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Density functional theory (DFT) allows for the treatment of relatively large systems at a relatively low computational cost. Unfortunately, while optical gaps are usually well-predicted by time-dependent DFT (TDDFT) with standard exchange-correlation functionals, the highest-occupied molecular orbital (HOMO) and the lowest-unoccupied molecular orbital (LUMO) are poor predictors of the ionization potential (IP) and the electron affinity (EA), respectively. Range-separated hybrid (RSH) functionals are a relatively new class of functionals that are based on treating exact exchange in the long-range and (semi-)local exchange in the short-range. It was recently suggested that excellent fundamental gap values of finite-size objects may be obtained directly from the HOMO and LUMO eigenvalues, if the range separation parameter is optimally tuned so as to obey the DFT version of Koopmans' theorem, for each system separately.
In this work we have examined a set of organic molecules of photovoltaic interest. We showed that with the optimally-tuned RSH approach it is indeed possible to obtain results for the IP and the fundamental gap that are as accurate as those obtained from many-body perturbation theory (within the GW approximation). We further showed that by using the same approach within TDDFT we obtain optical gaps that are at the same level of accuracy as other TDDFT methods. This provides a consistent framework for first-principles prediction of fundamental and optical gaps of gas-phase molecules at a modest computational cost.

At the center of epidemiology, public health and genetics lies the question of nature or nurture. The rise in frequency, morbidity and mortality of certain chronic conditions, such as diabetes and cancer, certainly suggests nurture contributes to disease risk. On the other hand, germline variation, linked to breast cancer risk has been extensively investigated. However, clinical implementation of either genotyping for allelic variations or lifestyle decisions, such as hormone replacement, parity, anti-estrogens, or anti-inflammatory compounds, are all attenuated by the lack of evidence based approach to integrate the nature (genetic) and nurture (life style and experience). Epigenetic packaging of the DNA into chromatin in different cells in different conditions is a key mechanism to control the repertoire of phenotypes exhibited by differentiated cells and offers a key molecular mechanism to track the impact lifestyle on genome-to-phenotype flow. This study focused on the epigenetic changes that occur in the normal precursors of breast cancer in a series of normal human breasts (obtained from reduction mammoplasty), from women who either had multiple child births, or none. We observe molecular pathways that operate during the course of pregnancy-birth-lactation-involution, which likely mediate the observed reduction in breast cancer risk. We are now testing compounds, which modulate these pathways, to reduce breast cancer risk as a chemopreventive supplement to contraceptive pills, by mimicking the experience of childbirth in nullyparous women. The test is performed on human breast implants growing in mice, and the readout is change in mammographic density, a surrogate marker to premalignant risk elevation in normal breast.

They are out there, they are detectable and they are crucial
theoretically. Detection of highly eccentric (e>~ 0.99) extra-solar
gas-giants with periastron of a few stellar radii may answer the
question of how hot Jupiters get so close to their host star. Detection
of early high energy emission (soft X-ray to gamma-rays) at the onset of
Supernovae will allow us to measure key properties of the exploding
star, including its pre-explosion radius and the blast wave velocity.