Nanoscale chemical imaging with structured X-ray illumination.

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

Capturing dynamical correlations using implicit neural representations.

Understanding the nature and origin of collective excitations in materials is of fundamental importance for unraveling the underlying physics of a many-body system. Excitation spectra are usually obtained by measuring the dynamical structure factor, S(Q, ω), using inelastic neutron or x-ray scattering techniques and are analyzed by comparing the experimental results against calculated predictions. We introduce a data-driven analysis tool which leverages 'neural implicit representations' that are specifically tailored for handling spectrographic measurements and are able to efficiently obtain unknown parameters from experimental data via automatic differentiation. In this work, we employ linear spin wave theory simulations to train a machine learning platform, enabling precise exchange parameter extraction from inelastic neutron scattering data on the square-lattice spin-1 antiferromagnet La2NiO4, showcasing a viable pathway towards automatic refinement of advanced models for ordered magnetic systems.

A machine learning photon detection algorithm for coherent x-ray ultrafast fluctuation analysis.

X-ray free electron laser experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely spaced sets of coherent x-ray pulses to be compared after scattering from a dynamic system at different times. This enables the study of fluctuations in many-body quantum systems at the level of the ultrafast pulse durations, but this method has been limited to a select number of examples and required complex and advanced analytical tools. By applying a new methodology to this problem, we have made qualitative advances in three separate areas that will likely also find application to new fields. As compared to the "droplet-type" models, which typically are used to estimate the photon distributions on pixelated detectors to obtain the coherent x-ray speckle patterns, our algorithm achieves an order of magnitude speedup on CPU hardware and two orders of magnitude improvement on GPU hardware. We also find that it retains accuracy in low-contrast conditions, which is the typical regime for many experiments in structural dynamics. Finally, it can predict photon distributions in high average-intensity applications, a regime which up until now has not been accessible. Our artificial intelligence-assisted algorithm will enable a wider adoption of x-ray coherence spectroscopies, by both automating previously challenging analyses and enabling new experiments that were not otherwise feasible without the developments described in this work.

Dynamics of particle network in composite battery cathodes.

Improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding conductive network. We formulate a network evolution model to interpret the regulation and equilibration between electrochemical activity and mechanical damage of these particles. Through statistical analysis of thousands of particles using x-ray phase contrast holotomography in a LiNi0.8Mn0.1Co0.1O2-based cathode, we found that the local network heterogeneity results in asynchronous activities in the early cycles, and subsequently the particle assemblies move toward a synchronous behavior. Our study pinpoints the chemomechanical behavior of individual particles and enables better designs of the conductive network to optimize the utility of all the particles during operation.

A nanofiber based antiviral (TAF) prodrug delivery system.

HIV and hepatitis B are two of the most prevalent viruses globally, and despite readily available preventive treatments unforgiving treatment regimens still exist, such as daily doses of medicine that are challenging to maintain especially in poorer countries. More advanced and longer-lasting delivery vehicles can potentially overcome this problem by reducing maintenance requirements and significantly increase access to medicine. Here, we designed a technology to control the delivery of an antiviral drug over a long timeframe via a nanofiber based delivery scaffold that is both easy to produce and use. An antiviral prodrug containing tenofovir alafenamide (TAF) was synthesized by initial conjugation to glycerol monomethacrylate followed by polymerization to form a diblock copolymer (pTAF) using reversible addition-fragmentation chain transfer (RAFT). In order to generate an efficient drug delivery system this copolymer was fabricated into an electrospun nanofiber (ESF) scaffold using blend electrospinning with poly(caprolactone) (PCL) as the carrier polymer. SEM images revealed that the pTAF-PCL ESFs were uniform with an average diameter of (787 ± 0.212 nm), while XPS analysis demonstrated that the pTAF was overrepresented at the surface of the ESFs. Additionally, the pTAF exhibited a sustained release profile over a 2 month period in human serum (HS), suggesting that these types of copolymer-based drugamers can be used in conjunction with electrospinning to produce long-lasting drug delivery systems.

CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images.

Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D electron scattering potential of a biomolecule from millions of extremely noisy 2D images. Existing reconstruction algorithms, however, cannot easily keep pace with the rapidly growing size of cryo-EM datasets due to their high computational and memory cost. We introduce cryoAI, an ab initio reconstruction algorithm for homogeneous conformations that uses direct gradient-based optimization of particle poses and the electron scattering potential from single-particle cryo-EM data. CryoAI combines a learned encoder that predicts the poses of each particle image with a physics-based decoder to aggregate each particle image into an implicit representation of the scattering potential volume. This volume is stored in the Fourier domain for computational efficiency and leverages a modern coordinate network architecture for memory efficiency. Combined with a symmetrized loss function, this framework achieves results of a quality on par with state-of-the-art cryo-EM solvers for both simulated and experimental data, one order of magnitude faster for large datasets and with significantly lower memory requirements than existing methods.

Automated prediction of lattice parameters from X-ray powder diffraction patterns.

A key step in the analysis of powder X-ray diffraction (PXRD) data is the accurate determination of unit-cell lattice parameters. This step often requires significant human intervention and is a bottleneck that hinders efforts towards automated analysis. This work develops a series of one-dimensional convolutional neural networks (1D-CNNs) trained to provide lattice parameter estimates for each crystal system. A mean absolute percentage error of approximately 10% is achieved for each crystal system, which corresponds to a 100- to 1000-fold reduction in lattice parameter search space volume. The models learn from nearly one million crystal structures contained within the Inorganic Crystal Structure Database and the Cambridge Structural Database and, due to the nature of these two complimentary databases, the models generalize well across chemistries. A key component of this work is a systematic analysis of the effect of different realistic experimental non-idealities on model performance. It is found that the addition of impurity phases, baseline noise and peak broadening present the greatest challenges to learning, while zero-offset error and random intensity modulations have little effect. However, appropriate data modification schemes can be used to bolster model performance and yield reasonable predictions, even for data which simulate realistic experimental non-idealities. In order to obtain accurate results, a new approach is introduced which uses the initial machine learning estimates with existing iterative whole-pattern refinement schemes to tackle automated unit-cell solution.

A macrophage-targeted platform for extending drug dosing with polymer prodrugs for pulmonary infection prophylaxis.

Pulmonary melioidosis is a bacterial disease with high morbidity and a mortality rate that can be as high as 40% in resource-poor regions of South Asia. This disease burden is linked to the pathogen's intrinsic antibiotic resistance and protected intracellular localization in alveolar macrophages. Current treatment regimens require several antibiotics with multi-month oral and intravenous administrations that are difficult to implement in under-resourced settings. Herein, we report that a macrophage-targeted polyciprofloxacin prodrug acts as a surprisingly effective pre-exposure prophylactic in highly lethal murine models of aerosolized human pulmonary melioidosis. A single dose of the polymeric prodrug maintained high lung drug levels and targeted an intracellular depot of ciprofloxacin to the alveolar macrophage compartment that was sustained over a period of 7 days above minimal inhibitory concentrations. This intracellular pharmacokinetic profile provided complete pre-exposure protection in a BSL-3 model with an aerosolized clinical isolate of Burkholderia pseudomallei from Thailand. This total protection was achieved despite the bacteria's relative resistance to ciprofloxacin and where an equivalent dose of pulmonary-administered ciprofloxacin was ineffective. For the first time, we demonstrate that targeting the intracellular macrophage compartment with extended antibiotic dosing can achieve pre-exposure prophylaxis in a model of pulmonary melioidosis. This fully synthetic and modular therapeutic platform could be an important therapeutic approach with new or re-purposed antibiotics for melioidosis prevention and treatment, especially as portable inhalation devices in high-risk, resource-poor settings.

Mannose Conjugated Polymer Targeting P. aeruginosa Biofilms.

Biofilms are one of the most challenging obstacles in bacterial infections. By providing protection against immune responses and antibiotic therapies, biofilms enable chronic colonization and the development of antibiotic resistance. As previous clinical observations and studies have shown, traditional antibiotic therapy alone cannot effectively treat and eliminate biofilm forming infections due to the protection conferred by the biofilm. A new strategy specifically targeting biofilms must be developed. Here, we specifically target and bind to the PAO1 biofilm and elucidate the molecular mechanism behind the interaction between a glycan targeted polymer and biofilm using a continuous flow biofilm model. The incubation of biofilms with fluorescent glycan targeted polymers demonstrated strong and persistent interactions with the mannose-containing polymer even after 24 h of continuous flow. To evaluate the role of major biofilm proteins LecB and CdrA, loss of function experiments with knockout variants established the dual involvement of both proteins in mannose targeted polymer retention. These results identify a persistent and specific targeting strategy to the biofilm, emphasizing its potential value as a delivery strategy and encouraging further exploration of biofilm targeted delivery.

Temporal X-ray Reconstruction using Temporal and Spectral Measurements at LCLS.

Transverse deflecting structures (TDSs) are widely used in accelerator physics to measure the longitudinal density of particle bunches. When used in combination with a dispersive section, the whole longitudinal phase space density can be imaged. At the Linac Coherent Light Source (LCLS), the installation of such a device downstream of the undulators enables the reconstruction of the X-ray temporal intensity profile by comparing longitudinal phase space distributions with lasing on and lasing off. However, the resolution of this TDS is limited to around 1 fs rms (root mean square), and therefore, it is not possible to resolve single self-amplified spontaneous emission (SASE) spikes within an X-ray photon pulse. By combining the power spectrum from a high resolution photon spectrometer and the temporal structure from the TDS, the overall resolution is enhanced, thus allowing the observation of temporal, single SASE spikes. The combined data from the spectrometer and the TDS is analysed using an iterative algorithm to obtain the actual intensity profile. In this paper, we present some improvements to the reconstruction algorithm as well as real data taken at LCLS.

Laguerre-Gaussian Mode Laser Heater for Microbunching Instability Suppression in Free-Electron Lasers.

Microbunching instability (MBI) driven by beam collective effects is known to be detrimental to high-brightness storage rings, linacs, and free-electron lasers (FELs). One known way to suppress this instability is to induce a small amount of energy spread to an electron beam by a laser heater. The distribution of the induced energy spread greatly affects MBI suppression and can be controlled by shaping the transverse profile of the heater laser. Here, we present the first experimental demonstration of effective MBI suppression using a LG_{01} transverse laser mode and compare the improved results with respect to traditional Gaussian transverse laser mode at the Linac Coherent Light Source. The effects on MBI suppression are characterized by multiple downstream measurements, including longitudinal phase space analysis and coherent radiation spectroscopy. We also discuss the role of LG_{01} shaping in soft x-ray self-seeded FEL emission, one of the most advanced operation modes of a FEL for which controlled suppression of MBI is critical.

What are the advantages of ghost imaging? Multiplexing for x-ray and electron imaging.

Ghost imaging, Fourier transform spectroscopy, and the newly developed Hadamard transform crystallography are all examples of multiplexing measurement strategies. Multiplexed experiments are performed by measuring multiple points in space, time, or energy simultaneously. This contrasts to the usual method of systematically scanning single points. How do multiplexed measurements work and when they are advantageous? Here we address these questions with a focus on applications involving x-rays or electrons. We present a quantitative framework for analyzing the expected error and radiation dose of different measurement scheme that enables comparison. We conclude that in very specific situations, multiplexing can offer improvements in resolution and signal-to-noise. If the signal has a sparse representation, these advantages become more general and dramatic, and further less radiation can be used to complete a measurement.

Attosecond transient absorption spooktroscopy: a ghost imaging approach to ultrafast absorption spectroscopy.

The recent demonstration of isolated attosecond pulses from an X-ray free-electron laser (XFEL) opens the possibility for probing ultrafast electron dynamics at X-ray wavelengths. An established experimental method for probing ultrafast dynamics is X-ray transient absorption spectroscopy, where the X-ray absorption spectrum is measured by scanning the central photon energy and recording the resultant photoproducts. The spectral bandwidth inherent to attosecond pulses is wide compared to the resonant features typically probed, which generally precludes the application of this technique in the attosecond regime. In this paper we propose and demonstrate a new technique to conduct transient absorption spectroscopy with broad bandwidth attosecond pulses with the aid of ghost imaging, recovering sub-bandwidth resolution in photoproduct-based absorption measurements.

Label-free biosensing with a multi-box sub-wavelength phase-shifted Bragg grating waveguide.

Sub-wavelength grating (SWG) metamaterials have been considered to provide promising solutions in the development of next-generation photonic integrated circuits. In recent years, increasied interest has been paid to silicon photonic planar biosensors based on SWG geometries for performance enhancement. In this work, we demonstrate a highly sensitive label-free phase-shifted Bragg grating (PSBG) sensing configuration, which consists of sub-wavelength block arrays in both propagation and transverse directions. By introducing salt serial dilutions and electrostatic polymers assays, bulk and surface sensitivities of the proposed sensor are characterized, obtaining measured results up to 579.2 nm/RIU and 1914 pm/nm, respectively. Moreover, the proposed multi-box PSBG sensor presents an improved quality factor as high as ∼ 8000 , roughly 3-fold of the microring-based counterpart, which further improves the detection limit. At last, by employing a biotin-streptavidin affinity assay, the capability for small molecule monitoring is exemplified with a minimum detectable concentration of biotin down to 2.28 × 10 - 8 M .

Erratum: Luan, E.X.; Shoman, H.; Ratner, D.M.; Cheung, K.C.; Chrostowski, L. Silicon Photonic Biosensors Using Label-Free Detection. Sensors 2018, 18, 3519.

The authors wish to make the following corrections in their published paper in Sensors [...].

Glycan targeted polymeric antibiotic prodrugs for alveolar macrophage infections.

Alveolar macrophages resident in the lung are prominent phagocytic effector cells of the pulmonary innate immune response, and paradoxically, are attractive harbors for pathogens. Consequently, facultative intracellular bacteria, such as Francisella tularensis, can cause severe systemic disease and sepsis, with high morbidity and mortality associated with pulmonary infection. Current clinical treatment, which involves exhaustive oral or intravenous antibiotic therapy, has limitations such as systemic toxicity and off-target effects. Pulmonary administration represents a promising alternative to systemic dosing for delivering antibiotics directly to the lung. Here, we present synthesized mannosylated ciprofloxacin polymeric prodrugs for efficient pulmonary delivery, targeting, and subsequent internalization by alveolar macrophages. We demonstrate significant improvement in efficacy against intracellular infections in an otherwise uniformly lethal airborne Francisella murine model (F. novicida). When administered to the lungs of mice in a prophylactic regimen, the mannosylated ciprofloxacin polymeric prodrugs led to 50% survival. In a treatment regimen that was concurrent with infection, the survival of mice increased to 87.5%. Free ciprofloxacin antibiotic was ineffective in both cases. This significant difference in antibacterial efficacy demonstrates the impact of this delivery platform based on improved physiochemical, pharmacokinetic, and pharmacodynamic properties of ciprofloxacin administered via our glycan polymeric prodrug. This modular platform provides a route for overcoming the limitations of free drug and increasing efficacy in treatment of intracellular infection.

Silicon Photonic Biosensors Using Label-Free Detection.

Thanks to advanced semiconductor microfabrication technology, chip-scale integration and miniaturization of lab-on-a-chip components, silicon-based optical biosensors have made significant progress for the purpose of point-of-care diagnosis. In this review, we provide an overview of the state-of-the-art in evanescent field biosensing technologies including interferometer, microcavity, photonic crystal, and Bragg grating waveguide-based sensors. Their sensing mechanisms and sensor performances, as well as real biomarkers for label-free detection, are exhibited and compared. We also review the development of chip-level integration for lab-on-a-chip photonic sensing platforms, which consist of the optical sensing device, flow delivery system, optical input and readout equipment. At last, some advanced system-level complementary metal-oxide semiconductor (CMOS) chip packaging examples are presented, indicating the commercialization potential for the low cost, high yield, portable biosensing platform leveraging CMOS processes.

Macrophage-targeted drugamers with enzyme-cleavable linkers deliver high intracellular drug dosing and sustained drug pharmacokinetics against alveolar pulmonary infections.

Intracellular bacterial infections localized to the lung alveolar macrophage (AM) remain one of the most challenging settings for antimicrobial therapy. Current systemic antibiotic treatment fails to deliver sustained doses to intracellular bacterial reservoirs, which necessitates prolonged treatment regimens. Herein, we demonstrate a new intracellular enzyme-cleavable polymeric prodrug with tailored ciprofloxacin release profiles in the lungs and AM. The targeted polymeric prodrug, termed "drugamers", incorporates (1) hydrophilic mannose residues to solubilize the antibiotic cargo and to target and enhance AM uptake and intracellular delivery, and (2) enzyme-cleavable linkage chemistry to provide high and sustained intracellular AM drug dosing. Prodrug monomers, derived from the antibiotic ciprofloxacin, were synthesized with either an intracellular protease cleavable dipeptide linker or a hydrolytic phenyl ester linker. RAFT polymerization was used to copolymerize the prodrug monomers and mannose monomer to synthesize well-defined drugamers without requiring a post-polymerization conjugation step. In addition to favorable in vivo safety profiles following intratracheal administration, a single dose of the drugamers sustained ciprofloxacin dosing in lungs and AMs above the minimum inhibitory concentration (MIC) over at least a 48 h period. The enzyme-cleavable therapeutic achieved a >10-fold increase in sustained ciprofloxacin in AM, and maintained a significantly higher whole lung PK as well. Ciprofloxacin dosed in identical fashion displayed rapid clearance with a half-life of approximately 30 min. Notably, inhalation of the mannose-targeted ciprofloxacin drugamers achieved full survival (100%) in a highly lethal mouse model of pneumonic tularemia, contrasted with 0% survival using free ciprofloxacin. These findings demonstrate the versatility of the drugamer platform for engineering the intracellular pharmacokinetic profiles and its strong therapeutic activity in treating pulmonary intracellular infections.

Polymer-augmented liposomes enhancing antibiotic delivery against intracellular infections.

Pulmonary intracellular infections, such as tuberculosis, anthrax, and tularemia, have remained a significant challenge to conventional antibiotic therapy. Ineffective antibiotic treatment of these infections can lead not only to undesired side effects, but also to the emergence of antibiotic resistance. Aminoglycosides (e.g., streptomycin) have long been part of the therapeutic regiment for many pulmonary intracellular infections. Their bioavailability for intracellular bacterial pools, however, is limited by poor membrane permeability and rapid elimination. To address this challenge, polymer-augmented liposomes (PALs) were developed to provide improved cytosolic delivery of streptomycin to alveolar macrophages, an important host cell for intracellular pathogens. A multifunctional diblock copolymer was engineered to functionalize PALs with carbohydrate-mediated targeting, pH-responsive drug release, and endosomal release activity with a single functional polymer that replaces the pegylated lipid component to simplify the liposome formulation. The pH-sensing functionality enabled PALs to provide enhanced release of streptomycin under endosomal pH conditions (70% release in 6 hours) with limited release at physiological pH 7.4 (16%). The membrane-destabilizing activity connected to endosomal release was characterized in a hemolysis assay and PALs displayed a sharp pH profile across the endosomal pH development target range. The direct connection of this membrane-destabilizing pH profile to model drug release was demonstrated in an established pyranine/p-xylene bispyridinium dibromide (DPX) fluorescence dequenching assay. PALs displayed similar sharp pH-responsive release, whereas PEGylated control liposomes did not, and similar profiles were then shown for streptomycin release. The mannose-targeting capability of the PALs was also demonstrated with 2.5 times higher internalization compared to non-targeted PEGylated liposomes. Finally, the streptomycin-loaded PALs were shown to have a significantly improved intracellular antibacterial activity in a Francisella-macrophage co-culture model, compared with free streptomycin or streptomycin delivered by control PEGylated liposomes (13× and 16×, respectively). This study suggests the potential of PALs as a useful platform to deliver antibiotics for the treatment of intracellular macrophage infections.

Synthetic Macromolecular Antibiotic Platform for Inhalable Therapy against Aerosolized Intracellular Alveolar Infections.

Lung-based intracellular bacterial infections remain one of the most challenging infectious disease settings. For example, the current standard for treating Franciscella tularensis pneumonia (tularemia) relies on administration of oral or intravenous antibiotics that poorly achieve and sustain pulmonary drug bioavailability. Inhalable antibiotic formulations are approved and in clinical development for upper respiratory infections, but sustained drug dosing from inhaled antibiotics against alveolar intracellular infections remains a current unmet need. To provide an extended therapy against alveolar intracellular infections, we have developed a macromolecular therapeutic platform that provides sustained local delivery of ciprofloxacin with controlled dosing profiles. Synthesized using RAFT polymerization, these macromolecular prodrugs characteristically have high drug loading (16-17 wt % drug), tunable hydrolysis kinetics mediated by drug linkage chemistry (slow-releasing alkyllic vs fast-releasing phenolic esters), and, in general, represent new fully synthetic nanotherapeutics with streamlined manufacturing profiles. In aerosolized and completely lethal F.t. novicida mouse challenge models, the fast-releasing ciprofloxacin macromolecular prodrug provided high cure efficiencies (75% survival rate under therapeutic treatment), and the importance of release kinetics was demonstrated by the inactivity of the similar but slow-releasing prodrug system. Pharmacokinetics and biodistribution studies further demonstrated that the efficacious fast-releasing prodrug retained drug dosing in the lung above the MIC over a 48 h period with corresponding Cmax/MIC and AUC0-24h/MIC ratios being greater than 10 and 125, respectively; the thresholds for optimal bactericidal efficacy. These findings identify the macromolecular prodrug platform as a potential therapeutic system to better treat alveolar intracellular infections such as F. tularensis, where positive patient outcomes require tailored antibiotic pharmacokinetic and treatment profiles.