Experimental and Theoretical Study on the One- and Two-Photon Absorption Properties of Novel Organic Molecules Based on Phenylacetylene and Azoaromatic Moieties

This Article reports a combined experimental and theoretical analysis on the one and two-photon absorption properties of a novel class of organic molecules with a pi-conjugated backbone based on phenylacetylene (JCM874, FD43, and FD48) and azoaromatic (YB3p2S) moieties. Linear optical properties show that the phenylacetylene-based compounds exhibit strong molar absorptivity in the UV and high fluorescence quantum yield with lifetimes of approximately 2.0 ns, while the azoaromatic-compound has a strong absorption in the visible region with very low fluorescence quantum yield. The two-photon absorption was investigated employing nonlinear optical techniques and quantum chemical calculations based on the response functions formalism within the density functional theory framework. The experimental data revealed well-defined 2PA spectra with reasonable cross-section values in the visible and IR. Along the nonlinear spectra we observed two 2PA allowed bands, as well as the resonance enhancement effect due to the presence of one intermediate one-photon allowed state. Quantum chemical calculations revealed that the 2PA allowed bands correspond to transitions to states that are also one-photon allowed, indicating the relaxation of the electric-dipole selection rules. Moreover, using the theoretical results, we were able to interpret the experimental trends of the 2PA spectra. Finally, using a few-energy-level diagram, within the sum-over-essential states approach, we observed strong qualitative and quantitative correlation between experimental and theoretical results.

The Role of Molecular Conformation and Polarizable Embedding for One- and Two-Photon Absorption of Disperse Orange 3 in Solution

Solvent effects on the one- and two-photon absorption (IPA and 2PA) of disperse orange 3 (DO3) in dimethyl sulfoxide (DMSO) are studied using a discrete polarizable embedding (PE) response theory. The scheme comprises a quantum region containing the chromophore and an atomically granulated classical region for the solvent accounting for full interactions within and between the two regions. Either classical molecular dynamics (MD) or hybrid Car-Parrinello (CP) quantum/classical (QM/MM) molecular dynamics simulations are employed to describe the solvation of DO3 in DMSO, allowing for an analysis of the effect of the intermolecular short-range repulsion, long-range attraction, and electrostatic interactions on the conformational changes of the chromophore and also the effect of the solute-solvent polarization. PE linear response calculations are performed to verify the character, solvatochromic shift, and overlap of the two lowest energy transitions responsible for the linear absorption spectrum of DO3 in DMSO in the visible spectral region. Results of the PE linear and quadratic response calculations, performed using uncorrelated solute-solvent configurations sampled from either the classical or hybrid CP QM/MM MD simulations, are used to estimate the width of the line shape function of the two electronic lowest energy excited states, which allow a prediction of the 2PA cross-sections without the use of empirical parameters. Appropriate exchange-correlation functionals have been employed in order to describe the charge-transfer process following the electronic transitions of the chromophore in solution.

P-Technique Factor Analyses of the Multiple Affect Adjective Checklist (MAACL)

The Multiple Affect Adjective Check List (MAACL) has been found to have five first-order factors representing Anxiety, Depression, Hostility, Positive Affect, and Sensation Seeking and two second-order factors representing Positive Affect and Sensation Seeking (PASS) and Dysphoria. The present study examines whether these first- and second-order conceptions of affect (based on R-technique factor analysis) can also account for patterns of intraindividual variability in affect (based on P-technique factor analysis) in eight elderly women. Although the hypothesized five-factor model of affect was not testable in all of the present P-technique datasets, the results were consistent with this interindividual model of affect. Moreover, evidence of second-order (PASS and Dysphoria) and third-order (generalized distress) factors was found in one data set. Sufficient convergence in findings between the present P-technique research and prior R-technique research suggests that the MAACL is robust in describing both inter- and intraindividual components of affect in elderly women.

THE MULTIPLE LOCATION TIME WEIGHTED INDEX: USING PATIENT ACTIVITY SPACES TO CALCULATE PRIMARY CARE SERVICE AREAS

Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

Unravelling the multiple roles of FUS in RNA processing and on ALS pathogenesis

Two genes with related functions in RNA biogenesis were recently reported in patients with familial ALS: the FUS/TLS gene at the ALS6 locus and the TARDBP/TDP-43 gene at the ALS10 locus [1, 2]. FUS has been implicated to function in several steps of gene expression, including transcription regulation [3], RNA splicing [4, 5], mRNA transport in neurons [6] and, interestingly, in microRNA (miRNA) processing [7]. The goal of this project is to identify the molecular mechanisms leading to the development of FUS mutations-associated ALS. Specifically, we want to test the hypothesis that these FUS mutations misregulate miRNA levels that in turn affect the expression of genes critical for motor neuron survival. In addition we want to test whether misregulation of the miRNA profile is a common feature in ALS. We have performed immunoprecipitations from total extracts of 293T cells expressing FLAG-tagged FUS to characterize its interactome by mass spectrometry. This proteomic study not only revealed a strong interaction of FUS with splicing factors, but shows that FUS might be involved in many, quite different pathways. To map which parts of the FUS protein contribute to the interaction with splicing factors, we have performed a set of experiments with a series of missense and deletion mutants. With this approach, we will not only gain information on the binding partners of FUS along with a map of the required domains for the interactions, but it will also help to unravel whether certain ALS-associated FUS mutations lead to a loss or gain of function due to gain or loss of interactors. Additionally, we have performed quantitative interactomics using SILAC to identify interactome differences of ALS-associated FUS mutants. To this end we have performed immunoprecipitations of total extract from 293T cells, stably transduced with constructs expressing wild-type FUS-FLAG as well as three different ALS-associated mutants (G156E, R244C, P525L). First results indicate striking differences in the interactome with certain RNA binding proteins. We are now validating these candidates in order to reveal the importance of these differential interactions in the context of ALS.

After-effects and after-effects and after-effects of after-effects: The multiple side effects of prospective memory

In a prospective memory task responding to a prospective memory target involves switching between ongoing and prospective memory task which can result in a slowing of subsequent ongoing task performance (i.e., an after-effect). Moreover, a slowing can also occur when prospective memory targets occur after the prospective memory task is deactivated (i.e., another after-effect). In this study, we investigated both after-effects within the same study. Moreover, we also tested whether the latter after-effects even occur on subsequent ongoing task trials. The results show, in fact, after-effects of all kinds. Thus, (1) correctly responding to prospective memory targets results in after-effects, a so far neglected cost on ongoing task performance, (2) responding to deactivated prospective memory targets also slows down performance, probably due to the involuntary retrieval of the intention, and (3) this slowing is present even on subsequent ongoing task trials, suggesting that even deactivated intentions are sufficient to induce a conflict that requires subsequent adaptation. Overall, these results indicate that performance slowing in a prospective memory experiment includes various kinds of sources, not only monitoring cost, and these sources may be understood best in terms of conflict adaptation.

The multiple location time weighted index: Using patient activity spaces to calculate primary care service areas

Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. ^ During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. ^ Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering "free or low cost visits", meeting "all of the patient's health care needs", and seeing "the patient quickly" were all ranked higher than geographic reasons. ^ Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts. ^