Enabling Applications of Electromagnetic Waves at 0.3-1.0 THz Using Silicon Electronic Integrated Circuits

Over the past 15 years, the output power of silicon submillimeter-wave electronics has increased by a factor greater than 1000 reaching -3.9 dBm at 440 GHz for a single unit in CMOS and -10.7 dBm at 1.01 THz for a 42-element array in SiGe BiCMOS. The smallest power of a 1 kHz bandwidth signal at 420 GHz that can be detected has improved by 100 million times. These and the expected improvements from the ongoing activities should be sufficient to support high resolution imaging with a range of up to several hundred meters, gas sensing up to ∼1 THz, and communication over ∼1000 m. The silicon IC technologies enable integration of complex systems into a small form factor and reduction of manufacturing cost. When broad deployment of submillimeter wave systems for everyday life applications becomes necessary, the silicon IC infrastructure will be the most capable to support the high-volume manufacturing need.

Enhancing Charge Transport Using Boron and Nitrogen Substitutions into Triphenylene-Based Discotic Liquid Crystals

The substitution of p-block heteroatoms into polyaromatic hydrocarbons offers the potential for introducing enhanced molecular properties and advancing material development for electro-optical applications. Using density functional theory, we characterize the substitution of boron and nitrogen atoms into a 2,3,6,7,10,11-hexakis(hexathiol)triphenylene (TTP) core, a precursor for a material with a discotic liquid crystal phase, to determine the strength of exciton dissociation and the influence doping has on the formation of a heterojunction with graphene. The substitution of nitrogen and boron into the TTP motif enables tunability of both electron and hole coupling between hetero- and homodyads. The coupling is found to far exceed that of TTP and varied transport behavior with different combinations of doped cores of nitrogen-TTP and boron-TTP is reported. Heterodyads of nitrogen-TTP with boron-TTP appear to be ambipolar in electron/hole coupling, whereas heterodyads of boron- or nitrogen-TTP with TTP form strong electron coupling dyads and homodyads of nitrogen-TTP and boron-TTP form strong hole coupling. Finally, we describe the heterojunction of nitrogen- or boron-TTP with monolayer graphene and observe Ohmic contacts with large hole transport barriers. The presence of induced dipoles occurs at the interface in all heterojunctions, suggesting the possibility of tuning the junction with external potentials and improving exciton dissociation.

Interplay between charge distribution and DNA in shaping HP1 paralog phase separation and localization

The heterochromatin protein 1 (HP1) family is a crucial component of heterochromatin with diverse functions in gene regulation, cell cycle control, and cell differentiation. In humans, there are three paralogs, HP1α, HP1β, and HP1γ, which exhibit remarkable similarities in their domain architecture and sequence properties. Nevertheless, these paralogs display distinct behaviors in liquid-liquid phase separation (LLPS), a process linked to heterochromatin formation. Here, we employ a coarse-grained simulation framework to uncover the sequence features responsible for the observed differences in LLPS. We highlight the significance of the net charge and charge patterning along the sequence in governing paralog LLPS propensities. We also show that both highly conserved folded and less-conserved disordered domains contribute to the observed differences. Furthermore, we explore the potential co-localization of different HP1 paralogs in multicomponent assemblies and the impact of DNA on this process. Importantly, our study reveals that DNA can significantly reshape the stability of a minimal condensate formed by HP1 paralogs due to competitive interactions of HP1α with HP1β and HP1γ versus DNA. In conclusion, our work highlights the physicochemical nature of interactions that govern the distinct phase-separation behaviors of HP1 paralogs and provides a molecular framework for understanding their role in chromatin organization.

Smaller Gold Nanoparticles Release DNA More Efficiently During fs Laser Pulsed Optical Heating

This work investigates the effect of plasmonic gold nanoparticle (AuNP) size on the rate of thermal release of single-stranded oligonucleotides under femtosecond (fs)-pulsed laser irradiation sources. Contrary to the theoretical predictions that larger AuNPs (50-60 nm diameter) would produce the most solution heating and fastest DNA release, it is found that smaller AuNP diameters (25 nm) lead to faster dsDNA denaturation rates. Controlling for the pulse energy fluence, AuNP concentration, DNA loading density, and the distance from the AuNP surface finds the same result. These results imply that the solution temperature increases around the AuNP during fs laser pulse optical heating may not be the only significant influence on dsDNA denaturation, suggesting that direct energy transfer from the AuNP to the DNA (phonon-phonon coupling), which is increased as AuNPs decrease in size, may play a significant role.

Impact of template denaturation prior to whole genome amplification on gene detection in high GC-content species, Burkholderia mallei and B. pseudomallei

OBJECTIVE

In this study, we sought to determine the types and prevalence of antimicrobial resistance determinants (ARDs) in Burkholderia spp. strains using the Antimicrobial Resistance Determinant Microarray (ARDM).

RESULTS

Whole genome amplicons from 22 B. mallei (BM) and 37 B. pseudomallei (BP) isolates were tested for > 500 ARDs using ARDM v.3.1. ARDM detected the following Burkholderia spp.-derived genes, aac(6), blaBP/MBL-3, blaABPS, penA-BP, and qacE, in both BM and BP while blaBP/MBL-1, macB, blaOXA-42/43 and penA-BC were observed in BP only. The method of denaturing template for whole genome amplification greatly affected the numbers and types of genes detected by the ARDM. BlaTEM was detected in nearly a third of BM and BP amplicons derived from thermally, but not chemically denatured templates. BlaTEM results were confirmed by PCR, with 81% concordance between methods. Sequences from 414-nt PCR amplicons (13 preparations) were 100% identical to the Klebsiella pneumoniae reference gene. Although blaTEM sequences have been observed in B. glumae, B. cepacia, and other undefined Burkholderia strains, this is the first report of such sequences in BM/BP/B. thailandensis (BT) clade. These results highlight the importance of sample preparation in achieving adequate genome coverage in methods requiring untargeted amplification before analysis.

Coarse-Grained Models to Study Protein-DNA Interactions and Liquid-Liquid Phase Separation

Recent advances in coarse-grained (CG) computational models for DNA have enabled molecular-level insights into the behavior of DNA in complex multiscale systems. However, most existing CG DNA models are not compatible with CG protein models, limiting their applications for emerging topics such as protein-nucleic acid assemblies. Here, we present a new computationally efficient CG DNA model. We first use experimental data to establish the model's ability to predict various aspects of DNA behavior, including melting thermodynamics and relevant local structural properties such as the major and minor grooves. We then employ an all-atom hydropathy scale to define nonbonded interactions between protein and DNA sites, to make our DNA model compatible with an existing CG protein model (HPS-Urry), which is extensively used to study protein phase separation, and show that our new model reasonably reproduces the experimental binding affinity for a prototypical protein-DNA system. To further demonstrate the capabilities of this new model, we simulate a full nucleosome with and without histone tails, on a microsecond time scale, generating conformational ensembles and provide molecular insights into the role of histone tails in influencing the liquid-liquid phase separation (LLPS) of HP1α proteins. We find that histone tails interact favorably with DNA, influencing the conformational ensemble of the DNA and antagonizing the contacts between HP1α and DNA, thus affecting the ability of DNA to promote LLPS of HP1α. These findings shed light on the complex molecular framework that fine-tunes the phase transition properties of heterochromatin proteins and contributes to heterochromatin regulation and function. Overall, the CG DNA model presented here is suitable to facilitate micrometer-scale studies with sub-nm resolution in many biological and engineering applications and can be used to investigate protein-DNA complexes, such as nucleosomes, or LLPS of proteins with DNA, enabling a mechanistic understanding of how molecular information may be propagated at the genome level.

Pupillary correlates of individual differences in n-back task performance

We used pupillometry during a 2-back task to examine individual differences in the intensity and consistency of attention and their relative role in a working memory task. We used sensitivity, or the ability to distinguish targets (2-back matches) and nontargets, as the measure of task performance; task-evoked pupillary responses (TEPRs) as the measure of attentional intensity; and intraindividual pretrial pupil variability as the measure of attentional consistency. TEPRs were greater on target trials compared with nontarget trials, although there was no difference in TEPR magnitude when participants answered correctly or incorrectly to targets. Importantly, this effect interacted with performance: high performers showed a greater separation in their TEPRs between targets and nontargets, whereas there was little difference for low performers. Further, in regression analysis, larger TEPRs on target trials predicted better performance, whereas larger TEPRs on nontarget trials predicted worse performance. Sensitivity positively correlated with average pretrial pupil diameter and negatively correlated with intraindividual variability in pretrial pupil diameter. Overall, we found evidence that both attentional intensity (TEPRs) and consistency (pretrial pupil variation) predict performance on an n-back working memory task.

Hexagonal Boron Nitride Slab Waveguides for Enhanced Spectroscopy of Encapsulated 2D Materials

The layered insulator hexagonal boron nitride (hBN) is a critical substrate that brings out the exceptional intrinsic properties of two-dimensional (2D) materials such as graphene and transition metal dichalcogenides (TMDs). In this work, the authors demonstrate how hBN slabs tuned to the correct thickness act as optical waveguides, enabling direct optical coupling of light emission from encapsulated layers into waveguide modes. Molybdenum selenide (MoSe2 ) and tungsten selenide (WSe2 ) are integrated within hBN-based waveguides and demonstrate direct coupling of photoluminescence emitted by in-plane and out-of-plane transition dipoles (bright and dark excitons) to slab waveguide modes. Fourier plane imaging of waveguided photoluminescence from MoSe2 demonstrates that dry etched hBN edges are an effective out-coupler of waveguided light without the need for oil-immersion optics. Gated photoluminescence of WSe2 demonstrates the ability of hBN waveguides to collect light emitted by out-of-plane dark excitons.Numerical simulations explore the parameters of dipole placement and slab thickness, elucidating the critical design parameters and serving as a guide for novel devices implementing hBN slab waveguides. The results provide a direct route for waveguide-based interrogation of layered materials, as well as a way to integrate layered materials into future photonic devices at arbitrary positions whilst maintaining their intrinsic properties.

Exploration of the In Vitro Violacein Synthetic Pathway with Substrate Analogues

Evolution has gifted enzymes with the ability to synthesize an abundance of small molecules with incredible control over efficiency and selectivity. Central to an enzyme's role is the ability to selectively catalyze reactions in the milieu of chemicals within a cell. However, for chemists it is often desirable to extend the substrate scope of reactions to produce analogue(s) of a desired product and therefore some degree of enzyme promiscuity is often desired. Herein, we examine this dichotomy in the context of the violacein biosynthetic pathway. Importantly, we chose to interrogate this pathway with tryptophan analogues in vitro, to mitigate possible interference from cellular components and endogenous tryptophan. A total of nine tryptophan analogues were screened for by analyzing the substrate promiscuity of the initial enzyme, VioA, and compared to the substrate tryptophan. These results suggested that for VioA, substitutions at either the 2- or 4-position of tryptophan were not viable. The seven analogues that showed successful substrate conversion by VioA were then applied to the five enzyme cascade (VioABEDC) for the production of violacein, where l-tryptophan and 6-fluoro-l-tryptophan were the only substrates which were successfully converted to the corresponding violacein derivative(s). However, many of the other tryptophan analogues did convert to various substituted intermediaries. Overall, our results show substrate promiscuity with the initial enzyme, VioA, but much less for the full pathway. This work demonstrates the complexity involved when attempting to analyze substrate analogues within multienzymatic cascades, where each enzyme involved within the cascade possesses its own inherent promiscuity, which must be compatible with the remaining enzymes in the cascade for successful formation of a desired product.

An investigation of cardiac vagal tone over time and its relation to vigilance performance: a growth curve modeling approach

Introduction

Research over the last couple of decades has demonstrated a relationship between psychophysiological measures, specifically cardiac functions, and cognitive performance. Regulation of the cardiac system under parasympathetic control is commonly referred to as cardiac vagal tone and is associated with the regulation of cognitive and socioemotional states. The goal of the current study was to capture the dynamic relationship between cardiac vagal tone and performance in a vigilance task.

Method/Results

We implemented a longitudinal growth curve modeling approach which unveiled a relationship between cardiac vagal tone and vigilance that was non-monotonic and dependent upon each person.

Discussion

The findings suggest that cardiac vagal tone may be a process-based physiological measure that further explains how the vigilance decrement manifests over time and differs across individuals. This contributes to our understanding of vigilance by modeling individual differences in cardiac vagal tone changes that occur over the course of the vigilance task.

Δ2 machine learning for reaction property prediction

The emergence of Δ-learning models, whereby machine learning (ML) is used to predict a correction to a low-level energy calculation, provides a versatile route to accelerate high-level energy evaluations at a given geometry. However, Δ-learning models are inapplicable to reaction properties like heats of reaction and activation energies that require both a high-level geometry and energy evaluation. Here, a Δ2-learning model is introduced that can predict high-level activation energies based on low-level critical-point geometries. The Δ2 model uses an atom-wise featurization typical of contemporary ML interatomic potentials (MLIPs) and is trained on a dataset of ∼167 000 reactions, using the GFN2-xTB energy and critical-point geometry as a low-level input and the B3LYP-D3/TZVP energy calculated at the B3LYP-D3/TZVP critical point as a high-level target. The excellent performance of the Δ2 model on unseen reactions demonstrates the surprising ease with which the model implicitly learns the geometric deviations between the low-level and high-level geometries that condition the activation energy prediction. The transferability of the Δ2 model is validated on several external testing sets where it shows near chemical accuracy, illustrating the benefits of combining ML models with readily available physical-based information from semi-empirical quantum chemistry calculations. Fine-tuning of the Δ2 model on a small number of Gaussian-4 calculations produced a 35% accuracy improvement over DFT activation energy predictions while retaining xTB-level cost. The Δ2 model approach proves to be an efficient strategy for accelerating chemical reaction characterization with minimal sacrifice in prediction accuracy.

Ultrafast and Nanoscale Energy Transduction Mechanisms and Coupled Thermal Transport across Interfaces

The coupled interactions among the fundamental carriers of charge, heat, and electromagnetic fields at interfaces and boundaries give rise to energetic processes that enable a wide array of technologies. The energy transduction among these coupled carriers results in thermal dissipation at these surfaces, often quantified by the thermal boundary resistance, thus driving the functionalities of the modern nanotechnologies that are continuing to provide transformational benefits in computing, communication, health care, clean energy, power recycling, sensing, and manufacturing, to name a few. It is the purpose of this Review to summarize recent works that have been reported on ultrafast and nanoscale energy transduction and heat transfer mechanisms across interfaces when different thermal carriers couple near or across interfaces. We review coupled heat transfer mechanisms at interfaces of solids, liquids, gasses, and plasmas that drive the resulting interfacial heat transfer and temperature gradients due to energy and momentum coupling among various combinations of electrons, vibrons, photons, polaritons (plasmon polaritons and phonon polaritons), and molecules. These interfacial thermal transport processes with coupled energy carriers involve relatively recent research, and thus, several opportunities exist to further develop these nascent fields, which we comment on throughout the course of this Review.

Super-swelling behavior of stacked lipid bilayer systems

Bilayer systems comprising lipid mixtures are the most well-studied model of biological membranes. While the plasma membrane of the cell is a single bilayer, many intra- and extra-cellular biomembranes comprise stacks of bilayers. Most bilayer stacks in nature are periodic, maintaining a precise water layer separation between bilayers. That equilibrium water separation is governed by multiple inter-bilayer forces and is highly responsive. Biomembranes re-configure inter-bilayer spacing in response to temperature, composition, or mass transport cues. In synthetic bilayer systems for applications in cosmetics or topical treatments, control of the hydration level is a critical design handle. Herein we investigate a binary lipid system that leverages key inter-bilayer forces leading to unprecedented levels of aqueous swelling while maintaining a coherent multilamellar form. We found that combining cationic lipids with bicontinuous cubic phase-forming lipids (lipids with positive Gaussian modulus), results in the stabilization of multilamellar phases against repulsive steric forces that typically lead to bilayer delamination at high degrees of swelling. Using ultra-small-angle X-ray scattering alongside confocal laser scanning microscopy, we characterized various super-swelled states of 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and glycerol monooleate (GMO) lipids, as well as other analogous systems, at varied concentration and molar ratios. Through these experiments we established swelling profiles of various binary lipid systems that were near-linear with decreasing lipid volume fraction, showing maximum swelling with periodicity well above 200 nanometers. Confocal fluorescence micrograph of super-swelled multilamellar structures in 90GMOD sample at 25 mM concentration. Inset plot shows intensity profile of orange line, with pink triangles indicating maxima.

Atomically Precise Detection and Manipulation of Nitrogen-Vacancy Centers in Nanodiamonds

Nitrogen-vacancy (NV) centers in nanodiamonds are a promising quantum communication system offering robust and discrete single photon emission, but a more thorough understanding of properties of the NV centers is critical for real world implementation in functional devices. The first step to understanding how factors such as surface, depth, and charge state affect NV center properties is to directly characterize these defects on the atomic scale. Here we use Angstrom-resolution scanning transmission electron microscopy (STEM) to identify a single NV center in a ∼4 nm natural nanodiamond through simultaneous acquisition of electron energy loss and energy dispersive X-ray spectra, which provide a characteristic NV center peak and a nitrogen peak, respectively. In addition, we identify NV centers in larger, ∼15 nm synthetic nanodiamonds, although without the single-defect resolution afforded by the lower background of the smaller natural nanodiamonds. We have further demonstrated the potential to directly position these technologically relevant defects at the atomic scale using the scanning electron beam to "herd" NV centers and nitrogen atoms across their host nanodiamonds.

Towards control of excitonic coupling in DNA-templated Cy5 aggregates: the principal role of chemical substituent hydrophobicity and steric interactions

Understanding and controlling exciton coupling in dye aggregates has become a greater focus as potential applications such as coherent exciton devices, nanophotonics, and biosensing have been proposed. DNA nanostructure templates allow for a powerful modular approach. Using DNA Holliday junction (HJ) templates variations of dye combinations and precision dye positions can be rapidly assayed, as well as creating aggregates of dyes that could not be prepared (either due to excess or lack of solubility) through alternative means. Indodicarbocyanines (Cy5) have been studied in coupled systems due to their large transition dipole moment, which contributes to strong coupling. Cy5-R dyes were recently prepared by chemically modifying the 5,5'-substituents of indole rings, resulting in varying dye hydrophobicity/hydrophilicity, steric considerations, and electron-donating/withdrawing character. We utilized Cy5-R dyes to examine the formation and properties of 30 unique DNA templated homodimers. We find that in our system the sterics of Cy5-R dyes play the determining factor in orientation and coupling strength of dimers, with coupling strengths ranging from 50-138 meV. The hydrophobic properties of the Cy5-R modify the percentage of dimers formed, and have a secondary role in determining the packing characteristics of the dimers when sterics are equivalent. Similar to other reports, we find that positioning of the Cy5-R within the HJ template can favor particular dimer interactions, specifically oblique or H-type dimers.

Tunable Electronic Structure via DNA-Templated Heteroaggregates of Two Distinct Cyanine Dyes

Molecular excitons are useful for applications in light harvesting, organic optoelectronics, and nanoscale computing. Electronic energy transfer (EET) is a process central to the function of devices based on molecular excitons. Achieving EET with a high quantum efficiency is a common obstacle to excitonic devices, often owing to the lack of donor and acceptor molecules that exhibit favorable spectral overlap. EET quantum efficiencies may be substantially improved through the use of heteroaggregates-aggregates of chemically distinct dyes-rather than individual dyes as energy relay units. However, controlling the assembly of heteroaggregates remains a significant challenge. Here, we use DNA Holliday junctions to assemble homo- and heterotetramer aggregates of the prototypical cyanine dyes Cy5 and Cy5.5. In addition to permitting control over the number of dyes within an aggregate, DNA-templated assembly confers control over aggregate composition, i.e., the ratio of constituent Cy5 and Cy5.5 dyes. By varying the ratio of Cy5 and Cy5.5, we show that the most intense absorption feature of the resulting tetramer can be shifted in energy over a range of almost 200 meV (1600 cm^-1). All tetramers pack in the form of H-aggregates and exhibit quenched emission and drastically reduced excited-state lifetimes compared to the monomeric dyes. We apply a purely electronic exciton theory model to describe the observed progression of the absorption spectra. This model agrees with both the measured data and a more sophisticated vibronic model of the absorption and circular dichroism spectra, indicating that Cy5 and Cy5.5 heteroaggregates are largely described by molecular exciton theory. Finally, we extend the purely electronic exciton model to describe an idealized J-aggregate based on Förster resonance energy transfer (FRET) and discuss the potential advantages of such a device over traditional FRET relays.

Extraction of Antioxidants from Aronia mitschurinii Juice Using Macroporous Resins

Antioxidants play a vital role in the human body by defending cells from damage caused by free radicals, highly reactive products of oxidation reactions. A major source of antioxidants is fruits and vegetables. Aronia mitschurinii, a breed created at the end of the 19th century by crossbreeding wild Aronia melanocarpa and Russian Mountain Ash, produces fruits with one of the highest known content of hydrophilic antioxidants. Aronia fruit contains a potent blend of anthocyanins, polyphenols, and flavonoids. The most popular way of consuming the fruit is through juicing. Yet, due to very high concentrations of tannins in the juice, very few food-related applications have been developed. Resin extraction of antioxidants provides an alternative for utilizing valuable phytochemicals from crops for applications in the food industry as nutraceutical supplements and more. To increase the market value of the plant, it is important to determine what resins can extract the optimum concentration of antioxidants from aronia juice, pulp, and whole berries. We have shown that macroporous resins such as Amberlite XAD 1180N, Amberlite XAD 7HP, Amberlite XAD 761, and Amberlite FPX66, which have been reported to be effective in extracting the anthocyanins and polyphenols from other fruit juices, skins of red grapes, and the wild breed, are also effective for use in juice, pulp, and whole fruits of Aronia mitchurinii. However, the extremely high content of antioxidants presents a challenge to obtaining high recovery; a notable change in the juice/resin ratio is required to obtain a higher recovery value. Our results showed that Amberlite FPX66 was the best at extracting anthocyanins, polyphenols, and flavonoids from aronia juice. A separate experiment conducted to determine how to optimize the efficiency of FPX66 extraction revealed that increasing the resin/juice ratio increased the percent recovery of anthocyanins from aronia juice. Moreover, we have compared recovery between juice, pulp, and whole aronia berries and batch versus column extraction.

Tunable physical properties in Bi-based layered supercell multiferroics embedded with Au nanoparticles

Multiferroic materials are an interesting functional material family combining two ferroic orderings, e.g., ferroelectric and ferromagnetic orderings, or ferroelectric and antiferromagnetic orderings, and find various device applications, such as spintronics, multiferroic tunnel junctions, etc. Coupling multiferroic materials with plasmonic nanostructures offers great potential for optical-based switching in these devices. Here, we report a novel nanocomposite system consisting of layered Bi_1.25AlMnO_3.25 (BAMO) as a multiferroic matrix and well dispersed plasmonic Au nanoparticles (NPs) and demonstrate that the Au nanoparticle morphology and the nanocomposite properties can be effectively tuned. Specifically, the Au particle size can be tuned from 6.82 nm to 31.59 nm and the 6.82 nm one presents the optimum ferroelectric and ferromagnetic properties and plasmonic properties. Besides the room temperature multiferroic properties, the BAMO-Au nanocomposite system presents other unique functionalities including localized surface plasmon resonance (LSPR), hyperbolicity in the visible region, and magneto-optical coupling, which can all be effectively tailored through morphology tuning. This study demonstrates the feasibility of coupling single phase multiferroic oxides with plasmonic metals for complex nanocomposite designs towards optically switchable spintronics and other memory devices.

Structural and Morphological Analysis of the First Alloy/Dealloy of a Bulk Si-Li System at Elevated Temperature

There have been tremendous improvements in the field of Si electrode materials, either by nanoscale or composite routes, and though silicon-containing carbon electrode materials have begun to penetrate the marketplace, the commercial capacities achieved by these cells still fall short of the promise of high capacity Si electrodes. Enabling a cheaper feedstock of Si in the bulk form would make this technology more accessible, though there are many challenges that must be overcome. Whereas other methods utilize nanomaterials and composites to overcome volume expansion and pulverization of a Si electrode, this study explores a thermal route to enable the use of carbon-free bulk Si. To accomplish this, a modified Swagelok cell has been constructed to accommodate high temperatures, corrosive molten salt electrolytes, and a molten lithium electrode to study lithiation of a bulk Si wafer at 250 °C. Scanning electron microscopy, X-ray diffraction, and microcomputed tomography were used to examine morphological and structural changes within the Si upon lithiation and delithiation. It was discovered that semiordered Li _x Si phases were formed upon lithiation in molten LiTFSI electrolyte at 250 °C, and the higher temperature does not completely mitigate pulverization of the bulk Si electrode.

Synthesis of Substituted Cy5 Phosphoramidite Derivatives and Their Incorporation into Oligonucleotides Using Automated DNA Synthesis

Cyanine dyes represent a family of organic fluorophores with widespread utility in biological-based applications ranging from real-time PCR probes to protein labeling. One burgeoning use currently being explored with indodicarbocyanine (Cy5) in particular is that of accessing exciton delocalization in designer DNA dye aggregate structures for potential development of light-harvesting devices and room-temperature quantum computers. Tuning the hydrophilicity/hydrophobicity of Cy5 dyes in such DNA structures should influence the strength of their excitonic coupling; however, the requisite commercial Cy5 derivatives available for direct incorporation into DNA are nonexistent. Here, we prepare a series of Cy5 derivatives that possess different 5,5'-substituents and detail their incorporation into a set of DNA sequences. In addition to varying dye hydrophobicity/hydrophilicity, the 5,5'-substituents, including hexyloxy, triethyleneglycol monomethyl ether, tert-butyl, and chloro groups were chosen so as to vary the inherent electron-donating/withdrawing character while also tuning their resulting absorption and emission properties. Following the synthesis of parent dyes, one of their pendant alkyl chains was functionalized with a monomethoxytrityl protective group with the remaining hydroxyl-terminated N-propyl linker permitting rapid, same-day phosphoramidite conversion and direct internal DNA incorporation into nascent oligonucleotides with moderate to good yields using a 1 μmole scale automated DNA synthesis. Labeled sequences were cleaved from the controlled pore glass matrix, purified by HPLC, and their photophysical properties were characterized. The DNA-labeled Cy5 derivatives displayed spectroscopic properties that paralleled the parent dyes, with either no change or an increase in fluorescence quantum yield depending upon sequence.

Development of a dual antigen lateral flow immunoassay for detecting Yersinia pestis

Background

Yersinia pestis is the causative agent of plague, a zoonosis associated with small mammals. Plague is a severe disease, especially in the pneumonic and septicemic forms, where fatality rates approach 100% if left untreated. The bacterium is primarily transmitted via flea bite or through direct contact with an infected host. The 2017 plague outbreak in Madagascar resulted in more than 2,400 cases and was highlighted by an increased number of pneumonic infections. Standard diagnostics for plague include laboratory-based assays such as bacterial culture and serology, which are inadequate for administering immediate patient care for pneumonic and septicemic plague.

Principal findings

The goal of this study was to develop a sensitive rapid plague prototype that can detect all virulent strains of Y. pestis. Monoclonal antibodies (mAbs) were produced against two Y. pestis antigens, low-calcium response V (LcrV) and capsular fraction-1 (F1), and prototype lateral flow immunoassays (LFI) and enzyme-linked immunosorbent assays (ELISA) were constructed. The LFIs developed for the detection of LcrV and F1 had limits of detection (LOD) of roughly 1–2 ng/mL in surrogate clinical samples (antigens spiked into normal human sera). The optimized antigen-capture ELISAs produced LODs of 74 pg/mL for LcrV and 61 pg/mL for F1 when these antigens were spiked into buffer. A dual antigen LFI prototype comprised of two test lines was evaluated for the detection of both antigens in Y. pestis lysates. The dual format was also evaluated for specificity using a small panel of clinical near-neighbors and other Tier 1 bacterial Select Agents.

Conclusions

LcrV is expressed by all virulent Y. pestis strains, but homologs produced by other Yersinia species can confound assay specificity. F1 is specific to Y. pestis but is not expressed by all virulent strains. Utilizing highly reactive mAbs, a dual-antigen detection (multiplexed) LFI was developed to capitalize on the diagnostic strengths of each target.

Self-assembled nanoparticle-enzyme aggregates enhance functional protein production in pure transcription-translation systems

Cell-free protein synthesis systems (CFPS) utilize cellular transcription and translation (TX-TL) machinery to synthesize proteins in vitro. These systems are useful for multiple applications including production of difficult proteins, as high-throughput tools for genetic circuit screening, and as systems for biosensor development. Though rapidly evolving, CFPS suffer from some disadvantages such as limited reaction rates due to longer diffusion times, significant cost per assay when using commercially sourced materials, and reduced reagent stability over prolonged periods. To address some of these challenges, we conducted a series of proof-of-concept experiments to demonstrate enhancement of CFPS productivity via nanoparticle assembly driven nanoaggregation of its constituent proteins. We combined a commercially available CFPS that utilizes purified polyhistidine-tagged (His-tag) TX-TL machinery with CdSe/CdS/ZnS core/shell/shell quantum dots (QDs) known to readily coordinate His-tagged proteins in an oriented fashion. We show that nanoparticle scaffolding of the CFPS cross-links the QDs into nanoaggregate structures while enhancing the production of functional recombinant super-folder green fluorescent protein and phosphotriesterase, an organophosphate hydrolase; the latter by up to 12-fold. This enhancement, which occurs by an undetermined mechanism, has the potential to improve CFPS in general and specifically CFPS-based biosensors (faster response time) while also enabling rapid detoxification/bioremediation through point-of-concern synthesis of similar catalytic enzymes. We further show that such nanoaggregates improve production in diluted CFPS reactions, which can help to save money and extend the amount of these costly reagents. The results are discussed in the context of what may contribute mechanistically to the enhancement and how this can be applied to other CFPS application scenarios.

Prototype Smartphone-Based Device for Flow Cytometry with Immunolabeling via Supra-nanoparticle Assemblies of Quantum Dots

Methods for the detection, enumeration, and typing of cells are important in many areas of research and healthcare. In this context, flow cytometers are a widely used research and clinical tool but are also an example of a large and expensive instrument that is limited to specialized laboratories. Smartphones have been shown to have excellent potential to serve as portable and lower-cost platforms for analyses that would normally be done in a laboratory. Here, we developed a prototype smartphone-based flow cytometer (FC). This compact 3D-printed device incorporated a laser diode and a microfluidic flow cell and used the built-in camera of a smartphone to track immunofluorescently labeled cells in suspension and measure their color. This capability was enabled by high-brightness supra-nanoparticle assemblies of colloidal semiconductor quantum dots (SiO₂@QDs) as well as a support vector machine (SVM) classification algorithm. The smartphone-based FC device detected and enumerated target cells against a background of other cells, simultaneously and selectively counted two different cell types in a mixture, and used multiple colors of SiO₂@QD-antibody conjugates to screen for and identify a particular cell type. The potential limits of multicolor detection are discussed alongside ideas for further development. Our results suggest that innovations in materials and engineering should enable eventual smartphone-based FC assays for clinical applications.

Models of Intervention: Helping Agents and Human Users Avoid Undesirable Outcomes

When working in an unfamiliar online environment, it can be helpful to have an observer that can intervene and guide a user toward a desirable outcome while avoiding undesirable outcomes or frustration. The Intervention Problem is deciding when to intervene in order to help a user. The Intervention Problem is similar to, but distinct from, Plan Recognition because the observer must not only recognize the intended goals of a user but also when to intervene to help the user when necessary. We formalize a family of Intervention Problems and show that how these problems can be solved using a combination of Plan Recognition methods and classification algorithms to decide whether to intervene. For our benchmarks, the classification algorithms dominate three recent Plan Recognition approaches. We then generalize these results to Human-Aware Intervention, where the observer must decide in real time whether to intervene human users solving a cognitively engaging puzzle. Using a revised feature set more appropriate to human behavior, we produce a learned model to recognize when a human user is about to trigger an undesirable outcome. We perform a human-subject study to evaluate the Human-Aware Intervention. We find that the revised model also dominates existing Plan Recognition algorithms in predicting Human-Aware Intervention.

Synthesis and applications of WO3 nanosheets: the importance of phase, stoichiometry, and aspect ratio

Tungsten trioxide (WO₃) is an abundant, versatile oxide that is widely explored for catalysis, sensing, electrochromic devices, and numerous other applications. The exploitation of WO₃ in nanosheet form provides potential advantages in many of these fields because the 2D structures have high surface area and preferentially exposed facets. Relative to bulk WO₃, nanosheets expose more active sites for surface-sensitive sensing/catalytic reactions, and improve reaction kinetics in cases where ionic diffusion is a limiting factor (e.g. electrochromic or charge storage). Synthesis of high aspect ratio WO₃ nanosheets, however, is more challenging than other 2D materials because bulk WO₃ is not an intrinsically layered material, making the widely-studied sonication-based exfoliation methods used for other 2D materials not well-suited to WO₃. WO₃ is also highly complex in terms of how the synthesis method affects the properties of the final material. Depending on the route used and subsequent post-synthesis treatments, a wide variety of different morphologies, phases, exposed facets, and defect structures are created, all of which must be carefully considered for the chosen application. In this review, the recent developments in WO₃ nanosheet synthesis and their impact on performance in various applications are summarized and critically analyzed.

Evidence approach imprecise intervals: extensions and evaluation measures

In a number of applications the data will be represented in an interval format. We consider here a nested representation of uncertain information in intervals using Dempster-Shafer evidence approaches. These representations can be used in variety of applications including spatial and temporal reasoning and economic cost valuations. Two representations of nested intervals, RP1 and RP2, are defined and used in the paper. Basically an inner interval represents the more certain data and is nested in the outer less certain interval. We illustrate how the specificity measure could be used to evaluate such nested Dempster-Shafer intervals. We then consider Gini information measures applicable to the RP1 representation. We describe an example using our interval approach to COVID contact tracing in epidemiology. Finally examples of aggregation of intervals are provided. It is seen that an aggregated result can be evaluated and shown to increase the specificity of the result. Additionally, it is not always the case that aggregation increases specificity. An example is given illustrating such a case.

Optimal periodic closure for minimizing risk in emerging disease outbreaks

Without vaccines and treatments, societies must rely on non-pharmaceutical intervention strategies to control the spread of emerging diseases such as COVID-19. Though complete lockdown is epidemiologically effective, because it eliminates infectious contacts, it comes with significant costs. Several recent studies have suggested that a plausible compromise strategy for minimizing epidemic risk is periodic closure, in which populations oscillate between wide-spread social restrictions and relaxation. However, no underlying theory has been proposed to predict and explain optimal closure periods as a function of epidemiological and social parameters. In this work we develop such an analytical theory for SEIR-like model diseases, showing how characteristic closure periods emerge that minimize the total outbreak, and increase predictably with the reproductive number and incubation periods of a disease- as long as both are within predictable limits. Using our approach we demonstrate a sweet-spot effect in which optimal periodic closure is maximally effective for diseases with similar incubation and recovery periods. Our results compare well to numerical simulations, including in COVID-19 models where infectivity and recovery show significant variation.

Quickest Detection of COVID-19 Pandemic Onset

This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. The decision statistic can be cast in a recursive form and is particularly suited for on-line analysis. By back-testing our approach on publicly-available COVID-19 data we find reliable early warning of infection flare-ups, in fact sufficiently early that the tool may be of use to decision-makers on the timing of restrictive measures that may in the future need to be taken.

Sequence dependent phase separation of protein-polynucleotide mixtures elucidated using molecular simulations

Ribonucleoprotein (RNP) granules are membraneless organelles (MLOs), which majorly consist of RNA and RNA-binding proteins and are formed via liquid-liquid phase separation (LLPS). Experimental studies investigating the drivers of LLPS have shown that intrinsically disordered proteins (IDPs) and nucleic acids like RNA and other polynucleotides play a key role in modulating protein phase separation. There is currently a dearth of modelling techniques which allow one to delve deeper into how polynucleotides play the role of a modulator/promoter of LLPS in cells using computational methods. Here, we present a coarse-grained polynucleotide model developed to fill this gap, which together with our recently developed HPS model for protein LLPS, allows us to capture the factors driving protein-polynucleotide phase separation. We explore the capabilities of the modelling framework with the LAF-1 RGG system which has been well studied in experiments and also with the HPS model previously. Further taking advantage of the fact that the HPS model maintains sequence specificity we explore the role of charge patterning on controlling polynucleotide incorporation into condensates. With increased charge patterning we observe formation of structured or patterned condensates which suggests the possible roles of polynucleotides in not only shifting the phase boundaries but also introducing microscopic organization in MLOs.

Overlapping and unique neural circuits are activated during perceptual decision making and confidence

The period of making a perceptual decision is often followed by a period of rating confidence where one evaluates the likely accuracy of the initial decision. However, it remains unclear whether the same or different neural circuits are engaged during periods of perceptual decision making and confidence report. To address this question, we conducted two functional MRI experiments in which we dissociated the periods related to perceptual decision making and confidence report by either separating their respective regressors or asking for confidence ratings only in the second half of the experiment. We found that perceptual decision making and confidence reports gave rise to activations in large and mostly overlapping brain circuits including frontal, parietal, posterior, and cingulate regions with the results being remarkably consistent across the two experiments. Further, the confidence report period activated a number of unique regions, whereas only early sensory areas were activated for the decision period across the two experiments. We discuss the possible reasons for this overlap and explore their implications about theories of perceptual decision making and visual metacognition.

ZnO Nanoparticle/Graphene Hybrid Photodetectors via Laser Fragmentation in Liquid

By combining the enhanced photosensitive properties of zinc oxide nanoparticles and the excellent transport characteristics of graphene, UV-sensitive, solar-blind hybrid optoelectronic devices have been demonstrated. These hybrid devices offer high responsivity and gain, making them well suited for photodetector applications. Here, we report a hybrid ZnO nanoparticle/graphene phototransistor that exhibits a responsivity up to 4 × 104 AW-1 and gain of up to 1.3 × 105 with high UV wavelength selectivity. ZnO nanoparticles were synthesized by pulsed laser fragmentation in liquid to attain a simple, efficient, ligand-free method for nanoparticle fabrication. By combining simple fabrication processes with a promising device architecture, highly sensitive ZnO nanoparticle/graphene UV photodetectors were successfully demonstrated.

Beacon-referenced pursuit for collective motions in three dimensions

Motivated by real-world applications of unmanned aerial vehicles, this paper introduces a decentralized control mechanism to guide steering control of autonomous agents manoeuvring in the vicinity of multiple moving entities (e.g. other autonomous agents) and stationary entities (e.g. fixed beacons or points of reference) in a three-dimensional environment. The proposed control law, which can be perceived as a modification of the three-dimensional constant bearing (CB) pursuit law, provides a means to allocate simultaneous attention to multiple entities. We investigate the behaviour of the closed-loop dynamics for a system with one agent referencing two beacons, as well as a two-agent mutual pursuit system wherein each agent employs the beacon-referenced CB pursuit law with regards to the other agent and a stationary beacon. Under certain assumptions on the associated control parameters, we demonstrate that this problem admits circling equilibria with agents moving on circular orbits with a common radius, in planes perpendicular to a common axis passing through the beacons. As the common radius and distances from the beacon are determined by the choice of parameters in the pursuit law, this approach provides a means to engineer desired formations in a three-dimensional setting.

Adaptive Bayesian Learning and Forecasting of Epidemic Evolution-Data Analysis of the COVID-19 Outbreak

Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused hundreds of thousands of deaths and put under heavy pressure the world's most advanced healthcare systems. In order to slow down the spread of the disease, known as COVID-19, and reduce the stress on healthcare structures and intensive care units, many governments have taken drastic and unprecedented measures, such as closure of schools, shops and entire industries, and enforced drastic social distancing regulations, including local and national lockdowns. To effectively address such pandemics in a systematic and informed manner in the future, it is of fundamental importance to develop mathematical models and algorithms to predict the evolution of the spread of the disease to support policy and decision making at the governmental level. There is a strong literature describing the application of Bayesian sequential and adaptive dynamic estimation to surveillance (tracking and prediction) of objects such as missiles and ships; and in this article, we transfer some of its key lessons to epidemiology. We show that we can reliably estimate and forecast the evolution of the infections from daily - and possibly uncertain - publicly available information provided by authorities, e.g., daily numbers of infected and recovered individuals. The proposed method is able to estimate infection and recovery parameters, and to track and predict the epidemiological curve with good accuracy when applied to real data from Lombardia region in Italy, and from the USA. In these scenarios, the mean absolute percentage error computed after the lockdown is on average below 5% when the forecast is at 7 days, and below 10% when the forecast horizon is 14 days.

MetaCarvel: linking assembly graph motifs to biological variants

Reconstructing genomic segments from metagenomics data is a highly complex task. In addition to general challenges, such as repeats and sequencing errors, metagenomic assembly needs to tolerate the uneven depth of coverage among organisms in a community and differences between nearly identical strains. Previous methods have addressed these issues by smoothing genomic variants. We present a variant-aware metagenomic scaffolder called MetaCarvel, which combines new strategies for repeat detection with graph analytics for the discovery of variants. We show that MetaCarvel can accurately reconstruct genomic segments from complex microbial mixtures and correctly identify and characterize several classes of common genomic variants.

Degree Dispersion Increases the Rate of Rare Events in Population Networks

There is great interest in predicting rare and extreme events in complex systems, and in particular, understanding the role of network topology in facilitating such events. In this Letter, we show that degree dispersion-the fact that the number of local connections in networks varies broadly-increases the probability of large, rare fluctuations in population networks generically. We perform explicit calculations for two canonical and distinct classes of rare events: network extinction and switching. When the distance to threshold is held constant, and hence stochastic effects are fairly compared among networks, we show that there is a universal, exponential increase in the rate of rare events proportional to the variance of a network's degree distribution over its mean squared.

Selection of Single-Domain Antibodies towards Western Equine Encephalitis Virus

In this work, we describe the selection and characterization of single-domain antibodies (sdAb) towards the E2/E3E2 envelope protein of the Western equine encephalitis virus (WEEV). Our purpose was to identify novel recognition elements which could be used for the detection, diagnosis, and perhaps treatment of western equine encephalitis (WEE). To achieve this goal, we prepared an immune phage display library derived from the peripheral blood lymphocytes of a llama that had been immunized with an equine vaccine that includes killed WEEV (West Nile Innovator + VEWT). This library was panned against recombinant envelope (E2/E3E2) protein from WEEV, and seven representative sdAb from the five identified sequence families were characterized. The specificity, affinity, and melting point of each sdAb was determined, and their ability to detect the recombinant protein in a MagPlex sandwich immunoassay was confirmed. Thus, these new binders represent novel recognition elements for the E2/E3E2 proteins of WEEV that are available to the research community for further investigation into their applicability for use in the diagnosis or treatment of WEE.

Photosynthesis by marine algae produces sound, contributing to the daytime soundscape on coral reefs

We have observed that marine macroalgae produce sound during photosynthesis. The resultant soundscapes correlate with benthic macroalgal cover across shallow Hawaiian coral reefs during the day, despite the presence of other biological noise. Likely ubiquitous but previously overlooked, this source of ambient biological noise in the coastal ocean is driven by local supersaturation of oxygen near the surface of macroalgal filaments, and the resultant formation and release of oxygen-containing bubbles into the water column. During release, relaxation of the bubble to a spherical shape creates a monopole sound source that ‘rings’ at the Minnaert frequency. Many such bubbles create a large, distributed sound source over the sea floor. Reef soundscapes contain vast quantities of biological information, making passive acoustic ecosystem evaluation a tantalizing prospect if the sources are known. Our observations introduce the possibility of a general, volumetrically integrative, noninvasive, rapid and remote technique for evaluating algal abundance and rates of primary productivity in littoral aquatic communities. Increased algal cover is one of the strongest indicators for coral reef ecosystem stress. Visually determining variations in algal abundance is a time-consuming and expensive process. This technique could therefore provide a valuable tool for ecosystem management but also for industrial monitoring of primary production, such as in algae-based biofuel synthesis.