radiation is delivered. Therefore, for a relatively long half-life radionuclide such as 90Y, a higher initial activity is required to achieve an outcome as effective as EBRT.

A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis.

Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients' survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.