Modeled Pathways and Fluxes of PCB Dechlorination by Redox Potentials.

Dechlorination is one of the main processes for the natural degradation of polychlorinated biphenyls (PCBs) in an anaerobic environment. However, PCB dechlorination pathways and products vary with PCB congeners, types of functional dechlorinating bacteria, and environmental conditions. The present study develops a novel model for determining dechlorination pathways and fluxes by tracking redox potential variability, transforming the complex dechlorination process into a stepwise sequence. The redox potential is calculated via the Gibbs free energy of formation, PCB concentrations in reactants and products, and environmental conditions. Thus, the continuous change in the PCB congener composition can be tracked during dechlorination processes. The new model is assessed against four measurements from several published studies on PCB dechlorination. The simulation errors in all four measurements are calculated between 2.67 and 35.1% under minimum (n = 0) and maximum (n = 34) numbers of co-eluters, respectively. The dechlorination fluxes for para-dechlorination pathways dominate PCB dechlorination in all measurements. Furthermore, the model also considers multiple-step dechlorination pathways containing intermediate PCB congeners absent in both the reactants and the products. The present study indicates that redox potential might be an appropriate indicator for predicting PCB dechlorination pathways and fluxes even without prior knowledge of the functional dechlorinating bacteria.

Treating Semiempirical Hamiltonians as Flexible Machine Learning Models Yields Accurate and Interpretable Results.

Quantum chemistry provides chemists with invaluable information, but the high computational cost limits the size and type of systems that can be studied. Machine learning (ML) has emerged as a means to dramatically lower the cost while maintaining high accuracy. However, ML models often sacrifice interpretability by using components such as the artificial neural networks of deep learning that function as black boxes. These components impart the flexibility needed to learn from large volumes of data but make it difficult to gain insight into the physical or chemical basis for the predictions. Here, we demonstrate that semiempirical quantum chemical (SEQC) models can learn from large volumes of data without sacrificing interpretability. The SEQC model is that of density-functional-based tight binding (DFTB) with fixed atomic orbital energies and interactions that are one-dimensional functions of the interatomic distance. This model is trained to ab initio data in a manner that is analogous to that used to train deep learning models. Using benchmarks that reflect the accuracy of the training data, we show that the resulting model maintains a physically reasonable functional form while achieving an accuracy, relative to coupled cluster energies with a complete basis set extrapolation (CCSD(T)*/CBS), that is comparable to that of density functional theory (DFT). This suggests that trained SEQC models can achieve a low computational cost and high accuracy without sacrificing interpretability. Use of a physically motivated model form also substantially reduces the amount of ab initio data needed to train the model compared to that required for deep learning models.

Design, Synthesis and Aromaticity of an Alternating Cyclo[4]Thiophene[4]Furan.

A new class of conjugated macrocycle, the cyclo[4]thiophene[4]furan hexyl ester (C4TE4FE), is reported. This cycle consists of alternating α-linked thiophene-3-ester and furan-3-ester repeat units, and was prepared in a single step using Suzuki-Miyaura cross-coupling of a 2-(thiophen-2-yl)furan monomer. The ester side groups help promote a syn conformation of the heterocycles, which enables formation of the macrocycle. Cyclic voltammetry studies revealed that C4TE4FE could undergo multiple oxidations, so treatment with SbCl5 resulted in formation of the [C4TE4FE]2+ dication. Computational work, paired with 1 H NMR spectroscopy of the dication, revealed that the cycle becomes globally aromatic upon 2e- oxidation, as the annulene pathway along the outer ring becomes Hückel aromatic. The change in ring current for the cycle upon oxidation was clear from 1 H NMR spectroscopy, as the protons of the thiophene and furan rings shifted downfield by nearly 6 ppm. This work highlights the potential of sequence control in furan-based macrocycles to tune electronic properties.

Testing the feasibility of operationalizing a prospective, randomized trial with remote cardiac safety EKG monitoring during a pandemic.

BACKGROUND: The coronavirus SARS-CoV-2 is highly contagious. Hydroxychloroquine (HCQ) has in vitro activity against SARS-CoV-2. The FDA authorized emergency use of HCQ against COVID-19. HCQ may have dose-related cardiotoxicity. This clinical trial received ethical approval on May 15, 2020, operationalized in June to evaluate a low prophylaxis dose of HCQ (200mg BID) in household contacts of COVID-19-positive patients without physical contact between investigators and participants. It represents the first report of the FDA approved 6-lead EKGs with a smartphone KardiaMobile® 6L application. METHODS: To reach a sample size of 170, household members were contacted by telephone, emailed consent forms with electronic signature capability, and randomized 2:1 to HCQ or observation for 10 days with follow-up of 14 days. Home saliva PCR tests recorded COVID status on days 1 and 14. Symptoms and 6-lead EKGs were obtained daily. RESULTS: Fifty-one participants were randomized with 42 evaluable at day 14. Remote monitoring of 407 EKGs revealed no QTc prolongation or other ECG changes in either group. At time of consent, no participants were symptomatic or COVID+. On days 1 and 14, COVID tests were positive in 4 and 2 in the HCQ group and 4 and 0 in the observation group. No tests converted to positive. There were no deaths or hospitalizations. CONCLUSIONS: A clinical trial without personal contact, rapidly initiated and operationalized to exclude cardiac toxicity using daily remote 6-lead EKG monitoring, is feasible. Of 407 EKGs from 42 participants, there was no evidence of cardiac toxicity. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov : NCT04652648 registration date: December 3, 2020.

The future is now: our experience starting a remote clinical trial during the beginning of the COVID-19 pandemic.

BACKGROUND: The World Health Organization declared the outbreak of SARS-CoV-2 a pandemic on February 11, 2020. This organism causes COVID-19 disease and the rapid rise in cases and geographic spread strained healthcare systems. Clinical research trials were hindered by infection control measures discouraging physical contact and diversion of resources to meet emergent requirements. The need for effective treatment and prevention of COVID-19 prompted an untested investigational response. Trial groups adapted approaches using remote enrolment and consenting, newly developed diagnostic tests, delivery of study medications and devices to participants' homes, and remote monitoring to ensure investigator/enrollee safety while preserving ethical integrity, confidentiality, and data accuracy. METHODS: Clinical researchers at our community health system in the USA undertook an outpatient randomized open-label study of hydroxychloroquine (HCQ) prophylaxis versus observation of SARS-CoV-2 infection in household COVID-19 contacts. Designed in March 2020, challenges included COVID-19 infection in the research group, HCQ shortage, and lack of well-established home SARS-CoV-2 tests and remote ECG monitoring protocols in populations naive to these procedures. The study was written, funded, and received ethical committee approval in 4 months and was completed by September 2020 during a period of fluctuating infection rates and conflicting political opinions on HCQ use; results have been published. Singular methodology included the use of a new RNA PCR saliva SARS-CoV-2 home diagnostic test and a remote smartphone-based 6-lead ECG recording system. RESULTS: Of 483 households contacted regarding trial participation, 209 (43.3%) did not respond to telephone calls/e-mails and 90 (18.6%) declined; others were not eligible by inclusion or exclusion criteria. Ultimately, 54 individuals were enrolled and 42 completed the study. Numbers were too small to determine the efficacy of HCQ prophylaxis. No serious treatment-related adverse events were encountered. CONCLUSIONS: Flexibility in design, a multidisciplinary research team, prompt cooperation among research, funding, ethics review groups, and finding innovative study approaches enabled this work. Concerns were balancing study recruitment against unduly influencing individuals anxious for protection from the pandemic and exclusion of groups based on lack of Internet access and technology. An issue to address going forward is establishing research cooperation across community health systems before emergencies develop. TRIAL REGISTRATION: ClinicalTrials.gov NCT04652648 . Registered on December 3, 2020.

Bacterial and fungal growth in sputum cultures from 165 COVID-19 pneumonia patients requiring intubation: evidence for antimicrobial resistance development and analysis of risk factors.

BACKGROUND: Coronavirus SARS-CoV-2 causes COVID-19 illness which can progress to severe pneumonia. Empiric antibacterials are often employed though frequency of bacterial coinfection superinfection is debated and concerns raised about selection of bacterial antimicrobial resistance. We evaluated sputum bacterial and fungal growth from 165 intubated COVID-19 pneumonia patients. Objectives were to determine frequency of culture positivity, risk factors for and outcomes of positive cultures, and timing of antimicrobial resistance development. METHODS: Retrospective reviews were conducted of COVID-19 pneumonia patients requiring intubation admitted to a 1058-bed four community hospital system on the east coast United States, March 1 to May 1, 2020. Length of stay (LOS) was expressed as mean (standard deviation); 95% confidence interval (95% CI) was computed for overall mortality rate using the exact binomial method, and overall mortality was compared across each level of a potential risk factor using a Chi-Square Test of Independence. All tests were two-sided, and significance level was set to 0.05. RESULTS: Average patient age was 68.7 years and LOS 19.9 days. Eighty-three patients (50.3% of total) originated from home, 10 from group homes (6.1% of total), and 72 from nursing facilities (43.6% of total). Mortality was 62.4%, highest for nursing home residents (80.6%). Findings from 253 sputum cultures overall did not suggest acute bacterial or fungal infection in 73 (45%) of 165 individuals sampled within 24 h of intubation. Cultures ≥ 1 week following intubation did grow potential pathogens in 72 (64.9%) of 111 cases with 70.8% consistent with late pneumonia and 29.2% suggesting colonization. Twelve (10.8% of total) of these late post-intubation cultures revealed worsened antimicrobial resistance predominantly in Pseudomonas, Enterobacter, or Staphylococcus aureus. CONCLUSIONS: In severe COVID-19 pneumonia, a radiographic ground glass interstitial pattern and lack of purulent sputum prior to/around the time of intubation correlated with no culture growth or recovery of normal oral flora ± yeast. Discontinuation of empiric antibacterials should be considered in these patients aided by other clinical findings, history of prior antimicrobials, laboratory testing, and overall clinical course. Continuing longterm hospitalisation and antibiotics are associated with sputum cultures reflective of hospital-acquired microbes and increasing antimicrobial resistance. TRIAL REGISTRATION: Not applicable as this was a retrospective chart review study without interventional arm.

Photostable Helical Polyfurans.

This report describes the design and synthesis of a new class of polyfurans bearing ester side chains. The macromolecules can be synthesized using catalyst-transfer polycondensation, providing precise control over molecular weight and molecular weight distribution. Such obtained furan ester polymers are significantly more photostable than their alkyl analogues owing to the electron-withdrawing nature of the attached subunit. Most interestingly, they spontaneously fold into a compact π-stacked helix, yielding a complex multilayer cylindrical nanoparticle with a hollow, rigid, conjugated core composed of the polyfuran backbone and a soft, insulating outer layer formed by the ester side chains. The length of polymer side chains dictates the outer diameter of such nanoparticles, which for the hexyl ester groups used in the present study is equal to ∼2.3 nm. The inner cavity of the conjugated core is lined with oxygen atoms, which set its effective diameter to 0.4 nm. Furthermore, installation of bulkier, branched chiral ester side chains on the repeat unit yields structures that, upon change of solvent, can reversibly transition between an ordered chiral helical folded and disordered unfolded state.

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians.

Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an integral part of the prediction process. This is done by implementing self-consistent-charge Density-Functional-Tight-Binding (DFTB) theory as a layer for use in deep learning models. The DFTB layer takes, as input, Hamiltonian matrix elements generated from earlier layers and produces, as output, electronic properties from self-consistent field solutions of the corresponding DFTB Hamiltonian. Backpropagation enables efficient training of the model to target electronic properties. Two types of input to the DFTB layer are explored, splines and feed-forward neural networks. Because overfitting can cause models trained on smaller molecules to perform poorly on larger molecules, regularizations are applied that penalize nonmonotonic behavior and deviation of the Hamiltonian matrix elements from those of the published DFTB model used to initialize the model. The approach is evaluated on 15 700 hydrocarbons by comparing the root-mean-square error in energy and dipole moment, on test molecules with eight heavy atoms, to the error from the initial DFTB model. When trained on molecules with up to seven heavy atoms, the spline model reduces the test error in energy by 60% and in dipole moments by 42%. The neural network model performs somewhat better, with error reductions of 67% and 59%, respectively. Training on molecules with up to four heavy atoms reduces performance, with both the spline and neural net models reducing the test error in energy by about 53% and in dipole by about 25%.

Constant size descriptors for accurate machine learning models of molecular properties.

Two different classes of molecular representations for use in machine learning of thermodynamic and electronic properties are studied. The representations are evaluated by monitoring the performance of linear and kernel ridge regression models on well-studied data sets of small organic molecules. One class of representations studied here counts the occurrence of bonding patterns in the molecule. These require only the connectivity of atoms in the molecule as may be obtained from a line diagram or a SMILES string. The second class utilizes the three-dimensional structure of the molecule. These include the Coulomb matrix and Bag of Bonds, which list the inter-atomic distances present in the molecule, and Encoded Bonds, which encode such lists into a feature vector whose length is independent of molecular size. Encoded Bonds' features introduced here have the advantage of leading to models that may be trained on smaller molecules and then used successfully on larger molecules. A wide range of feature sets are constructed by selecting, at each rank, either a graph or geometry-based feature. Here, rank refers to the number of atoms involved in the feature, e.g., atom counts are rank 1, while Encoded Bonds are rank 2. For atomization energies in the QM7 data set, the best graph-based feature set gives a mean absolute error of 3.4 kcal/mol. Inclusion of 3D geometry substantially enhances the performance, with Encoded Bonds giving 2.4 kcal/mol, when used alone, and 1.19 kcal/mol, when combined with graph features.

A Least-Squares Commutator in the Iterative Subspace Method for Accelerating Self-Consistent Field Convergence.

A least-squares commutator in the iterative subspace (LCIIS) approach is explored for accelerating self-consistent field (SCF) calculations. LCIIS is similar to direct inversion of the iterative subspace (DIIS) methods in that the next iterate of the density matrix is obtained as a linear combination of past iterates. However, whereas DIIS methods find the linear combination by minimizing a sum of error vectors, LCIIS minimizes the Frobenius norm of the commutator between the density matrix and the Fock matrix. This minimization leads to a quartic problem that can be solved iteratively through a constrained Newton's method. The relationship between LCIIS and DIIS is discussed. Numerical experiments suggest that LCIIS leads to faster convergence than other SCF convergence accelerating methods in a statistically significant sense, and in a number of cases LCIIS leads to stable SCF solutions that are not found by other methods. The computational cost involved in solving the quartic minimization problem is small compared to the typical cost of SCF iterations and the approach is easily integrated into existing codes. LCIIS can therefore serve as a powerful addition to SCF convergence accelerating methods in computational quantum chemistry packages.

In-Situ Platinum Deposition on Nitrogen-Doped Carbon Films as a Source of Catalytic Activity in a Hydrogen Evolution Reaction.

Copolymer-templated nitrogen-doped carbon (CTNC) films deposited on glassy carbon were used as electrodes to study electrochemically driven hydrogen evolution reaction (HER) in 0.5 M H2SO4. The activity of these materials was extremely enhanced when a platinum counter electrode was used instead of a graphite rod and reached the level of commercial Pt/C electrodes. Postreaction scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) measurements of electrode surfaces revealed that incorporation of even extremely low amounts of Pt resulted in this considerable gain of HER activity. High resolution XPS analysis and density functional theory (DFT) calculations confirmed that pyridinic nitrogen atoms act as active sites for Pt coordination and deposition. The Pt can be incorporated in both molecular (Pt(2+)) and metallic (Pt(0)) form. This study shows that great caution must be taken when designing "metal-free" HER catalysts based on N-doped carbons.

Conjugated Polymers with Repeated Sequences of Group 16 Heterocycles Synthesized through Catalyst-Transfer Polycondensation.

Periodic π-conjugated polymers of the group 16 heterocycles (furan, thiophene, and selenophene) were synthesized with controlled chain lengths and relatively low dispersities using catalyst-transfer polycondensation. The optical gap and redox potentials of these copolymers were fine-tuned by altering the heterocycle sequence, and atomic force microscopy revealed nanofibrillar morphologies for all the materials. Grazing incidence wide-angle X-ray scattering of the thiophene-selenophene copolymers indicated that the π-stacking distance increased with incorporation of the larger heteroatom (from ∼3.7-4.0 Å), while the lamellar spacing decreased (from ∼15.8-15.2 Å). The study also revealed that periodic sequences allow electronic properties to be tuned while retaining nanofibrillar morphologies similar to those observed for poly(3-hexylthiophene).

Spectral fine tuning of cyanine dyes: electron donor-acceptor substituted analogues of thiazole orange.

The introduction of electron donor and acceptor groups at strategic locations on a fluorogenic cyanine dye allows fine-tuning of the absorption and emission spectra while preserving the ability of the dye to bind to biomolecular hosts such as double-stranded DNA and a single-chain antibody fragment originally selected for binding to the parent unsubstituted dye, thiazole orange (TO). The observed spectral shifts are consistent with calculated HOMO-LUMO energy gaps and reflect electron density localization on the quinoline half of TO in the LUMO. A dye bearing donating methoxy and withdrawing trifluoromethyl groups on the benzothiazole and quinoline rings, respectively, shifts the absorption spectrum to sufficiently longer wavelengths to allow excitation at green wavelengths as opposed to the parent dye, which is optimally excited in the blue.

Modeling Field-Induced Quenching in Poly(p-phenylene vinylene) Polymers and Oligomers.

Field-induced fluorescence quenching of poly(p-phenylene vinylene) (PPV) oligomers due to nonradiative relaxation through free electron-hole pair (FEHP) states is modeled using singles configuration interaction computations with the intermediate neglect of differential overlap Hamiltonian. The computations find FEHP states with energies that drop linearly with applied field and undergo avoided crossings with the fluorescent state. The coupling between the FEHP and fluorescent state, computed for multiple FEHP states on a variety of oligomer lengths, is found to depend primarily on the field strength required for the state to cross the fluorescent state. The rate of decay to these dark FEHP states is then calculated from Marcus theory, which is modified to take into account dielectric in addition to other bulk measurement considerations. The results predict that individual molecules go from being emissive to fully quenched over a small range of applied field strengths. Phenomenological introduction of inhomogeneous broadening for the energies of the FEHP states leads to a more gradual dependence on applied field. The fluorescence quenching mechanism considered here is found to be important for applied fields above about 1 MV cm(-1), which is similar in magnitude to those present in light-emitting diodes.

Computational and experimental characterization of a fluorescent dye for detection of potassium ion concentration.

The fluorescence of the SKC-513 ((E)-N-(9-(4-(1,4,7,10,13-pentaoxa-16-azacyclooctadecan-16-yl)phenyl)-6-(butyl(3-sulfopropyl)amino)-3H-xanthen-3-ylidene)-N-(3-sulfopropyl)butan-1-aminium) dye is shown experimentally to have high sensitivity to binding of the K(+) ion. Computations are used to explore the potential origins of this sensitivity and to make some suggestions regarding structural improvements. In the absence of K(+), excitation is to two nearly degenerate states, a neutral (N) excited state with a high oscillator strength, and a charge-transfer (CT) state with a lower oscillator strength. Binding of K(+) destabilizes the CT state, raising its energy far above the N state. The increase in fluorescence quantum yield upon binding of K(+) is attributed to the increased energy of the CT state suppressing a nonradiative pathway mediated by the CT state. The near degeneracy of the N and CT excited states can be understood by considering SKC-513 as a reduced symmetry version of a parent molecule with 3-fold symmetry. Computations show that acceptor-donor substituents can be used to alter the relative energies of the N and CT state, whereas a methylene spacer between the heterocycle and phenylene groups can be used to increase the coupling between these states. These modifications provide synthetic handles with which to optimize the dye for K(+) detection.

Tuning thiophene with phosphorus: synthesis and electronic properties of benzobisthiaphospholes.

1,4-Dimercapto-2,5-diphosphinobenzene and 3,6-bis(hexyloxy)-1,4-dimercapto-2,5-diphosphinobenzene were synthesized and combined with various acid chlorides to obtain a series of benzobisthiaphospholes. Electrochemical and photophysical properties of the substituted benzobisthiaphospholes have been evaluated, and the observed reductions are more facile than the related benzothiaphospholes and 2,6-diphenylbenzobisthiazole. A benzobisthiaphosphole with C6H4-p-CN substituents was reduced at E(1/2)=-1.08 V (vs. saturated calomel electrode (SCE)). X-ray diffraction data for several of these phosphorus heterocycles has been obtained, and DFT calculations at the B3LYP level have been performed.

Brownian dynamics simulations of charge mobility on conjugated polymers in solution.

A model is developed for the mobility of a charge carrier along a conjugated polymer dissolved in solution, as measured by time-resolved microwave conductivity. Each unit cell of the polymer is assigned a torsional degree of freedom, with Brownian dynamics used to include the effects of solvent on the torsions. The barrier to torsional motion is substantially enhanced in the vicinity of the charge, leading to self-trapping of the charge onto a planarized region of the polymer chain. Within the adiabatic approximation used here, motion arises when regions of the polymer on either side of the charge fluctuate into planarity and the wavefunction spreads in the corresponding direction. Well-converged estimates for the mobility are obtained for model parameters where the adiabatic approximation holds. For the parameters expected for conjugated polymers, where crossing between electronic surfaces may lead to breakdown in the adiabatic approximation, estimates for the mobility are obtained via extrapolation. Nonadiabatic contributions from hopping between electronic surfaces are therefore ignored. The resulting mobility is inversely proportional to the rotational diffusion time, trot, of a single unit cell about the polymer axis in the absence of intramolecular forces. For trot of 75 ps, the long-chain mobility of poly(para-phenylene vinylene) is estimated to be between 0.09 and 0.4 cm(2)∕Vs. This is in reasonable agreement with experimental values for the polymer, however, the nonadiabatic contribution to the mobility is not considered, nor are effects arising from stretching degrees of freedom or breaks in conjugation.

Second-order dispersion interactions in π-conjugated polymers.

We calculate the ground state and excited state second-order dispersion interactions between parallel π-conjugated polymers. The unperturbed eigenstates and energies are calculated from the Pariser-Parr-Pople model using CI-singles theory. Based on large-scale calculations using the molecular structure of trans-polyacetylene as a model system and by exploiting dimensional analysis, we find that: (1) For inter-chain separations, R, greater than a few lattice spacings, the ground-state dispersion interaction, ΔE(GS), satisfies, ΔE(GS)∼L(2)/R(6) for L ≪ R and ΔE(GS)∼L/R(5) for R ≪ L, where L is the chain length. The former is the London fluctuating dipole-dipole interaction while the latter is a fluctuating line dipole-line dipole interaction. (2) The excited state screening interaction exhibits a crossover from fluctuating monopole-line dipole interactions to either fluctuating dipole-dipole or fluctuating line dipole-line dipole interactions when R exceeds a threshold R(c), where R(c) is related to the root-mean-square separation of the electron-hole excitation. Specifically, the excited state screening interaction, ΔE(n), satisfies, ΔE(n) ∼ L∕R(6) for R(c) < L ≪ R and ΔE(n) ∼ L(0)∕R(5) for R(c) < R ≪ L. For R < R(c) < L, ΔE(n) ∼ R(-ν), where ν ≃ 3. We also investigate the relative screening of the primary excited states in conjugated polymers, namely the n = 1, 2, and 3 excitons. We find that a larger value of n corresponds to a larger value of ΔE(n). For example, for poly(para-phenylene), ΔE(n = 1) ≃ 0.1 eV, ΔE(n = 2) ≃ 0.6 eV, and ΔE(n = 3) ≃ 1.2 eV (where n = 1 is the 1(1)B(1) state, n = 2 is the m(1)A state, and n = 3 is the n(1)B(1) state). Finally, we find that the strong dependence of ΔE(n) on inter-chain separation implies a strong dependency of ΔE(n) on density fluctuations. In particular, a 10% density fluctuation implies a fluctuation of 13 meV, 66 meV, and 120 meV for the 1(1)B(1), m(1)A state, and n(1)B(1) states of poly(para-phenylene), respectively. Our results for the ground-state dispersion are applicable to all types of conjugated polymers. However, our excited state results are only applicable to conjugated polymers, such as the phenyl-based class of light emitting polymers, in which the primary excitations are particle-hole (or ionic) states.

Substituent effects on the assembly of helical cyanine dye aggregates in the minor groove of a DNA template.

Double-helical DNA was used as a template for the assembly of helical cyanine dye aggregates. The aggregates consist of cofacial dimers aligned end-to-end in the minor groove of the DNA. The effect of methoxy or fluoro substituents placed on the periphery of the cyanine dye heterocycles on aggregation both in water and on the DNA template was studied by UV-vis and circular dichroism spectroscopy. Methoxy groups were found to be stronger promoters of aggregation than fluoro, and a dimethoxy dye exhibited a higher propensity to aggregate compared with an unsymmetrical methoxy/fluoro dye. Semiempirical calculations supported the experimental observation of methoxy substitution favoring aggregation. These results indicate that dispersion and hydrophobic effects contribute more to dimerization/aggregation than do electron donor-acceptor effects.