Energy dependence on fractional charge for strongly interacting subsystems

The energies of a pair of strongly-interacting subsystems with arbitrary noninteger charges are examined from closed and open system perspectives. An ensemble representation of the charge dependence is derived, valid at all interaction strengths. Transforming from resonance-state ionicity to ensemble charge dependence imposes physical constraints on the occupation numbers in the strong-interaction limit. For open systems, the chemical potential is evaluated using microscopic and thermodynamic models, leading to a novel correlation between ground-state charge and an electronic temperature.Comment: 4 pages, 3 figs.; as accepted (Phys. Rev. Lett.

An Empirical Charge Transfer Potential with Correct Dissociation Limits

The empirical valence bond (EVB) method [J. Chem. Phys. 52, 1262 (1970)] has always embodied charge transfer processes. The mechanism of that behavior is examined here and recast for use as a new empirical potential energy surface for large-scale simulations. A two-state model is explored. The main features of the model are: (1) Explicit decomposition of the total system electron density is invoked; (2) The charge is defined through the density decomposition into constituent contributions; (3) The charge transfer behavior is controlled through the resonance energy matrix elements which cannot be ignored; and (4) A reference-state approach, similar in spirit to the EVB method, is used to define the resonance state energy contributions in terms of "knowable" quantities. With equal validity, the new potential energy can be expressed as a nonthermal ensemble average with a nonlinear but analytical charge dependence in the occupation number. Dissociation to neutral species for a gas-phase process is preserved. A variant of constrained search density functional theory is advocated as the preferred way to define an energy for a given charge.Comment: Submitted to J. Chem. Phys. 11/12/03. 14 pages, 8 figure

Defining genetic intra-tumor heterogeneity: a chronological annotation of mutational pathways

Tumor heterogeneity is believed to be important in tumor progression and its response to therapies. However, despite numerous mutations being reported in human tumors, genetic intra-tumor heterogeneity remains poorly defined. We have developed a novel strategy to provide a chronological annotation of mutational events in a tumor. We used an endometrial tumor from a patient and transplanted it into athymic mice to create many tumor xenografts. While the patient tumor xenografts were initially responsive to raloxifene treatment, xenografts created with cancer cell clones isolated from the same patient tumor showed dramatic differences in response to raloxifene, indicating existence of intra-tumor heterogeneity with some subpopulations inherently resistant to the drug. A 250K single nucleotide polymorphism (SNP) array from Affymetrix was used to profile genotype changes on 3 xenografts and 10 single cells from another 10 xenografts. We found 797 SNP sites containing loss of heterozygosity (LOH) common to all these specimens, indicating that genetic mutations in these regions may contain the earliest genetic events in the original patient tumor. Based upon the genotype information from the 10 single cancer cells, we developed a phylogenetic tree using neighbor-joining method. We showed that there are at least 3 distinct subpopulations in the patient tumor. Additionally, the phylogenetic tree was used to determine the order of genetic events, thus providing a chronological annotation to genetic mutations. Our approach represents an important analytic strategy for defining genetic intra-tumor heterogeneity and providing chronological annotations to the genetic landscape revealed by future whole genome sequencing in tumors

Atomic Resonance and Scattering

Contains reports on eight research projects.National Science Foundation (Grant PHY79-09743)National Bureau of Standards (Grant NB-8-NAHA-3017)Joint Services Electronics Program (Contract DAAG29-80-C-0104)National Science Foundation (Grant PHY82-10486)U.S. Navy - Office of Naval Research (Contract N00014-79-C-0183)National Science Foundation (Grant CHE79-02967-A04)U.S. Air Force - Office of Scientific Research (Contract AFOSR-81-0067)Joint Services Electronics Program (Contract DAAG29-83-K-0003

Building a community to engineer synthetic cells and organelles from the bottom-up

Employing concepts from physics, chemistry and bioengineering, 'learning-by-building' approaches are becoming increasingly popular in the life sciences, especially with researchers who are attempting to engineer cellular life from scratch. The SynCell2020/21 conference brought together researchers from different disciplines to highlight progress in this field, including areas where synthetic cells are having socioeconomic and technological impact. Conference participants also identified the challenges involved in designing, manipulating and creating synthetic cells with hierarchical organization and function. A key conclusion is the need to build an international and interdisciplinary research community through enhanced communication, resource-sharing, and educational initiatives

Atomic Resonance and Scattering

Contains reports on nine research projects.National Science Foundation (Grant PHY79-09743)National Science Foundation (Grant PHY82-10486)Joint Services Electronics Program (Contract DAAG29-83-K-0003)U.S. Navy - Office of Naval Research (Contract N00014-79-C-0183)National Bureau of Standards (Grant NB83-NAHA-4058)National Science Foundation (Grant CHE79-02967-A04)National Science Foundation (Grant PHY83-07172)Joint Services Electronics Program (Grant DAAG29-83-K-0003

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab

Purpose: We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients. Patients and Methods: TCGA microRNA expression data from tumors resected at first diagnosis of glioblastoma in patients treated with bevacizumab at any time during the course of their disease were randomly separated into training (n=50) and test (n=37) groups for model generation. MicroRNA-seq data for 51 patients whose treatment included bevacizumab in the BELOB trial were used as an independent validation cohort. Results: Using penalized regression we identified 8 microRNAs as potential predictors of overall survival in the training set. We dichotomized the response score based on the most prognostic minimum of a density plot of the response scores (log-rank HR=0.16, p=1.2e-5) and validated the profile in the test cohort (one-sided log-rank HR=0.34, p=0.026). Analysis of the profile using all samples in the TCGA glioblastoma dataset, regardless of treatment received, (n=473) showed that the prediction of patient benefit was not significant (HR=0.84, p=0.083) suggesting the profile is specific to bevacizumab. Further independent validation of our microRNA profile in RNA-seq data from patients treated with bevacizumab (alone or in combination with CCNU) at glioblastoma recurrence in the BELOB trial confirmed that our microRNA profile predicted patient benefit from bevacizumab (HR=0.59, p=0.043). Conclusion: We have identified and validated an 8-microRNA profile that predicts overall survival in patients with glioblastoma treated with bevacizumab. This may be useful for identifying patients who are likely to benefit from this agent

Simultaneous detection of lung fusions using a multiplex RT-PCR next generation sequencing-based approach:A multi-institutional research study

Contains fulltext : 195300.pdf (publisher's version ) (Open Access