Evasive Spike Variants Elucidate the Preservation of T Cell Immune Response to the SARS-CoV-2 Omicron Variant.

The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants render them resistant to antibodies that otherwise neutralize the spike protein of the original SARS-CoV-2 spike protein. Recent research has shown that despite its strong immune evasion, Omicron still induces strong T Cell responses similar to the original variant. This work investigates the molecular basis for this observation using the neural network tools NetMHCpan-4.1 and NetMHCiipan-4.0. The antigens presented through the MHC Class I and Class II pathways from all the notable SARS-CoV-2 variants were compared across numerous high frequency HLAs. All variants were observed to have equivalent T cell antigenicity. A novel positive control system was engineered in the form of spike variants that did evade T Cell responses, unlike Omicron. These evasive spike proteins were used to statistically confirm that the Omicron variants did not exhibit lower antigenicity in the MHC pathways. These results suggest that T Cell immunity mounts a strong defense against COVID-19 which is difficult for SARS-CoV-2 to overcome through mere evolution.

Neural network execution using nicked DNA and microfluidics.

DNA has been discussed as a potential medium for data storage. Potentially it could be denser, could consume less energy, and could be more durable than conventional storage media such as hard drives, solid-state storage, and optical media. However, performing computations on the data stored in DNA is a largely unexplored challenge. This paper proposes an integrated circuit (IC) based on microfluidics that can perform complex operations such as artificial neural network (ANN) computation on data stored in DNA. We envision such a system to be suitable for highly dense, throughput-demanding bio-compatible applications such as an intelligent Organ-on-Chip or other biomedical applications that may not be latency-critical. It computes entirely in the molecular domain without converting data to electrical form, making it a form of in-memory computing on DNA. The computation is achieved by topologically modifying DNA strands through the use of enzymes called nickases. A novel scheme is proposed for representing data stochastically through the concentration of the DNA molecules that are nicked at specific sites. The paper provides details of the biochemical design, as well as the design, layout, and operation of the microfluidics device. Benchmarks are reported on the performance of neural network computation.

Computing mathematical functions with chemical reactions via stochastic logic.

This paper presents a novel strategy for computing mathematical functions with molecular reactions, based on theory from the realm of digital design. It demonstrates how to design chemical reaction networks based on truth tables that specify analog functions, computed by stochastic logic. The theory of stochastic logic entails the use of random streams of zeros and ones to represent probabilistic values. A link is made between the representation of random variables with stochastic logic on the one hand, and the representation of variables in molecular systems as the concentration of molecular species, on the other. Research in stochastic logic has demonstrated that many mathematical functions of interest can be computed with simple circuits built with logic gates. This paper presents a general and efficient methodology for translating mathematical functions computed by stochastic logic circuits into chemical reaction networks. Simulations show that the computation performed by the reaction networks is accurate and robust to variations in the reaction rates, within a log-order constraint. Reaction networks are given that compute functions for applications such as image and signal processing, as well as machine learning: arctan, exponential, Bessel, and sinc. An implementation is proposed with a specific experimental chassis: DNA strand displacement with units called DNA "concatemers".

Digital circuits and neural networks based on acid-base chemistry implemented by robotic fluid handling.

Acid-base reactions are ubiquitous, easy to prepare, and execute without sophisticated equipment. Acids and bases are also inherently complementary and naturally map to a universal representation of "0" and "1." Here, we propose how to leverage acids, bases, and their reactions to encode binary information and perform information processing based upon the majority and negation operations. These operations form a functionally complete set that we use to implement more complex computations such as digital circuits and neural networks. We present the building blocks needed to build complete digital circuits using acids and bases for dual-rail encoding data values as complementary pairs, including a set of primitive logic functions that are widely applicable to molecular computation. We demonstrate how to implement neural network classifiers and some classes of digital circuits with acid-base reactions orchestrated by a robotic fluid handling device. We validate the neural network experimentally on a number of images with different formats, resulting in a perfect match to the in-silico classifier. Additionally, the simulation of our acid-base classifier matches the results of the in-silico classifier with approximately 99% similarity.

Evaluating NetMHCpan performance on non-European HLA alleles not present in training data.

Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare applications is vital to ensure equity. Two such machine learning models are NetMHCpan-4.1 and NetMHCIIpan-4.0, used to predict antigen binding scores to major histocompatibility complex class I and II molecules, respectively. As antigen presentation is a critical step in mounting the adaptive immune response, previous work has used these or similar predictions models in a broad array of applications, from explaining asymptomatic viral infection to cancer neoantigen prediction. However, these models have also been shown to be biased toward hydrophobic peptides, suggesting the network could also contain other sources of bias. Here, we report the composition of the networks' training datasets are heavily biased toward European Caucasian individuals and against Asian and Pacific Islander individuals. We test the ability of NetMHCpan-4.1 and NetMHCpan-4.0 to distinguish true binders from randomly generated peptides on alleles not included in the training datasets. Unexpectedly, we fail to find evidence that the disparities in training data lead to a meaningful difference in prediction quality for alleles not present in the training data. We attempt to explain this result by mapping the HLA sequence space to determine the sequence diversity of the training dataset. Furthermore, we link the residues which have the greatest impact on NetMHCpan predictions to structural features for three alleles (HLA-A*34:01, HLA-C*04:03, HLA-DRB1*12:02).

Hydrophobicity identifies false positives and false negatives in peptide-MHC binding.

Major Histocompability Complex (MHC) Class I molecules allow cells to present foreign and endogenous peptides to T-Cells so that cells infected by pathogens can be identified and killed. Neural networks tools such as NetMHC-4.0 and NetMHCpan-4.1 are used to predict whether peptides will bind to variants of MHC molecules. These tools are trained on data gathered from binding affinity and eluted ligand experiments. However, these tools do not track hydrophobicity, a significant biochemical factor relevant to peptide binding, in their predictions. A previous study had concluded that the peptides predicted to bind to HLA-A*0201 by NetMHC-4.0 were much more hydrophobic than expected. This paper expands that study by also focusing on HLA-B*2705 and HLA-B*0801, which prefer binding hydrophilic and balanced peptides respectively. The correlation of hydrophobicity of 9-mer peptides with their predicted binding strengths to these various HLAs was investigated. Two studies were performed, one using the data that the two neural networks were trained on, and the other using a sample of the human proteome. NetMHC-4.0 was found to have a statistically significant bias towards predicting highly hydrophobic peptides as strong binders to HLA-A*0201 and HLA-B*2705 in both studies. Machine Learning metrics were used to identify the causes for this bias: hydrophobic false positives and hydrophilic false negatives. These results suggest that the retraining the neural networks with biochemical attributes such as hydrophobicity and better training data could increase the accuracy of their predictions. This would increase their impact in applications such as vaccine design and neoantigen identification.

Tailoring of the photocatalytic activity of CeO2 nanoparticles by the presence of plasmonic Ag nanoparticles.

The present study investigates basic features of a photoelectrochemical system based on CeO2 nanoparticles fixed on gold electrodes. Since photocurrent generation is limited to the absorption range of the CeO2 in the UV range, the combination with metal nanoparticles has been studied. It can be shown that the combination of silver nanoparticles with the CeO2 can shift the excitation range into the visible light wavelength range. Here a close contact between both components has been found to be essential and thus, hybrid CeO2@Ag nanoparticles have been prepared and analyzed. We have collected arguments that electron transfer occurs between both compositional elements of the hybrid nanoparticles.The photocurrent generation can be rationalized on the basis of an energy diagram underlying the necessity of surface plasmon excitation in the metal nanoparticles, which is also supported by wavelength-dependent photocurrent measurements. However, electrochemical reactions seem to occur at the CeO2 surface and consequently, the catalytic properties of this material can be exploited as exemplified with the photoelectrochemical reduction of hydrogen peroxide. It can be further demonstrated that the layer-by layer technique can be exploited to create a multilayer system on top of a gold electrode which allows the adjustment of the sensitivity of the photoelectrochemical system. Thus, with a 5-layer electrode with hybrid CeO2@Ag nanoparticles submicromolar hydrogen peroxide concentrations can be detected.

Introducing visible-light sensitivity into photocatalytic CeO2 nanoparticles by hybrid particle preparation exploiting plasmonic properties of gold: enhanced photoelectrocatalysis exemplified for hydrogen peroxide sensing.

In this report we combine the catalytic properties of CeO2 nanoparticles with their transduction ability for photoelectrochemical sensing. This study highlights the usage of CeO2 providing catalytic activity towards H2O2, but only with a limited excitation range in the UV for the construction of a sensing system. In order to improve the photoelectrocatalysis of CeO2 nanoparticles by extending their excitation to visible light, Au/CeO2 core/shell hybrid nanoparticles have been synthesized. The hybrid nanoparticles are fixed on electrodes, allowing for the generation of photocurrents, the direction of which can be controlled by the electrode potential (without bias). The application of the hybrid nanoparticles results in an enhanced photocurrent amplitude under white light illumination as compared to the pure CeO2 nanoparticles. Wavelength-dependent measurements confirm the participation of the Au core in the signal transduction. This can be explained by improved charge carrier generation within the hybrid particles. Thus, by using a plasmonic element the photoelectochemical response of a catalytic nanoparticle (i.e. CeO2) has been spectrally extended. The effect can be exploited for sensorial hydrogen peroxide detection. Here higher photocatalytic current responses have been found for the hybrid particles fixed to gold electrodes although the catalytic reduction has been comparable for both types of nanoparticles. Thus, it can be demonstrated that Au/CeO2 core-shell nanoparticles allow the utilization of visible light for photoelectrochemical hydrogen peroxide (H2O2) detection with improved sensitivity under white light illumination or application of such particles with only visible light excitation, which is not possible for pure CeO2. With help of the layer-by-layer (LbL) technique for nanoparticle immobilization, the electrode response can be adjusted and with a 5 layers electrode a low detection limit of about 3 µM H2O2 with a linear detection range up to 2000 µM is obtained.

A Tandem Solar Biofuel Cell: Harnessing Energy from Light and Biofuels.

We report on a photobioelectrochemical fuel cell consisting of a glucose-oxidase-modified BiFeO3 photobiocathode and a quantum-dot-sensitized inverse opal TiO2 photobioanode linked to FAD glucose dehydrogenase via a redox polymer. Both photobioelectrodes are driven by enzymatic glucose conversion. Whereas the photobioanode can collect electrons from sugar oxidation at rather low potential, the photobiocathode shows reduction currents at rather high potential. The electrodes can be arranged in a sandwich-like manner due to the semi-transparent nature of BiFeO3 , which also guarantees a simultaneous excitation of the photobioanode when illuminated via the cathode side. This tandem cell can generate electricity under illumination and in the presence of glucose and provides an exceptionally high OCV of about 1 V. The developed semi-artificial system has significant implications for the integration of biocatalysts in photoactive entities for bioenergetic purposes, and it opens up a new path toward generation of electricity from sunlight and (bio)fuels.

Light-controlled imaging of biocatalytic reactions via scanning photoelectrochemical microscopy for multiplexed sensing.

A light-controlled multiplexing platform has been developed on the basis of a quantum dot-sensitized inverse opal TiO2 electrode with integrated biocatalytic reactions. Spatially resolved illumination enables multiplexed sensing and imaging of enzymatic oxidation reactions at relatively negative applied potentials.

Evaluation in humans of ELF-EMF exposure on chromogranin A, a marker of neuroendocrine tumors and stress.

Chromogranin A (CgA), which is a major protein in adrenal chromaffin cells and adrenergic neurons, is a clinically relevant endocrine and neuroendocrine tumor marker including pheochromocytomas, neuroblastomas, and related neurogenic tumors. In this study, we looked at the effect in humans of chronic daily exposure to a 50-Hz magnetic field. We examined in 15 men (38.0 ± 0.9 years) the effects of chronic daily exposure to a 50-Hz magnetic field for 1-20 yrs both at home and at work. EMDEX II dosimeters were used to record magnetic field all day long every 30 s. for 1 week. The weekly geometric mean of the individual exposures ranged from 0.1 to 2.6 µT. Blood samples were taken hourly between 20:00 h and 08:00 h. CgA patterns of exposed subjects were compared to age-matched controls. The results of exposed subjects were compared with those for 15 unexposed men who served as controls and whose individual exposure was ten times lower ranging from 0.004 to 0.092 µT. This work shows that in the control group the serum CgA levels exhibited a nighttime peak with a progressive decline of the serum concentrations and a nadir in the morning. Both the profile and the serum concentrations of CgA, a marker of neuroendocrine tumors and stress, did not appear to be impaired in the subjects chronically exposed over a long period (up to 20 yrs) to magnetic fields though a trend toward lower levels were found at the highest exposure (>0.3 µT). This does not rule out, however, that the potential deleterious risk of ELF-EMF on frail populations such as children and the elderly may be greater at low exposure and should hence be documented, at least for their residential exposure.

Twenty-four-hour pattern of operations-related injury occurrence and severity of off-site/on-call volunteer French firefighters.

We assessed the 24-h pattern of operations-related injuries (ORI) experienced by scheduled off-site/on-call French volunteer firefighters (VFF) through analysis of an archival database. Occurrence and severity - evaluated by number of lost work days (LWD) and total medical costs (TMC) - of ORI were explored in terms of risk ratios, respectively, number of ORI/number of service operations (RRORI), number of LWD/number of ORI (RSLWD,) and TMC/number of ORI (RSTMC). Additionally, the collective work performance of all involved VFF was measured in terms of the lag time (LT) between emergency call-center firefighter-answered communication for service of observer-presumed out-of-hospital cardiac arrest (OHCA) and departure of vehicle from fire station to render aid, designated LTOHCA. Cosinor and cross-correlation statistical methods were applied. A total of 252 ORI occurred while performing 146,479 service operations. High-amplitude 24 h variation was detected in RRORI (p < .003), SRLWD (p < .001), SRTMC (p < .012), and LTOHCA (p < .001), all with nocturnal peak time. Coherence was found between the day/night variation of LTOHCA and RRORI (r = 0.7, p < .0002), SRLWD (r = 0.5, p < .02), and SRTMC (r = 0.4, p < .05). This investigation verifies the occurrence and severity of ORI of scheduled off-site/on-call VFF exhibit high-amplitude 24 h patterning with nocturnal excess that closely coincides with their day/night work performance measured by LTOHCA. These findings, which are essentially identical to ones of a previous study entailing on-site/on-call career firefighters, indicate the need for fatigue management and ORI prevention programs not yet available to VFF, who compose the majority of the field service workforce of French fire departments. Abbreviations:FF: firefighters; CFF: career firefighters; VFF: volunteer firefighters; FD: fire department; LTOHCA: lag time (LT) response in min:sec between fire department call-center-answered communication for service of presumed out-of-hospital cardiac arrest (OHCA) and departure from fire station of vehicle to render aid; LWD: lost work days; ORI: operations-related injuries; SRLWD: severity ratio of operations-related injuries in terms of number of lost work days, calculated as number of lost work days/number of operations-related injuries; RRORI: risk ratio of operations-related injuries calculated as number of operations-related injuries/number of operations; SRTMC: severity ratio of operations-related injuries in terms of total medical costs, calculated as total medical costs/number of operations-related injuries; TMC: total medical costs.

Multiplexed Readout of Enzymatic Reactions by Means of Laterally Resolved Illumination of Quantum Dot Electrodes.

Triggering electrochemical reactions with light provides a powerful tool for the control of complex reaction schemes on photoactive electrodes. Here, we report on the light-directed, multiplexed detection of enzymatic substrates using a nonstructured gold electrode modified with CdSe/ZnS quantum dots (QDs) and two enzymes, glucose oxidase (GOx) and sarcosine oxidase (SOx). While QDs introduce visible-light sensitivity into the electrode architecture, GOx and SOx allow for a selective conversion of glucose and sarcosine, respectively. For the QD immobilization to the gold electrode, a linker-assisted approach using trans-4,4'-stilbenedithiol has been used, resulting in the generation of a photocurrent. Subsequently, GOx and SOx have been immobilized in spatially separated spots onto the QD electrode. For the local readout of the QD electrode, a new measurement setup has been developed by moving a laser pointer across the surface to defined positions on the chip surface. The amplitudes of the photocurrents upon illumination of the GOx or SOx spot depend in a concentration-dependent manner on the presence of glucose and sarcosine, respectively. This measurement also allows for a selective detection in the presence of other substances. The setup demonstrates the feasibility of multiplexed measurements of enzymatic reactions using a focused light pointer, resulting in an illumination area with a diameter of 0.3 mm for analyzing spots of different enzymes. Moving the laser pointer in the x- and y-direction and simultaneously detecting the local photocurrent also allow a spatial imaging of enzyme immobilization. Here, not only the spot dimensions but also the activity of the enzyme can be verified.

A Z-Scheme-Inspired Photobioelectrochemical H2 O/O2 Cell with a 1†V Open-Circuit Voltage Combining Photosystem†II and PbS Quantum Dots.

A biohybrid photobioanode mimicking the Z-scheme has been developed by functional integration of photosystem II (PSII) and PbS quantum dots (QDs) within an inverse opal TiO2 architecture giving rise to a rather negative water oxidation potential of about -0.55 V vs. Ag/AgCl, 1 m KCl at neutral pH. The electrical linkage between both light-sensitive entities has been established through an Os-complex-modified redox polymer (POs ), which allows the formation of a multi-step electron-transfer chain under illumination starting with the photo-activated water oxidation at PSII followed by an electron transfer from PSII through POs to the photo-excited QDs and finally to the TiO2 electrode. The photobioanode was coupled to a novel, transparent, inverse-opal ATO cathode modified with an O2 -reducing bilirubin oxidase for the construction of a H2 O/O2 photobioelectrochemical cell reaching a high open-circuit voltage of about 1 V under illumination.

Computing Mathematical Functions using DNA via Fractional Coding.

This paper discusses the implementation of mathematical functions such as exponentials, trigonometric functions, the sigmoid function and the perceptron function with molecular reactions in general, and DNA strand displacement reactions in particular. The molecular constructs for these functions are predicated on a novel representation for input and output values: a fractional encoding, in which values are represented by the relative concentrations of two molecular types, denoted as type-1 and type-0. This representation is inspired by a technique from digital electronic design, termed stochastic logic, in which values are represented by the probability of 1's in a stream of randomly generated 0's and 1's. Research in the electronic realm has shown that a variety of complex functions can be computed with remarkably simple circuitry with this stochastic approach. This paper demonstrates how stochastic electronic designs can be translated to molecular circuits. It presents molecular implementations of mathematical functions that are considerably more complex than any shown to date. All designs are validated using mass-action simulations of the chemical kinetics of DNA strand displacement reactions.

Integration of Enzymes in Polyaniline-Sensitized 3D Inverse Opal TiO2 Architectures for Light-Driven Biocatalysis and Light-to-Current Conversion.

Inspired by natural photosynthesis, coupling of artificial light-sensitive entities with biocatalysts in a biohybrid format can result in advanced photobioelectronic systems. Herein, we report on the integration of sulfonated polyanilines (PMSA1) and PQQ-dependent glucose dehydrogenase (PQQ-GDH) into inverse opal TiO2 (IO-TiO2) electrodes. While PMSA1 introduces sensitivity for visible light into the biohybrid architecture and ensures the efficient wiring between the IO-TiO2 electrode and the biocatalytic entity, PQQ-GDH provides the catalytic activity for the glucose oxidation and therefore feeds the light-driven reaction with electrons for an enhanced light-to-current conversion. Here, the IO-TiO2 electrodes with pores of around 650 nm provide a suitable interface and morphology needed for the stable and functional assembly of polymer and enzyme. The IO-TiO2 electrodes have been prepared by a template approach applying spin coating, allowing an easy scalability of the electrode height and surface area. The successful integration of the polymer and the enzyme is confirmed by the generation of an anodic photocurrent, showing an enhanced magnitude with increasing glucose concentrations. Compared to flat and nanostructured TiO2 electrodes, the three-layered IO-TiO2 electrodes give access to a 24-fold and 29-fold higher glucose-dependent photocurrent due to the higher polymer and enzyme loading in IO films. The three-dimensional IO-TiO2|PMSA1|PQQ-GDH architecture reaches maximum photocurrent densities of 44.7 ± 6.5 µA cm-2 at low potentials in the presence of glucose (for a three TiO2 layer arrangement). The onset potential for the light-driven substrate oxidation is found to be at -0.315 V vs Ag/AgCl (1 M KCl) under illumination with 100 mW cm-2, which is more negative than the redox potential of the enzyme. The results demonstrate the advantageous properties of IO-TiO2|PMSA1|PQQ-GDH biohybrid architectures for the light-driven glucose conversion with improved performance.

Bioelectronic Circuit on a 3D Electrode Architecture: Enzymatic Catalysis Interconnected with Photosystem I.

Artificial light-driven signal chains are particularly important for the development of systems converting light into a current, into chemicals or for light-induced sensing. Here, we report on the construction of an all-protein, light-triggered, catalytic circuit based on photosystem I, cytochrome c (cyt c) and human sulfite oxidase (hSOX). The defined assembly of all components using a modular design results in an artificial biohybrid electrode architecture, combining the photophysical features of PSI with the biocatalytic properties of hSOX for advanced light-controlled bioelectronics. The working principle is based on a competitive switch between electron supply from the electrode or by enzymatic substrate conversion.

Do night and around-the-clock firefighters' shift schedules induce deviation in tau from 24 hours of systolic and diastolic blood pressure circadian rhythms?

Systolic (S) and diastolic (D) blood pressures (BP) [SBP and DBP] are circadian rhythmic with period (τ) in healthy persons assumed to be maintained at 24.0h. We tested this assumption in a sample of 30 healthy career (mean >12 yrs) 30-to-46 yr-old male Caucasian French firefighters (FFs) categorized into three groups according to work schedule and duties: Group A - 12 FFs working 12h day, 12h night, and occasionally 24h shifts and whose primary duties are firefighting plus paramedical and road rescue services; Group B - 9 FFs working mostly 12h day and 12h night shifts and whose duties are answering incoming emergency calls and coordinating service vehicle dispatch from fire stations with Group A personnel; Group C - 9 day shift (09:00-17:00h) FFs charged with administrative tasks. SBP and DBP, both in winter and in summer studies of the same FFs, were sampled by ambulatory BP monitoring every 1h between 06:00-23:00h and every 2h between 23:01-05:59h, respectively, their approximate off-duty wake and sleep spans, for 7 consecutive days. Activity (wrist actigraphy) was also sampled at 1-min intervals. Prominent τ of each variable was derived by a power spectrum program written for unequal-interval time series data, and between-group differences in incidence of τ≠24h of FFs were assessed by chi square test. Circadian rhythm disruption (τ≠24h) of either the SBP or DBP rhythm occurred almost exclusively in night and 24h shift FFs of Group A and B, but almost never in day shift FFs of Group C, and it was not associated with altered τ from 24.0h of the circadian activity rhythm. In summer, occurrence of τ≠24 for FFs of Group A and B differed from that for FFs of Group C in SBP (p=0.042) and DBP (p=0.015); no such differences were found in winter (p>0.10). Overall, manifestation of prominent τ≠24h of SBP or DBP time series was greater in summer than winter, 27.6% versus 16.7%, when workload of Group B FFs, i.e. number of incoming emergency telephone calls, and of Group A FFs, i.e. number of dispatches for provision of emergency services, was, respectively, two and fourfold greater and number of 12h night shifts worked by Group B FFs and number of 24h shifts worked by Group A FFs was, respectively, 92% and 25% greater. FFs of the three groups exhibited no winter-summer difference in τ≠24h of SBP or SDP; however, τ≠24h of DBP in Group B FFs was more frequent in summer than winter (p=0.046). Sleep/wake cycle disruption, sleep deprivation, emotional and physical stress, artificial light-at-night, and altered nutrient timings are hypothesized causes of τ≠24h for BP rhythms of affected Groups A and B FFs, but with unknown future health effects.

Chemical Reaction Networks for Computing Polynomials.

Chemical reaction networks (CRNs) provide a fundamental model in the study of molecular systems. Widely used as formalism for the analysis of chemical and biochemical systems, CRNs have received renewed attention as a model for molecular computation. This paper demonstrates that, with a new encoding, CRNs can compute any set of polynomial functions subject only to the limitation that these functions must map the unit interval to itself. These polynomials can be expressed as linear combinations of Bernstein basis polynomials with positive coefficients less than or equal to 1. In the proposed encoding approach, each variable is represented using two molecular types: a type-0 and a type-1. The value is the ratio of the concentration of type-1 molecules to the sum of the concentrations of type-0 and type-1 molecules. The proposed encoding naturally exploits the expansion of a power-form polynomial into a Bernstein polynomial. Molecular encoders for converting any input in a standard representation to the fractional representation as well as decoders for converting the computed output from the fractional to a standard representation are presented. The method is illustrated first for generic CRNs; then chemical reactions designed for an example are mapped to DNA strand-displacement reactions.

Photo-electrochemical Bioanalysis of Guanosine Monophosphate Using Coupled Enzymatic Reactions at a CdS/ZnS Quantum Dot Electrode.

A photo-electrochemical sensor for the specific detection of guanosine monophosphate (GMP) is demonstrated, based on three enzymes combined in a coupled reaction assay. The first reaction involves the adenosine triphosphate (ATP)-dependent conversion of GMP to guanosine diphosphate (GDP) by guanylate kinase, which warrants substrate specificity. The reaction products ADP and GDPare co-substrates for the enzymatic conversion of phosphoenolpyruvate to pyruvate in a second reaction mediated by pyruvate kinase. Pyruvate in turn is the co-substrate for lactate dehydrogenase that generates lactate via oxidation of nicotinamide adenine dinucleotide (reduced form) NADH to NAD(+). This third enzymatic reaction is electrochemically detected. For this purpose a CdS/ZnS quantum dot (QD) electrode is illuminated and the photocurrent response under fixed potential conditions is evaluated. The sequential enzyme reactions are first evaluated in solution. Subsequently, a sensor for GMP is constructed using polyelectrolytes for enzyme immobilization.