A Platform To Enhance Quantitative Single Molecule Localization Microscopy.

Quantitative single molecule localization microscopy (qSMLM) is a powerful approach to study in situ protein organization. However, uncertainty regarding the photophysical properties of fluorescent reporters can bias the interpretation of detected localizations and subsequent quantification. Furthermore, strategies to efficiently detect endogenous proteins are often constrained by label heterogeneity and reporter size. Here, a new surface assay for molecular isolation (SAMI) was developed for qSMLM and used to characterize photophysical properties of fluorescent proteins and dyes. SAMI-qSMLM afforded robust quantification. To efficiently detect endogenous proteins, we used fluorescent ligands that bind to a specific site on engineered antibody fragments. Both the density and nano-organization of membrane-bound epidermal growth factor receptors (EGFR, HER2, and HER3) were determined by a combination of SAMI, antibody engineering, and pair-correlation analysis. In breast cancer cell lines, we detected distinct differences in receptor density and nano-organization upon treatment with therapeutic agents. This new platform can improve molecular quantification and can be developed to study the local protein environment of intact cells.

Enzymatic synthesis of magnetic nanoparticles.

We report the first in vitro enzymatic synthesis of paramagnetic and antiferromagnetic nanoparticles toward magnetic ELISA reporting. With our procedure, alkaline phosphatase catalyzes the dephosphorylation of l-ascorbic-2-phosphate, which then serves as a reducing agent for salts of iron, gadolinium, and holmium, forming magnetic precipitates of Fe45±14Gd5±2O50±15 and Fe42±4Ho6±4O52±5. The nanoparticles were found to be paramagnetic at 300 K and antiferromagnetic under 25 K. Although weakly magnetic at 300 K, the room-temperature magnetization of the nanoparticles found here is considerably greater than that of analogous chemically-synthesized LnxFeyOz (Ln = Gd, Ho) samples reported previously. At 5 K, the nanoparticles showed a significantly higher saturation magnetization of 45 and 30 emu/g for Fe45±14Gd5±2O50±15 and Fe42±4Ho6±4O52±5, respectively. Our approach of enzymatically synthesizing magnetic labels reduces the cost and avoids diffusional mass-transfer limitations associated with pre-synthesized magnetic reporter particles, while retaining the advantages of magnetic sensing.

Using quantitative single molecule localization microscopy to optimize multivalent HER2-targeting ligands.

Introduction: The progression-free survival of patients with HER2-positive metastatic breast cancer is significantly extended by a combination of two monoclonal antibodies, trastuzumab and pertuzumab, which target independent epitopes of the extracellular domain of HER2. The improved efficacy of the combination over individual antibody therapies targeting HER2 is still being investigated, and several molecular mechanisms may be in play: the combination downregulates HER2, improves antibody-dependent cell mediated cytotoxicity, and/or affects the organization of surface-expressed antigens, which may attenuate downstream signaling. Methods: By combining protein engineering and quantitative single molecule localization microscopy (qSMLM), here we both assessed and optimized clustering of HER2 in cultured breast cancer cells. Results: We detected marked changes to the cellular membrane organization of HER2 when cells were treated with therapeutic antibodies. When we compared untreated samples to four treatment scenarios, we observed the following HER2 membrane features: (1) the monovalent Fab domain of trastuzumab did not significantly affect HER2 clustering; (2) individual therapy with either trastuzumab or (3) pertuzumab produced significantly higher levels of HER2 clustering; (4) a combination of trastuzumab plus pertuzumab produced the highest level of HER2 clustering. To further enhance this last effect, we created multivalent ligands using meditope technology. Treatment with a tetravalent meditope ligand combined with meditope-enabled trastuzumab resulted in pronounced HER2 clustering. Moreover, compared to pertuzumab plus trastuzumab, at early time points this meditope-based combination was more effective at inhibiting epidermal growth factor (EGF) dependent activation of several downstream protein kinases. Discussion: Collectively, mAbs and multivalent ligands can efficiently alter the organization and activation of the HER2 receptors. We expect this approach could be used in the future to develop new therapeutics.

Predictions of cognitive detriments from galactic cosmic ray exposures to astronauts on exploration missions.

For the first-time we report on predictions on cognitive detriments from galactic cosmic ray (GCR) exposures on long-duration space missions outside the protection of the Earth's magnetosphere and solid body shielding. Estimates are based on a relative risk (RR) model of the fluence response for proton and heavy ion in rodent studies using the widely used novel object recognition (NOR) test, which estimates detriments in recognition or object memory. Our recent meta-analysis showed that linear and linear-quadratic dose response models were not accurate, while exponential increasing fluence response models based on particle track structure provided good descriptions of rodent data for doses up to 1 Gy. Using detailed models of the GCR environment and particle transport in shielding and tissue, we predict the excess relative risk (ERR) for NOR detriments for several long-term space mission scenarios. Predictions suggest ERR < 0.15 for most space mission scenarios with ERR<0.1 for 1-year lunar surface missions, and about ERR~0.1 for a 1000 day Mars mission for average solar cycle conditions. We discuss possible implications of these ERR levels of cognitive performance detriments relative to other neurological challenges such as rodent models of Alzheimer's disease (AD), Parkinson's disease (PD) and traumatic brain injury (TBI). Comparisons suggest a small but potentially clinically significant risk for possible space mission scenarios.

Benchmarking risk predictions and uncertainties in the NSCR model of GCR cancer risks with revised low let risk coefficients.

We report on the contributions of model factors that appear in projection models to the overall uncertainty in cancer risks predictions for exposures to galactic cosmic ray (GCR) in deep space, including comparisons with revised low LET risks coefficients. Annual GCR exposures to astronauts at solar minimum are considered. Uncertainties in low LET risk coefficients, dose and dose-rate modifiers, quality factors (QFs), space radiation organ doses, non-targeted effects (NTE) and increased tumor lethality at high LET compared to low LET radiation are considered. For the low LET reference radiation parameters we use a revised assessment of excess relative risk (ERR) and excess additive risk (EAR) for radiation induced cancers in the Life-Span Study (LSS) of the Atomic bomb survivors that was recently reported, and also consider ERR estimates for males from the International Study of Nuclear Workers (INWORKS). For 45-y old females at mission age the risk of exposure induced death (REID) per year and 95% confidence intervals is predicted as 1.6% [0.71, 1.63] without QF uncertainties and 1.64% [0.69, 4.06] with QF uncertainties. However, fatal risk predictions increase to 5.83% [2.56, 9.7] based on a sensitivity study of the inclusion of non-targeted effects on risk predictions. For males a comparison using LSS or INWORKS lead to predictions of 1.24% [0.58, 3.14] and 2.45% [1.23, 5.9], respectively without NTEs. The major conclusion of our report is that high LET risk prediction uncertainties due to QFs parameters, NTEs, and possible increase lethality at high LET are dominant contributions to GCR uncertainties and should be the focus of space radiation research.

Risks of cognitive detriments after low dose heavy ion and proton exposures.

Purpose: Heavy ion and proton brain irradiations occur during space travel and in Hadron therapy for cancer. Heavy ions produce distinct patterns of energy deposition in neuron cells and brain tissues compared to X-rays leading to large uncertainties in risk estimates. We make a critical review of findings from research studies over the last 25 years for understanding risks at low dose. Conclusions: A large number of mouse and rat cognitive testing measures have been reported for a variety of particle species and energies for acute doses. However, tissue reactions occur above dose thresholds and very few studies were performed at the heavy ion doses to be encountered on space missions (<0.04 Gy/y) or considered dose-rate effects, such that threshold doses are not known in rodent models. Investigations of possible mechanisms for cognitive changes have been limited by experimental design with largely group specific and not subject specific findings reported. Persistent oxidative stress and activated microglia cells are common mechanisms studied, while impairment of neurogenesis, detriments in neuron morphology, and changes to gene and protein expression were each found to be important in specific studies. Future research should focus on estimating threshold doses carried out with experimental designs aimed at understating causative mechanisms, which will be essential for extrapolating rodent findings to humans and chronic radiation scenarios, while establishing if mitigation are needed.

Meta-analysis of Cognitive Performance by Novel Object Recognition after Proton and Heavy Ion Exposures.

Experimental studies of cognitive detriments in mice and rats after proton and heavy ion exposures have been performed by several laboratories to investigate possible risks to astronauts exposed to cosmic rays in space travel and patients treated for brain cancers with proton and carbon beams in Hadron therapy. However, distinct radiation types and doses, cognitive tests and rodent models have been used by different laboratories, while few studies have considered detailed dose-response characterizations, including estimates of relative biological effectiveness (RBE). Here we report on the first quantitative meta-analysis of the dose response for proton and heavy ion rodent studies of the widely used novel object recognition (NOR) test, which estimates detriments in recognition or object memory. Our study reveals that linear or linear-quadratic dose-response models of relative risk (RR) do not provide accurate descriptions. However, good descriptions for doses up to 1 Gy are provided by exponentially increasing fluence or dose-response models observed with an LET dependence similar to a classical radiation quality response, which peaks near 100-120 keV/µm and declines at higher LET values. Exponential models provide accurate predictions of experimental results for NOR in mice after mixed-beam exposures of protons and 56Fe, and protons, 16O and 28Si. RBE estimates are limited by available X-ray or gamma-ray experiments to serve as a reference radiation. RBE estimates based on use of data from combined gamma-ray and high-energy protons of low-LET experiments suggest modest RBEs, with values <8 for most heavy ions, while higher values <20 are based on limited gamma-ray data. In addition, we consider a log-normal model for the variation of subject responses at defined dose levels. The log-normal model predicts a heavy ion dose threshold of approximately 0.01 Gy for NOR-related cognitive detriments.

NON-TARGETED EFFECTS LEAD TO A PARIDIGM SHIFT IN RISK ASSESSMENT FOR A MISSION TO THE EARTH'S MOON OR MARTIAN MOON PHOBOS.

Cancer risk is an important limitation for galactic cosmic ray (GCR) exposures, which consist of a wide-energy range of protons, heavy ions and secondary radiation produced in shielding and tissues. Many studies suggest non-targeted effects (NTEs) occur for low doses of high-linear energy transfer (LET) radiation, leading to deviation from the linear dose response model used in radiation protection. We investigate corrections to quality factors (QF) for NTEs, which are used in predictions of fatal cancer risks for exploration missions. Prediction of fatal cancer risks for missions to the Martian moon, Phobos of 500-d and the Earth's moon of 365-d for average solar minimum condition show increases of 2- to 4-fold higher in the NTE model compared with the conventional model. Limitations in estimating uncertainties in NTE model parameters due to sparse radiobiology data at low doses are discussed.

Modeling Reveals the Dependence of Hippocampal Neurogenesis Radiosensitivity on Age and Strain of Rats.

Cognitive dysfunction following radiation treatment for brain cancers in both children and adults have been correlated to impairment of neurogenesis in the hippocampal dentate gyrus. Various species and strains of rodent models have been used to study radiation-induced changes in neurogenesis and these investigations have utilized only a limited number of doses, dose-fractions, age and time after exposures conditions. In this paper, we have extended our previous mathematical model of radiation-induced hippocampal neurogenesis impairment of C57BL/6 mice to delineate the time, age, and dose dependent alterations in neurogenesis of a diverse strain of rats. To the best of our knowledge, this is the first predictive mathematical model to be published about hippocampal neurogenesis impairment for a variety of rat strains after acute or fractionated exposures to low linear energy transfer (low LET) radiation, such as X-rays and γ-rays, which are conventionally used in cancer radiation therapy. We considered four compartments to model hippocampal neurogenesis and its impairment following radiation exposures. Compartments include: (1) neural stem cells (NSCs), (2) neuronal progenitor cells or neuroblasts (NB), (3) immature neurons (ImN), and (4) glioblasts (GB). Additional consideration of dose and time after irradiation dependence of microglial activation and a possible shift of NSC proliferation from neurogenesis to gliogenesis at higher doses is established. Using a system of non-linear ordinary differential equations (ODEs), characterization of rat strain and age-related dynamics of hippocampal neurogenesis for unirradiated and irradiated conditions is developed. The model is augmented with the description of feedback regulation on early and late neuronal proliferation following radiation exposure. Predictions for dose-fraction regimes compared to acute radiation exposures, along with the dependence of neurogenesis sensitivity to radiation on age and strain of rats are discussed. A major result of this work is predictions of the rat strain and age dependent differences in radiation sensitivity and sub-lethal damage repair that can be used for predictions for arbitrary dose and dose-fractionation schedules.

Stochastic Modeling of Radiation-induced Dendritic Damage on in silico Mouse Hippocampal Neurons.

Cognitive dysfunction associated with radiotherapy for cancer treatment has been correlated to several factors, one of which is changes to the dendritic morphology of neuronal cells. Alterations in dendritic geometry and branching patterns are often accompanied by deficits that impact learning and memory. The purpose of this study is to develop a novel predictive model of neuronal dendritic damages caused by exposure to low linear energy transfer (LET) radiation, such as X-rays, γ-rays and high-energy protons. We established in silico representations of mouse hippocampal dentate granule cell layer (GCL) and CA1 pyramidal neurons, which are frequently examined in radiation-induced cognitive decrements. The in silico representations are used in a stochastic model that describes time dependent dendritic damage induced by exposure to low LET radiation. Changes in morphometric parameters, such as total dendritic length, number of branch points and branch number, including the Sholl analysis for single neurons are described by the model. Our model based predictions for different patterns of morphological changes based on energy deposition in dendritic segments (EDDS) will serve as a useful basis to compare specific patterns of morphological alterations caused by EDDS mechanisms.

Non-Targeted Effects Models Predict Significantly Higher Mars Mission Cancer Risk than Targeted Effects Models.

Cancer risk is an important concern for galactic cosmic ray (GCR) exposures, which consist of a wide-energy range of protons, heavy ions and secondary radiation produced in shielding and tissues. Relative biological effectiveness (RBE) factors for surrogate cancer endpoints in cell culture models and tumor induction in mice vary considerable, including significant variations for different tissues and mouse strains. Many studies suggest non-targeted effects (NTE) occur for low doses of high linear energy transfer (LET) radiation, leading to deviation from the linear dose response model used in radiation protection. Using the mouse Harderian gland tumor experiment, the only extensive data-set for dose response modelling with a variety of particle types (>4), for the first-time a particle track structure model of tumor prevalence is used to investigate the effects of NTEs in predictions of chronic GCR exposure risk. The NTE model led to a predicted risk 2-fold higher compared to a targeted effects model. The scarcity of data with animal models for tissues that dominate human radiation cancer risk, including lung, colon, breast, liver, and stomach, suggest that studies of NTEs in other tissues are urgently needed prior to long-term space missions outside the protection of the Earth's geomagnetic sphere.

Predictions of space radiation fatality risk for exploration missions.

In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. POPULATION: The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits.

Modeling Impaired Hippocampal Neurogenesis after Radiation Exposure.

Radiation impairment of neurogenesis in the hippocampal dentate gyrus is one of several factors associated with cognitive detriments after treatment of brain cancers in children and adults with radiation therapy. Mouse models have been used to study radiation-induced changes in neurogenesis, however the models are limited in the number of doses, dose fractions, age and time after exposure conditions that have been studied. The purpose of this study is to develop a novel predictive mathematical model of radiation-induced changes to neurogenesis using a system of nonlinear ordinary differential equations (ODEs) to represent the time, age and dose-dependent changes to several cell populations participating in neurogenesis as reported in mouse experiments exposed to low-LET radiation. We considered four compartments to model hippocampal neurogenesis and, consequently, the effects of radiation treatment in altering neurogenesis: (1) neural stem cells (NSCs), (2) neuronal progenitor cells or neuroblasts (NB), (3) immature neurons (ImN) and (4) glioblasts (GB). Because neurogenesis is decreasing with increasing mouse age, a description of the age-related dynamics of hippocampal neurogenesis is considered in the model, which is shown to be an important factor in comparisons to experimental data. A key feature of the model is the description of negative feedback regulation on early and late neuronal proliferation after radiation exposure. The model is augmented with parametric descriptions of the dose and time after irradiation dependences of activation of microglial cells and a possible shift of NSC proliferation from neurogenesis to gliogenesis reported at higher doses (∼10 Gy). Predictions for dose-fractionation regimes and for different mouse ages, and prospects for future work are then discussed.

Modeling Heavy-Ion Impairment of Hippocampal Neurogenesis after Acute and Fractionated Irradiation.

Radiation-induced impairment of neurogenesis in the hippocampal dentate gyrus is a concern due to its reported association with cognitive detriments after radiotherapy for brain cancers and the possible risks to astronauts chronically exposed to space radiation. Here, we have extended our recent work in a mouse model of impaired neurogenesis after exposure to low-linear energy transfer (LET) radiation to heavy ion irradiation. To our knowledge, this is the first report of a predictive mathematical model of radiation-induced changes to neurogenesis for a variety of radiation types after acute or fractionated irradiation. We used a system of nonlinear ordinary differential equations (ODEs) to represent age, time after exposure and dose-dependent changes to several cell populations participating in neurogenesis, as reported in mouse experiments. We considered four compartments to model hippocampal neurogenesis and, consequently, the effects of radiation in altering neurogenesis: 1. neural stem cells (NSCs); 2. neuronal progenitor cells or neuroblasts (NB); 3. immature neurons (ImN); and 4. glioblasts (GB), with additional consideration of microglial activation. The model describes the negative feedback regulation on early and late neuronal proliferation after irradiation, and the dynamics of the age dependence of neurogenesis. We compared our model to experimental data for X rays, and protons, carbon and iron particles, including data for fractionated iron-particle irradiation. Heavy-ion irradiation is predicted to lead to poor recovery or no recovery from impaired neurogenesis at doses as low as 0.5 Gy in mice. This is only partially ameliorated by dose fractionation, which suggests important implications for Hardon therapy near the Bragg peak, and possibly for space radiation exposures as well. Predictions of the threshold doses where neurogenesis recovery fails for given radiation types are described, and the role of subthreshold transient impairments are briefly discussed.

Space Radiation Quality Factors and the Delta Ray Dose and Dose-Rate Reduction Effectiveness Factor.

In this paper, the authors recommend that the dose and dose-rate effectiveness factor used for space radiation risk assessments should be based on a comparison of the biological effects of energetic electrons produced along a cosmic ray particles path in low fluence exposures to high dose-rate gamma-ray exposures of doses of about 1 Gy. Methods to implement this approach are described.

Relative Biological Effectiveness of HZE Particles for Chromosomal Exchanges and Other Surrogate Cancer Risk Endpoints.

The biological effects of high charge and energy (HZE) particle exposures are of interest in space radiation protection of astronauts and cosmonauts, and estimating secondary cancer risks for patients undergoing Hadron therapy for primary cancers. The large number of particles types and energies that makeup primary or secondary radiation in HZE particle exposures precludes tumor induction studies in animal models for all but a few particle types and energies, thus leading to the use of surrogate endpoints to investigate the details of the radiation quality dependence of relative biological effectiveness (RBE) factors. In this report we make detailed RBE predictions of the charge number and energy dependence of RBE's using a parametric track structure model to represent experimental results for the low dose response for chromosomal exchanges in normal human lymphocyte and fibroblast cells with comparison to published data for neoplastic transformation and gene mutation. RBE's are evaluated against acute doses of γ-rays for doses near 1 Gy. Models that assume linear or non-targeted effects at low dose are considered. Modest values of RBE (<10) are found for simple exchanges using a linear dose response model, however in the non-targeted effects model for fibroblast cells large RBE values (>10) are predicted at low doses <0.1 Gy. The radiation quality dependence of RBE's against the effects of acute doses γ-rays found for neoplastic transformation and gene mutation studies are similar to those found for simple exchanges if a linear response is assumed at low HZE particle doses. Comparisons of the resulting model parameters to those used in the NASA radiation quality factor function are discussed.

Harderian Gland Tumorigenesis: Low-Dose and LET Response.

Increased cancer risk remains a primary concern for travel into deep space and may preclude manned missions to Mars due to large uncertainties that currently exist in estimating cancer risk from the spectrum of radiations found in space with the very limited available human epidemiological radiation-induced cancer data. Existing data on human risk of cancer from X-ray and gamma-ray exposure must be scaled to the many types and fluences of radiations found in space using radiation quality factors and dose-rate modification factors, and assuming linearity of response since the shapes of the dose responses at low doses below 100 mSv are unknown. The goal of this work was to reduce uncertainties in the relative biological effect (RBE) and linear energy transfer (LET) relationship for space-relevant doses of charged-particle radiation-induced carcinogenesis. The historical data from the studies of Fry et al. and Alpen et al. for Harderian gland (HG) tumors in the female CB6F1 strain of mouse represent the most complete set of experimental observations, including dose dependence, available on a specific radiation-induced tumor in an experimental animal using heavy ion beams that are found in the cosmic radiation spectrum. However, these data lack complete information on low-dose responses below 0.1 Gy, and for chronic low-dose-rate exposures, and there are gaps in the LET region between 25 and 190 keV/µm. In this study, we used the historical HG tumorigenesis data as reference, and obtained HG tumor data for 260 MeV/u silicon (LET ∼70 keV/µm) and 1,000 MeV/u titanium (LET ∼100 keV/µm) to fill existing gaps of data in this LET range to improve our understanding of the dose-response curve at low doses, to test for deviations from linearity and to provide RBE estimates. Animals were also exposed to five daily fractions of 0.026 or 0.052 Gy of 1,000 MeV/u titanium ions to simulate chronic exposure, and HG tumorigenesis from this fractionated study were compared to the results from single 0.13 or 0.26 Gy acute titanium exposures. Theoretical modeling of the data show that a nontargeted effect model provides a better fit than the targeted effect model, providing important information at space-relevant doses of heavy ions.

Nanoscale effects of ethanol and naltrexone on protein organization in the plasma membrane studied by photoactivated localization microscopy (PALM).

BACKGROUND: Ethanol affects the signaling of several important neurotransmitter and neuromodulator systems in the CNS. It has been recently proposed that ethanol alters the dynamic lateral organization of proteins and lipids in the plasma membrane, thereby affecting surface receptor-mediated cellular signaling. Our aims are to establish whether pharmacologically relevant levels of ethanol can affect the lateral organization of plasma membrane and cytoskeletal proteins at the nanoscopic level, and investigate the relevance of such perturbations for mu-opioid receptor (MOP) function. METHODOLOGY/PRINCIPAL FINDINGS: We used Photoactivated Localization Microscopy with pair-correlation analysis (pcPALM), a quantitative fluorescence imaging technique with high spatial resolution (15-25 nm) and single-molecule sensitivity, to study ethanol effects on protein organization in the plasma membrane. We observed that short (20 min) exposure to 20 and 40 mM ethanol alters protein organization in the plasma membrane of cells that harbor endogenous MOPs, causing a rearrangement of the lipid raft marker glycosylphosphatidylinositol (GPI). These effects could be largely occluded by pretreating the cells with the MOP antagonist naltrexone (200 nM for 3 hours). In addition, ethanol induced pronounced actin polymerization, leading to its partial co-localization with GPI. CONCLUSIONS/SIGNIFICANCE: Pharmacologically relevant levels of ethanol alter the lateral organization of GPI-linked proteins and induce actin cytoskeleton reorganization. Pretreatment with the MOP antagonist naltrexone is protective against ethanol action and significantly reduces the extent to which ethanol remodels the lateral organization of lipid-rafts-associated proteins in the plasma membrane. Super-resolution pcPALM reveals details of ethanol action at the nanoscale level, giving new mechanistic insight on the cellular and molecular mechanisms of its action.

High-resolution, high-throughput, positive-tone patterning of poly(ethylene glycol) by helium beam exposure through stencil masks.

In this work, a collimated helium beam was used to activate a thiol-poly(ethylene glycol) (SH-PEG) monolayer on gold to selectively capture proteins in the exposed regions. Protein patterns were formed at high throughput by exposing a stencil mask placed in proximity to the PEG-coated surface to a broad beam of helium particles, followed by incubation in a protein solution. Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) spectra showed that SH-PEG molecules remain attached to gold after exposure to beam doses of 1.5-60 µC/cm(2) and incubation in PBS buffer for one hour, as evidenced by the presence of characteristic ether and methoxy peaks at 1120 cm(-1) and 2870 cm(-1), respectively. X-ray Photoelectron Spectroscopy (XPS) spectra showed that increasing beam doses destroy ether (C-O) bonds in PEG molecules as evidenced by the decrease in carbon C1s peak at 286.6 eV and increased alkyl (C-C) signal at 284.6 eV. XPS spectra also demonstrated protein capture on beam-exposed PEG regions through the appearance of a nitrogen N1s peak at 400 eV and carbon C1s peak at 288 eV binding energies, while the unexposed PEG areas remained protein-free. The characteristic activities of avidin and horseradish peroxidase were preserved after attachment on beam-exposed regions. Protein patterns created using a 35 µm mesh mask were visualized by localized formation of insoluble diformazan precipitates by alkaline phosphatase conversion of its substrate bromochloroindoyl phosphate-nitroblue tetrazolium (BCIP-NBT) and by avidin binding of biotinylated antibodies conjugated on 100 nm gold nanoparticles (AuNP). Patterns created using a mask with smaller 300 nm openings were detected by specific binding of 40 nm AuNP probes and by localized HRP-mediated deposition of silver nanoparticles. Corresponding BSA-passivated negative controls showed very few bound AuNP probes and little to no enzymatic formation of diformazan precipitates or silver nanoparticles.

Helium beam shadowing for high spatial resolution patterning of antibodies on microstructured diagnostic surfaces.

We have developed a technique for the high-resolution, self-aligning, and high-throughput patterning of antibody binding functionality on surfaces by selectively changing the reactivity of protein-coated surfaces in specific regions of a workpiece with a beam of energetic helium particles. The exposed areas are passivated with bovine serum albumin (BSA) and no longer bind the antigen. We demonstrate that patterns can be formed (1) by using a stencil mask with etched openings that forms a patterned exposure, or (2) by using angled exposure to cast shadows of existing raised microstructures on the surface to form self-aligned patterns. We demonstrate the efficacy of this process through the patterning of anti-lysozyme, anti-Norwalk virus, and anti-Escherichia coli antibodies and the subsequent detection of each of their targets by the enzyme-mediated formation of colored or silver deposits, and also by binding of gold nanoparticles. The process allows for the patterning of three-dimensional structures by inclining the sample relative to the beam so that the shadowed regions remain unaltered. We demonstrate that the resolution of the patterning process is of the order of hundreds of nanometers, and that the approach is well-suited for high throughput patterning.